bluuebunny/crossref_metadata_2025_split huggingface dataset:
Readsynth: short-read simulation for consideration of composition-biases in reduced metagenome sequencing approaches
Authors: Kuster Ryan , Staton Margaret 
Published: May 2024

Abstract
Background
The application of reduced metagenomic sequencing approaches holds promise as a middle ground between targeted amplicon sequencing and whole metagenome sequencing approaches but has not been widely adopted as a technique. A major barrier to adoption is the lack of read simulation software built to handle characteristic features of these novel approaches. Reduced metagenomic sequencing (RMS) produces unique patterns of fragmentation per genome that are sensitive to restriction enzyme choice, and the non-uniform size selection of these fragments may introduce novel challenges to taxonomic assignment as well as relative abundance estimates.

Results
Through the development and application of simulation software, readsynth, we compare simulated metagenomic sequencing libraries with existing RMS data to assess the influence of multiple library preparation and sequencing steps on downstream analytical results. Based on read depth per position, readsynth achieved 0.79 Pearson’s correlation and 0.94 Spearman’s correlation to these benchmarks. Application of a novel estimation approach, fixed length taxonomic ratios, improved quantification accuracy of simulated human gut microbial communities when compared to estimates of mean or median coverage.

Conclusions
We investigate the possible strengths and weaknesses of applying the RMS technique to profiling microbial communities via simulations with readsynth. The choice of restriction enzymes and size selection steps in library prep are non-trivial decisions that bias downstream profiling and quantification. The simulations investigated in this study illustrate the possible limits of preparing metagenomic libraries with a reduced representation sequencing approach, but also allow for the development of strategies for producing and handling the sequence data produced by this promising application.
Osmolyte-producing microbial biostimulants regulate the growth of Arachis hypogaea L. under drought stress
Authors: Eswaran Sakthi Uma Devi , Sundaram Lalitha , Perveen Kahkashan , Bukhari Najat A. , Sayyed R. Z. 
Published: May 2024

AbstractGlobally, drought stress poses a significant threat to crop productivity. Improving the drought tolerance of crops with microbial biostimulants is a sustainable strategy to meet a growing population’s demands. This research aimed to elucidate microbial biostimulants’ (Plant Growth Promoting Rhizobacteria) role in alleviating drought stress in oil-seed crops. In total, 15 bacterial isolates were selected for drought tolerance and screened for plant growth-promoting (PGP) attributes like phosphate solubilization and production of indole-3-acetic acid, siderophore, hydrogen cyanide, ammonia, and exopolysaccharide. This research describes two PGPR strains: Acinetobacter calcoaceticus AC06 and Bacillus amyloliquefaciens BA01. The present study demonstrated that these strains (AC06 and BA01) produced abundant osmolytes under osmotic stress, including proline (2.21 and 1.75 µg ml− 1), salicylic acid (18.59 and 14.21 µg ml− 1), trehalose (28.35 and 22.74 µg mg− 1 FW) and glycine betaine (11.35 and 7.74 mg g− 1) respectively. AC06 and BA01 strains were further evaluated for their multifunctional performance by inoculating in Arachis hypogaea L. (Groundnut) under mild and severe drought regimes (60 and 40% Field Capacity). Inoculation with microbial biostimulants displayed distinct osmotic-adjustment abilities of the groundnut, such as growth parameters, plant biomass, photosynthetic pigments, relative water content, proline, and soluble sugar in respective to control during drought. On the other hand, plant sensitivity indexes such as electrolyte leakage and malondialdehyde (MDA) contents were decreased as well as cooperatively conferred plant drought tolerance by induced alterations in stress indicators such as catalase (CAT), ascorbate peroxidase (APX), and superoxide dismutase (SOD). Thus, Acinetobacter sp. AC06 and Bacillus sp. BA01 can be considered as osmolyte producing microbial biostimulants to simultaneously induce osmotic tolerance and metabolic changes in groundnuts under drought stress.
A “twelve-section ultrasonic screening and diagnosis method” and management system for screening and treating neonatal congenital heart disease at the grassroots level in Tang County, Hebei Province, China
Authors: Cui Yun , He Xin-jian , Wang Le , Fan Yan-hui , Chen Jiao-yang , Zhao Ning , Zhang Shuai , Liu Lei , Yao Jie , Ren Zhe , Fan Di , Chen Jing , He Xinjian 
Published: May 2024

Abstract
Background
To explore a method for screening and diagnosing neonatal congenital heart disease (CHD) applicable to grassroots level, evaluate the prevalence of CHD, and establish a hierarchical management system for CHD screening and treatment at the grassroots level.

