Objective:To develop and validate a prediction model for medication adherence among patients receiving allergen sublingual immunotherapy (SLIT).Methods:A prospective cross-sectional study was conducted, and a total of 288 patients who received SLIT treatment at an allergy center in the First Affiliated Hospital with Nanjing Medical University (Jiangsu Province Hospital) from December 2023 to July 2024 were assigned to the modeling group. Additionally, 122 patients from August to October 2024 were assigned to the validation group. Data of patients′ general information, medication beliefs, anxiety levels, social support, disease perception, and medication adherence were collected. Single-factor analysis and LASSO regression were utilized to identify potential predictors, and a prediction model for medication adherence was constructed using multifactorial logistic regression. A nomogram was then developed based on the model. The model′s discriminatory ability was evaluated using receiver operating characteristic curve (ROC), the area under curve (AUC), sensitivity, and specificity. The model was then validated in the validation cohort.Results:Single-factor analysis and LASSO regression identified a total of nine predictive factors. Logistic regression revealed that medical belief tendency [ OR (95% CI) =2.420 (1.116-5.248), P=0.025], the somatic control dimension in self-rating anxiety scales [ OR (95% CI)=1.404 (1.241-1.589), P<0.001], the subjective support dimension in social support assessment [ OR (95% CI)=0.784 (0.725-0.847), P<0.001], and the cognitive dimension in illness perception [ OR (95% CI)=0.725 (0.647-0.813), P<0.001] were independent predictors of medication adherence in patients undergoing SLIT. The AUC value of the model was 0.899 (95% CI=0.863-0.934) in the modeling group and 0.882 (95% CI=0.820-0.944) in the validation group, indicating good discriminatory ability. The optimal cutoff value of the model was 0.493, with a sensitivity of 81.1% and specificity of 85.7% in the modeling group, and a sensitivity of 87.3% and specificity of 82.5% in the validation group. Conclusion:The medication adherence prediction model developed in this study for patients undergoing SLIT exhibits good predictive performance and provides valuable guidance for early intervention by clinical healthcare professionals.

Objective:To analyze and validate the reliability and validity of the social skills improvement system-rating scales Chinese version (parent version) (SSIS-RS-C) in middle school students.Method:A total of 1 486 parents of middle school students were recruited according to the cluster sampling method.The social responsiveness scale and strengths and difficulties questionnaire were used as criterion validity tools.A retest was conducted one month later.SPSS 27.0 was used for descriptive statistics, item analysis, internal consistency test, test-retest reliability test and criterion validity test. AMOS 24.0 was used to perform confirmatory factor analysis .Results:Item analysis indicated significant positive correlations between each item and the subscales ( r=0.293-0.782, all P<0.01), with significant differences in scores between high and low groups ( t=10.079-37.038, all P<0.01).Confirmatory factor analysis supported a seven-factor structure for the social skills subscale(communication, cooperation, assertion, responsibility, empathy, engagement and self control) and a five-factor structure for the problem behavior subscale (externalizing, bullying, hyperactivity/inattention, internalizing and autism spectrum) of the SSIS-RS-C.There was a positive correlation between the social skills subscale and prosocial behavior ( r=0.637, P<0.001), and between the problem behavior subscale and social impairments and difficult behaviors ( r=0.765, 0.688, both P<0.001).The Cronbach's α coefficients for the total scale, social skills subscale and problem behavior subscale were 0.934, 0.972 and 0.963, respectively.The test-retest correlation coefficients for the total score and the two subscales were 0.665, 0.871 and 0.598, respectively (all P<0.001). Conclusion:The SSIS-RS-C demonstrated good reliability and validity in the Chinese adolescent population.

