bluuebunny/crossref_metadata_2025_split huggingface dataset:
Motor network dynamic resting state fMRI connectivity of neurotypical children in regions affected by cerebral palsy
Authors: Boerwinkle Varina L. , Sussman Bethany L. , de Lima Xavier Laura , Wyckoff Sarah N. , Reuther William , Kruer Michael C. , Arhin Martin , Fine Justin M. 
Published: May 2024

BackgroundNormative childhood motor network resting-state fMRI effective connectivity is undefined, yet necessary for translatable dynamic resting-state-network-informed evaluation in pediatric cerebral palsy.MethodsCross-spectral dynamic causal modeling of resting-state-fMRI was investigated in 50 neurotypically developing 5- to 13-year-old children. Fully connected six-node network models per hemisphere included primary motor cortex, striatum, subthalamic nucleus, globus pallidus internus, thalamus, and contralateral cerebellum. Parametric Empirical Bayes with exhaustive Bayesian model reduction and Bayesian modeling averaging informed the model; Purdue Pegboard Test scores of hand motor behavior were the covariate at the group level to determine the effective-connectivity-functional behavior relationship.ResultsAlthough both hemispheres exhibited similar effective connectivity of motor cortico-basal ganglia-cerebellar networks, magnitudes were slightly greater on the right, except for left-sided connections of the striatum which were more numerous and of opposite polarity. Inter-nodal motor network effective connectivity remained consistent and robust across subjects. Age had a greater impact on connections to the contralateral cerebellum, bilaterally. Motor behavior, however, affected different connections in each hemisphere, exerting a more prominent effect on the left modulatory connections to the subthalamic nucleus, contralateral cerebellum, primary motor cortex, and thalamus.DiscussionThis study revealed a consistent pattern of directed resting-state effective connectivity in healthy children aged 5–13 years within the motor network, encompassing cortical, subcortical, and cerebellar regions, correlated with motor skill proficiency. Both hemispheres exhibited similar effective connectivity within motor cortico-basal ganglia-cerebellar networks reflecting inter-nodal signal direction predicted by other modalities, mainly differing from task-dependent studies due to network differences at rest. Notably, age-related changes were more pronounced in connections to the contralateral cerebellum. Conversely, motor behavior distinctly impacted connections in each hemisphere, emphasizing its role in modulating left sided connections to the subthalamic nucleus, contralateral cerebellum, primary motor cortex, and thalamus. Motor network effective connectivity was correlated with motor behavior, validating its physiological significance. This study is the first to evaluate a normative effective connectivity model for the pediatric motor network using resting-state functional MRI correlating with behavior and serves as a foundation for identifying abnormal findings and optimizing targeted interventions like deep brain stimulation, potentially influencing future therapeutic approaches for children with movement disorders.
Black tea preserves intestinal homeostasis through balancing barriers and microbiota in mice
Authors: Shi Yuxuan , Guo Shasha , Zhou Jihong , Xu Ping , Wang Yuefei 
Published: May 2024

IntroductionBlack tea, a beverage consumed worldwide, possesses favorable effects on gastrointestinal tract, including nourishing stomach and promoting digestion. Nevertheless, its specific effects on intestinal homeostasis remains inconclusive.MethodsWe applied black tea to mice prior to inducing colitis with DSS and then monitored their body weight and disease activity index (DAI) daily. When sacrificed, we measured intestinal permeability and conducted analyses of mucin and tight junction proteins. We detected inflammatory cytokines, immune cells, and related inflammatory signaling pathways. In addition, the gut microbiota was analyzed through 16S rRNA sequencing, and the concentrations of short-chain fatty acids (SCFAs) were also measured.ResultsThe results showed that black tea-treated group significantly rescued the DSS-disrupted intestinal structure. It reduced the relative abundance of the pathogenic bacterium Turicibacter, while increased the abundance of beneficial bacteria norank_f_Muribaculaceae and restored the contents of SCFAs such as acetate, propionate, and butyrate. It also protected the intestinal barrier by reducing the levels of immune response-related factors (e.g., TNF-α, IL-6, IL-1β) and increasing the expression of tight junction proteins (TJs) (e.g., ZO-1, occludin). Furthermore, black tea exhibited the capacity to suppress the expression of MMP-9 and ICAM-1, as well as to inhibit the activation of NF-κB signaling pathway.DiscussionOur findings provide a theoretical framework that elucidates the mechanisms by which black tea preserves intestinal homeostasis, highlighting its potential as a preventive strategy against intestinal disruptions. This study contributes to the understanding of the dietary effects of black tea on gastrointestinal health.
Spinal myeloid sarcoma presenting as initial symptom in acute promyelocytic leukemia with a rare cryptic PLZF::RARα fusion gene: a case report and literature review
Authors: Zhang Xuejiao , Wang Tao , Chen Pu , Chen Yan , Wang Zhimei , Xu Tianhong , Yu Pengfei , Liu Peng 
Published: May 2024

