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ENeuro Jun 2024Typical statistical practices in the biological sciences have been increasingly called into question due to difficulties in the replication of an increasing number of...
Typical statistical practices in the biological sciences have been increasingly called into question due to difficulties in the replication of an increasing number of studies, many of which are confounded by the relative difficulty of null significance hypothesis testing designs and interpretation of p-values. Bayesian inference, representing a fundamentally different approach to hypothesis testing, is receiving renewed interest as a potential alternative or complement to traditional null significance hypothesis testing due to its ease of interpretation and explicit declarations of prior assumptions. Bayesian models are more mathematically complex than equivalent frequentist approaches, which have historically limited applications to simplified analysis cases. However, the advent of probability distribution sampling tools with exponential increases in computational power now allows for quick and robust inference under any distribution of data. Here we present a practical tutorial on the use of Bayesian inference in the context of neuroscientific studies in both rat electrophysiological and computational modeling data. We first start with an intuitive discussion of Bayes' rule and inference followed by the formulation of Bayesian-based regression and ANOVA models using data from a variety of neuroscientific studies. We show how Bayesian inference leads to easily interpretable analysis of data while providing an open-source toolbox to facilitate the use of Bayesian tools. Bayesian inference has received renewed interest as an alternative to null-significance hypothesis testing for its interpretability, ability to incorporate prior knowledge into current inference, and robust model comparison paradigms. Despite this renewed interest, discussions of Bayesian inference are often obfuscated by undue mathematical complexity and misunderstandings underlying the Bayesian inference process. In this article, we aim to empower neuroscientists to adopt Bayesian statistical inference by providing a practical methodological walkthrough using single and multi-unit recordings from the rodent auditory circuit accompanied by a well-documented and user-friendly toolkit containing regression and ANOVA statistical models commonly encountered in neuroscience.
PubMed: 38918054
DOI: 10.1523/ENEURO.0484-23.2024 -
Infection and Drug Resistance 2024To preliminarily assess the prevalence and control effect of tuberculosis and drug-resistant tuberculosis (TB) in Anhui province, and analyze the trends in the changing...
OBJECTIVE
To preliminarily assess the prevalence and control effect of tuberculosis and drug-resistant tuberculosis (TB) in Anhui province, and analyze the trends in the changing drug resistance spectrum of Mycobacterium tuberculosis (Mtb) isolated in Anhui province from 2016 to 2022.
METHODS
From 2016 to 2022, a total of 2336 culture-positive tuberculosis strains were collected from four drug resistance monitoring sites. Patient demographic information was collected and drug susceptibility testing was conducted.
RESULTS
Among the 2336 Mycobacterium tuberculosis complex strains, 1788 (76.54%) were from male patients and 548 (23.46%) were from female patients. The majority were of Han ethnicity, from rural areas, and employed in agriculture, with 12.54% (285/2273) having diabetes. A total of 1893 (81.04%) strains were sensitive to all six anti-TB drugs tested, and 443 (18.96%) strains were resistant to at least one or more anti-TB drugs. The drug resistance rate for patients undergoing initial treatment was 16.80% (348/2071), and 35.85% (95/265) for those receiving retreatment. Among the six anti-TB drugs, the resistance rates from highest to lowest were: INH (10.55%, 236/2336), SM (8.18%, 183/2336), OFX (6.53%, 146/2336), RFP (5.95%, 133/2336), EMB (2.37%, 53/2336), KM (1.97%, 44/2336). Significant differences were observed in MDR strains across different ages, types, with or without diabetes, and geographical sources (χ2=14.895,76.534,6.032,5.109, all P<0.05).
CONCLUSION
The tuberculosis prevention and control measures have controlled the drug resistance rate of Mycobacterium tuberculosis to a certain extent. However, there are still statistical differences in drug resistance rates among TB patients with different categories, age groups, regions, and diabetic diseases. Early detection and prompt treatment of patients with drug-resistant TB remain critical to controlling the spread of this disease.
PubMed: 38915321
DOI: 10.2147/IDR.S460080 -
Scientific Reports Jun 2024Musculoskeletal disorders (MSDs) impact people globally, cause occupational illness and reduce productivity. Exercise therapy is the gold standard treatment for MSDs and...
