The plant F-box protein more axillary growth 2 (MAX2) is a key factor in the signal transduction of strigolactones (SLs) and karrinkins (KARs). As the main component of the SKP1-CUL1-FBX (SCF) complex ubiquitin ligase E3, MAX2 is responsible for specifically recognizing the target proteins, suppressor of MAX2 1/SMAX1-like proteins (SMAX1/SMXLs), which would be degraded after ubiquitination. It can thereby regulate plant morphogenesis and stress responses. There exist homologous genes of MAX2 in the important grain and oil crop soybean (Glycine max). However, its role in plant defense responses has not been investigated yet. Here, GmMAX2b, a homologous gene of MAX2, was successfully cloned from stressed soybean. Bioinformatics analysis revealed that there were two MAX2 homologous genes, GmMAX2a and GmMAX2b, with a similarity of 96.2% in soybean. Their F-box regions were highly conserved. The sequence alignment and cluster analysis of plant MAX2 homologous proteins basically reflected the evolutionary relationship of plants and also suggested that soybean MAX2 might be a multifunctional protein. Expression analysis showed that plant pathogen infection and salicylic acid treatment induced the expression of GmMAX2b in soybean, which is consistent with that of MAX2 in Arabidopsis. Ectopic expression of GmMAX2b compensated for the susceptibility of Arabidopsis max2-2 mutant to pathogen, indicating that GmMAX2b positively regulated plant disease resistance. In addition, yeast two hybrid technology was used to explore the potential target proteins of GmMAX2b. The results showed that GmMAX2b interacted with SMXL6 and weakly interacted with SMXL2. In summary, GmMAX2b is a positive regulator in plant defense responses, and its expression is induced by pathogen infection and salicylic acid treatment. GmMAX2b might exert its effect through interaction with SMXL6 and SMXL2. This study expands the theoretical exploration of soybean disease resistant F-box and provides a scientific basis for future soybean disease resistant breeding.
Glycine max/metabolism* ; Disease Resistance/genetics* ; Plant Diseases/immunology* ; Plant Proteins/genetics* ; Cloning, Molecular ; Gene Expression Regulation, Plant ; F-Box Proteins/genetics* ; Arabidopsis/genetics* ; Phylogeny

As the social pressure is increasing,the incidence of depression is growing.Testosterone is synthesized and secreted through the hypothalamic-pituitary-gonadal axis,which plays a regulatory role in men's mental health.Studies have shown that low testosterone levels,clinical hypogonadism,and androgen deprivation therapy-induced testosterone deficiency are significantly associated with male depression,while there are still many uncertainties about the mechanism of their effects.Given that low testosterone levels may serve as a characteristic biomarker of male depression risk,testosterone replacement therapy may have a good therapeutic effect on male depression.This article focuses on assessing the role of testosterone levels and related clinical therapies in mood regulation in men.
Humans ; Testosterone/physiology* ; Male ; Depression/etiology* ; Hormone Replacement Therapy

Objective To compare the effects of different doses of budesonide and formoterol fumarate powder for inhalation combined with montelukast sodium tablet in the treatment of cough variant asthma(CVA)and the improvement of airway function and inflammatory factors.Methods Elderly patients with cough variant asthma were randomly divided into group A and group B.Both groups of patients received budesonide and formoterol fumarate powder for inhalation combined with montelukast sodium tablet.Group A was given budesonide and formoterol fumarate powder for inhalation(Ⅱ),2 inhalation per time,twice a day;Group B was given budesonide and formoterol fumarate powder for inhalation,4 inhalation per time,twice a day;budesonide fumatrol inhalation powder mist for continuous treatment for 6 months,and montelukast sodium tablet 10 mg once a day for at least 3 months.The nighttime cough scores of the two groups were compared before treatment and after treatment.The percentage of forced expiratory volume in one second(FEV1)in the predicted value,the maximum mid expiratory flow(MMEF),the fractional exhaled nitric oxide(FeNO),interleukin-5(IL-5)and eosinophils were compared between the two groups.The incidence of adverse drug reactions and the recurrence rate within 1 year were compared between the two groups.Results A total of 45 cases were enrolled in both the group A and the group B.At 9 months after treatment,the nocturnal cough scores of the group A and the group B were(0.93±0.42)and(0.65±0.29)points,respectively;the percentage of FEV1 in the predicted value were(97.75±9.67)％and(100.93±11.06)％,respectively;the MMEF values were(2.81±1.04)and(3.08±1.09)L·s-1,respectively;the FeNO values were(18.94±9.75)and(15.94±7.96)ppb,respectively;the IL-5 levels were(10.88±7.06)and(8.11±5.56)pg·mL-1,respectively.The above indicators in group B showed statistically significant differences compared to group A(all P＜0.05).The total incidence of adverse drug reactions in group A and group B were 8.89％(5 cases/45 cases)and 13.33％(6 cases/45 cases),respectively.The recurrence rates was 15.56％(7 cases/45 cases)and 13.33％(6 cases/45 cases),respectively.There was no statistically significant difference in the above indicators between group B and group A(all P＞0.05).Conclusion For elderly patients with CVA,higher dose of budesonide and formoterol fumarate powder for inhalation combined with montelukast sodium tablet can better improve cough symptoms,reduce the level of airway hyperresponsiveness and inflammatory factors,reduce the recurrence rate,and the patients are well tolerated.

