Summary Of Data Research Articles

Critical assessment of G0W0 calculations for 2D materials: the example of monolayer MoS2

Two-dimensional (2D) materials combine many fascinating properties that make them more interesting than their three-dimensional counterparts for a variety of applications. For example, 2D materials exhibit stronger electron-phonon and electron-hole interactions, and their energy gaps and effective carrier masses can be easily tuned. Surprisingly, published band gaps of several 2D materials obtained with the GW approach, the state-of-the-art in electronic-structure calculations, are quite scattered. The details of these calculations, such as the underlying geometry, the starting point, the inclusion of spin-orbit coupling, and the treatment of the Coulomb potential can critically determine how accurate the results are. Taking monolayer MoS2 as a representative material, we employ the linearized augmented planewave + local orbital method to systematically investigate how all these aspects affect the quality of G0W0 calculations, and also provide a summary of literature data. We conclude that the best overall agreement with experiments and coupled-cluster calculations is found for G0W0 results with HSE06 as a starting point including spin-orbit coupling, a truncated Coulomb potential, and an analytical treatment of the singularity at q = 0.

Effects of Testosterone in Mediating the Relationship Between Daytime Napping and Osteoporosis in European Populations: A Mendelian Randomization Study.

We aimed to explore the causal effect of daytime napping on the risk of osteoporosis and the mediation role of testosterone in explaining this relationship. Summary data for Mendelian randomization (MR) analysis were obtained from the IEU OpenGWAS database. Univariable MR(UVMR) analysis and multiple sensitivity analyses were applied to explore the casual relationship between daytime napping and bone mineral density (BMD)/osteoporosis. We also conducted multivariable Mendelian randomization (MVMR) analysis to evaluate the correlation between testosterone-associated single-nucleotide variations and BMD/osteoporosis. Then, mediation analysis was performed to explore whether the association between daytime napping and BMD/osteoporosis was mediated via testosterone. Genetically predicted daytime napping was significantly associated with femoral neck BMD (β [95% CI]: 0.2573 [0.0487, 0.4660];P = 0.0156), lumbar spine BMD (β [95% CI]: 0.2526 [0.0211, 0.4840];P = 0.0324), and osteoporosis (OR [95% CI]: 0.5063 [0.2578, 0.9942];P = 0.0481). β and 95%CIs indicate the standard deviation (SD) unit of BMD increase per category increase in daytime napping. OR and 95%CIs represent the change in the odds ratio of osteoporosis per category increase in daytime napping. We observed a potentially causal effect of more frequent daytime nappingon higher BMD and a lower risk of osteoporosis. Daytime napping was causally associated with a higher level of bioavailable testosterone (β [95% CI]: 0.1397 [0.0619, 0.2175]; P = 0.0004). β and 95%CIs represent the change in the SD of testosterone per category increase in daytime napping. Furthermore, the causal effects of daytime napping on BMD/osteoporosis were partly mediated by bioavailable testosterone. Daytime napping can efficiently increase BMD and reduce the risk of osteoporosis, and testosterone plays a key mediating role in this process.

Noteworthy in Cardiothoracic Surgery 2023.

Noteworthy in Cardiothoracic Surgery 2023 summarizes a few of the most high-impact trials and provocative trends in cardiothoracic surgery and transplantation this past year. Transplantation using organs procured from donation after circulatory death (DCD) continues to increase, and the American Society of Transplant Surgeons released recommendations on best practices in 2023. We review a summary of data on the impact of DCD on heart and lung transplantation. There has been increased interest in extracorporeal life support (ECLS), particularly after the COVID-19 pandemic, and we review the results of the highly discussed ECLS-SHOCK trial, which randomized patients in cardiogenic shock with planned revascularization to ECLS vs usual care. With improving survival outcomes in complex aortic surgery, there is a need for higher-quality evidence to guide which cooling and cerebral perfusion strategies may optimize cognitive outcomes in these patients. We review the short-term outcomes of the GOT ICE trial (Cognitive Effects of Body Temperature During Hypothermic Circulatory Arrest), a multicenter, randomized controlled trial of three different nadir temperatures, evaluating outcomes in cognition and associated changes in functional magnetic resonance imaging. Finally, both the Society of Thoracic Surgeons (STS) and the American College of Cardiology, American Heart Association, American College of Chest Physicians and Heart Rhythm Society (ACC/AHA/ACCP/HRS) updated atrial fibrillation guidelines in 2023, and we review surgically relevant updates to the guidelines and the evidence behind them.

