bluuebunny/crossref_metadata_2025_split huggingface dataset:
Take good care of your fish: fish re-identification with synchronized multi-view camera system
Authors: Fan Suzhen , Song Chengyang , Feng Haiyang , Yu Zhibin 
Published: November 2024

IntroductionFish re-identification (re-ID) is of great significance for fish monitoring and can contribute to aquaculture and fish breeding. Synchronizing information from different cameras is beneficial for optimizing re-ID performance.MethodsWe constructed the first underwater fish re-identification benchmark dataset (FS48) under three camera conditions. FS48 encompasses 48 different fish identities, 10,300 frames, and 39,088 bounding boxes, covering various lighting conditions and background environments. Additionally, we developed the first robust and accurate fish re-identification baseline, FSNet, which fuses information from three camera positions by extracting features from synchronized video frames of each position and combining the synchronized information.ResultsThe experimental results show that FS48 is universal and of high quality. FSNet has an effective network design and demonstrates good performance, achieving better re-identification performance by combining information from three positions, helping improve overall re-test accuracy, and evaluating the effectiveness of re-identification among detectors.DiscussionOur dataset will be released upon acceptance of this paper, which is expected to further promote the development of underwater fish re-identification.
Primary care physicians' attitudes, practices, and perceived barriers toward depression screening in older people in the Kingdom of Bahrain
Authors: Habbash Fatema , Khamis Zainab , Alasfoor Zahra , Mahdi Aayat , Alsharkhat Masooma , Hasan Noor , Al Qari Alaa , Chlif Sadok , Almarabheh Amer , Ben Salah Afif 
Published: November 2024

PurposeThis study aimed to explore attitudes, practices, and perceived barriers of primary care physicians (PCPs) toward depression screening in older people.MethodsThis cross-sectional study enrolled PCPs from randomly selected representative primary care centers in Bahrain. A self-administered piloted semi-structured questionnaire was used for data collection.ResultsWe enrolled 248 PCPs in the study (82.3% females, and the mean age = 40 ± 8.7 years). More than half of the participants (54.4%) had a positive attitude toward depression screening in older people. However, only 10.9% of the participants reported systematically screening for this condition without using specific tools for screening in 45.5%. The most reported barriers toward this service are short consultation time (95%), the presence of multiple co-morbidities in this age group (90%), and the absence of guidelines or appropriate training in around 30%. Positive attitudes were significantly higher among older PCPs (p = 0.039), family physician consultants (p = 0.008), those with more than 10 years of work experience (p = 0.024), and those who participated in related educational activities (p = 0.007). Under-screening practice is associated with perceived short consultation time (p = 0.002), insufficient continuous medical education (CME) activities attendance in older people's mental health (p = 0.048) as well as having a general physician's title (p = 0.049). Only the PCPs' job title, Adjusted Odds Ratio (OR) = 3.513, 95 C.I [1.225-10.074] and attendance of CME activities, OR = 1.278, 95 C.I [1.098 – 3.192] remained significant when controlled for age and experience.ConclusionMore training on older people's mental health and provision of screening and management guidelines are priorities to promote older people's mental health in primary care settings.
Construction of a disease risk prediction model for postherpetic pruritus by machine learning
Authors: Lin Zheng , Dou Yuan , Ju Ru-yi , Lin Ping , Cao Yi 
Published: November 2024

