Miracle-dz/UniFAR-FTUs huggingface dataset:
A Radio Counterpart to a Jupiter-mass Binary Object in Orion

Using James Webb Space Telescope near-infrared data of the inner Orion Nebula, Pearson & McCaughrean detected 40 Jupiter-mass binary objects (JuMBOs). These systems are not associated with stars and their components have masses of giant Jupiter-like planets and separations in the plane of the sky of order ∼100 au. The existence of these wide free-floating planetary-mass binaries was unexpected in our current theories of star and planet formation. Here we report the radio continuum (6.1 and 10.0 GHz) Karl G. Jansky Very Large Array detection of a counterpart to JuMBO 24. The radio emission appears to be steady at a level of ∼50 μJy over timescales of days and years. We set an upper limit of ≃15 km s−1 to the velocity of the radio source in the plane of the sky. As in the near-infrared, the radio emission seems to be coming from both components of the binary.
Estimation of SARS-CoV-2 fitness gains from genomic surveillance data without prior lineage classification

The emergence of SARS-CoV-2 variants with increased fitness has had a strong impact on the epidemiology of COVID-19, with the higher effective reproduction number of the viral variants leading to new epidemic waves. Tracking such variants and their genetic signatures, using data collected through genomic surveillance, is therefore crucial for forecasting likely surges in incidence. Current methods of estimating fitness advantages of variants rely on tracking the changing proportion of a particular lineage over time, but describing successful lineages in a rapidly evolving viral population is a difficult task. We propose a new method of estimating fitness gains directly from nucleotide information generated by genomic surveillance, without a-priori assigning isolates to lineages from phylogenies, based solely on the abundance of Single Nucleotide Polymorphisms (SNPs). The method is based on mapping changes in the genetic population structure over time. Changes in the abundance of SNPs associated with periods of increasing fitness allow for the unbiased discovery of new variants, and thereby obviating a deliberate lineage assignment and phylogenetic inference. We conclude that the method provides a fast and reliable way to estimate fitness advantages of variants without the need for a-priori assigning isolates to lineages.
Predicting dimensions of depression from smartphone data

Depressive disorders are highly prevalent but demand nuanced personalized treatment that traditional approaches in psychiatry cannot address. This gap has prompted a surge of interest in leveraging digital technology, particularly smartphones, for remote monitoring to enhance outpatient care. This study utilizes the BRIGHTEN dataset to construct interpretable prediction models for overall depression severity, measured by PHQ-9, and various depression dimensions using a factor modelling approach. Our factor model unveils a three-factor solution encompassing mood, somatic, and concentration/psychomotor-related factors. Machine learning models effectively predict both the PHQ-9 scores and individual factors, with feature importance methods analyses underscoring the influence of the PHQ-2 scale and communication-related features. These findings are corroborated by models trained on data subsets. Through nested multi-level models, we identify between-subject effects for the PHQ-2 and select communication-related features, along with within-subject effects for these features. In summary, this study underscores the robust predictive capacity of ecological momentary assessments and highlights features of potential relevance for future investigations, such as communication-related fea- tures. We advocate for future studies to assess the cost-effectiveness and intervention potential of these models.
Metformin use is associated with lower risks of dementia, anxiety and depression: The Hong Kong Diabetes Study