Assessing causal relationships between gut microbiota and psoriasis: evidence from two sample Mendelian randomization analysis

Mounting data hints that the gut microbiota's role may be pivotal in understanding the emergence of psoriasis. However, discerning a direct causal link is yet elusive. In this exploration, we adopted a Mendelian randomization (MR) strategy to probe the prospective causal interplay between the gut's microbial landscape and the predisposition to psoriasis. Genetic markers acting as instrumental variables for gut microbiota were extrapolated from a genome-wide association study (GWAS) encompassing 18,340 individuals. A separate GWAS yielded summary data for psoriasis, which covered 337,159 patients and 433,201 control subjects. The primary analysis hinged on inverse variance weighting (IVW). Additional methods like the weighted median approach and MR-Egger regression were employed to validate the integrity of our findings. Intriguing correlations emerged between psoriasis risk and eight specific bacterial traits. To illustrate: Mollicutes presented an odds ratio (OR) of 1.003 with a 95% confidence interval (CI) spanning 1.001–1.005 (p = 0.016), while the family. Victivallaceae revealed an OR of 0.998 with CI values between 0.997 and 0.999 (p = 0.023). Eubacterium (coprostanoligenes group) revealed an OR of 0.997 with CI values between 0.994 and 0.999 (p = 0.027). Eubacterium (fissicatena group) revealed an OR of 0.997 with CI values between 0.996 and 0.999 (p = 0.005). Holdemania revealed an OR of 1.001 with CI values 1–1.003 (p = 0.034). Lachnospiraceae (NK4A136 group) revealed an OR of 0.997 with CI values between 0.995 and 0.999 (p = 0.046). Lactococcus revealed an OR of 0.998 with CI values between 0.996 and 0.999 (p = 0.008). Tenericutes revealed an OR of 1.003 with CI values between 1.001 and 1.006 (p = 0.016). Sensitivity analysis for these bacterial features yielded congruent outcomes, reinforcing statistically significant ties between the eight bacterial entities and psoriasis. This comprehensive probe underscores emerging evidence pointing towards a plausible causal nexus between diverse gut microbiota and the onset of psoriasis. It beckons further research to unravel the intricacies of how the gut's microbial constituents might sway psoriasis's pathogenesis.

Impact of clinically relevant posthepatectomy liver failure predicted by preoperative evaluation of functional remnant hepatic reserve

Abstract Background: Few studies have investigated the remnant hepatic functional reserve before hepatectomy by calculating the functional remnant liver rate (RLR) using threedimensional computed tomography (3D-CT)/technetium-99m-diethylenetriaminepentaacetic acid galactosyl human serum albumin (99mTc-GSA) single-photon emission CT (SPECT) fusion imaging. We aimed to preoperatively evaluate the predictive value of functional remnant liver rate (RLR) and indocyanine green (ICG) disappearance rate (KICG) in determining the occurrence of posthepatectomy liver failure (PHLF). Summary of Background Data: The conventional method of volumetric rem-KICG calculated from remnant liver volume and the KICG is difficult to accurately reflect heterogenous remnant liver function. Methods: In total, 106 patients who underwent major hepatectomy were retrospectively analysed. Of these, 24 (22.6%) developed clinically relevant PHLF grades B/C. We examined the ICG retention rate at 15 min (ICGR15) and KICG and constructed a 3DCT/ 99mTc-GSA SPECT fusion image to calculate the volumetric RLR, functional RLR, volumetric rem-KICG, and functional rem-KICG. Results: The multivariate analysis showed functional rem-KICG as the strongest independent risk factor for PHLF grade B/C. The functional-to-volumetric RLR ratios in the patients with portal vein obstruction and/or tumor volume of ≥500 mL was significantly higher. The volumetric rem-KICG determined that hepatectomy was unsafe in 7 patients, whereas the functional rem-KICG determined that it was unsafe in 3 patients. Conclusions: Functional rem-KICG was more reliable than volumetric rem-KICG in predicting clinically relevant PHLF grade B/C, as the resected side’s hepatic status highly influenced the function of the remnant liver. This finding could lead to a wider application of this technique.

