bluuebunny/crossref_metadata_2025_split huggingface dataset:
Genetic variants in DBC1, SIRT1, UCP2 and ADRB2 as potential biomarkers for severe obesity and metabolic complications
Authors: da Fonseca Ana Carolina Proença , Assis Izadora Sthephanie da Silva , Salum Kaio Cezar Rodrigues , Palhinha Lohanna , Abreu Gabriella de Medeiros , Zembrzuski Verônica Marques , Campos Junior Mario , Nogueira-Neto José Firmino , Cambraia Amanda , Souza Junior Mauro Lucio Ferreira , Maya-Monteiro Clarissa Menezes , Cabello Pedro Hernán , Bozza Patrícia Torres , Carneiro João Regis Ivar 
Published: May 2024

IntroductionObesity is a multifactorial disease associated with the development of many comorbidities. This disease is associated with several metabolic alterations; however, it has been shown that some individuals with obesity do not exhibit metabolic syndrome. Adipose tissue neutralizes the detrimental effects of circulating fatty acids, ectopic deposition, and inflammation, among others, through its esterification into neutral lipids that are stored in the adipocyte. However, when the adipocyte is overloaded, i.e., its expansion capacity is exceeded, this protection is lost, resulting in fatty acid toxicity with ectopic fat accumulation in peripheral tissues and inflammation. In this line, this study aimed to investigate whether polymorphisms in genes that control adipose tissue fat storage capacity are potential biomarkers for severe obesity susceptibility and also metabolic complications.MethodsThis study enrolled 305 individuals with severe obesity (cases, BMI≥35 kg/m2) and 196 individuals with normal weight (controls, 18.5≤BMI≤24.9 kg/m2). Demographic, anthropometric, biochemical, and blood pressure variables were collected from the participants. Plasma levels of leptin, resistin, MCP1, and PAI1 were measured by Bio-Plex 200 Multiplexing Analyzer System. Genomic DNA was extracted and variants in DBC1 (rs17060940), SIRT1 (rs7895833 and rs1467568), UCP2 (rs660339), PPARG (rs1801282) and ADRB2 (rs1042713 and rs1042714) genes were genotyped by PCR allelic discrimination using TaqMan® assays.ResultsOur findings indicated that SIRT1 rs7895833 polymorphism was a risk factor for severe obesity development in the overdominant model. SIRT1 rs1467568 and UCP2 rs660339 were associated with anthropometric traits. SIRT1 rs1467568 G allele was related to lower medians of body adipose index and hip circumference, while the UCP2 rs660339 AA genotype was associate with increased body mass index. Additionally, DBC1 rs17060940 influenced glycated hemoglobin. Regarding metabolic alterations, 27% of individuals with obesity presented balanced metabolic status in our cohort. Furthermore, SIRT1 rs1467568 AG genotype increased 2.5 times the risk of developing metabolic alterations. No statistically significant results were observed with Peroxisome Proliferator-Activated Receptor Gama and ADRB2 polymorphisms.Discussion/ConclusionThis study revealed that SIRT1 rs7895833 and rs1467568 are potential biomarkers for severe obesity susceptibility and the development of unbalanced metabolic status in obesity, respectively. UCP2 rs660339 and DBC1 rs17060940 also showed a significant role in obesity related-traits.
Clinical outcomes of immune checkpoint inhibitor combined with other targeted or immunological therapy regimens for the treatment of advanced bile tract cancer: a systematic review and meta-analysis
Authors: Zhou Jianpeng , Li Jia , Fan Zhongqi , Lv Guoyue , Wang Guangyi 
Published: May 2024

