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*

OBJECTIVES: To investigate the chain mediating role of family care and emotional management in the relationship between social support and anxiety among rural primary school students. METHODS: A questionnaire survey was conducted among students in grades 4 to 6 from four counties in Hunan Province. Data were collected using the Social Support Rating Scale, Family Care Index Scale, Emotional Intelligence Scale, and Generalized Anxiety Disorder -7. Logistic regression analysis was used to explore the influencing factors of anxiety symptoms. Mediation analysis was conducted to assess the chain mediating effects of family care and emotional management between social support and anxiety. RESULTS: A total of 4 141 questionnaires were distributed, with 3 874 valid responses (effective response rate: 93.55%). The prevalence rate of anxiety symptoms among these students was 9.32% (95%CI: 8.40%-10.23%). Significant differences were observed in the prevalence rates of anxiety symptoms among groups with different levels of social support, family functioning, and emotional management ability (P<0.05). The total indirect effect of social support on anxiety symptoms via family care and emotional management was significant (β=-0.137, 95%CI: -0.167 to -0.109), and the direct effect of social support on anxiety symptoms remained significant (P<0.05). Family care and emotional management served as significant chain mediators in the relationship between social support and anxiety symptoms (β=-0.025,95%CI:-0.032 to -0.018), accounting for 14.5% of the total effect. CONCLUSIONS Social support can directly affect anxiety symptoms among rural primary school students and can also indirectly influence anxiety symptoms through the chain mediating effects of family care and emotional management. These findings provide scientific evidence for the prevention of anxiety in primary school students from multiple perspectives.
Humans ; Female ; Male ; Social Support ; Anxiety/etiology* ; Child ; Students/psychology* ; Emotions ; Logistic Models

OBJECTIVES: To assess the preliminary efficacy and safety of a dose-intensified C5VD regimen (cisplatin, 5-fluorouracil, vincristine, and doxorubicin) in children with locally advanced hepatoblastoma. METHODS: This prospective study enrolled 24 children with newly diagnosed, locally advanced hepatoblastoma who received the dose-intensified C5VD regimen at Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, and Shanghai Children's Hospital between January 2020 and December 2023. Clinical characteristics, treatment outcomes, and chemotherapy-related toxicities were analyzed. RESULTS: Of the 24 patients, 13 were male and 11 were female, with a median age at diagnosis of 18.7 months (range: 3.5-79.4 months). All patients achieved complete macroscopic resection of hepatic lesions without liver transplantation. Serum alpha-fetoprotein levels decreased significantly after two chemotherapy cycles. During a median follow-up of 38.4 months (range: 15.8-50.7 months), all patients maintained continuous complete remission, with 3-year event-free survival and overall survival rates of 100%. Across 144 chemotherapy cycles, the incidence rates of grade 3-4 neutropenia, thrombocytopenia, and infections were 97%, 77%, and 71%, respectively; no treatment-related deaths occurred. Notably, 5 patients (21%) developed Brock grade ≥3 hearing loss, of whom 1 required a hearing aid. CONCLUSIONS The dose-intensified C5VD regimen demonstrates significant efficacy with an overall favorable safety profile in the treatment of newly diagnosed, locally advanced pediatric hepatoblastoma. Grade 3-4 myelosuppression and infection are the predominant toxicities. However, high‑dose cisplatin-induced ototoxicity remains a concern, highlighting the need for improved otoprotective strategies.
Humans ; Hepatoblastoma/pathology* ; Male ; Female ; Infant ; Liver Neoplasms/pathology* ; Antineoplastic Combined Chemotherapy Protocols/therapeutic use* ; Child, Preschool ; Prospective Studies ; Doxorubicin/adverse effects* ; Child ; Cisplatin/adverse effects* ; Vincristine/adverse effects* ; Fluorouracil/adverse effects*

OBJECTIVE: To investigate the effect of different previous treatments on the efficacy of flumatinib in patients with chronic myeloid leukemia (CML). METHODS: The clinical data of 69 patients with CML treated with flumatinib in the Affiliated Hospital of Xuzhou Medical University from 2019 to 2024 were retrospectively analyzed. The patients were divided into a first-line flumatinib group and a first-line non-flumatinib group according to whether flumatinib was used as first-line treatment. The molecular response (MR) at 3, 6 and 12 months of treatment was compared between the two groups to evaluate the early efficacy. The first-line non-flumatinib group was further divided into imatinib group, nilotinib group, and dasatinib group according to the previous first-line drugs used. The efficacy data of these three groups at 3, 6 and 12 months after switching to flumatinib were collected, and the MR was evaluated to compare efficacy differences. RESULTS: The rate of early molecular response (EMR) in the first-line flumatinib group was significantly higher than that in the first-line non-flumatinib group (P < 0.05). At 6 months and 12 months of treatment, the proportion of patients achieving MR 4.5 in the first-line flumatinib group was significantly higher than that in the first-line non-flumatinib group (P < 0.05). Compared with the imatinib and nilotinib groups, the previous dasatinib group showed a significantly higher proportion of patients achieving MR 5.0 at 3, 6, and 12 months after switching to flumatinib (P < 0.05). CONCLUSION Compared with the previous treatment with other tyrosine kinase inhibitors (TKIs), initial use of flumatinib at diagnosis enable patients to achieve deeper molecular remission more rapidly. Compared with previous use of imatinib or nilotinib, previous use of dasatinib is associated with deeper molecular remission after switching to flumatinib.
Humans ; Leukemia, Myelogenous, Chronic, BCR-ABL Positive/drug therapy* ; Retrospective Studies ; Imatinib Mesylate/therapeutic use* ; Dasatinib/therapeutic use* ; Treatment Outcome ; Pyrimidines/therapeutic use* ; Female ; Male ; Protein Kinase Inhibitors/therapeutic use* ; Middle Aged ; Antineoplastic Agents/therapeutic use*

