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.

ObjectiveTo investigate the role of 4-week high-intensity interval training (HIIT) in modulating the metabolic homeostasis of the pyruvate-lactate axis in the hippocampus of rats with chronic unpredictable mild stress (CUMS) to improve their depressive-like behavior. MethodsForty-eight SPF-grade 8-week-old male SD rats were randomly divided into 4 groups: the normal quiet group (C), the CUMS quiet group (M), the normal exercise group (HC), and the CUMS exercise group (HM). The M and HM groups received 8 weeks of CUMS modeling, while the HC and HM groups were exposed to 4 weeks of HIIT starting from the 5th week (3 min (85%-90%) S_max+1 min (50%-55%) S_max, 3-5 cycles, S_max is the maximum movement speed). A lactate analyzer was used to detect the blood lactate concentration in the quiet state of rats in the HC and HM groups at week 4 and in the 0, 2, 4, 8, 12, and 24 h after exercise, as well as in the quiet state of rats in each group at week 8. Behavioral indexes such as sucrose preference rate, number of times of uprightness and number of traversing frames in the absenteeism experiment, and other behavioral indexes were used to assess the depressive-like behavior of the rats at week 4 and week 8. The rats were anesthetized on the next day after the behavioral test in week 8, and hippocampal tissues were taken for assay. LC-MS non-targeted metabolomics, target quantification, ELISA and Western blot were used to detect the changes in metabolite content, lactate and pyruvate concentration, the content of key metabolic enzymes in the pyruvate-lactate axis, and the protein expression levels of monocarboxylate transporters (MCTs). Results4-week HIIT intervention significantly increased the sucrose preference rate, the number of uprights and the number of traversed frames in the absent field experiment in CUMS rats; non-targeted metabolomics assay found that 21 metabolites were significantly changed in group M compared to group C, and 14 and 11 differential metabolites were significantly dialed back in the HC and HM groups, respectively, after the 4-week HIIT intervention; the quantitative results of the targeting showed that, compared to group C, lactate concentration in the hippocampal tissues of M group, compared with group C, lactate concentration in hippocampal tissue was significantly reduced and pyruvate concentration was significantly increased, and 4-week HIIT intervention significantly increased the concentration of lactate and pyruvate in hippocampal tissue of HM group; the trend of changes in blood lactate concentration was consistent with the change in lactate concentration in hippocampal tissue; compared with group C, the LDHB content of group M was significantly increased, the content of PKM2 and PDH, as well as the protein expression level of MCT2 and MCT4 were significantly reduced. The 4-week HIIT intervention upregulated the PKM2 and PDH content as well as the protein expression levels of MCT2 and MCT4 in the HM group. ConclusionThe 4-week HIIT intervention upregulated blood lactate concentration and PKM2 and PDH metabolizing enzymes in hippocampal tissues of CUMS rats, and upregulated the expression of MCT2 and MCT4 transport carrier proteins to promote central lactate uptake and utilization, which regulated metabolic homeostasis of the pyruvate-lactate axis and improved depressive-like behaviors.

