* Larger groups - inquire with VBH as to availability.
* Off season / Season advance time for making reservation: 30 / 45 days.
* Seasonal group pricing may vary from regular pricing; inquire with VBH.
* Separate rooms: all beds in rooms to be paid for as group reservation.
* Reservation payment at time of Reservation: modifies Reservation Service form, above. Non-refundable.
* All group reservations subject to direct confirmation from VBH. No real-time on-line availability.
* Season: if other guests or reservations need to be moved or cancelled as result of group reservation, costs associated with this are added charges to group reservation. e.g., in busy times, it may be necessary to block out or move out/not renew guests prior day(s) to enable availability and room allocation. Such block out/move out/non-renewal will be charged as surcharge at check-in.
* SHARED ROOMS: 6 - 12 (BUNKS) & roll-away & EN-SUITE & FREE INTERNET.
* Minors - in own rooms only; chaperoned only.
If separate room(s) required; then applicable private rates used.
Relax in your Room with - INTERNET & WI-FI.
SHARED ROOMS -- WHAT YOU WANT – IS WHAT YOU GET – in VBH!
BEDS have: * shelf for personal items; * light for reading; * outlet to charge phones/computers; * curtain for privacy; * linen. ROOMS have:* Private Bathroom; * phone lockers for overnight; * 10ft /3m high ceilings; * curtain between bunks; * carpeting; * ceiling fan & heater; * closet & lockers. BATHROOMS have: * tub / shower; * granite tops & vessel sinks or pedestal sinks; * granite shelves; * tile or plank floor.
* we beat the price/cost of any other hostel in area if you use the internet & eat!
Enjoy Venice Beach Hostel life & Enjoy the best value on the Beach!
Venice Beach Hostel has a Creative Community Program : contribute your creativity : Everyone Can Win !
All Rooms - private & shared - are small apartments; with their own bathrooms!!
All Rooms Have included in room Internet Access (Ethernet) - and included building commons Computers & Wireless Access (Wi FI)!!
2 Common Recreation Rooms: Internet, Piano, Wii; Lockers, TV, Pool Table.
Commons Has included COMPUTERS & Internet WI-FI Access!!
Guest Laundry Room - available for guests all day & evening long !!
Lockers Available; Safety Box Available In Office.
Large Kitchen - Good Cooking & Dining Area.
BREAKFAST – an egg or fruit (occasional / seasonal), all you can eat Pancakes & Waffles & cereal; home fry potatoes (certain days); or bread. margarine, jam; Coffee & Tea.
$3 Spaghetti pot or Chili pot (only some nights) - Pasta & pasta sauce or Veggie Chili & Rice or Fried Rice or (if cold) Soups (some nights).
Potatoes,Onions, Oil, tortillas; & Spices, Condiments, etc.
You cook for yourself with our food and save over eating out on meal program!
(2) Due at check-in: balance of price; tax, refundable security deposit; card use charge is extra.
(3) PLEASE NOTE: (a) If you have already contacted hostel directly and we have sent a Reservation Form - you must reserve through hostel and not an outside Reservation Service, such as here. The outside Reservation Service charges us a 15% commission - your "deposit" - to them. Such reservation and/or - deposit - commission is not honored if you had previously contacted hostel and we have sent you our info or sent a reservation info form.
(b) Renewals of guests in hostel may only be done in hostel; not through outside reservation services.
(4) Holiday Periods (incl. its weekend): added charge in hostel per night. Shared - $3 and Private - $6; added person/private - $3.
(5) Prices calculated on per person basis. Amounts due for pricing / charges rounded up to next dollar.
(1a) IN SEASON CANCELLATION IS 7 DAYS (NOT 3 days) PRIOR TO THE ARRIVAL DATE (March - October).
(1b) NO PARTIAL CANCELLATION of reservation dates / reservation at check-in or in VBH; no cancellation of holidays or holiday weekends dates.
(1c) OFF SEASON CANCELLATION is 72 hours (3 days) prior to the arrival date (Nov. - Feb.).
(1d) Cancellation only by email or other writing.
Venice Beach Hostel Rules and Regulations (R&R'S) apply.
(1a) In Season Cancellation is 7 days (3 days) prior to the arrival date. No partial cancellation of reservation dates; NO PARTIAL CANCELLATION of reservation at check-in or in VBH; no cancellation of holidays or holiday weekends dates. Off Season Cancellation is 72 hours (3 days) prior to the arrival date.
(1b) Cancellation only by email or other writing.
(2) Reservations may be required to be fully paid in advance when reserving: (a) with credit card expiring before date; (b) more that 1 private room; (c) 4 or more beds; (d) 1 week or longer; (e) less than VBH cancellation period; (f) in season; (g) third party credit card provided; (h) more than three months in advance. Credit card provided will be used. Refundable deposit will be due at check-in.
(3) Debit Card Reservations are to be fully paid upon receipt of reservation and in advance.
(4) Children are welcome. Children may only be in private rooms and with parent or authorized adult.
(5) Proper & valid picture ID required. International travelers: passport; U.S. Travelers: driver's license. Locals only in private rooms. VBH reserves the right to refuse service.
(6) Special rules/limits apply for locals and non-travelers in shared rooms: contact hostel and read R & R's before reserving for shared. This reservation service is only for foreign & out-of state travelers who are continuing travels. All others must contact VBH directly to confirm reservation and verify that they are non-locals & travelers.
(7) No Drug Use Policy. No drugs allowed in VBH; no drug use in or about VBH. Immediate removal and no refunds if this is violated.
(8) We have a 14 night maximum stay. Any guest booking for longer than 14 nights will have their bookings cancelled.
* Special Note Re Our Internet,etc.: It Is an extra Service; We are small, no IT staff & we are not techies - so if it goes down; or machines break do not expect that it will be instantly fixed - or that we can do anything about it during your stay. There are no refunds There is extra WI-FI in Commons and halls.
- And To Really Enjoy -- Please Reserve & enjoy Venice Beach and Venice Beach Hostel!
10 % OFF SHARED SPECIAL - or – FREE NIGHT SHARED SPECIAL off season – mid-OCTOBER & NOVEMBER!
FREE NIGHT FOR YOU – TO STAY LONGER !
(b) Additional week – Free Night (8th night) Added to your week extension.
I have stayed at this hostel twice. Its in a great location right next to the Boardwalk. Will stay here again next time I'm in Venice.
Great location. I stayed in a single private ensuite which was clean and very spacious. Comfortable bed. Good value for money. WiFi worked fine.
Great location one block from the beach, got a lovely big airy private room with 2 big beds, kitchenette & bathroom. Only there for one night so didn't use the facilities but saw a big TV room, kitchen & little outdoor seating area which was cute. Only thing I would criticise is the left luggage situation, it was a corner in the reception which was often unattended do anyone could actually come off the street & take a bag, having a locked storage area would be better.
When we arrived first person we saw took a $50 room deposit without explaining it- didn't find out until someone else was on the desk and there was no warning. Not a major issue but takes up to 4 working days to get your money back in your bank so could have done with some warning as we're on a super tight budget!
The price seems a little expensive for a hostel that's not on the beach.
Is a good hostel only for one night is really close to Venice beach, but I think they need to improve their facilities looks very old and tetric some parts, the beds wear clean, the breakfast really nice, as a recommendation they ask you for a 50 USD deposit maybe something you need to consider before make your book or arrive to the property. also the attention and service from the staff its ok.
This was the worst hostel I never stayed in my life Dirty, unsafe, no facilities at all, the breakfast it doesn't exist. The manager was rude and impolite. I payed by cash and then the addebit the amount in my credit card also. Staff rude. All the place is dirty and smell really bad.


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Northern Apennines: The U.S. Army Campaigns of World War II (Pamphlet)
World War II was the largest and most violent armed conflict in the history of mankind. Highly relevant today, World War II has much to teach us, not only about the profession of arms, but also about military preparedness, global strategy, and combined operations in the coalition war against fascism. This illustrated brochure is one of a series of 40 that describe the campaigns in which U.S. Army troops participated during the war. Each brochure describes the strategic setting, traces the operations of the major American units involved, and analyzes the impact of the campaign on future operations. CMH 72-18.
Other products produced by the U.S. Army, Center of Military History (CMH) can be found here: https://bookstore.gpo.gov/agency/1061
This brochure would be a valuable resource for military scholars, historians, veterans, students, and others interested in WWII history.
Oland, Dwight D.
United states Army Campaigns of World War II
Army History
Normandy: The U. S. Army Campaigns of World War II (Pamphlet)
Po Valley: The U.S. Army Campaigns of World War II (Pamphlet)
Rhineland: The U.S. Army Campaigns of World War II (Pamphlet)
Aleutian Islands: The U.S. Army Campaigns of World War II (Pamphlet)
China Defensive: The U.S. Army Campaigns of World War II (Pamphlet)

redpajama_set_name: RedPajamaCommonCrawl


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Measuring quality in Malawi's community health system: Barriers and challenges
As the drive for Universal Health Coverage and the Sustainable Development Goals (SDGs) has led to a push for greater health service access, the issue of sustaining and embedding quality in the ways in which these services are delivered has gained prominence. Measurement of quality and attribution of its effects in health is challenging at any level. But little is known about how quality is assessed within community health programmes, who are on the frontline of health service delivery in many low- and middle-income settings. The degree to which new initiatives like the Lancet Commission on Quality in Health Systems…
Tailoring mass drug administration to context: implementation research is critical in achieving equitable progress in the control and elimination of helminth neglected tropical diseases in sub-Saharan Africa
The concept of a technological quick fix or 'magic-bullet' for control and elimination of Neglected Tropical Diseases (NTDs) is flawed. NTDs are embedded within complex biological and social systems that are shaped by ecological and political contexts. This commentary emphasises the need for implementation research to address implementation gaps in the control of NTDs. With a specific focus on sub-Saharan Africa and helminth diseases amenable to preventive chemotherapy through mass drug administration, we explore the important role of context, programme partnerships and community in achieving equitable and effective NTD control.