BackgroundAcute promyelocytic leukemia (APL) is rarely caused by the PLZF::RARα fusion gene. While APL patients with PLZF::RARα fusion commonly exhibit diverse hematologic symptoms, the presentation of myeloid sarcoma (MS) as an initial manifestation is infrequent.Case presentationA 61-year-old patient was referred to our hospital with 6-month history of low back pain and difficulty walking. Before this admission, spine magnetic resonance imaging (MRI) conducted at another hospital revealed multiple abnormal signals in the left iliac bone and vertebral bodies spanning the thoracic (T11-T12), lumbar (L1-L4), and sacral (S1/S3) regions. This led to a provisional diagnosis of bone tumors with an unknown cause. On admission, complete blood count (CBC) test and peripheral blood smear revealed a slightly increased counts of monocytes. Immunohistochemical staining of both spinal and bone marrow (BM) biopsy revealed positive expression for CD117, myeloperoxidase (MPO), and lysozyme. BM aspirate showed a significant elevation in the percentage of promyelocytes (21%), which were morphologically characterized by round nuclei and hypergranular cytoplasm. Multiparameter flow cytometry of BM aspirate revealed that blasts were positive for CD13, CD33, CD117, and MPO. Through the integrated application of chromosome analysis, fluorescence in situ hybridization (FISH), reverse transcriptase polymerase chain reaction (RT-PCR), and Sanger sequencing, it was determined that the patient possessed a normal karyotype and a rare cryptic PLZF::RARα fusion gene, confirming the diagnosis of APL.ConclusionIn the present study, we report the clinical features and outcome of a rare APL patient characterized by a cryptic PLZF::RARα fusion and spinal myeloid sarcoma (MS) as the initial presenting symptom. Our study not only offers valuable insights into the heterogeneity of APL clinical manifestations but also emphasizes the crucial need to promptly consider the potential link between APL and MS for ensuring a timely diagnosis and personalized treatments.
Physician preferences for nonmetastatic castration-resistant prostate cancer treatment in China
Authors: Fan Yu , Guo Xuanjun , Campobasso Davide , He Zhisong 
Published: May 2024

IntroductionThe treatment preferences of Chinese physicians who treat nonmetastatic castration-resistant prostate cancer (nmCRPC) and how they weigh the benefits and risks of nmCRPC treatment are still unknown. This study aimed to evaluate Chinese physicians’ benefit–risk treatment preferences for nmCRPC and assist in setting nmCRPC treatment goals.MethodsA paper-based discrete choice experiment (DCE) survey was administered to 80 nmCRPC-treating physicians. DCE responses were analyzed to produce the preference weight and the relative importance score for each attribute level. The marginal rate of substitution (MRS) was used to quantify the amount of overall survival (OS) physicians were willing to trade for a reduction in treatment-related adverse events (AEs). We further conducted the exploratory analysis, stratifying physicians from 5 perspectives into different subgroups and examining the treatment preferences and OS trade-off in each subgroup.ResultsIn terms of efficacy attributes, physicians placed greater emphasis on OS than time to pain progression. With regard to safety attributes, serious fracture was perceived as the most important AE by physicians, followed by serious fall, cognitive problems, skin rash, and fatigue. In the exploratory analysis, we found generally that physicians with less clinical practice experience and those from more economically developed regions placed more emphasis on AEs and were willing to give up more of their patients’ OS to reduce the risk of AEs.ConclusionPhysicians from mainland China value the importance of minimizing treatment-related AEs when considering different treatment options for patients with nmCRPC, and they are willing to trade a substantial amount of OS to avoid AEs.
Serum vitamin D and obesity among US adolescents, NHANES 2011–2018
Authors: Chen Zisu , Qiu Xiaojin , Wang Qiong , Wu Jing , Li Min , Niu Wenquan 
Published: May 2024

