ObjectiveZheng’s San Qi San (ZSQS) power, a classic traditional Chinese medicine (TCM) formula, is used for treating soft tissue injuries involving muscles, tendons, and ligaments. However, its underlying therapeutic mechanisms remain unclear. This study aimed to screen and identify pharmaceutically active ingredients and their candidate biomolecule targets, and further elucidate the molecular mechanism of ZSQS in the treatment of skeletal muscle injury. MethodsNetwork pharmacology was employed to construct “ZSQS-component-target”, “protein-protein interaction (PPI)” and “active ingredient-core protein-pathway” networks to predict the key active ingredients and potential core targets of ZSQS for skeletal muscle injury. The predicted results were then validated via microarray data from the GEO database. Molecular docking was then performed to assess the binding ability between the screened active ingredients of ZSQS and the candidate core targets. Moreover, liquid chromatography-mass spectrometry (LC-MS) was used for qualitative and quantitative analysis to verify the active components of the drug and ZSQS serum. Finally, an animal model of eccentric exercise-induced skeletal muscle injury and a myotube cell model of oxidative stress-induced injury were established to validate the effects of ZSQS and its interventional effects on the biological functions of critical targets, thereby demonstrating the potential therapeutic mechanism of ZSQS. ResultsAmong the 111 active components identified in ZSQS and their corresponding 204 targets related to the skeletal muscle injury repair process, 14 core targets (including AKT1) and 4 core active components (quercetin, luteolin, kaempferol, and β‑sitosterol) were screened out, while the corresponding metabolites of quercetin, luteolin and kaempferol were detected in the ZSQS serum. Among these targets, 5 candidate genes (IL-6, CASP3, HIF1A, STAT3, and JUN) overlapped with the differential expression screening results with GEO data, and IL-6 was confirmed to be enriched in the PI3K/AKT pathway. Combined with the prediction results of the AKT expression levels, these findings suggest that the phosphorylation level of AKT1 plays a core role in the therapeutic mechanism of ZSQS. Molecular docking analysis further revealed that the PH domain of AKT1 had high binding energy with all 4 core active components, as verified by LC-MS. Finally, animal model studies have shown the promoting effect of ZSQS administration on skeletal muscle injury repair and its possible antioxidant damage mechanism. Cell model studies further demonstrated that ZSQS-containing serum, core active ingredient combination therapy, and quercetin monomer could increase the phosphorylation level of AKT, promote the nuclear translocation of Nrf2, upregulate the expression of downstream antioxidant enzymes (SOD, GPx, and GR), and inhibit the expression of inflammatory factors (IL-6 and TNF-α), thereby alleviating oxidative stress and the inflammatory response. ConclusionZSQS alleviates skeletal muscle injury mainly by activating the AKT/Nrf2 signaling pathway, enhancing cellular antioxidant and anti-inflammatory capabilities. The results of this study provide a scientific basis for the clinical application and modernized development of ZSQS.

With the accelerating trend of population aging, the number of elderly patients with lung cancer continues to rise, and the disease burden is becoming increasingly heavy. The clinical management of these patients faces severe challenges due to their decreased physiological reserve, complex comorbidities, and significant individual heterogeneity. Consequently, under traditional diagnosis and treatment models, doctors often struggle to identify the individualized risks of elderly patients in a timely and comprehensive manner, which can easily lead to decision biases such as undertreatment or overtreatment. In view of this, this study advocates for the establishment of an umbrella decision-making model specifically tailored for elderly lung cancer patients. Grounded in a multidisciplinary team (MDT) platform, this model deeply integrates oncological indicators with the comprehensive geriatric assessment (CGA) system. By holistically considering multidimensional variables including tumor burden, organ function, frailty index, cognitive status, and social support, the model establishes an operational mechanism characterized by "single entry, precise stratification, and targeted selection". Accordingly, patients can be scientifically triaged into distinct intervention tiers, such as active surveillance, minimally invasive surgery, drug therapy, radiotherapy, and best supportive care, thereby achieving real-time alignment between treatment intensity and patient fitness. This article elaborates on the construction logic and key operational procedures of this novel decision-making framework, aiming to guide clinical practice beyond the limitations of a tumor-centric perspective toward a holistic, dynamic, whole-course management strategy. This transition seeks to ensure optimal quality of life and clinical net benefit for elderly patients alongside survival prolongation.

