bluuebunny/crossref_metadata_2025_split huggingface dataset:
Stroke severity mediates the effect of socioeconomic disadvantage on poor outcomes among patients with intracerebral hemorrhage
Authors: Potter Thomas B. H. , Tannous Jonika , Pan Alan P. , Bako Abdulaziz , Johnson Carnayla , Baig Eman , Kelly Hannah , McCane Charles D. , Garg Tanu , Gadhia Rajan , Misra Vivek , Volpi John , Britz Gavin , Chiu David , Vahidy Farhaan S. 
Published: June 2023

BackgroundSocioeconomic deprivation drives poor functional outcomes after intracerebral hemorrhage (ICH). Stroke severity and background cerebral small vessel disease (CSVD) burden have each been linked to socioeconomic status and independently contribute to worse outcomes after ICH, providing distinct, plausible pathways for the effects of deprivation. We investigate whether admission stroke severity or cerebral small vessel disease (CSVD) mediates the effect of socioeconomic deprivation on 90-day functional outcomes.MethodsElectronic medical record data, including demographics, treatments, comorbidities, and physiological data, were analyzed. CSVD burden was graded from 0 to 4, with severe CSVD categorized as ≥3. High deprivation was assessed for patients in the top 30% of state-level area deprivation index scores. Severe disability or death was defined as a 90-day modified Rankin Scale score of 4–6. Stroke severity (NIH stroke scale (NIHSS)) was classified as: none (0), minor (1–4), moderate (5–15), moderate–severe (16–20), and severe (21+). Univariate and multivariate associations with severe disability or death were determined, with mediation evaluated through structural equation modelling.ResultsA total of 677 patients were included (46.8% female; 43.9% White, 27.0% Black, 20.7% Hispanic, 6.1% Asian, 2.4% Other). In univariable modelling, high deprivation (odds ratio: 1.54; 95% confidence interval: [1.06–2.23]; p = 0.024), severe CSVD (2.14 [1.42–3.21]; p &lt; 0.001), moderate (8.03 [2.76–17.15]; p &lt; 0.001), moderate–severe (32.79 [11.52–93.29]; p &lt; 0.001), and severe stroke (104.19 [37.66–288.12]; p &lt; 0.001) were associated with severe disability or death. In multivariable modelling, severe CSVD (3.42 [1.75–6.69]; p &lt; 0.001) and moderate (5.84 [2.27–15.01], p &lt; 0.001), moderate–severe (27.59 [7.34–103.69], p &lt; 0.001), and severe stroke (36.41 [9.90–133.85]; p &lt; 0.001) independently increased odds of severe disability or death; high deprivation did not. Stroke severity mediated 94.1% of deprivation’s effect on severe disability or death (p = 0.005), while CSVD accounted for 4.9% (p = 0.524).ConclusionCSVD contributed to poor functional outcome independent of socioeconomic deprivation, while stroke severity mediated the effects of deprivation. Improving awareness and trust among disadvantaged communities may reduce admission stroke severity and improve outcomes.
Correlation analysis between 18F-fluorodeoxyglucose positron emission tomography and cognitive function in first diagnosed Parkinson’s disease patients
Authors: Zhihui Sun , Yinghua Li , Hongguang Zhao , Yuyin Dai , Xiaoxiao Du , Lulu Gao , Yi Li , Kangli Fan , Ying Zhang 
Published: June 2023

