Objective To explore the correlation and lag effect between meteorological factors and the incidence of scarlet fever in Xicheng District, Beijing, and to provide a theoretical basis for the surveillance, early warning，and scientific prevention and control of scarlet fever. Methods Based on the daily scarlet fever incidence data and concurrent meteorological data in Xicheng District, Beijing from 2010 to 2019, the distributed lag non-linear model (DLNM) was used to analyze the impact of meteorological factors on the incidence of scarlet fever. Results The risk of scarlet fever was the highest when the daily average temperature was 34.2℃ with a lag of 0 days (RR=1.175, 95% CI:1.006-1.372). The risk was the second highest when the daily average temperature was 2.2℃ with a lag of 12 days (RR=1.123, 95% CI:1.044 -1.209). The cumulative relative risk of scarlet fever was statistically significant when the daily average temperature ranged from 27.2℃ to 34.2℃, with the highest cumulative relative risk at 34.2℃ (RR=1.906, 95%CI:1.215-2.989). When the daily average relative humidity was 19.5% with a lag of 6 days, the risk of scarlet fever incidence was the highest (RR=1.022, 95% CI: 1.005-1.040). The cumulative relative risk was statistically significant when the daily average relative humidity ranged from 24.7% to 40.2%, with the highest cumulative relative risk at 27.3% (RR=1.170, 95% CI: 1.020-1.343). The risk of scarlet fever was the highest when the daily average vapor pressure was 1.2 hPa with a lag of 5 days (RR=1.029, 95%CI:1.008-1.050). The cumulative relative risk of scarlet fever was statistically significant when the daily average vapor pressure was 1.2-7.4 hPa, and the highest cumulative risk was when the daily average vapor pressure was 1.2 hPa (RR=1.362, 95% CI:1.022-1.815). Conclusion There is a nonlinear relationship between meteorological factors and the incidence of scarlet fever in Xicheng District, Beijing, with a certain lag effect. Daily average temperature (27.2-34.2℃), daily average relative humidity (28.6~36.3%) and daily average vapor pressure (1.2-7.4 hPa) increase the risk of scarlet fever. These factors can be used as indicators for the prevention, control, surveillance, and early warning of scarlet fever.

AIM To investigate the effects of Congrong San on neuronal apoptosis and the Bax/Bcl-2/Caspase3 signaling pathway in a rat model of Alzheimer's disease(AD).METHODS A total of 60 2-month-old SD male rats were randomly divided into the blank group,the model group,the memantine hydrochloride group(0.025 g/kg)and low-dose,medium-dose and high-dose Congrong San groups(4.62,9.24,18.48 g/kg).All groups except the control group received stereotactic intracerebral injection of Aβ1-42 to establish AD models.Following the successful modeling,each group received its corresponding intragastric administration once daily for 28 consecutive days.After the administration,the rats had their learning and memory ability detected by the morris water maze test;their hippocampal neuronal morphology observed with HE and Nissl staining;their hippocampal neuronal apoptosis observed with TUNEL staining;and their hippocampal expressions of amyloid precursor protein(APP),β-site APP-cleaving enzyme 1(BACE1),and apoptosis-related proteins Bax,Bcl-2 and Caspase3 detected with Western blot assay.RESULTS Compared with the model group,the groups intervened with medium-dose and high-dose Congrong San exhibited improved learning and memory performance,alleviated hippocampal neuronal damage,increased Nissl body count(P＜0.01),reduced hippocampal apoptosis rate(P＜0.05,P＜0.01),decreased protein expressions of APP,BACE1,Bax and cleaved-Caspase3/Caspase3 ratio(P＜0.05,P＜0.01),and elevated Bcl-2 expression(P＜0.01).CONCLUSION Congrong San mitigates cognitive impairment,hippocampal neuronal damage,and apoptosis in AD rats,probably through inhibition of the Bax/Bcl-2/Caspase3 signaling pathway activation.

