bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluating the effects of temperature and agitation on biofilm formation of bacterial pathogens isolated from raw cow milk
Authors: Alabdullatif Meshari 
Published: July 2024

Abstract
Objectives
To study the effect of agitation and temperature on biofilm formation (cell aggregates embedded within a self-produced matrix) by pathogenic bacteria isolated from Raw cow milk (RCM).

Methods
A 40 RCM samples were gathered from eight dairy farms in Riyadh, Saudi Arabia. After bacterial culturing and isolation, gram staining was performed, and all pathogenic, identified using standard criteria established by Food Standards Australia New Zealand (FSANZ), and non-pathogenic bacteria were identified using VITEK-2 and biochemical assays. To evaluate the effects of temperature and agitation on biofilm formation, isolated pathogenic bacteria were incubated for 24 h under the following conditions: 4 °C with no agitation (0 rpm), 15 °C with no agitation, 30 °C with no agitation, 30 °C with 60 rpm agitation, and 30 °C with 120 rpm agitation. Then, biofilms were measured using a crystal violet assay.

Results
Of the eight farm sites, three exhibited non-pathogenic bacterial contamination in their raw milk samples. Of the total of 40 raw milk samples, 15/40 (37.5%; from five farms) were contaminated with pathogenic bacteria. Overall, 346 bacteria were isolated from the 40 samples, with 329/346 (95.1%) considered as non-pathogenic and 17/346 (4.9%) as pathogenic. Most of the isolated pathogenic bacteria exhibited a significant (p < 0.01) increase in biofilm formation when grown at 30 °C compared to 4 °C and when grown with 120 rpm agitation compared to 0 rpm.

Conclusion
Herein, we highlight the practices of consumers in terms of transporting and storing (temperature and agitation) can significantly impact on the growth of pathogens and biofilm formation in RCM.
Genomic characterization of multi drug resistant ESBL-producing Escherichia coli isolates from patients and patient environments in a teaching hospital in Ghana
Authors: Asare Yeboah Esther Eyram , Agyepong Nicholas , Mbanga Joshua , Amoako Daniel Gyamfi , Abia Akebe Luther King , Ismail Arshad , Owusu-Ofori Alexander , Essack Sabiha Yusuf 
Published: July 2024

Abstract
Background
ESBL-producing Escherichia coli pose a growing health risk in community and healthcare settings. We investigated the resistome, virulome, mobilome, and genetic relatedness of multidrug-resistant (MDR) E. coli isolates from patients and their environment in a Ghanaian teaching hospital.

Materials and methods
Twenty-three MDR ESBL-producing or carbapenem-resistant E. coli isolates from a collection of MDR Gram-negative bacteria (GNB) from patients and environments were selected for genomic analyses. Whole genome sequencing and bioinformatics tools were used to analyze genomic characteristics and phylogeny.

Results
The prevalence and incidence of rectal carriage of ESBL E. coli among patients were 13.65% and 11.32% respectively. The β-lactamase genes, blaTEM−1B (10 isolates) and blaCTX−M−15 (12 isolates) were commonly associated with IncFIB plasmid replicons and co-occurred with aminoglycoside, macrolide, and sulfamethoxazole/trimethoprim resistance. Insertion sequences, transposons, and class I integrons were found with blaCTX−M−15. Carriage and environmental isolates carried multiple virulence genes, with terC being the most prevalent in 21 isolates. Seventeen sequence types (STs) were identified, including a novel ST (ST13846). Phylogenetic analysis grouped the isolates into four main clusters, with one outlier. High genetic relatedness was observed between two carriage isolates of ST940 and between a carriage isolate and an environmental isolate of ST648. Isolates with different STs, collected at different times and locations, also showed genetic similarities.