ObjectiveEvaluation of the correlation between 18F-fluorodeoxyglucose-positron emission tomography (18F-FDG PET) and cognitive function in first-diagnosed and untreated Parkinson’s disease (PD) patients.Materials and methodThis cross-sectional study included 84 first diagnosed and untreated PD patients. The individuals were diagnosed by movement disorder experts based on the 2015 MDS Parkinson’s disease diagnostic criteria. The patients also underwent 18F-FDG PET scans and clinical feature assessments including the Montreal Cognitive Assessment (MoCA) scale. Glucose metabolism rates were measured in 26 brain regions using region of interest (ROI) and pixel-wise analyses with displayed Z scores. The cognitive function was assessed by professionals using the MoCA scale, which covers five cognitive domains. Spearman’s linear correlation and linear regression models were used to compare the correlations between 18F-FDG metabolism in each brain region and cognitive domain, using SPSS 25.0 software.ResultThe results indicated a positive correlation between executive function and glucose metabolism in the lateral prefrontal cortex of the left hemisphere (p = 0.041). Additionally, a positive correlation between memory function and glucose metabolism in the right precuneus (p = 0.014), right lateral occipital cortex (p = 0.017), left lateral occipital cortex (p = 0.031), left primary visual cortex (p = 0.008), and right medial temporal cortex (p = 0.046). Further regression analysis showed that for every one-point decrease in the memory score, the glucose metabolism in the right precuneus would decrease by 0.3 (B = 0.30, p = 0.005), the glucose metabolism in the left primary visual cortex would decrease by 0.25 (B = 0.25, p = 0.040), the glucose metabolism in the right lateral occipital cortex would decrease by 0.38 (B = 0.38, p = 0.012), and the glucose metabolism in the left lateral occipital cortex would decrease by 0.32 (B = 0.32, p = 0.045).ConclusionThis study indicated that cognitive impairment in PD patients mainly manifests as changes in executive function, visual-spatial function and memory functions, while glucose metabolism mainly decreases in the frontal and posterior cortex. Further analysis shows that executive function is related to glucose metabolism in the left lateral prefrontal cortex. On the other hand, memory ability involves changes in glucose metabolism in a more extensive brain region. This suggests that cognitive function assessment can indirectly reflect the level of glucose metabolism in the relevant brain regions.
Independent effect of fat-to-muscle mass ratio at bioimpedance analysis on long-term survival in patients receiving surgery for pancreatic cancer
Authors: Sandini Marta , Paiella Salvatore , Cereda Marco , Angrisani Marco , Capretti Giovanni , Famularo Simone , Giani Alessandro , Roccamatisi Linda , Fontani Andrea , Malleo Giuseppe , Salvia Roberto , Roviello Franco , Zerbi Alessandro , Bassi Claudio , Gianotti Luca 
Published: June 2023

IntroductionMalnutrition and alteration of body composition are early features in pancreatic cancer and appear to be predictors of advanced stages and dismal overall survival. Whether specific patient characteristics measured at the preoperative bioimpedance analysis (BIA) could be associated with long-term outcomes following curative resection has not been yet described.MethodsIn a prospective multicenter study, all histologically proven resected pancreatic cancer patients were included in the analysis. BIA was measured for all patients on the day before surgery. Demographics, perioperative data, and postoperative outcomes were prospectively collected. Patients who experienced 90-day mortality were excluded from the analysis. Survival data were obtained through follow-up visits and phone interviews. Bioimpedance variables were analyzed according to the overall survival using the Kaplan–Meier curves and the univariate and multivariate Cox regression model.ResultsOverall, 161 pancreatic cancer patients were included. The median age was 66 (60–74) years, and 27.3% received systemic neoadjuvant treatment. There were 23 (14.3%) patients malnourished in the preoperative evaluation. Median OS was 34.0 (25.7–42.3) months. Several bioimpedance variables were associated with OS at the univariate analysis, namely the phase angle [HR 0.85, 95% CI 0.74–0.98)], standardized phase angle [HR 0.91, 95% CI 0.82–0.99)], and an increased ratio between the fat and lean mass (FM/FFM) [HR 4.27, 95% CI 1.10–16.64)]. At the multivariate analysis, the FM/FFM ratio was a confirmed independent predictor of OS following radical resection, together with a positive lymph nodal status.ConclusionAlteration of body composition at the preoperative bioimpedance vector analysis (BIVA) can predict dismal oncologic outcomes following pancreatic resection for cancer.
Clinical trial of a probiotic and herbal supplement for lung health
Authors: Wenger Nancy M. , Qiao Luhua , Nicola Teodora , Nizami Zoha , Martin Isaac , Halloran Brian A. , Tanaka Kosuke , Evans Michael , Xu Xin , Dinan Timothy G. , Kakilla Charles , DunnGalvin Gillian , Ambalavanan Namasivayam , Willis Kent A. , Gaggar Amit , Lal Charitharth Vivek 
Published: June 2023