Central nervous system(CNS)degenerative disorders refer to a spectrum of pathological alterations triggered by struc-tural damage to cerebral neural tissues,clinically manifested as diverse neurological dysfunction syndromes,including multiple sclerosis(MS),neurodegenerative diseases(NDs),and ische-mic stroke.The hallmark pathological features of these disorders involve irreversible neuronal damage and decompensation of functional neural networks,ultimately leading to progressive neurological deficits.Notably,with the accelerating global popu-lation aging,the incidence of these diseases has surged signifi-cantly.According to WHO statistics,they now rank among the top three global causes of disability and mortality.Current re-search has confirmed that the pathogenesis of CNS degenerative disorders exhibits high heterogeneity,encompassing multifaceted pathophysiological processes such as genetic predisposition,oxi-dative stress,protein misfolding,and metabolic dysregulation.This intricate pathogenic network not only complicates clinical differential diagnosis but also poses substantial challenges to the development of precision therapeutic strategies.Importantly,re-cent studies have revealed that mitochondrial homeostasis disrup-tion-induced inflammatory cascades(termed mitochondrial in-flammation)play a pivotal regulatory role in neurodegenerative progression.Key molecular mechanisms include impaired mito-phagy,aberrant mitochondrial DNA(mtDNA)release and NL-RP3 inflammasome activation.This review systematically deci-phers the molecular regulatory network of mitochondrial inflam-mation,with a focus on its biological effects in critical pathologi-cal events such as blood-brain barrier disruption,microglial hy-peractivation and neuronal apoptosis.The overarching aim is to provide a theoretical foundation for developing innovative thera-peutic strategies targeting mitochondrial homeostasis restoration.

Peritoneal metastasis is a common form of distant metastasis in patients with colorectal cancer, and it is typically associated with a poor prognosis. The development of peritoneal metastasis involves complex molecular mechanisms and multifactorial regulation of the tumor microenvironment. Due to the presence of the blood-peritoneal barrier, only a small amount of systemic medication reaches the peritoneal cavity, resulting in limited efficacy against peritoneal metastasis. Intraperitoneal administration shows significant therapeutic advantages as it can directly target the tumor microenvironment, maintain high local drug concentrations, and reduce systemic toxicity. Intraperitoneal chemotherapy, especially hyperthermic intraperitoneal chemotherapy, has become a cornerstone therapeutic strategy in the clinical treatment of peritoneal metastasis. When selecting chemotherapy drugs and drug combinations, pharmacokinetic properties, efficacy, and safety must be comprehensively considered to optimize the treatment outcomes. In addition, the unique microenvironment of the peritoneal cavity provides new treatment approaches for biological treatment strategies, including antitoxins, vaccines, immune checkpoint inhibitors, etc. Techniques such as pressurized intraperitoneal aerosol chemotherapy and novel drug delivery systems demonstrate potential for enhanced efficacy, offering promising alternatives to improve patient outcomes. This article will review peritoneal barrier characteristics, intraperitoneal drug transport, intraperitoneal chemotherapy, and intraperitoneal biological therapies, thereby establishing a theoretical framework for precision therapy in colorectal cancer peritoneal metastasis.

Objective To propose a multiple regression-variational auto-encoders(MR-VAE)model to realize precise and non-invasive prediction of intra-abdominal pressure(IAP)in critically ill patients.Methods At first,a dataset was constructed by retrospectively analysing baseline characteristics and clinical indicators of 100 critically ill patients admitted to the Intensive Care Unit of Daping Hospital of Army Medical University between 30 August 2019 and 30 March 2021.Then,a MR-VAE prediction model was developed by integrating a feedforward neural network for supervised regression onto a variational autoencoder(VAE)framework and incorporating multiple regression strategies to mitigate feature interference.Finally,the MR-VAE model had its performance evaluated by its comparison with five classical models including support vector machines(SVM),convolutional neural networks(CNN),Scikit-learn integrated model(SIM),multi-layer perceptron(MLP)and K-nearest neighbors(KNN),and its prediction accuracy verified by testing the data of 10 randomly selected patients.Results The MR-VAE model behaved the best when compared with the five classical models,with a mean squared error(MSE)of 0.207,a root mean square error(RMSE)of 0.454,a mean absolute error(MAE)of 0.361,a median absolute deviation(MAD)of 0.243,an explained variance score(EVS)of 0.814 and a R2of 0.823,which also outperformed the five models in fitting performance,convergence and final loss.In random sample testing,the MR-VAE model exhibited high consistency between predicted and actual values.Conclusion The MR-VAE model proposed can accurately predict IAP,which has great potential in reducing the repeated measurements of IAP in critically ill patients and providing new ideas for the early diagnosis and treatment of IAH.