BackgroundPostherpetic itch (PHI) is an easily overlooked complication of herpes zoster that greatly affects patients' quality of life. Studies have shown that early intervention can reduce the occurrence of itch. The aim of this study was to develop and validate a predictive model through a machine learning approach to identify patients at risk of developing PHI among patients with herpes zoster, making PHI prevention a viable clinical option.MethodWe conducted a retrospective review of 488 hospitalized patients with herpes zoster at The First Affiliated Hospital of Zhejiang Chinese Medical University and classified according to whether they had PHI. Fifty indicators of these participants were collected as potential input features for the model. Features associated with PHI were identified for inclusion in the model using the least absolute shrinkage selection operator (LASSO). Divide all the data into five pieces, and then use each piece as a verification set and the others as a training set for training and verification, this process is repeated 100 times. Five models, logistic regression, random forest (RF), k-nearest neighbor, gradient boosting decision tree and neural network, were built in the training set using machine learning methods, and the performance of these models was evaluated in the test set.ResultsSeven non-zero characteristic variables from the Lasso regression results were selected for inclusion in the model, including age, moderate pain, time to recovery from rash, diabetes, severe pain, rash on the head and face, and basophil ratio. The RF model performs better than other models. On the test set, the AUC of the RF model is 0.84 [(95% confidence interval (CI): 0.80–0.88], an accuracy of 0.78 (95% CI: 0.69–0.86), a precision of 0.61 (95% CI: 0.45–0.77), a recall of 0.73 (95% CI: 0.58–0.89), and a specificity of 0.79 (95% CI: 0.70–0.89).ConclusionsIn this study, five machine learning methods were used to build postherpetic itch risk prediction models by analyzing historical case data, and the optimal model was selected through comparative analysis, with the random forest model being the top performing model.
Successful treatment of refractory palmoplantar pustulosis by upadacitinib: report of 28 patients
Authors: Du Na , Yang Jingyi , Zhang Yiwen , Lv Xinyan , Cao Lei , Min Wei 
Published: November 2024

BackgroundUpadacitinib, a specific JAK1 inhibitor, has minimal effect on other JAK subtypes. It influences the inflammatory process in various ways. Upadacitinib has been approved for conditions such as rheumatoid arthritis, psoriatic arthritis, atopic dermatitis, and ulcerative colitis in various countries. The purpose of this study is to assess the clinical efficacy and safety of upadacitinib in patients with refractory palmoplantar pustulosis who have not responded to conventional treatments (e.g., Acitretin, Tripterygium wilfordii Hook F, cyclosporine, methotrexate).MethodsWe conducted a retrospective collection of clinical data from 28 patients who received upadacitinib treatment at the Department of Dermatology, First Affiliated Hospital of Suzhou University, from July 2022 to December 2023. We evaluated the Palmoplantar Pustulosis Area and Severity Index (PPPASI) scores, Dermatology Life Quality Index (DLQI) scores, and Physician’s Global Assessment (PGA) scores before and after treatment. We also recorded any adverse events during the treatment process.ResultsA total of 28 patients were diagnosed with PPP, including 10 males and 18 females, and 8 patients (3 males and 5 females) were diagnosed with SAPHO syndrome. The mean age was (36.3 ± 10.5) years. After 12 weeks of treatment, PPPASI scores decreased from baseline (13.86 ± 2.76) to (5.56 ± 1.08), with a statistically significant difference (p &lt; 0.05). DLQI scores decreased from (12.55 ± 4.56) to (2.03 ± 1.13), also showing a statistically significant difference (p &lt; 0.05). Additionally, 20 patients achieved a PGA score of 0/1. No severe adverse events were reported during the treatment and follow-up period.ConclusionUpadacitinib could be an additional safe and effective treatment for treating refractory palmoplantar pustulosis with a potential benefit on patients’ quality of life. Further studies are needed to assess its short-and long-term efficacy and safety in larger sample sizes in randomized double-blind controlled trials.
Application of large language model combined with retrieval enhanced generation technology in digestive endoscopic nursing
Authors: Fu Zhaoli , Fu Siyuan , Huang Yuan , He Wenfang , Zhong Zhuodan , Guo Yan , Lin Yanfeng 
Published: November 2024

BackgroundAlthough large language models (LLMs) have demonstrated powerful capabilities in general domains, they may output information in the medical field that could be incorrect, incomplete, or fabricated. They are also unable to answer personalized questions related to departments or individual patient health. Retrieval-augmented generation technology (RAG) can introduce external knowledge bases and utilize the retrieved information to generate answers or text, thereby enhancing prediction accuracy.MethodWe introduced internal departmental data and 17 commonly used gastroenterology guidelines as a knowledge base. Based on RAG, we developed the Endo-chat medical chat application, which can answer patient questions related to gastrointestinal endoscopy. We then included 200 patients undergoing gastrointestinal endoscopy, randomly divided into two groups of 100 each, for a questionnaire survey. A comparative evaluation was conducted between the traditional manual methods and Endo-chat.ResultsCompared to ChatGPT, Endo-chat can accurately and professionally answer relevant questions after matching the knowledge base. In terms of response efficiency, completeness, and patient satisfaction, Endo-chat outperformed manual methods significantly. There was no statistical difference in response accuracy between the two. Patients showed a preference for AI services and expressed support for the introduction of AI. All participating nurses in the survey believed that introducing AI could reduce nursing workload.ConclusionIn clinical practice, Endo-chat can be used as a highly effective auxiliary tool for digestive endoscopic care.
Molecular characterization of wheat dwarf virus isolates from Serbia based on complete genome sequences
Authors: Stanković Ivana , Zečević Katarina , Ristić Danijela , Vučurović Ivan , Krstić Branka 
Published: November 2024