To analyze the relationship between gut microbiota, metabolites and migraine: a two-sample Mendelian randomization study.

It has been suggested in several observational studies that migraines are associated with the gut microbiota. It remains unclear, however, how the gut microbiota and migraines are causally related. We performed a bidirectional two-sample mendelian randomization study. Genome-wide association study (GWAS) summary statistics for the gut microbiota were obtained from the MiBioGen consortium (n = 18,340) and the Dutch Microbiota Project (n = 7,738). Pooled GWAS data for plasma metabolites were obtained from four different human metabolomics studies. GWAS summary data for migraine (cases = 48,975; controls = 450,381) were sourced from the International Headache Genetics Consortium. We used inverse-variance weighting as the primary analysis. Multiple sensitivity analyses were performed to ensure the robustness of the estimated results. We also conducted reverse mendelian randomization when a causal relationship between exposure and migraine was found. LachnospiraceaeUCG001 (OR = 1.12, 95% CI: 1.05-1.20) was a risk factor for migraine. Blautia (OR = 0.93, 95% CI: 0.88-0.99), Eubacterium (nodatum group; OR = 0.94, 95% CI: 0.90-0.98), and Bacteroides fragilis (OR = 0.97, 95% CI: 0.94-1.00) may have a suggestive association with a lower migraine risk. Functional pathways of methionine synthesis (OR = 0.89, 95% CI: 0.83-0.95) associated with microbiota abundance and plasma hydrocinnamate (OR = 0.85, 95% CI: 0.73-1.00), which are downstream metabolites of Blautia and Bacteroides fragilis, respectively, may also be associated with lower migraine risk. No causal association between migraine and the gut microbiota or metabolites was found in reverse mendelian randomization analysis. Both significant horizontal pleiotropy and significant heterogeneity were not clearly identified. This Mendelian randomization analysis showed that LachnospiraceaeUCG001 was associated with an increased risk of migraine, while some bacteria in the gut microbiota may reduce migraine risk. These findings provide a reference for a deeper comprehension of the role of the gut-brain axis in migraine as well as possible targets for treatment interventions.

The causal relationship of human blood metabolites with the components of Sarcopenia: a two-sample Mendelian randomization analysis

BackgroundSarcopenia is a progressive loss of muscle mass and function. Since skeletal muscle plays a critical role in metabolic homeostasis, identifying the relationship of blood metabolites with sarcopenia components would help understand the etiology of sarcopenia.MethodsA two-sample Mendelian randomization study was conducted to examine the causal relationship of blood metabolites with the components of sarcopenia. Summary genetic association data for 309 known metabolites were obtained from the Twins UK cohort and KORA F4 study (7824 participants). The summary statistics for sarcopenia components [hand grip strength (HGS), walking pace (WP), and appendicular lean mass (ALM)] were obtained from the IEU Open GWAS project (461,089 participants). The inverse variance weighted method was used, and the MR-Egger, weighted median, and MR-PRESSO were used for the sensitivity analyses. Metabolic pathways analysis was further performed.ResultsFifty-four metabolites associated with sarcopenia components were selected from 275 known metabolites pool. Metabolites that are causally linked to the sarcopenia components were mainly enriched in amino sugar and nucleotide sugar metabolism, galactose metabolism, fructose and mannose metabolism, carnitine synthesis, and biotin metabolism. The associations of pentadecanoate (15:0) with ALM, and 3-dehydrocarnitine and isovalerylcarnitine with HGS were significant after Bonferroni correction with a threshold of P < 1.82 × 10− 4 (0.05/275). Meanwhile, the association of hyodeoxycholate and glycine with the right HGS, and androsterone sulfate with ALM were significant in the sensitivity analyses.ConclusionBlood metabolites from different metabolism pathways were causally related to the components of sarcopenia. These findings might benefit the understanding of the biological mechanisms of sarcopenia and targeted drugs development for muscle health.

