bluuebunny/crossref_metadata_2025_split huggingface dataset:
Wood density can best predict carbon stock in the forest aboveground biomass following restoration in a post open limestone mining in a tropical region
Authors: Mao Junyang , Xue Peipei , Chen Yuxin , Xiang Ting , Zhang Hui , Chen Cui , Yang Qingqing , Gong Wenfeng 
Published: February 2025

IntroductionReforestation has been widely considered to best solve this problem, but this requires an accurate estimation of carbon stocks in the forest aboveground biomass (AGB) at a large scale. AGB models based on traits and remote sensing indices (moisture vegetation index (MVI)) are the two good methods for this purpose. But limited studies have developed them to estimate carbon stock in AGB during restoration of degraded mining areas.MethodsHere, we have successfully addressed this challenge as we have developed trait-based and MVI-based AGB models to estimate carbon stock in the AGB after performing reforestation in a 0.2 km2 degraded tropical mining area in Hainan Island in China. During this reforestation, seven non-native fast-growing tree species were planted, which has successfully recovered soil processes (including soil microorganisms, nematodes and chemical and physical properties).Results and discussionsBy using these two models to evaluate carbon stock in AGB, we have found that an average of 78.18 Mg C hm-2 could be accumulated by our reforestation exercise. Moreover, wood density could predict AGB for this restored tropical mining site, and indicated that strategies of planting fast-growing species leads to fast-growing strategies (indicated by wood density) which in turn determined the largely accumulated carbon stocks in the AGB during restoration. This restoration technology (multiple-planting of several non-native fast-growing tree species) and the two accurate and effective AGB models (trait-based and MVI-based AGB models) developed by us could be applied to 1) restore other degraded tropical mining area in China, and 2) estimate carbon stock in forest AGB after performing restoration.
Bibliometric analysis of global research on dialectical behavior therapy from 1987 to 2024
Authors: Shi Kuo , Zhang Li-Yi , Gao Bing-Ling , Qian Ying , Huang Xue-Bing , Yue Jing-Li 
Published: February 2025

ObjectiveThis study explores researches of dialectical behavior therapy (DBT) in mental health to provide an overview of current knowledge landscape and predict future development trends of DBT.MethodThe bibliometric approach was used in the study. Articles on DBT-related research were retrieved from the Web of Science Core Collection (WoSCC) database up to December 31, 2024, and analyzed using VOSviewer and CiteSpace.ResultsA total of 2,723 articles were analyzed. DBT research has grown significantly since the 1990s, with the United States leading in publication volume, citation impact, and academic collaboration. Research is primarily conducted in developed countries like the United States, the United Kingdom, and Germany, with limited contributions from emerging economies. Cognitive and Behavioral Practice is the most prolific journal in DBT research. Key topics include borderline personality disorder (BPD), suicide, adolescent interventions, forensic psychiatry, and family therapy. Recently, keywords such as “emotion dysregulation” and “mobile phone” have become research hotspots.ConclusionDBT research has evolved from early focus areas like BPD and suicide to studies on emotion dysregulation mechanisms and digital interventions. While the United States dominates the field, expanding participation from emerging countries and strengthening global collaboration could advance DBT research and improve mental health accessibility. This bibliometric analysis provides a global perspective and long-term trend insights, highlighting future directions in neurobiological mechanisms, methodological innovation, and technological integration.
Psychosocial hazards and work-life balance: the role of workplace conflict, rivalry, and harassment in Latvia
Authors: Paegle Diāna Inga , Lakiša Svetlana , Matisāne Linda , Matisāne Monta , Paegle Linda , Mārtinsone Kristīne , Kamerāde Daiga , Krūmiņa Valentīna , Akmane Elīna , Ķule Amanda , Vanadziņš Ivars 
Published: February 2025