Snap shots from a photo competition: what does it reveal about close-to-community providers, gender and power in health systems?
In this commentary, we discuss a photography competition, launched during the summer of 2014, to explore the everyday stories of how gender plays out within health systems around the world. While no submission fees were charged nor financial awards involved, the winning entries were exhibited at the Global Symposium on Health Systems Research in Cape Town, South Africa, in October 2014, with credits to the photographers involved. Anyone who had an experience of, or interest in, gender and health systems was invited to participate. Underlying the aims of the photo competition was a recognition of the importance of participation of…
Gender and the contemporary migrant journey
From the 30 June – 2 July 2015 a group of researchers, policy analysis and civil society representatives met in Singapore to debate and discuss how gender roles and expectations influence the factors leading to migration, male and female migrants' different experiences of migration and its impact on migrants, their families and communities. Our analysis does not equate gender with women and girls but aims to unpack how changes to occupational niches and flows of female migrants shape relationships with employers, families and friends, how they shape society and change our notions of gender and age appropriate behaviour. This conference…
Sexuality and development program: An annotated bibliography
This is an annotated bibliography that has been put together by the IDS Sexuality and Development Programme. The IDS Sexuality and Development Programme is a reaction to the inadequate manner in which sexuality is approached by the development sector. Sexuality is not taken seriously: it is considered a frivolous, trivial issue that doesn't relate to the more important aspects of development such as poverty. This is something that needs to change. This eclectic bibliography reflects global thinking on sexuality, bringing together texts on poverty, pleasure, gender, heteronormativity, rights, and a lot more! The ideas it contains will inspire you to think…
Strengthening the research to policy and practice interface: exploring strategies used by research organisations working on sexual and reproductive health and HIV/AIDS
This commentary introduces the HARPS supplement on getting research into policy and practice in sexual and reproductive health (SRH). The papers in this supplement have been produced by the Sexual Health and HIV Evidence into Practice (SHHEP) collaboration of international research, practitioner and advocacy organizations based in research programmes funded by the UK Department for International Development.
Sexuality and Empowerment: An Intimate Connection
What does sexuality have to do with women's empowerment? Research from the Pathways of Women's Empowerment RPC shows that sexuality affects women's political and economic empowerment in a number of important ways. For example, in the ways that women experience seeking election to political office, how women are treated and respected (or disrespected) in the workplace and in public, and how families and communities place expectations on how women should behave. Being exposed to sexual harassment and sexual violence and not being able to exercise choice in their sexual relationships affects women's wellbeing and ultimately undermines political, social and economic…


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Viral resistance to antiretroviral therapy threatens our best methods to control and prevent HIV infection. Current drug resistance genotyping methods are costly, optimized for subtype B virus, and primarily detect resistance mutations to protease and reverse transcriptase inhibitors. With the increasing use of integrase inhibitors in first-line therapies, monitoring for integrase inhibitor drug resistance mutations is a priority. We designed a universal primer pair to PCR amplify all major group M HIV-1 viruses for genotyping using Illumina MiSeq to simultaneously detect drug resistance mutations associated with protease, nucleoside reverse transcriptase, non-nucleoside reverse transcriptase, and integrase inhibitors.
A universal primer pair targeting the HIV pol gene was used to successfully PCR amplify HIV isolates representing subtypes A, B, C, D, CRF01_AE and CRF02_AG. The universal primers were then tested on 62 samples from a US cohort of injection drug users failing treatment after release from prison. 94% of the samples were successfully genotyped for known drug resistance mutations in the protease, reverse transcriptase and integrase gene products. Control experiments demonstrate that mutations present at ≥ 2% frequency are reliably detected and above the threshold of error for this method. New drug resistance mutations not found in the baseline sample were identified in 54% of the patient samples after treatment failure. 86% of patients with major drug resistance mutations had 1 or more mutations associated with drug resistance to the treatment regimen at the time point of treatment failure. 59% of the emerging mutations were found at frequencies between 2% and 20% of the total sequences generated, below the estimated limit of detection of current FDA-approved genotyping techniques. Primary plasma samples with viral loads as low as 799 copies/ml were successfully genotyped using this method.
Here we present an Illumina MiSeq-based HIV drug resistance genotyping assay. Our data suggests that this universal assay works across all major group M HIV-1 subtypes and identifies all drug resistance mutations in the pol gene known to confer resistance to protease, reverse transcriptase and integrase inhibitors. This high-throughput and sensitive assay could significantly improve access to drug resistance genotyping worldwide.
Antiretroviral therapy has been shown to be the most potent intervention for both treating and preventing HIV ,. However, the effectiveness of antiretroviral drugs is threatened by the development and transmission of drug resistant virus ,. HIV drug resistance genotyping is a clinically important tool to detect the emergence of viral resistance and maximize the benefit of current treatment options ,. New sequencing techniques can improve sensitivity of drug resistance genotyping while also reducing costs. We recently published a paper outlining the benefits of using Roche/454 pyrosequencing to detect HIV drug resistance mutations with a capacity to reduce costs by 5-fold . As sequencing technologies have continually improved, the genotyping methods used in clinical settings to detect drug resistance have failed to evolve at a comparable pace. Here we present an updated deep sequencing genotyping assay utilizing the Illumina MiSeq. Advantages of this novel method over our Roche/454 approach include fewer systemic basecalling sequencing errors, increased multiplexing, use of a FDA-approved sequencing platform, detection of drug resistance to integrase inhibitors in addition to reverse transcription inhibitors and protease inhibitors with a single amplicon, and finally, simultaneous genotyping of all major group M HIV subtypes with a single set of amplification primers.
Detection of Integrase inhibitor drug resistance is particularly noteable because integrase inhibitors are now recommended by the department of Health and Human Services as part of first-line antiretroviral therapy in the United States . The use of integrase inhibitors as part of initial antiretroviral therapy is expected to increase because of the recent FDA approval of a new once daily integrase inhibitor (elvitegravir) that can be co-formulated with emtricitabine, tenofovir disoproxyl fumarate and cobicistat as a single pill once daily regimen (STRIBILD) . Current genotyping methods used to detect drug resistance to integrase inhibitors are limited and typically involve a separate assay from that used to identify drug resistance to reverse transcriptase and protease inhibitors ,. However, due to proximity of the integrase protein-coding region to the reverse transcriptase and protease protein-coding region in the viral genome, it is feasible to incorporate drug resistance genotyping of all three gene products together from a single PCR amplicon. By using a single amplicon, no additional labor or expense is added to the assay already detecting protease and reverse transcriptase drug resistance mutations.
The FDA-approved HIV drug resistance genotyping assays currently in use were developed using HIV group M subtype B viruses . However, subtype C comprises about half of the worldwide epidemic followed by subtype A (12%) and then B (11%) . Current commercial genotyping assays perform rather poorly with non-subtype B viruses because seven sets of sequencing primers must bind to highly variable targets during sequencing ,. Therefore, non-B assays require more replication and for many samples, fail altogether with the current commercially available genotyping assays. There have been many successful adaptations of the commercial Sanger-based genotyping assay to improve genotyping of non-B HIV subtypes, however, these assays do not include detection of integrase inhibitor mutations and are less sensitive than next-generation sequencing approaches -.
Cost is a major barrier to drug resistance genotyping in resource-limited settings. Deep sequencing technologies have significantly reduced the cost of sequencing but are not yet incorporated into standard HIV drug resistance genotyping. An Illumina MiSeq sequencer can yield over 25 million sequencing reads per run with the latest technology (MiSeq reagent kit v3). Through multiplexing, 96 samples can be processed in one run, bringing the cost of sequencing alone to < $10/sample. This is 3-fold less than Sanger-based sequencing. In addition, the clonal nature of deep sequencing methods along with the large number of sequencing reads generated improves sensitivity for the detection of mutations compared to Sanger-based sequencing ,,. Lastly, the Illumina MiSeq platform is currently the least error-prone deep sequencing method ,.
HIV sequences from all subtypes found in the Los Alamos National Labs HIV database (http://www.hiv.lanl.gov) were used to design a universal primer set to amplify all major HIV subtypes as described in the Methods section (HIV2252-F and HIV5073-R). We obtained HIV isolates from the International Panel of 60 HIV-1 isolates from the NIH AIDS Research and Reference Reagent Program, Division of AIDS, NIAID, NIH (cat. #11412) representing subtypes A, B, C, D, CRF01_AE and CRF02_AG. We selected 19 isolates to represent geographically diverse regions as shown in Table 1, isolated viral RNA and performed one step RT-PCR to create PCR amplicons according to the protocol outlined in the Methods section. Despite a wide range of TCID50 and/or P24 content in the panel isolates tested, all isolates yielded a strong amplification product after 40 cycles of PCR as visualized on a 1% agarose gel (Additional file 1). These results suggest that the primer pair designed for this method could be used to amplify all major group M HIV subtypes.
* Provided by the NIH AIDS Research and Reference Reagent Program.