The safety, quality evaluation, and lot release of COVID-19 vaccines imported and used in Nigeria from march 2021 to march 2022

Coronavirus disease (COVID-19) caused by the Severe Acute Respiratory Syndrome Corona 2 Virus (SARS-COV-2 Virus) was a major global health crisis that resulted in severe illness and death around the globe. The swift development of effective vaccines against the disease to mitigate severe illness and death was one of the greatest public health scientific achievements. Most of these vaccines required cold storage and were exported to many developing countries with resource limitations to verify the quality of these products. The National Agency for Food and Drug Administration and Control (NAFDAC) regulates the quality of vaccines imported into Nigeria. This study provides summaries of data collected and QC measures conducted on all the COVID-19 vaccines imported into Nigeria within 2021–2022. Cold-chain parameters and other data requirements for meeting international standards for assessing the quality of vaccines were conducted in ISO17025-accredited laboratories of the Nigerian FDA. QC tests used to assess the safety of the products included tests for sterility, bacterial endotoxin, abnormal toxicity, pH, Physical appearance, extractable volumes, protein tests, and DNA: protein ratios. The products yielded satisfactory compliance, however, there were unsatisfactory sterility and protein test results for two batches of the samples tested. There are additional non-QC regulatory measures employed by NAFDAC to ensure the safety of the COVID-19 vaccines, including supply chain management. Out of ninety-five batches of different COVID-19 vaccines evaluated, 95.5% passed sterility testing. There is a 100% pass of all the vaccines for the Bacteria Endotoxin Test while an 80% pass was observed for the protein content.

Statistical techniques to assess publication integrity in groups of randomized trials: a narrative review

ObjectivesTo describe statistical tools available for assessing publication integrity of groups of randomized controlled trials (RCTs). Study Design and SettingNarrative review. ResultsFreely available statistical tools have been developed that compare the observed distributions of baseline variables with the expected distributions that would occur if successful randomization occurred. For continuous variables, the tools assess baseline means, baseline P values, and the occurrence of identical means and/or standard deviation. For categorical variables, they assess baseline P values, frequency counts for individual or all variables, numbers of trial participants randomized or withdrawing, and compare reported with independently calculated P values. The tools have been used to identify publication integrity concerns in RCTs from individual groups, and performed at an acceptable level in discriminating intentionally fabricated baseline summary data from genuine RCTs. The tools can be used when concerns have been raised about RCT(s) from an individual/group and when the whole body of their work is being examined, when conducting systematic reviews, and could be adapted to aid screening of RCTs at journal submission. ConclusionStatistical tools are useful for the assessment of publication integrity of groups of RCTs.

Mendelian randomization and transcriptome analysis identified immune-related biomarkers for osteoarthritis.

The immune microenvironment assumes a significant role in the pathogenesis of osteoarthritis (OA). However, the current biomarkers for the diagnosis and treatment of OA are not satisfactory. Our study aims to identify new OA immune-related biomarkers to direct the prevention and treatment of OA using multi-omics data. The discovery dataset integrated the GSE89408 and GSE143514 datasets to identify biomarkers that were significantly associated with the OA immune microenvironment through multiple machine learning methods and weighted gene co-expression network analysis (WGCNA). The identified signature genes were confirmed using two independent validation datasets. We also performed a two-sample mendelian randomization (MR) study to generate causal relationships between biomarkers and OA using OA genome-wide association study (GWAS) summary data (cases n = 24,955, controls n = 378,169). Inverse-variance weighting (IVW) method was used as the main method of causal estimates. Sensitivity analyses were performed to assess the robustness and reliability of the IVW results. Three signature genes (FCER1G, HLA-DMB, and HHLA-DPA1) associated with the OA immune microenvironment were identified as having good diagnostic performances, which can be used as biomarkers. MR results showed increased levels of FCER1G (OR = 1.118, 95% CI 1.031-1.212, P = 0.041), HLA-DMB (OR = 1.057, 95% CI 1.045 -1.069, P = 1.11E-21) and HLA-DPA1 (OR = 1.030, 95% CI 1.005-1.056, P = 0.017) were causally and positively associated with the risk of developing OA. The present study identified the 3 potential immune-related biomarkers for OA, providing new perspectives for the prevention and treatment of OA. The MR study provides genetic support for the causal effects of the 3 biomarkers with OA and may provide new insights into the molecular mechanisms leading to the development of OA.

