Statistical inference for transfer learning with high-dimensional quantile regression

Transfer learning has become an essential technique to exploit information from the source domain to boost performance of the target task. Despite the prevalence in high-dimensional data, heterogeneity and/or heavy tails are insufficiently accounted for by current transfer learning approaches and thus may undermine the resulting performance. We propose a transfer learning procedure in the framework of high-dimensional quantile regression models to accommodate the heterogeneity and heavy tails in the source and target domains. We establish error bounds of the transfer learning estimator based on delicately selected transferable source domains, showing that lower error bounds can be achieved for critical selection criterion and larger sample size of source tasks. We further propose valid confidence interval and hypothesis test procedures for individual component of high-dimensional quantile regression coefficients by advocating a double transfer learning estimator, which is the one-step debiased estimator for the transfer learning estimator wherein the technique of transfer learning is designed again. Simulation results demonstrate that the proposed method exhibits some favorable performances, further corroborating our theoretical results.Comment: 122 pages, 6 figure

FishMOT: A Simple and Effective Method for Fish Tracking Based on IoU Matching

The tracking of various fish species plays a profoundly significant role in understanding the behavior of individual fish and their groups. Present tracking methods suffer from issues of low accuracy or poor robustness. In order to address these concerns, this paper proposes a novel tracking approach, named FishMOT (Fish Multiple Object Tracking). This method combines object detection techniques with the IoU matching algorithm, thereby achieving efficient, precise, and robust fish detection and tracking. Diverging from other approaches, this method eliminates the need for multiple feature extractions and identity assignments for each individual, instead directly utilizing the output results of the detector for tracking, thereby significantly reducing computational time and storage space. Furthermore, this method imposes minimal requirements on factors such as video quality and variations in individual appearance. As long as the detector can accurately locate and identify fish, effective tracking can be achieved. This approach enhances robustness and generalizability. Moreover, the algorithm employed in this method addresses the issue of missed detections without relying on complex feature matching or graph optimization algorithms. This contributes to improved accuracy and reliability. Experimental trials were conducted in the open-source video dataset provided by idtracker.ai, and comparisons were made with state-of-the-art detector-based multi-object tracking methods. Additionally, comparisons were made with idtracker.ai and TRex, two tools that demonstrate exceptional performance in the field of animal tracking. The experimental results demonstrate that the proposed method outperforms other approaches in various evaluation metrics, exhibiting faster speed and lower memory requirements. The source codes and pre-trained models are available at: https://github.com/gakkistar/FishMO

THE EFFICACY AND SAFETY OF URTICA DIOICA IN TREATING BENIGN PROSTATIC HYPERPLASIA: A SYSTEMATIC REVIEW AND META-ANALYSIS

Background: Urtica dioica is extract from the root of a stinging nettle. Materials and Methods: We carried out a systematic review and meta-analysis to assess the efficacy and safety of Urtica dioica for treating Benign prostatic hyperplasia (BPH). A literature review was performed to identify all published randomized double-blind, controlled trials of Urtica dioica for the treatment of BPH. The search included the following databases: MEDLINE, EMBASE, and the Cochrane Controlled Trials Register. The reference lists of the retrieved studies were also investigated. Results: Five publications involving a total of 1128 patients were used in the analysis. Primary efficacy end points: the international prostate symptom score (IPSS) (the standardized mean difference (SMD) =-10.47, 95% confidence interval (CI) =-18.12 to -2.82, p=0.007); the peak urinary flow rate (Qmax) (SMD=4.37, 95%CI=1.55 to 7.19, p=0.002) and prostate volume (SMD=-3.63, 95%CI=-4.67 to -2.57,

Efficacy of mirabegron for ureteral stones: a systematic review with meta-analysis of randomized controlled trials