Aims: To compare the effects of metformin and sulphonylurea on new-onset dementia, anxiety disorder and depression, and all-cause mortality in patients with type 2 diabetes mellitus. Methods: This is a retrospective population-based cohort study of type 2 diabetes mellitus patients exposed to either metformin or sulphonylureas attending the Hospital Authority of Hong Kong between 1st and 31st December 2009. The follow-up was until 31st December 2019. The primary outcome was a new diagnosis of dementia, and anxiety disorder/depression. Propensity score matching (1:1 ratio) between metformin and sulphonylurea users based on demographics, CAIDE score, CHA-DS-VASc score, Charlson comorbidity index, past comorbidities, medications, and total cholesterol was performed. Cox regression was used to identify significant risk predictors. Cause-specific and subdistribution hazard models were also used. Results: A total of 89,711 patients (46% men, mean age: 67 years old [SD: 12]) followed-up for 1,579 days (SD: 650). Metformin users were at a lower risk of dementia (before: 0.78 [0.72, 0.84], P-value < 0.0001; after: 0.88 [0.80, 0.97], P-value = 0.0074), anxiety disorder and depression (before: 0.77 [0.69, 0.86], P-value < 0.0001; after: 0.71 [0.61, 0.82], P-value < 0.0001), and all-cause mortality (before: 0.69 [0.68, 0.71], P-value < 0.0001; after: 0.83 [0.80, 0.85], P-value < 0.0001). These associations remained significant in the competing risk models. Conclusion: Metformin use is associated with lower risks of dementia, new-onset anxiety disorder and depression, and all-cause mortality, compared to sulphonylurea use. The protective effects of metformin and possible use in drug repurposing for indications beyond diabetes warrant further investigation. Key words: metformin; cognitive; depression; anxiety; drug repurposing
Immunotherapy Time of Infusion Impacts Survival in Head and Neck Cancer: A Propensity Score Matched Analysis

The adaptive immune response is physiologically regulated by the circadian rhythm. Data in lung and melanoma malignancies suggests immunotherapy infusions earlier in the day may be associated with improved response; however, the optimal time of administration for patients with HNSCC is not known. We aimed to evaluate the association of immunotherapy infusion time with overall survival (OS) and progression free survival (PFS) in patients with HNSCC in an Institutional Review Board-approved, retrospective cohort study. 113 patients met study inclusion criteria and 98 patients were included in a propensity score-matched cohort. In the full unmatched cohort (N=113), each additional 20% of infusions received after 1500h conferred an OS hazard ratio (HR) of 1.35 (95% C.I.1.2-1.6; p-value=0.0003) and a PFS HR of 1.34 (95% C.I.1.2-1.6; p-value <0.0001). A propensity score-matched analysis of patients who did or did not receive [≥] 20% of infusions after 1500h showed that those who were administered [≥] 20% of infusions after 1500h trended towards a shorter OS (HR=1.35; p-value=0.26) and a shorter PFS (HR=1.57, 95% C.I. 1.02-2.42, p-value=0.04). Each additional 20% of infusions received after 1500h remained robust in the matched cohort multivariable analysis and was associated with shorter OS (adjusted HR=1.4 (95% C.I.1.2-1.8), p-value<0.001). Patients with advanced HNSCC who received more of their infusions in the afternoon were associated with shorter OS and PFS and scheduling immunotherapy infusions earlier in the day may be warranted.
Applying Multimodal Data Fusion based on Deep Learning Methods for the Diagnosis of Neglected Tropical Diseases: A Systematic Review

Neglected tropical diseases (NTDs) are the most prevalent diseases worldwide affecting one tenth of the world population. Although there are multiple approaches to diagnose these diseases, using skin manifestations and lesions caused as a result of these diseases along with other medical records is the preferred method. This fact triggers the need to explore and implement a deep learning -based diagnostic model using multimodal data fusion (MMDF) techniques to enhance the diagnostic process. This paper, thus, endeavored to present a thorough systematic review of studies regarding the implementation of MMDF techniques for the diagnoses of skin related NTDs. To achieve its objective, the study used the PRISMA method based on predefined questions and collected 427 articles from seven major and reputed sources and critically appraised each article. Although there are studies that demonstrate the utilization of deep learning methods for the diagnoses of NTDs, no previous studies were found regarding the implementation of MMDF for the diagnoses of skin related NTDs. Similar studies using MMDF for the diagnoses of other skin diseases, such as skin cancer, were collected and analyzed in this review to extract information about the implementation of these methods. In doing so, various studies are analyzed using six different parameters including research approaches, disease selected for diagnosis, dataset, algorithms, performance achievements and future directions. Accordingly, although all the studies analyzed used diverse research methods and datasets based on their problem, deep learning -based convolutional neural network algorithms are the most frequently used and best performing model in all studies reviewed.
Evaluating and Improving the Performance and Racial Fairness of Algorithms for GFR Estimation

