Weakest-link methods and applications for detecting joint effects in biology

The joint effect of several variables is a prevailing statistical concept in biology. The public health importance of developing methods to better assess joint effects is evident when studying gene combinations that function together to produce a disease phenotype, or biomarker pairs that jointly affect prognosis or treatment response. The "weakest-link" paradigm, introduced earlier by Richards and Day, constructs derived covariates accounting for the joint effect of multiple variables. The weakest-link method posits a one-dimensional locus in covariate space, called the curve of optimal use (COU). For a data set with two predictors and an associated outcome, the COU separates the two-dimensional covariate space into two subsets. The subset of an observation determines its weakest-link covariate, which alone locally affects the corresponding outcome. With a modest generalization, one can extend weakest-link methods to assess interactions between more than two variables.Current methods for detecting interesting variable combinations have shortcomings. Some methods, such as logic regression, require dichotomization, and lose information. Other methods such as support vector machines, are too computationally intensive, especially with large data sets. With these issues in mind, the primary objectives in expanding the practical applications of weakest-link methodology are: (1) to develop a semi-parametric method to screen hundreds or thousands of variables for combinations associated with an outcome, (2) to adapt the method for a more complicated data structure found in a multi-parameter cell-based cytometry study, where data sets typically consist of thousands of cell observations per outcome. In a high-throughput microarray data set of breast cancer patients, conventional additive linear models and weakest-link models identified multiple combinations of biomarkers associated with lymph node positivity. Simulations of high-throughput data sets found that weakest-link models had better success than additive models in detecting covariate pairs used to generate outcomes; weakest-link models were preferable even in some situations when the additive model was the true outcome-generating model.The weakest-link approach showed promising results in modeling recurrence-free survival in a cytometry data set of lung cancer samples. Weakest-link models, compared to logic regression and linear regression, provided the best results according to cross-validation assessments

Fed-LSAE: Thwarting Poisoning Attacks against Federated Cyber Threat Detection System via Autoencoder-based Latent Space Inspection

The significant rise of security concerns in conventional centralized learning has promoted federated learning (FL) adoption in building intelligent applications without privacy breaches. In cybersecurity, the sensitive data along with the contextual information and high-quality labeling in each enterprise organization play an essential role in constructing high-performance machine learning (ML) models for detecting cyber threats. Nonetheless, the risks coming from poisoning internal adversaries against FL systems have raised discussions about designing robust anti-poisoning frameworks. Whereas defensive mechanisms in the past were based on outlier detection, recent approaches tend to be more concerned with latent space representation. In this paper, we investigate a novel robust aggregation method for FL, namely Fed-LSAE, which takes advantage of latent space representation via the penultimate layer and Autoencoder to exclude malicious clients from the training process. The experimental results on the CIC-ToN-IoT and N-BaIoT datasets confirm the feasibility of our defensive mechanism against cutting-edge poisoning attacks for developing a robust FL-based threat detector in the context of IoT. More specifically, the FL evaluation witnesses an upward trend of approximately 98% across all metrics when integrating with our Fed-LSAE defense

Radicular cyst in a primary molar following pulp therapy with gutta percha : a case report and literature review

A radicular cyst (RC) in deciduous dentition is relatively rare. This clinical report presents a case of RC that condition derived from a primary molar undergone an endodontic treatment with gutta-percha approximately one year ago. In addition, we also considered whether intracanal medicaments and gutta-percha filling material related to the formation and development of the cyst or not

Short Tandem Repeats Used in Preimplantation Genetic Testing of Î’-Thalassemia: Genetic Polymorphisms For 15 Linked Loci in the Vietnamese Population

BACKGROUND: β-thalassemia is one of the most common monogenic diseases worldwide. Preimplantation genetic testing (PGT) of β-thalassemia is performed to avoid affected pregnancies has become increasingly popular worldwide. In which, the indirect analysis using short tandem repeat (STRs) linking with HBB gene to detect different β-globin (HBB) gene mutation is a simple, accurate, economical and also provides additional control of contamination and allele-drop-out ADO. AIM: This study established microsatellite markers for PGT of Vietnamese β-thalassemia patient. METHODS: Fifteen (15) STRs gathered from 5 populations were identified by in silico tools within 1 Mb flanking the HBB gene. The multiplex PCR reaction was optimized and performed on 106 DNA samples from at-risk families. RESULTS: After estimating, PIC values were ≥ 0.7 for all markers, with expected heterozygosity and observed heterozygosity values ranged from 0.81 to 0.92 and 0.53 to 0.86, respectively. One hundred percent of individuals had at least seven heterozygous markers and were found to be heterozygous for at least two markers on either side of the HBB gene. The STRs panel was successfully performed on one at-risk family. CONCLUSION: In general, a pentadecaplex marker (all < 1 Mb from the HBB gene) assay was constituted for β-thalassemia PGT on Vietnamese population

Smoke-free environment policy in Vietnam: What did people see and how did they react when they visited various public places?