To assess the error associated with the RT-PCR amplification and sequencing of samples, a clonal virus stock was generated from a plasmid containing the HXB2 HIV sequence. We PCR amplified and sequenced the stock as described in the Methods section and as depicted in Figure 1. We assessed all nucleotide variants present above a 0.1% frequency across the entire Pol region sequenced from two independent amplifications and sequencing runs of the HXB2 clonal stock amplicons. Any variant found in our clonal virus stock is expected to be due to PCR or sequencing errors. The frequency of these variants determined our error limit threshold for this assay. Nucleotide polymorphisms that result in a non-synonymous amino acid changes are presented in Additional file 2. Most nucleotide variants were present at frequencies less than 0.4%, however, two regions contained variants at frequencies between 0.6% and 0.9%. One insertion was present at a frequency of 0.9% that was associated with the end of the first of two back-to-back long homopolymer runs (AAAAAAGAAAAAA) found near the K101 and K103 drug resistance mutations, but not within them. Another single nucleotide polymorphism was found at a 0.6-0.7% frequency downstream of the integrase drug resistance mutations (nucleotide position 2779 (R275R in integrase)). This polymorphism was a synonymous change that did not alter the amino acid sequence. These results suggest that we see some evidence of increased mutations associated with homopolymers in Illumina data, as has been published, but that those mutations are not present above a 1% frequency nor do they impact the codons directly associated with drug resistance . In addition, errors associated with the GGC sequence motif were also not found above a frequency of 0.5%. We also detected five variants present at 99.9-100% frequencies that are likely differences between the modified HXB2 plasmid we sequenced and the published HXB2 strain and were ignored as variants caused by PCR or sequencing errors (non-synonymous changes shown in Additional file 2). Overall, no variants were found above a 0.9% frequency in our clonal HIV stock.
Preparation and sequencing of samples. (A) Plasma is isolated from whole blood from up to 96 samples. (B) Viral RNA is isolated from up to 1 ml of plasma. (C) Viral RNA is used in a one-step RT-PCR amplification of a 2.8 kb region of the pol gene. When nested PCR is required, a 4.8 kb region is amplified as an external PCR followed by the 2.8 kb nested PCR of the pol gene. (D) PCR products are purified either by gel electrophoresis followed by gel extraction or through size-exclusion magnetic beads and then quantitated using the Qubit system. (E) Purified products are randomly fragmented and subjected to a limited cycle PCR to add sequencing adaptors and indices used for multiplexing samples. (F) Newly created libraries are purified by size-exclusion magnetic beads to remove short fragments. (G) The average size of the library fragments are calculated by bioanalysis and final concentration of the libraries calculated by Qubit are used to normalize each library and pool multiple libraries together at equimolar ratios. (H) Libraries are sequenced on the Illumina MiSeq. (I) Geneious Pro Software is used to trim sequencing reads based on quality scores and assemble the reads to a HXB2 reference sequence annotated with HIV drug resistance mutations. Geneious is used to identify variants within each sample relative to HXB2. Finally, variants associated with drug resistance mutations were extracted and their frequencies noted. Details about the analysis parameters are outlined in the Methods section.
When specifically assessing nucleotide variants associated with amino acid changes linked to HIV drug resistance across the pol gene, we found that all variants within drug resistance sites were present at frequencies below 0.3% of the viruses sampled from our clonal stock (Additional file 2). Therefore, given both the error limits within the drug resistance sites and outside of the drug resistance sites, variants found at frequencies greater than 1%, are likely authentic, while those below this threshold may result from RT-PCR and sequencing artifacts. Repeated sequencing of a subset of samples revealed that variants above 2.0% are consistently detected, while some variants found at frequencies between 1.0% and 2.0% are not (Additional file 2). Therefore, we designated 2.0% as the minimum threshold frequency for variants in subsequent experiments. Previous studies suggest that incorrect nucleotide incorporation associated with PCR error typically occurs at rates under 2.0%, supporting our finding that variants found at a greater than 2.0% frequency are likely true variants . Also, the error rates described here are very specific to the precise protocol, polymerases and sequencing kit used in this manuscript. Error rates should be reassessed if any changes to the method are made.
To determine whether nested PCR increased the error associated with low-frequency mutations, we performed the same test as described above, but subjected the clonal virus stock to two rounds of PCR under the same conditions used for primary samples. Once again, variants from the expected HXB2 sequence were present below a frequency of 1.0% (Additional file 2).
We previously published a high throughput next-generation-based HIV drug resistance genotyping technique based on the Roche/454 sequencing platform . One of the disadvantages of this system was the error associated with nucleotide homopolymer runs resulting from the sequencing chemistry used in the Roche/454 system. Sequence regions with homopolymer runs of three or more nucleotides are often miscalled, presenting a problem for some important drug resistance mutations like K103N and K65R that are encoded by homopolymeric nucleotide sequences. The competitive addition of reversible terminators used in Illumina's sequencing technology greatly reduces homopolymer errors resulting in more accurate identification of drug resistance mutations within these important sites. After trimming, the nucleotides representing the homopolymers in K103N and K65R mutations found in our patient samples maintained Phred quality scores > Q30 (or p = 0.001), lending greater confidence to the nucleotide bases called in these regions than was afforded by the Roche/454 assay where quality scores in these regions often dropped below Q20.
We obtained plasma samples collected from adults with a history of injection drug use who participated in the AIDS Linked to the IntraVenous Experience (ALIVE) study in Baltimore, MD . Previous research with this cohort showed that virologic failure occurs with high frequency when participants experience incarceration, but it is not known whether the viral rebound that occurs in this setting is associated with development of drug resistance . To answer this question while testing our method on primary HIV isolates, we genotyped HIV RNA from stored plasma specimens obtained from ALIVE participants. First, we isolated plasma viral RNA from 29 patients with samples from at least two time points for a total of 62 samples (see Additional file 3). 94% (58/62) of the samples were successfully amplified and sequenced, though 9 of these samples required nested PCR amplification. Most of the samples that either failed or required nested PCR either had low viral load values (<1,000 copies/ml) or were 5–13 years old and underwent multiple freeze-thaw cycles prior to PCR amplification (see Additional file 3). Of the samples that were successfully sequenced with viral loads above 2,000 copies/ml, 94% (48/51) of the samples amplified with one round of PCR using the universal primer set. Since each unique patient sample amplified in at least one time point and our primers are universal for multiple subtypes, we do not believe that the subtype of the patient virus was the reason for the failure to amplify in three samples. In any event, our sequences clustered with subtype B virus in phylogenetic analysis of the pol gene sequences (Additional file 4). Overall, we expect that if this method was used on recently collected samples with viral loads greater than 2,000 copies/ml for timely genotyping assays, nested PCR would not be required. Lastly, we were able to sequence primary isolate samples with a viral load as low as 799 copies/ml with nested PCR and 1070 copies/ml with a single round of PCR (see Additional file 3). However, each patient sample likely exhibits a unique limit of detection depending on the sequence concordance between the primers and patient virus.
Including controls, 63 PCR amplicons were fragmented and pooled together in a single MiSeq run. The cluster density of the sequencing run was 663 k/mm2 and the average number of sequence reads obtained per sample was 146,780 (range: 74,848-244,428, stdev: 34,556). The coverage, or number of sequences that represent each drug resistance site after mapping to a reference sequence, varied between each patient and across the pol gene. Figure 2 shows the coverage of a representative sample (patient 16) with 142,169 total reads. All nucleotides present between the first protease inhibitor resistance mutation (HXB2 position 1826) and last integrase inhibitor drug resistance mutation (HXB2 position 4238) were represented by more than 1,000 sequence reads in this patient (red squares in Figure 2). The goal of this method to generate a depth of coverage of >1000 sequencing reads/nucleotide position and in fact, at the major drug resistance sites, the average coverage of each mutation was over 1000 sequence reads (Table 2). Based on previous next-generation sequencing work, to accurately detect mutations at a frequency of 1.0%, minimal coverage requirements have ranged from 300 to 1850 sequencing reads ,-. With our minimum frequency threshold set to 2.0%, requiring a minimum of 1000 sequencing reads is conservative relative to previous publications. Across all samples, the average number of sequences representing each drug resistance site was 3,795 sequences. While coverage varied across the pol gene, the quality of all assembled sequences was very high due to the stringent trimming parameters (see Methods section) used during analysis.to remove nucleotides whose base call was deemed less than 99.9% accurate by the sequencing software prior to assembly (phred quality score > Q30 or p > 0.001). Note that this data was generated prior to the release of the latest MiSeq sequencing kits, which now have an average output capacity of 25 million reads per sequencing run. This would more than double the reads obtained per sample as well as double the sequence read coverage at each nucleotide site given the same pooling strategy.
Representative sequence coverage across the pol gene. The number of sequences representing each nucleotide across the pol gene (i.e. "coverage") is shown for all sites that differed from HXB2 in a representative sample (sample 16 v11). Sites of all known drug resistance mutations are over-layed as red squares and the graph is divided into sections representing mutations associated with protease, reverse transcriptase or integrase drug resistance for reference.
*Boldface mutations are major drug resistance mutations, non-boldface mutations are accessory mutations.