BackgroundEven though the link between the psychosocial work environment and work-life balance (WLB) has been thoroughly researched, there is limited evidence evaluating the impact of workplace violence, sexual harassment, conflicts, and rivalry on WLB.MethodsA cross-sectional study was conducted among 2,471 respondents in Latvia from December 20, 2021, to July 14, 2022. WLB was measured through a survey question assessing the frequency of work-life imbalance, with responses categorized into dichotomous variables. The study evaluated the association between the selected workplace psychosocial hazards (conflicts, rivalry, psychological abuse, physical abuse, and sexual harassment), work characteristics, socio-demographic factors, and WLB by using binomial logistic regression.ResultsOur study reveals a significant lack of WLB among Latvian employees. A striking one-third of the respondents (30.9%, n = 762) reported experiencing this imbalance. The odds of WLB decrease with age, with the youngest age group having twice the odds compared to the oldest age group. Lower education levels and lower income groups also show significantly lower odds of WLB. Notably, those who have experienced selected workplace psychosocial hazards, such as sexual harassment or psychological abuse, have five- and three-times higher odds of work-life imbalance (aOR = 4.90 with 95% CI 2.06–11.67 and aOR = 3.47 with 95% CI 2.75–4.35, respectively). All types of conflicts at work significantly increase the odds of a lack of WLB. Our findings also indicate that WLB varies depending on various work characteristics, such as job position, work sector, company size, length of service, and remote or on-site work.ConclusionOur study highlights the importance of addressing WLB in the context of workplace conflicts, rivalry, violence, and harassment. It provides indirect evidence favoring leadership quality and manager training instead of employee training in diminishing psychosocial hazards. Practical implications include prioritizing leadership development programs focusing on conflict resolution and fostering a supportive organizational culture to improve employee WLB.
Proteome analysis of the prefrontal cortex and the application of machine learning models for the identification of potential biomarkers related to suicide
Authors: Rojo-Romero Manuel Alejandro , Gutiérrez-Nájera Nora Andrea , Cruz-Fuentes Carlos Sabás , Romero-Pimentel Ana Luisa , Mendoza-Morales Roberto , García-Dolores Fernando , Morales-Marín Mirna Edith , Castro-Martínez Xóchitl , González-Sáenz Elier , Torres-Campuzano Jonatan , Medina-Sánchez Tania , Hernández-Fonseca Karla , Nicolini-Sánchez Humberto , Jiménez-García Luis Felipe 
Published: February 2025

IntroductionSuicide is a significant public health problem, with increased rates in low- and middle-income countries such as Mexico; therefore, suicide prevention is important. Suicide is a complex and multifactorial phenomenon in which biological and social factors are involved. Several studies on the biological mechanisms of suicide have analyzed the proteome of the dorsolateral prefrontal cortex (DLPFC) in people who have died by suicide. The aim of this work was to analyze the protein expression profile in the DLPFC of individuals who died by suicide in comparison to age-matched controls in order to gain information on the molecular basis in the brain of these individuals and the selection of potential biomarkers for the identification of individuals at risk of suicide. In addition, this information was analyzed using machine learning (ML) algorithms to propose a model for predicting suicide.MethodsBrain tissue (Brodmann area 9) was sampled from male cases (n=9) and age-matched controls (n=7). We analyzed the proteomic differences between the groups using two-dimensional polyacrylamide gel electrophoresis and mass spectrometry. Bioinformatics tools were used to clarify the biological relevance of the differentially expressed proteins. In addition, this information was analyzed using machine learning (ML) algorithms to propose a model for predicting suicide.ResultsTwelve differentially expressed proteins were also identified (t14 ≤ 0.5). Using Western blotting, we validated the decrease in expression of peroxiredoxin 2 and alpha-internexin in the suicide cases. ML models were trained using densitometry data from the 2D gel images of each selected protein and the models could differentiate between both groups (control and suicide cases).DiscussionOur exploratory pathway analysis highlighted oxidative stress responses and neurodevelopmental pathways as key processes perturbed in the DLPFC of suicides. Regarding ML models, KNeighborsClassifier was the best predicting conditions. Here we show that these proteins of the DLPFC may help to identify brain processes associated with suicide and they could be validated as potential biomarkers of this outcome.
Systematic review and meta-analysis of post-traumatic stress disorder as a risk factor for multiple autoimmune diseases
Authors: Mandagere Kevin , Stoy Savanna , Hammerle Nathan , Zapata Isain , Brooks Benjamin 
Published: February 2025