Introduction: Since Vietnam has signed WHO framework on tobacco control (FCTC) in 2003 and has issued tobacco control law in 2013, there has been little research concerning about what impacts smoke-free regulations have had on public compliance. The objective of this study was to assess public exposure to secondhand smoke and reaction toward smoke-free policy regulations in Vietnam and the associated factor. Methods: Using the design of GATS (Global Adult Tobacco Survey), a nationally representative sample of 8,996 adults were approached for data collection. Logistic regression was used to examine the associated factor.Results: The study revealed that the prevalence of respondents exposed to secondhand smoke was much higher in bars/café/tea shops (90.07%) and restaurants (81.81%) than in any other public places, universities (36.70%), government buildings (31.12%), public transport (20.04%), healthcare facilities (17.85%) and schools (15.84%). 13.23% of respondents saw smokers violate smoke-free regulations. Among those who saw them violate smoke-free regulations, just one-third cautioned them to stop smoking. Strikingly, a higher rate of cautioning smokers to stop smoking was observed among the older, married, and better educated respondents. Respondents who were married, better educated and in lower economic status were more likely to remind smokers to stop smoking.Conclusions: The study has called for strengthening two of the six MPOWER (Monitor, Protect, Offer, Warn, Enforce and Raise) components of the tobacco free initiative introduced by WHO, Monitoring tobacco use and prevention policies and Protecting people from tobacco smoke

Awareness and preparedness of healthcare workers against the first wave of the COVID-19 pandemic: A cross-sectional survey across 57 countries.

BACKGROUND: Since the COVID-19 pandemic began, there have been concerns related to the preparedness of healthcare workers (HCWs). This study aimed to describe the level of awareness and preparedness of hospital HCWs at the time of the first wave. METHODS: This multinational, multicenter, cross-sectional survey was conducted among hospital HCWs from February to May 2020. We used a hierarchical logistic regression multivariate analysis to adjust the influence of variables based on awareness and preparedness. We then used association rule mining to identify relationships between HCW confidence in handling suspected COVID-19 patients and prior COVID-19 case-management training. RESULTS: We surveyed 24,653 HCWs from 371 hospitals across 57 countries and received 17,302 responses from 70.2% HCWs overall. The median COVID-19 preparedness score was 11.0 (interquartile range [IQR] = 6.0-14.0) and the median awareness score was 29.6 (IQR = 26.6-32.6). HCWs at COVID-19 designated facilities with previous outbreak experience, or HCWs who were trained for dealing with the SARS-CoV-2 outbreak, had significantly higher levels of preparedness and awareness (p<0.001). Association rule mining suggests that nurses and doctors who had a 'great-extent-of-confidence' in handling suspected COVID-19 patients had participated in COVID-19 training courses. Male participants (mean difference = 0.34; 95% CI = 0.22, 0.46; p<0.001) and nurses (mean difference = 0.67; 95% CI = 0.53, 0.81; p<0.001) had higher preparedness scores compared to women participants and doctors. INTERPRETATION: There was an unsurprising high level of awareness and preparedness among HCWs who participated in COVID-19 training courses. However, disparity existed along the lines of gender and type of HCW. It is unknown whether the difference in COVID-19 preparedness that we detected early in the pandemic may have translated into disproportionate SARS-CoV-2 burden of disease by gender or HCW type

A modified Sequential Organ Failure Assessment score for dengue: development, evaluation and proposal for use in clinical trials

Background Dengue is a neglected tropical disease, for which no therapeutic agents have shown clinical efficacy to date. Clinical trials have used strikingly variable clinical endpoints, which hampers reproducibility and comparability of findings. We investigated a delta modified Sequential Organ Failure Assessment (delta mSOFA) score as a uniform composite clinical endpoint for use in clinical trials investigating therapeutics for moderate and severe dengue. Methods We developed a modified SOFA score for dengue, measured and evaluated its performance at baseline and 48 h after enrolment in a prospective observational cohort of 124 adults admitted to a tertiary referral hospital in Vietnam with dengue shock. The modified SOFA score included pulse pressure in the cardiovascular component. Binary logistic regression, cox proportional hazard and linear regression models were used to estimate association between mSOFA, delta mSOFA and clinical outcomes. Results The analysis included 124 adults with dengue shock. 29 (23.4%) patients required ICU admission for organ support or due to persistent haemodynamic instability: 9/124 (7.3%) required mechanical ventilation, 8/124 (6.5%) required vasopressors, 6/124 (4.8%) required haemofiltration and 5/124 (4.0%) patients died. In univariate analyses, higher baseline and delta (48 h) mSOFA score for dengue were associated with admission to ICU, requirement for organ support and mortality, duration of ICU and hospital admission and IV fluid use. Conclusions The baseline and delta mSOFA scores for dengue performed well to discriminate patients with dengue shock by clinical outcomes, including duration of ICU and hospital admission, requirement for organ support and death. We plan to use delta mSOFA as the primary endpoint in an upcoming host-directed therapeutic trial and investigate the performance of this score in other phenotypes of severe dengue in adults and children