In general, across all patient samples and as exemplified in Figure 2, the coverage of the nucleotides associated with the protease inhibitor mutations found closest to the 5′ end of protease were lower than the number of sequences representing all other drug resistance mutation sites downstream. There are four accessory mutations (L10, V11, G16E and K20) and zero major mutations that sit close to the end of the original pol gene PCR amplicon that are sometimes affected by this reduced coverage (Table 2). These four sites are less represented because transposon-based fragmentation creates fewer fragments at the ends of the input DNA strand (original full-length pol gene amplicon) that have the necessary adaptor required for sequencing. Instead of 1000s of reads, sometimes these mutations are represented by hundreds of reads in this cohort (see Table 2). For the two mutations (L10 and V11) in our cohort that are represented by an average of 300 sequencing reads, a minimum frequency requirement could be increased to 6.5% to ensure that at least 20 reads are found containing the mutation, keeping the requirement the same as a mutation found at a 2% frequency in 1000 sequencing reads. This caveat to this approach could be solved by generating a primer that sits further upstream in the protease region, however, primers design is constrained when trying to keep the primers universal across multiple HIV clades. As mentioned above, with the latest MiSeq sequencing kits, coverage will also double at these sites. Lastly, reducing the multiplexing would also yield greater coverage per sample at this site if coverage of these mutations was a concern. The data from this patient cohort shows that this method combining 63 samples together results in characterization of major drug resistance mutations with thousands of sequencing reads representing most mutations. Based on our average coverage of 3,795 sequences, extrapolation would suggest that 96 samples could be pooled together and average coverage of major drug resistance mutations would still be over 1,000 sequences per drug resistance site when optimal cluster density is reached on the MiSeq sequencing chip. This would further increase by at least 2-fold by using the latest MiSeq reagent kit V3 technology.
Although transposon-based fragmentation is theoretically unbiased, we observed consistently greater coverage in the reverse transcriptase protein coding region than protease and integrase coding regions across all samples, as exemplified in Figure 2. This similar coverage pattern between different samples over the same genetic regions is similar to that previously observed with whole genome HIV and SIV sequencing using the same fragmentation method . Therefore, it is likely that there is some bias in fragmentation that yields ideally sized fragments for sequencing in some parts of the HIV genome over others.
Lastly, the assembled sequences were aligned and a maximum likelihood phylogenetic analysis was performed along with reference sequences from the panel of HIV isolates that we PCR amplified with our universal primer set (Additional file 4). As shown in Additional file 4, all samples from this cohort cluster with subtype B viruses, including the HXB2 control samples that we sequenced. In addition, the two time points from each sample clustered with each other and not with other samples, indicating that there was no cross-contamination resulting in the changes in drug resistance mutations found between the two time points from each patient sample.
To detect HIV drug resistance mutations in virus from the 29 ALIVE participants failing treatment after release from prison/jail, we analyzed the pol gene sequencing reads from two time points. First, the ALIVE participants successfully suppressed HIV before incarceration by using antiretroviral therapy. The first time point we sampled was at the time point just prior to this viral suppression. Some patients were drug naïve at this time point, but others were previously drug experienced (as outlined in Additional file 3) and either changed regimens or began taking ARTs after a break in treatment to reach viral suppression at the subsequent time point. The second time point represents the virus after treatment failure, as detected at an ALIVE study visit, after release from jail or prison. We obtained sequence data from both time points from 26/29 specimens. Relative to the first time point sequenced (baseline), new drug resistance mutations emerged in 54% (14/26) of the patients exhibiting treatment failure that were not detected at baseline (Figure 3A and Table 3). One additional sample (patient 27) contained major drug resistance mutations at both time points tested that may have contributed to treatment failure at the second time point (Table 4). These mutations, I54V, L90M, K103N and M184V, were present at frequencies >85% at both time points with most being present at >99% of sequences. The remaining samples without emerging drug resistance mutations contained primarily accessory mutations at baseline or at the second time point or very low level major drug resistance mutations that disappeared by the second time point and therefore likely do not contribute to treatment failure. Therefore, these patients may be failing treatment for reasons other than drug resistance mutations in the pol gene product. For example, some patients may fail due to lack of adherence or presence of mutations in Gag or the cytoplasmic tail of Env, which have been recently reported to affect drug resistance to protease inhibitors -. In the future it will be possible to expand our technique to include these regions outside of the pol gene, however, it would require amplification of more than one amplicon prior to fragmentation and sequencing.
Characterization of the drug resistance mutations identified in the ALIVE cohort after treatment failure. (A) The frequency of different types of HIV drug resistance mutations found in 26 patient samples with after treatment failure. Major mutations are as defined by the Stanford drug resistance database and accessory mutations are all other mutations associated with drug resistance as designated by the International AIDS Society (IAS). (B) Percentages of the 29 emerging mutations found at the second time point but not first time for all participant samples that were major or accessory mutations and whether the mutations rose above the 20% threshold expected to be detected by commercial HIV drug resistance genotyping techniques.
Boldface font = major mutation. Regular font = accessory mutation.
Boldface: correlation between mutation, treatment and drug resistance profile in each patient sample at the time point of treatment failure. H = high level drug resistance, I = intermediate drug resistance, L = low level drug resistance, PL: potential low level drug resistance. Drug resistance mutations in italics are not associated with any reported drug taken by the patients throughout the course of this study. *Coverage refers to the number of sequencing reads representing a given nucleotide. **Patient 27 virus also harbored I54V, L90M, K103N and M184V at both time points. These mutations did not emerge between treatment success and failure, but likely contributed to overall failure.
As a way to assess our drug resistance genotyping assay, we compared the major drug resistance mutations identified by our genotyping assay with the treatment regimens reported by the ALIVE study participants at the time of treatment failure. We define major drug resistance mutations as those included in the Stanford Drug Resistance Database matrices that are associated with high levels of phenotypic drug resistance ,. This is opposed to accessory mutations whose role in treatment failure is less clear. Overall, 57% (8/14) of the patients with virus harboring any emerging drug resistance mutations relative to the first time point tested had major drug resistance mutations (Figure 3A and Table 3). We focused our mutation/treatment association analysis on these eight patients and analyzed the major mutations found in their virus using the Stanford drug resistance database Genotype Resistance Interpretation calculator ,. The results of the calculator were then compared to each patient's self-reported treatment regimen at the time of failure (Table 4). Of the eight patients harboring virus with major drug resistance mutations, seven patients had virus with mutations associated with a high level of drug resistance to one or more of the drugs in their regimen at the time point of failure (boldface in Table 4). Table 4 also shows the mutational load (viral load*frequency of mutation) of each mutation within each patient. M184V and K103N were the major mutations associated with treatment failure in this cohort and it is notable that the major drug resistance mutations that correlate with the drug regimen at the point of treatment failure are found at frequencies well above 50%, indicating drug selection pressure. As expected, the major mutations identified in most of the patients of this cohort using our genotyping technique associated well with the treatment regimens reported by the patients at the time of treatment failure.
Major drug resistance mutations emerging after treatment failure were then compared with all drugs self-reported for each individual during the course of all time points where data was collected. As shown in figure 3B, almost half (14/29) of all the 29 mutations emerging after treatment failure were major mutations. Overall, 10/14 major drug resistance mutations were associated with the patient self-reported drug regimens from either the time point of failure or previous time points (Table 4). These mutations were found at frequencies >50% while those that do not associate with the treatment regimen are found at <20%. Altogether, these data are consistent with the conclusion that this genotyping assay is detecting drug resistance mutations that would be expected based on the treatment regimens reported by the participants in the ALIVE cohort.
Accessory mutations are those that alone may not render resistance, but may contribute to resistance when combined with other mutations. All mutations identified on the International AIDS Society (IAS) USA drug resistance mutation list that were not part of the Stanford drug resistance database major mutation matrices were categorized as accessory mutations in this study. We identified accessory mutations in 23% of ALIVE patient samples that did not have major drug resistance mutations at the time of treatment failure (Figure 3A). Most of these mutations were present at frequencies <20% (Figure 3B and Table 3). While it is likely that these accessory mutations contributed to resistance, this cohort was not appropriately powered to explore the correlations between accessory mutations and drug resistance more definitively.
Currently, FDA-approved Sanger sequencing-based HIV drug resistance genotyping methods such as ViroSeq identify mutations present above a frequency of 20% within a host's viral population ,. Therefore, mutations found below this 20% frequency (i.e. minority variants) might be missed by current commercial techniques. As shown in figure 3B and detailed in Table 3, 59% (17/29) of all drug resistance mutations found in the ALIVE cohort by this genotyping technique were below the 20% frequency limit of detection of current genotyping. This indicates that the presented genotyping technique is likely more sensitive than those currently available commercially. Development of sensitive assays, like the genotyping assay presented here, will support future studies designed to delineate which minority mutations are important prior to the start of specific antiretroviral therapy. In our cohort, mutations likely contributing to treatment failure of a given drug regimen were predominantly present at frequencies >20%.
An important consideration when detecting lower frequency mutations or variants from samples with lower viral loads is reliability of the variant frequency detected and possibility of template resampling. While we were unable to do this with the presented cohort due to sample limitations, PCR amplifying a sample in triplicate and assessing the variant frequencies of each independent test for samples of different viral loads would be an important reliability test if adapting this methodology to clinical samples. In addition, when the number of sequences representing each nucleotide variant exceeds the number of virus genome templates (due to low viral loads) used to initiate the RT-PCR, then the sequences are representing each template more than once. This could result in false variant frequencies if there is a bias for one template over another during the PCR amplification. One way to address this concern would be to require higher viral loads or multiplex more samples on the sequencer to reduce the number of sequencing reads to below the number of templates added to the initial RT-PCR reaction. In this study, therefore, it is possible that some of the frequencies presented for samples with lower viral loads are not entirely accurate due to possible template resampling (Additional file 3). It remains questionable exactly what it means to have a mutation present at 10%, 50% or 99%. With our current understanding of drug resistance mutations, a mutation present at any frequency could quickly turn into a mutation present in nearly all viruses given drug selection pressure. Therefore, an important drug resistance mutation present at any frequency above the error rate would likely warrant recommendations for changes to drug regimens regardless of the actual frequency detected.
