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Identifying opioid agonist treatment prescriber networks from health administrative data: A validation study
Background Given the growth of collaborative care strategies for people with opioid use disorder and the changing composition of the illicit drug supply, there is a need to identify and analyze clinic-level outcomes for centers prescribing opioid agonist treatment (OAT). We aimed to determine and validate whether prescriber networks, constructed with administrative data, can successfully identify distinct clinical practice facilities in Ontario, Canada. Methods We executed a retrospective population-based cohort study using OAT prescription records from the Canadian Addiction Treatment Centres in Ontario, Canada between 01/01/2013 and 12/31/2020. Social network analysis was utilized to create networks with connections between physicians based on their shared OAT clients. We defined connections two different ways, by including the number of clients shared or a relative threshold on the percentage of shared OAT clients per physician. Clinics were identified using modularity maximization, with sensitivity analyses applying Louvain, Walktrap, and Label Propagation algorithms. Concordance between network-identified facilities and the (gold standard) de-identified facility-level IDs was assessed using overall, positive and negative agreement, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). Results From 144 physicians at 105 clinics with 32,842 OAT clients, we assessed 250 different versions of the created networks. The three different detection algorithms had wide variation in concordance, with ranges on sensitivity from 0.02 to 0.88 and PPV from 0.06 to 0.97. The optimal result, derived from the modularity maximization method, achieved high specificity (0.98, 95% CI: 0.98, 0.98) and NPV (0.98, 95% CI: 0.97, 0.98) and moderate PPV (0.54, 95% CI: 0.52, 0.57) and sensitivity (0.45, 95% CI: 0.43, 0.47). This scenario had an overall agreement of 0.96, negative agreement of 0.98, and positive agreement of 0.49. Conclusions Social network analysis can be used to identify clinics prescribing OAT in the absence of clinic-level identifiers, thus facilitating construction and comparison of clinic-level caseloads and treatment outcomes.
Weighting health-related estimates in the GCAT cohort and the general population of Catalonia
The probability of reducing hospitalization rates for bronchiolitis with epinephrine and dexamethasone: A Bayesian analysis
Background Bronchiolitis exerts a high burden on children, their families and the healthcare system. The Canadian Bronchiolitis Epinephrine Steroid Trial (CanBEST) assessed whether administering epinephrine alone, dexamethasone alone, or in combination (EpiDex) could reduce bronchiolitis-related hospitalizations among children less than 12 months of age compared to placebo. CanBEST demonstrated a statistically significant reduction in 7-day hospitalization risk with EpiDex in an unadjusted analysis but not after adjustment. Objective To explore the probability that EpiDex results in a reduction in hospitalizations using Bayesian methods. Study design Using prior distributions that represent varying levels of preexisting enthusiasm or skepticism, i.e., how confident or doubtful one is that EpiDex may reduce hospitalizations, and information about the treatment effect before data were collected, the posterior distribution of the relative risk of hospitalization compared to placebo was determined. The probability that the treatment effect is less than 1, 0.9, 0.8 and 0.6, indicating increasing reductions in hospitalization risk, are computed alongside 95% credible intervals. Results Combining a minimally informative prior distribution with the data from CanBEST provides comparable results to the original analysis. Unless strongly skeptical views about the effectiveness of EpiDex were considered, the 95% credible interval for the treatment effect lies below 1, indicating a reduction in hospitalizations. There is a 90% probability that EpiDex results in a clinically meaningful reduction in hospitalization of 10% even when incorporating skeptical views, with a 67% probability when considering strongly skeptical views. Conclusion A Bayesian analysis demonstrates a high chance that EpiDex reduces hospitalization rates for bronchiolitis, although strongly skeptical individuals may require additional evidence to change practice. Trial registration Clinical Trial registry name, registration number: Current Controlled Trials number, ISRCTN56745572
Enhancing Shiga toxin detection using surface plasmon resonance a study of antibody immobilization strategies
Abstract This study demonstrates enhanced detection of Shiga toxin (Stx), a key virulence factor in Shigella dysenteriae-induced bloody diarrhea, through optimized surface plasmon resonance (SPR) biosensor design. We present a comparative evaluation of antibody immobilization strategies, revealing significant advantages of protein G-mediated oriented immobilization over conventional covalent attachment. The covalent (non-oriented) approach using 11-mercaptoundecanoic acid-modified chip showed moderate performance (KD = 37 nM, LOD = 28 ng/mL). In contrast, protein G-assisted orientation dramatically improved detection capabilities, achieving a 2.9-fold lower detection limit (9.8 ng/mL) and 2.3-fold higher binding affinity (KD = 16 nM). Control measurements with free antibody-antigen interactions established a baseline affinity (KD = 10 nM), demonstrating that the oriented method preserves 63% of native binding efficiency versus only 27% in the covalent approach. Mechanistic studies attribute these improvements to protein G’s ability to maintain optimal antibody orientation, thereby: (1) maximizing paratope accessibility, (2) minimizing steric interference, and (3) preserving binding site functionality. The 57% reduction in KD relative to covalent immobilization confirms the method’s efficacy in maintaining antibody performance post-immobilization. These findings establish protein G-mediated orientation as the superior strategy for SPR-based Stx detection, offering substantial improvements in sensitivity and reliability for clinical diagnostics and food safety applications. The approach demonstrates particular promise for rapid, label-free detection of bacterial toxins in resource-limited settings.