Objective To propose a multiple regression-variational auto-encoders(MR-VAE)model to realize precise and non-invasive prediction of intra-abdominal pressure(IAP)in critically ill patients.Methods At first,a dataset was constructed by retrospectively analysing baseline characteristics and clinical indicators of 100 critically ill patients admitted to the Intensive Care Unit of Daping Hospital of Army Medical University between 30 August 2019 and 30 March 2021.Then,a MR-VAE prediction model was developed by integrating a feedforward neural network for supervised regression onto a variational autoencoder(VAE)framework and incorporating multiple regression strategies to mitigate feature interference.Finally,the MR-VAE model had its performance evaluated by its comparison with five classical models including support vector machines(SVM),convolutional neural networks(CNN),Scikit-learn integrated model(SIM),multi-layer perceptron(MLP)and K-nearest neighbors(KNN),and its prediction accuracy verified by testing the data of 10 randomly selected patients.Results The MR-VAE model behaved the best when compared with the five classical models,with a mean squared error(MSE)of 0.207,a root mean square error(RMSE)of 0.454,a mean absolute error(MAE)of 0.361,a median absolute deviation(MAD)of 0.243,an explained variance score(EVS)of 0.814 and a R2of 0.823,which also outperformed the five models in fitting performance,convergence and final loss.In random sample testing,the MR-VAE model exhibited high consistency between predicted and actual values.Conclusion The MR-VAE model proposed can accurately predict IAP,which has great potential in reducing the repeated measurements of IAP in critically ill patients and providing new ideas for the early diagnosis and treatment of IAH.

Objective:To study the effects of arsenic exposure on neurological function including voluntary motor ability, anxiety, and short-term memory ability of rats, as well as its impact on the expression levels of synaptic function related genes such as neuropeptide 1 (NLGN1), glutamate receptor 2A (NR2A), and postsynaptic density protein 95 (PSD95).Methods:Forty 3-week-old male specific pathogen free (SPF) grade Wistar rats [weighing (453.97 ± 35.68) g] were selected and divided into four groups using a random number table: 0 (control group) and 2, 10, and 50 mg/L arsenic exposure groups, with 10 rats in each group. They were given deionized water and 2, 10, and 50 mg/L sodium arsenite solutions for 12 weeks, respectively. The open field experiment and Y-maze experiment were used to test the voluntary motor ability, anxiety, and short-term memory ability of rats. Nissl staining was used to observe the pathological damage of the hippocampus in the brain. Real time fluorescence quantitative PCR and Western blot were used to detect the mRNA and protein expression levels of NLGN1, NR2A, and PSD95 in the hippocampus, respectively.Results:The results of the open field experiment revealed that the horizontal movement distances of rats in the 2 and 10 mg/L arsenic exposure groups were reduced compared to the control group, the movement distances in the central area in the 2, 10, and 50 mg/L arsenic exposure groups were reduced compared to the control group, and the residence time in the central area in the 10 and 50 mg/L arsenic exposure groups was reduced compared to the control group ( P < 0.05). The results of Y-maze experiment showed that the retention time of new arms in rats of the 2 and 10 mg/L arsenic exposure groups was shorter than that in the control group ( P < 0.05). The pathological examination results of Nissl staining showed that the control group had abundant Nissl bodies in hippocampal tissues of the cytoplasm with intact neuronal structures, tightly arranged cells, appearing blue purple in color and clear visible nuclei. However, the number of Nissl bodies decreased, intercellular gaps increased, disordered arrangement increased, cytoplasmic staining was lighter, and nuclear shrinkage phenomenon increased in the hippocampal tissues of rats in the 2, 10 and 50 mg/L arsenic exposure groups. The real-time fluorescence quantitative PCR detection results showed that there was a statistically significant difference in the mRNA expression levels of NLGN1, NR2A, and PSD95 in the hippocampal tissues of the four groups ( F = 13.85, 44.94, 4.63, P < 0.05). The results of Western blot analysis showed that the protein expression levels of NLGN1 and NR2A in the hippocampal tissues of rats in the 10 and 50 mg/L arsenic exposure groups were lower than those in the control group (0.65 ± 0.07, 0.69 ± 0.03 vs 1.00 ± 0.04, 0.51 ± 0.11, 0.51 ± 0.13 vs 1.00 ± 0.07, P < 0.05), and the expression level of PSD95 in the hippocampal tissues of rats in the 50 mg/L arsenic exposure group was lower than that in the control group (0.51 ± 0.09 vs 1.00 ± 0.05, P < 0.05). Conclusion:Arsenic may affect synaptic function and cause neurological dysfunction in rats by adjusting the expression levels of NLGN1, NR2A, and PSD95.