Causal association between rheumatoid arthritis and an increased risk of age-related macular degeneration: A Mendelian randomization study.

This study's goal is to evaluate if there is a causal connection between rheumatoid arthritis (RA) and age-related macular degeneration (AMD), despite past epidemiological studies suggesting an association between the 2 disorders. The impact of RA on AMD is still unknown. Mendelian randomization (MR) was utilized in this study to assess the two-sample causal relationship between RA and AMD. Summary data from GWAS for RA and AMD in individuals with all European ancestries were gathered using the IEU GWAS database. The GWAS summary statistics of RA (14,361 RA patients and 43,923 healthy controls) and AMD (14,034 AMD patients and 91,214 controls participated) were obtained from the IEU GWAS database. After identifying suitable instrumental variables in line with the 3 MR assumptions, we conducted MR using the Mendelian randomization-Egger (MR-Egger), weighted median, and inverse variance weighting techniques. The MR-Egger intercept and MR-Polyvalent Residuals and Outliers methods were used to investigate the effects of horizontal pleiotropy. The leave-one-out strategy was used to prevent bias caused by certain single nucleotide polymorphisms. Sensitivity analysis was used to detect the heterogeneity. Using 50 single nucleotide polymorphisms as instrumental variables, this study examined the relationship between RA and AMD and discovered that RA increased the risk of AMD (inverse variance weighting odds ratio [OR] = 1.056, 95% confidence interval [CI] = 1.02-1.09, P = 5.44E-04; weighted median OR = 1.085, 95% CI = 1.04-1.14, P = 4.05E-04; MR-Egger OR = 1.074, 95% CI = 1.01-1.14, P = 2.18E-2). The current investigation demonstrated a causal link between AMD and RA. RA increased the risk of AMD. It is advised that future research concentrate on the processes underlying the relationship between RA and AMD.

Causal influence of celiac disease on the risk of sarcoidosis: A Mendelian randomization study.

Observational research shows a link between celiac disease (CeD) and sarcoidosis, but the causal link between CeD and sarcoidosis is still unknown. A two-sample Mendelian randomization (MR) study was conducted to ascertain the causal connection between the 2 disorders. In our two-sample MR analysis, we identified independent genetic variants associated with CeD using publicly accessible GWAS data from people of European ancestry. Summary data for sarcoidosis were obtained from the FinnGen Consortium, the UK-Biobank, and a large GWAS dataset. To assess the association between CeD and sarcoidosis, our MR analysis used inverse variance weighted (IVW) as the primary method, incorporating the MR-Egger, weighted median (WM), and MR-PRESSO (outliers test) as a complementary method. In order to ensure that the findings were reliable, several sensitivity analyses were performed. Our study indicated that CeD had a significant causal relationship with sarcoidosis (IVW odds ratio (OR) = 1.13, 95% confidence interval (CI): 1.07-1.20, P = 5.58E-05; WM OR = 1.12, 95% CI: 1.03-1.23, P = 1.03E-02; MR-Egger OR = 1.07, 95% CI: 0.96-1.19, P = 2.20E-01). Additionally, we obtain the same results in the duplicated datasets as well, which makes our results even more reliable. The results of this investigation did not reveal any evidence of horizontal pleiotropy or heterogeneity. Our MR analysis showed a causal effect between CeD and an elevated risk of sarcoidosis. Further study is still needed to confirm the findings and look into the processes underlying these relationships.

