Background: Visceral white adipose tissue (vWAT) inflammation is a critical pathology of obesity-caused heart damage and is closely associated with adipocyte endoplasmic reticulum (ER) dysfunction. Serine (or cysteine) peptidase inhibitor, clade A, member 3C (Serpina3c) has been identified as an adipokine with anti-vWAT inflammatory effects. However, it remains unclear whether Serpina3c deficiency promotion of vWAT inflammation involves adipocyte ER dysfunction and whether it further contributes to heart damage in obesity. Methods: Wild type and Serpina3c knockout (Serpina3c–/–) mice were fed a high-fat diet (HFD) for 12 weeks. An adeno-associated virus (AAV) was injected locally into epididymal white adipose tissue (eWAT) of Serpina3c–/– mice to induce eWAT-adipocyte- specific overexpression of Serpina3c (AAV-Serpina3c) or knockdown of hypoxia-inducible factor 1α (AAV-shHIF1α). In vitro experiments were performed in 3T3-L1 adipocytes. Results: Serpina3c–/– mice exhibited more severe eWAT, serum and heart inflammation after HFD feeding. Consistently, these adverse phenotypes were mitigated in AAV-Serpina3c and AAV-shHIF1α mice. Mechanistically, ER oxidoreductase 1α (Ero1α) and protein disulfide isomerase (PDI) family members PDIA3 and PDIA4 were found to be target genes of HIF1α. In the obese mice, Serpina3c deficiency caused adipocyte more hypertrophy, and activated HIF1α-Ero1α/PDI mediated ER overoxidation and ER stress in eWAT. Subsequently, this led to increased adipocyte apoptosis and chemokine production and decreased adiponectin expression, which promoted macrophage infiltration and M1 polarization in eWAT, thus exacerbating eWAT inflammation and ultimately facilitating serum and distal heart inflammation. Conclusion These findings indicate that Serpina3c is a significant regulator of adipocyte ER redox homeostasis, thus highlighting Serpina3c as a potential therapeutic target for obesity-related eWAT inflammation and heart damage.

Objective To investigate the status of population dynamics and distribution changes of Aedes aegypti in Guangdong Province.Methods Continuous monitoring was conducted from May 2018 to July 2024 in Wushi Town and Qishui Town,Leizhou City,Zhanjiang City,Guangdong Province.Additionally,a survey of the distribution of Ae.aegypti along the Leizhou Peninsula coast was carried out.Results The density of Ae.aegypti in Zhanjiang showed a gradual decline from 2018 to 2024.The last detection of adult Ae.aegypti in Wushi Town was in September 2021,and the last larva was found in October 2023.No Ae.aegypti was detected in Qishui Town during surveys from 2021 to 2024.A survey of 18 coastal villages in the Leizhou Peninsula revealed no detections of Ae.aegypti.Conclusions This study provides a basis for understanding the distribution and population density fluctuations of Ae.aegypti,assessing its invasion risk,and scientifically conducting relevant prevention and control efforts.

OBJECTIVES: To study the clinical and genetic characteristics of children with congenital adrenal hyperplasia (CAH). METHODS: Clinical data, laboratory findings, and genetic test results of 63 children diagnosed with CAH at Henan Children's Hospital from January 2017 to December 2024 were retrospectively reviewed. RESULTS: Of the 63 patients, the mean age at the first visit was (21 ± 14) days; 29 (46%) were of male sex and 34 (54%) were of female sex. The predominant clinical manifestations were poor weight gain or weight loss (92%, 58/63), poor feeding (84%, 53/63), skin hyperpigmentation (83%, 52/63), and female external genital anomalies (100%, 34/34). Laboratory abnormalities included hyponatremia (87%, 55/63), hyperkalemia (68%, 43/63), metabolic acidosis (68%, 43/63), and markedly elevated 17-hydroxyprogesterone (92%, 58/63), testosterone (89%, 56/63), and adrenocorticotropic hormone (81%, 51/63). Among 49 patients who underwent genetic testing, CYP21A2 variants were identified in 90% (44/49), with c.293-13A/C>G (33%, 30/91) and large deletions/gene conversions (29%, 26/91) being the most frequent; STAR (8%, 4/49) and HSD3B2 (2%, 1/49) variants were also detected. Following hormone replacement therapy, electrolyte disturbances were corrected in 57 cases, with significant reductions in 17-hydroxyprogesterone, adrenocorticotropic hormone, and testosterone levels (P<0.001). CONCLUSIONS CAH presenting in neonates or young infants is characterized by electrolyte imbalance, external genital anomalies, and abnormal hormone levels. Genetic testing enables definitive subtype classification; in CYP21A2-related CAH, c.293-13A/C>G is a hotspot variant. These findings underscore the clinical value of genetic testing for early diagnosis and genetic counseling in CAH. Citation:Chinese Journal of Contemporary Pediatrics, 2025, 27(11): 1367-1372.
Humans ; Adrenal Hyperplasia, Congenital/diagnosis* ; Male ; Female ; Retrospective Studies ; Infant ; Infant, Newborn