Conclusion
We identified ESBL-producing E. coli with diverse genomic characteristics circulating in different hospital directorates. Clonal relatedness was observed among isolates from patients and the environment, as well as between different patients, suggesting transmission within and between sources.
Proposal and validation of a new approach in tele-rehabilitation with 3D human posture estimation: a randomized controlled trial in older individuals with sarcopenia
Authors: He Shichun , Meng Deyu , Wei Meiqi , Guo Hongzhi , Yang Guang , Wang Ziheng 
Published: July 2024

Abstract
Objective
Through a randomized controlled trial on older adults with sarcopenia, this study compared the training effects of an AI-based remote training group using deep learning-based 3D human pose estimation technology with those of a face-to-face traditional training group and a general remote training group.

Methods
Seventy five older adults with sarcopenia aged 60–75 from community organizations in Changchun city were randomly divided into a face-to-face traditional training group (TRHG), a general remote training group (GTHG), and an AI-based remote training group (AITHG). All groups underwent a 3-month program consisting of 24-form Taichi exercises, with a frequency of 3 sessions per week and each session lasting 40 min. The participants underwent Appendicular Skeletal Muscle Mass Index (ASMI), grip strength, 6-meter walking pace, Timed Up and Go test (TUGT), and quality of life score (QoL) tests before the experiment, during the mid-term, and after the experiment. This study used SPSS26.0 software to perform one-way ANOVA and repeated measures ANOVA tests to compare the differences among the three groups. A significance level of p < 0.05 was defined as having significant difference, while p < 0.01 was defined as having a highly significant difference.

Results
(1) The comparison between the mid-term and pre-term indicators showed that TRHG experienced significant improvements in ASMI, 6-meter walking pace, and QoL (p < 0.01), and a significant improvement in TUGT timing test (p < 0.05); GTHG experienced extremely significant improvements in 6-meter walking pace and QoL (p < 0.01); AITHG experienced extremely significant improvements in ASMI, 6-meter walking pace, and QoL (p < 0.01), and a significant improvement in TUGT timing test (p < 0.05). (2) The comparison between the post-term and pre-term indicators showed that TRHG experienced extremely significant improvements in TUGT timing test (p < 0.01); GTHG experienced significant improvements in ASMI and TUGT timing test (p < 0.05); and AITHG experienced extremely significant improvements in TUGT timing test (p < 0.01). (3) During the mid-term, there was no significant difference among the groups in all tests (p > 0.05). The same was in post-term tests (p > 0.05).

Conclusion
Compared to the pre-experiment, there was no significant difference at the post- experiment in the recovery effects on the muscle quality, physical activity ability, and life quality of patients with sarcopenia between the AI-based remote training group and the face-to-face traditional training group. 3D pose estimation is equally as effective as traditional rehabilitation methods in enhancing muscle quality, functionality and life quality in older adults with sarcopenia.

Trial registration
The trial was registered in ClinicalTrials.gov (NCT05767710).
MR–CT image fusion method of intracranial tumors based on Res2Net
Authors: Chen Wei , Li Qixuan , Zhang Heng , Sun Kangkang , Sun Wei , Jiao Zhuqing , Ni Xinye 
Published: July 2024

AbstractBackgroundInformation complementarity can be achieved by fusing MR and CT images, and fusion images have abundant soft tissue and bone information, facilitating accurate auxiliary diagnosis and tumor target delineation.PurposeThe purpose of this study was to construct high-quality fusion images based on the MR and CT images of intracranial tumors by using the Residual-Residual Network (Res2Net) method.MethodsThis paper proposes an MR and CT image fusion method based on Res2Net. The method comprises three components: feature extractor, fusion layer, and reconstructor. The feature extractor utilizes the Res2Net framework to extract multiscale features from source images. The fusion layer incorporates a fusion strategy based on spatial mean attention, adaptively adjusting fusion weights for feature maps at each position to preserve fine details from the source images. Finally, fused features are input into the feature reconstructor to reconstruct a fused image.ResultsQualitative results indicate that the proposed fusion method exhibits clear boundary contours and accurate localization of tumor regions. Quantitative results show that the method achieves average gradient, spatial frequency, entropy, and visual information fidelity for fusion metrics of 4.6771, 13.2055, 1.8663, and 0.5176, respectively. Comprehensive experimental results demonstrate that the proposed method preserves more texture details and structural information in fused images than advanced fusion algorithms, reducing spectral artifacts and information loss and performing better in terms of visual quality and objective metrics.ConclusionThe proposed method effectively combines MR and CT image information, allowing the precise localization of tumor region boundaries, assisting clinicians in clinical diagnosis.
Rash caused by lurasidone in old chinese patient with bipolar disorder: case-based review
Authors: Yang Wenjuan , Hu Danhong , Zheng Bei , Han Bing , Feng Pingping , Zhou Yongcan , Wang Weixin , Li Gonghua , Zhang Meiling 
Published: July 2024