Evaluation for the operational risk factors of public transportation process based on entropy weighted- DEMATEL method
Identifying and assessing the key factors that influence the operations of public transportation from an operational risk perspective is a critical challenge. In this paper, in order to tackle this issue by dissecting 18 risk factors through a comprehensive lens that encompasses five dimensions of the public transportation operation: infrastructure completeness, operational procedures, management practices, process requirements, and risk mitigation strategies, each with its respective evaluative metrics. To offer a nuanced analysis of these risk factors, we introduce an entropy weight-based DEMATEL (Decision-Making Trial and Evaluation Laboratory) method. This approach leverages the entropy weight decision-making process to quantify the significance of each risk factor, acknowledging the inherent uncertainties in the evaluation process. By applying the DEMATEL method to the collected data, it becomes evident that safety consciousness stands out as a pivotal factor, with human initiative emerging as a central element in the operational flow of public transportation. Furthermore, our study reveals that substantial funding, technological advancements, regular inspections, and stringent regulations are critical risk factors that warrant considerable attention in the management of public transportation operations. The findings underscore the necessity for a multifaceted approach to risk management to bolster the safety and efficiency of public transportation services. To foster a safer and more effective public transportation system, it is imperative for stakeholders to not only heighten their vigilance regarding safety but also to ensure that adequate financial resources and regulatory frameworks are in place. Only through a holistic and multidimensional risk management strategy can we hope to minimize the incidence of public safety risks.
Entanglement dynamics in a three-atom multi-photon nonlinear JCM with f-deformed Kerr nonlinearity
An efficient leukemia prediction method using machine learning and deep learning with selected features
Leukemia is a serious problem affecting both children and adults, leading to death if left untreated. Leukemia is a kind of blood cancer described by the rapid proliferation of abnormal blood cells. An early, trustworthy, and precise identification of leukemia is important to treating and saving patients’ lives. Acute and myelogenous lymphocytic, chronic and myelogenous leukemia are the four kinds of leukemia. Manual inspection of microscopic images is frequently used to identify these malignant growth cells. Leukemia symptoms include fatigue, a lack of enthusiasm, a dull appearance, recurring illnesses, and easy blood loss. Identifying subtypes of leukemia for specialized therapy is one of the hurdles in this area. The suggested work predicts and classifies leukemia subtypes in gene data CuMiDa (GSE9476) using feature selection and ML techniques. The Curated Microarray Database (CuMiDa) collected 64 samples representing five classes of leukemia genes out of 22283 genes. The proposed approach utilizes the 25 most differentiating selected features for classification using machine and deep learning techniques. This study has a classification accuracy of 96.15% using Random Fores, 92.30 using Linear Regression, 96.15% using SVM, and 100% using LSTM. Deep learning methods have been shown to outperform traditional methods in leukemia gene classification by utilizing specific features.