Lastly, one of the advantages of this MiSeq genotyping method includes detection of integrase inhibitor drug resistance mutations. One patient in the ALIVE cohort (patient 16) with no prior exposure to integrase inhibitors had a virus with a minority (7.6%) drug resistance mutation to Elvitegravir (Tables 3 and 4). Such a mutation should be considered when assigning a treatment regimen to this individual already failing their current antiretroviral regimen at the time of sample collection. The rollout of integrase inhibitors as part of initial treatment regimens increases the need for integrase inhibitor drug resistance testing prior to treatment initiation.
We have already highlighted the advantages of the Illumina MiSeq platform over our previous work using the Roche/454 GS junior platform. Additionally, Roche plans to phase out 454 machines in 2016 making this platform obsolete for future development. This work is also conceptually similar to recent work from Gibson et al. describing comprehensive HIV drug resistance genotyping across multiple HIV group M subtypes for protease, reverse transcriptase and integrase inhibitors as well as coreceptor tropism using the Ion Torrent Personal Genome Machine . There are, however, specific advantages of our methodologies using the MiSeq, including greater output (Illumina MiSeq: 13-15Gb vs. Ion Torrent PGM: 1Gb) and reduced systemic sequencing error rates (Illumina MiSeq: <0.4%, Ion Torrent: 1.78%) . Fewer errors reduce analysis time and improve data reliability. In addition, our method is technically simpler, requiring a single fragmented PCR amplicon over the three required for the Gibson et al. method. Lastly, Illumina MiSeq is the first and only next-generation sequencing platform to receive FDA approval for assays developed on that device, making it the optimal deep sequencing platform to develop a HIV drug resistance assay for possible clinical use in the future .
Data analysis of next-generation sequencing techniques can be exceptionally difficult and requires many considerations. For example, when assessing viral variants related to HIV drug resistance one must consider the viral load of the samples to assess the possibility of template resampling and its effects on frequency determination, error associated with PCR amplification, systematic errors associated with sequencing, and accurate data analysis.
One of the advantages of the described data analysis approach is its relative simplicity using Geneious software. This software is very user-friendly and does not require a strong background in bioinformatics or programming skills. The parameters used in this analysis are fully defined in the Methods section and briefly include 3 basic steps: (1) pair the paired-end sequences together for each sample (2) trim ends based on quality and reference map against an annotated HXB2 sequence available here: (https://dholk.primate.wisc.edu/wiki/dho/public/page.view?name=default) (3) call variants relative to the HXB2 reference sequence. Steps 2 and 3 can be performed simultaneously for all samples in a sequencing run. Overall, only a few hours of hands-on time are necessary to complete steps 1, initiate step 2 and initiate step 3, with several hours of hands-off time to complete steps 2 and 3. Once the variants have been detected, the annotation table results can be exported out of Geneious and assessed in Microsoft Excel or in a text editor to determine which samples have which drug resistance mutations and their frequencies. Depending on the speed of the computer used to perform this analysis, a run of 64 samples could be fully analyzed within two days on a standard laptop with most of the analysis performed in Geneious being hands-off. A fully automated analysis approach would be required to use this method in a clinical setting, however, the provided methods are relatively quick and simple for research-based projects and is considerably faster than Sanger-based data analysis of 64 samples.
One of the sequence analysis challenges with working with HIV drug resistance is that resistance is defined by changes in amino acid sequence that could be rendered by several different nucleotide variants. Many analysis tools consider a single nucleotide variant at a time and not necessarily the effect of two nucleotide changes from a single sequence within a codon that might change an amino acid. For example, a variant caller might call a change from ATG (Met) to GTA (Val) as a mix of ATA (Ile) and GTG (Val), considering each single nucleotide change away from ATG as separate even though they are present in the same sequence. We have worked with the developers at Geneious to create a phased variant detection approach that is accurate when assessing nucleotide variants in the context of amino acid changes, which is paramount to our analysis approach. This variant detection approach is now built into the latest Geneious software release.
Lastly, while we can identify drug resistance mutations in the protease, reverse transcriptase and integrase regions simultaneously with this assay, given the nature of library formation and Illumina MiSeq sequencing we cannot necessarily associate together mutations found in one area of the pol gene product with mutations found in another area. With the paired-end technology it is possible to link one mutation from the same template to a mutation found ~600 bp downstream, but we cannot make those associations with mutations that span further apart. In this regard, this assay is not more informative than traditional genotyping assays using Sanger-based sequencing, which also cannot associate mutations together across multiple pol gene products. The only way to reliably span the entire pol gene from a single virus involves either cloning and sequencing or limiting dilution PCR and sequencing. However, sequencing technologies continue to improve and as error rates improve for techniques that sequence thousands of nucleotides in a single sequencing read, linking together all drug resistance mutations will become much easier.
We have designed a universal primer set that amplifies part of the pol gene from the major HIV-1 subtypes A, B, C, D, CRF01_AE and CRF02_AG. These primers were used in an Illumina MiSeq-based sequencing method for the detection of drug resistance in primary HIV samples from individuals failing treatment after release from prison. We characterized drug resistance to protease, reverse transcriptase and integrase inhibitors simultaneously. 54% of the patients failing treatment harbored mutations in their virus at the time of treatment failure that were not present before treatment. Of the patients with virus harboring major drug resistance mutations, all but one patient had virus with mutations associated with resistance to the self-reported treatment regimen at the time of treatment failure. This finding suggests that virologic failure associated with incarceration may be due to the development of drug resistance mutations in about half of cases. This implies that actions to prevent drug resistance, such as preventing treatment interruption during and after incarceration, may reduce virologic failure associated with incarceration. 59% of all the mutations found were present at frequencies between 2% and 20% of the within-host virus population and would likely have been missed by traditional Sanger-based genotyping techniques. The technique presented in this manuscript should facilitate larger studies to elucidate the role(s) of these minority variants in treatment failure- an important consideration as genotyping moves to more sensitive sequencing platforms. Additionally, these methods can be adapted to sequence any region of the HIV virus by designing new primer sets to study a variety of questions related to HIV evolution. The results shown here suggest that the presented method is a significant advance over current HIV drug resistance genotyping by improving sensitivity, broadening the detection of mutations from protease through integrase, and improving genotyping in non-B HIV subtypes.
The subjects used in this study provided informed written consent. The phlebotomy protocol and consent forms were approved by the Internal Review Board of Johns Hopkins University. The collected samples were de-identified and sent to the University of Wisconsin-Madison for sequencing. The protocol was approved by the Health Sciences Institutional Review Board at the University of Wisconsin-Madison (protocol number 2012–0140).
Sixty-two participant samples were selected for inclusion in this study. These samples originated from individuals with a history of injection drug use who participated in the ALIVE study between 1997 and 2009 ,-. Selected participants were successfully treated with antiretroviral therapy (ART) prior to incarceration, but failed ART after release from prison. A baseline, pre-incarceration blood sample collected at a study visit before viral suppression was achieved and a follow-up sample collected after release from prison and treatment failure were obtained for this study (Additional file 3). As outlined in Additional file 3, many study participants were not drug naïve at the first time point we genotyped, but either failed their drug regimen or stopped taking antiretroviral drugs leading to an increase in viral load at the time point we sampled. Either a change in regimen or restarting a drug regimen resulted in viral suppression at the time point following the first time point we sampled. However, at a subsequent time point that coincided with the release from prison, individuals failed treatment again, which is the second time point that we tested. The range of viral load of these samples was 799–1,110,000 copies/ml. Treatment regimens were self-reported by the patients at each time point a sample was collected.
Viral stocks containing subtypes A, B, C, D, CRF01_AE, and CRF02_AG were obtained from the NIH AIDS Research and Reference Reagent Program, Division of AIDS, NIAID, NIH (cat. #11412) and used to test the subtype specificity of our primers. Viruses were provided by Robert Gallo, Smita Kularni, UNAIDS, Nelson Michael, and Victoria Polonis. The pHXBn-PLAP-IRES-N+ plasmid (cat. #3610) was obtained through the NIH AIDS research and reference reagent program, Division of AIDS, NIAID, NIH from Dr. Benjamin K. Chen and Dr. David Baltimore. To produce a clonal viral stock to assess error associated with our method, the pHXBnPLAP-IRES-N+ (HXBn) plasmid was transfected into 239 T packaging cells using the Xfect Transfection Reagent (Clontech). The supernatant was collected two days after transfection to limit virus production to a single round and the virus was quantitated using the Lenti-X qRT-PCR titration kit (Clontech). Viral RNA was isolated from this supernatant (viral load = 115,000 copies/ml) and subjected to one-step RT-PCR and sequenced using the same protocol that was used to sequence patient samples. The initial plasmid DNA was also sequenced using the same protocol as the research samples without the initial reverse transcription step. Both DNA and viral RNA starting templates are expected to have no variants relative to the HXB2 reference sequence (GenBank NC_001802). In addition, we sequenced the protease and reverse transcriptase gene products from the HIV plasmid used to generate the clonal virus using a Sanger-based approach as a standard to verify the pol gene sequence in the plasmid. This verification revealed two mutations in (HXB2 positions 1805 and 2473) the plasmid that were not expected based on the published map of the vector and GenBank entry. These mutations in the plasmid were found in 99% of the viral RNA sequenced from the clonal virus stock and were ignored during analysis as changes in the plasmid relative to the published HXB2 sequence. All other variants found by Illumina sequencing in either the plasmid or the viral stock were considered "false" variants that likely resulted from error in the PCR, sequencing, or analysis of the sequences. We used the maximum frequency found as "false" variants (0.9%) as the minimum frequency threshold for "real" variants found within a patient's viral population (1.0%) that do not likely stem from error associated with the sequencing method.