Abstract
Background
Rash is one of common adverse drug reaction and which have been reported in typical and atypical antipsychotics. Reports of lurasidone induced skin reactions are sparse. In this study, we report a case of rash caused by lurasidone.

Case presentation
A 63-year-old man with bipolar disorder (BD) who is treated by lurasidone. However, the patient presents a rash all over after lurasidone dose increasing from 40 mg/day to 60 mg/day. With the diagnosis of drug induced rash, lurasidone was discontinued, and the rash complete disappears within 2 weeks. In addition, all case reports about antipsychotics associated rash were reviewed by searching English and Chinese database including Pubmed, Embase, Cochrane Library, CNKI and Wanfang database. A total of 139 articles contained 172 patients were included in our study. The literature review and our case suggest that the cutaneous adverse events caused by antipsychotic drugs should not be ignored, particularly for the patient who was first use or at dose increasing of antipsychotic.

Conclusions
In conclusion, we report a case of lurasidone related rash and review rash caused by antipsychotics. Psychiatrists should be alert to the possibility of the rash caused by antipsychotics, especially the patient was first use of antipsychotics or the antipsychotic dose was increasing.
Strategies to promote treatment compliance: a grounded theory study with relatives of people with a serious mental health condition
Authors: Hempeler Christin , Potthoff Sarah , Scholten Matthé , Juckel Georg , Gather Jakov 
Published: July 2024

Abstract
Background
Treatment pressures encompass communicative strategies that influence mental healthcare service users’ decision-making to increase their compliance with recommended treatment. Persuasion, interpersonal leverage, inducements, and threats have been described as examples of treatment pressures. Research indicates that treatment pressures are exerted not only by mental healthcare professionals but also by relatives. While relatives play a crucial role in their family member’s pathway to care, research on the use of treatment pressures by relatives is still scarce. Likewise, little is known about other strategies relatives may use to promote the treatment compliance of their family member with a serious mental health condition. In particular, no study to date has investigated this from the perspective of relatives of people with a serious mental health condition.

Aim
The aim of this study was to answer the following research questions: Which types of treatment pressures do relatives use? Which other strategies do relatives use to promote the treatment compliance of their family member with a serious mental health condition? How do treatment pressures relate to these other strategies?

Methods
Eleven semi-structured interviews were conducted with relatives of people with a serious mental health condition in Germany. Participants were approached via relatives’ self-help groups and flyers in a local psychiatric hospital. Inclusion criteria were having a family member with a psychiatric diagnosis and the family member having experienced formal coercion. The data were analyzed using grounded theory methodology.

Results
Relatives use a variety of strategies to promote the treatment compliance of their family member with a serious mental health condition. These strategies can be categorized into three general approaches: influencing the decision-making of the family member; not leaving the family member with a choice; and changing the social or legal context of the decision-making process. Our results show that the strategies that relatives use to promote their family member’s treatment compliance go beyond the treatment pressures thus far described in the literature.