OBJECTIVE: To study the efficacy and prognosis of patients with myelodysplastic/myeloproliferative neoplasms (MDS/MPN) treated with hypomethylating agents (HMA), and to analyze the factors that may affect their efficacy and prognosis, in order to provide a clinical basis for the choice of treatment options for patients with MDS/MPN. METHODS: 35 patients with newly diagnosed MDS/MPN who received hypomethylating therapy from January 2018 to April 2024 in the Department of Hematology of Affiliated Hospital of Xuzhou Medical University were included. The patients were divided into decitabine group (15 cases) and azacitidine group (20 cases) according to the treatment regimen. The efficacy, median overall survival (OS), and median progression-free survival (PFS) of the patients after HMA treatment were evaluated. The differences in efficacy and survival between the two groups were compared, and factors affecting efficacy and prognosis of MDS/MPN patients were analyzed. RESULTS: The overall response rate (ORR) of the 35 MDS/MPN patients treated with HMA was 51.4%. The ORR was 73.3% in decitabine group and 35.0% in azacitidine group, with a statistically significant difference (P =0.041). Survival analysis showed that the median OS was 12 months and the median PFS was 10 months in the entire cohort of the patients. There was no difference in median OS between decitabine group and azacitidine group. The median PFS in decitabine group was 12 months, higher than that in azacitidine group (7 months), but the difference was not statistically significant (P =0.505). Multivariate analysis showed that the treatment regimen and platelet count were independent influencing factors for the efficacy of HAM treatment; The course and therapeutic efficacy of HMA treatment were independent influencing factors for OS in MDS/MPN patients. The main adverse reactions of HMA treatment were myelosuppression and pulmonary infection. Gastrointestinal reactions were more likely to occur in the azacitidine group than in the decitabine group, and the difference was statistically significant (P =0.027). CONCLUSION HMA treatment is effective and well-tolerated in some MDS/MPN patients. Decitabine shows superior efficacy compared with azacitidine and is less likely to cause gastrointestinal reactions. Patients who received ≥4 courses of HMAs and responded to hypomethylating therapy had longer OS.
Humans ; Prognosis ; Decitabine/therapeutic use* ; Azacitidine/therapeutic use* ; Male ; Female ; Myelodysplastic Syndromes/drug therapy* ; Middle Aged ; Myelodysplastic-Myeloproliferative Diseases/drug therapy* ; Antimetabolites, Antineoplastic/therapeutic use* ; Treatment Outcome ; Aged ; Myeloproliferative Disorders/drug therapy* ; Adult ; DNA Methylation

The ventral anterior (VA) nucleus of the thalamus is a major target of the basal ganglia and is closely associated with the pathogenesis of Parkinson's disease (PD). Notably, the VA receives direct innervation from the hypothalamic histaminergic system. However, its role in PD remains unknown. Here, we assessed the contribution of histamine to VA neuronal activity and PD motor deficits. Functional magnetic resonance imaging showed reduced VA activity in PD patients. Optogenetic activation of VA neurons or histaminergic afferents significantly alleviated motor deficits in 6-OHDA-induced PD rats. Furthermore, histamine excited VA neurons via H1 and H2 receptors and their coupled hyperpolarization-activated cyclic nucleotide-gated channels, inward-rectifier K⁺ channels, or Ca²⁺-activated K⁺ channels. These results demonstrate that histaminergic afferents actively compensate for Parkinsonian motor deficits by biasing VA activity. These findings suggest that targeting VA histamine receptors and downstream ion channels may be a potential therapeutic strategy for PD motor dysfunction.
Animals ; Histamine/metabolism* ; Male ; Oxidopamine/toxicity* ; Rats ; Ventral Thalamic Nuclei/physiopathology* ; Rats, Sprague-Dawley ; Disease Models, Animal ; Parkinson Disease/metabolism* ; Neurons/physiology* ; Humans ; Optogenetics