Musculoskeletal disorders (MSDs) impact people globally, cause occupational illness and reduce productivity. Exercise therapy is the gold standard treatment for MSDs and can be provided by physiotherapists and/or also via mobile apps. Apart from the obvious differences between physiotherapists and mobile apps regarding communication, empathy and physical touch, mobile apps potentially offer less personalized exercises. The use of artificial intelligence (AI) may overcome this issue by processing different pain parameters, comorbidities and patient-specific lifestyle factors and thereby enabling individually adapted exercise therapy. The aim of this study is to investigate the risks of AI-recommended strength, mobility and release exercises for people with MSDs, using physiotherapist risk assessment and retrospective consideration of patient feedback on risk and non-risk exercises. 80 patients with various MSDs received exercise recommendations from the AI-system. Physiotherapists rated exercises as risk or non-risk, based on patient information, e.g. pain intensity (NRS), pain quality, pain location, work type. The analysis of physiotherapists' agreement was based on the frequencies of mentioned risk, the percentage distribution and the Fleiss- or Cohens-Kappa. After completion of the exercises, the patients provided feedback for each exercise on an 11-point Likert scale., e.g. the feedback question for release exercises was "How did the stretch feel to you?" with the answer options ranging from "painful (0 points)" to "not noticeable (10 points)". The statistical analysis was carried out separately for the three types of exercises. For this, an independent t-test was performed. 20 physiotherapists assessed 80 patient examples, receiving a total of 944 exercises. In a three-way agreement of the physiotherapists, 0.08% of the exercises were judged as having a potential risk of increasing patients' pain. The evaluation showed 90.5% agreement, that exercises had no risk. Exercises that were considered by physiotherapists to be potentially risky for patients also received lower feedback ratings from patients. For the 'release' exercise type, risk exercises received lower feedback, indicating that the patient felt more pain (risk: 4.65 (1.88), non-risk: 5.56 (1.88)). The study shows that AI can recommend almost risk-free exercises for patients with MSDs, which is an effective way to create individualized exercise plans without putting patients at risk for higher pain intensity or discomfort. In addition, the study shows significant agreement between physiotherapists in the risk assessment of AI-recommended exercises and highlights the importance of considering individual patient perspectives for treatment planning. The extent to which other aspects of face-to-face physiotherapy, such as communication and education, provide additional benefits beyond the individualization of exercises compared to AI and app-based exercises should be further investigated.Trial registration: 30.12.2021 via OSF Registries, https://doi.org/10.17605/OSF.IO/YCNJQ .
Topics: Humans; Artificial Intelligence; Female; Male; Musculoskeletal Diseases; Adult; Middle Aged; Exercise Therapy; Risk Assessment; Retrospective Studies; Physical Therapists; Exercise; Aged; Mobile Applications
PubMed: 38914582
DOI: 10.1038/s41598-024-65016-1 -
Statistics and Computing 2024The collection of data on populations of networks is becoming increasingly common, where each data point can be seen as a realisation of a network-valued random...
UNLABELLED
The collection of data on populations of networks is becoming increasingly common, where each data point can be seen as a realisation of a network-valued random variable. Moreover, each data point may be accompanied by some additional covariate information and one may be interested in assessing the effect of these covariates on network structure within the population. A canonical example is that of brain networks: a typical neuroimaging study collects one or more brain scans across multiple individuals, each of which can be modelled as a network with nodes corresponding to distinct brain regions and edges corresponding to structural or functional connections between these regions. Most statistical network models, however, were originally proposed to describe a single underlying relational structure, although recent years have seen a drive to extend these models to populations of networks. Here, we describe a model for when the outcome of interest is a network-valued random variable whose distribution is given by an exponential random graph model. To perform inference, we implement an exchange-within-Gibbs MCMC algorithm that generates samples from the doubly-intractable posterior. To illustrate this approach, we use it to assess population-level variations in networks derived from fMRI scans, enabling the inference of age- and intelligence-related differences in the topological structure of the brain's functional connectivity.
SUPPLEMENTARY INFORMATION
The online version contains supplementary material available at 10.1007/s11222-024-10446-0.
PubMed: 38911222
DOI: 10.1007/s11222-024-10446-0 -
JSLS : Journal of the Society of... 2024Haemostasis-related complications associated with Medtronic Tri-staple with preloaded buttress material and the novel, naked AEON gastrointestinal staplers have not been... (Comparative Study)
Comparative Study
BACKGROUND AND OBJECTIVES
Haemostasis-related complications associated with Medtronic Tri-staple with preloaded buttress material and the novel, naked AEON gastrointestinal staplers have not been extensively studied in bariatric surgery. The study aimed to assess and compare the 30-day haemostasis-related complications between Medtronic Tri-staple and AEON GIA staplers.