IntroductionWheat dwarf virus (WDV), the species Mastrevirus hordei of the genus Mastrevirus in the family Geminiviridae, is a cereal virus commonly detected in several European, African and Asian countries that causes economic losses.MethodsIn the spring of 2019, a severe outbreak of wheat dwarfing and yellowing was observed in many winter wheat crops across Serbia. A total of 161 samples were tested for the presence of WDV and other common wheat viruses using double-antibody sandwich enzyme-linked immunosorbent assay (DAS-ELISA). To obtain the complete genome of 23 selected isolates, several overlapping segments of the WDV genome were amplified and sequenced. A phylogenetic tree was constructed using the whole genome sequences of the WDV isolates identified in this study and 40 selected sequences from GenBank.Results and discussionThe results of DAS-ELISA indicated the presence of WDV in all samples collected from 21 sites in all nine districts surveyed. Further molecular characterization based on complete genome sequencing of 23 selected isolates showed that the Serbian WDV isolates had low nucleotide diversity and were closely related to wheat-infecting isolates from Europe, suggesting the presence of wheat-adapted forms of WDV in Serbia. The constructed phylogenetic tree revealed that Serbian isolates grouped in clade E within the wheat-adapted forms. This study provided the first insight into the genetic structure of WDV in Serbia based on its whole genome sequence. Further studies on the vector biology and population dynamics are needed to better understand the factors influencing the emergence and spread of WDV under local agroecological conditions.
Genome-wide comparative analysis of clinical and environmental strains of the opportunistic pathogen Paracoccus yeei (Alphaproteobacteria)
Authors: Szuplewska Magdalena , Sentkowska Dorota , Lasek Robert , Decewicz Przemysław , Hałucha Mateusz , Funk Łukasz , Chmielowska Cora , Bartosik Dariusz 
Published: November 2024

IntroductionParacoccus yeei is the first species in the genus Paracoccus to be implicated in opportunistic infections in humans. As a result, P. yeei strains provide a valuable model for exploring how bacteria shift from a saprophytic to a pathogenic lifestyle, as well as for investigating the role of horizontally transferred DNA in this transition. In order to gain deeper insights into the unique characteristics of this bacterium and the molecular mechanisms underlying its opportunistic behavior, a comparative physiological and genomic analysis of P. yeei strains was performed.ResultsComplete genomic sequences of 7 P. yeei isolates (both clinical and environmental) were obtained and analyzed. All genomes have a multipartite structure comprising numerous extrachromosomal replicons (59 different ECRs in total), including large chromids of the DnaA-like and RepB families. Within the mobile part of the P. yeei genomes (ECRs and transposable elements, TEs), a novel non-autonomous MITE-type element was identified. Detailed genus-wide comparative genomic analysis permitted the identification of P. yeei-specific genes, including several putative virulence determinants. One of these, the URE gene cluster, determines the ureolytic activity of P. yeei strains—a unique feature among Paracoccus spp. This activity is induced by the inclusion of urea in the growth medium and is dependent on the presence of an intact nikR regulatory gene, which presumably regulates expression of nickel (urease cofactor) transporter genes.DiscussionThis in-depth comparative analysis provides a detailed insight into the structure, composition and properties of P. yeei genomes. Several predicted virulence determinants (including URE gene clusters) were identified within ECRs, indicating an important role for the flexible genome in determining the opportunistic properties of this bacterium.
First report on the physicochemical and proteomic characterization of Proteus mirabilis outer membrane vesicles under urine-mimicking growth conditions: comparative analysis with Escherichia coli
Authors: González María José , Navarro Nicolás , Cruz Erlen , Sánchez Sofía , Morales Javier O. , Zunino Pablo , Robino Luciana , Lima Analía , Scavone Paola 
Published: November 2024