OBJECTIVE: As an age-related neurodegenerative disease, the prevalence of mild cognitive impairment (MCI) increases with age. Within the framework of traditional Chinese medicine, spleen-kidney deficiency syndrome (SKDS) is recognized as the most frequent MCI subtype. Due to the covert and gradual onset of MCI, in community settings it poses a significant challenge for patients and their families to discern between typical aging and pathological changes. There exists an urgent need to devise a preliminary diagnostic tool designed for community-residing older adults with MCI attributed to SKDS (MCI-SKDS). METHODS: This investigation enrolled 312 elderly individuals diagnosed with MCI, who were randomly distributed into training and test datasets at a 3:1 ratio. Five machine learning methods, including logistic regression (LR), decision tree (DT), naive Bayes (NB), support vector machine (SVM), and gradient boosting (GB), were used to build a diagnostic prediction model for MCI-SKDS. Accuracy, sensitivity, specificity, precision, F1 score, and area under the curve were used to evaluate model performance. Furthermore, the clinical applicability of the model was evaluated through decision curve analysis (DCA). RESULTS: The accuracy, precision, specificity and F1 score of the DT model performed best in the training set (test set), with scores of 0.904 (0.845), 0.875 (0.795), 0.973 (0.875) and 0.973 (0.875). The sensitivity of the training set (test set) of the SVM model performed best among the five models with a score of 0.865 (0.821). The area under the curve of all five models was greater than 0.9 for the training dataset and greater than 0.8 for the test dataset. The DCA of all models showed good clinical application value. The study identified ten indicators that were significant predictors of MCI-SKDS. CONCLUSION The risk prediction index derived from machine learning for the MCI-SKDS prediction model is simple and practical; the model demonstrates good predictive value and clinical applicability, and the DT model had the best performance. Please cite this article as: Ai YT, Zhou S, Wang M, Zheng TY, Hu H, Wang YC, Li YC, Wang XT, Zhou PJ. Development of a machine learning-based risk prediction model for mild cognitive impairment with spleen-kidney deficiency syndrome in the elderly. J Integr Med. 2025; 23(4): 390-397.
Humans ; Cognitive Dysfunction/diagnosis* ; Aged ; Male ; Female ; Machine Learning ; Spleen ; Aged, 80 and over ; Kidney ; Medicine, Chinese Traditional

ObjectiveTo simulate the microstructure and mechanical properties of tendon tissue and promote its regeneration and repair, electrospinning technology was used to prepare L-polylactic acid (PLLA) fiber membranes loaded with different nano zinc oxide contents and with oriented structures. Physical and chemical characterization and biological performance evaluation were carried out to explore their effects on tendon cell proliferation and differentiation. MethodsPreparation of PLLA fiber scaffolds and PLLA/ZnO fiber scaffolds containing different mass fractions of nano ZnO was performed using electrospinning technology. The physicochemical properties of the scaffold were characterized by scanning electron microscopy, mechanical stretching, and EDS spectroscopy. The scaffold was co-cultured with mouse tendon cells to detect its biocompatibility and regulatory effects on cell differentiation behavior. ResultsThe fiber scaffolds were arranged in an oriented manner, and zinc elements were uniformly distributed in the fibers. The tensile strength and Young’s modulus of PLLA/0.1%ZnO fiber scaffolds were significantly higher than PLLA fiber scaffolds. The number of cells on the surface of PLLA/0.1%ZnO fiber scaffold was significantly higher than that of the PLLA group, and the activity was better; mouse tendon cells exhibit directional adhesion and growth along the fiber arrangement direction. ConclusionThe oriented PLLA/0.1%ZnO fiber scaffold had excellent physicochemical properties, which can significantly promote the oriented growth, proliferation and differentiation of tendon cells. It is expected to be used for tendon tissue regeneration and repair in the future.

Aim To investigate the changes in the proliferation and apoptosis of Siha cells after knocking down Rho GTPase-activating protein 30(ARHGAP30).Methods After designing specific shARHGAP30 primers and connecting them to the pLKO.1 vector,we transformed them into Escherichia coli competent cells,then co-transfecting them with lentiviral helper plasmids into HEK-293T cells.We collected and filtered cell supernatant to obtain the vi-rus to infect Siha cells.RT-qPCR and Western blot were used to detect knockdown efficiency,as well as changes in the expression of Bax and Bcl-2 after trans-fection.The CCK-8 method was employed to measure the proliferation level of cells after knockdown.Results After successful construction of a lentiviral plasmid with knockdown of the ARHGAP30 gene and establish-ment of stably transfected Siha cells,ARHGAP30 tran-scription and translation(P＜0.01)in Siha cells de-creased,Bax/Bcl-2 significantly decreased(P＜0.01),indicating decreased apoptosis and increased cell proliferation(P＜0.01).Conclusions This study suggests the involvement of ARHGAP30 in the proliferation and apoptosis of Siha cells,and regulating the ARHGAP30 gene may interfere with the occurrence and development of cervical cancer.

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.