METHODS
A retrospective analysis was performed on data from patients who underwent primary or revision sleeve gastrectomy (SG) or the sleeve component of single anastomosis duodeno-ileal bypass with SG (SADI-S) in a private hospital in Australia between November 2021 and December 2022. The surgeries were performed by a single surgeon, using either Medtronic Tri-staple or AEON staplers.
RESULTS
The analysis included 250 patients, with the first 125 consecutive patients receiving staple line using the Medtronic Tri-staple GIA stapler and the subsequent 125 patients receiving staple line using the AEON GIA stapler. Statistical analysis revealed no significant differences in the distribution of surgical procedures between the Medtronic and AEON groups. In the AEON group, there were statistically higher numbers of diabetics and former tobacco users, while other preoperative characteristics did not significantly differ between the two groups. The AEON group had a significantly longer mean operative time, while the length of hospital stay was significantly shorter. No intraoperative or 30-day complications, deaths, emergency room visits, readmissions, or reoperations were observed in either group.
CONCLUSION
The novel, naked AEON stapler demonstrated non-inferiority to the established Medtronic Tri-Staple with preloaded buttress material in achieving hemostasis and maintaining staple-line integrity in bariatric surgery.
Topics: Humans; Retrospective Studies; Female; Male; Bariatric Surgery; Middle Aged; Surgical Staplers; Surgical Stapling; Adult; Obesity, Morbid; Hemostasis, Surgical; Gastrectomy; Equipment Design
PubMed: 38910956
DOI: 10.4293/JSLS.2023.00058 -
BMC Public Health Jun 2024There has been extensive research conducted on open defecation in Ethiopia, but a notable gap persists in comprehensively understanding the spatial variation and...
INTRODUCTION
There has been extensive research conducted on open defecation in Ethiopia, but a notable gap persists in comprehensively understanding the spatial variation and predictors at the household level. This study utilizes data from the 2021 Performance Monitoring for Action Ethiopia (PMA-ET) to address this gap by identifying hotspots and predictors of open defecation. Employing geographically weighted regression analysis, it goes beyond traditional models to account for spatial heterogeneity, offering a nuanced understanding of geographical variations in open defecation prevalence and its determinants. This research pinpoints hotspot areas and significant predictors, aiding policymakers and practitioners in tailoring interventions effectively. It not only fills the knowledge gap in Ethiopia but also informs global sanitation initiatives.
METHODS
The study comprised a total weighted sample of 24,747 household participants. ArcGIS version 10.7 and SaT Scan version 9.6 were used to handle mapping, hotspots, ordinary least squares, Bernoulli model analysis, and Spatial regression. Bernoulli-based model was used to analyze the purely spatial cluster detection of open defecation at the household level in Ethiopia. Ordinary Least Square (OLS) analysis and geographically weighted regression analysis were employed to assess the association between an open defecation and explanatory variables.
RESULTS
The spatial distribution of open defecation at the household level exhibited clustering (global Moran's I index value of 4.540385, coupled with a p-value of less than 0.001), with significant hotspots identified in Amhara, Afar, Harari, and parts of Dire Dawa. Spatial analysis using Kuldorff's Scan identified six clusters, with four showing statistical significance (P-value < 0.05) in Amhara, Afar, Harari, Tigray, and southwest Ethiopia. In the geographically weighted regression model, being male [coefficient = 0.87, P-value < 0.05] and having no media exposure (not watching TV or listening to the radio) [coefficient = 0.47, P-value < 0.05] emerged as statistically significant predictors of household-level open defecation in Ethiopia.
CONCLUSION
The study revealed that open defecation at the household level in Ethiopia varies across the regions, with significant hotspots identified in Amhara, Afar, Harari, and parts of Dire Dawa. Geographically weighted regression analysis highlights male participants lacking media exposure as substantial predictors of open defecation. Targeted interventions in Ethiopia should improve media exposure among males in hotspot regions, tailored sanitation programs, and region-specific awareness campaigns. Collaboration with local communities is crucial.
Topics: Ethiopia; Humans; Male; Female; Adult; Defecation; Sanitation; Middle Aged; Young Adult; Spatial Regression; Spatial Analysis; Family Characteristics; Toilet Facilities; Adolescent
PubMed: 38910246
DOI: 10.1186/s12889-024-19222-1 -
BMC Pediatrics Jun 2024Diarrhea is considered to be one of the major public health concerns in developing countries. It has a detrimental impact, reflecting one of the highest child mortality...