IntroductionUropathogenic bacteria employ multiple strategies to colonize the urinary tract, including biofilm formation, invasion of urothelial cells, and the production of adhesins, toxins, and siderophores. Among the most prevalent pathogens causing urinary tract infections (UTIs) are Uropathogenic Escherichia coli and Proteus mirabilis. A notable feature of Gram-negative bacteria is their ability to produce outer membrane vesicles (OMVs), which play critical roles in bacterial survival, virulence, and host-pathogen interactions, including UTIs.MethodsIn this study, OMVs were isolated and characterized from two clinical strains, E. coli U144 and P. mirabilis 2,921, cultured in both Luria-Bertani broth and artificial urine.Result and discussionThe OMVs ranged in size from 85 to 260 nm, with the largest vesicles observed in artificial urine. Proteomic analysis allowed the identification of 282 proteins in OMVs from E. coli and 353 proteins from P. mirabilis when cultured LB medium, while 215 were identified from E. coli and 103 from P. mirabilis when cultured in artificial urine. The majority of these proteins originated from the bacterial envelope, while others were linked to motility and adhesion. Notably, the protein composition of OMVs varied depending on the growth medium, and proteins associated with zinc and iron uptake being more prominent in artificial urine, suggesting their importance in the urinary environment. Crucially, this is the first report to characterize P. mirabilis OMVs under different culture conditions, offering novel insights into the role of OMVs in UTI pathogenesis. These findings provide a deeper understanding of the molecular mechanisms by which OMVs contribute to bacterial virulence, establishing the foundation for potential therapeutic interventions targeting OMV-mediated processes in UTIs.
Correlation between oxygenation function and laboratory indicators in COVID-19 patients based on non-enhanced chest CT images and construction of an artificial intelligence prediction model
Authors: Kong Weiheng , Liu Yujia , Li Wang , Yang Keyi , Yu Lixin , Jiao Guangyu 
Published: November 2024

ObjectiveBy extracting early chest CT radiomic features of COVID-19 patients, we explored their correlation with laboratory indicators and oxygenation index (PaO2/FiO2), thereby developed an Artificial Intelligence (AI) model based on radiomic features to predict the deterioration of oxygenation function in COVID-19 patients.MethodsThis retrospective study included 384 patients with COVID-19, whose baseline information, laboratory indicators, oxygenation-related parameters, and non-enhanced chest CT images were collected. Utilizing the PaO2/FiO2 stratification proposed by the Berlin criteria, patients were divided into 4 groups, and differences in laboratory indicators among these groups were compared. Radiomic features were extracted, and their correlations with laboratory indicators and the PaO2/FiO2 were analyzed, respectively. Finally, an AI model was developed using the PaO2/FiO2 threshold of less than 200 mmHg as the label, and the model’s performance was assessed using the area under the receiver operating characteristic curve (AUC), sensitivity and specificity. Group datas comparison was analyzed using SPSS software, and radiomic features were extracted using Python-based Pyradiomics.ResultsThere were no statistically significant differences in baseline characteristics among the groups. Radiomic features showed differences in all 4 groups, while the differences in laboratory indicators were inconsistent, with some PaO2/FiO2 groups showed differences and others not. Regardless of whether laboratory indicators demonstrated differences across different PaO2/FiO2 groups, they could all be captured by radiomic features. Consequently, we chose radiomic features as variables to establish an AI model based on chest CT radiomic features. On the training set, the model achieved an AUC of 0.8137 (95% CI [0.7631–0.8612]), accuracy of 0.7249, sensitivity of 0.6626 and specificity of 0.8208. On the validation set, the model achieved an AUC of 0.8273 (95% CI [0.7475–0.9005]), accuracy of 0.7739, sensitivity of 0.7429 and specificity of 0.8222.ConclusionThis study found that the early chest CT radiomic features of COVID-19 patients are strongly associated not only with early laboratory indicators but also with the lowest PaO2/FiO2. Consequently, we developed an AI model based on CT radiomic features to predict deterioration in oxygenation function, which can provide a reliable basis for further clinical management and treatment.
Optimal time for the addition of non-corticosteroid immunosuppressants in myasthenia gravis: a single-center retrospective study in China
Authors: Ma Jiaojiao , Chen Dan , Yi Fangfang , Song Jie , Luo Sushan , Zhong Huahua , Xi Jianying , Wu Zongtai , Li Zunbo , Zhao Chongbo 
Published: November 2024

