Tag: nevin manimala

PLoS One. 2024 Apr 3;19(4):e0301103. doi: 10.1371/journal.pone.0301103. eCollection 2024.

ABSTRACT

Birch bark tar is the most widely documented adhesive in prehistoric Europe. More recent periods attest to a diversification in terms of the materials used as adhesives and their application. Some studies have shown that conifer resins and beeswax were added to produce compound adhesives. For the Iron Age, no comparative large-scale studies have been conducted to provide a wider perspective on adhesive technologies. To address this issue, we identify adhesive substances from the Iron Age in north-eastern France. We applied organic residue analysis to 65 samples from 16 archaeological sites. This included residues adhering to ceramics, from vessel surface coatings, repaired ceramics, vessel contents, and adhesive lumps. Our findings show that, even during the Iron Age in north-eastern France, birch bark tar is one of the best-preserved adhesive substances, used for at least 400 years. To a lesser extent, Pinaceae resin and beeswax were also identified. Through statistical analyses, we show that molecular composition differs in samples, correlating with adhesive function. This has implications for our understanding of birch bark tar production, processing and mode of use during the Iron Age in France and beyond.

PMID:38568980 | DOI:10.1371/journal.pone.0301103

Proc Natl Acad Sci U S A. 2024 Apr 9;121(15):e2322083121. doi: 10.1073/pnas.2322083121. Epub 2024 Apr 3.

ABSTRACT

While reliable data-driven decision-making hinges on high-quality labeled data, the acquisition of quality labels often involves laborious human annotations or slow and expensive scientific measurements. Machine learning is becoming an appealing alternative as sophisticated predictive techniques are being used to quickly and cheaply produce large amounts of predicted labels; e.g., predicted protein structures are used to supplement experimentally derived structures, predictions of socioeconomic indicators from satellite imagery are used to supplement accurate survey data, and so on. Since predictions are imperfect and potentially biased, this practice brings into question the validity of downstream inferences. We introduce cross-prediction: a method for valid inference powered by machine learning. With a small labeled dataset and a large unlabeled dataset, cross-prediction imputes the missing labels via machine learning and applies a form of debiasing to remedy the prediction inaccuracies. The resulting inferences achieve the desired error probability and are more powerful than those that only leverage the labeled data. Closely related is the recent proposal of prediction-powered inference [A. N. Angelopoulos, S. Bates, C. Fannjiang, M. I. Jordan, T. Zrnic, Science 382, 669-674 (2023)], which assumes that a good pretrained model is already available. We show that cross-prediction is consistently more powerful than an adaptation of prediction-powered inference in which a fraction of the labeled data is split off and used to train the model. Finally, we observe that cross-prediction gives more stable conclusions than its competitors; its CIs typically have significantly lower variability.

PMID:38568975 | DOI:10.1073/pnas.2322083121

PLoS One. 2024 Apr 3;19(4):e0299993. doi: 10.1371/journal.pone.0299993. eCollection 2024.

ABSTRACT

The selection of proper reference genes is critical for accurate gene expression analysis in all fields of biological and medical research, mainly because there are many distinctions between different tissues and specimens. Given this variability, even in known classic reference genes, demands of a comprehensive analysis platform is needed to identify the most suitable genes for each study. For this purpose, we present an analysis tool for assisting in decision-making in the analysis of reverse transcription-quantitative polymerase chain reaction (RT-qPCR) data. EndoGeneAnalyzer, an open-source web tool for reference gene analysis in RT-qPCR studies, was used to compare the groups/conditions under investigation. This interactive application offers an easy-to-use interface that allows efficient exploration of datasets. Through statistical and stability analyses, EndoGeneAnalyzer assists in the select of the most appropriate reference gene or set of genes for each condition. It also allows researchers to identify and remove unwanted outliers. Moreover, EndoGeneAnalyzer provides a graphical interface to compare the evaluated groups, providing a visually informative differential analysis.

PMID:38568963 | DOI:10.1371/journal.pone.0299993

Clin Infect Dis. 2024 Apr 3:ciae183. doi: 10.1093/cid/ciae183. Online ahead of print.

ABSTRACT

BACKGROUND: One month of daily rifapentine + isoniazid (1HP) is an effective, ultrashort option for TB prevention in people with HIV (PWH). However, rifapentine may decrease antiretroviral drug concentrations and increase the risk of virologic failure. ACTG A5372 evaluated the effect of 1HP on the pharmacokinetics of twice daily dolutegravir.

