bluuebunny/crossref_metadata_2025_split huggingface dataset:
Enigmatic Presentation of Primary Cutaneous Lymphoma in a Boy
Authors: Farhan Abeer , Fakhro Abdulla , Burshaid Dalal 
Published: September 2024

Background:
Primary cutaneous follicle center lymphoma (PCFCL) is a subtype of primary cutaneous B-cell lymphoma. It is exceedingly rare in the pediatric population, with less than two dozen cases documented in individuals younger than 20 years. The rarity of the disease, coupled with the scarcity of comprehensive clinical data, emphasizes the importance of a meticulous approach in the diagnostic process to avoid under-diagnosis or misdiagnosis.

Methods:
We report a case of an eight-year-old boy who presented with a unique form of scalp lesion, ultimately diagnosed as PCFCL. A complete excision of the remaining defect was addressed by a rotational flap based on the superficial temporal artery.

Results:
Adopting a multidisciplinary approach in managing PCFCL in the pediatric age group exemplifies the importance of collaborative care in addressing complex and rare conditions. The favorable outcome post surgical intervention reinforces the role of complete excision in treating localized PCFCL, aligning with current treatment guidelines for this patient demographic.

Conclusions:
The management of pediatric PCFCL consists of complete surgical excision as the primary treatment modality, reserving radiotherapy for cases of relapse. This case adds to the scant literature on pediatric primary cutaneous B-cell lymphoma and highlights this rare entity’s diagnostic challenges and clinical peculiarities. Ongoing research is essential to enhance our understanding, refine diagnostic criteria, and develop more effective treatment protocols for PCFCL.
Associations Between Organizational Support, Burnout, and Professional Fulfillment Among US Physicians During the First Year of the COVID-19 Pandemic
Authors: Carlasare Lindsey E. , Wang Hanhan , West Colin P. , Trockel Mickey , Dyrbye Liselotte N. , Tutty Michael , Sinsky Christine , Shanafelt Tait D. 
Published: September 2024

Goal:
This research aimed to evaluate variations in perceived organizational support among physicians during the first year of the COVID-19 pandemic and the associations between perceived organizational support, physician burnout, and professional fulfillment.

Methods:
Between November 20, 2020, and March 23, 2021, 1,162 of 3,671 physicians (31.7%) responded to the study survey by mail, and 6,348 of 90,000 (7.1%) responded to an online version. Burnout was assessed using the Maslach Burnout Inventory, and perceived organizational support was assessed by questions developed and previously tested by the Stanford Medicine WellMD Center. Professional fulfillment was measured using the Stanford Professional Fulfillment Index.

Principal Findings:
Responses to organizational support questions were received from 5,933 physicians. The mean organizational support score (OSS) for male physicians was higher than the mean OSS for female physicians (5.99 vs. 5.41, respectively, on a 0–10 scale, higher score favorable; p < .001). On multivariable analysis controlling for demographic and professional factors, female physicians (odds ratio [OR] 0.66; 95% CI: 0.55–0.78) and physicians with children under 18 years of age (OR 0.72; 95% CI: 0.56–0.91) had lower odds of an OSS in the top quartile (i.e., a high OSS score). Specialty was also associated with perceived OSS in mean-variance analysis, with some specialties (e.g., pathology and dermatology) more likely to perceive significant organizational support relative to the reference specialty (i.e., internal medicine subspecialty) and others (e.g., anesthesiology and emergency medicine) less likely to perceive support. Physicians who worked more hours per week (OR for each additional hour/week 0.99; 95% CI: 0.99–1.00) were less likely to have an OSS in the top quartile. On multivariable analysis, adjusting for personal and professional factors, each one-point increase in OSS was associated with 21% lower odds of burnout (OR 0.79; 95% CI: 0.77–0.81) and 32% higher odds of professional fulfillment (OR 1.32; 95% CI: 1.28–1.36).

Practical Applications:
Perceived organizational support of physicians during the COVID-19 pandemic was associated with a lower risk of burnout and a higher likelihood of professional fulfillment. Women physicians, physicians with children under 18 years of age, physicians in certain specialties, and physicians working more hours reported lower perceived organizational support. These gaps must be addressed in conjunction with broad efforts to improve organizational support.
Rural Hospital Service Lines: Changes Over Time and Impacts on Profitability
Authors: Whitacre Brian E. , Rhoades Claudia A. , Davis Alison F. 
Published: September 2024

Goal:
To document shifts in rural hospital service line offerings between 2010 and 2021 and to assess the resulting impacts on hospital profitability.