Objective:To observe the efficacy and safety of polatuzumab vedotin(pola)combined with chemotherapy in the treatment of relapsed and refractory diffuse large B-cell lymphoma(R/R DLBCL).Methods:A total of 23 patients with R/R DLBCL treated at the First Affiliated Hospital of Zhejiang University and its Liangzhu Branch from April 2023 to March 2024 were retrospectively collected.All patients were treated with pola combined with chemotherapy regimens such as BR,R-GDP,R-CHOP,or other regimens.Results:All 23 patients were evaluable for efficacy,with 10 achieving complete response(CR),7 partial response(PR),3 stable disease(SD),and 3 progressive disease(PD).The most common adverse events included myelosuppression,fever,and pulmonary infection.No severe adverse events resulted in drug withdrawal.Conclusion:Pola combined with chemotherapy demonstrates promising efficacy and a favorable safety profile in the treatment of R/R DLBCL.

Objective:To develop and validate a prediction model for medication adherence among patients receiving allergen sublingual immunotherapy (SLIT).Methods:A prospective cross-sectional study was conducted, and a total of 288 patients who received SLIT treatment at an allergy center in the First Affiliated Hospital with Nanjing Medical University (Jiangsu Province Hospital) from December 2023 to July 2024 were assigned to the modeling group. Additionally, 122 patients from August to October 2024 were assigned to the validation group. Data of patients′ general information, medication beliefs, anxiety levels, social support, disease perception, and medication adherence were collected. Single-factor analysis and LASSO regression were utilized to identify potential predictors, and a prediction model for medication adherence was constructed using multifactorial logistic regression. A nomogram was then developed based on the model. The model′s discriminatory ability was evaluated using receiver operating characteristic curve (ROC), the area under curve (AUC), sensitivity, and specificity. The model was then validated in the validation cohort.Results:Single-factor analysis and LASSO regression identified a total of nine predictive factors. Logistic regression revealed that medical belief tendency [ OR (95% CI) =2.420 (1.116-5.248), P=0.025], the somatic control dimension in self-rating anxiety scales [ OR (95% CI)=1.404 (1.241-1.589), P<0.001], the subjective support dimension in social support assessment [ OR (95% CI)=0.784 (0.725-0.847), P<0.001], and the cognitive dimension in illness perception [ OR (95% CI)=0.725 (0.647-0.813), P<0.001] were independent predictors of medication adherence in patients undergoing SLIT. The AUC value of the model was 0.899 (95% CI=0.863-0.934) in the modeling group and 0.882 (95% CI=0.820-0.944) in the validation group, indicating good discriminatory ability. The optimal cutoff value of the model was 0.493, with a sensitivity of 81.1% and specificity of 85.7% in the modeling group, and a sensitivity of 87.3% and specificity of 82.5% in the validation group. Conclusion:The medication adherence prediction model developed in this study for patients undergoing SLIT exhibits good predictive performance and provides valuable guidance for early intervention by clinical healthcare professionals.