IntroductionDysbiosis of the gut microbiome may augment lung disease via the gut-lung axis. Proteobacteria may contribute to tissue proteolysis followed by neutrophil recruitment, lung tissue injury, and perpetuation of chronic inflammation. To study the effects of probiotics across the gut-lung axis, we sought to determine if a Lactobacillus probiotic and herbal blend was safe and well-tolerated in healthy volunteers and asthmatic patients.MethodsWe conducted a 1-month randomized, open-label clinical trial in Cork, Ireland with healthy and asthmatic patients who took the blend twice a day. The primary endpoint was safety with exploratory endpoints including quality of life, lung function, gut microbiome ecology, and inflammatory biomarkers.ResultsAll subjects tolerated the blend without adverse events. Asthmatic subjects who took the blend showed significant improvements in lung function as measured by forced expiratory volume and serum short chain fatty acid levels from baseline to Week 4. The gut microbiome of asthmatic subjects differed significantly from controls, with the most prominent difference in the relative abundance of the proteobacteria Escherichia coli. Administration of the probiotic maintained overall microbial community architecture with the only significant difference being an increase in absolute abundance of the probiotic strains measured by strain-specific PCR.ConclusionThis study supports the safety and efficacy potential of a Lactobacillus probiotic plus herbal blend to act on the gut-lung axis. However, due to the lack of a control group, a longer blinded, placebo-controlled study will be warranted to confirm the efficacy improvements observed in this trial.Clinical trial registrationhttps://clinicaltrials.gov/, identifier NCT05173168.
A Bayesian optimization tunning integrated multi-stacking classifier framework for the prediction of radiodermatitis from 4D-CT of patients underwent breast cancer radiotherapy
Authors: Wu Kuan , Miu Xiaoyan , Wang Hui , Li Xiadong 
Published: June 2023

PurposeIn this study, we aimed to develop a novel Bayesian optimization based multi-stacking deep learning platform for the prediction of radiation-induced dermatitis (grade ≥ two) (RD 2+) before radiotherapy, by using multi-region dose-gradient-related radiomics features extracted from pre-treatment planning four-dimensional computed tomography (4D-CT) images, as well as clinical and dosimetric characteristics of breast cancer patients who underwent radiotherapy.Materials and methodsThe study retrospectively included 214 patients with breast cancer who received radiotherapy after breast surgeries. Six regions of interest (ROIs) were delineated based on three PTV dose -gradient-related and three skin dose-gradient-related parameters (i.e., isodose). A total of 4309 radiomics features extracted from these six ROIs, as well as clinical and dosimetric characteristics, were used to train and validate the prediction model using nine mainstream deep machine learning algorithms and three stacking classifiers (i.e., meta-learners). To achieve the best prediction performance, a Bayesian optimization based multi-parameter tuning technology was adopted for the AdaBoost, random forest (RF), decision tree (DT), gradient boosting (GB) and extra tree (XTree) five machine learning models. The five parameter -tuned learners and the other four learners (i.e., logistic regression (LR), K-nearest neighbors (KNN), linear discriminant analysis (LDA), Bagging) whose parameters cannot be tuned, all as the primary week learners, were fed into the subsequent meta-learners for training and learning the final prediction model.ResultsThe final prediction model included 20 radiomics features and eight clinical and dosimetric characteristics. At the primary learner level, on base of Bayesian parameter tuning optimization, the RF, XGBoost, AdaBoost, GBDT, and LGBM models with the best parameter combinations achieved AUC of 0.82, 0.82, 0.77, 0.80, and 0.80 prediction performance in the verification data set, respectively. In the secondary meta-learner lever, compared with LR and MLP meta-learner, the best predictor of symptomatic RD 2+ for stacked classifiers was the GB meta-learner with an area under the curve (AUC) of 0.97 [95% CI: 0.91-1.0] and an AUC of 0.93 [95% CI: 0.87-0.97] in the training and validation datasets, respectively and the 10 top predictive characteristics were identified.ConclusionA novel multi-region dose-gradient-based Bayesian optimization tunning integrated multi-stacking classifier framework can achieve a high-accuracy prediction of symptomatic RD 2+ in breast cancer patients than any other single deep machine learning algorithm.
Myopia among children and adolescents: an epidemiological study in Fuzhou City
Authors: Zhu Mei-hong , Lin Tai-nan , Lin Jing-hua , Wen Qian 
Published: June 2023