ObjectiveThis study aimed to investigate the effects of 4-week high-intensity interval training (HIIT) on synaptic plasticity in the prefrontal cortex (PFC) of rats exposed to chronic unpredictable mild stress (CUMS), and to explore its potential mechanisms. MethodsA total of 48 male Sprague-Dawley rats were randomly divided into 4 groups: control (C), model (M), control plus HIIT (HC), and model plus HIIT (HM). Rats in groups M and HM underwent 8 weeks of CUMS to establish depression-like behaviors, while groups HC and HM received HIIT intervention beginning from the 5th week for 4 consecutive weeks. The HIIT protocol consisted of repeated intervals of 3 min at high speed (85%-90% maximal training speed, S_max) alternated with one minute at low speed (50%-55% S_max), with 3 to 5 sets per session, conducted 5 d per week. Behavioral assessments and tail-vein blood lactate levels were measured at the end of the 4th and 8th weeks. After the intervention, rat PFC tissues were collected for Golgi staining to analyze synaptic morphology. Enzyme-linked immunosorbent assays (ELISA) were employed to detect brain-derived neurotrophic factor (BDNF), monocarboxylate transporter 1 (MCT1), lactate, and glutamate levels in the PFC, as well as serotonin (5-HT) levels in serum. Additionally, Western blot analysis was conducted to quantify the expression of synaptic plasticity-related proteins, including c-Fos, activity-regulated cytoskeleton-associated protein (Arc), and N-methyl-D-aspartate receptor 1 (NMDAR1). ResultsCompared to the control group (C), the CUMS-exposed rats (group M) exhibited significant reductions in sucrose preference rates, number of grid crossings, frequency of upright postures, and entries into and duration spent in open arms of the elevated plus maze, indicating marked depressive-like behaviors. Additionally, the group M showed significantly reduced dendritic spine density in the PFC, along with elevated levels of c-Fos, Arc, NMDAR1 protein expression, and increased concentrations of lactate and glutamate. Conversely, BDNF and MCT1 contents in the PFC and 5-HT levels in serum were significantly decreased. Following HIIT intervention, rats in the group HM displayed considerable improvement in behavioral indicators compared with the group M, accompanied by significant elevations in PFC MCT1 and lactate concentrations. Furthermore, HIIT notably normalized the expression levels of c-Fos, Arc, NMDAR1, as well as glutamate and BDNF contents in the PFC. Synaptic spine density also exhibited significant recovery. ConclusionFour weeks of HIIT intervention may alleviate depressive-like behaviors in CUMS rats by increasing lactate levels and reducing glutamate concentration in the PFC, thereby downregulating the overexpression of NMDAR, attenuating excitotoxicity, and enhancing synaptic plasticity.

Objective To analyze the acupoint selection rules of acupuncture for the treatment of tic disorders in children based on data mining techniques.Methods A computerized search was conducted for the clinical research literature on acupuncture treatment of tic disorders in children included in the CNKI,Wanfang,VIP,SinoMed,and PubMed databases from January 1992 to December 2022.A database was established by Excel 2019 to count the commonly used treatment methods and analyze the high-frequency application methods acupuncture(high-frequency acupoints,channel entry of acupoints,acupoint association rules,and acupoint clustering),auricular point seed-pressing(high-frequency auricular points,and acupoint association rules),and the high frequency division of cluster needling of scalp point.Results A total of 190 valid literature articles were included,involving 270 acupuncture prescriptions;among them,184 acupoints were counted in the acupuncture method,with a total application frequency of 1 906 times,and the high-frequency application of the acupoints in descending order were Baihui(DU20),Taichong(LR3),Fengchi(GB20),Hegu(LI4),Sanyinjiao(SP6),Neiguan(PC6),Shenmen(HT7),Zusanli(ST36),Yintang(EX-HN3),Sishencong(EX-HN1);and the high-frequency meridians were governor vessol,foot taiyang stomach meridian,foot taiyang stomach meridian,foot shaoyang gallbladder meridian,hand taiyang large intestine meridian,foot taiyang bladder meridian,foot jueyin gallbladder meridian;three sets of strong association rules and five clusters of acupoints were analyzed by SPSS modeler 18.0 and IBM SPSS Statistics 26.0 software.There were 29 acupoints of auricular point seed-pressing,application total frequency was 206 times,high-frequency application of auricular points in descending order of Shenmen(HT7),liver,heart,subcortex,kidney;four groups of acupoint strong association rules were obtained through the analysis of SPSS modeler 18.0 software.A total of 14 zones were involved in the application of cephalic acupoint plexus zoning,of which the high-frequency zones were parietal anterior temporal diagonal,parietal parietal 1,and chorea tremor control zone.Conclusion Acupuncture treatment of tic disorders in children,according to its pathogenesis(liver hyperactivity,kidney depletion,spleen deficiency,phlegm disturbance,etc.)and tic site,select acupoints compatibility,and mostly choose yang meridian acupoints,which is related to the nature and treatment characteristics of wind pathogen.Children's tic disorders are closely related to emotional disorders,therefore acupuncture and auricular acupoints all emphasize the method of soothing the liver and clearing the heart,and regulating the emotional state.Cluster needling of scalp point mostly used parietal temporal anterior oblique line,parietal 1 line,and dance tremor control area for the treatment of tic disorders.For children,auricular point seed-pressing and cluster needling of scalp point has the minimun of pain,the effect of treatment is long,and it is not easy to have dangerous situations such as bent needle,broken needle and so on.