Background and aimsA single immune checkpoint inhibitor (ICI) regimen has limited value in treating advanced bile tract cancer (BTC); therefore, ICI combination therapy is often applied. This meta-analysis aimed to evaluate the effectiveness and safety of ICI combination therapy for advanced BTC.MethodsThe study protocol was registered on PROSPERO (CRD42023452422). Data on the median progression-free survival (PFS), median overall survival (OS), objective response rate (ORR), disease control rate (DCR), and grade ≥3 adverse events (AEs) reported in relevant studies were pooled and analyzed to determine the efficacy and safety of ICI combination therapy.ResultsIn total, 15 studies with 665 patients were included in this meta-analysis. The overall ORR and DCR were 34.6% and 77.6%, respectively. The overall median PFS and OS were 6.06 months [95% confidence interval (CI): 4.91–7.21] and 12.11 months (95% CI: 10.66–13.55), respectively. Patients receiving ICI combination therapy in addition to other therapies had a considerably prolonged median PFS and OS (z=9.69, p&lt;0.001 and z=16.17, p&lt;0.001). Patients treated as first-line treatment had a substantially longer median PFS and OS compared to patients treated as non-first-line treatment (z=11.19, p&lt;0.001 and z=49.17, p&lt;0.001). The overall pooled grade ≥3 AEs rate was 38.2% (95% CI: 0.268–0.497) and was not influenced by whether ICI therapy was combined with other treatments or not or the treatment line.ConclusionAdvanced BTC patients may benefit from ICI combination treatment without additional AEs. However, concurrent chemotherapy or radiotherapy is still needed to achieve better outcomes.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/, identifier CRD42023452422.
Interpretable machine learning for predicting the response duration to Sintilimab plus chemotherapy in patients with advanced gastric or gastroesophageal junction cancer
Authors: Wang Dan-qi , Xu Wen-huan , Cheng Xiao-wei , Hua Lei , Ge Xiao-song , Liu Li , Gao Xiang 
Published: May 2024

BackgroundSintilimab plus chemotherapy has proven effective as a combination immunotherapy for patients with advanced gastric and gastroesophageal junction adenocarcinoma (GC/GEJC). A multi-center study conducted in China revealed a median progression-free survival (PFS) of 7.1 months. However, the prediction of response duration to this immunotherapy has not been thoroughly investigated. Additionally, the potential of baseline laboratory features in predicting PFS remains largely unexplored. Therefore, we developed an interpretable machine learning (ML) framework, iPFS-SC, aimed at predicting PFS using baseline (pre-treatment) laboratory features and providing interpretations of the predictions.Materials and methodsA cohort of 146 patients with advanced GC/GEJC, along with their baseline laboratory features, was included in the iPFS-SC framework. Through a forward feature selection process, predictive baseline features were identified, and four ML algorithms were developed to categorize PFS duration based on a threshold of 7.1 months. Furthermore, we employed explainable artificial intelligence (XAI) methodologies to elucidate the relationship between features and model predictions.ResultsThe findings demonstrated that LightGBM achieved an accuracy of 0.70 in predicting PFS for advanced GC/GEJC patients. Furthermore, an F1-score of 0.77 was attained for identifying patients with PFS durations shorter than 7.1 months. Through the feature selection process, we identified 11 predictive features. Additionally, our framework facilitated the discovery of relationships between laboratory features and PFS.ConclusionA ML-based framework was developed to predict Sintilimab plus chemotherapy response duration with high accuracy. The suggested predictive features are easily accessible through routine laboratory tests. Furthermore, XAI techniques offer comprehensive explanations, both at the global and individual level, regarding PFS predictions. This framework enables patients to better understand their treatment plans, while clinicians can customize therapeutic approaches based on the explanations provided by the model.
What improvements do general exercise training and traditional Chinese exercises have on knee osteoarthritis? A narrative review based on biological mechanisms and clinical efficacy
Authors: Du Xingbin , Fan Rao , Kong Jianda 
Published: May 2024

BackgroundKnee osteoarthritis (KOA) is a disease that significantly affects the quality of life of patients, with a complex pathophysiology that includes degeneration of cartilage and subchondral bone, synovitis, and associations with mechanical load, inflammation, metabolic factors, hormonal changes, and aging.ObjectiveThis article aims to comprehensively review the biological mechanisms and clinical effects of general exercise training and traditional Chinese exercises (such as Tai Chi and Qigong) on the treatment of KOA, providing references for the development of clinical exercise prescriptions.MethodsA systematic search of databases including PubMed, Web of Science, Google Scholar, and China National Knowledge Infrastructure (CNKI) was conducted, reviewing studies including randomized controlled trials (RCTs), observational studies, systematic reviews, and meta-analyses. Keywords included “knee osteoarthritis,” “exercise therapy,” “physical activity,” and “traditional Chinese exercise.”Results and conclusionGeneral exercise training positively affects KOA by mechanisms such as promoting blood circulation, improving the metabolism of inflammatory factors, enhancing the expression of anti-inflammatory cytokines, and reducing cartilage cell aging. Traditional Chinese exercises, like Tai Chi and Qigong, benefit the improvement of KOA symptoms and tissue repair by regulating immune function and alleviating joint inflammation. Clinical studies have shown that both types of exercise can improve physical function, quality of life, and pain relief in patients with KOA. Both general exercise training and traditional Chinese exercises are non-pharmacological treatment options for KOA that can effectively improve patients’ physiological function and quality of life. Future research should further explore the long-term effects and biological mechanisms of these exercise interventions and develop personalized exercise programs based on the specific needs of patients.
Screening of drug targets for tuberculosis on the basis of transcription factor regulatory network and mRNA sequencing technology
Authors: Wang Shuai , Yan Na , Yang Yue , Sun Li , Huang Yingxin , Zhang Jian , Xu Guangyu 
Published: May 2024