This study aims to explore the synergistic effects of the main components in salvianolic acids for Injection(SAFI) on key pathological events in cerebral ischemia, elucidating the pharmacological characteristics of SAFI in neuroprotection. Two major pathological gene modules related to endothelial injury and neuroinflammation in cerebral ischemia were mined from single-cell data. According to the topological distance calculated in network medicine, potential synergistic component combinations of SAFI were screened out. The results showed that the combination of caffeic acid and salvianolic acid B scored the highest in addressing both endothelial injury and neuroinflammation, demonstrating potential synergistic effects. The cell experiments confirmed that the combination of these two components at a ratio of 1∶1 significantly protected brain microvascular endothelial cells(bEnd.3) from oxygen-glucose deprivation/reoxygenation(OGD/R)-induced reperfusion injury and effectively suppressed lipopolysaccharide(LPS)-induced neuroinflammatory responses in microglial cells(BV-2). This study provides a new method for uncovering synergistic effects among active components in traditional Chinese medicine(TCM) and offers novel insights into the multi-component, multi-target acting mechanisms of TCM.
Brain Ischemia/metabolism* ; Neuroprotective Agents/pharmacology* ; Animals ; Drugs, Chinese Herbal/administration & dosage* ; Benzofurans/pharmacology* ; Mice ; Drug Synergism ; Caffeic Acids/pharmacology* ; Polyphenols/pharmacology* ; Humans ; Alkenes/pharmacology* ; Endothelial Cells/drug effects* ; Depsides

This study aims to elucidate the role and mechanism of clematichinenoside AR(CAR) in protecting bone marrow mesenchymal stem cells(BMSCs) from hypoxia-induced apoptosis. BMSCs were isolated by the bone fragment method and identified by flow cytometry. Cells were cultured under normal conditions(37℃, 5% CO_2) and hypoxic conditions(37℃, 90% N_2, 5% CO_2) and treated with CAR. The BMSCs were classified into eight groups: control(normal conditions), CAR(normal conditions + CAR), hypoxia 24 h, hypoxia 24 h + CAR, hypoxia 48 h, hypoxia 48 h + CAR, hypoxia 72 h, and hypoxia 72 h + CAR. The cell counting kit-8(CCK-8) assay and terminal-deoxynucleoitidyl transferase mediated nick end labeling(TUNEL) were employed to measure cell proliferation and apoptosis, respectively. The number of mitochondria and mitochondrial membrane potential were measured by MitoTracker®Red CM-H2XRo staining and JC-1 staining, respectively. The level of reactive oxygen species(ROS) was measured with the DCFH-DA fluorescence probe. The protein levels of B-cell lymphoma-2 associated X protein(BAX), caspase-3, and optic atrophy 1(OPA1) were determined by Western blot. The results demonstrated that CAR significantly increased cell proliferation. Compared with the control group, the hypoxia groups showed increased apoptosis rates, reduced mitochondria, elevated ROS levels, decreased mitochondrial membrane potential, upregulated expression of BAX and caspase-3, and downregulated expression of OPA1. In comparison to the corresponding hypoxia groups, CAR intervention significantly decreased the apoptosis rate, increased mitochondria, reduced ROS levels, elevated mitochondrial membrane potential, downregulated the expression of BAX and caspase-3, and upregulated the expression of OPA1. Therefore, it can be concluded that CAR may exert an anti-apoptotic effect on BMSCs under hypoxic conditions by regulating OPA1 to maintain mitochondrial homeostasis.
Mesenchymal Stem Cells/metabolism* ; Apoptosis/drug effects* ; Mitochondria/metabolism* ; Animals ; Rats ; Cell Hypoxia/drug effects* ; Homeostasis/drug effects* ; Reactive Oxygen Species/metabolism* ; Rats, Sprague-Dawley ; Membrane Potential, Mitochondrial/drug effects* ; Saponins/pharmacology* ; Caspase 3/genetics* ; Male ; bcl-2-Associated X Protein/genetics* ; Bone Marrow Cells/metabolism* ; Cell Proliferation/drug effects* ; Protective Agents/pharmacology* ; Cells, Cultured