Superior vena cava syndrome(SVCS)is a group of clinical syndromes caused by obstruction of the superior vena cava and its major branches from various causes.Pulmonary artery stenosis(PS)is a complication of lung cancer or mediastinal tumours.SVCS combined with PS due to pulmonary metastases from bladder cancer is extremely rare and has not been reported in the literature.Here we reported an old male patient with pulmonary metastases from bladder cancer presenting with swelling of the head,neck and both upper limbs.SVCS combined with PS was clarified by pulmonary artery computed tomography angiography(CTA)and digital subtraction angiography(DSA).Endovascular stenting was used to treat SVCS.Angiography also showed that PS had not caused pulmonary hypertension and did not need to be treated.The swelling of the patient's head,neck and upper limbs was gradually reduced after the procedure.

Objective Recombinase-aided polymerase chain reaction(RAP)is a sensitive,single-tube,two-stage nucleic acid amplification method.This study aimed to develop an assay that can be used for the early diagnosis of three types of bacteremia caused by Staphylococcus aureus(SA),Pseudomonas aeruginosa(PA),and Acinetobacter baumannii(AB)in the bloodstream based on recombinant human mannan-binding lectin protein(M1 protein)-conjugated magnetic bead(M1 bead)enrichment of pathogens combined with RAP. Methods Recombinant plasmids were used to evaluate the assay sensitivity.Common blood influenza bacteria were used for the specific detection.Simulated and clinical plasma samples were enriched with M1 beads and then subjected to multiple recombinase-aided PCR(M-RAP)and quantitative PCR(qPCR)assays.Kappa analysis was used to evaluate the consistency between the two assays. Results The M-RAP method had sensitivity rates of 1,10,and 1 copies/μL for the detection of SA,PA,and AB plasmids,respectively,without cross-reaction to other bacterial species.The M-RAP assay obtained results for<10 CFU/mL pathogens in the blood within 4 h,with higher sensitivity than qPCR.M-RAP and qPCR for SA,PA,and AB yielded Kappa values of 0.839,0.815,and 0.856,respectively(P<0.05). Conclusion An M-RAP assay for SA,PA,and AB in blood samples utilizing M1 bead enrichment has been developed and can be potentially used for the early detection of bacteremia.