Sequences representing multiple HIV subtypes were downloaded from the Los Alamos National Laboratory HIV database and aligned using the software program Geneious version 5.6. Regions of the pol gene flanking all known drug resistance mutations found in the protease, reverse transcriptase, and integrase protein coding regions were searched for conservation between group M HIV isolates. Two regions containing high conservation were identified and used to design PCR primers. Primers were optimized for melting temperatures, GC content and reduced hairpin and/or primer dimer formation as much as possible given restraints of the conserved regions (NetPrimer, Premier Biosoft International). The sequences of these primers named HIV2252-F and HIV5073-R can be found in Additional file 5 (nested primers). The forward primer contains a mismatch in the middle of the primer for some subtypes and is therefore designed with a degenerate nucleotide at that position (R = A/G). The reverse primer contained a mismatch in the middle of the sequence in some subtype C isolates. Two separate reverse primers were designed and tested with subtype C isolates. The primer that matched all group M isolates but contained a mismatch with some subtype C isolates amplified all subtypes well including all subtype C viruses tested and was used in this study (HIV5073-R). The expected PCR product size is 2892 bp. The external primers, as shown in Additional file 5, were previously designed (Todd Allen, personal communication).
A schematic diagram representing the major steps to prepare samples for drug resistance genotyping using the method described in this paper is presented in Figure 1. Plasma from each sample was centrifuged at 14,000 x rpm at 4°C for 1 hour to concentrate virus for viral RNA extraction using the QIAamp Viral RNA Mini Kit (Qiagen). Viral RNA was subjected to one-step RT-PCR amplification using Superscript III Reverse Transcriptase and High Fidelity Platinum Taq Polymerase (Invitrogen) and the primers HIV2252-F and HIV5073-R. RT-PCR conditions were as follows: reverse transcription was performed at 50°C for 30 min., the enzyme was denatured at 94°C for 2 min., 40 cycles of amplification was performed at 94°C for 15 sec., 55°C for 30 sec., and 68°C for 3 min., followed by a 68°C extension for 10 minutes. Amplification was more reliable with the addition of 5% DMSO to the PCR reaction. Products were visualized on a DNA Flashgel (Lonza) and any sample containing PCR amplicons other than the product of interest was electrophoresed on a 1% agarose gel and the expected 2.8 kb amplicon was extracted using a Qiagen gel extraction MinElute kit (Qiagen). All samples were further purified using size exclusion beads (Agilent XP) to remove primer dimers at a 1:1 DNA:bead (volume) ratio. Samples that failed to amplify with a single round of PCR were subjected to nested PCR using the following primers in an external PCR (Additional file 5): HIV737-F and HIV5578-R. External PCR conditions included reverse transcription at 50°C for 60 min., polymerase activation at 94°C for 2 min., 2 cycles of 94°C for 15 sec., 60°C for 30 sec., and 68°C for 4 min. and 45 sec., 2 cycles of 94°C for 15 sec., 58°C for 30 sec., and 68°C for 4 min. and 45 sec., 31 cycles of 94°C for 15 sec., 55°C for 30 sec., and 68°C for 4 min. and 45 sec. followed by a 10 min. extension at 68°C. 5 μl of the 25 μl external PCR was used in a nested PCR using the conditions for single round PCR described above excluding the reverse transcription step. The nested primer set is shown in Additional file 5 and is the same primer set used for samples requiring only a single round of amplification.
Following size exclusion purification, PCR amplicons were quantitated using picogreen dye and the Qubit (Invitrogen) fluorometer or DTX 800 Multimode detector plate reader (Beckman Coulter). 1 ng of each sample was fragmented using Nextera XT transposon technology (Epicentre). The average size of the fragmented PCR amplicons was 774 bp (range 519-1060 bp) as detected by bioanalysis (Agilent). Following Nextera tagmentation, Illumina sequencing adaptors and molecular tags were added via PCR, size exclusion bead purification was performed, and samples were quantitated using picogreen as previously described. Individual samples were then pooled at equimolar ratios (1–2 nM/sample, depending on run) based on the mean size of each library. The final diluted 8–9 pM pool was denatured using sodium hydroxide according to the Illumina MiSeq protocol and 1% denatured PhiX beads were added as a sequencing control. Samples were loaded into a 300-cycle MiSeq cartridge and sequenced This protocol is also amenable to the updated Illumina 500 and 600 cycle MiSeq kits.
Data was analyzed using Geneious version 5.6 software. A HXB2 reference sequence (GenBank accession # NC_001802) was uploaded into Geneious and all drug resistance mutations were manually annotated onto the sequence to generate an annotated reference sequence for reference-based assembly (https://dholk.primate.wisc.edu/wiki/dho/public/page.view?name=default). Sequences are demultiplexed automatically on the MiSeq as part of the data processing steps and two paired .fastq files are generated for each sample representing the two paired-end reads. After importing the .fastq files from the MiSeq into Geneious, the two sequence lists from each sample were paired. Next, all sequences were trimmed at the ends as part of the assembly process using the modified-Mott algorithm and quality scores assigned by the sequencing base caller. This algorithm trims the ends to the point where trimming no longer improves the error rate by more than the error probability limit threshold set, in this case 0.001, or a 0.1% error rate. Sequences were then mapped to the annotated reference sequence with the following parameters: Gaps were allowed with a maximum of 15% per read and gap size of 15, word length was set to 14, maximum mismatches per read were set to 25%, minimum overlap identity was set to 80%, maximum ambiguity was set to 16 and "search more thoroughly for poor matching reads" was selected. In general, the reference assembler uses a seed and expand-type mapper, followed by a fine-tuning step that was set to none (fast / read mapping) for this analysis. All nucleotide variants represented by at least 5 sequencing reads and at a frequency >1% from the reference sequence were then called using the variant finder. This threshold was set based on previous work to establish minimum sequencing read coverage for next-generation sequencing ,. To ensure that variants were called relative to the correct codon, the "merge adjacent variations" and "use separate annotations for each variant at a position" were selected. Geneious developed a variant finder analysis tool that allows amino acid variants within a codon to be called together when present on the same sequence to accurately reflect the effects of all single nucleotide changes on the amino acid sequence. This variant finder was used as a plugin with Geneious 5.6 at the time of this analysis but has since been incorporated into Geneious starting with version 6.1 and is now part of their standard Geneious Pro software. Variants and their frequencies were exported into an excel document and filtered for those present in amino acid sites known to correlate with drug resistance based on the Stanford drug resistance database list and the 2012 list of IAS-USA HIV drug resistance mutations as annotated on the reference sequence. Frequency of each variant and the number of sequences representing each nucleotide position containing a variant away from the reference sequence was also calculated by the variant finder plugin.
A consensus sequence was constructed from the reference-based assemblies performed on each sample using the 50% strict setting. These nucleotide sequences were aligned by the CLUSTAL algorithm in MEGA 6 . A maximum likelihood (ML) phylogenetic analysis was conducted based on the GTR + G + I model, which was chosen using the Bayes Information Criterion in MEGA 6. The reliability of the clustering patterns in ML trees was tested by bootstrapping; 1000 bootstrap pseudo-samples were used.
Funding for this study was provided through the National Institutes of Health/National Institute on Drug Abuse (Grants: K23DA032306; U01DA023832; R01DA04334; and R01DA12568). We acknowledge the NIH AIDS Research and Reference Reagent Program, Division of AIDS, NIAID, NIH for the International panel of 60 HIV-1 isolates (cat. # 11412) from Robert Gallo, Smita Kularni, UNAIDS, Nelson Michael, and Victoria Polonis and pHXBn-PLAP-IRES-N+ plasmid (cat. #3610) from Dr. Benjamin K. Chen and Dr. David Baltimore. We thank Matt Kearse and Geneious for developing the variant finder plugin. We thank Jacquie Astemborski for help locating samples and generating the dataset for the samples used in this study.
DMD designed and carried out the drug resistance genotyping assay, analyzed data and wrote the manuscript. ALB participated in data analysis. ALH performed phylogenetic analysis. RPW provided the primary samples, helped design the experiments, and initiated the drug resistance genotyping of the ALIVE cohort. GDK and SHM are Co-PIs of the ALIVE study who designed the ALIVE study and oversaw data collection. DHO helped conceive and design the drug resistance genotyping assay. All authors read and approved the manuscript.
Administration USFaD: FDA allows marketing of four "next generation" gene sequencing devices. FDA news release, 2013. Department of Health and Human Services website: http://www.fda.gov/NewsEvents/Newsroom/PressAnnouncements/ucm375742.htm.


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Under what circumstances would you use Tenax Stone Liquid Wax?
Marbles are very prone to etching and becoming dull. Especially when marble is used in more harsh settings such as bars where alcohol, lime, lemon, salt, and other strong acid type products are used. In this instance, a professional stone sealer most certainly should be used. That really isn't an option. Marble should be sealed at least once per year, preferable twice per year, under these circumstances. The Sealer will penetrate into the pores of the marble to fill in microscopic holes and create a strong seal that keeps food, acid, wine, etc out of the stone. But the Sealer is not topical. Yes it definitely coats the top of the stone. But if a lime is left on the surface for a period of time, even the best sealer will break down and an etch will occur.
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Learn more about Sake in general by reading the answers to the most commonly asked questions below.
Sake is essentially a fermented alcoholic beverage made from rice.
