A growing body of research points out that gut microbiota plays a key role in tumor immunotherapy. By optimizing the composition of intestinal microbiota, it is possible to effectively improve immunotherapy resistance and enhance its therapeutic effect. This article comprehensively analyzes the mechanism of intestinal microbiota influencing tumor immunotherapy resistance, expounds the current strategies for targeted regulation of intestinal microbiota, such as traditional Chinese medicine and plant components, fecal microbiota transplantation, probiotics, prebiotics and dietary therapy, and explores the potential mechanisms of these strategies to improve patients' resistance to tumor immunotherapy. At the same time, the article also briefly discusses the prospects and challenges of targeting intestinal microbiota to improve tumor immunotherapy resistance, which provides a reference for related research to help the strategy research of reversing tumor immunotherapy resistance.

Lung transplantation is the optimal treatment for end-stage lung diseases and can significantly improve prognosis of the patients. However, postoperative complications such as infection, rejection, ischemia-reperfusion injury, and other challenges (like shortage of donor lungs) , limit the practical application of lung transplantation in clinical practice. Chinese research teams have been making continuous efforts and have achieved breakthroughs in basic research on lung transplantation by integrating emerging technologies and cutting-edge achievements from interdisciplinary fields, which has strongly propelled the development of this field. This article will comprehensively review the academic progress made by Chinese research teams in the field of lung transplantation in 2024, with a focus on the achievements of Chinese teams in basic research on lung transplantation. It aims to provide innovative ideas and strategies for key issues in the basic field of lung transplantation and to help China's lung transplantation cause reach a higher level.

Objective: To evaluate the application of blood conservation measures in obstetric patients with different red blood cell transfusion volumes and to assess the impact of different transfusion volumes on postpartum outcomes. Methods: A retrospective investigation was conducted on 448 obstetric patients who received blood transfusions at the Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine from January 2016 to December 2022. Patients were divided into four groups (1-2 units group, 3-4 units group, 5-6 units group, and >6 units group) based on the volumes of red blood cells (RBCs) transfused during and within 7 days after delivery. The maternal physiological indicators, pre- and postpartum laboratory test indicators, obstetric complications, application of blood conservation measures, use of blood products, and postpartum outcomes were reviewed. The clinical characteristics, application of blood conservation measures, and their impact on postpartum outcomes were compared among different transfusion groups. Results: There were statistically significant differences in the multivariate logistic analysis of history of previous cesarean section (OR=1.781), eclampsia/pre-eclampsia/(OR=1.972) and postpartum blood loss>1 000 mL（OR=1.699）(P<0.05) among different transfusion groups. In terms of blood conservation measures, the more RBCs transfused, the higher the rate of mothers receiving blood conservation measures such as balloon occlusion, arterial ligation, autologous blood transfusion with a cell saver, and hysterectomy. With the increase in the volume of RBCs transfusion, the demand for fresh frozen plasma（FFP）, cryoprecipitate, and platelet transfusions also increased. The hospitalization days for the four groups of parturients were 6.0 (4.0-9.0), 7.5 (5.0-14.8), 7.0 (4.5-13.0) and 11.0 (9.0-20.5), respectively (P<0.05) and the rates of ICU transfer were 2.0% (5/250), 9.4% (12/128),18.2% (6/33) and 51.4% (19/37), respectively (P<0.05). Both increased significantly with the increase in the volume of RBCs transfusion, and the differences between groups were statistically significant. Conclusion: Parturients who received higher volume of RBCs had multiple risks factors for bleeding before childbirth, had higher postpartum blood loss, and had a higher rate of application of various blood conservation measures. In addition, an increase in the volume of RBCs transfusion may have adverse effects on postpartum recovery.