Background: Medical expulsive therapy demonstrates efficacy in managing ureteral stones in patients amenable to conservative interventions. This meta-analysis aims to evaluate the effectiveness of mirabegron in the treatment of ureteral stones.Methods: From conception to November 2023, we examined PubMed databases, the Cochrane Library, Embase, Ovid, Scopus, and trial registries for this systematic review and meta-analysis. We chose relevant randomized controlled trials (RCTs) evaluating the efficacy of mirabegron as an expulsive treatment for ureteral stones. The Cochrane risk of bias method was used to assess the quality of the evidence. Outcome measures, which included the stone expulsion rate (SER), expulsion time, and pain episodes, were analyzed using RevMan 5.4 and Stata 17.Results: Seven RCTs (N = 701) had enough information and were ultimately included. In patients with ureteral stones, mirabegron-treated patients had a substantially higher SER [odds ratio (OR) = 2.57, 95% confidence interval (CI) = 1.41–4.68, p = 0.002] than placebo-treated patients. Subgroup analysis revealed that mirabegron was superior to placebo in patients with small ureteral stones (OR = 2.26, 95% CI = 1.05–4.87, p = 0.04), with no heterogeneity between studies (p = 0.54; I2 = 0%). Mirabegron patients had a higher SER than the control group for distal ureteral stones (DUSs) (OR = 2.48, 95% CI = 1.31–4.68, p = 0.005). However, there was no difference in stone ejection time or pain episodes between groups.Conclusion: Mirabegron considerably improves SER in patients with ureteral stones, and the effect appears to be more pronounced for small and DUSs. Nevertheless, mirabegron treatment was not associated with improved stone expulsion time or pain management

Biological Effects and Applications of Chitosan and Chito-Oligosaccharides

The numerous functional properties and biological effects of chitosan and chito-oligosaccharides (COS) have led to a significant level of interest, particularly with regard to their potential use in the agricultural, environmental, nutritional, and pharmaceutical fields. This review covers recent studies on the biological functions of COS and the impacts of dietary chitosan and COS on metabolism. The majority of results suggest that the use of chitosan as a feed additive has favorable biological effects, such as antimicrobial, anti-oxidative, cholesterol reducing, and immunomodulatory effects. The biological impacts reviewed herein may provide a new appreciation for the future use of COS

Risk and Protective Factors for the Mental Wellbeing of Deployed Healthcare Workers During the COVID-19 Pandemic in China: A Qualitative Study.

Background: Though many literatures documented burnout and occupational hazard among healthcare workers and frontliners during pandemic, not many adopted a systemic approach to look at the resilience among this population. Another under-studied population was the large numbers of global healthcare workers who have been deployed to tackle the crisis of COVID-19 pandemic in the less resourceful regions. We investigated both the mental wellbeing risk and protective factors of a deployed healthcare workers (DHWs) team in Wuhan, the epicenter of the virus outbreak during 2020. Method: A consensual qualitative research approach was adopted with 25 DHWs from H province through semi-structured interviews after 3 months of deployment period. Results: Inductive-Deductive thematic coding with self-reflexivity revealed multi-layered risk and protective factors for DHWs at the COVID-19 frontline. Intensive working schedule and high-risk environment, compounded by unfamiliar work setting and colleagues; local culture adaptation; isolation from usual social circle, strained the DHWs. Meanwhile, reciprocal relationships and "familial relatedness" with patients and colleagues; organizational support to the DHWs and their immediate families back home, formed crucial wellbeing resources in sustaining the DHWs. The dynamic and dialectical relationships between risk and protective factors embedded in multiple layers of relational contexts could be mapped into a socio-ecological framework. Conclusion: Our multidisciplinary study highlights the unique social connectedness between patient-DHWs; within DHWs team; between deploying hospital and DHWs; and between DHWs and the local partners. We recommend five organizational strategies as mental health promotion and capacity building for DHWs to build a resilient network and prevent burnout at the disaster frontline

Job burnout among primary healthcare workers during COVID-19 pandemic: cross-sectional study in China

ObjectiveThis study evaluated job burnout among primary healthcare workers (PHCWs) in China during the COVID-19 pandemic, explored its influencing factors, and examined PHCWs' preferences for reducing job burnout.MethodWe conducted a multicenter cross-sectional study in Heilongjiang, Sichuan, Anhui, Gansu, and Shandong Provinces. An electronic questionnaire survey was conducted through convenience sampling in communities from May to July 2022. We collected sociodemographic characteristics, job burnout level, job satisfaction, and preferred ways to reduce job burnout among PHCWs.ResultsThe job burnout rate among PHCWs in China was 59.87% (937/1565). Scores for each dimension of job burnout were lower among PHCWs who had a better work environment (emotional exhaustion OR: 0.60; depersonalization OR: 0.73; personal accomplishment OR: 0.76) and higher professional pride (emotional exhaustion OR: 0.63; depersonalization OR: 0.70; personal accomplishment OR: 0.44). PHCWs with higher work intensity (emotional exhaustion OR: 2.37; depersonalization OR: 1.34; personal accomplishment OR: 1.19) had higher scores in all job burnout dimensions. Improving work environments and raising salaries were the preferred ways for PHCWs to reduce job burnout.ConclusionStrategies should be developed to improve job satisfaction among PHCWs, enhance their professional identity, and alleviate burnout to ensure the effective operation of the healthcare system, especially during periods of overwork