Methods
A total of 24,253 newborns born in Tang County between January 2016 and December 2020 were consecutively enrolled and screened by trained primary physicians via the “twelve-section ultrasonic screening and diagnosis method” (referred to as the “twelve-section method”). Specialized staff from the CHD Screening and Diagnosis Center of Hebei Children’s Hospital regularly visited the local area for definite diagnosis of CHD in newborns who screened positive. Newborns with CHD were managed according to the hierarchical management system.

Results
The centre confirmed that, except for 2 newborns with patent ductus arteriosus missed in the diagnosis of ventricular septal defect combined with severe pulmonary hypertension, newborns with other isolated or concomitant simple CHDs were identified at the grassroots level. The sensitivity, specificity and diagnostic coincidence rate of the twelve-section method for screening complex CHD were 92%, 99.6% and 84%, respectively. A total of 301 children with CHD were identified. The overall CHD prevalence was 12.4‰. According to the hierarchical management system, 113 patients with simple CHD recovered spontaneously during local follow-up, 48 patients continued local follow-up, 106 patients were referred to the centre for surgery (including 17 patients with severe CHD and 89 patients with progressive CHD), 1 patient died without surgery, and 8 patients were lost to follow-up. Eighteen patients with complex CHD were directly referred to the centre for surgery, 3 patients died without surgery, and 4 patients were lost to follow-up. Most patients who received early intervention achieved satisfactory results. The mortality rate of CHD was approximately 28.86 per 100,000 children.

Conclusions
The “twelve-section method” is suitable for screening neonatal CHD at the grassroots level. The establishment of a hierarchical management system for CHD screening and treatment is conducive to the scientific management of CHD, which has important clinical and social significance for early detection, early intervention, reduction in mortality and improvement of the prognosis of complex and severe CHDs.
Associations between over-the-counter analgesics usage and symptoms of anxiety and depression in adolescents: a network analysis
Authors: Roalsø Elise Solbu , Klonteig Sandra , Kraft Brage , Skarstein Siv , Aalberg Marianne , Jonassen Rune 
Published: May 2024

Abstract
Background
The use of over-the-counter analgesics (OTCA) is common among adolescents and has been linked with increased symptoms of anxiety and depression. However, little is known about which specific symptoms are most strongly connected to OTCA usage. The current study assessed which anxiety and depression symptoms were most closely associated with OTCA usage in a large sample of adolescents and examined whether this differed across genders.

Method
The present study was based on data from 626,581 participants from the Ungdata survey in Norway. Associations between OTCA and anxiety and depression symptoms were examined using network analysis. Non-regularized partial-correlation networks were constructed to estimate the conditional dependent relations between the use of OTCA and symptoms while controlling for pain. Gender-specific networks were created for comparison.

Results
OTCA usage was associated with most symptoms, even after controlling for pain, with the strongest associations with “sleep problems”, “stiff or tense”, “everything is a struggle” and “suddenly scared”. There were some gender differences, showing that “sleep problems” and “hopeless” were more strongly related to OTCA usage in females, whereas “stiff or tense” was more strongly related to OTCA usage in males.

Conclusion
Overall, the somatic symptoms of anxiety and depression displayed the strongest associations with OTCA usage. When examining the gender-specific networks, both showed similar trends, although males exhibited slightly stronger associations between OTCA usage and somatic symptoms.
The longitudinal analysis for the association between smoking and the risk of depressive symptoms
Authors: Park Sung Keun , Oh Chang-Mo , Kim Eugene , Ryoo Jae-Hong , Jung Ju Young 
Published: May 2024

Abstract
Background
Despite high smoking rate in people with depressive symptoms, there is ongoing debate about relationship between smoking and depressive symptoms.