Methods:
We used annual Medicare cost report data for all rural hospitals that did not change payment classifications between 2010 and 2021. We documented changes in the percentages of hospitals offering each of the 37 inpatient or ancillary service lines included in the data. We then used panel event studies to assess effects on hospital operating margin for specific service lines that changed most prominently during this period.

Principal Findings:
Twelve service lines changed by more than 5% during our period of analysis. These are highlighted by hospitals adding rural health clinics (+32%) and CT scans (+20%) and removing delivery rooms (−21%) and skilled nursing facilities (−19%). Panel event studies demonstrated that the addition or subtraction of most services did not have statistically significant impacts on future hospital operating margins. Notable exceptions were the addition of rural health clinics and the removal of delivery services, both of which positively affected future operating margins. The addition of occupational therapy services had a positive effect on operating margin in the near term, but adding MRI services had a negative effect.

Practical Applications:
The finding that only a select few service line changes resulted in meaningful impacts to hospital operating margins suggests that hospital leaders should be wary of implementing such changes as a means of improving financial viability.
Eating disorders: etiology, risk factors, and suggestions for prevention
Authors: Keski-Rahkonen Anna 
Published: September 2024

Purpose of review
The incidence of eating disorders has increased worldwide. This narrative review gives an overview of research on etiology and risk factors of eating disorders published in 2022–2024.

Recent findings
Eating disorders arise from a complex set of risk factors. The recent increase in incidence of eating disorders can be linked to root causes that include sociocultural pressure to conform to unrealistic and gendered body ideals, rise in obesogenic environments, and the global COVID-19 pandemic. Recent studies have shown that screen time and social media intensify sociocultural pressure to look a certain way. Individual-specific risk factors also increase the likelihood of onset of eating disorders. These include sports, stressful and traumatic life events, family factors, and psychological factors, including disgust sensitivity, aversive experiences, low self-esteem, perfectionism, neuroticism, obsessive-compulsive and impulsive features, and emotional dysregulation. Preexisting mental health conditions, particularly anxiety, depression, and posttraumatic stress disorder, and neurodevelopmental conditions, such as autism and attention-deficit hyperactive disorder, are also associated with increased eating disorder risk. Genetic and biological factors contribute both to risk and resiliency.

Summary
The risk factors of eating disorders are well established. Future studies should focus on increasing resilience and preventive interventions.
Serine chirality guides metabolic flow between one-carbon metabolism and neuromodulator synthesis
Authors: Suzuki Masataka , Adachi Kenichiro , Wiriyasermukul Pattama , Fukumura Mariko , Tamura Ryota , Hirano Yoshinori , Aizawa Yumi , Miyamoto Tetsuya , Taniguchi Sakiko , Toda Masahiro , Homma Hiroshi , Kanekura Kohsuke , Yasuoka Kenji , Kanai Takanori , Sugimoto Masahiro , Nagamori Shushi , Yasui Masato , Sasabe Jumpei 
Published: September 2024

AbstractNeural development requires metabolic adaptations that coincide with a functional shift from differentiation to neurotransmission. Serine metabolism provides essential metabolites for cellular growth and proliferation, and also produces neurotransmitters. However, how serine metabolism coordinates functional development of neurons remains unclear. Here, we report that neurons undergo metabolic transitions through an enantiomeric shift of serine during functional maturation. Developmental alterations of neural transcriptional profiles and serine enantiomers indicated that L- to D-serine conversion is a signature of neural maturation. Metabolomic analysis of neural progenitors revealed that D-serine decreases glycine synthesis, thereby suppressing one-carbon metabolism, in which L-serine is a crucial carbon donor. D-serine inhibits one-carbon metabolism by competing with transport of cytosolic L-serine to mitochondria, which restrains proliferation and triggers apoptosis of neural progenitors as well as neural tumor cells, but not mature neurons,in vitroandex vivo. Thus, our findings suggest that the metabolic transition from L- to D-serine during neural maturation inhibits one-carbon metabolism essential for proliferation of immature neural cells, leading to acquisition of characteristics tailored to functional development toward neurotransmission.
GenoM7GNet: An Efficient N7-methylguanosine Site Prediction Approach Based on a Nucleotide Language Model
Authors: Li Chuang , Wang Heshi , Wen Yanhua , Yin Rui , Zeng Xiangxiang , Li Keqin 
Published: September 2024

