The introduction of immunotherapy has changed the traditional paradigms in cancer treatment and has demonstrated substantial clinical benefits across various malignancies. However, this progress is accompanied with emerging challenges, such as immune evasion and low response rates to immunotherapy. As an immunomodulatory molecule, zymogen granule protein 16 (ZG16) plays a crucial role in immunotherapy by inhibiting the binding of programmed death 1 (PD-1) to its ligand PD-L1, preventing immune evasion and restoring the immune system's ability to recognize and eliminate tumor cells. ZG16 is downregulated in multiple gastrointestinal tumors, and its regulatory mechanisms vary depending on the tumor type. ZG16 expression is closely associated with patient prognosis, and it has been identified as a favorable prognostic marker in colorectal cancer. This article provides a systematic overview of the structural characteristics, expression regulation mechanisms, and antitumor immune functions of ZG16.

Voice biomarkers， as an emerging smart medical technology， are now being used in applications such as assisting in the diagnosis and treatment of diseases， facilitating accurate and personalized medical services for patients. However， it also raises many ethical issues， including informed consent， privacy protection， accuracy and reliability， data security， legal risks， and other issues. This paper systematically sorted out the ethical issues in the applications of voice biomarkers in the medical field， summarized these issues， such as informed consent， privacy protection， accuracy and reliability， data security， and legal risks， as well as explored the corresponding coping strategies. These countermeasures encompassed utilizing new media platforms to raise public awareness of voice biomarkers， strengthening supervision and management to promote the privacy protection of voice biomarkers， reducing algorithm biases to promote the general benefits of voice biomarkers to the public， establishing multidisciplinary teams to protect the data security of voice biomarkers， and encouraging medical professionals and researchers to participate in policy research， with a view to providing references for promoting and regulating the applications of voice biomarkers in the medical field.

Neuraxial opioids, widely used in obstetric and perioperative pain management, often lead to unwanted itch, reducing patient satisfaction. While the μ-opioid receptor has been implicated in opioid-induced itch, the genetic basis for variable itch incidence remains unknown. This study examined 3616 patients receiving epidural opioids, revealing an itch occurrence of 26.55%, with variations among opioid types and gender. Analysis of the OPRM1 gene identified six single-nucleotide polymorphisms, notably rs1799971 (A118G), that correlated with opioid-induced itch. Mouse models with an equivalent A112G mutation showed reduced neuraxial opioid-induced itch and light touch-evoked itch, mirroring human findings. The 118G allele demonstrated an anti-itch effect without impacting analgesia, addiction, or tolerance, offering insights for risk stratification and potential anti-itch pretreatment strategies.
Receptors, Opioid, mu/genetics* ; Pruritus/chemically induced* ; Humans ; Analgesics, Opioid/administration & dosage* ; Female ; Male ; Animals ; Polymorphism, Single Nucleotide/genetics* ; Adult ; Mice ; Middle Aged

Objective To investigate the value of CT radiomics for predicting effect of neoadjuvant chemotherapy(NACT)for locally advanced gastric cancer(LAGC).Methods Totally 325 LAGC patients who received NACT were retrospectively enrolled,among them 247 were taken as training set,while the rest 78 were taken as validation set.Tumor regression scale(TRG)was evaluated according to postoperation pathology after NACT,and the efficacy of NACT was evaluated.Univariate logistic regression was used to analyze and screen clinical predictors of effect of NACT,and clinical model was constructed.Radiomics features were extracted based on venous phase enhanced CT pre-and post-NACT,and Delta radiomics features(i.e.the ratio of the difference of pre-and post-NACT radiomics features and pre-NACT radiomics features)were calculated.The best features were screened based on pre-NACT,post-NACT and Delta radiomics features to construct radiomics labels,the optimal label was screened and used to construct combined model through combining clinical model.Receiver operating characteristic(ROC)curve was plotted,and the area under the curve(AUC)was calculated to evaluate predicting efficiency of the above models.Decision curve analysis(DCA)was performed to explore the clinical value of each model.Results In training set,significant effect was found in 67 cases,but not in 180 cases,while in validation set,significant effect was found in 18 cases but not in 60 cases.Borrmann classification of LAGC before NACT was the clinical predictor(P=0.031),and clinical model was constructed,which had AUC of 0.577 and 0.520 in training and validation sets,respectively.Based on pre-NACT,post-NACT and Delta radiomics features,19,14 and 17 best features were selected,and AUC of the established radiomics labels of Pre-Rad,Post-Rad and Delta-Rad in training set was 0.672,0.796 and 0.789,while in validation set was 0.558,0.805 and 0.666,respectively.Post-Rad was the optimal label,which was used to construct combined model.AUC of the obtained combined model in training and validation sets was 0.824 and 0.818,respectively,both higher than that of clinical model(both P＜0.001)but not different with that of Post-Rad(both P＞0.05).Taken 0.4 to 0.7 as the threshold,the combined model had higher clinical net benefit than the other two.Conclusion Venous CT radiomics could effectively predict effect of NACT for LAGC.Combining with clinical features could improve its predictive efficacy.