Methods
Study participants were 57,441 Korean men. We collected their baseline data between 2011 and 2012, and conducted follow-up from 2013 to 2019. They were categorized by smoking status (never: < 100 cigarettes smoking in life time, former: currently quitting smoking, and current smoker: currently smoking), smoking amount (pack/day and pack-year) and urine cotinine excretion. The development of depressive symptoms was determined in CES-D score ≥ 16. Cox proportional hazards model was used to analyze the multivariable-adjusted hazard ratio (HR) and 95% confidence intervals (CI) for depressive symptoms in relation to smoking status, smoking amount, and urine cotinine excretion.

Results
During 6.7 years of median follow-up, the risk of depressive symptoms increased in order of never (reference), former (HR = 1.08, 95% CI: 1.01—1.15) and current smoker (HR = 1.24, 95% CI: 1.16—1.32). Among current smoker, the risk of depressive symptoms increased proportionally to daily smoking amount (< 1 pack; HR = 1.21, 95% CI: 1.13—1.29, and ≥ 1 pack; HR = 1.34, 95% CI: 1.23 – 1.45). This pattern of relationship was consistently observed for pack-year in former smoker and current smoker. Additionally, urine cotinine excretion was proportionally associated with the risk of depressive symptoms.

Conclusion
Exposure to smoking was associated with the increased risk of depressive symptoms. Dose dependent relationship was observed between smoking amount and the risk of depressive symptoms.
Gender differences in attitudes towards psychological help-seeking among chinese medical students: a comparative analysis
Authors: Qiu Lei , Xu Hengyi , Li Yingqi , Zhao Yonghui , Yang Qin 
Published: May 2024

Abstract
Background
Medical students are known to be at a greater risk of psychological disorders compared to the general population. However, their rate of help-seeking behavior is low. The purpose of this study was to explore the influencing factors of attitudes towards psychological help-seeking among Chinese medical students and to examine its gender differences.

Methods
A total of 3,453 medical students from three medical colleges in Hainan Province, China, completed anonymous questionnaires that included socio-demographic attributes, the Family APGAR Index, the General Health Questionnaire (GHQ-20), and the Attitudes Towards Seeking Professional Psychological Help Short Form (ATSPPH-SF). Associations between predictor variables and attitudes towards help-seeking were explored using multivariate linear regression, and regression models with interaction terms were employed to test gender difference.

Results
The mean score on ATSPPH-SF Scale was 15.04 ± 3.45, with males scoring significantly lower than females (14.34 vs. 15.64, P < 0.0001). For both male and female groups, psych knowledge, mental health status, family function and help-seeking utility perception significantly influenced attitudes toward psychological help-seeking. Furthermore, having more than once psycho-help experiences was positively correlated with women’s attitudes. Significant interactions were found between gender and mental health status.

Conclusion
Attitude towards seeking psychological help was relatively negative among Chinese medical students. The implementation of interventions should take into account the at-risk population, especially the males and individuals with poor mental health.
Genetic variations in anti-diabetic drug targets and COPD risk: evidence from mendelian randomization
Authors: Su Yue , Zhang Youqian , Xu Jinfu 
Published: May 2024

Abstract
Background
Previous research has emphasized the potential benefits of anti-diabetic medications in inhibiting the exacerbation of Chronic Obstructive Pulmonary Disease (COPD), yet the role of anti-diabetic drugs on COPD risk remains uncertain.

Methods
This study employed a Mendelian randomization (MR) approach to evaluate the causal association of genetic variations related to six classes of anti-diabetic drug targets with COPD. The primary outcome for COPD was obtained from the Global Biobank Meta-analysis Initiative (GBMI) consortium, encompassing a meta-analysis of 12 cohorts with 81,568 cases and 1,310,798 controls. Summary-level data for HbA1c was derived from the UK Biobank, involving 344,182 individuals. Positive control analysis was conducted for Type 2 Diabetes Mellitus (T2DM) to validate the choice of instrumental variables. The study applied Summary-data-based MR (SMR) and two-sample MR for effect estimation and further adopted colocalization analysis to verify evidence of genetic variations.