Objective:To evaluate the efficacy of preoperative prediction of regional lymph node (RLN) metastasis in renal cell carcinoma (RCC) using a machine learning model based on habitat imaging radiomics from renal MRI.Methods:This cross-sectional study retrospectively analyzed 220 patients with RCC who underwent nephrectomy and RLN dissection at four medical centers of Chinese PLA General Hospital from January 2010 to August 2023. The cohort included 65 patients with RLN metastasis and 155 without. A stratified random sampling method was used to divide 175 patients from the first medical center into a training set ( n=140) and an internal test set ( n=35) in an 8∶2 ratio, while 45 patients from the third, fourth, and fifth medical centers constituted the external test set. The primary RCC lesions were categorized into 15 habitat subregions based on corticomedullary-phase enhancement and T 2WI signal intensity on MRI, and the volume fractions of different subregions were analyzed. In the training cohort, radiomics features derived from the habitat subregions were used to construct a radiomics model employing various machine learning algorithms, including extremely random trees (ET), gradient boosting decision trees (GBDT), random forest (RF), and support vector machine (SVM). The optimal model was selected and combined with RLN short-axis diameter to develop a combined model. The efficacy of each model in predicting RLN metastasis was evaluated using the receiver operating characteristic (ROC) curve. Results:The volume fraction of hyper-enhanced hyper-intense regions in the non-metastatic group was significantly higher than that in the metastatic group (0.05±0.09 vs. 0.02±0.03; t=3.00, P=0.003). Among the machine learning models constructed using 15 optimal habitat radiomics features, the SVM model demonstrated the best performance, with area under the ROC curve (AUC) values of 0.85 (95% CI 0.72-0.98) in the internal test set and 0.82 (95% CI 0.67-0.98) in the external test set, surpassing those of the ET, GBDT, and RF models. The combined model, integrating the SVM model with RLN short-axis diameter, achieved AUC values of 0.94 (95% CI 0.85-1.00) in the internal test set and 0.89 (95% CI 0.78-1.00) in the external test set, with RLN short-axis diameter contributing AUC values of 0.81 (95% CI 0.66-0.96) and 0.81 (95% CI 0.68-0.94), respectively. The diagnostic sensitivity of the combined model was 91.7% in the internal test set and 85.7% in the external test set, with specificities of 78.3% and 67.7%, respectively. Conclusion:The combined model based on MRI habitat imaging radiomics and RLN short-axis diameter demonstrates excellent preoperative assessment capability for RLN metastasis in RCC.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Acute respiratory distress syndrome (ARDS) is the leading cause of respiratory failure with high morbidity and mortality. Pulmonary surfactant (PS)-based complementary therapies have exhibited potential for ARDS healing and applied as an adjunctive therapy strategy. Coacervate (Coac) has the characteristics of softness, deformability and excellent molecular enrichment properties, and has attracted extensive attention in the biomedical field. Here PS and coacervate were combined for the potential ARDS treatment. The Coac, fabricated from polyallylamine hydrochloride (PAH) and adenosine triphosphate (ATP) by simple mixing, exhibited soft droplet property and high enrichment for dexamethasone sodium phosphate (DSP). To avoid the fusion effect of membraneless coacervate and endow it with biological functions of PS, liposomes with PS-biomimetic lipid components (PS-lipo) were further introduced to construct PS-biomimetic membranized coacervate (DSP@PS-Coac). The DSP@PS-Coac demonstrated high lung targeting effect and significant penetration efficiency after intravenous injection. Furthermore, PS-lipo replenished the endogenous PS pool and facilitated the distribution of DSP in inflammatory cells in the lung. In the ARDS mouse model, PS-Coac and DSP exerted synergetic anti-inflammatory functions, via reducing the recruitment of inflammatory neutrophils and modulating macrophages into anti-inflammatory phenotype. The overall results confirmed that DSP@PS-Coac may provide a promising delivery option for the treatment of ARDS.