BackgroundTuberculosis is a worldwide epidemic disease, posing a serious threat to human health. To find effective drug action targets for Mycobacterium tuberculosis, differentially expressed genes in tuberculosis patients and healthy people were screened by mRNA sequencing in this study. A total of 556 differentially expressed genes in tuberculosis patients and healthy people were screened out by mRNA sequencing technology. 26 transcription factors and 66 corresponding target genes were screened out in the AnimalTFDB 3.0 database, and a transcription factor regulatory network was constructed.ResultsThree key transcription factors (TP53, KLF5 and GATA2) and one key gene (AKT1) were screened as new potential drug targets and diagnostic targets for tuberculosis by MCODE cluster analysis, and the key genes and key transcription factors were verified by RT-PCR. Finally, we constructed the and a key factor and KEGG signaling pathway regulatory network to clarify the possible molecular pathogenesis of tuberculosis.ConclusionThis study suggested M. tuberculosis may activate the AKT1 gene expression by regulating transcription factors TP53, KLF5, and GATA2, thus activating the B cell receptor signaling pathway to induce the infection and invasion of M. tuberculosis. AKT1, TP53, KLF5, and GATA2 can be used as new potential drug targets for tuberculosis.
P-hydroxybenzaldehyde protects Caenorhabditis elegans from oxidative stress and β-amyloid toxicity
Authors: Yu Xingzhi , Tao Jie , Xiao Tian , Duan Xiaohua 
Published: May 2024

IntroductionGastrodia elata is the dried tuber of the orchid Gastrodia elata Bl. It is considered a food consisting of a source of precious medicinal herbs, whose chemical composition is relatively rich. Gastrodia elata and its extracted fractions have been shown to have neuroprotective effects. P-hydroxybenzaldehyde (p-HBA), as one of the main active components of Gastrodia elata, has anti-inflammatory, antioxidative stress, and cerebral protective effects, which has potential for the treatment of Alzheimer’s disease (AD). The aim of this study was to verify the role of p-HBA in AD treatment and to investigate its mechanism of action in depth based using the Caenorhabditis elegans (C. elegans) model.MethodsIn this study, we used paralysis, lifespan, behavioral and antistress experiments to investigate the effects of p-HBA on AD and aging. Furthermore, we performed reactive oxygen species (ROS) assay, thioflavin S staining, RNA-seq analysis, qPCR validation, PCR Array, and GFP reporter gene worm experiment to determine the anti-AD effects of p-HBA, as well as in-depth studies on its mechanisms.Resultsp-HBA was able to delay paralysis, improve mobility and resistance to stress, and delay aging in the AD nematode model. Further mechanistic studies showed that ROS and lipofuscin levels, Aβ aggregation, and toxicity were reduced after p-HBA treatment, suggesting that p-HBA ameliorated Aβ-induced toxicity by enhancing antioxidant and anti-aging activity and inhibiting Aβ aggregation. p-HBA had a therapeutic effect on AD by improving stress resistance, as indicated by the down-regulation of NLP-29 and UCR-11 expression and up-regulation of PQN-75 and LYS-3 expression. In addition, the gene microarray showed that p-HBA treatment played a positive role in genes related to AD, anti-aging, ribosomal protein pathway, and glucose metabolism, which were collectively involved in the anti-AD mechanism of p-HBA. Finally, we also found that p-HBA promoted nuclear localization of DAF-16 and increased the expression of SKN-1, SOD-3, and GST-4, which contributed significantly to inhibition of Aβ toxicity and enhancement of antioxidative stress.ConclusionOur work suggests that p-HBA has some antioxidant and anti-aging activities. It may be a viable candidate for the treatment and prevention of Alzheimer’s disease.
Neurocognitive outcome in children with sickle cell disease after myeloimmunoablative conditioning and haploidentical hematopoietic stem cell transplantation: a non-randomized clinical trial
Authors: Braniecki Suzanne , Vichinsky Elliott , Walters Mark C. , Shenoy Shalini , Shi Qiuhu , Moore Theodore B. , Talano Julie-An , Parsons Susan K. , Flower Allyson , Panarella Anne , Fabricatore Sandra , Morris Erin , Mahanti Harshini , Milner Jordan , McKinstry Robert C. , Duncan Christine N. , van de Ven Carmella , Cairo Mitchell S. 
Published: May 2024