Comparison of RNA- and DNA-based 16S amplicon sequencing to find the optimal approach for the analysis of the uterine microbiome
Abstract Studies in humans and large animals indicate a relationship between the uterine microbiome composition and endometrial receptivity. Despite many studies have been performed, the analysis of the uterine microbiome remains challenging due to the very low microbial biomass. Studies in other biological systems showed that RNA-based microbiome analysis complements DNA-based results and provides information about active bacteria in a sample. Thus, the aim of this study was to establish a highly sensitive and specific 16S rRNA gene V3-V4 amplicon PCR from equine uterine cytobrush samples and to compare DNA- and RNA-based 16S rRNA microbiome analysis. An optimized 16S rRNA gene V3-V4 amplicon PCR protocol from equine uterine cytobrush samples was developed, which was able to detect less than 38 bacterial genome copies using a bacterial DNA community standard. For the RNA-based amplicon generation protocol starting from cDNA, at least a 10-fold higher sensitivity was estimated compared to DNA-based approach. The comparison of using RNA and DNA isolated from the same uterine cytobrush samples as input for 16S V3-V4 amplicon sequencing revealed a much higher number of amplicon sequence variants as well as taxonomic units for the RNA-based approach. This resulted in significant differences in alpha (Simpson, Chao1) and beta diversity between RNA- and DNA-based analysis. Differential abundance analysis revealed significant differences between DNA and RNA samples at all taxonomic levels. Despite these differences, the overall microbiome composition was similar between the paired DNA and RNA samples. Many differences were probably found due to the higher sensitivity of the RNA-based approach. Furthermore, the DNA-based analysis is biased by the rRNA gene copy numbers (1–21), and the RNA-based analysis by the number of ribosomes per cell, which was reflected in the differences in the microbiome composition between the approaches. In addition, the results suggested that the DNA-based analysis is detecting cell-free bacterial DNA and/or DNA of dead bacteria that could be present in the samples. Altogether, the obtained results indicate advantages of a combined DNA- and RNA-based microbiome analysis, offering complementary and valuable information in the context of fertility-related studies of the uterine microbiome.
Parent-mediated interventions versus usual care in children with autism spectrum disorders: A protocol for a systematic review with meta-analysis and Trial Sequential Analysis
Introduction Autism spectrum disorder encompasses diverse patterns of social communication and repetitive, restricted behaviours. Various interventions have been developed to reduce the negative consequences of this disorder and improve levels of functioning, and recently interest in parent-mediated interventions has increased. Previous reviews and meta-analyses have investigated the effects of the parent-mediated interventions, however; a systematic review with meta-analysis of high quality has not been performed since 2013. This protocol for a systematic review with meta-analysis aims to describe the methods and purpose of synthesising current evidence regarding the effects (both positive and adverse) of parent-mediated interventions in both children with autism and their parents. Methods Electronic searches will be conducted in Cochrane Central Register of Controlled Trials (CENTRAL), Medical Literature Analysis and Retrieval System Online (MEDLINE), Excerpta Medica database (EMBASE), Latin American and Caribbean Health Sciences Literature (LILACS), American Psychological Association PsycInfo (PsycInfo) and Science Citation Index Expanded (SCI-EXPANDED). Randomised clinical trials of parent-mediated interventions for children with autism and control groups of usual care, waiting list or no treatment will be included. Two reviewers will independently screen, select and collect data. Methodological quality of included studies will be evaluated using Cochrane methodology. The primary outcome will be autism symptom severity as measured by the Autism Diagnostic Observation Schedule. Secondary outcomes will be adaptive functioning, adverse effects, child language, child´s quality of life, parental quality of life and parental stress. Meta-analyses and Trial Sequential Analysis will be performed. Discussion This is the study protocol for a systematic review and meta-analysis of parent-mediated interventions versus usual care for children with ASD. Results of the review will inform clinicians and parents about the current evidence of the effects, both positive and negative, of parent-mediated interventions on younger children with autism and their parents, through improved methodology and inclusion of new studies. PROSPERO registration number: 385188
Unknown intrusion traffic detection method based on unsupervised learning and open-set recognition
Chemotherapy-related adverse drug reaction and associated factors among adult cancer patient attending Jimma medical center oncology unit, Southwest Ethiopia
