Human Respiratory Stem Cells (RSCs) play a crucial role in the maintenance, repair and regeneration of the respiratory system. As a novel therapeutic method, stem cell therapy is a popular research direction in the medical field. And with the in-depth research on the mechanism of pneumonia caused by respiratory infections in recent years, the use of RSCs to explore pneumonia caused by respiratory infections and its therapeutic strategies has become a hot topic. In this paper, we firstly outlined the types of RSCs, summarized the mechanism of pneumonia caused by respiratory tract infections, discussed the advantages of RSCs application and the progress of culture differentiation, and elaborated the therapeutic exploration of RSCs in pneumonia caused by respiratory tract infections.

Traditional Chinese medicine(TCM) decoction pieces are a core carrier for the inheritance and innovation of TCM, and their quality and safety are critical to public health and the sustainable development of the industry. Conventional quality control models, while having established a well-developed system through long-term practice, still face challenges such as relatively long inspection cycles, insufficient objectivity in characterizing complex traits, and urgent needs for improving the efficiency of integrating multidimensional quality information when confronted with the dual demands of large-scale production and precision quality control. With the rapid development of artificial intelligence, machine learning can deeply analyze multidimensional data of the morphology, spectroscopy, and chemical fingerprints of decoction pieces by constructing high-dimensional feature space analysis models, significantly improving the standardization level and decision-making efficiency of quality evaluation. This article reviews the research progress in the application of machine learning in the processing, production, and rapid quality evaluation of TCM decoction pieces. It further analyzes current challenges in technological implementation and proposes potential solutions, offering theoretical and technical references to advance the digital and intelligent transformation of the industry.
Machine Learning ; Drugs, Chinese Herbal/standards* ; Quality Control ; Medicine, Chinese Traditional/standards* ; Humans

Cardiovascular disease is one of the most common causes of death in the world,and related western drugs usually have obvious side effects.Traditional Chinese medicine,characterized by its multi-component and multi-target,has unique advantage in the prevention and treatment of cardiovascular diseases.Cornus Officinal is a histor-ically used plants with medicinal and edible properties.Ancient books and modern literatures have shown that Cor-nus Officinal has the potential to prevent and treat cardiovascular diseases.With the in-depth study of the chemical composition and pharmacological effect of Cornus Officinal,its pharmacodynamic substances and mechanism in the prevention and treatment of cardiovascular diseases are gradually clear.This article reviews the pathways and targets of Cornus Officinal in the prevention and treatment of cardiovascular diseases in recent years,and summarizes its potential effective components,in order to provide theoretical support for the clinical application and traditional Chinese medicine development.

OBJECTIVE: This study aimed to explore the association between body mass index (BMI) and mortality based on the 10-year population-based multicenter prospective study. METHODS: A general population-based multicenter prospective study was conducted at four sites in rural China between 2013 and 2023. Multivariate Cox proportional hazards models and restricted cubic spline analyses were used to assess the association between BMI and mortality. Stratified analyses were performed based on the individual characteristics of the participants. RESULTS: Overall, 19,107 participants with a sum of 163,095 person-years were included and 1,910 participants died. The underweight (< 18.5 kg/m ²) presented an increase in all-cause mortality (adjusted hazards ratio [ aHR] = 2.00, 95% confidence interval [ CI]: 1.66-2.41), while overweight (≥ 24.0 to < 28.0 kg/m ²) and obesity (≥ 28.0 kg/m ²) presented a decrease with an aHR of 0.61 (95% CI: 0.52-0.73) and 0.51 (95% CI: 0.37-0.70), respectively. Overweight ( aHR = 0.76, 95% CI: 0.67-0.86) and mild obesity ( aHR = 0.72, 95% CI: 0.59-0.87) had a positive impact on mortality in people older than 60 years. All-cause mortality decreased rapidly until reaching a BMI of 25.7 kg/m ² ( aHR = 0.95, 95% CI: 0.92-0.98) and increased slightly above that value, indicating a U-shaped association. The beneficial impact of being overweight on mortality was robust in most subgroups and sensitivity analyses. CONCLUSION This study provides additional evidence that overweight and mild obesity may be inversely related to the risk of death in individuals older than 60 years. Therefore, it is essential to consider age differences when formulating health and weight management strategies.
Humans ; Body Mass Index ; China/epidemiology* ; Male ; Female ; Middle Aged ; Prospective Studies ; Rural Population/statistics & numerical data* ; Aged ; Follow-Up Studies ; Adult ; Mortality ; Cause of Death ; Obesity/mortality* ; Overweight/mortality*