Data-driven clinical prediction algorithms are used widely by clinicians. Understanding what factors can impact the performance and fairness of data-driven algorithms is an important step towards achieving equitable healthcare. To investigate the impact of modeling choices on the algorithmic performance and fairness, we make use of a case study to build a prediction algorithm for estimating glomerular filtration rate (GFR) based on the electronic health record (EHR). We compare three distinct approaches for estimating GFR: CKD-EPI equations, epidemiological models, and EHR-based models. For epidemiological models and EHR-based models, four machine learning models of varying computational complexity (i.e., linear regression, support vector machine, random forest regression, and neural network) were compared. Performance metrics included root mean squared error (RMSE), median difference, and the proportion of GFR estimates within 30% of the measured GFR value (P30). Differential performance between non-African American and African American group was used to assess algorithmic fairness with respect to race. Our study showed that the variable race had a negligible effect on error, accuracy, and differential performance. Furthermore, including more relevant clinical features (e.g., common comorbidities of chronic kidney disease) and using more complex machine learning models, namely random forest regression, significantly lowered the estimation error of GFR. However, the difference in performance between African American and non-African American patients did not decrease, where the estimation error for African American patients remained consistently higher than non-African American patients, indicating that more objective patient characteristics should be discovered and included to improve algorithm performance.
An evaluation of traffic calming devices for major highways passing through rural Australian communities

Rural communities are overrepresented in the Australian crash statistics with 66% of the Australian road fatalities occurring on rural roads despite only 33% of the road fleet using rural roads frequently. Australian literature on traffic calming is dated and provides information predominantly for the urban road environment and does not direct road designers to modern engineering means. In the past decade a number of traffic calming devices have been implemented into the urban road network and this has been represented by a significant reduction in the number of fatalities. However, these have not been incorporated into rural communities due to a perceived unbeneficial cost by use ratio. The report aims to analyse 14 sites and compare before and after traffic calming installation crash data to determine if traffic calming provides significant improvements to the safety of the road network. The report will also analyse the speed of drivers using these traffic‐ calming devices to quantify how driver behaviour in moderated at each site. To achieve this each site will be investigated and the speed of drivers recorded over a given distance before and after the traffic‐calming device. This will provide a map of driver behaviour and interactions through the rural community. This behavioural analysis will be instrumental in viewing the operational efficiency of traffic calming devices and recommending where the optimum positioning of a device would be for maximum benefit. A Z‐test will be performed on the data to determine if the speed variations are statistically significant or a result of statistical deviation. The report finds that traffic calming provides varying degrees of benefit depending on each individual road environment. It quantifies the predicted area of influence of each traffic‐ calming device and provides advice as to appropriate scenarios to provide the predicted maximum safety benefit.
The NF-κB signaling system in the immunopathogenesis of inflammatory bowel disease

Inflammatory bowel disease (IBD) is an idiopathic, chronic condition characterized by episodes of inflammation in the gastrointestinal tract. The nuclear factor κB (NF-κB) system describes a family of dimeric transcription factors. Canonical NF-κB signaling is stimulated by and enhances inflammation, whereas noncanonical NF-κB signaling contributes to immune organogenesis. Dysregulation of NF-κB factors drives various inflammatory pathologies, including IBD. Signals from many immune sensors activate NF-κB subunits in the intestine, which maintain an equilibrium between local microbiota and host responses. Genetic association studies of patients with IBD and preclinical mouse models confirm the importance of the NF-κB system in host defense in the gut. Other studies have investigated the roles of these factors in intestinal barrier function and in inflammatory gut pathologies associated with IBD. NF-κB signaling modulates innate and adaptive immune responses and the production of immunoregulatory proteins, anti-inflammatory cytokines, antimicrobial peptides, and other tolerogenic factors in the intestine. Furthermore, genetic studies have revealed critical cell type–specific roles for NF-κB proteins in intestinal immune homeostasis, inflammation, and restitution that contribute to the etiopathology of IBD-associated manifestations. Here, we summarize our knowledge of the roles of these NF-κB pathways, which are activated in different intestinal cell types by specific ligands, and their cross-talk, in fueling aberrant intestinal inflammation. We argue that an in-depth understanding of aberrant immune signaling mechanisms may hold the key to identifying predictive or prognostic biomarkers and developing better therapeutics against inflammatory gut pathologies. The roles of the canonical and noncanonical NF-κB signaling pathways in the pathogenesis of IBD are discussed.
Visible “Soil” as an Indicator of Bacterial Concentration on Farmworkers' Hands