Background In 2017, reports of adverse drug reactions worldwide reached an estimated 35 million.Chemotherapeutic agents were one of the most often implicated pharmacological classes in inducing adverse drug reactions. Adverse drug reactions increase the overall expense and mortality. Adverse drug reactions increase morbidity, mortality, hospitalization rate and financial expenses. Therefore, this study intended to assess chemotherapy-related adverse drug reactions and associated factors among adult cancer patients. Patients and method A facility-based prospective observational study was conducted from July 2022 to October 2022 at Jimma Medical Center’s oncology unit. A standard data collection tool (Naranjo’s algorithm, modified Hartwig’s severity scale, and modified Schumock-Thornton criteria) was used for assessment of causality, severity, and preventability of adverse reactions, respectively. Socio-demographic profile and any adverse drug reactions reported were collected separately. The data was collected by one pharmacist and two nurses after giving training. Data was entered into Epidata version 4.6.0 and analyzed by SPSS version 25. Bivariate and multivariable logistic regression was conducted to identify independent predictors of the pattern of adverse drug reaction occurrence. A P-value of 0.05 was taken as statistically significant. Result Out of 154 patients enrolled in the study, 66.2% were female. The mean age of patients was 41.20 ± 13.54 years. From the total, 98 (63.6%) cases developed a total of 198 adverse drug reactions. Out of them, 59.2% were female. The most commonly encountered adverse drug reactions were nausea and vomiting (33.8%) and hair loss (29.3%). Most of the reactions were probable (61.1%) in causality, mild (66.2%) in severity, and not preventable (43.9%) in nature. Female sex (AOR = 1.054; 95% CI= (1.021–1.087); P = 0.001), number of chemotherapy treatments (AOR = 3.33; 95% CI= (1.301–8.52); P = 0.012), and elderly age (AOR = 3.065; 95% CI= (1.01–9.296); P = 0.048) were associated with occurrences of adverse drug reactions. Conclusion We can deduce from the data that adverse drug reactions are a significant concern for patients undergoing chemotherapy, with nearly two-thirds experiencing ADRs. The most common reactions are nausea and vomiting, which are mostly mild and probable. Age, gender, and the use of several chemotherapy drugs were associated with an increased risk of adverse drug reactions. Hence all concerned bodies should make an effort for early detection and take preventive measure of chemotherapy-related adverse drug reactions. Where feasible, use chemotherapy protocols with alower risk of ADRs. Evaluate dose adjustments for elderly patients. Implement protocols for risk assessment before initiating chemotherapy.
On the optimal layout of (Kp − Cp)n into grid and certain structures
Abstract Interconnection networks constitute complex configurations of processors and communication links that facilitate data transmission between processors in a parallel computing system. Their architecture and design heavily depend on parameters such as wirelength, dilation, bandwidth, and minimum cutwidth. The process of constructing layouts on a board using the necessary modules determines the manufacturing cost in computer networks, where knowledge of graph embedding serves as an integral tool. Placement problems associated with circuit designs, for which no deterministic techniques exist, can be addressed by obtaining the optimal architecture through the embedding function. This article focuses on embedding the guest graph (K p − C p ) n into various host graphs, including the grid, generalized book graph, triangular snake, and variants of the banana tree. Furthermore, their optimal wirelengths are also obtained.
The neuronal chaperone proSAAS is highly expressed in the retina
The many layers of the neuroretina contain a complex, interconnected network of specialized neurons that both process visual stimuli and conduct processed information to higher brain areas. Neural networks rely on proteostatic control mechanisms to maintain proper protein homeostasis both in cell bodies as well as within synapses; protein chaperones play an important role in regulating and supporting this process. ProSAAS is a small neuronal chaperone that functions as an anti-aggregant in in vitro assays and is released upon depolarization in neuronal primary cultures. We here report a potential role for proSAAS in the retina. A review of human and mouse retinal RNAseq studies reveals that proSAAS expression is abundant within the retina. Single cell sequencing data from mouse and human studies show that proSAAS levels are highest in retinal ganglion cells (RGCs) and horizontal cells. Using proSAAS antibodies in combination with antisera to known retinal cell markers in mouse retinal sections, we confirm RNAseq data showing that proSAAS expression is highest in RGCs and horizontal cells. The proSAAS signal is concentrated within the ganglion cell layer and the inner plexiform layer, a dense synaptic layer connecting retinal neurons. Western blotting of mouse retinal extracts indicates the presence of two processed proSAAS forms, a 21 kDa C-terminally processed form, and a small 13 kDa species which, based on antibody specificity, likely represents an internal fragment. This fragment is also found in extracts prepared from human retinas. Taken together, our data provide support for the hypothesis that retinal synapses utilize the proSAAS chaperone to support visual signaling.