Tumor drug resistance is an important problem in the failure of chemotherapy and targeted drug therapy, which is a complex process involving chromatin remodeling. SWI/SNF is one of the most studied ATP-dependent chromatin remodeling complexes in tumorigenesis, which plays an important role in the coordination of chromatin structural stability, gene expression, and post-translation modification. However, its mechanism in tumor drug resistance has not been systematically combed. SWI/SNF can be divided into 3 types according to its subunit composition: BAF, PBAF, and ncBAF. These 3 subtypes all contain two mutually exclusive ATPase catalytic subunits (SMARCA2 or SMARCA4), core subunits (SMARCC1 and SMARCD1), and regulatory subunits (ARID1A, PBRM1, and ACTB, etc.), which can control gene expression by regulating chromatin structure. The change of SWI/SNF complex subunits is one of the important factors of tumor drug resistance and progress. SMARCA4 and ARID1A are the most widely studied subunits in tumor drug resistance. Low expression of SMARCA4 can lead to the deletion of the transcription inhibitor of the BCL2L1 gene in mantle cell lymphoma, which will result in transcription up-regulation and significant resistance to the combination therapy of ibrutinib and venetoclax. Low expression of SMARCA4 and high expression of SMARCA2 can activate the FGFR1-pERK1/2 signaling pathway in ovarian high-grade serous carcinoma cells, which induces the overexpression of anti-apoptosis gene BCL2 and results in carboplatin resistance. SMARCA4 deletion can up-regulate epithelial-mesenchymal transition (EMT) by activating YAP1 gene expression in triple-negative breast cancer. It can also reduce the expression of Ca²⁺ channel IP3R3 in ovarian and lung cancer, resulting in the transfer of Ca²⁺ needed to induce apoptosis from endoplasmic reticulum to mitochondria damage. Thus, these two tumors are resistant to cisplatin. It has been found that verteporfin can overcome the drug resistance induced by SMARCA4 deletion. However, this inhibitor has not been applied in clinical practice. Therefore, it is a promising research direction to develop SWI/SNF ATPase targeted drugs with high oral bioavailability to treat patients with tumor resistance induced by low expression or deletion of SMARCA4. ARID1A deletion can activate the expression of ANXA1 protein in HER2+ breast cancer cells or down-regulate the expression of progesterone receptor B protein in endometrial cancer cells. The drug resistance of these two tumor cells to trastuzumab or progesterone is induced by activating AKT pathway. ARID1A deletion in ovarian cancer can increase the expression of MRP2 protein and make it resistant to carboplatin and paclitaxel. ARID1A deletion also can up-regulate the phosphorylation levels of EGFR, ErbB2, and RAF1 oncogene proteins.The ErbB and VEGF pathway are activated and EMT is increased. As a result, lung adenocarcinoma is resistant to epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs). Although great progress has been made in the research on the mechanism of SWI/SNF complex inducing tumor drug resistance, most of the research is still at the protein level. It is necessary to comprehensively and deeply explore the detailed mechanism of drug resistance from gene, transcription, protein, and metabolite levels by using multi-omics techniques, which can provide sufficient theoretical basis for the diagnosis and treatment of poor tumor prognosis caused by mutation or abnormal expression of SWI/SNF subunits in clinical practice.

Degenerative cervical myelopathy(DCM)is a group of diseases caused by cervical spine degeneration that compresses the spinal cord.It is a major cause of spinal cord dysfunction in adults,and its incidence is increasing globally.In the late stage,DCM could lead to paralysis due to spinal cord injury,which makes rapid,effective,and accurate medical diagnosis clinically significant.Deep learning(DL)technology can assist physicians in the rapid and accurate diagnosis of DCM by analyzing and processing a large amount of imaging data to extract features of the affected regions.In recent years,DL algorithm models have been leveraged for DCM-related research,which has become a focal point of intelligent medical development.In this review,domestic and international literature is surveyed,and the research progress and application of DL technology in the auxiliary diagnosis and prognosis evaluation of DCM are systematically summarized,aiming to provide a reference for intelligent diagnosis in clinical practice.

Mesangial cell proliferation is an early pathological indicator of diabetic nephropathy (DN). Growing evidence highlights the pivotal role of paired-related homeobox 1 (Prrx1), a key regulator of cellular proliferation and tissue differentiation, in various disease pathogenesis. Notably, Prrx1 is highly expressed in mesangial cells under DN conditions. Both in vitro and in vivo studies have demonstrated that Prrx1 overexpression promotes mesangial cell proliferation and contributes to renal fibrosis in db/m mice. Conversely, Prrx1 knockdown markedly suppresses hyperglycemia-induced mesangial cell proliferation and mitigates renal fibrosis in db/db mice. Mechanistically, Prrx1 directly interacts with the Yes-associated protein 1 (YAP) promoter, leading to the upregulation of YAP expression. This upregulation promotes mesangial cell proliferation and exacerbates renal fibrosis. These findings emphasize the crucial role of Prrx1 upregulation in high glucose-induced mesangial cell proliferation, ultimately leading to renal fibrosis in DN. Therefore, targeting Prrx1 to downregulate its expression presents a promising therapeutic strategy for treating renal fibrosis associated with DN.