Type 1 diabetes mellitus and non-alcoholic fatty liver disease: a two-sample Mendelian randomization study.

NAFLD (Nonalcoholic fatty liver disease) is becoming an increasingly common cause of chronic liver disease. Metabolic dysfunction, overweight/obesity, and diabetes are thought to be closely associated with increased NAFLD risk. However, few studies have focused on the mechanisms of NAFLD occurrence in T1DM. We conducted a two-sample Mendelian randomization (MR) analysis to assess the causal association between T1DM and NAFLD with/without complications, such as coma, renal complications, ketoacidosis, neurological complications, and ophthalmic complications. Multiple Mendelian randomization methods, such as the inverse variance weighted (IVW) method, weighted median method, and MR-Egger test were performed to evaluate the causal association of T1DM and NAFLD using genome-wide association study summary data from different consortia, such as Finngen and UK biobank. We selected 37 SNPs strongly associated with NAFLD/LFC (at a significance level of p < 5 × 10-8) as instrumental variables from the Finnish database based on the T1DM phenotype (8,967 cases and 308,373 controls). We also selected 14/16 SNPs based on with or without complications. The results suggest that the genetic susceptibility of T1DM does not increase the risk of NAFLD (OR=1.005 [0.99, 1.02], IVW p=0.516, MR Egger p=0.344, Weighted median p=0.959, Weighted mode p=0.791), regardless of whether complications are present. A slight causal effect of T1DM without complications on LFC was observed (OR=1.025 [1.00, 1.03], MR Egger p=0.045). However, none of the causal relationships were significant in the IVW (p=0.317), Weighted median (p=0.076), and Weighted mode (p=0.163) methods. Our study did not find conclusive evidence for a causal association between T1DM and NAFLD, although clinical observations indicate increasing abnormal transaminase prevalence and NAFLD progression in T1DM patients.

The genetic association between hyperthyroidism and heart failure: a Mendelian randomization study.

Hyperthyroidism is an endocrine disease with multiple etiologies and manifestations. Heart failure (HF) is a common, costly, and deadly medical condition in clinical practice. Numerous studies have suggested that abnormal thyroid function can induce or aggravate the development of heart disease. However, no study has demonstrated a causal relationship between hyperthyroidism and heart failure. Therefore, the purpose of this study was to explore the causal link between hyperthyroidism and HF. Summary data for genetically predicted hyperthyroidism were obtained from a genetic association study. The data examined for genetically determined all-cause heart failure came from 218,208 individuals from the FinnGen Consortium. Two-sample Mendelian randomization (MR) analysis was used to estimate the causal link between hyperthyroidism and heart failure. Statistical analyses were conducted using the inverse variance-weighted, weighted median, simple median, weighted mode, MR-PRESSO (number of distribution = 5000), MR-Egger, and leave-one-out. The results of the inverse-variance weighted analysis indicated a causal association between hyperthyroidism and an increased risk of all-cause heart failure (IVW: β=0.048, OR=1.049, 95%CI: [1.013 to 1.087], P=0.007). Similarly, the weighted median approach demonstrated a positive correlation between hyperthyroidism and all-cause heart failure (OR=1.049, [95% CI, 1.001-1.100]; P=0.044). Additionally, no horizontal pleiotropy or heterogeneity was observed. The leave-one-out analysis revealed that the majority of the SNP-driven associations were not influenced by a single genetic marker. Our study observed a causal relationship between hyperthyroidism and all-cause heart failure. Hyperthyroidism may associate with heart failure genetically.