BackgroundDue to the risk of cerebral vascular injury, children and adolescents with high-risk sickle cell disease (SCD) experience neurocognitive decline over time. Haploidentical stem cell transplantation (HISCT) from human leukocyte antigen-matched sibling donors may slow or stop progression of neurocognitive changes.ObjectivesThe study is to determine if HISCT can ameliorate SCD-associated neurocognitive changes and prevent neurocognitive progression, determine which specific areas of neurocognitive functioning are particularly vulnerable to SCD, and determine if there are age-related differences in neurocognitive functioning over time.MethodsWe performed neurocognitive and neuroimaging in SCD recipients following HISCT. Children and adolescents with high-risk SCD who received parental HISCT utilizing CD34+ enrichment and mononuclear cell (T-cell) addback following myeloimmunoablative conditioning received cognitive evaluations and neuroimaging at three time points: pre-transplant, 1 and 2 years post-transplant.ResultsNineteen participants (13.1 ± 1.2 years [3.3–20.0]) received HISCT. At 2 years post-transplant, neuroimaging and cognitive function were stable. Regarding age-related differences pre-transplantation, older children (≥13 years) had already experienced significant decreases in language functioning (p &lt; 0.023), verbal intelligence quotient (p &lt; 0.05), non-verbal intelligence quotient (p &lt; 0.006), and processing speed (p &lt; 0.05), but normalized post-HISCT in all categories.ConclusionThus, HISCT has the potential to ameliorate SCD-associated neurocognitive changes and prevent neurocognitive progression. Further studies are required to determine if neurocognitive performance remains stable beyond 2 years post-HISCT.Clinical trial registration: The study was conducted under an investigator IND (14359) (MSC) and registered at clinicaltrials.gov (NCT01461837).
Establishment and validation of a 3-month prediction model for poor functional outcomes in patients with acute cardiogenic cerebral embolism related to non-valvular atrial fibrillation
Authors: Hu Lan , Qiao Zhenguo , Xu Mengshi , Feng Jie , Shan Qingting , Sheng Xihua , Xu Guoli , Xu Yuan , Hu Wenze , Wang Guojun , Jin Xuehong 
Published: May 2024

ObjectivesCardiogenic cerebral embolism (CCE) poses a significant health risk; however, there is a dearth of published prognostic prediction models addressing this issue. Our objective is to establish prognostic prediction models (PM) for predicting poor functional outcomes at 3 months in patients with acute CCE associated with non-valvular atrial fibrillation (NVAF) and perform both internal and external validations.MethodsWe included a total of 730 CCE patients in the development cohort. The external regional validation cohort comprised 118 patients, while the external time-sequential validation cohort included 63 patients. Multiple imputation by chained equations (MICE) was utilized to address missing values and the least absolute shrink and selection operator (LASSO) regression was implemented through the glmnet package, to screen variables.ResultsThe 3-month prediction model for poor functional outcomes, denoted as N-ABCD2, was established using the following variables: NIHSS score at admission (N), Age (A), Brain natriuretic peptide (BNP), C-reactive protein (CRP), D-dimer polymers (D), and discharge with antithrombotic medication (D). The model’s Akaike information criterion (AIC) was 637.98, and the area under Curve (AUC) for the development cohort, external regional, and time-sequential cohorts were 0.878 (95% CI, 0.854–0.902), 0.918 (95% CI, 0.857–0.979), and 0.839 (95% CI, 0.744–0.934), respectively.ConclusionThe N-ABCD2 model can accurately predict poor outcomes at 3 months for CCE patients with NVAF, demonstrating strong prediction abilities. Moreover, the model relies on objective variables that are readily obtainable in clinical practice, enhancing its convenience and applicability in clinical settings.
Clinicopathological characteristics and prognosis of synchronous brain metastases from non-small cell lung cancer compared with metachronous brain metastases
Authors: Li Jing , Zhang Xiaofang , Wang Ye , Jin Yi , Song Yingqiu , Wang Tianlu 
Published: May 2024