This study aims to explore the impact of host plants on the quality of Taxilli Herba and provide a theoretical basis for the quality control of Taxilli Herba. The components of Taxilli Herba from three different host plants(Morus alba, Salix babylonica, and Cinnamomum cassia) and its 3 hosts(mulberry branch, willow branch, and cinnamon branch) were detected by widely targeted metabolomics based on ultra-high performance liquid chromatography-tandem mass spectrometry(UPLC-MS/MS). Principal component analysis(PCA), orthogonal partial least squares discriminant analysis(OPLS-DA), and Venn diagram were employed for analysis. A total of 717 metabolites were detected in Taxilli Herba from the three host plants and the branches of these host plants by UPLC-MS/MS. The results of PCA and OPLS-DA of Taxilli Herba from the three different host plants showed an obvious separation trend due to the different effects of host plants. The Venn diagram showed that there were 32, 8, and 26 characteristic metabolites in samples of Taxilli Herba from M. alba host, S. babylonica host, and C. cassia host, respectively. It was found by comparing the characteristic metabolites of Taxilli Herba and its hosts that each host transmits its characteristic components to Taxilli Herba, so that the Taxilli Herba contains the characteristic components of the host. The Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway analysis showed that the differential metabolites of Taxilli Herba from the three hosts were mainly enriched in flavonoid biosynthesis, arginine and proline metabolism, and glycolysis/gluconeogenesis pathways. Furthermore, the differential metabolites enriching pathways of Taxilli Herba from the three hosts were different depending on the host. In a word, host plants have a significant impact on the metabolites of Taxilli Herba, and it may be an important factor for the quality of Taxilli Herba.
Metabolomics/methods* ; Drugs, Chinese Herbal/chemistry* ; Chromatography, High Pressure Liquid ; Tandem Mass Spectrometry ; Quality Control ; Salix/chemistry* ; Cinnamomum aromaticum/metabolism* ; Principal Component Analysis