Deep learning progressive distill for predicting clinical response to conversion therapy from preoperative CT images of advanced gastric cancer patients
Distribution analysis of the finless porpoises (Neophocaena sp.) and oceanic dolphins (Delphinidae) in the Korean Sea using environmental DNA
Environmental DNA (eDNA) serves as a non-invasive tool for monitoring the presence of specific organisms in challenging or hard-to-access areas. We attempted non-invasive monitoring of Korean cetacean species by extracting eDNA from the western and southern seas of the Republic of Korea, as well as around Jeju Island. In the present study, we focused on two representative cetaceans of the Korean Sea: the narrow-ridged finless porpoise (Neophocaena asiaeorientalis sunameri) and oceanic dolphins (Family Delphinidae). When selecting polymerase chain reaction primers, mitochondrial DNA (mtDNA) of N. asiaeorientalis and microsatellite Slo4 of oceanic dolphins were identified as the most effective gene sequences in high abundance in low concentration eDNA samples, using tissue samples for eDNA detection of the target species. A total of 139 samples were collected, and eDNA was detected from finless porpoises (Neophocaena sp.) in 94 samples (68%) and from oceanic dolphins in 50 samples (36%). Significantly, eDNA revealed the considerable presence of finless porpoise around Jeju Island, despite a lack of visual confirmation. In the Yellow Sea, eDNA primarily detected the presence of common dolphin (Delphinus delphis), orca (Orcinus orca), and Indo-Pacific bottlenose dolphin (Tursiops aduncus). Indo-Pacific bottlenose dolphins were identified along the coast of Jeju Island. The value of this research lies in being the first attempt to explore cetacean eDNA across various species in Korea. Further cetacean eDNA research should focus on developing metabarcoding primers capable of detecting a greater variety of cetacean species and primers for detecting specific porpoise species. This study will serve as a valuable reference for future studies.
Genetic and imaging features of CADASIL patients with acute ischemic stroke
What is the lifetime cost of alcohol consumption? an estimation of economic burden in Thailand
This study aimed to estimate the lifetime cost of alcohol consumption per individual drinker in Thailand to support policy formulation. Using an incidence-based cost-of-illness (COI) approach, a hybrid model combining a decision tree and a Markov model, incorporating six major alcohol-related diseases and conditions (i.e., hypertension, hemorrhagic stroke, liver cirrhosis, liver cancer, alcohol use disorders, and road injuries), was employed to analyze both direct costs (i.e., direct medical, direct nonmedical, property damage) and indirect costs (i.e., absenteeism, premature mortality). All costs were reported in Thai baht 2022 (35.06 THB = 1US$). From a societal perspective, the lifetime costs for individual male and female drinker were estimated at 721,344 THB (95% CI: 687,910–754,779) and 263,812 THB (95% CI: 249,250–278,374), respectively. Quitting earlier reduced costs significantly, with average quitting ages resulting in the cost of 568,932 THB for males and 115,167 THB for females. On average, each Thai drinker incurs a cost of 498,196 THB. These findings highlight the substantial economic burden of alcohol consumption in Thailand, underscoring the critical need for effective interventions and policies, along with more rigorous enforcement of current regulations aimed at encouraging early cessation and preventing the initiation of drinking, such as through advertising bans, sales restrictions, improving access to counseling and treatment.
Global trends and burden of brain and central nervous system cancers in adolescents and young adults GBD 2021 study
Evaluating the effectiveness of a population-level health intervention to increment HCV treatment coverage in tuscany region, Italy: An interrupted time series analysis
Worldwide, an estimated 57.8 million people are chronically infected with the Hepatitis C virus (HCV). The advent of direct-acting antivirals (DAAs) has made possible the definition of elimination targets by 2030. This study aimed to evaluate the effectiveness of a population-level health intervention to expand access to HCV treatment in the Tuscany Region, Italy. We used individual-level administrative data from the Tuscany region, collected between January 2015 and December 2022. Data include monthly observations on i) the number of serological tests to detect HCV, ii) the number of PCR tests to detect HCV and, iii) the number of prescriptions of direct-acting antivirals against HCV. We implemented an Interrupted Time Series (ITS) model, where the primary outcome was the number of monthly prescriptions of direct-acting antivirals, while the number of tests to detect HCV were included as control variables. The analysis was implemented i) in the general population, ii) in specific sub-population groups. Results show that the health intervention promoted by the Tuscany Regional Health Authority was highly effective in increasing DAAs treatment coverage in the general population, while no significant effects were observed among sub-population groups. Findings of this study provide evidence to support policies at national and subnational levels to booster HCV screening and simplify access to DAA prescriptions.