BACKGROUND AND OBJECTIVE: Patients with glioma experience a high symptom burden and have diverse palliative care needs. However, the assessment scales used in palliative care remain non-standardized and highly heterogeneous. To evaluate the application patterns of the current scales used in palliative care for glioma, we aim to identify gaps and assess the need for disease-specific scales in glioma palliative care. METHODS: We conducted a systematic search of five databases including PubMed, Web of Science, Medline, EMBASE, and CINAHL for quantitative studies that reported scale-based assessments in glioma palliative care. We extracted data on scale characteristics, domains, frequency, and psychometric properties. Quality assessments were performed using the Cochrane ROB 2.0 and ROBINS-I tools. RESULTS: Of the 3,405 records initially identified, 72 studies were included. These studies contained 75 distinct scales that were used 193 times. Mood (21.7%), quality of life (24.4%), and supportive care needs (5.2%) assessments were the most frequently assessed items, exceeding half of all scale applications. Among the various assessment dimensions, the Distress Thermometer (DT) was the most frequently used tool for assessing mood, while the Short Form-36 Health Survey Questionnaire (SF-36) was the most frequently used tool for assessing quality of life. The Mini Mental Status Examination (MMSE) was the most common tool for cognitive assessment. Performance status (5.2%) and social support (6.8%) were underrepresented. Only three brain tumor-specific scales were identified. Caregiver-focused scales were limited and predominantly burden-oriented. CONCLUSIONS: There are significant heterogeneity, domain imbalances, and validation gaps in the current use of assessment scales for patients with glioma receiving palliative care. The scale selected for use should be comprehensive and user-friendly.
Humans ; Glioma/psychology* ; Palliative Care/methods* ; Quality of Life ; Psychometrics ; Brain Neoplasms/psychology*

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective To screen biomarkers for forensic identification of acute myocardial infarction (AMI) by non-targeted metabolomic studies on changes of urine metabolites in rats with AMI.Methods The rat models of the sham surgery group,AMI group and hyperlipidemia+acute myocardial infarction (HAMI) group were established.Ultra-high performance liquid chromatography-mass spectrometry (UPLC-MS) was used to analyze the changes of urine metabolic spectrometry in AMI rats.Principal compo-nent analysis,partial least squares-discriminant analysis,and orthogonal partial least squares-discriminant analysis were used to screen differential metabolites.The MetaboAnalyst database was used to analyze the metabolic pathway enrichment and access the predictive ability of differential metabolites.Results A total of 40 and 61 differential metabolites associated with AMI and HAMI were screened,respec-tively.Among them,22 metabolites were common in both rat models.These small metabolites were mainly concentrated in the niacin and nicotinamide metabolic pathways.Within the 95% confidence in-terval,the area under the curve (AUC) values of receiver operator characteristic curve for N8-acetyl-spermidine,3-methylhistamine,and thymine were greater than 0.95.Conclusion N8-acetylspermidine,3-methylhistamine,and thymine can be used as potential biomarkers for AMI diagnosis,and abnormal metabolism in niacin and nicotinamide may be the main causes of AMI.This study can provide reference for the mechanism and causes of AMI identification.

Background/Aims: Despite the high efficacy of direct-acting antivirals (DAAs), approximately 1–3% of hepatitis C virus (HCV) patients fail to achieve a sustained virological response. We conducted a nationwide study to investigate risk factors associated with DAA treatment failure. Machine-learning algorithms have been applied to discriminate subjects who may fail to respond to DAA therapy. Methods: We analyzed the Taiwan HCV Registry Program database to explore predictors of DAA failure in HCV patients. Fifty-five host and virological features were assessed using multivariate logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), and artificial neural network. The primary outcome was undetectable HCV RNA at 12 weeks after the end of treatment. Results: The training (n=23,955) and validation (n=10,346) datasets had similar baseline demographics, with an overall DAA failure rate of 1.6% (n=538). Multivariate logistic regression analysis revealed that liver cirrhosis, hepatocellular carcinoma, poor DAA adherence, and higher hemoglobin A1c were significantly associated with virological failure. XGBoost outperformed the other algorithms and logistic regression models, with an area under the receiver operating characteristic curve of 1.000 in the training dataset and 0.803 in the validation dataset. The top five predictors of treatment failure were HCV RNA, body mass index, α-fetoprotein, platelets, and FIB-4 index. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model (cutoff value=0.5) were 99.5%, 69.7%, 99.9%, 97.4%, and 99.5%, respectively, for the entire dataset. Conclusions Machine learning algorithms effectively provide risk stratification for DAA failure and additional information on the factors associated with DAA failure.