As China accelerates its efforts in deep space exploration and long-duration space missions, including the operationalization of the Tiangong Space Station and the development of manned lunar missions, safeguarding astronauts’ physiological and cognitive functions under extreme space conditions becomes a pressing scientific imperative. Among the multifactorial stressors of spaceflight, microgravity emerges as a particularly potent disruptor of neurobehavioral homeostasis. Dopamine (DA) plays a central role in regulating behavior under space microgravity by influencing reward processing, motivation, executive function and sensorimotor integration. Changes in gravity disrupt dopaminergic signaling at multiple levels, leading to impairments in motor coordination, cognitive flexibility, and emotional stability. Microgravity exposure induces a cascade of neurobiological changes that challenge dopaminergic stability at multiple levels: from the transcriptional regulation of DA synthesis enzymes and the excitability of DA neurons, to receptor distribution dynamics and the efficiency of downstream signaling pathways. These changes involve downregulation of tyrosine hydroxylase in the substantia nigra, reduced phosphorylation of DA receptors, and alterations in vesicular monoamine transporter expression, all of which compromise synaptic DA availability. Experimental findings from space analog studies and simulated microgravity models suggest that gravitational unloading alters striatal and mesocorticolimbic DA circuitry, resulting in diminished motor coordination, impaired vestibular compensation, and decreased cognitive flexibility. These alterations not only compromise astronauts’ operational performance but also elevate the risk of mood disturbances and motivational deficits during prolonged missions. The review systematically synthesizes current findings across multiple domains: molecular neurobiology, behavioral neuroscience, and gravitational physiology. It highlights that maintaining DA homeostasis is pivotal in preserving neuroplasticity, particularly within brain regions critical to adaptation, such as the basal ganglia, prefrontal cortex, and cerebellum. The paper also discusses the dual-edged nature of DA plasticity: while adaptive remodeling of synapses and receptor sensitivity can serve as compensatory mechanisms under stress, chronic dopaminergic imbalance may lead to maladaptive outcomes, such as cognitive rigidity and motor dysregulation. Furthermore, we propose a conceptual framework that integrates homeostatic neuroregulation with the demands of space environmental adaptation. By drawing from interdisciplinary research, the review underscores the potential of multiple intervention strategies including pharmacological treatment, nutritional support, neural stimulation techniques, and most importantly, structured physical exercise. Recent rodent studies demonstrate that treadmill exercise upregulates DA transporter expression in the dorsal striatum, enhances tyrosine hydroxylase activity, and increases DA release during cognitive tasks, indicating both protective and restorative effects on dopaminergic networks. Thus, exercise is highlighted as a key approach because of its sustained effects on DA production, receptor function, and brain plasticity, making it a strong candidate for developing effective measures to support astronauts in maintaining cognitive and emotional stability during space missions. In conclusion, the paper not only underscores the centrality of DA homeostasis in space neuroscience but also reflects the authors’ broader academic viewpoint: understanding the neurochemical substrates of behavior under microgravity is fundamental to both space health and terrestrial neuroscience. By bridging basic neurobiology with applied space medicine, this work contributes to the emerging field of gravitational neurobiology and provides a foundation for future research into individualized performance optimization in extreme environments.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Neuroscience is a significant frontier discipline within the natural sciences and has become an important interdisciplinary frontier scientific field. Brain is one of the most complex organs in the human body, and its structural and functional analysis is considered the “ultimate frontier” of human self-awareness and exploration of nature. Driven by the strategic layout of “China Brain Project”, Chinese scientists have conducted systematic research focusing on “understanding the brain, simulating the brain, and protecting the brain”. They have made breakthrough progress in areas such as the principles of brain cognition, mechanisms and interventions for brain diseases, brain-like computation, and applications of brain-machine intelligence technology, aiming to enhance brain health through biomedical technology and improve the quality of human life. Due to limited understanding and comprehension of neuroscience, there are still many important unresolved issues in the field of neuroscience, resulting in a lack of effective measures to prevent and protect brain health. Therefore, in addition to actively developing new generation drugs, exploring non pharmacological treatment strategies with better health benefits and higher safety is particularly important. Epidemiological data shows that, exercise is not only an indispensable part of daily life but also an important non-pharmacological approach for protecting brain health and preventing neurodegenerative diseases, forming an emerging research field known as motor neuroscience. Basic research in motor neuroscience primarily focuses on analyzing the dynamic coding mechanisms of neural circuits involved in motor control, breakthroughs in motor neuroscience research depend on the construction of dynamic monitoring systems across temporal and spatial scales. Therefore, high spatiotemporal resolution detection of movement processes and movement-induced changes in brain structure and neural activity signals is an important technical foundation for conducting motor neuroscience research and has developed a set of tools based on traditional neuroscience methods combined with novel motor behavior decoding technologies, providing an innovative technical platform for motor neuroscience research. The protective effect of exercise in neurodegenerative diseases provides broad application prospects for its clinical translation. Applied research in motor neuroscience centers on deciphering the regulatory networks of neuroprotective molecules mediated by exercise. From the perspectives of exercise promoting neurogenesis and regeneration, enhancing synaptic plasticity, modulating neuronal functional activity, and remodeling the molecular homeostasis of the neuronal microenvironment, it aims to improve cognitive function and reduce the incidence of Parkinson’s disease and Alzheimer’s disease. This has also advanced research into the molecular regulatory networks mediating exercise-induced neuroprotection and facilitated the clinical application and promotion of exercise rehabilitation strategies. Multidimensional analysis of exercise-regulated neural plasticity is the theoretical basis for elucidating the brain-protective mechanisms mediated by exercise and developing intervention strategies for neurological diseases. Thus,real-time analysis of different neural signals during active exercise is needed to study the health effects of exercise throughout the entire life cycle and enhance lifelong sports awareness. Therefore, this article will systematically summarize the innovative technological developments in motor neuroscience research, review the mechanisms of neural plasticity that exercise utilizes to protect the brain, and explore the role of exercise in the prevention and treatment of major neurodegenerative diseases. This aims to provide new ideas for future theoretical innovations and clinical applications in the field of exercise-induced brain protection.

Objective To externally validate a prediction model based on clinical and CT imaging features for the preoperative identification of high-grade patterns (HGP), such as micropapillary and solid subtypes, in early-stage lung adenocarcinoma, in order to guide clinical treatment decisions. Methods This study conducted an external validation of a previously developed prediction model using a cohort of patients with clinical stage ⅠA lung adenocarcinoma from the Fourth Hospital of Hebei Medical University. The model, which incorporated factors including tumor size, density, and lobulation, was assessed for its discrimination, calibration performance, and clinical impact. Results A total of 650 patients (293 males, 357 females; age range: 30-82 years) were included. The validation showed that the model demonstrated good performance in discriminating HGP (area under the curve>0.7). After recalibration, the model's calibration performance was improved. Decision curve analysis (DCA) indicated that at a threshold probability>0.6, the number of HGP patients predicted by the model closely approximated the actual number of cases. Conclusion This study confirms the effectiveness of a clinical and imaging feature-based prediction model for identifying HGP in stage ⅠA lung adenocarcinoma in a clinical setting. Successful application of this model may be significant for determining surgical strategies and improving patients' prognosis. Despite certain limitations, these findings provide new directions for future research.