BackgroundPost Traumatic Stress Disorder (PTSD) is a prevalent and debilitating psychiatric illness that has been linked to poor health outcomes and increased risk of developing chronic health conditions, including multiple autoimmune diseases such as Systemic Lupus Erythematosus (SLE), Inflammatory Bowel Disease (IBD), Rheumatoid Arthritis (RA), and Multiple Sclerosis (MS).AimThis meta-analysis assesses the epidemiological research in this field and briefly explores the hypothesized neurobiological and immunological mechanisms that may underlie the association between PTSD and the development of Autoimmune Disease.MethodsPubMed, SCOPUS, and Cochrane Reviews databases were searched for all relevant articles in August 2023. Studies were systematically screened for relevance and inclusion criteria by two reviewers before quality assessment and data extraction were performed. Fixed and random-effect meta-analyses were performed to evaluate PTSD as a risk factor for the development of specific autoimmune diseases. Subgroup analyses examining the roles of biological sex and PTSD severity were also performed.ResultsThe initial search yielded 3010 articles where only eight prospective and retrospective cohort studies met criteria for inclusion in the meta-analysis. These eight studies were subdivided based on specific disease outcomes. Random effects model for risk of developing any autoimmune disease in persons with PTSD vs. control was 1.291 (95% CI = 1.179 to 1.412; P &lt;0.001; n=1,984,310; 4 studies included). The strength of the association between PTSD and risk of developing specific autoimmune diseases varied by outcome condition from 1.142 (95% CI = 1.085 to 1.202, P &lt;0.001) for risk of IBD to 1.302 (1.037 to 1.635, P = 0.023) for risk of MS. Random effects models showed statistically significant associations between PTSD and IBD, SLE, RA, MS, and Thyroiditis.ConclusionThese results suggest that the risk for developing autoimmune conditions, including SLE, MS, RA, and IBD, is significantly increased in the setting of PTSD. This association may have important implications on clinical practice and research into the pathophysiology of stress disorders.
MRI quantified enlarged perivascular space volumes as imaging biomarkers correlating with severity of anxiety depression in young adults with long-time mobile phone use
Authors: Li Li , Wu Yalan , Wu Jiaojiao , Li Bin , Hua Rui , Shi Feng , Chen Lizhou , Wu Yeke 
Published: February 2025

IntroductionLong-time mobile phone use (LTMPU) has been linked to emotional issues such as anxiety and depression while the enlarged perivascular spaces (EPVS), as marker of neuroinflammation, is closely related with mental disorders. In the current study, we aim to develop a predictive model utilizing MRI-quantified EPVS metrics and machine learning algorithms to assess the severity of anxiety and depression symptoms in patients with LTMPU.MethodsEighty-two participants with LTMPU were included, with 37 suffering from anxiety and 44 suffering from depression. Deep learning algorithms were used to segment EPVS lesions and extract quantitative metrics. Comparison and correlation analyses were performed to investigate the relationship between EPVS and self-reported mood states. Training and testing datasets were randomly assigned in the ratio of 8:2 to perform radiomics analysis, where EPVS metrics combined with sex and age were used to select the most valuable features to construct machine learning models for predicting the severity of anxiety and depression.ResultsSeveral EPVS features were significantly different between the two comparisons. For classifying anxiety status, eight features were selected to construct a logistic regression model, with an AUC of 0.819 (95%CI 0.573-1.000) in the testing dataset. For classifying depression status, eight features were selected to construct a K nearest neighbors model with an AUC value of 0.931 (95%CI 0.814-1.000) in the testing dataset.DiscussionThe utilization of MRI-quantified EPVS metrics combined with machine-learning algorithms presents a promising method for evaluating severity of anxiety and depression symptoms in patients with LTMPU, which might introduce a non-invasive, objective, and quantitative approach to enhance diagnostic efficiency and guide personalized treatment strategies.
Association of work ability with job burnout and sleep quality among biosafety laboratory personnel in Xinjiang, China: a cross-sectional study
Authors: Ju Keke , Wu Ruikai , Yu Jing , Ding Lei , Xia Mengjie , Liu Jiwen , Lu Yaoqin 
Published: February 2025