Adaptive immunity is a critical component of the human immune system, playing an essential role in identifying antigens and orchestrating a tailored immune response. This review delves into the significant strides made in the development of epitope prediction tools, their integration into vaccine design, and their pivotal role in enhancing immunotherapy strategies. The review emphasizes the transformative potential of these tools in refining our understanding and application of immune responses. Adaptive immunity distinguishes itself from innate immunity by its ability to recognize specific antigens and remember past infections, leading to quicker and more effective responses upon subsequent exposures. This facet of immunity involves complex interactions between various cell types, primarily B cells and T cells, which recognize distinct epitopes presented by antigens. Epitopes are small sequences or configurations on antigens that are recognized by the immune receptors on B cells and T cells, acting as the focal points of immune recognition and response. Epitopes can be broadly classified into two types: linear (or sequential) epitopes and conformational (or discontinuous) epitopes. Linear epitopes consist of a sequence of amino acids in a protein that are recognized by B cells and T cells in their primary structure form. Conformational epitopes, on the other hand, are formed by spatially distinct amino acids that come together in the tertiary structure of the protein, often recognized by the immune system only when the protein folds into its native conformation. The role of epitopes in the immune response is critical as they are the primary triggers for the activation of B cells and T cells. When an epitope is recognized, it can stimulate B cells to produce antibodies, mobilize helper T cells to secrete cytokines, or prompt cytotoxic T cells to kill infected cells. These actions form the basis of the adaptive immune response, tailored to eliminate specific pathogens or infected cells effectively. The prediction of B cell and T cell epitopes has evolved with advances in computational biology, leading to the development of several sophisticated tools that utilize a variety of algorithms to predict the likelihood of epitope regions on antigens. Tools employing machine learning methods, such as support vector machines (SVMs), XGBoost, random forest, analyze large datasets of known epitopes to classify new sequences as potential epitopes based on their similarity to known data. Moreover, deep learning has emerged as a powerful method in epitope prediction, leveraging neural networks capable of learning high-dimensional data from vast amounts of immunological inputs to identify patterns that may not be evident to other predictive models. Deep learning models, such as convolutional neural networks (CNNs), recurrent neural networks (RNNs) and ESM protein language model have demonstrated superior accuracy in mapping the nonlinear relationships inherent in protein structures and epitope interactions. The application of epitope prediction tools in vaccine design is transformative, enabling the development of epitope-based vaccines that can elicit targeted immune responses against specific parts of the pathogen. These vaccines, by focusing the immune response on highly specific regions of the pathogen, can offer high efficacy and reduced side effects. Similarly, in cancer immunotherapy, epitope prediction tools help identify tumor-specific antigens that can be targeted to develop personalized immunotherapeutic strategies, thereby enhancing the precision of cancer treatments. The future of epitope prediction technology appears promising, with ongoing advancements anticipated to enhance the precision and efficiency of these tools further. The integration of broader immunological data, such as patient-specific immune profiles and pathogen variability, along with advances in AI and machine learning, will likely drive the development of more adaptive, robust, and clinically relevant prediction models. This will not only improve the effectiveness of vaccines and immunotherapies but also contribute to our broader understanding of immune mechanisms, potentially leading to breakthroughs in the treatment and prevention of multiple diseases. In conclusion, the development and refinement of epitope prediction tools stand as a cornerstone in the advancement of immunological research and therapeutic design, highlighting a path toward more precise and personalized medicine. The ongoing integration of computational models with experimental immunology holds the promise of revolutionizing our approach to combating infectious diseases and cancer.

AIM To investigate the effects of total Astragalus saponins on the improvement of sarcopenia in a rat model of type 2 diabetes mellitus(T2DM).METHODS The rats were divided into the normal group for a normal feeding and the model group for the feeding of high-sugar and high-fat diet combined with intraperitoneal injection of STZ to establish a T2DM model.The successful model rats were randomly divided into the model group,the metformin group(0.2 g/kg)and the total Astragalus saponins group(80 mg/kg),and given corresponding doses of drugs by gavage.After 12 weeks administration,the rats had their FBG,postprandial blood glucose(PG2h)and wet weight of skeletal muscle measured;their serum levels of INS,C-peptide(C-P),IGF-1,TNF-α and IL-1β detected by ELISA;their morphological changes of skeletal muscle observed by HE staining;their protein expressions of PI3K,p-Akt,mTOR,S6K1,FoxO1 and Murf1 in skeletal muscle detected by Western blot;and their mRNA expressions of Pi3k,Akt and mtor in skeletal muscle detected by RT-qPCR method.RESULTS Compared with the model group,the total Astragalus saponins group displayed decreased levels of FBG,PG2h,OGTT-AUC,HOMA-IR,TNF-α and IL-1β(P＜0.01);increased levels of INS,C-P,IGF-1 and wet weight of skeletal muscle(P＜0.05,P＜0.01);improved skeletal muscle atrophy and increased protein expressions of PI3K,p-Akt,mTOR and S6K1 in skeletal muscle(P＜0.05,P＜0.01);decreased protein expressions of FoxO1 and Murf1(P＜0.05,P＜0.01);and increased mRNA expressions of Pi3k,Akt and mtor(P＜0.01).CONCLUSION The improvement effects of total Astragalus saponins on sarcopenia in T2DM rats may be associated with the regulation of PI3K/Akt/mTOR and PI3K/Akt/FoxO1 pathways.