Control of false discoveries in grouped hypothesis testing for eQTL data

BackgroundExpression quantitative trait locus (eQTL) analysis aims to detect the genetic variants that influence the expression of one or more genes. Gene-level eQTL testing forms a natural grouped-hypothesis testing strategy with clear biological importance. Methods to control family-wise error rate or false discovery rate for group testing have been proposed earlier, but may not be powerful or easily apply to eQTL data, for which certain structured alternatives may be defensible and may enable the researcher to avoid overly conservative approaches.ResultsIn an empirical Bayesian setting, we propose a new method to control the false discovery rate (FDR) for grouped hypotheses. Here, each gene forms a group, with SNPs annotated to the gene corresponding to individual hypotheses. The heterogeneity of effect sizes in different groups is considered by the introduction of a random effects component. Our method, entitled Random Effects model and testing procedure for Group-level FDR control (REG-FDR), assumes a model for alternative hypotheses for the eQTL data and controls the FDR by adaptive thresholding. As a convenient alternate approach, we also propose Z-REG-FDR, an approximate version of REG-FDR, that uses only Z-statistics of association between genotype and expression for each gene-SNP pair. The performance of Z-REG-FDR is evaluated using both simulated and real data. Simulations demonstrate that Z-REG-FDR performs similarly to REG-FDR, but with much improved computational speed.ConclusionOur results demonstrate that the Z-REG-FDR method performs favorably compared to other methods in terms of statistical power and control of FDR. It can be of great practical use for grouped hypothesis testing for eQTL analysis or similar problems in statistical genomics due to its fast computation and ability to be fit using only summary data.

Beyond Extractive Methods – Navigating the landscape of Abstractive Summarization Methods

Today, millions of data are generated every hour, which highlights the need for summarizing all this data accurately and efficiently. Doing such a task manually is tedious. This welcomes the need for automatic summarizing techniques. Generating precise and concise summaries of long text data is a necessity. Automatic summarization includes two primary techniques- Extractive and Abstractive Summarization. Extractive Summarization uses important sentences and keywords to construct the summary whereas abstractive summarization understands the text and generates a summary. The encoder-decoder architecture is generally used for abstractive summarization. This study briefs about various transformer architectures, including T5, BART, and Pegasus. Furthermore, a comparative analysis of these models on the same data is presented and the result of the same is compared on scores with the manually generated summaries- ROUGE1, ROUGE2, and ROUGEL. The purpose of this study is to understand the advancement of abstractive text summarization models as well as to understand the strategies and their usefulness.

Time Efficiency, Reliability, and User Satisfaction of the Tooth Memo App for Recording Oral Health Information: Cross-Sectional Questionnaire Study.

Digitalizing oral health data through an app can help manage the extensive data obtained through oral health surveys. The Tooth Memo app collects data from oral health surveys and personal health information. This study aims to evaluate the evaluate the time efficiency, reliability, and user satisfaction of the Tooth Memo app. There are 2 sections in the Tooth Memo app: oral health survey and personal oral health record. For the oral health survey section of the Tooth Memo app, different data entry methods were compared and user satisfaction was evaluated. Fifth-year dental students had access to the oral health survey section in the Tooth Memo app during their clinical work. The time required for data entry, analysis, and summary of oral health survey data by 3 methods, that is, pen-and-paper (manual), Tooth Memo app on iOS device, and Tooth Memo app on Android device were compared among 3 data recorders who entered patients' information on decayed, missing, and filled permanent teeth (DMFT) index and community periodontal index (CPI), which were read aloud from the database of 103 patients by another dental personnel. The interobserver reliability of the 3 different data-entering procedures was evaluated by percent disagreement and kappa statistic values. Laypeople had access to the personal oral health record section of this app, and their satisfaction was evaluated through a Likert scale questionnaire. The satisfaction assessments for both sections of the Tooth Memo app involved the same set of questions on the app design, usage, and overall satisfaction. Of the 103 dental records on DMFT and CPI, 5.2% (177/3399) data points were missing in the manual data entries, but no data on tooth status were missing in the Android and iOS methods. Complete CPI information was provided by all 3 methods. Transferring data from paper to computer took an average of 55 seconds per case. The manual method required 182 minutes more than the iOS or Android methods to clean the missing data and transfer and analyze the tooth status data of 103 patients. The users, that is, 109 fifth-year dental students and 134 laypeople, expressed high satisfaction with using the Tooth Memo app. The overall satisfaction with the oral health survey ranged between 3 and 10, with an average (SD) of 7.86 (1.46). The overall satisfaction with the personal oral health record ranged between 4 and 10, with an average (SD) of 8.09 (1.28). The Tooth Memo app was more efficacious than manual data entry for collecting data of oral health surveys. Dental personnel as well as general users reported high satisfaction when using this app.