Results
SMR analysis revealed that elevated KCNJ11 gene expression levels in blood correlated with reduced COPD risk (OR = 0.87, 95% CI = 0.79–0.95; p = 0.002), whereas an increase in DPP4 expression corresponded with an increased COPD incidence (OR = 1.18, 95% CI = 1.03–1.35; p = 0.022). Additionally, the primary method within MR analysis demonstrated a positive correlation between PPARG-mediated HbA1c and both FEV1 (OR = 1.07, 95% CI = 1.02–1.13; P = 0.013) and FEV1/FVC (OR = 1.08, 95% CI = 1.01–1.14; P = 0.007), and a negative association between SLC5A2-mediated HbA1c and FEV1/FVC (OR = 0.86, 95% CI = 0.74–1.00; P = 0.045). No colocalization evidence with outcome phenotypes was detected (all PP.H4 < 0.7).

Conclusion
This study provides suggestive evidence for anti-diabetic medications' role in improving COPD and lung function. Further updated MR analyses are warranted in the future, following the acquisition of more extensive and comprehensive data, to validate our results.
Clinical significance of pleural fluid lactate dehydrogenase/adenosine deaminase ratio in the diagnosis of tuberculous pleural effusion
Authors: Zhao Tingting , Zhang Jianhua , Zhang Xiufeng , Wang Cheng 
Published: May 2024

Abstract
Background
Pleural fluid is one of the common complications of thoracic diseases, and tuberculous pleural effusion (TPE) is the most common cause of pleural effusion in TB-endemic areas and the most common type of exudative pleural effusion in China. In clinical practice, distinguishing TPE from pleural effusion caused by other reasons remains a relatively challenging issue. The objective of present study was to explore the clinical significance of the pleural fluid lactate dehydrogenase/adenosine deaminase ratio (pfLDH/pfADA) in the diagnosis of TPE.

Methods
The clinical data of 618 patients with pleural effusion were retrospectively collected, and the patients were divided into 3 groups: the TPE group (412 patients), the parapneumonic pleural effusion (PPE) group (106 patients), and the malignant pleural effusion (MPE) group (100 patients). The differences in the ratios of pleural effusion-related and serology-related indicators were compared among the three groups, and receiver operating characteristic curves were drawn to analyze the sensitivity and specificity of the parameter ratios of different indicators for the diagnosis of TPE.

Results
The median serum ADA level was higher in the TPE group (13 U/L) than in the PPE group (10 U/L, P < 0.01) and MPE group (10 U/L, P < 0.001). The median pfADA level in the TPE group was 41 (32, 52) U/L; it was lowest in the MPE group at 9 (7, 12) U/L and highest in the PPE group at 43 (23, 145) U/L. The pfLDH level in the PPE group was 2542 (1109, 6219) U/L, which was significantly higher than that in the TPE group 449 (293, 664) U/L. In the differential diagnosis between TPE and non-TPE, the AUC of pfLDH/pfADA for diagnosing TPE was the highest at 0.946 (0.925, 0.966), with an optimal cutoff value of 23.20, sensitivity of 93.9%, specificity of 87.0%, and Youden index of 0.809. In the differential diagnosis of TPE and PPE, the AUC of pfLDH/pfADA was the highest at 0.964 (0.939, 0.989), with an optimal cutoff value of 24.32, sensitivity of 94.6%, and specificity of 94.4%; this indicated significantly better diagnostic efficacy than that of the single index of pfLDH. In the differential diagnosis between TPE and MPE, the AUC of pfLDH/pfADA was 0.926 (0.896, 0.956), with a sensitivity of 93.4% and specificity of 80.0%; this was not significantly different from the diagnostic efficacy of pfADA.

Conclusions
Compared with single biomarkers, pfLDH/pfADA has higher diagnostic value for TPE and can identify patients with TPE early, easily, and economically.
Expert assessment of ChatGPT’s ability to generate illness scripts: an evaluative study
Authors: Yanagita Yasutaka , Yokokawa Daiki , Fukuzawa Fumitoshi , Uchida Shun , Uehara Takanori , Ikusaka Masatomi 
Published: May 2024

Abstract
Background
An illness script is a specific script format geared to represent patient-oriented clinical knowledge organized around enabling conditions, faults (i.e., pathophysiological process), and consequences. Generative artificial intelligence (AI) stands out as an educational aid in continuing medical education. The effortless creation of a typical illness script by generative AI could help the comprehension of key features of diseases and increase diagnostic accuracy. No systematic summary of specific examples of illness scripts has been reported since illness scripts are unique to each physician.