Conclusion
This qualitative study supports and conceptually expands prior findings that treatment pressures are not only frequently used within mental healthcare services but also by relatives in the home setting. Mental healthcare professionals should acknowledge the difficulties faced and efforts undertaken by relatives in seeking treatment for their family member. At the same time, they should recognize that a service user’s consent to treatment may be affected and limited by strategies to promote treatment compliance employed by relatives.
Association between non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (NHHR) and kidney stone: evidence from NHANES 2007–2018
Authors: Chen Tao , Cheng Yu , Song Zheng , Zhang Gan , Zeng Tao , Chao Haichao 
Published: July 2024

Abstract
Background
As an innovative lipid parameter, NHHR (the ratio of non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol) can serve as a valuable tool for assessing cardiovascular disease risk. Nevertheless, the relationship between NHHR and the risk of kidney stones remains unexplored.

Methods
A cross-sectional survey utilized data from the National Health and Population Survey (NHANES) database in the United States spanning from 2007 to 2018. Distinct statistical analyses were applied, including weighted logistic regression, stratified and interaction analysis and restricted cubic spline curve (RCS) models, to examine the correlation between NHHR and the incidence of kidney stones.

Results
This analysis encompassed 24,664 participants, with 9.63% reporting incidents of kidney stones. Following multivariate logistic regression and comprehensive adjustments, participants in NHHR quartile 4 (OR 1.34; 95% CI 1.12, 1.60, P < 0.01) exhibited a significantly increased risk of kidney stones compared to those in NHHR quartile 1 (Q1). The RCS result further illustrated a non-linear correlation between NHHR and the incidence of kidney stones. The result of subgroup analysis manifested that participants without diabetes had a higher risk of kidney stones when measured high NHHR levels compared those with diabetes (p for interaction < 0.05).

Conclusion
Elevated NHHR levels were found to be associated with an increased risk of kidney stones. Based on these findings, NHHR appears to be a promising predictive indicator for the occurrence of kidney stones.
Effects of exercise on depression and anxiety in postmenopausal women: a pairwise and network meta-analysis of randomized controlled trials
Authors: Han Bing , Duan Yaya , Zhang Peizhen , Zeng Liqing , Pi Peng , Chen Jiping , Du Guoli 
Published: July 2024

Abstract
Background
Exercise has been identified as a promising non-pharmacological therapy for the management of depression, but there is still controversy over which type is most effective. We aimed to compare and rank the types of exercise that improve depression in postmenopausal women by quantifying information from randomized controlled trials (RCTs).

Methods
The PubMed, Web of Science, SPORTDiscus, CNKI, The Cochrane Library, PsycINFO, EMBASE, and CINAHL Plus databases were searched to identify articles published from inception to 1 March 2024 reporting RCTs that examined the effectiveness of exercise on depression in postmenopausal women. The risk of bias was assessed using the revised Cochrane risk-of-bias tool for RCTs. The quality of the evidence for each comparison was graded using the online confidence in network meta-analysis tool (CINeMA). Standardized mean differences (SMDs) were calculated using the mean and standard deviation of pre-to-post intervention changes and then pooled using a random effects model in a pairwise meta-analysis using Review Manager 5.4. Then, a frequentist network meta-analysis was conducted using a random effects model was conducted to evaluate the efficacy of different exercise types using the network package of Stata 15.

Results
This study included 26 studies involving 2,170 participants. The pairwise meta-analysis revealed that exercise had a significant positive effect on depression in postmenopausal women (SMD = -0.71, 95% confidence interval [CI] = -0.94 to -0.48; I2 = 78%). The network meta-analysis revealed that mind-body exercise (SMD = -0.97, 95% CI = -1.28 to -0.67), aerobic exercise (SMD = -0.58, 95% CI = -0.88 to -0.27) and multicomponent exercise (SMD = -0.57, 95% CI = -1.15 to -0.002) significantly reduced depression compared to the control intervention. Mind-body exercise had the highest probability of being the most effective intervention. Exercise interventions also showed positive effects on anxiety. Most studies were judged to have some concerns regarding their risk of bias, and the confidence in evidence was often very low according to CINeMA.

Conclusion
For postmenopausal women, there is very low to moderate quality evidence that exercise interventions are an effective antidepressant therapy, with mind-body exercise most likely being the optimal type.