Objective:To investigate the status quo of cognitive frailty in elderly patients with heart failure and analyze its influencing factors, so as to provide evidence for healthcare professionals to formulate effective intervention strategies.Methods:A total of 330 elderly patients with heart failure admitted to the First Affiliated Hospital of the University of South China and the Second Affiliated Hospital of the University of South China from October 2023 to January 2024 were selected as the study objects by convenience sampling method. General data questionnaire, Frailty Phenotype, Montreal Cognitive Assessment, Clinical Dementia Rating Scale, Geriatric Depression Scale-15 and Short Form Mini Nutritional Assessment were used for a sectional investigation. Random forest algorithm was used to rank the importance of variables and binary logistic regression was combined to explore the influencing factors of elderly patients with heart failure.Results:According to the evaluation criteria of cognitive frailty, 330 elderly patients with heart failure were divided into cognitive frailty group (124 cases) and non-cognitive frailty group (206 cases). The incidence of cognitive frailty was 37.6% (124/330). Among which, the median age of the cognitive frailty group was 73 years old, with 63 males and 61 females. The median age of the non-cognitive frailty group was 71 years old, with 117 males and 89 females. The random forest results showed that the top 7 variables in importance ranking were weekly intellectual activity, frequency of physical exercise, age, educational levels, depression status, cardiac function grade and risk of malnutrition. Binary logistic regression analysis showed that weekly intellectual activity ( OR=0.076, 95% CI 0.027-0.216), requency of physical exercise ( OR=0.184, 95% CI 0.079-0.430), age ( OR=1.173, 95% CI 1.077-1.277), educational levels ( OR=0.283, 95% CI 0.143-0.559), depression status ( OR=4.440, 95% CI 1.451-13.585), cardiac function grade ( OR=3.030, 95% CI 1.673-5.489) and risk of malnutrition ( OR=3.833, 95% CI 1.530-9.602) were the main influencing factors (all P<0.05). Conclusions:The incidence of cognitive frailty in elderly patients with heart failure is high. Healthcare professionals ought to focus on the screening and assessing of cognitive frailty in elderly patients with heart failure, and formulate effective intervention strategies by considering the above influencing factors to mitigate the occurrence of cognitive frailty.