It is at times referred to as a "rice wine" and, for import purposes it is actually taxed like a wine, but it is brewed more like a beer and has considerably different flavour profiles to wine; a wider range of temperature at which it can be enjoyed; a wider range of style of tableware including glassware and porcelain in which you can enjoy it; and a wider range of food with which it can be paired than wine.
So, simply put, it does it a disservice to classify it as a wine and it deserves to have its own category.
While the key, distinguishing ingredient in sake is obviously rice, there are a limited number of other key ingredients from which premium sake can be made.
First of all, there is the yeast which is essential in any alcohol production. However, the yeast requires sugars to consume and convert into alcohol, with carbon dioxide as a by-product.
Rice does not contain any available sugars but is made up of starch and, in sake production, the work of a fungus called "Koji-kin" is essential to breakdown the starch into the smaller fermentable sugars which the yeast can then eat.
Water is also an essential element in sake brewing. It makes up approximately 80% of the ingredients in a bottle of sake and is also used extensively during production for washing the rice, soaking the rice, steaming the rice and producing the fermentable sake mash. It is also used to wash the equipment.
Other additional ingredients can include brewer's alcohol which is only added to non-junmai sake. This is not to increase the alcohol percentage but to ensure that the aromas present in the main sake mash are captured in the liquid once the mash is pressed and do not stay in the sake lees (the leftover solids after pressing the sake mash). The addition of the brewer's alcohol is strictly limited to 10% of the weight of rice to produce the volume of sake.
Lactic acid is another permitted ingredient in the production of sake. Naturally occurring in the fermentation process, the addition of lactic acid cuts the production process down by around two weeks. The style of sake produced by adding lactic acid is called "Sokujo" and has less depth of flavour and concentration of umami than sake produced where the lactic acid is produced naturally by fermentation.
As for the non-premium, table sake, the addition of amino acids and sugars is also allowed, along with a higher percentage of brewer's alcohol.
The majority of sake produced and consumed in Japan (approximately 70-75%) is table sake which is called "Futshu-shu".
Premium Sake, however, has strict rules limiting the ingredients used and is then categorised depending upon the rice polishing ratio; the percentage of rice remaining after it has been polished.
First of all, Premium Sake falls broadly into two distinct styles of Junmai sake and non-Junmai sake. Junmai sake is sake to which no brewer's alcohol has been added. Non-Junmai sake has a limited amount of brewer's alcohol (10% of the volume of rice used) added to it prior to pressing. The Junmai style of sake tend to be richer in flavour on the palate making them more suitable for pairing with food and less aromatic. The non-Junmai style of sake tend to be more aromatic and smoother on the palate.
Within those two main styles, premium sake is further separated into an additional four categories according to the rice polishing ratio (the percentage of rice remaining after being polished), with the exception of Junmai sake which does not have a restriction on the rice polishing ratio.
One category is simply "Junmai" which does not have a rice polishing ratio requirement but is simply sake which is only made from rice, water, yeast, koji-kin fungus and lactic acid (as the only permitted additive).
On the other side the non-Junmai version is called "Honjozo" ("real brew") and for sake to be classified as Honjozo, the rice polishing ratio needs to be 70% or less of the rice remaining. It is usually quite flavoursome but suitable for warming and is quite smooth drinking with a light bouquet.
Then there is a category called "Tokubetsu" meaning "special" which either means that the rice polishing ratio is less than 70% or that there has been a special method used for production. You can either have a "Tokubetsu Honjozo" or a "Tokubetsu Junmai". Due to the higher polishing rate they have more elevated aromatics than the non-Tokubetsu version.
The next main category is the "Ginjo" and to be classified as "Ginjo" or "Junmai Ginjo" the rice must have been polished down to 60% of the rice grain remaining or less (the "Junmai Ginjo" not having any brewer's alcohol added). The effect of the polishing of the rice is that the flavour on the palate is not so umami rich but has more elegance and the aromatics are more elevated with aromas of fruit and flowers.
Then, at the pinnacle, the highest quality of premium sake is either "Daiginjo" or "Junmai Daiginjo". Along with the limited ingredients allowed for premium sake, the additional requirements are that the rice is polished down to 50% or less of its original size. The effect of polishing the rice to this extent means that you have very fragrant and complex aromatics on the nose and a more elegant, restrained, delicate flavour on the palate but also with increased complexity.
Sake brewing is quite complex with many different stages and is more time-consuming and hands on than with other alcoholic beverages.
If you look at the fermentation process alone then you will notice distinct differences in wine production and beer brewing.
The fermentation process for producing wine is "simple fermentation" as the sugars from the grape juice are available for the yeast to eat and produce alcohol.
When brewing beer an additional process is required in order to release the sugar in the cereal grain by germinating the barley or wheat in the malting process. This malt, now with fermentable sugars, is then transferred to the main tank mash for the yeast to convert the sugars to alcohol in a "multiple fermentation" process.
When it comes to brewing sake there are two separate fermentation processes that occur in the same tank. Firstly, the starches in the rice have to be converted into fermentable sugars. This is initially started by propagating the koji-kin fungus on steamed rice in the Koji room but continues in the same tank as the yeast is converting the sugars into alcohol. The result of this "multiple parallel fermentation" is that the sugars from the rice are released slowly meaning that the yeast eats slower and produces alcohol slower over a longer period of time. Combined with temperature control to maintain a slow production of alcohol and regular mixing of the tank the yeast does not die in a high concentration of alcohol and can go on to produce the highest naturally occurring volume of alcohol without distillation of around 22%.
What Food can you Pair with Sake?
As a result of the fermentation process, Sake naturally contains amino acids which make up "umami" the underlying delicious savoury notes. When you combine two different types of umami you have a synergistic effect and rather than simply doubling the flavour impact the result can be three or four times as flavoursome as the original flavours were.
When it comes to pairing chocolate, blue cheese and artichokes with wine it is considerably difficult to get a good flavour combination. However, sake does not create such clashes in flavour when paired but has the potential to improve the flavour of the food with which it is paired. It is therefore a good companion with most food including non-Japanese cuisine such as Chinese, Italian or French. Due to a wide range of styles of sake you can inevitably find a sake which not only accompanies the food you are eating but actually supports and increases the flavour of that food.
As a simple guide, choose the richer, more flavoursome Junmai and Yamahai for red meat or game, more elegant Honjozo and Junmai Ginjo for white fish, more aromatic Junmai Ginjo, Ginjo, Junmai Daiginjo and Daiginjo for simple, elegant appetisers and Nama (unpasteurised) for spicy food.


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Super Robot Wars 3 Download (1993 Strategy Game)
Strategy Games:
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Download full Super Robot Wars 3:
Super Robot Wars 3 screenshots:
Virtually unknown outside Asia, Banpresto's Super Robot War is a popular series of video wargames that began on the NES way back in 1990. The series is based on Banpresto's wide range of "mecha" franchises including Gundam, Magaziner, and Eva to name the more famous ones. SRW also features Cybuster, a new mecha series created by Banpresto specificially for this series. Super Robot War 3 is the third game in the series, released on the Super Nintendo in 1993. Like all other games in this series, SRW3 features "SD" (short for "super-deformed") robots collectively known as "Divine Crusaders" as they battle to save the galaxy from the evil robots.
The game is turn-based, and plays much like a typical hex-based wargame on PC, except of course much simpler. Each turn, you move units around the tactical starmap, trying to annihilate all the enemy units (some battles have a different objective, but those are few and far between). When you issue "attack" command and the enemy units are in range, the 2D overhead view switched to a cool close-up of two mecha units in combat, much like in Gundam anime series. As someone who grew up with Gundam (aired on TV when I was a kid) and friends, these close-up combat sequences are my favorite part of the game, although I suspect anyone who is not familiar with these robots will find them merely cool ;) In between battles, you see how the story advances, and get to upgrade your robots and their weapons with funds you receive as a reward for defeating enemy robots.
Compared to a typical wargame on PC, SRW3 is very simple. However, the simplicity in my opinion is a boon in this case given the focus on storytelling - and the story in this one is as fun as the best of Gundam episode. Although the overall plot is hackneyed, the way it develops is very well handled, thanks largely to a good translation effort (for once) from the original Japanese. Gundam fans will find a lot of familiar characters who have a lot of speaking parts. Clashes between characters' motives and agenda, secret conspiracies, and surprise attacks are part of what makes SRW3 a lot of fun to play. If you like mecha, anime, or just fun "beer & pretzel" turn-based wargames in general, check out this fun game that never made it outside Japan - but can now be played in English thanks to the efforts of tireless translation group Aeon Genesis. Recommended!
People who downloaded Super Robot Wars 3 have also downloaded:
Super Dune 2, Supremacy, Subtrade: Return to Irata, SuperPower, Sudden Strike 2, Submarine TITANS, SuperPower 2, Stronghold: Crusader


This is a ladies-only, free event, but please bring along a cake or other sweet treat to share over a cup of tea or coffee. Grannies, Aunts, Sisters and younger siblings are all welcome.
Toys will be available for toddlers.
There will be a few stalls offering pampering treatments* and gifts* too, so come along and spoil yourselves!
Reception's Camp Café – tomorrow!
Don't forget it's Reception's Camp Café from 2pm tomorrow!
All cakes (shop bought, or home baked) would be appreciated. They can be dropped off in the dining room in the morning or brought along from 2pm. And don't forget to come along and buy something yummy too!
Please come along and share a coffee and chat before or after picking your children up.
Donations of cakes / biscuits to sell would be appreciated and can be brought at 2 or at the start of school and left on the side in the dining room.
Further details to follow – please see newsletter!