AbstractN7-methylguanosine (m7G), one of the mainstream post-transcriptional RNA modifications, occupies an exceedingly significant place in medical treatments. However, classic approaches for identifying m7G sites are costly both in time and equipment. Meanwhile, the existing machine learning methods extract limited hidden information from RNA sequences, thus making it difficult to improve the accuracy. Therefore, we put forward to a deep learning network, called “GenoM7GNet,” for m7G site identification. This model utilizes a Bidirectional Encoder Representation from Transformers (BERT) and is pretrained on nucleotide sequences data to capture hidden patterns from RNA sequences for m7G site prediction. Moreover, through detailed comparative experiments with various deep learning models, we discovered that the one-dimensional convolutional neural network (CNN) exhibits outstanding performance in sequence feature learning and classification. The proposed GenoM7GNet model achieved 0.953 in accuracy, 0.932 in sensitivity, 0.976 in specificity, 0.907 in Matthews Correlation Coefficient and 0.984 in Area Under the receiver operating characteristic Curve on performance evaluation. Extensive experimental results further prove that our GenoM7GNet model markedly surpasses other state-of-the-art models in predicting m7G sites, exhibiting high computing performance.
Exploratory Validation of a Survey Instrument Based on the Theory of Planned Behavior to Assess Vaping Attitude and Perceptions
Authors: Barakat Muna , Abuarab Roa’a , Alkharabsheh Baraah , Budair Nada , Fareed Mais , Kharabsheh Rahma , Laban Dana Oshroq , Sallam Malik 
Published: September 2024

AbstractThe prevalence of vaping (e-cigarette use) surged among young individuals, especially university students, highlighting the necessity to explore the factors influencing this behavior. This study aimed to develop and validate the Vaping Attitude and Perceptions Scale (VAPeS), based on the Theory of Planned Behavior (TPB). A cross-sectional design was employed using a self-administered electronic questionnaire to collect data from university students in Jordan. The questionnaire assessed demographic variables and key constructs of the VAPeS: Social Influence, Perceived Harms, Pleasure Derived from Vaping, Behavioral Influences, and Economic Factors and Self-Efficacy. The survey engaged 671 university students, with 201 (30.0%) reporting the use of tobacco products. Among these tobacco users, a majority (n=126, 62.7%) reported the current use of e-cigarettes. The exploratory factor analysis (EFA) using Principal Component Analysis (PCA) revealed a five-factor solution explaining 64.5% of the variance. These factors—Social Influence, Perceived Harms, Vaping Pleasure, Behavioral Influences, and Economic and Self-Efficacy—demonstrated high internal consistency. Regression analysis showed that Social Influence, Behavioral Influences, and sex were significant predictors of vaping behavior, with standardized coefficients of 0.494, 0.206, and −0.154, respectively (P<.001,P=.008, andP=.018). The VAPeS displayed satisfactory psychometric properties, making it a valuable tool for investigating vaping behaviors among the youth. Factors such as Social Influence and Behavioral Influences were significant factors in shaping vaping behaviors among the participants. These insights emphasize the need to consider these dimensions in public health initiatives aimed at managing the rising vaping prevalence among university students. The VAPeS instrument can be utilized for better delineation of vaping behaviors among the younger demographic. Subsequently, the insights gained through VAPeS-based research can help devise targeted educational campaigns aimed at addressing the perceived social acceptability and the supposed safety of vaping.
Assisting focused attention meditation through EEG-based alpha-theta cross-frequency neurofeedback
Authors: Vuyst Hendrik-Jan De , Karaiskou Angeliki-Ilektra , Soriano Javier R. , Pergens Jelle , Op de Beeck Ruth , Van der Gucht Katleen , Raes Filip , Vos Maarten De , Varon Carolina , Alaerts Kaat 
Published: September 2024