OBJECTIVE: To investigate the associations between eight serum per- and polyfluoroalkyl substances (PFASs) and regional fat depots, we analyzed the data from the National Health and Nutrition Examination Survey (NHANES) 2011-2018 cycles. METHODS: Multiple linear regression models were developed to explore the associations between serum PFAS concentrations and six fat compositions along with a fat distribution score created by summing the concentrations of the six fat compositions. The associations between structurally grouped PFASs and fat distribution were assessed, and a prediction model was developed to estimate the ability of PFAS exposure to predict obesity risk. RESULTS: Among females aged 39-59 years, trunk fat mass was positively associated with perfluorooctane sulfonate (PFOS). Higher concentrations of PFOS, perfluorohexane sulfonate (PFHxS), perfluorodecanoate (PFDeA), perfluorononanoate (PFNA), and n-perfluorooctanoate (n-PFOA) were linked to greater visceral adipose tissue in this group. In men, exposure to total perfluoroalkane sulfonates (PFSAs) and long-chain PFSAs was associated with reductions in abdominal fat, while higher abdominal fat in women aged 39-59 years was associated with short-chain PFSAs. The prediction model demonstrated high accuracy, with an area under the curve (AUC) of 0.9925 for predicting obesity risk. CONCLUSION PFAS exposure is associated with regional fat distribution, with varying effects based on age, sex, and PFAS structure. The findings highlight the potential role of PFAS exposure in influencing fat depots and obesity risk, with significant implications for public health. The prediction model provides a highly accurate tool for assessing obesity risk related to PFAS exposure.
Humans ; Fluorocarbons/blood* ; Female ; Adult ; Middle Aged ; Male ; Environmental Pollutants/blood* ; Abdominal Fat ; Nutrition Surveys ; Alkanesulfonic Acids/blood* ; Obesity ; Environmental Exposure

Objective:To analyze and validate the reliability and validity of the social skills improvement system-rating scales Chinese version (parent version) (SSIS-RS-C) in middle school students.Method:A total of 1 486 parents of middle school students were recruited according to the cluster sampling method.The social responsiveness scale and strengths and difficulties questionnaire were used as criterion validity tools.A retest was conducted one month later.SPSS 27.0 was used for descriptive statistics, item analysis, internal consistency test, test-retest reliability test and criterion validity test. AMOS 24.0 was used to perform confirmatory factor analysis .Results:Item analysis indicated significant positive correlations between each item and the subscales ( r=0.293-0.782, all P<0.01), with significant differences in scores between high and low groups ( t=10.079-37.038, all P<0.01).Confirmatory factor analysis supported a seven-factor structure for the social skills subscale(communication, cooperation, assertion, responsibility, empathy, engagement and self control) and a five-factor structure for the problem behavior subscale (externalizing, bullying, hyperactivity/inattention, internalizing and autism spectrum) of the SSIS-RS-C.There was a positive correlation between the social skills subscale and prosocial behavior ( r=0.637, P<0.001), and between the problem behavior subscale and social impairments and difficult behaviors ( r=0.765, 0.688, both P<0.001).The Cronbach's α coefficients for the total scale, social skills subscale and problem behavior subscale were 0.934, 0.972 and 0.963, respectively.The test-retest correlation coefficients for the total score and the two subscales were 0.665, 0.871 and 0.598, respectively (all P<0.001). Conclusion:The SSIS-RS-C demonstrated good reliability and validity in the Chinese adolescent population.

Objective:To observe the efficacy and safety of polatuzumab vedotin(pola)combined with chemotherapy in the treatment of relapsed and refractory diffuse large B-cell lymphoma(R/R DLBCL).Methods:A total of 23 patients with R/R DLBCL treated at the First Affiliated Hospital of Zhejiang University and its Liangzhu Branch from April 2023 to March 2024 were retrospectively collected.All patients were treated with pola combined with chemotherapy regimens such as BR,R-GDP,R-CHOP,or other regimens.Results:All 23 patients were evaluable for efficacy,with 10 achieving complete response(CR),7 partial response(PR),3 stable disease(SD),and 3 progressive disease(PD).The most common adverse events included myelosuppression,fever,and pulmonary infection.No severe adverse events resulted in drug withdrawal.Conclusion:Pola combined with chemotherapy demonstrates promising efficacy and a favorable safety profile in the treatment of R/R DLBCL.