IntroductionPatients with myasthenia gravis (MG) display strong treatment heterogeneity. Recent studies have indicated that low-dose steroids or immunosuppressants are effective. However, factors affecting the add-on of non-corticosteroid immunosuppressants to corticosteroids remain unknown.MethodConsecutive patients with MG were retrospectively reviewed from May 15, 2015, to December 29, 2020. We included one group of patients with steroid treatment alone and another group who transitioned to non-steroid immunosuppressant therapy. Clinical features of the included patients were analyzed. Univariate and multivariate Cox regression models were used to identify potential influential factors.ResultsA total of 107 patients with MG were analyzed, including 66 receiving corticosteroid treatment alone and 41 who subsequently also received non-corticosteroid immunosuppressant therapy. Eight potential factors were primarily selected in univariate analysis (Ps &lt; 0.1). Achieving minimal symptom expression (MSE) within 6 months (HR: 4.424, 95%CI: 2.102–11.865), body mass index (BMI) (HR: 0.385, 95% CI: 0.186–0.797), quantitative MG (QMG) bulbar muscle score (HR: 1.553, 95% CI: 1.140–2.118), disease duration (HR: 0.987, 95% CI: 0.977–0.997) and relapse (HR: 2.638, 95% CI: 1.031–6.750) were finally identified as potential influencing factors.DiscussionWe found multifactorial clinical factors were highly associated with the add-on of non-steroid immunosuppressants after steroid treatment in patients with MG. Achieving MSE within 6 months, BMI, QMG bulbar muscle score at baseline before steroid treatment, disease duration, and disease relapse may represent crucial influencing factors, which should be considered to improve the long-term prognosis for patients with MG in future studies and practice.
A comparison of natalizumab’s effects on SDMT between pediatric-onset and adult-onset multiple sclerosis patients
Authors: Puthenparampil Marco , Scialpi Graziana , Gaggiola Marta , Zanotelli Giovanni , Miscioscia Alessandro , Berardi Angela , Riccardi Alice , Nosadini Margherita , Sartori Stefano , Perini Paola , Rinaldi Francesca , Gallo Paolo 
Published: November 2024

BackgroundPediatric-onset multiple sclerosis (POMS) patients often exhibit a wide range of cognitive deficits. Therefore, therapeutic approaches should aim not only to prevent cognitive decline but also to promote cognitive improvement.ObjectiveThis study aimed to explore the effects of natalizumab (NTZ) on cognitive function, as measured by the Symbol Digit Modalities Test (SDMT), in both POMS and adult-onset multiple sclerosis (AOMS) patients.MethodA total of 63 patients (34 AOMS and 29 POMS) were enrolled in this retrospective, single-center study. Patients were clinically and radiologically assessed every 6 months, and they completed the SDMT at baseline and after at least 24 months of follow-up. SDMT values were reported as corrected values (cSDMT) and z-scores (zSDMT). Annualized cSDMT and zSDMT scores were calculated by dividing the change in scores by the length of the follow-up period (expressed in years).ResultsBoth POMS and AOMS groups showed improvement in annualized cSDMT and zSDMT scores, but the improvement was significantly greater in the POMS group compared to the AOMS group (+3.85 ± 4.32 vs. +1.76 ± 2.80, p = 0.010 for cSDMT; 0.41 ± 0.40 vs. 0.25 ± 0.34, p = 0.026 for zSDMT). After re-baselining at 6 months, 93% of POMS patients (27 patients) and 85.3% of AOMS patients (29 patients, p = 0.84) achieved NEDA-3 (no evidence of disease activity). The NEDA-3 status, along with clinical and demographic parameters at baseline, did not account for the observed SDMT improvement.ConclusionThe favorable clinical, radiological, and neuropsychological outcomes observed in this study support the use of natalizumab as a viable treatment option in POMS.