BACKGROUND
Diarrhea is considered to be one of the major public health concerns in developing countries. It has a detrimental impact, reflecting one of the highest child mortality rates globally, especially in Sub-Saharan Africa, where 2 out of every 10 children in Uganda under the age of five die. The objective of this study was to investigate the factors associated with time to treatment seeking by caretakers of children under-five with Diarrhea in Uganda.
METHOD
DOVE dataset of 745 caretakers in a prospective and retrospective incidence-based study using multi-stage sampling design was used in the assessment. The analysis was done using a time-to-event approach using life tables, Kaplan Meier survival analysis and multilevel proportional hazards model.
RESULTS
Kaplan-Meier survival analysis indicated the median time to seeking treatment among 745 caretakers of children under-Five after onset of diarrhea was 2 days. The multi-level proportional hazards model of a Weibull distribution showed that the estimated frailty variance was 0.13, indicating heterogeneity of treatment seeking time by caretakers of under-five children with diarrhea across regions in Uganda. Significant factors found to influence time to treatment-seeking by caretakers of children under-five with diarrhea were, male children (HR = 0.82; 95% CI = 0.71-0.95, p = 0.010), belonging to richest wealth quintile (HR = 1.37; 95% CI = 1.05-1.78, p = 0.022), and residing more than 5 km away from a health facility (HR = 0.68; 95% CI = 0.56-0.84, p = 0.000).
CONCLUSIONS
There are delays in seeking diarrhea treatment in Uganda because two days are enough to claim a life after dehydration.The policymakers should pay attention to formulate effective intervention to sensitize caregivers on the importance of early treatment-seeking behavior to avoid severe malnutrition caused by diarrhea. Community awareness program should also be encouraged particularly in areas of more than 5 km from the health facility to make people aware of the necessity to take prompt action to seek care in the early stage.
Topics: Humans; Uganda; Male; Female; Diarrhea; Infant; Child, Preschool; Caregivers; Retrospective Studies; Proportional Hazards Models; Patient Acceptance of Health Care; Prospective Studies; Time-to-Treatment; Kaplan-Meier Estimate; Adult; Multilevel Analysis
PubMed: 38909217
DOI: 10.1186/s12887-024-04879-9 -
Annals of Clinical Microbiology and... Jun 2024Escherichia. coli is the most frequent host for New Delhi metallo-β-lactamase (NDM) which hydrolyzes almost all β-lactams except aztreonam. The worldwide spread of...
BACKGROUND
Escherichia. coli is the most frequent host for New Delhi metallo-β-lactamase (NDM) which hydrolyzes almost all β-lactams except aztreonam. The worldwide spread of blaNDM-carrying E. coli heavily threatens public health.
OBJECTIVE
This study aimed to explore the global genomic epidemiology of blaNDM- carrying E. coli isolates, providing information for preventing the dissemination of such strains.
METHODS
Global E. coli genomes were downloaded from NCBI database and blaNDM was detected using BLASTP. Per software was used to extract meta information on hosts, resources, collection data, and countries of origin from GenBank. The sequence types (STs) and distribution of antimicrobial resistance gene (ARG) were analyzed by CLC Workbench; Plasmid replicons, serotypes and virulence genes (VFs) were analyzed by submitting the genomes to the websites. Statistical analyses were performed to access the relationships among ARGs and plasmid replicons.
RESULTS
Until March 2023, 1,774 out of 33,055 isolates collected during 2003-2022 were found to contain blaNDM in total. Among them, 15 blaNDM variants were found with blaNDM-5 (74.1%) being most frequent, followed by blaNDM-1 (16.6%) and blaNDM-9 (4.6%). Among the 213 ARGs identified, 27 blaCTX-M and 39 blaTEM variants were found with blaCTX-M-15 (n = 438, 24.7%) and blaTEM-1B (n = 1092, 61.6%) being the most frequent ones, respectively. In addition, 546 (30.8%) plasmids mediated ampC genes, 508 (28.6%) exogenously acquired 16 S rRNA methyltransferase encoding genes and 262 (14.8%) mcr were also detected. Among the 232 distinct STs, ST167 (17.2%) were the most prevalent. As for plasmids, more than half of isolates contained IncFII, IncFIB and IncX3. The VF terC, gad, traT and iss as well as the serotypes O101:H9 (n = 231, 13.0%), O8:H9 (n = 115, 6.5%) and O9:H30 (n = 99, 5.6%) were frequently observed.