Trial registration
This meta-analysis was prospectively registered with PROSPERO (registration number: CRD42024505425).
Machine learning models to predict systemic inflammatory response syndrome after percutaneous nephrolithotomy
Authors: Zhang Tianwei , Zhu Ling , Wang Xinning , Zhang Xiaofei , Wang Zijie , Xu Shang , Jiao Wei 
Published: July 2024

Abstract
Objective
The objective of this study was to develop and evaluate the performance of machine learning models for predicting the possibility of systemic inflammatory response syndrome (SIRS) following percutaneous nephrolithotomy (PCNL).

Methods
We retrospectively reviewed the clinical data of 337 patients who received PCNL between May 2020 and June 2022. In our study, 80% of the data were used as the training set, and the remaining data were used as the testing set. Separate prediction models based on the six machine learning algorithms were created using the training set. The predictive performance of each machine learning model was determined by the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity and specificity using the testing set. We used coefficients to interpret the contribution of each variable to the predictive performance.

Results
Among the six machine learning algorithms, the support vector machine (SVM) delivered the best performance with accuracy of 0.868, AUC of 0.942 (95% CI 0.890–0.994) in the testing set. Further analysis using the SVM model showed that prealbumin contributed the most to the prediction of the outcome, followed by preoperative urine culture, systemic immune-inflammation (SII), neutrophil to lymphocyte ratio (NLR), staghorn stones, fibrinogen, operation time, preoperative urine white blood cell (WBC), preoperative urea nitrogen, hydronephrosis, stone burden, sex and preoperative lymphocyte count.

Conclusion
Machine learning-based prediction models can accurately predict the possibility of SIRS after PCNL in advance by learning patient clinical data, and should be used to guide surgeons in clinical decision-making.
Subgroups of relational job characteristics and their differences in turnover intention and subjective well-being among nurses: a latent profile analysis
Authors: Chen Yi-ping , Li Yifei , Zhang Jie , Li Juan , Yang Xiu-fen , Xiong Lile , Xia Guili , Zhang Jingping 
Published: July 2024

Abstract
Objective
Relational job characteristics include perceived social worth and perceived social influence. Good relational job characteristics mean that nurses have high prosocial behavior. The purpose of this study was to explore the potential profile of nurses’ relational job characteristics, influencing factors and their differences in turnover intention and subjective well-being, thus finding the most suitable clinical relationship job characteristics.

Methods
A cross-sectional survey was conducted among 1013 clinical nurses using the general demographic data questionnaire, Relational Job Characteristics scale, Turnover Intention Questionnaire and Campbell index of well-being. A latent profile analysis was performed to explore relational job characteristics latent profiles. Multinomial logistic regression analysis was conducted to examine the predictors of profile membership, and a one-way analysis of variance was applied to compare the turnover intention and subjective well-being in each latent profile.

Results
Five latent profiles were identified and labeled ‘High prosocial job characteristics’ profile (20.7%), ‘Moderate prosocial job characteristics’ profile (41.7%), ‘High social worth-low social impact perceived’ profile (6.3%), ‘Low social worth‐high social impact perceived’ profile (18.8%) and ‘Low prosocial job characteristics’ profile (12.5%). Factors affecting the different types of nurse relationship job characteristics include age, marital status, hospital department, nursing years, professional title and hospital position. Among them, chief nurse, nurses with more than 20 years of nursing experience and obstetrics and gynecology nurses were more likely to be ‘high prosocial job characteristics’ profile. The turnover intention of nurses in ‘high prosocial job characteristics’ profile was significantly lower than that of other profiles, and their subjective well-being was significantly higher than that of other profiles.

Conclusion
Improving nurses’ perception of social worth and social impact on clinical work can improve nurses’ prosocial behavior and subjective well-being, and reduce their turnover intention. Nursing managers or policy makers can formulate targeted intervention measures according to the influencing factors of potential profiles.