Objective To investigate the diagnostic value of our regression model based on quantitative parameters of dual-energy CT and clinical features for stages T2 and T3 colorectal cancer.Methods A cross-section study was performed on 91 patients with colorectal cancer confirmed by postoperative pathology in our hospital from January 2022 to November 2023.All of them underwent dual-energy CT examination.According to the pathological T staging criteria of Chinese Colorectal Cancer Diagnosis and Treatment Standard(2020 Edition),they were divided into T2 group(n=43)and T3 group(n=48).Univariate analysis was used to compare the differences in quantitative CT parameters and clinical features between the 2 groups,and the obtained significant variables were employed to construct diagnosis models by univariate or multivariate logistic regression analysis.The area under receiver operating characteristic curve(AUC)of the CT parametric model and the model combined with clinical features was compared to evaluate the efficacy of diagnosing T2 and T3 stages.Results Univariate analysis showed that carcinoembryonic antigen(CEA),N stage,tumor location,tumor longest diameter(LD),CT value of virtual noncontrast(CT-VNC),fat fraction,electron density(Rho)and dual energy index(DEI)were significantly different between the T2 and T3 groups(P＜0.05).Multivariate logistic regression analysis found that N stage,tumor location,LD,fat fraction and DEI were independent risk factors for the diagnosis of stage T3.The AUC value of the model of above CT parameters in diagnosing stage T3 colorectal cancer was 0.671(95％CI:0.558～0.783),and the AUC value of the combined model of above CT parameters and clinical features was 0.886(95％CI:0.815～0.957),and statistical difference was observed in the AUC value between the combined model and the CT parametric model(P＜0.01).Conclusion The regression model constructed with dual-energy CT quantitative parameters combined with clinical features has high value in the preoperative diagnosis of stages T2 and T3 colorectal cancer before surgery.

Objective:This study aims to investigate the expression of uridine diphosphate-glucose[]pyrophos-phorylase 2(UGP2)in breast cancer(BC)tissues and its oncogenic mechanism,assessing its potential value as a diag-nostic and prognostic biomarker for breast cancer.Methods:(1)Online database analysis was conducted to assess UGP2 mRNA and protein expression levels in breast cancer and explore their correlation with clinical characteristics.Im-munohistochemistry(IHC)was used to verify UGP2 expression in human breast cancer tumor tissues and evaluate its relationship with clinicopathological features.(2)Kaplan-Meier survival analysis and COX regression models were used to analyze the impact of UGP2 expression on breast cancer patient prognosis.(3)Bioinformatics methods were em-ployed to investigate the correlation between UGP2 and tumor immune cell infiltration,and to predict the biological func-tions and associated signaling pathways of UGP2 in breast cancer.Results:(1)The mRNA and protein expression levels of UGP2 were upregulated in breast cancer tissues(both P<0.05),and were negatively correlated with ER-positive and PR-positive status(OR<1,P<0.05),while positively correlated with Ki-67 levels and the triple-negative breast cancer(TNBC)subtype(OR>1,P<0.05).(2)Elevated expression levels of UGP2 were associated with poorer survival rates in breast cancer patients(both P<0.05)and were identified as an independent adverse prognostic factor for breast cancer(HR=1.40,P<0.05).(3)Functional analysis results suggested that UGP2 may promote tumor progression by regulating metabolism,hormone signaling,and the immune microenvironment.Additionally,UGP2 expression was negatively cor-related with NK cell activation status and positively correlated with the inhibitory state.Conclusion:UGP2 expression is elevated in breast cancer tissues and is closely associated with poor patient prognosis.It may promote cancer pro-gression through mechanisms such as metabolic reprogramming and immune suppression.UGP2 shows promise as a potential biomarker and therapeutic target in breast cancer,providing a basis for personalized treatment.