Objective To compare the effects of different doses of budesonide and formoterol fumarate powder for inhalation combined with montelukast sodium tablet in the treatment of cough variant asthma(CVA)and the improvement of airway function and inflammatory factors.Methods Elderly patients with cough variant asthma were randomly divided into group A and group B.Both groups of patients received budesonide and formoterol fumarate powder for inhalation combined with montelukast sodium tablet.Group A was given budesonide and formoterol fumarate powder for inhalation(Ⅱ),2 inhalation per time,twice a day;Group B was given budesonide and formoterol fumarate powder for inhalation,4 inhalation per time,twice a day;budesonide fumatrol inhalation powder mist for continuous treatment for 6 months,and montelukast sodium tablet 10 mg once a day for at least 3 months.The nighttime cough scores of the two groups were compared before treatment and after treatment.The percentage of forced expiratory volume in one second(FEV1)in the predicted value,the maximum mid expiratory flow(MMEF),the fractional exhaled nitric oxide(FeNO),interleukin-5(IL-5)and eosinophils were compared between the two groups.The incidence of adverse drug reactions and the recurrence rate within 1 year were compared between the two groups.Results A total of 45 cases were enrolled in both the group A and the group B.At 9 months after treatment,the nocturnal cough scores of the group A and the group B were(0.93±0.42)and(0.65±0.29)points,respectively;the percentage of FEV1 in the predicted value were(97.75±9.67)％and(100.93±11.06)％,respectively;the MMEF values were(2.81±1.04)and(3.08±1.09)L·s-1,respectively;the FeNO values were(18.94±9.75)and(15.94±7.96)ppb,respectively;the IL-5 levels were(10.88±7.06)and(8.11±5.56)pg·mL-1,respectively.The above indicators in group B showed statistically significant differences compared to group A(all P＜0.05).The total incidence of adverse drug reactions in group A and group B were 8.89％(5 cases/45 cases)and 13.33％(6 cases/45 cases),respectively.The recurrence rates was 15.56％(7 cases/45 cases)and 13.33％(6 cases/45 cases),respectively.There was no statistically significant difference in the above indicators between group B and group A(all P＞0.05).Conclusion For elderly patients with CVA,higher dose of budesonide and formoterol fumarate powder for inhalation combined with montelukast sodium tablet can better improve cough symptoms,reduce the level of airway hyperresponsiveness and inflammatory factors,reduce the recurrence rate,and the patients are well tolerated.

Dormant tumor cells constitute a population of cancer cells that reside in a non-proliferative or low-proliferative state, typically arrested in the G0/G1 phase and exhibiting minimal mitotic activity. These cells are commonly observed across multiple cancer types, including breast, lung, and ovarian cancers, and represent a central cellular component of minimal residual disease (MRD) following surgical resection of the primary tumor. Dormant cells are closely associated with long-term clinical latency and late-stage relapse. Due to their quiescent nature, dormant cells are intrinsically resistant to conventional therapies—such as chemotherapy and radiotherapy—that preferentially target rapidly dividing cells. In addition, they display enhanced anti-apoptotic capacity and immune evasion, rendering them particularly difficult to eradicate. More critically, in response to microenvironmental changes or activation of specific signaling pathways, dormant cells can re-enter the cell cycle and initiate metastatic outgrowth or tumor recurrence. This ability to escape dormancy underscores their clinical threat and positions their effective detection and elimination as a major challenge in contemporary cancer treatment. Hypoxia, a hallmark of the solid tumor microenvironment, has been widely recognized as a potent inducer of tumor cell dormancy. However, the molecular mechanisms by which tumor cells sense and respond to hypoxic stress—initiating the transition into dormancy—remain poorly defined. In particular, the lack of a systems-level understanding of the dynamic and multifactorial regulatory landscape has impeded the identification of actionable targets and constrained the development of effective therapeutic strategies. Accumulating evidence indicates that hypoxia-induced dormancy tumor cells are accompanied by a suite of adaptive phenotypes, including cell cycle arrest, global suppression of protein synthesis, metabolic reprogramming, autophagy activation, resistance to apoptosis, immune evasion, and therapy tolerance. These changes are orchestrated by multiple converging signaling pathways—such as PI3K-AKT-mTOR, Ras-Raf-MEK-ERK, and AMPK—that together constitute a highly dynamic and interconnected regulatory network. While individual pathways have been studied in depth, most investigations remain reductionist and fail to capture the temporal progression and network-level coordination underlying dormancy transitions. Systems biology offers a powerful framework to address this complexity. By integrating high-throughput multi-omics data—such as transcriptomics and proteomics—researchers can reconstruct global regulatory networks encompassing the key signaling axes involved in dormancy regulation. These networks facilitate the identification of core regulatory modules and elucidate functional interactions among key effectors. When combined with dynamic modeling approaches—such as ordinary differential equations—these frameworks enable the simulation of temporal behaviors of critical signaling nodes, including phosphorylated AMPK (p-AMPK), phosphorylated S6 (p-S6), and the p38/ERK activity ratio, providing insights into how their dynamic changes govern transitions between proliferation and dormancy. Beyond mapping trajectories from proliferation to dormancy and from shallow to deep dormancy, such dynamic regulatory models support topological analyses to identify central hubs and molecular switches. Key factors—such as NR2F1, mTORC1, ULK1, HIF-1α, and DYRK1A—have emerged as pivotal nodes within these networks and represent promising therapeutic targets. Constructing an integrative, systems-level regulatory framework—anchored in multi-pathway coordination, omics-layer integration, and dynamic modeling—is thus essential for decoding the architecture and progression of tumor dormancy. Such a framework not only advances mechanistic understanding but also lays the foundation for precision therapies targeting dormant tumor cells during the MRD phase, addressing a critical unmet need in cancer management.