Induced Expression of the <i>Acinetobacter sp.</i> Oxa Gene in <i>Lactobacillus acidophilus</i> and Its Increased ZEN Degradation Stability by Immobilization

Zearalenone (ZEN, ZEA) contamination in various foods and feeds is a significant global problem. Similar to deoxynivalenol (DON) and other mycotoxins, ZEN in feed mainly enters the body of animals through absorption in the small intestine, resulting in estrogen-like toxicity. In this study, the gene encoding Oxa, a ZEN-degrading enzyme isolated from Acinetobacter SM04, was cloned into Lactobacillus acidophilus ATCC4356, a parthenogenic anaerobic gut probiotic, and the 38 kDa sized Oxa protein was expressed to detoxify ZEN intestinally. The transformed strain L. acidophilus pMG-Oxa acquired the capacity to degrade ZEN, with a degradation rate of 42.95% at 12 h (initial amount: 20 μg/mL). The probiotic properties of L. acidophilus pMG-Oxa (e.g., acid tolerance, bile salt tolerance, and adhesion properties) were not affected by the insertion and intracellular expression of Oxa. Considering the low amount of Oxa expressed by L. acidophilus pMG-Oxa and the damage to enzyme activity by digestive juices, Oxa was immobilized with 3.5% sodium alginate, 3.0% chitosan, and 0.2 M CaCl2 to improve the ZEN degradation efficiency (from 42.95% to 48.65%) and protect it from digestive juices. The activity of immobilized Oxa was 32–41% higher than that of the free crude enzyme at different temperatures (20–80 °C), pH values (2.0–12.0), storage conditions (4 °C and 25 °C), and gastrointestinal simulated digestion conditions. Accordingly, immobilized Oxa could be resistant to adverse environmental conditions. Owing to the colonization, efficient degradation performance, and probiotic functionality of L. acidophilus, it is an ideal host for detoxifying residual ZEN in vivo, demonstrating great potential for application in the feed industry

Bioinformatics-Based Identification of Potential Hypoxia-Related Genes Associated With Peyronie’s Disease

Hypoxia is one of the most important predisposing conditions for Peyronie’s disease (PD) and the pathogenetic mechanism is yet to be completely elucidated. This study applied bioinformatic approaches to select candidate hypoxia-related genes involved in the pathogenesis of PD. The Gene Expression Omnibus (GEO) data set GSE146500 was introduced to compare the transcriptional profiling between normal and PD samples. The differential expression of hypoxia-related gene was determined with R software. On the selected candidate genes, further functional analyses were applied, including protein–protein interactions (PPIs), gene correlation, gene ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway. A total of 66 candidate genes (24 candidates overexpressed in PD and 42 showing reduced expression in PD) were distinguished according to the differential expression between human fibroblast cells from normal and PD patients. The interactions among these candidate genes were recognized according to PPI analysis. The functional enrichment analyses revealed the potential modulatory functions of the candidate genes in some major biological processes, especially in glycolysis/gluconeogenesis and carbon metabolism. The findings would facilitate further study on the pathogenesis of PD, which might consequently promote the improvement of clinical strategies against PD

NMF-based approach for missing values imputation of mass spectrometry metabolomics data

In mass spectrometry (MS)-based metabolomics, missing values (NAs) may be due to different causes, including sample heterogeneity, ion suppression, spectral overlap, inappropriate data processing, and instrumental errors. Although a number of methodologies have been applied to handle NAs, NA imputation remains a challenging problem. Here, we propose a non-negative matrix factorization (NMF)-based method for NA imputation in MS-based metabolomics data, which makes use of both global and local information of the data. The proposed method was compared with three commonly used methods: k-nearest neighbors (kNN), random forest (RF), and outlier-robust (ORI) missing values imputation. These methods were evaluated from the perspectives of accuracy of imputation, retrieval of data structures, and rank of imputation superiority. The experimental results showed that the NMF-based method is well-adapted to various cases of data missingness and the presence of outliers in MS-based metabolic profiles. It outperformed kNN and ORI and showed results comparable with the RF method. Furthermore, the NMF method is more robust and less susceptible to outliers as compared with the RF method. The proposed NMF-based scheme may serve as an alternative NA imputation method which may facilitate biological interpretations of metabolomics data