BackgroundIn recent years, the importance of biosafety research has garnered significant attention due to its critical implications for public health and safety. Biosafety Laboratory (BSL) personnel face numerous challenges as they work with high-risk pathogens, including high-pressure environments, stringent safety protocols, and the risk of infection. Research indicates that occupational stress and burnout significantly affect the physical and mental well-being of laboratory personnel, potentially diminishing their work efficiency and capabilities. This study aims to investigate the effects of occupational burnout and sleep quality on the work ability of BSL personnel in Xinjiang, ultimately providing valuable insights for enhancing biosafety and improving work efficiency.MethodsIn July 2022, a cluster sampling method was employed to survey the staff of BSL in Xinjiang. The study utilized the Maslach Burnout Inventory, the Pittsburgh Sleep Quality Index, and the Work Ability Index to assess the levels of occupational burnout, sleep quality, and work ability among the BSL personnel. Statistical analyses were performed using R Studio 4.2.2 and AMOS 26.0. Through t-tests, analysis of variance, and logistic regression analyses, the study explored the current status and influencing factors of work ability among Xinjiang BSL personnel, as well as the interactive and mediating effects of occupational burnout and sleep quality on work ability.ResultsThe prevalence of occupational burnout was 67.4%, while the prevalence of sleep disorders was 38.9%. Interaction analysis revealed that BSL personnel experiencing both occupational burnout and sleep disorders faced a risk of impaired work ability 21.43 times greater than those without burnout and with good sleep quality (OR = 21.43, 95%CI: 14.30–32.12). Structural equation modeling indicated that occupational burnout indirectly impacts work ability through its effect on sleep quality. The indirect effect was significant with a path coefficient of β = −0.28 (0.64 × −0.43), p &lt; 0.01.ConclusionThe overall work ability of staff in BSL in Xinjiang is relatively good. Occupational burnout and sleep quality are significant risk factors affecting the work ability of BSL personnel. Improving occupational burnout and sleep quality can enhance the work ability of BSL personnel both directly and indirectly.
The role of environmental efficiency and economic development in fertility: implications for public health and sustainability among OECD nations
Authors: Mu Renyan , Zhang Fuang , He Shidi , Zhang Jingshu 
Published: February 2025

IntroductionAs global economies rapidly develop, the interplay between environmental efficiency, economic development, and public health outcomes has gained significant attention. Air pollution and resource-intensive economic activities threaten both environmental sustainability and human health, including reproductive health and overall well-being.MethodsThis study focuses on OECD member countries, using data from 1999 to 2021. An undesirable outputs-oriented DEA approach is employed to assess environmental efficiency across these countries. Baseline regression analysis is conducted to examine the relationship between environmental efficiency and fertility, while heterogeneity analysis explores the impact of industrial and energy consumption structures. Additionally, the moderating effect of economic development levels is investigated.ResultsThe baseline regression results indicate an inverted U-shaped relationship between environmental efficiency and fertility, where fertility initially declines as environmental efficiency increases, then rises after reaching a certain threshold. Heterogeneity analysis reveals that industrial and energy consumption structures significantly influence this relationship across different regions. Furthermore, economic development is found to be a reverse moderator: in countries with higher economic development levels, the relationship between environmental efficiency and fertility follows a significant U-shaped curve.DiscussionThese findings highlight the necessity of integrating environmental policies with public health strategies. Improvements in environmental efficiency may reduce pollution-related health risks, indirectly supporting fertility recovery in advanced economies. By addressing the interaction between environmental efficiency, economic development, and fertility, this study provides evidence-based insights for designing policies that promote sustainable environmental health and equitable social outcomes.
Food handling practices among street food vendors and their associated factors in the town administration of Gamo Zone, Southern Ethiopia
Authors: Girma Zeleke , Temesgen Kidus , Dubale Amanuel , Waritu Nuredin Chura , Jemal Mohammed , Wakeyo Mamud Umer 
Published: February 2025