The purpose of this study was to investigate the regulatory effects of biofilm associated non-coding small RNA(sRNA)00085 on the survival and environmental fitness of Listeria monocytogenes.Homologous recombination technology was used to construct a deletion mutant strain(△sRNA 00085)and a complementary strain(C △sRNA 00085)of the sRNA00085 target gene.The differences in biological characteristics were compared among the standard strain,△sRNA 00085,and C△sRNA 00085.The deletion of sRNA00085 led to a significant decrease in biofilm formation capacity and sensitivity to several antibiotics,including penicillin,piperacillin,doxycycline,tetracycline,vancomycin,and cotrimoxazole.However,only the minimum inhibitory concentration(MIC)of tetracycline exhibited a significant decrease in △sRNA00085.Meanwhile,the decreased biofilm formation and antibiotic resistance of the sRNA00085 mutant were restored in the C△sRNA00085 strain.Furthermore,we investigated the transcription levels of tetracycline resistance-related genes in L.monocytogenes.Down-regu-lated transcription of the tetS gene but no significant difference in transcription of the tetA gene were observed in △sRNA 00085 compared with the standard strain and C△sRNA00085.Moreover,the elimination of sRNA00085 did not affect bacterial growth ability or sensitivity to disinfectants.These findings highlight that sRNA00085 plays an important role in the environ-mental adaptability of L.monocytogenes by affecting bacterial biofilm formation and resistance.

Objective:To investigate the effect of pre-treatment plasma Epstein-Barr virus(EBV)DNA copy number on the clinical features and prognosis of patients with adult secondary hemophagocytic lymphohistiocytosis(sHLH).Methods:The clinical characteristics,survival rate,and prognostic factors of 171 patients with adult sHLH treated at Jiangsu Province Hospital from June 2017 to January 2022 were retrospectively analyzed in this study.Patients were divided into three groups,including the EBV DNA-negative group(＜5.0 × 102 copies/ml),lower EBV-DNA loads group(5.0 × 102-8.51 × 104 copies/ml),and higher EBV-DNA loads group(＞8.51 × 104 copies/ml),according to pre-treatment plasma EBV-DNA copy number.Cox regression model was established for screening prognostic factors.Adult sHLH survival prediction model was constructed and realized through the nomogram based on EBV-DNA load after adjusted the factors affecting survival of etiology and treatment strategy.Concordance index(C-index)and calibration curves were calculated to verify model predictive and discriminatory capacity.Results:Among 171 adult sHLH patients,84 patients were not infected with EBV(EBV DNA-negative group),and 87 with EBV(EBV DNA-positive group,48 lower EBV-DNA loads group and 39 higher EBV-DNA loads group).Consistent elevations in the levels of liver enzymes(ALT and AST),LDH,TG,β2-microglobulin and ferritin across the increasing of EBV-DNA load(all P＜0.05),while the levels of fibrinogen decrease(P＜0.001).The median follow-up time was 52 days(range 20-230 days),and 123 patients died.The overall survival(OS)rate of patients in EBV DNA-positive group was lower than that in EBV DNA-negative group(median OS:40 days vs 118 days,P＜0.001).Higher EBV-DNA loads had worse OS(median OS:24 days vs 45 days vs 118 days,P＜0.0001 for trend)compared to lower EBV-DNA loads and EBV DNA-negative group.Multivariate Cox analysis revealed that higher EBV-DNA loads(P=0.005),fibrinogen≤ 1.5 g/L(P=0.012),ferritin(P=0.041),associated lymphoma(P=0.002),and anti-tumor based strategy(P=0.001)were independent prognostic factors for OS.The C-indexes of 30 day,90 days,365 days survival rate were all greater than 0.8 of the nomogram model and calibration curves provided credibility to their predictive capability.Subgroup analysis showed that patients with higher EBV-DNA loads had a significantly worse prognosis in adult sHLH who were women,ferritin＞5 000 μg/L,β2-microglobulin＞7.4 mmol/L and regardless of age,etiologies,HScore points.Conclusion:The EBV-DNA load is a strong and independent predictor for survival in patients with sHLH.The prognostic nomogram based on EBV-DNA loads was dependable and provides a visual tool for evaluating the survival of adult sHLH.