Genetic correlation and Mendelian randomization analyses support causal relationships between dietary habits and age at menarche

Dietary habits are essential in the mean age at menarche (AAM). However, the causal relationship between these factors remains unclear. Therefore, this study aimed to elucidate the genetic relationship between dietary habits and AAM. Genetic summary statistics for dietary habits were obtained from the UK Biobank. GWAS summary data for AAM was obtained from the ReproGen Consortium. Linkage disequilibrium score regression was used to test genetic correlations between dietary habits and AAM. The Mendelian randomization (MR) analyses used the inverse-variance weighted method. Genetic correlations with AAM were identified for 29 candi-date dietary habits, such as milk type (skimmed, semi-skimmed, full cream; coefficient = 0.2704, Pldsc = 1.13 × 10−14). MR evaluations revealed that 19 dietary habits were associated with AAM, including bread type (white vs. any other; OR 1.71, 95% CI 1.28–2.29, Pmr = 3.20 × 10−4), tablespoons of cooked vegetables (OR 0.437, 95% CI 0.29–0.67; Pmr = 1.30 × 10−4), and cups of coffee per day (OR 0.72, 95% CI 0.57–0.92, Pmr = 8.31 × 10−3). These results were observed to be stable under the sensitivity analysis. Our study provides potential insights into the genetic mechanisms underlying AAM and evidence that dietary habits are associated with AAM.

MaMD Analytical 1.0

We outline the functionalities and application of MaMD Analytical—a new, freely available software package for the estimation of population affinity using human cranial macromorphoscopic (MMS) traits. MaMD Analytical captures MMS scores using line drawings following the procedures outlined by Hefner and Linde (2018). MaMD Analytical generates classifications (with estimated likelihoods) into forensically significant populations using an artificial neural network and reference samples drawn from the Macromorphoscopic Databank (MaMD). Summary data (sensitivity, specificity, x-validated classification accuracies) are provided. In this article, we apply MaMD Analytical to a large sample of identified individuals not used in the original model building to assess utility and demonstrate the typical outputs for MaMD Analytical. MaMD Analytical facilitates construction of the biological profile and provides a number of safeguards in summary statistics as a valuable addition to the forensic anthropological analysis toolkit. MaMD Analytical is written in the open-source R environment integrating a previously developed artificial neural network model to estimate population affinity using well-documented and validated approaches.

Mendelian randomization analyses for the causal relationship between early age at first sexual intercourse, early age at first live birth, and postpartum depression in pregnant women.

There are insufficient epidemiological studies on the impact of age at first sexual intercourse (AFS) and age at first live birth (AFB) on postpartum depression (PPD) in pregnant women, and the conclusions of these studies are inconsistent. We performed a Mendelian randomization (MR) study to determine the causal relationship between AFS or AFB and the risk of PPD. The summary data were extracted from genome-wide association study (GWAS) summary datasets. We selected the instrumental variables according to the P value of exposure-related single nucleotide polymorphisms (P<5 ×10-9 for AFS and P<5 ×10-8 for AFB) and estimated the linkage disequilibrium using the clump parameter (10,000 kb, r2 < 0.001). Single nucleotide polymorphisms were considered instrumental variables that were significantly associated with exposure factors without linkage disequilibrium. The F-statistics of the instrumental variables should all be larger than 10.A random-effects model of IVW was constructed as the main method in our study. MR studies based on GWAS data revealed that both AFS (OR = 0.4, P <0.001) and AFB (OR = 0.38, P <0.001) were negatively correlated with the risk of PPD. Early AFS and early AFB should be studied as possible risk factors for PPD in the future. Public health departments should attach importance to sex education for young girls. The results of our TSMR should be verified by high-quality prospective epidemiological studies in the future.