Objective:To investigate the status quo of cognitive frailty in elderly patients with heart failure and analyze its influencing factors, so as to provide evidence for healthcare professionals to formulate effective intervention strategies.Methods:A total of 330 elderly patients with heart failure admitted to the First Affiliated Hospital of the University of South China and the Second Affiliated Hospital of the University of South China from October 2023 to January 2024 were selected as the study objects by convenience sampling method. General data questionnaire, Frailty Phenotype, Montreal Cognitive Assessment, Clinical Dementia Rating Scale, Geriatric Depression Scale-15 and Short Form Mini Nutritional Assessment were used for a sectional investigation. Random forest algorithm was used to rank the importance of variables and binary logistic regression was combined to explore the influencing factors of elderly patients with heart failure.Results:According to the evaluation criteria of cognitive frailty, 330 elderly patients with heart failure were divided into cognitive frailty group (124 cases) and non-cognitive frailty group (206 cases). The incidence of cognitive frailty was 37.6% (124/330). Among which, the median age of the cognitive frailty group was 73 years old, with 63 males and 61 females. The median age of the non-cognitive frailty group was 71 years old, with 117 males and 89 females. The random forest results showed that the top 7 variables in importance ranking were weekly intellectual activity, frequency of physical exercise, age, educational levels, depression status, cardiac function grade and risk of malnutrition. Binary logistic regression analysis showed that weekly intellectual activity ( OR=0.076, 95% CI 0.027-0.216), requency of physical exercise ( OR=0.184, 95% CI 0.079-0.430), age ( OR=1.173, 95% CI 1.077-1.277), educational levels ( OR=0.283, 95% CI 0.143-0.559), depression status ( OR=4.440, 95% CI 1.451-13.585), cardiac function grade ( OR=3.030, 95% CI 1.673-5.489) and risk of malnutrition ( OR=3.833, 95% CI 1.530-9.602) were the main influencing factors (all P<0.05). Conclusions:The incidence of cognitive frailty in elderly patients with heart failure is high. Healthcare professionals ought to focus on the screening and assessing of cognitive frailty in elderly patients with heart failure, and formulate effective intervention strategies by considering the above influencing factors to mitigate the occurrence of cognitive frailty.

Objective To investigate the value of CT radiomics for predicting effect of neoadjuvant chemotherapy(NACT)for locally advanced gastric cancer(LAGC).Methods Totally 325 LAGC patients who received NACT were retrospectively enrolled,among them 247 were taken as training set,while the rest 78 were taken as validation set.Tumor regression scale(TRG)was evaluated according to postoperation pathology after NACT,and the efficacy of NACT was evaluated.Univariate logistic regression was used to analyze and screen clinical predictors of effect of NACT,and clinical model was constructed.Radiomics features were extracted based on venous phase enhanced CT pre-and post-NACT,and Delta radiomics features(i.e.the ratio of the difference of pre-and post-NACT radiomics features and pre-NACT radiomics features)were calculated.The best features were screened based on pre-NACT,post-NACT and Delta radiomics features to construct radiomics labels,the optimal label was screened and used to construct combined model through combining clinical model.Receiver operating characteristic(ROC)curve was plotted,and the area under the curve(AUC)was calculated to evaluate predicting efficiency of the above models.Decision curve analysis(DCA)was performed to explore the clinical value of each model.Results In training set,significant effect was found in 67 cases,but not in 180 cases,while in validation set,significant effect was found in 18 cases but not in 60 cases.Borrmann classification of LAGC before NACT was the clinical predictor(P=0.031),and clinical model was constructed,which had AUC of 0.577 and 0.520 in training and validation sets,respectively.Based on pre-NACT,post-NACT and Delta radiomics features,19,14 and 17 best features were selected,and AUC of the established radiomics labels of Pre-Rad,Post-Rad and Delta-Rad in training set was 0.672,0.796 and 0.789,while in validation set was 0.558,0.805 and 0.666,respectively.Post-Rad was the optimal label,which was used to construct combined model.AUC of the obtained combined model in training and validation sets was 0.824 and 0.818,respectively,both higher than that of clinical model(both P＜0.001)but not different with that of Post-Rad(both P＞0.05).Taken 0.4 to 0.7 as the threshold,the combined model had higher clinical net benefit than the other two.Conclusion Venous CT radiomics could effectively predict effect of NACT for LAGC.Combining with clinical features could improve its predictive efficacy.