METHODS: A5372 was a multicenter, pharmacokinetic study in PWH (≥18 years) already on dolutegravir-containing antiretroviral therapy with HIV RNA < 50 copies/mL. Participants received daily rifapentine/isoniazid (600mg/300mg) for 28 days as part of 1HP. Dolutegravir was increased to 50mg twice daily during 1HP and intensive pharmacokinetic sampling was performed on day 0 (before 1HP) and on the final day of 1HP treatment.

RESULTS: Thirty-two participants (41% female; 66% Black/African; median (Q1, Q3) age 42 (34, 49) years) were included in the pharmacokinetic analysis. Thirty-one of 32 had HIV RNA levels <50 copies/mL at the end of 1HP dosing. One participant had an HIV RNA of 160 copies/mL at day 28, with HIV RNA <50 copies/mL upon repeat testing on day 42. The median (Q1, Q3) dolutegravir trough concentration was 1751 ng/mL (1195, 2542) on day 0 vs. 1987ng/mL (1331, 2278) on day 28 (day 28:day 0 GMR 1.05, [90% CI 0.93-1.2]; p = 0.43). No serious adverse events were reported.

CONCLUSION: Dolutegravir trough concentrations with 50mg twice daily dosing during 1HP treatment were greater than those with standard dose dolutegravir once daily without 1HP. These pharmacokinetic, virologic, and safety data provide support for twice daily dolutegravir use in combination with 1HP for TB prevention.

PMID:38568956 | DOI:10.1093/cid/ciae183

PLoS One. 2024 Apr 3;19(4):e0295352. doi: 10.1371/journal.pone.0295352. eCollection 2024.

ABSTRACT

INTRODUCTION: The burden and impact of neck pain is high in African countries including Nigeria. This study investigated the occupational biomechanical and occupational psychosocial factors associated with neck pain intensity, neck disability and sick leave amongst construction labourers in an urban Nigerian population.

METHODS: This cross-sectional study measured clinical neck pain outcomes, occupational biomechanical factors, and occupational psychosocial factors. Descriptive, and univariate/multivariate inferential statistical analyses were conducted.

RESULTS: Significant independent factors associated with neck pain intensity were order and pace of tasks being dependent on others (β = 0.35; p<0.0001); inability to take breaks in addition to scheduled breaks (β = 0.25; p<0.0001); inability to work because of unexpected events (β = 0.21; p<0.0001); inability to control the order and pace of tasks (β = 0.20; p<0.0001); and weight of load (β = 0.17; p<0.0001); accounting for 53% of the variance in neck pain intensity. Significant independent factors associated with neck disability were weight of load (β = 0.30; p<0.0001); duration of load carriage (β = 0.16; p = 0.01); working under time pressure/deadlines (β = 0.16; p = 0.02); and accounting for 20% of the variance in neck disability. Significant independent factor associated with sick leave was duration of load carriage (β = 0.15; p = 0.04), in a non-significant regression model explaining -4% of the variance in sick leave. Addition of pain intensity significantly explained more variance in neck disability (31.0%) but less variance in sick leave (-5%), which was not statistically significant (F (10, 190) = 0.902, p = 0.533).

CONCLUSIONS: Occupational biomechanical factors may be more important than occupational psychosocial factors in explaining neck disability and sick leave. In contrast, occupational psychosocial factors may be more important than occupational biomechanical factors in explaining neck pain intensity in this population in Nigeria.

PMID:38568955 | DOI:10.1371/journal.pone.0295352

PLoS One. 2024 Apr 3;19(4):e0300194. doi: 10.1371/journal.pone.0300194. eCollection 2024.

ABSTRACT

During the COVID-19 pandemic, the scientific literature related to SARS-COV-2 has been growing dramatically. These literary items encompass a varied set of topics, ranging from vaccination to protective equipment efficacy as well as lockdown policy evaluations. As a result, the development of automatic methods that allow an in-depth exploration of this growing literature has become a relevant issue, both to identify the topical trends of COVID-related research and to zoom-in on its sub-themes. This work proposes a novel methodology, called LDA2Net, which combines topic modelling and network analysis, to investigate topics under their surface. More specifically, LDA2Net exploits the frequencies of consecutive words pairs (i.e. bigram) to build those network structures underlying the hidden topics extracted from large volumes of text by Latent Dirichlet Allocation (LDA). Results are promising and suggest that the topic model efficacy is magnified by the network-based representation. In particular, such enrichment is noticeable when it comes to displaying and exploring the topics at different levels of granularity.

PMID:38568954 | DOI:10.1371/journal.pone.0300194

Br J Sociol. 2024 Apr 3. doi: 10.1111/1468-4446.13089. Online ahead of print.