ObjectiveTo provide a reference for the prevention and control of myopia by analyzing and discussing the findings of an epidemiological survey of the prevalence of myopia among children and adolescents in Fuzhou City from 2019 to 2021.MethodsParticipants for this cross-sectional study were drawn from Gulou District and Minqing County in Fuzhou City using cluster random sampling to account for differences in population density, economic development, and other environmental variables.ResultsMyopia was more prevalent in 2020 than in 2019, but by 2021 it had dropped to about the same level as in 2019. Myopia was more prevalent among girls than boys during the course of the study period, with a three-year prevalence of 44.72% for boys and 52.16% for girls. Mild myopia accounted for 24.14% of all cases, followed by moderate myopia at 19.62%, and severe myopia at 4.58%. Students in urban regions had a prevalence of myopia equivalent to that of students in the suburbs, and this prevalence rose with age.ConclusionMyopia was quite prevalent among children and adolescents in Fuzhou City, and was shown to be steadily rising as students progressed through the school system. This suggests that all levels of government, educational institutions, medical facilities, and concerned parents in Fujian Province should focus on the issue of myopia and collaborate to reduce the risk factors for the development of myopia in school-aged participants.
Risk of diabetic ketoacidosis of SGLT2 inhibitors in patients with type 2 diabetes: a systematic review and network meta-analysis of randomized controlled trials
Authors: Yang Shiwen , Liu Ying , Zhang Shengzhao , Wu Fengbo , Liu Dan , Wu Qingfang , Zheng Hanrui , Fan Ping , Su Na 
Published: June 2023

Background: Sodium–glucose cotransporter-2 (SGLT2) inhibitors have proven to be effective in improving glycemic control in patients with type 2 diabetes mellitus (T2DM). However, the risk of diabetic ketoacidosis (DKA) in patients remains unclear. The purpose of this study is to conduct this systematic review and network meta-analysis for the risk of DKA of SGLT2 inhibitors in patients with T2DM.Methods: We searched for randomized controlled trials (RCTs) concerning SGLT2 inhibitors in patients with T2DM in PubMed, EMBASE (Ovid SP), Cochrane Central Register of Controlled Trials (Ovid SP), and ClinicalTrials.gov from inception to January 2022. The primary outcomes were the risk of DKA. We assessed the sparse network with a fixed-effect model and consistency model in a frequentist framework with a graph-theoretical method by the netmeta package in R. We assessed the evidence quality of evidence of outcomes according to the Grading of Recommendations Assessment, Development, and Evaluation (GRADE).Results: In total, 36 studies involving 52,264 patients were included. The network showed that there was no significant difference observed among SGLT2 inhibitors, other active antidiabetic drugs, and placebo in the risk of DKA. There was no significant difference in the DKA risk between different doses of SGLT2 inhibitors. The certainty of the evidence ranged from very low to moderate. The probabilities of rankings and P-score showed that compared to placebo, SGLT2 inhibitors might increase the risk of DKA (P-score = 0.5298). Canagliflozin might have a higher DKA risk than other SGLT2 inhibitors (P-score = 0.7388).Conclusion: Neither SGLT2 inhibitors nor other active antidiabetic drugs were associated with an increased risk of DKA compared to placebo, and the risk of DKA with SGLT2 inhibitors was not found to be dose-dependent. In addition, the use of canagliflozin was less advisable than other SGLT2 inhibitors according to the rankings and P-score.Systematic Review Registration:https://www.crd.york.ac.uk/prospero/, identifier PROSPERO, CRD42021297081.
An instrument to measure atrial fibrillation knowledge in Chinese patients: validation of the Jessa Atrial fibrillation Knowledge Questionnaire
Authors: Chang Sijie , Xu Wenlin , Wu Shuyi , Desteghe Lien , Zhang Feilong , Zhang Jinhua 
Published: June 2023

Background: There is no validated tool to assess patients’ knowledge of oral anticoagulant therapy in atrial fibrillation in China.Methods: Using a standard translation program, the Jessa Atrial fibrillation Knowledge Questionnaire (JAKQ) was translated into Chinese. The reliability of the JAKQ was assessed by internal consistency (Cronbach’s α coefficient), repeatability (test-retest reliability), and sensitivity tests. Effectiveness was assessed by hypothesizing that a lower JAKQ score was a risk factor for bleeding. A total of 447 patients with atrial fibrillation (AF) who were hospitalized between July 2019 and December 2021 were studied and followed up. Participants were followed up 1, 3, 6, and 12 months after enrollment. Bleeding during follow-up was recorded. Data were obtained from hospital databases and telephone follow-up.Result: A total of 447 patients with AF completed JAKQ. The mean age of patients was 67.7 ± 10.2 years. The median JAKQ score was 31.3% (12.5–43.8). The Cronbach’s α coefficient of JAKQ was 0.616–0.637, and the test-retest reliability value was 0.902 (p &lt; 0.001). Multivariate logistic regression showed that the higher knowledge level of AF was associated with secondary education or above, an income of more than 2000 yuan, and a history of AF of more than 1 year. Bleeding was associated with a lower JAKQ score, hypertension, and a history of bleeding. Non-bleeding patients on VKA had a better understanding of how often INR should be monitored and what to do if an OAC dose was missed.Conclusion: The Chinese version of JAKQ shows good reliability and validity, indicating that it is a valuable tool for AF and oral anticoagulation (OAC) knowledge assessment. It can be used in clinical practice to guide educational activities and improve the effectiveness and safety of treatment. It was shown that Chinese patients with AF have insufficient knowledge about AF and OAC. Lower JAKQ scores are associated with bleeding, so targeted education is necessary. Targeted educational efforts should focus on patients recently diagnosed with AF and those with lower formal education and income.
A tricarboxylic acid cycle-based machine learning model to select effective drug targets for the treatment of esophageal squamous cell carcinoma
Authors: Liang Yicheng , Tan Binghua , Du Minjun , Wang Bing , Gao Yushun , Wang Minghui 
Published: June 2023