Objective To develop an objective and precise prognostic model for assessing severity and prognosis in elderly patients with community-acquired pneumonia(CAP)admitted to the emergency department.Methods A retrospective analysis was conducted on elderly patients with CAP admitted to Department of Emergency,Minhang Hospital,Fudan University between Jun 2018 and Dec 2020.With the primary outcome being the 30-day in-hospital mortality rate of elderly CAP patients,four systemic inflammatory response markers,including the neutrophil-to-lymphocyte ratio(NLR),monocyte-to-lymphocyte ratio(MLR),platelet-to-lymphocyte ratio(PLR),and systemic immune-inflammation index(SII)were evaluated using univariate and multivariate Logistic regression analyses.The predictive performance of different scoring systems was compared.Results A total of 421 elderly CAP cases were enrolled.The results of the multivariate Logistic regression analysis demonstrated that NLR was an independent risk factor for elderly inpatients with CAP.We combined NLR with the existing CURB-65 score for joint optimization to construct a scoring system or a clinical prognosis model,by quantifying and assigning optimal cut-off value of 11.4 for NLR,and established the NLR+CURB-65 score.The ROC curve was constructed to compare the areas under the curve of the three different scoring systems(NLR,CURB-65,and NLR+CURB-65).The area under the curve of the NLR+CURB-65 score was significantly higher than that of the CURB-65 score.Based on the optimal cut-off value of 3 for NLR+CURB-65 score,the patients were stratified into high-risk group(n=188)and low-risk group(n=233).The K-M survival curve was utilized and indicated that compared with high-risk group,low-risk group had a lower mortality rate and a higher discharge rate.Conclusion For elderly emergency hospitalized patients with CAP,the combination of NLR and CURB-65 score showed high predictive value for assessing disease severity and prognosis.

Aim To explore the mechanism of action of Guizhi Jia Gegen decoction(GGD)in treating pneu-monia-enteritis induced by H1N1 influenza virus infec-tion in a mouse model,using network pharmacology and molecular docking techniques,followed by in vivo verification.Methods A pneumonia-enteritis mouse model was established,and the intervention effects of GGD on the model mice were evaluated using indica-tors such as body weight,rectal temperature,lung in-dex,colon length,H1N1 M gene expression,relative mRNA expression levels of inflammatory cytokines,and pathological sections of the lung and intestine.The targets of the blood-absorbed components of GGD were identified using the Swiss Target Prediction platform,and the disease targets were retrieved from the Gene-Cards platform.The intersecting targets were analyzed through PPI network analysis using the STRING data-base to identify core targets.GO analysis and KEGG pathway enrichment analysis were performed using the Metascape database.RT-qPCR was employed to vali-date the core targets and pathways.Molecular docking was conducted using AutoDock Tools software to verify the interactions between blood-absorbed components and key targets.Results GGD demonstrated signifi-cant therapeutic effects on the pneumonia-enteritis mouse model.The results of network pharmacology in-dicated that the therapeutic effects of GGD were strong-ly associated with targets such as TNF,ALB,PTGS2,MMP9,EGFR,ESR1,SRC,HSP90AA1,PPARG and MMP2.RT-qPCR results indicated that GGD could intervene in pneumonia-enteritis by regulating the targets TNF,ALB,EGFR and the related targets of the NF-κB pathway.Molecular docking results re-vealed that blood-absorbed components such as puerar-in and liquiritin could stably bind to TNF,ALB and EGFR.Conclusion Components such as puerarin and liquiritin in GGD may exert therapeutic effects on pneumonia-enteritis induced by H1N1 influenza virus infection by acting on targets such as TNF,ALB and EGFR.