ObjectiveTo investigate the therapeutic effect of paeoniflorin on metabolic dysfunction-associated fatty liver disease （MASLD） combined with insulin resistance （IR）， and to elucidate its regulatory mechanisms on the Toll-like receptor 4 （TLR4）/nuclear transcription factor （NF）-κB-insulin receptor substrate 1 （IRS1） inflammation-insulin signaling axis. MethodsMASLD mouse model was established using a 60% high-fat diet. Mice were randomly assigned to a normal control group， a MASLD model group， and paeoniflorin groups （low dose： 25 mg·kg^-1·d^-1， medium dose： 50 mg·kg^-1·d^-1， high dose： 100 mg·kg^-1·d^-1）， receiving intragastric administration for consecutive 12 weeks. Concurrently， a palmitic acid/oleic acid （PA/OA）-induced lipid deposition model was established in HepG2 cells. Cell counting kit-8 （CCK-8） assay was performed to determine the optimal concentrations of PA/OA and paeoniflorin for intervention. Mice body weight， liver index， and serum levels of alanine aminotransferase （ALT）， aspartate aminotransferase （AST）， triglycerides （TG）， and total cholesterol （TC） were measured. Fasting blood glucose （FBG） and fasting insulin （FINS） levels were measured， and the homeostatic model assessment of insulin resistance （HOMA-IR） was calculated， while an oral glucose tolerance test （OGTT） was performed to evaluate glucose metabolism. Hematoxylin and eosin （HE） staining was used to observe pathological changes and inflammatory cell infiltration in liver tissue， and oil red O staining was used to evaluate lipid droplet deposition in liver tissue and HepG2 cells. Potential targets were screened using network pharmacology and molecular docking. Western blot analysis was performed to detect the expression of HSP90AA1， TLR4， p-NF-κB p65， p-IRS1， and p-Akt proteins in liver tissue and HepG2 cells. ResultsCompared with the normal control group， mice in the MASLD model group exhibited significantly increased body weight， liver index， and serum levels of ALT， AST， TG， and TC， as well as markedly elevated FBG， FINS， and HOMA-IR， and impaired glucose tolerance （P<0.01）. HE staining revealed marked hepatic steatosis and inflammatory cell infiltration， while oil red O staining showed a significant increase in lipid droplet deposition. Compared with the MASLD model group， after intervention with various doses of paeoniflorin， the increase in body weight and liver index was reduced， serum ALT， AST， TG， and TC levels decreased， and FBG， FINS， and HOMA-IR were significantly lowered， with glucose tolerance markedly improved （P<0.05， P<0.01）， showing a certain dose-dependent trend. HE and oil red O staining results showed a marked reduction in hepatic steatosis and lipid deposition. In vitro experiments demonstrated that， compared with the control group， PA/OA treatment significantly induced increased lipid deposition in HepG2 cells. Compared with the model group， paeoniflorin intervention significantly reduced intracellular lipid droplets， and lipid deposition showed a dose-dependent decreasing trend. Mechanism studies indicated that， compared with the normal control group， the MASLD model group exhibited significantly elevated expression of TLR4， HSP90AA1， and p-NF-κB p65， while p-IRS1 （Ser307） expression was elevated and p-Akt （Ser473） expression was reduced （P<0.01）. Compared with the model group， the expression of the aforementioned proteins was significantly reversed in all treatment groups following intervention （P<0.05， P<0.01）. ConclusionPaeoniflorin significantly alleviates lipid deposition and insulin resistance in MASLD mice. Its mechanism of action may involve targeting HSP90AA1， TLR4， and NF-κB1 to regulate the TLR4/NF-κB-IRS1 inflammation-insulin signaling axis. This regulation suppresses inflammatory responses and restores insulin signaling， thereby ameliorating abnormalities in glucose and lipid metabolism.

ObjectiveTo investigate the therapeutic effect of paeoniflorin on metabolic dysfunction-associated fatty liver disease （MASLD） combined with insulin resistance （IR）， and to elucidate its regulatory mechanisms on the Toll-like receptor 4 （TLR4）/nuclear transcription factor （NF）-κB-insulin receptor substrate 1 （IRS1） inflammation-insulin signaling axis. MethodsMASLD mouse model was established using a 60% high-fat diet. Mice were randomly assigned to a normal control group， a MASLD model group， and paeoniflorin groups （low dose： 25 mg·kg^-1·d^-1， medium dose： 50 mg·kg^-1·d^-1， high dose： 100 mg·kg^-1·d^-1）， receiving intragastric administration for consecutive 12 weeks. Concurrently， a palmitic acid/oleic acid （PA/OA）-induced lipid deposition model was established in HepG2 cells. Cell counting kit-8 （CCK-8） assay was performed to determine the optimal concentrations of PA/OA and paeoniflorin for intervention. Mice body weight， liver index， and serum levels of alanine aminotransferase （ALT）， aspartate aminotransferase （AST）， triglycerides （TG）， and total cholesterol （TC） were measured. Fasting blood glucose （FBG） and fasting insulin （FINS） levels were measured， and the homeostatic model assessment of insulin resistance （HOMA-IR） was calculated， while an oral glucose tolerance test （OGTT） was performed to evaluate glucose metabolism. Hematoxylin and eosin （HE） staining was used to observe pathological changes and inflammatory cell infiltration in liver tissue， and oil red O staining was used to evaluate lipid droplet deposition in liver tissue and HepG2 cells. Potential targets were screened using network pharmacology and molecular docking. Western blot analysis was performed to detect the expression of HSP90AA1， TLR4， p-NF-κB p65， p-IRS1， and p-Akt proteins in liver tissue and HepG2 