CONCLUSIONS
The study delves into the intricate relationship between plasmid types, virulence factors, and ARGs, which provides valuable insights for clinical treatment and public health interventions, and serves as a critical resource for guiding future research, surveillance, and implementation of effective strategies to address the challenges posed by blaNDM-carrying E. coli. The findings underscore the urgent need for sustained global collaboration, surveillance efforts, and antimicrobial stewardship to mitigate the impact of these highly resistant strains on public health.
Topics: Escherichia coli; beta-Lactamases; Escherichia coli Infections; Plasmids; Humans; Genome, Bacterial; Anti-Bacterial Agents; Microbial Sensitivity Tests; Genomics; Virulence Factors; Virulence; Global Health
PubMed: 38907245
DOI: 10.1186/s12941-024-00719-x -
BMC Complementary Medicine and Therapies Jun 2024This study explores the medicinal plant knowledge of the Baiku Yao, a unique ethnic group in China. Despite existing research on their ethnobotanical practices, a...
BACKGROUND
This study explores the medicinal plant knowledge of the Baiku Yao, a unique ethnic group in China. Despite existing research on their ethnobotanical practices, a comprehensive understanding of their medicinal flora remains lacking. This study aims to document and analyze the species distribution, utilization, and traditional knowledge of medicinal plants used by Baiku Yao.
METHODS
Ethnobotanical surveys were conducted in various Baiku Yao villages across different seasons from 2019 to 2023. Informants were interviewed, and plant specimens were collected and identified. Statistical analyses, including the Relative Frequency of Citation (RFC), were employed to understand plant importance in Baiku Yao culture.
RESULTS
In an ethnobotanical survey conducted in the Baiku Yao region, 434 medicinal plant species were documented, highlighting significant ethnobotanical diversity and a deep cultural integration of traditional medicinal practices. The study revealed pronounced geographical variations in plant knowledge among villages, with a notable reliance on wild plants, as 85.48% were sourced from the wild, reflecting unique local ethnobotanical knowledge. Predominantly herbs and shrubs were used due to their accessibility and abundance in the local environment. High Relative Frequency of Citation (RFC) values for certain species underscored their importance for local health needs and additional economic value. The utilization of various plant parts, particularly whole plants, roots, and leaves, indicates a holistic approach to medicinal applications, adapted to combat prevalent health issues such as skin and infectious diseases. The study also uncovered the Baiku Yao's cultural practices for countering "Gu" afflictions-a range of pathogenic conditions-with 18 diverse antidote plants used for skin, digestive, and musculoskeletal disorders. The study underscores the imperative of preserving this rich medicinal heritage through innovative models that engage youth and leverage new media, ensuring the inheritance and evolution of Baiku Yao's traditional knowledge.
CONCLUSIONS
Baiku Yao's medicinal plant use reflects a deep, culturally ingrained knowledge, closely tied to local ecology. The study highlights the importance of preserving this unique ethnobotanical heritage and suggests interdisciplinary approaches for future research.
Topics: Humans; China; Ethnicity; Ethnobotany; Health Knowledge, Attitudes, Practice; Medicine, Chinese Traditional; Plants, Medicinal; Surveys and Questionnaires
PubMed: 38907195
DOI: 10.1186/s12906-024-04545-8 -
Scientific Reports Jun 2024This paper explores the complex interplay between topological indices and structural patterns in networks of iron telluride (FeTe). We want to analyses and characterize...
This paper explores the complex interplay between topological indices and structural patterns in networks of iron telluride (FeTe). We want to analyses and characterize the distinct topological features of (FeTe) by utilizing an extensive set of topological indices. We investigate the relationship that these indicators have with the network's physical characteristics by employing sophisticated statistical techniques and curve fitting models. Our results show important trends that contribute to our knowledge of the architecture of the (FeTe) network and shed light on its physiochemical properties. This study advances the area of material science by providing a solid foundation for using topological indices to predict and analyses the behavior of intricate network systems. More preciously, we study the topological indices of iron telluride networks, an artificial substance widely used with unique properties due to its crystal structure. We construct a series of topological indices for iron telluride networks with exact mathematical analysis and determine their distributions and correlations using statistical methods. Our results reveal significant patterns and trends in the network structure when the number of constituent atoms increases. These results shed new light on the fundamental factors that influence material behavior, thus offering a deeper understanding of the iron telluride network and may contribute to future research and engineering of these materials.
PubMed: 38906950
DOI: 10.1038/s41598-024-65205-y