AbstractObjectivesNeurofeedback training involves real-time monitoring and self-regulation of neural activity. Neurofeedback training paradigms have been widely employed in the context of meditation. Interestingly, prior research revealed focused attention meditation to be associated with desynchronized, non-harmonic, cross-frequency relationships between alpha and theta rhythms, suggesting cross-frequency decoupling. However, the potential of training these brainwave patterns to assist meditative practices remains unexplored.MethodsWe assessed the trainability of non-harmonic alpha-theta cross-frequency relationships during focused attention meditation through EEG-neurofeedback training. Thirty individuals underwent 25 minutes of both experimental and sham training. During experimental training, participants received auditory feedback upon detection of non-harmonic alpha-theta brainwaves, whereas during sham training, feedback was unrelated to the measured brainwaves. Neural changes were assessed locally at training site Pz and globally across all scalp electrodes.ResultsMixed model analyses showed a global, but not local, interaction effect between trainings over time, indicating that the incidence of non-harmonic alpha-theta relationships across the scalp increased during experimental training compared to sham training (p< 0.001). This effect persisted in the post-training resting-state recording (p= 0.004). Notably, these training-induced increases were associated with improvements in depressive mood state (p< 0.001). Furthermore, participants with a higher depressive mood state at baseline showed stronger training effects (p< 0.001).ConclusionsNeurofeedback training can be used to upregulate non-harmonic alpha-theta cross-frequency relationships during focused attention meditation with durable post-training effects, particularly for those experiencing depressive mood symptoms. These findings lay the groundwork for investigating the effectiveness of multiple-session neurofeedback-assisted mindfulness training.
Steroidal Therapy plus Conventional Therapy versus Conventional Therapy alone for Tuberculous Meningitis: A systematic review and Meta-analysis
Authors: Naseem Ansa , Javed Muhammad Moiz , Rehmani Malaika , Tariq Muhammad Haider , Sikandar Mahnoor , Ejaz Usama , Bajwa Muhammad Shahzaib , Raza Tehseen , Khan Muhammad Usman , Shehram Ali , Khan Muhammad Hammad , Ayyan Muhammad , Luqman Muhammad 
Published: September 2024

AbstractBackgroundTuberculosis meningitis (TBM) is the most severe form of extrapulmonary tuberculosis with a high rate of morbidity and mortality. Treatments for TBM include conventional therapy alone as well as adjunctive use of steroidal therapy.MethodsA comprehensive search of electronic databases such as PubMed, Cochrane, and Scopus was conducted from inception to April 2024 to retrieve all randomized controlled trials (RCTs) that compared steroidal therapy plus conventional antituberculosis therapy with antituberculosis therapy alone for patients of TBM. Meta-analysis was performed using Review Manager 5.4. Dichotomous outcomes were compared using risk ratio (RR).ResultsThere was a statistically significant decrease in risk of mortality in the Steroid group compared to the control group (RR 0.84; 95% CI 0.75, 0.94; p-value < 0.05). However, there was no statistically significant difference in the risk of neurological deficit between the two groups. There was a statistically significant reduction in the risk of adverse events in the steroidal therapy group compared to the control group (RR 0.90; 95% CI 0.83, 0.98; p-value = 0.03). Similarly, there was a significant improvement in the clinical efficacy in the steroidal therapy group compared to the control (RR 1.16; 95% CI 1.02, 1.31; p-value = 0.02).ConclusionSteroids in addition to antituberculosis therapy significantly reduce mortality and adverse events, while improving clinical outcomes in patients of TBM. There is a need for controlled studies with longer follow-up durations to improve the robustness of the results.
Academic institution extensive, building-by-building wastewater-based surveillance platform for SARS-CoV-2 monitoring, clinical data correlation, and potential national proxy
Authors: Armenta-Castro Arnoldo , Oyervides-Muñoz Mariel Araceli , Aguayo-Acosta Alberto , Lucero-Saucedo Sofia Liliana , Robles-Zamora Alejandro , Rodriguez-Aguillón Kassandra O. , Ovalle-Carcaño Antonio , Parra-Saldívar Roberto , Sosa-Hernández Juan Eduardo 
Published: September 2024