Central nervous system(CNS)degenerative disorders refer to a spectrum of pathological alterations triggered by struc-tural damage to cerebral neural tissues,clinically manifested as diverse neurological dysfunction syndromes,including multiple sclerosis(MS),neurodegenerative diseases(NDs),and ische-mic stroke.The hallmark pathological features of these disorders involve irreversible neuronal damage and decompensation of functional neural networks,ultimately leading to progressive neurological deficits.Notably,with the accelerating global popu-lation aging,the incidence of these diseases has surged signifi-cantly.According to WHO statistics,they now rank among the top three global causes of disability and mortality.Current re-search has confirmed that the pathogenesis of CNS degenerative disorders exhibits high heterogeneity,encompassing multifaceted pathophysiological processes such as genetic predisposition,oxi-dative stress,protein misfolding,and metabolic dysregulation.This intricate pathogenic network not only complicates clinical differential diagnosis but also poses substantial challenges to the development of precision therapeutic strategies.Importantly,re-cent studies have revealed that mitochondrial homeostasis disrup-tion-induced inflammatory cascades(termed mitochondrial in-flammation)play a pivotal regulatory role in neurodegenerative progression.Key molecular mechanisms include impaired mito-phagy,aberrant mitochondrial DNA(mtDNA)release and NL-RP3 inflammasome activation.This review systematically deci-phers the molecular regulatory network of mitochondrial inflam-mation,with a focus on its biological effects in critical pathologi-cal events such as blood-brain barrier disruption,microglial hy-peractivation and neuronal apoptosis.The overarching aim is to provide a theoretical foundation for developing innovative thera-peutic strategies targeting mitochondrial homeostasis restoration.

Peritoneal metastasis is a common form of distant metastasis in patients with colorectal cancer, and it is typically associated with a poor prognosis. The development of peritoneal metastasis involves complex molecular mechanisms and multifactorial regulation of the tumor microenvironment. Due to the presence of the blood-peritoneal barrier, only a small amount of systemic medication reaches the peritoneal cavity, resulting in limited efficacy against peritoneal metastasis. Intraperitoneal administration shows significant therapeutic advantages as it can directly target the tumor microenvironment, maintain high local drug concentrations, and reduce systemic toxicity. Intraperitoneal chemotherapy, especially hyperthermic intraperitoneal chemotherapy, has become a cornerstone therapeutic strategy in the clinical treatment of peritoneal metastasis. When selecting chemotherapy drugs and drug combinations, pharmacokinetic properties, efficacy, and safety must be comprehensively considered to optimize the treatment outcomes. In addition, the unique microenvironment of the peritoneal cavity provides new treatment approaches for biological treatment strategies, including antitoxins, vaccines, immune checkpoint inhibitors, etc. Techniques such as pressurized intraperitoneal aerosol chemotherapy and novel drug delivery systems demonstrate potential for enhanced efficacy, offering promising alternatives to improve patient outcomes. This article will review peritoneal barrier characteristics, intraperitoneal drug transport, intraperitoneal chemotherapy, and intraperitoneal biological therapies, thereby establishing a theoretical framework for precision therapy in colorectal cancer peritoneal metastasis.

OBJECTIVE To study the pharmacokinetic characteristics of ciprofol in pregnant and fetal rats， and provide reference for the application of ciprofol in cesarean section. METHODS Eight pregnant rats were selected. A single dose of 2.4 mg/kg of ciprofol was administered via the tail vein. One fetal rat was selected at 2， 4， 8， 12， 16， 25， 35， 45， 60， and 90 minutes respectively after ciprofol administration. Subsequently， whole blood samples were collected simultaneously from both the pregnant rats and fetal rats. HPLC-MS/MS method was used to determine the concentration of ciprofol in the bodies of pregnant and fetal rats. The ratios of fetal-to-maternal blood concentrations （F/M ratios） at each time point were calculated， and the F/M-time curves were plotted. Subsequently， non-compartmental pharmacokinetic parameters were computed using DAS 2.0 software. RESULTS Compared with pregnant rats， cmax， AUC0-90 min and AUC0-∞ of ciprofol in fetal rats were decreased significantly， while MRT was increased significantly （P＜0.05）. The F/M curve of ciprofol initially increased and then decreased， and between 0.16- 0.84， reaching a maximum value of 0.84 at 45 minutes. CONCLUSIONS Ciprofol can penetrate the placental barrier， and there are significant differences in pharmacokinetic parameters between pregnant and fetal rats. Moreover， the exposure level of ciprofol in fetal rats is much lower than that in pregnant rats. Therefore， ciprofol shows promise as an ideal anesthetic agent for cesarean section delivery.