ABSTRACT

Social and spatial mobility have been subject to substantial recent sociological and policy debate. Complementing other recent work, in this paper we explore these patterns in relation to higher education. Making use of high-quality data from the higher education statistics agency (HESA), we ran a set of multilevel models to test whether the local authority areas where young people grow up influence social and spatial mobility into a higher professional or managerial job on graduation. We found entry to these patterns reflect pre-existing geographies of wealth and income, with more affluent rural and suburban areas in South-East England having higher levels of entry to these occupations. Graduates clustered from major cities tended to be spatially immobile and those from peripheral areas further away from these cities show a higher density of long-distance moves following graduation. We also explored the intersection between social and spatial mobility for graduates with the economic geography of Britain, showing that access to high-class occupations is not necessarily associated with long-distance moves across most British districts. Our evidence further suggests that the ‘London effect’, where working-class students have higher school attainment than their peers elsewhere, may not continue through to graduate employment.

PMID:38568931 | DOI:10.1111/1468-4446.13089

J Med Internet Res. 2024 Apr 3;26:e57422. doi: 10.2196/57422.

NO ABSTRACT

PMID:38568734 | DOI:10.2196/57422

J Med Internet Res. 2024 Apr 3;26:e54090. doi: 10.2196/54090.

NO ABSTRACT

PMID:38568721 | DOI:10.2196/54090

JAMA Netw Open. 2024 Apr 1;7(4):e244769. doi: 10.1001/jamanetworkopen.2024.4769.

ABSTRACT

IMPORTANCE: Elimination of tuberculosis (TB) disease in the US hinges on the ability of tests to detect individual risk of developing disease to inform prevention. The relative performance of 3 available TB tests-the tuberculin skin test (TST) and 2 interferon-γ release assays (IGRAs; QuantiFERON-TB Gold In-Tube [QFT-GIT] and SPOT.TB [TSPOT])-in predicting TB disease development in the US remains unknown.

OBJECTIVE: To compare the performance of the TST with the QFT-GIT and TSPOT IGRAs in predicting TB disease in high-risk populations.

DESIGN, SETTING, AND PARTICIPANTS: This prospective diagnostic study included participants at high risk of TB infection (TBI) or progression to TB disease at 10 US sites between 2012 and 2020. Participants of any age who had close contact with a case patient with infectious TB, were born in a country with medium or high TB incidence, had traveled recently to a high-incidence country, were living with HIV infection, or were from a population with a high local prevalence were enrolled from July 12, 2012, through May 5, 2017. Participants were assessed for 2 years after enrollment and through registry matches until the study end date (November 15, 2020). Data analysis was performed in June 2023.

EXPOSURES: At enrollment, participants were concurrently tested with 2 IGRAs (QFT-GIT from Qiagen and TSPOT from Oxford Immunotec) and the TST. Participants were classified as case patients with incident TB disease when diagnosed more than 30 days from enrollment.

MAIN OUTCOMES AND MEASURES: Estimated positive predictive value (PPV) ratios from generalized estimating equation models were used to compare test performance in predicting incident TB. Incremental changes in PPV were estimated to determine whether predictive performance significantly improved with the addition of a second test. Case patients with prevalent TB were examined in sensitivity analysis.

RESULTS: A total of 22 020 eligible participants were included in this study. Their median age was 32 (range, 0-102) years, more than half (51.2%) were male, and the median follow-up was 6.4 (range, 0.2-8.3) years. Most participants (82.0%) were born outside the US, and 9.6% were close contacts. Tuberculosis disease was identified in 129 case patients (0.6%): 42 (0.2%) had incident TB and 87 (0.4%) had prevalent TB. The TSPOT and QFT-GIT assays performed significantly better than the TST (PPV ratio, 1.65 [95% CI, 1.35-2.02] and 1.47 [95% CI, 1.22-1.77], respectively). The incremental gain in PPV, given a positive TST result, was statistically significant for positive QFT-GIT and TSPOT results (1.64 [95% CI, 1.40-1.93] and 1.94 [95% CI, 1.65-2.27], respectively).

CONCLUSIONS AND RELEVANCE: In this diagnostic study assessing predictive value, IGRAs demonstrated superior performance for predicting incident TB compared with the TST. Interferon-γ release assays provided a statistically significant incremental improvement in PPV when a positive TST result was known. These findings suggest that IGRA performance may enhance decisions to treat TBI and prevent TB.

PMID:38568690 | DOI:10.1001/jamanetworkopen.2024.4769