PurposeBrain metastasis (BM) from non-small cell lung cancer (NSCLC) is a serious complication severely affecting patients’ prognoses. We aimed to compare the clinicopathological features and prognosis of synchronous and metachronous BM from NSCLC.MethodsClinical data of 461 patients with brain metastases from NSCLC who visited the Cancer Hospital of China Medical University from 2005 to 2017 were retrospectively collected. We analyzed the pathophysiological characteristics of synchronous and metachronous BM from NSCLC and survival rates of the patients. Propensity score matching analysis was used to reduce bias between groups. In addition, we used the Kaplan-Meier method for survival analysis, log-rank test to compare survival rates, and Cox proportional hazards regression model for multivariate prognosis analysis.ResultsAmong 461 patients with BM, the number of people who met the inclusion criteria was 400 cases, and after 1:2 propensity score matching,130 had synchronous BM and 260 had metachronous BM. The survival time was longer for metachronous BM in driver mutation-negative patients with squamous cell carcinoma than synchronous BM. Conversely, metachronous and synchronous BM with gene mutations and adenocarcinoma showed no differences in survival time. Multivariate analysis showed that metachronous BM was an independent prognostic factor for overall survival. Furthermore, the pathological type squamous cell carcinoma and Karnofsky Performance Status score &lt;80 were independent risk factors affecting overall survival.ConclusionBM status is an independent factor influencing patient outcome. Moreover, synchronous and metachronous BM from NSCLC differ in gene mutation profile, pathological type, and disease progression and hence require different treatments.
Is it possible to diagnose therapeutic adherence in mild cognitive impairment and dementia patients in clinical practice?
Authors: Barnestein-Fonseca Pilar , Guerrero-Pertiñez Gloria , Gúzman-Parra Jose , Valera-Moreno Esperanza , Mayoral-Cleries Fermín 
Published: May 2024

BackgroundNon-adherence is common and contributes to adverse health outcomes, reduced quality of life, and increased healthcare expenditure. The objective of this study was to assess the diagnostic validity to estimate the prevalence of non-adherence in patients with mild cognitive impairment (MCI) and dementia using two self-reported methods (SRMs) that are useful and easy in clinical practice, considering the pill count as a reference method (RM).MethodsThe cohort study was nested in a multicenter randomized controlled trial NCT03325699. A total of 387 patients from 8 health centers were selected using a non-probabilistic consecutive sampling method. Inclusion criteria were as follows: a score of 20–28 points on the Mini-Mental State Examination (MMSE); older than 55 years; taking prescribed medication; and are in charge of their own medication use. Participants were followed up for 18 months after the baseline visit, i.e., 6, 12, and 18 months. Variables related with treatment adherences were measured in all visits. The variables included age, sex, treatment, comorbidities, and the MMSE test. Adherences included pill counts and Morisky–Green test (MGT) and Batalla test (BT) as SRMs. Statistical analysis included descriptive analysis and 95% confidence intervals (CIs). The diagnostic validity included the following: 1) open comparison statistical association between SRMs and RMs and 2) hierarchy comparison: the RM as the best method to assess non-adherence, kappa value (k), sensitivity (S), specificity (Sp), and likelihood ratio (PPV/PPN).ResultsA total of 387 patients were recruited with an average age of 73.29 years (95% CI, 72.54–74.04), of which 59.5% were female. Comorbidities were 54.4% HTA, 35.9% osteoarticular pathology, and 24.5% DM. The MMSE mean score was 25.57 (95% CI, 25.34–25.8). The treatment adherence for the RM oscillates between 22.5% in the baseline and 26.3%, 14.8%, and 17.9% in the follow-up visits. For SRMs, the treatment adherence oscillates between 43.5% in the baseline and 32.4%, 21.9%, and 20.3% in the follow-up visits. The kappa value was statistically significant in all the comparison in all visits with a score between 0.16 and 035. Regarding the diagnostic validity, for the MGT, the sensibility oscillated between 0.4 and 0.58, and the specificity oscillated between 0.68 and 0.87; for the BT, the sensibility oscillated between 0.4 and 0.7, and the specificity oscillated between 0.66 and 0.9; and when both tests were used together, the sensibility oscillated between 0.22 and 0.4, and the specificity oscillated between 0.85 and 0.96.ConclusionSRMs classify non-adherent subjects correctly. They are very easy to use and yield quick results in clinical practice, so SRMs would be used for the non-adherence diagnosis in patients with MCI and mild dementia.