Background and objectivesChildhood obesity is highly prevalent worldwide. We aimed to assess whether serum 25-hydroxyvitamin D was associated with general/central obesity among US adolescents, and further to explore the mediatory impact of homeostasis model assessment of insulin resistance (HOMA-IR) on this association.MethodsThis study is cross-sectional in design. Study adolescents were enrolled from the National Health and Nutrition Examination Survey (NHANES), 2011–2018. Serum 25-hydroxyvitamin D categories associated with general (indexed by body mass index) and central (indexed by waist circumference to height ratio) obesity were regressed. The possible mediatory effect of HOMA-IR on this association was explored. The nonlinear and dose-response association was examined by restricted cubic spline (RCS) test.ResultsTotal 2,696 adolescents were eligible for inclusion, and the mean age of all adolescents was 15.4 years. Overall, the percentage of general and central obesity was 38.0% and 38.6%, respectively. Compared with adolescents with sufficient vitamin D, adolescent with deficient and insufficient vitamin D intake were associated with general obesity and central obesity; fully-adjusted OR for general obesity was 1.602 (95% CI: 1.161–2.211) and 1.659 (1.385–1.986), and fully-adjusted OR for central obesity was 2.025 (1.445–2.837) and 1.557 (1.287–1.884), respectively, while there was no observable significance in adolescents with possibly harmful vitamin D. The proportion mediated by HOMA-IR was estimated to be 31.7% for global obesity and 50.3% for central obesity (both P &lt; 0.05). More stratified analyses were presented, and identified that the association with general obesity was particularly present among Mexican American, while with central obesity among Non-Hispanic Black adolescents.ConclusionsOur findings indicate that deficient or insufficient 25-hydroxyvitamin D concentrations were associated with the significant risk of general and central obesity among US adolescents, and approximately 30% and 50%, respectively, of these associations were mediated by HOMA-IR.
Predicting the PSQA results of volumetric modulated arc therapy based on dosiomics features: a multi-center study
Authors: Ni Qianxi , Chen Luqiao , Tan Jianfeng , Pang Jinmeng , Luo Longjun , Zhu Jun , Yang Xiaohua 
Published: May 2024

Backgroud and objectivesThe implementation of patient-specific quality assurance (PSQA) has become a crucial aspect of the radiation therapy process. Machine learning models have demonstrated their potential as virtual QA tools, accurately predicting the gamma passing rate (GPR) of volumetric modulated arc therapy (VMAT)plans, thereby ensuring safe and efficient treatment for patients. However, there is limited multi-center research dedicated to predicting the GPR. In this study, a dosiomics-based machine learning approach was employed to construct a prediction model for classifying GPR in multiple radiotherapy institutions. Additionally, the model’s performance was compared by evaluating the impact of two distinct feature selection methods.MethodsA retrospective data collection was conducted on 572 VMAT patients across three radiotherapy institutions. Utilizing a three-dimensional dose verification technique grounded in real-time measurements, γ analysis was conducted according to the criteria of 3%/2 mm and 2%/2 mm, employing a dose threshold of 10% along with absolute dose and global normalization mode. Dosiomics features were extracted from the dose files, and distinct subsets of features were selected as inputs for the model using the random forest (RF) and RF combined with SHapley Additive exPlanations (SHAP) methods. The data underwent training using the extreme gradient boosting (XGBoost) algorithm, and the model’s classification performance was assessed through F1-score and area under the curve (AUC) values.ResultsThe model exhibited optimal performance under the 3%/2 mm criteria, utilizing a subset of 20 features and attaining an AUC value of 0.88 and an F1-score of 0.89. Similarly, under the 2%/2 mm criteria, the model demonstrated superior performance with a subset of 10 features, resulting in an AUC value of 0.91 and an F1-score of 0.89. The feature selection methods of RF and RF + SHAP have achieved good model performance by selecting as few features as possible.ConclusionBased on the multi-center PSQA results, it is possible to utilize dosiomics features extracted from dose files to construct a machine learning predictive model. This model demonstrates excellent discriminative abilities, thus promoting the progress of gamma passing rate prognostic models in clinical application and implementation. Furthermore, it holds potential in providing patients with secure and efficient personalized QA management, while also reducing the workload of medical physicists.
A 12-month longitudinal naturalistic follow-up of cariprazine in schizophrenia
Authors: Carmassi Claudia , Dell’Oste Valerio , Fantasia Sara , Bordacchini Andrea , Bertelloni Carlo Antonio , Scarpellini Pietro , Pedrinelli Virginia 
Published: May 2024