Objective
This study investigated whether generative AI can generate illness scripts.

Methods
We utilized ChatGPT-4, a generative AI, to create illness scripts for 184 diseases based on the diseases and conditions integral to the National Model Core Curriculum in Japan for undergraduate medical education (2022 revised edition) and primary care specialist training in Japan. Three physicians applied a three-tier grading scale: “A” denotes that the content of each disease’s illness script proves sufficient for training medical students, “B” denotes that it is partially lacking but acceptable, and “C” denotes that it is deficient in multiple respects.

Results
By leveraging ChatGPT-4, we successfully generated each component of the illness script for 184 diseases without any omission. The illness scripts received “A,” “B,” and “C” ratings of 56.0% (103/184), 28.3% (52/184), and 15.8% (29/184), respectively.

Conclusion
Useful illness scripts were seamlessly and instantaneously created using ChatGPT-4 by employing prompts appropriate for medical students. The technology-driven illness script is a valuable tool for introducing medical students to key features of diseases.
Effectiveness of a flipped classroom for undergraduate in implant dentistry hands-on course
Authors: Wu Tao , Xia Haibin , Sun Wei , Ge Yan , Liu Chun , He Fengxiao , Cheng Tiange , Zhao Yi , Chen Si 
Published: May 2024

Abstract
Purpose
The purpose of this study was to compare the learning in the implant dentistry hands-on course to that of the flipped classroom (FC) and the traditional lecture cohorts (control).

Materials and methods
In this study,80 students were enrolled for the first time in an implant dentistry program. Subsequently, they were divided into two groups. The first, the FC group, which had free access to a video with a PowerPoint presentation on the Chaoxing-WHU-MOOC platform about the implant placement on first molar sites before class. The second, the control group, which attended a didactic lecture describing implant practice on the first molar site via a bidirectional multimedia interactive teaching demonstration and then operated on a simulation model. Cone beam computed tomography (CBCT) and the deviation gauge were utilized to analyze the accuracy of the implant placement in the students’ models. An online satisfaction questionnaire was distributed to both groups one week after the class.

Results
The linear deviation of the CBCT examination did not show any statistical difference between the two groups concerning cervical, apex, and angular. A significant buccal deviation was observed in the control group compared with the FC group (mean: 0.7436 mm vs. 0.2875 mm, p = 0.0035), according to the restoration-level deviation gauge. A total of 74.36% of students in the FC group placed implant within 0.5 mm buccal-to-lingual deviations, but only 41.03% of students in the control group reached within 0.5 mm buccal-to-lingual deviation ranges. Additionally, 91.67% of the students in the FC group and 97.5% of the students in the control group were satisfied with the practical implant class.

Conclusion
FC was more effective than a didactic lecture for implant dentistry practical skill acquisition.
Optimizing deep learning-based segmentation of densely packed cells using cell surface markers
Authors: Han Sunwoo , Phasouk Khamsone , Zhu Jia , Fong Youyi 
Published: May 2024

Abstract
Background
Spatial molecular profiling depends on accurate cell segmentation. Identification and quantitation of individual cells in dense tissues, e.g. highly inflamed tissue caused by viral infection or immune reaction, remains a challenge.

Methods
We first assess the performance of 18 deep learning-based cell segmentation models, either pre-trained or trained by us using two public image sets, on a set of immunofluorescence images stained with immune cell surface markers in skin tissue obtained during human herpes simplex virus (HSV) infection. We then further train eight of these models using up to 10,000+ training instances from the current image set. Finally, we seek to improve performance by tuning parameters of the most successful method from the previous step.

Results
The best model before fine-tuning achieves a mean Average Precision (mAP) of 0.516. Prediction performance improves substantially after training. The best model is the cyto model from Cellpose. After training, it achieves an mAP of 0.694; with further parameter tuning, the mAP reaches 0.711.

Conclusion
Selecting the best model among the existing approaches and further training the model with images of interest produce the most gain in prediction performance. The performance of the resulting model compares favorably to human performance. The imperfection of the final model performance can be attributed to the moderate signal-to-noise ratio in the imageset.