cells. ResultsCompared with the normal control group， mice in the MASLD model group exhibited significantly increased body weight， liver index， and serum levels of ALT， AST， TG， and TC， as well as markedly elevated FBG， FINS， and HOMA-IR， and impaired glucose tolerance （P<0.01）. HE staining revealed marked hepatic steatosis and inflammatory cell infiltration， while oil red O staining showed a significant increase in lipid droplet deposition. Compared with the MASLD model group， after intervention with various doses of paeoniflorin， the increase in body weight and liver index was reduced， serum ALT， AST， TG， and TC levels decreased， and FBG， FINS， and HOMA-IR were significantly lowered， with glucose tolerance markedly improved （P<0.05， P<0.01）， showing a certain dose-dependent trend. HE and oil red O staining results showed a marked reduction in hepatic steatosis and lipid deposition. In vitro experiments demonstrated that， compared with the control group， PA/OA treatment significantly induced increased lipid deposition in HepG2 cells. Compared with the model group， paeoniflorin intervention significantly reduced intracellular lipid droplets， and lipid deposition showed a dose-dependent decreasing trend. Mechanism studies indicated that， compared with the normal control group， the MASLD model group exhibited significantly elevated expression of TLR4， HSP90AA1， and p-NF-κB p65， while p-IRS1 （Ser307） expression was elevated and p-Akt （Ser473） expression was reduced （P<0.01）. Compared with the model group， the expression of the aforementioned proteins was significantly reversed in all treatment groups following intervention （P<0.05， P<0.01）. ConclusionPaeoniflorin significantly alleviates lipid deposition and insulin resistance in MASLD mice. Its mechanism of action may involve targeting HSP90AA1， TLR4， and NF-κB1 to regulate the TLR4/NF-κB-IRS1 inflammation-insulin signaling axis. This regulation suppresses inflammatory responses and restores insulin signaling， thereby ameliorating abnormalities in glucose and lipid metabolism.

[Objective] To investigate the infection status and characteristics of HEV among voluntary blood donors in Ningbo, and to provide a basis for improving the blood screening strategy. [Methods] A total of 12 227 blood samples from voluntary blood donors in Ningbo from June 2022 to May 2023 were tested for HEV serology, enzymology, and nucleic acid testing. Furthermore, HEV gene sequencing was performed for genotyping analysis, and donors with reactive nucleic acid testing results were followed up to confirm their infection status. [Results] The reactivity rate of HEV Ag, anti-HEV IgM and anti-HEV IgG was 0.098%, 0.899% and 29.198%, respectively. There was no difference in the reactivity of anti-HEV IgM and anti-HEV IgG between genders, donation frequencies and donation types (P>0.05). The reactivity rate increased significantly with age (P<0.05). The rate of ALT disqualification (ALT>50U/L) was significantly higher than that in non-reactive samples (P<0.05). The HEV Ag reactivity rate (0.098%) was not correlated with gender, donation frequency, donation type or age. One HEV RNA positive case was found, with a positive rate of 0.008%(1/12 227). It was confirmed to be hepatitis E virus genotype 3 by sequencing analysis. Apart from HEV Ag reactivity, all other blood safety screening items were non-reactive, suggesting this case might be in the acute infection phase. The follow-up results showed that all indicators of the donor's previous blood donation were non-reactive. [Conclusion] Pre-donation ALT detection can reduce the risk of transfusion-transmitted HEV (TT-HEV) to a certain extent, and the effective way to prevent TT-HEV is to detect HEV RNA and serology of donor blood.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To analyze CD36 gene by PacBio Sequel Ⅱ the third-generation sequencing technology (TGS), including non-coding sequence, and to investigate the molecular mechanism of CD36 deficiency. Methods: Flow cytometry was performed in the southern Chinese population to detect the CD36 phenotype. Among them, 15 cases of CD36 type I deficiency, 15 cases of CD36 type Ⅱ deficiency, and 10 positive samples were selected. The TGS of the CD36 gene was performed and statistical analysis was conducted. Results: 40 samples (including 15 cases of type I deficiency, 15 cases of type Ⅱ deficiency, and 10 positive samples) were subjected by TGS of CD36 full-length sequences (except part of intron1). A total of 180 polymorphic loci were identified. Among them, 13 kinds were in the coding region, the rest were in non-coding region, with most mutations located in regulatory regions such as the 5′-UTR and 3′-UTR. Conclusion: The high polymorphism of CD36 non-coding regions, particularly in regulatory sequences, provides mechanistic insights into type Ⅱ CD36 deficiency.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Heat stroke is a heat-related illness caused by an imbalance between the body's heat production and heat dissipation,which could lead to multiple organ dysfunction syndrome with a high mortality rate.Rapid and effective reduction of core body temperature is key to successful treatment.This article reviews recent progress in the treatment of heat stroke,including new understandings of organ injury mechanisms,the timing,velocity and goals of cooling treatment,evaluation and selection of traditional cooling techniques(such as cold water immersion),and scientific evaluation of new cooling technologies(such as blood purification technology and intravascular heat exchange cooling technology),aiming to promote understanding and treatment of heat stroke.