IntroductionFood handling practice is a serious issue that can increase the risk of contracting foodborne illnesses unless it is well-practiced by street food vendors. Food sold on the street is currently very popular in Ethiopia and is contaminated with various sources of infections due to the poor handling practices of street food vendors that can cause foodborne illnesses. However, there has been little research on the food handling practices of street food vendors in the Gamo zone. Thus, we aimed to assess food handling practices among street food vendors and their associated factors in the town administration of the Gamo Zone.MethodsA cross-sectional study design was conducted from October to December 2021. A simple random sampling technique by the lottery method was used to select 421 participants. The data were collected through interviews and observations, entered into EpiData version 7, and transported to STATA version 13 for analysis by logistic regression. Statistical significance was set at p &lt; 0.05.Results and discussionThe magnitude of good food handling was 40%. Male gender [AOR = 7.03, 95% CI: 3.36–14.71], ages 19–25 [AOR = 9.34, 95% CI: 3.11–28.07] and 26–35 [AOR = 4.80, 95% CI: 1.54–14.99], married participants [AOR = 6.48, 95% CI: 1.69–24.89], college diploma and above [AOR = 5, 95% CI: 1.46–23], monthly income of 1,001–2,000 ETB [AOR = 3.46, 95% CI: 1.50–7.96], and availability of hand washing facility [AOR = 2.68, 95% CI: 1.24–5.77] were significant predictors of good food handling practices.ConclusionAbove half of the food vendors had poor food handling practices. Gender, ages, marital and educational status, monthly income, and handwashing facility were factors associated with food handling practice. Therefore, improving the monthly income and educational status of the food handlers, counseling, and periodic inspections may improve their good food handling practices.
Bilateral parasternal and rectus sheath blocks reduce pain post-cardiac surgery: a pilot trial
Authors: Huang Yangsi , Ouyang Chengdi , He Fang , Zhong Yu , Liu Guofeng , Lu Yizhi , Chen Yanhua 
Published: February 2025

ObjectiveThis study aimed to investigate the effects of ultrasound-guided bilateral parasternal block (PSB) combined with rectus sheath block (RSB) on postoperative recovery quality in patients undergoing median sternotomy for cardiac surgery.MethodsEighty patients were randomly assigned to either the intervention group (receiving PSB + RSB, n = 40) or the control group (not receiving PSB + RSB, n = 40). The primary outcome was opioid consumption within the first 24 h postoperatively. Secondary outcomes included Visual Analog Scale (VAS) pain scores and various surgery and recovery-related parameters.ResultsThe intervention group showed significantly reduced opioid consumption in the first 24 h postoperatively compared to the control group (P &lt; 0.05), though no significant difference was observed at 48 h postoperatively. VAS pain scores at extubation and at 12, 24, and 48 h post-extubation were significantly lower in the intervention group (P &lt; 0.05). The intervention group also demonstrated superior Quality of Recovery-15 (QoR-15) scores at all observed time points compared to the control group (P &lt; 0.05), with no block-related adverse events. There were no significant differences in surgical and recovery-related parameters between the groups.ConclusionUltrasound-guided bilateral PSB combined with RSB effectively enhances postoperative analgesia and the quality of recovery in patients undergoing median sternotomy for cardiac surgery. The application of ultrasound-guided bilateral parasternal block combined with rectus sheath block in median sternotomy cardiac surgery offers a new pain management strategy that is both safe and highly effective. This approach reduces postoperative analgesic requirements and improves recovery quality for cardiac surgery patients.Clinical Trial Registrationhttps://www.chictr.org.cn/showproj.html?proj=180456, China Clinical Trial Registry (ChiCTR2200064733).