BackgroundCariprazine, a third-generation antipsychotic (TGAs), has demonstrated efficacy in the treatment of schizophrenia with good tolerability profile. Actual real-world literature data are lacking, particularly when exploring its efficacy in the long term. The present study examined the effects of cariprazine treatment on specific psychopathological domains with a particular focus on outcomes and side effects in real-life experience, after a long-term treatment.MethodsThe present 12-month longitudinal naturalistic study included a sample of subjects with a DSM-5-TR diagnosis of schizophrenia, recruited in the outpatients’ psychiatric services of university and community hospitals in Italy, naturally treated with cariprazine. The assessments included: a sociodemographic data sheet, the Structured Clinical Interview for the DSM-5 (SCID-5), the Positive and Negative Symptom Scale (PANSS) and the St. Hans Rating Scale (SHRS). The PANSS was also administered after 6 (T1) and 12 (T2) months of treatment with cariprazine while the SHRS at T1.ResultsThe total sample consisted of 31 patients, 15 males and 16 females. A significant decrease of the PANSS’ subscales, Marder factors and total mean scores emerged at both T1 and T2 with respect to T0. Extrapyramidal symptoms occurred in a minority of patients and in mild or mild/moderate forms: no patient showed moderate forms of psychic/motor akathisia or dystonia, three subjects showed moderate parkinsonism.ConclusionsThis study confirms a good efficacy profile of cariprazine in both positive and negative symptoms in patients with Schizophrenia, combined with a good tolerability profile in extrapyramidal symptoms.
Association of maternal postpartum depression symptoms with infant neurodevelopment and gut microbiota
Authors: Zhou Lepeng , Tang Linghong , Zhou Chuhui , Wen Shi Wu , Krewski Daniel , Xie Ri-hua 
Published: May 2024

IntroductionUnderstanding the mechanisms underlying maternal postpartum depression (PPD) and its effects on offspring development is crucial. However, research on the association between maternal PPD, gut microbiota, and offspring neurodevelopment remains limited. This study aimed to examine the association of maternal PPD symptoms with early gut microbiome, gut metabolome, and neurodevelopment in infants at 6 months.MethodsMaternal PPD symptoms were assessed using the Edinburgh Postpartum Depression Scale (EPDS) at 42 days postpartum. Infants stool samples collected at 42 days after birth were analyzed using 16S rRNA sequencing and liquid chromatography–mass spectrometry (LC–MS) detection. Infant neurodevelopment was measured at 6 months using the Ages and Stages Questionnaire, Third Edition (ASQ-3). Correlations between gut microbiota, metabolites and neurodevelopment were identified through co-occurrence network analysis. Finally, mediation analyses were conducted to determine potential causal pathways.ResultsA total of 101 mother-infant dyads were included in the final analysis. Infants born to mothers with PPD symptoms at 42 days postpartum had lower neurodevelopmental scores at 6 months. These infants also had increased alpha diversity of gut microbiota and were abundant in Veillonella and Finegoldia, while depleted abundance of Bifidobacterium, Dialister, Cronobacter and Megasphaera. Furthermore, alterations were observed in metabolite levels linked to the Alanine, aspartate, and glutamate metabolic pathway, primarily characterized by decreases in N-Acetyl-L-aspartic acid, L-Aspartic acid, and L-Asparagine. Co-occurrence network and mediation analyses revealed that N-Acetyl-L-aspartic acid and L-Aspartic acid levels mediated the relationship between maternal PPD symptoms and the development of infant problem-solving skills.ConclusionsMaternal PPD symptoms are associated with alterations in the gut microbiota and neurodevelopment in infants. This study provides new insights into potential early intervention for infants whose mother experienced PPD. Further research is warranted to elucidate the biological mechanisms underlying these associations.
Retrospective study on the emotional status of healthcare workers in a COVID-19 field hospital in Oman
Authors: McCall Roopa Koshy , Al-Sinawi Hamed , Al-Kharusi Nutaila , Al Rawahi Sulaiman , Al Balushi Rola , Al-Lawati Nabil , Rizzo Manfredi , Al-Rasadi Khalid , Al Maniri Abdullah 
Published: May 2024