Numerous studies have shown that depression is main-ly associated with the abnormal expression of connexin 43(Cx43)in astrocytes(Astro)and its mediated dysfunction of gap junction(GJ).However,the molecular mechanism of post-translational modifications targeting Cx43 to regulate neuroin-flammation-associated depression is still unclear.Post-transla-tional modifications of Cx43 mainly include phosphorylation of specific amino acid sites by PKC,PKA,PKG,MAPK and PTK,and protein degradation of Cx43 through the K48/K63 polyubiq-uitylation and deubiquitination pathways,which ultimately lead to protein degradation through K48/K63 polyubiquitination and deubiquitination.These modifications are ultimately involved in the regulation of neuroinflammatory responses through the associ-ation of GJ function.In this paper,we systematically review the role of Cx43 post-translational modifications in neuroinflamma-tion,with the aim of further exploring the potential application of targeting these modifications to modulate the inflammatory re-sponse mechanism in improving depressive symptoms.

Cardiovascular disease is one of the most common causes of death in the world,and related western drugs usually have obvious side effects.Traditional Chinese medicine,characterized by its multi-component and multi-target,has unique advantage in the prevention and treatment of cardiovascular diseases.Cornus Officinal is a histor-ically used plants with medicinal and edible properties.Ancient books and modern literatures have shown that Cor-nus Officinal has the potential to prevent and treat cardiovascular diseases.With the in-depth study of the chemical composition and pharmacological effect of Cornus Officinal,its pharmacodynamic substances and mechanism in the prevention and treatment of cardiovascular diseases are gradually clear.This article reviews the pathways and targets of Cornus Officinal in the prevention and treatment of cardiovascular diseases in recent years,and summarizes its potential effective components,in order to provide theoretical support for the clinical application and traditional Chinese medicine development.

Numerous studies have shown that depression is main-ly associated with the abnormal expression of connexin 43(Cx43)in astrocytes(Astro)and its mediated dysfunction of gap junction(GJ).However,the molecular mechanism of post-translational modifications targeting Cx43 to regulate neuroin-flammation-associated depression is still unclear.Post-transla-tional modifications of Cx43 mainly include phosphorylation of specific amino acid sites by PKC,PKA,PKG,MAPK and PTK,and protein degradation of Cx43 through the K48/K63 polyubiq-uitylation and deubiquitination pathways,which ultimately lead to protein degradation through K48/K63 polyubiquitination and deubiquitination.These modifications are ultimately involved in the regulation of neuroinflammatory responses through the associ-ation of GJ function.In this paper,we systematically review the role of Cx43 post-translational modifications in neuroinflamma-tion,with the aim of further exploring the potential application of targeting these modifications to modulate the inflammatory re-sponse mechanism in improving depressive symptoms.

Objective:This study aims to investigate the expression of uridine diphosphate-glucose[]pyrophos-phorylase 2(UGP2)in breast cancer(BC)tissues and its oncogenic mechanism,assessing its potential value as a diag-nostic and prognostic biomarker for breast cancer.Methods:(1)Online database analysis was conducted to assess UGP2 mRNA and protein expression levels in breast cancer and explore their correlation with clinical characteristics.Im-munohistochemistry(IHC)was used to verify UGP2 expression in human breast cancer tumor tissues and evaluate its relationship with clinicopathological features.(2)Kaplan-Meier survival analysis and COX regression models were used to analyze the impact of UGP2 expression on breast cancer patient prognosis.(3)Bioinformatics methods were em-ployed to investigate the correlation between UGP2 and tumor immune cell infiltration,and to predict the biological func-tions and associated signaling pathways of UGP2 in breast cancer.Results:(1)The mRNA and protein expression levels of UGP2 were upregulated in breast cancer tissues(both P<0.05),and were negatively correlated with ER-positive and PR-positive status(OR<1,P<0.05),while positively correlated with Ki-67 levels and the triple-negative breast cancer(TNBC)subtype(OR>1,P<0.05).(2)Elevated expression levels of UGP2 were associated with poorer survival rates in breast cancer patients(both P<0.05)and were identified as an independent adverse prognostic factor for breast cancer(HR=1.40,P<0.05).(3)Functional analysis results suggested that UGP2 may promote tumor progression by regulating metabolism,hormone signaling,and the immune microenvironment.Additionally,UGP2 expression was negatively cor-related with NK cell activation status and positively correlated with the inhibitory state.Conclusion:UGP2 expression is elevated in breast cancer tissues and is closely associated with poor patient prognosis.It may promote cancer pro-gression through mechanisms such as metabolic reprogramming and immune suppression.UGP2 shows promise as a potential biomarker and therapeutic target in breast cancer,providing a basis for personalized treatment.