Background: The tricarboxylic acid cycle (TCA cycle) is an important metabolic pathway and closely related to tumor development. However, its role in the development of esophageal squamous cell carcinoma (ESCC) has not been fully investigated.Methods: The RNA expression profiles of ESCC samples were retrieved from the TCGA database, and the GSE53624 dataset was additionally downloaded from the GEO database as the validation cohort. Furthermore, the single cell sequencing dataset GSE160269 was downloaded. TCA cycle-related genes were obtained from the MSigDB database. A risk score model for ESCC based on the key genes of the TCA cycle was built, and its predictive performance was evaluated. The association of the model with immune infiltration and chemoresistance were analyzed using the TIMER database, the R package “oncoPredict” score, TIDE score and so on. Finally, the role of the key gene CTTN was validated through gene knockdown and functional assays.Results: A total of 38 clusters of 8 cell types were identified using the single-cell sequencing data. The cells were divided into two groups according to the TCA cycle score, and 617 genes were identified that were most likely to influence the TCA cycle. By intersecting 976 key genes of the TCA cycle with the results of WGCNA, 57 genes significantly associated with the TCA cycle were further identified, of which 8 were screened through Cox regression and Lasso regression to construct the risk score model. The risk score was a good predictor of prognosis across subgroups of age, N, M classification and TNM stage. Furthermore, BI-2536, camptothecin and NU7441 were identified as possible drug candidates in the high-risk group. The high-risk score was associated with decreased immune infiltration in ESCC, and the low-risk group had better immunogenicity. In addition, we also evaluated the relationship between risk scores and immunotherapy response rates. Functional assays showed that CTTN may affect the proliferation and invasion of ESCC cells through the EMT pathway.Conclusion: We constructed a predictive model for ESCC based on TCA cycle-associated genes, which achieved good prognostic stratification. The model are likely associated with the regulation of tumor immunity in ESCC.
The macrocyclic lactone oxacyclododecindione reduces fibrosis progression
Authors: Saurin Sabrina , Meineck Myriam , Rohr Markus , Roth Wilfried , Opatz Till , Erkel Gerhard , Pautz Andrea , Weinmann-Menke Julia 
Published: June 2023

Background: Renal fibrosis is one of the most important triggers of chronic kidney disease (CKD), and only a very limited number of therapeutic options are available to stop fibrosis progression. As fibrosis is characterized by inflammation, myofibroblast activation, and extracellular matrix (ECM) deposition, a drug that can address all these processes might be an interesting therapeutic option.Methods: We tested in vivo in an ischemia–reperfusion (I/R) model in C57BL/6 mice and in kidney tubular epithelial cells (TEC) (HK2 cell line and primary cells) whether the natural product oxacyclododecindione (Oxa) reduces fibrosis progression in kidney disease. This was evaluated by Western blot, mRNA expression, and mass spectrometry secretome analyses, as well as by immunohistochemistry.Results: Indeed, Oxa blocked the expression of epithelial–mesenchymal transition marker proteins and reduced renal damage, immune cell infiltration, and collagen expression and deposition, both in vivo and in vitro. Remarkably, the beneficial effects of Oxa were also detected when the natural product was administered at a time point of established fibrotic changes, a situation close to the clinical situation. Initial in vitro experiments demonstrated that a synthetic Oxa derivative possesses similar features.Conclusion: Although open questions such as possible side effects need to be investigated, our results indicate that the combination of anti-inflammatory and anti-fibrotic effects of Oxa make the substance a promising candidate for a new therapeutic approach in fibrosis treatment, and thus in the prevention of kidney disease progression.