*Author for correspondence: Telephone: +1 404.317. 5042; E-mail: juan.leon@emory.edu Visible Soil as an Indicator of Bacteria Concentration on Farmworkers’ Hands 1Hubert Dept. of Global Health, Rollins School of Public Health, Emory University, Atlanta, Georgia 30322, USA 2Departamento de Microbiología e Inmunología, Facultad de Ciencias Biológicas, Universidad Autónoma de Nuevo León, San Nicolás, Nuevo Leon 66451, México 3GOJO Industries, Inc., Akron, Ohio 44311, USA Valerie N. Morrill,1 Anna M. Fabiszewski de Aceituno,1 Faith E. Bartz,1 Norma Heredia,2 Santos Garcia,2 David J. Shumaker,3 James Grubb,3 James W. Arbogast3 and Juan S. Leon1*
Comprehensive study of nanostructured Bi2Te3 thermoelectric materials – insights from synchrotron radiation XRD, XAFS, and XRF techniques

In this contribution, a comprehensive study of nanostructured Bi2Te3 (BT) thermoelectric material was performed using a combination of synchrotron radiation-based techniques such as XAFS, and XRF, along with some other laboratory techniques such as XRD, XPS, FESEM, and HRTEM. This study aims to track the change in morphological, compositional, average and local/electronic structures of Bi2Te3 of two different phases; nanostructure (thin film) and nanopowders (NPs). Bi2Te3 nanomaterial was fabricated as pellets using zone melting process in a one step process, while Bi2Te3 thin film was deposited on sodalime glass substrate using a vacuum thermal evaporation technique. Synchrotron radiation-based Bi LIII-edge fluorescence-mode X-ray absorption fine structure (XAFS) technique was performed to probe locally the electronic and fine structures of BT thin film around the Bi atom, while transmission-mode XAFS was used for BT NPs distributed in the PVP matrix. The structural features of the collected Bi LIII XANES spectra of thin film and powder samples of BT are compared with the simulated XANES spectrum of BT calculated using FDMNES code at 5 Å cluster size. Combining different off-line structural characterization techniques (XRD, FESEM, XPS, and HRTEM), along with those of synchrotron radiation-based techniques (XAFS and XRF) is necessary for complementary and supported average crystal, chemical, morphological and local electronic structural analyses for unveiling the variation between Bi2Te3 in the nanostructure/thin film and nanopowder morphology, and then connecting between the structural features and functions of BT in two different morphologies. After that, we measured the Seebeck coefficient and the power factor values for both the BT nanopowder and thin film.
Effects of Duloxetine on Gastrointestinal Symptoms, Depression, Anxiety, Stress, and Quality of Life in Patients with the Moderate-to-Severe Irritable Bowel Syndrome

Abstract Background: Irritable bowel syndrome (IBS) is a chronic disease. There are very few studies on the Duloxetine efficacy in improving the gastrointestinal and psychological symptoms, in IBS. The current study attempted to evaluate the effectiveness of Duloxetine in symptoms and quality of life in moderate-to-severe IBS patients. Materials and Methods: This is a double-blind placebo-controlled clinical trial in which the population is composed of 37 patients with moderate-to-severe IBS in Isfahan from March 2018 to March 2019. For the intervention group, Duloxetine was administered for three months, and the treatment protocol was the same for the control group but using a placebo. The severity of IBS symptoms, quality of life, and negative emotions such as depression, anxiety, and stress were assessed. Results: Our data showed no significant difference between the two groups of the study for the severity of IBS symptoms (P value = 0.150); however, in the intervention group, it was significantly lower than controls after six, eight, and ten weeks of the intervention (P value = 0.023). Overall evaluation of the quality of life in patients indicated significantly higher quality of life in the Duloxetine group than the control group from the eighth week to the twelfth week after the intervention (P value <0.038). Anxiety and stress in the Duloxetine group were significantly lower than controls after the intervention (P value <0.05). Conclusion: Duloxetine is probably helpful for reducing anxiety, stress, and the severity of symptoms in IBS patients. It also could increase the quality of life in patients.
The Assessment of Neonatal Anthropometric Indices Association with Umbilical Cord Blood Zinc and Magnesium Levels