AbstractWastewater-based surveillance has been proposed as a cost-effective toolset to generate data about public health status by detecting specific biomarkers in wastewater samples, as shown during the COVID-19 pandemic. In this work, we report on the performance of an extensive, building-by-building wastewater surveillance platform deployed across 38 locations of the largest private university system in Mexico, spanning 19 of the 32 states. Sampling took place weekly from January 2021 and June 2022. Data from 343 sampling sites was clustered by campus and by state and evaluated through its correlation with the seven-day average of daily new COVID-19 cases in each cluster. Statistically significant linear correlations (p-values below 0.05) were found in 25 of the 38 campuses and 13 of the 19 states. Moreover, to evaluate the effectiveness of epidemiologic containment measures taken by the institution across 2021 and the potential of university campuses as representative sampling points for surveillance in future public health emergencies in the Monterrey Metropolitan Area, correlation between new COVID-19 cases and viral loads in weekly wastewater samples was found to be stronger in Dulces Nombres, the largest wastewater treatment plant in the city (Pearson coefficient: 0.6456, p-value: 6.36710−8), than in the largest university campus in the study (Pearson coefficient: 0.4860, p-value: 8.288×10−5). However, when comparing the data after urban mobility returned to pre-pandemic levels, correlation levels in both locations became comparable (0.894 for the university campus and 0.865 for Dulces Nombres).
Visual processing oscillates differently through time for adults with ADHD
Authors: Pelland-Goulet Pénélope , Arguin Martin , Brisebois Hélène , Gosselin Nathalie 
Published: September 2024

AbstractADHD is a neurodevelopmental disorder affecting 3-4% of Canadian adults and 2.6% of adults worldwide. Its symptoms include inattention, hyperactivity and impulsivity. Though ADHD is known to affect several brain functions and cognitive processes, little is known regarding its impact on perceptual oscillations. This study compared the temporal features of visual processing between ADHD and neurotypical individuals in a word recognition task. These features were sufficiently different across groups while at the same time sufficiently congruent across participants of the same group that a machine learning algorithm classified participants in their respective groups with a 91.8% accuracy using only a small portion of the available features. Secondary findings showed that individuals with ADHD could be classified with high accuracy (91.3%) regarding their use of psychostimulant medication. These findings suggest the existence of strong behavioral markers of ADHD as well as of regular medication usage on visual performance which can be uncovered by random temporal sampling.
Modelling the impact of behavioural interventions during pandemics: A systematic review.
Authors: Gebretekle Tsega Kahsay , Albers Casper 
Published: September 2024

Background. Many studies examined the impact of behavioural interventions on COVID-19 outcomes. We conducted a systematic review to gain insight into transmission models, following PRISMA 2020 guidelines. We included peer-reviewed studies published in English until December 31, 2022, focusing on human subjects, modelling, and examining behavioural interventions during COVID-19 using real data across diverse geographical regions. Methods. We searched seven databases. We used descriptive analysis, network analysis for textual synthesis, and regression analysis to identify the relationship between basic reproduction number (R_0) and various characteristics. From 30,114 articles gathered, 15,781 met the inclusion criteria. After deduplication, 7,616 articles remained. The titles and abstracts screening reduced these to 1,764 articles. Full-text screening reduced this to 270, and risk-of-bias assessment narrowed it to 245 articles. We employed combined criteria for risk of bias assessment, incorporating domains from ROBINS-I and principles for modeling. Results. Primary outcomes focused on the R_0, COVID-19 cases, and transmission rates. The average R_0 was approximately 3.184, indicating an infected individual could spread the disease to about 3.184 of others. The average effective reproduction number (R_c) was about 0.936, reflecting the impact of interventions. Most studies (90.3%) used compartmental models, particularly SEIR. Social distancing, mask-wearing, and lockdowns were frequently analyzed interventions. Early and strict implementation of these interventions significantly reduced transmission rates. Risk of bias assessment revealed 61.9% of studies with low risk, 24.8% moderate, and 9.3% high risks. Common issues included transparency, attrition bias, and confounding factors. Conclusions. This comprehensive review highlights the importance of behavioural interventions in reducing COVID-19 transmission and areas for improving future research transparency and robustness. Our risk of bias criteria offers an important framework for future systematic reviews in modeling studies of interventions. We recommend that future studies enhance transparency in reporting and address common biases such as attrition and confounding.