Hope to see as many of you as possible at the next PA meeting on either Mon 23rd or Fri 27th Jan.


The Niagara Frontier Transportation Authority announced that the Buffalo Niagara International Airport will host a new low-cost airline, with flights beginning December 5.
The new airline serves more than 55 cities in the United States, Mexico and the Dominican Republic on approximately 275 daily flights with a workforce of 3,000 employees. The airline is the recipient of the Federal Aviation Administration's 2015 Diamond Award for maintenance excellence, and they were recently named the industry's most fuel-efficient airline by The International Council on Clean Transportation.
Flights from Buffalo will include Fort Myers, Florida, Orlando, Tampa, Florida, Miami year-round and Denver, summers only.


Every page on your web site should have at least a couple of contextual links that point to other pages on your web site. These links should follow naturally from the content of your page. For example, if your page mentions PORTFOLIO, you can use those words to link to a page that is relevant to them. That's a contextual link.
To make your web site even more search engine-friendly, consider putting the menu on the right, as with this web site. This will ensure that the first thing Google sees after the <head> section is your content. This is because search engines read pages from top to bottom and from left to right. Putting the menu on the right-hand side ensures that search engines will come to it after your main content. This is related to having a high signal-to-noise ratio.
The contents tag should be identical or similar to the title tag - it has been found that Google loves this.
In the dark ages of the pre-Google anarchy the keywords meta-tag was taken very seriously by the primordial search engines. Accordingly, the SERPs were dominated by spam web sites that stuffed their meta-tags with keywords. Nowadays the keyword tag is almost irrelevant. By all means include it, but make absolutely sure that no keyword appears in the tag more than once. Do not put more than 20 words in the meta-tag.
The essence of SEO is putting high-quality content on a page, and making sure that search engines can fully read and understand the content. This means that the heart of SEO is quality text. Any text that is displayed as a JPEG file or other graphics cannot be read by the search engines. Look at the source code of a web page: that's what search engine can see. If you can't read it in the source code, search engines will not be able to read it either, and you will therefore get no search-engine credit for it.
Spiders are programs that search engines use to analyse pages on the Internet; they go from page to page, following links and reading every page, making decisions on their quality and keeping a copy in order to show them on the search results pages for relevant queries. SEO is essentially about convincing these automated programs that a given page deserves to rank highly for a specific search query.


hello to everybody *how r u doing man, r u fine.
10x ok what ab u?
hi man how r u sorry do u really sturdy in TORINO. Could u tell me please r u 1st year student or 2nd year or 3rd year. U know i sturdy in Torino as well but i havnt seen u there so far. Or have u entered to this unv. This year.


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Home International International Community Slams Trump's WHO Defunding
International Community Slams Trump's WHO Defunding
U.S. President Donald Trump (Front) addresses a news conference at the White House in Washington D.C., the United States, on March 13, 2020. (Xinhua/Liu Jie)
BEIJING (Xinhua) — The international community has regretted U.S. President Donald Trump's decision to suspend funding to the World Health Organization (WHO), voicing support for and highlighting the organization's crucial role in guiding global efforts to combat the coronavirus pandemic.
Trump announced Tuesday that his administration is halting the nation's funding to the WHO, which he accused of "severely mismanaging and covering up the spread of the coronavirus."
This triggered widespread backlash and criticism across the world on Wednesday. WHO Director-General Tedros Adhanom Ghebreyesus said the WHO regretted the U.S. decision.
"The U.S. has been a longstanding and generous friend to WHO, and we hope it will continue to be so," he told a virtual press conference from Geneva.
Tedros called on all the nations to be united in the common struggle against the common pandemic, because "when we are divided, the virus exploits the cracks between us."
Irish Deputy Prime Minister and Minister for Foreign Affairs and Trade Simon Coveney described the U.S. decision as "indefensible" and "shocking."
"This is indefensible decision in midst of global pandemic. So many vulnerable populations rely on WHO — deliberately undermining funding & trust now is shocking. Now is a time for global leadership & unity to save lives, not division and blame!" he tweeted.
Iranian Foreign Ministry spokesman Abbas Mousavi condemned the Trump administration's decision, saying "the U.S. act to punish the only coordinator of world health affairs amid the fight against a global disaster is the utmost irresponsibility and crime against humanity."
"Main aim of Trump's decision to defund WHO is blaming others and covering up the U.S. government's inefficiency in dealing with the novel coronavirus," said Mousavi.
The African Union (AU) said the U.S. decision is "deeply regrettable."
"Today more than ever the world depends on WHO's leadership to steer the global COVID-19 pandemic response," tweeted AU Commission Chairperson Moussa Faki Mahamat.
"Our collective responsibility to ensure WHO can fully carry out its mandate has never been more urgent," he added.
Noting the U.S. funding suspension is "a major setback," Finnish Foreign Minister Pekka Haavisto told Finnish news agency STT that "the work of the WHO is needed especially these days for overcoming the coronavirus."
The Finnish government pledged to increase its funding for the WHO by restoring it to the 2015 level — 5.5 million euros (6 million U.S. dollars).
"It is a decision that we regret," French government spokesperson Sibeth Ndiaye told a press conference following a cabinet meeting.
France expects "a return to normal" so that the WHO could pursue its work, she added.
German Foreign Minister Heiko Maas also slammed the U.S. decision.
"Blaming does not help. The virus knows no borders. We must cooperate closely against COVID-19," said Maas on Twitter. "One of the best investments is that the United Nations, especially the underfunded WHO, to strengthen, for example in the development and distribution of tests and vaccines."
Cuban Foreign Minister Bruno Rodriguez said on Twitter the U.S. decision is "attack vs intl community."
"It's criminal to do so amidst the pandemic. It's a selfish action intended to distract attention from inefficient response & neglect of its people. Cuba will keep working with WHO in defense of solidarity & cooperation," he tweeted.
Microsoft co-founder Bill Gates tweeted that halting funding for the WHO during a world health crisis is "as dangerous as it sounds."
"Their work is slowing the spread of COVID-19 and if that work is stopped no other organization can replace them. The world needs @WHO now more than ever," the philanthropist stressed.
The United States is the country worst hit by COVID-19, registering more than 637,000 confirmed cases and over 30,000 deaths by Wednesday, according to Johns Hopkins University tally. More than 2 million confirmed COVID-19 cases with over 136,000 deaths have been reported globally.
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The rise in allocation to MGNREGA is not 25% but just 1%, say activists
The government needs to make adequate funds available for the rural work programme, they say.
People's Action for Employment Guarantee
Feb 01, 2017 · 03:52 pm
Women NREGA
At first glance it would seem as if the Finance Minister's announcement of an allocation of Rs 48,000 crore for the Mahatma Gandhi National Rural Employment Guarantee scheme is a dramatic increase of nearly 25% over last year's allocation of Rs. 38,500 crores. In fact, the increase is a mere 1%, of Rs 500 crore, as two supplementary allocations during the course of the year made the total budget of 2016-'17, Rs 47,500 crore.
Regardless of the budget allocation, what needs to be understood is that for the MGNREGA to work as per the legislation, it needs to have adequate resources to be made available for work to be provided on demand. As of today, 22 out of 34 states have negative balances. As per the ministry's own data a total of Rs 3,469 crores in pending liabilities have already piled up, even as they have spent 93% of the funds available for this financial year. This is likely to dramatically go up over the next two months, as traditionally demand for work has peaked during this season.
The Supreme Court has issued a series of strong orders in the ongoing Swaraj Abhiyan Public Interest Litigation, one of which stated, "the Government of India is directed to release to the State Governments adequate funds under the Scheme in a timely manner so that the 'workforce' is paid its wages well in time. The Government of India must shape up in this regard."
Despite this, as per the Ministry's mechanism of preparing indicative labour budgets, even to honour only the approved budget for the months of February 2017 and March 2017, nearly Rs 10,013 crores would be required (at the average cost per person day of Rs 228). This means that we would end the year with close to Rs 13,482 crores in pending liabilities, and a budgetary allocation that has not even kept pace with last year's amount in real terms.
This unpredictable under resourced fund flow mechanism has implications for implementation, particuarly timely payment to workers, which greatly affects faith in the employment guarantee. The Supreme Court order emphatically stated that delayed wages were unacceptable and a violation of the rights of workers. Yet this continues with impunity. At present 54% of the wage payments continue to be delayed, and as a result Rs 231 crores of compensation to workers also remains due.
For casual workers suffering from the distress of demonetisation, the MGNREGA is intended to provide livelihood security net for exactly such situations. However, with pending liabilities already piling up, the situation is likely to get worse in the next two months as budget releases will only be made in April. Further, the notification for the requirement of aadhaar for accessing work under the MGNREGA from the next financial year, again in violation of repeated Supreme Court orders to not make aadhaar mandatory, is likely to have massive disruptive and exclusionary effects. The People's Action for Employment Guarantee demands that the Supreme Court orders on Aadhaar and adequate funding be followed, the notification on mandatory Aadhaar be revoked and the adequate funds be made available to the MGNREGA to truly function as a demand based programme.
Signed by Aruna Roy, Mazdoor (Kisan Shakti Sangathan), Nikhil Dey (Mazdoor Kisan Shakti Sangathan),
Shankar Singh (Mazdoor Kisan Shakti Sangathan), Annie Raja (National Federation of Indian Women),
Kamayani Swamy (Jan Jagran Shakti Sangathan), Ashish Ranjan (Jan Jagran Shakti Sangathan) for People's Action for Employment Guarantee.
MGNREGA
Budget 2017: The Election Commission has a lesson to learn from Trump's America