Abstract Background: The present research aims to find the association between neonatal anthropometric parameters and zinc and magnesium concentration in cord blood. Materials and Methods: The current cross-sectional report is a sub-study from the “PERSIAN Birth Cohort Study” conducted on 112 pairs of mother-neonate referring to the index hospitals for giving birth to their children during 2018–19. Umbilical cord blood was collected at delivery for the measurement of zinc and magnesium. Anthropometric indices were measured in standard protocols. Validated questionnaires were used for maternal diet in different trimesters. Dietary patterns were acquired based on exploratory factor analysis. Results: The birth weight was reversely correlated with zinc concentration (r = -0.249, P-value = 0.008); however, the other anthropometric parameters did not show any association with zinc levels (P-value > 0.05). Similar evaluations for magnesium revealed no association between any of the anthropometric indices and this micronutrient agent (P-value > 0.05). Further evaluations represented insignificant differences in both zinc (P-value = 0.51) and magnesium levels (P-value = 0.49) between those with normal versus low birth weight. There was a negative association between the Western dietary pattern in the first trimester of pregnancy and cord blood zinc concentration (β (SE) = -0.21 (0.10); P = 0.026); while healthy and traditional dietary patterns in second and third trimesters were positively related to cord zinc concentration (all P < 0.05). Conclusion: This research did not document a positive statistical association of cord blood zinc and magnesium with birth weight. The association of maternal Western dietary patterns with lower cord blood zinc levels highlights the importance of healthy nutritional habits in pregnancy.
Clinical and Patient-Reported Outcomes After Total Wrist Arthroplasty and Total Wrist Fusion

Background: The functional benefits of total wrist arthroplasty (TWA) over total wrist fusion (TWF) are unknown. The purpose of this prospective cohort study was to compare TWA and TWF with respect to functional outcomes and activity limitations at up to 2 years postoperatively. Methods: Between 2015 and 2020, we enrolled all adult patients undergoing TWA or TWF for the management of symptomatic end-stage wrist arthritis at 1 hand surgery department. The primary outcome was the Patient-Rated Wrist Evaluation (PRWE). The secondary outcomes were the visual analog scale (VAS) for pain at rest, on motion, and on loading; grip strength; Disabilities of the Arm, Shoulder and Hand (DASH); and range of motion. Patients completed questionnaires and were examined by the same physiotherapist at baseline and at 3, 6, 12, and 24 months postoperatively. Mixed-model analyses adjusting for age, diagnosis, the preoperative value of the dependent variable, and time since surgery were performed to compare differences in PRWE scores, VAS pain scores, and grip strength between TWA and TWF. Results: Of the 51 patients who had been included at baseline, 47 (18 in the TWA group and 29 in the TWF group) responded to questionnaires and underwent examinations at up to 2 years postoperatively. At baseline, the 2 groups did not differ in terms of age, sex, diagnosis (inflammatory or noninflammatory arthritis), PRWE score, VAS pain score, grip strength, DASH score, or range of motion. No differences between the groups were found for the PRWE (β, −0.1; 95% confidence interval [CI], −14 to 13; p = 0.99), VAS pain at rest (β, −3.3; 95% CI, −15 to 9; p = 0.58), VAS pain on loading (β, −5.3; 95% CI, −22 to 11; p = 0.52), or grip strength (β, −0.02; 95% CI, −0.18 to 0.14; p = 0.80) on the adjusted mixed-model analyses. Conclusions: Among patients with symptomatic end-stage wrist arthritis, those who underwent TWA did not demonstrate short-term outcomes, including patient-reported disability, pain, and grip strength, superior to those of patients who underwent TWF. These findings call into question the widespread use of TWA. Level of Evidence: Therapeutic Level II. See Instructions for Authors for a complete description of levels of evidence.