Objective:To evaluate the incidence and case fatality rate of cardiovascular disease (CVD) among populations in urban and rural communities in eastern, central and western regions of China.Methods:The present study was based on the data of the Prospective Urban and Rural Epidemiology (PURE)-China cohort, which enrolled participants who had at least one follow-up visit and complete information on age and sex. Information on baseline demographics, cardiovascular risk factors, and prevention and treatment for CVD were collected. CVD and mortality events were documented using the standardized case report form of the PURE Global Study to assess the incidence and case fatality rate of CVD among populations in urban and rural communities in eastern, central and western China.Results:This study included a total of 47 262 community-dwelling participants (age: (51.1±9.6) years; female, n=27 529, 58.2%) from 115 urban and rural communities in 12 provinces across the eastern, central, and western regions of China. Over a follow-up period of 11.9 (9.5, 12.6) years, 2 686 deaths and 5 873 cardiovascular events were documented. The incidence of CVD was 11.90 (95%CI: 11.60-12.21)/1 000 person-years. A significant difference in CVD incidence was observed across regions ( Ptrend<0.001), which was highest in the western provinces (13.99 (95% CI: 13.33-14.65)/1 000 person-years), intermediate in the eastern provinces (11.92 (95% CI: 11.52-12.33)/1 000 person-years), and lowest in the central provinces (8.87 (95% CI: 8.25-9.50)/1 000 person-years). The 1-year case fatality rate of CVD demonstrated an increasing trend from eastern to western regions (eastern: 10.20% (95% CI: 6.95-14.73); central: 13.50% (95% CI: 9.90-18.14); western: 18.62% (95% CI: 14.95-22.94); Ptrend<0.001). Moreover, the incidence of major CVD was consistently higher in rural areas compared with urban areas across eastern ( P<0.001), central ( P=0.01) and western ( P<0.001)_regions, respectively. The 1-year case fatality rate in rural areas was also significantly higher compared with that in urban areas in both eastern ( P<0.001) and western regions ( P=0.02). Conclusions:The incidence and case fatality rate of CVD were high among middle-aged population in China, especially those in western regions with low socioeconomic levels and in rural areas.

Post-amputation pain causes great suffering to amputees, but still no effective drugs are available due to its elusive mechanisms. Our previous clinical studies found that surgical removal or radiofrequency treatment of the neuroma at the axotomized nerve stump effectively relieves the phantom pain afflicting patients after amputation. This indicated an essential role of the residual nerve stump in the formation of chronic post-amputation pain (CPAP). However, the molecular mechanism by which the residual nerve stump or neuroma is involved and regulates CPAP is still a mystery. In this study, we found that nociceptors expressed the mechanosensitive ion channel TMEM63A and macrophages infiltrated into the dorsal root ganglion (DRG) neurons worked synergistically to promote CPAP. Histology and qRT-PCR showed that TMEM63A was mainly expressed in mechanical pain-producing non-peptidergic nociceptors in the DRG, and the expression of TMEM63A increased significantly both in the neuroma from amputated patients and the DRG in a mouse model of tibial nerve transfer (TNT). Behavioral tests showed that the mechanical, heat, and cold sensitivity were not affected in the Tmem63a^-/- mice in the naïve state, suggesting the basal pain was not affected. In the inflammatory and post-amputation state, the mechanical allodynia but not the heat hyperalgesia or cold allodynia was significantly decreased in Tmem63a^-/- mice. Further study showed that there was severe neuronal injury and macrophage infiltration in the DRG, tibial nerve, residual stump, and the neuroma-like structure of the TNT mouse model, Consistent with this, expression of the pro-inflammatory cytokines TNF-α, IL-6, and IL-1β all increased dramatically in the DRG. Interestingly, the deletion of Tmem63a significantly reduced the macrophage infiltration in the DRG but not in the tibial nerve stump. Furthermore, the ablation of macrophages significantly reduced both the expression of Tmem63a and the mechanical allodynia in the TNT mouse model, indicating an interaction between nociceptors and macrophages, and that these two factors gang up together to regulate the formation of CPAP. This provides a new insight into the mechanisms underlying CPAP and potential drug targets its treatment.
Animals ; Mice ; Amputation, Surgical ; Chronic Pain/pathology* ; Disease Models, Animal ; Ganglia, Spinal/pathology* ; Hyperalgesia/etiology* ; Ion Channels/metabolism* ; Macrophages ; Neuroma/pathology*