OverviewTo combat the overwhelming demand for medical services and care during the COVID-19 Pandemic, the Sultanate of Oman launched the COVID-19 Field Hospital in 2020, designed to respond and alleviate the burden on the medical infrastructure. Several studies globally and from the Middle East suggested that frontline healthcare workers (HCW) were at risk of developing markers of psychological distress. It was further understood through research findings that HCW were resilient during times of crisis. However, there is a dearth in studies evaluating the emotional status of frontline HCW posted in the COVID-19 field hospitals in Gulf Countries, including Oman. This study attempts to shed light on the emotional status of HCW that were on the frontlines in the field hospital in the Sultanate of Oman.AimThis study aims to quantify and evaluate the emotional status of HCW in the frontline field hospital by screening for symptoms of depression, anxiety, and sleep quality.MethodThe data was collected by a local private mental healthcare facility as part of digital feedback to design and implement supportive strategies. Data was collected between September 2021 and October 2021 from 121 HCW in the COVID-19 Field hospital in Oman via ‘WhatsApp’.ResultsChi square and binary logistic regression tests were administered to evaluate the data. The participants comprised of 63.6% females and 79.3% were between 30 and 39 years of age. Majority of the participants (65.2%) described themselves as ‘financially unstable’ and possess an average of 7.5 years of work experience. Of the participants 73.6% of the HCW were based solely in the field hospital for 6–9 months at the time of the survey. Majority of the participants denied the presence of emotional distress expressed through depression (92.6%), anxiety (92.6%) and poor quality of sleep (59.5%).ConclusionThe findings of the present study reflect the HCW ability to cope during challenging situations likely owing to a variety of environmental, social and personal protective factors. The findings of this study can translate into further research on identifying and addressing stressors and targeting the enhancement of protective factors to safeguard the well-being of HCW.
Multi-centre benchmarking of deep learning models for COVID-19 detection in chest x-rays
Authors: Harkness Rachael , Frangi Alejandro F. , Zucker Kieran , Ravikumar Nishant 
Published: May 2024

IntroductionThis study is a retrospective evaluation of the performance of deep learning models that were developed for the detection of COVID-19 from chest x-rays, undertaken with the goal of assessing the suitability of such systems as clinical decision support tools.MethodsModels were trained on the National COVID-19 Chest Imaging Database (NCCID), a UK-wide multi-centre dataset from 26 different NHS hospitals and evaluated on independent multi-national clinical datasets. The evaluation considers clinical and technical contributors to model error and potential model bias. Model predictions are examined for spurious feature correlations using techniques for explainable prediction.ResultsModels performed adequately on NHS populations, with performance comparable to radiologists, but generalised poorly to international populations. Models performed better in males than females, and performance varied across age groups. Alarmingly, models routinely failed when applied to complex clinical cases with confounding pathologies and when applied to radiologist defined “mild” cases.DiscussionThis comprehensive benchmarking study examines the pitfalls in current practices that have led to impractical model development. Key findings highlight the need for clinician involvement at all stages of model development, from data curation and label definition, to model evaluation, to ensure that all clinical factors and disease features are appropriately considered during model design. This is imperative to ensure automated approaches developed for disease detection are fit-for-purpose in a clinical setting.