Premature ejaculation refers to a sexual dysfunction in which men experience a short intravaginal ejaculation latency and a lack of control over ejaculation during sexual activity. The onset of this condition is often accompanied by anxiety and depression, which can seriously affect the quality of the patient′s sexual life and the relationship between partners. Based on the "integration of body and spirit" theory in traditional Chinese medicine, our team believes that this condition is a comorbidity of physical and spiritual factors. We propose that the core pathogenesis of this disease lies in the "loss of form and essence, impairment of spirit, and depression of the mind, "while the primary treatment principle involves "nourishing form and regulating spirit." As a result, a new diagnosis and treatment approach of "four-dimensional integration" is summarized in this study. The disease is treated through the four dimensions of shape, body, spirit, and emotion. Traditional Chinese medicine is used to adjust the shape in cases where the physical form is damaged. For individuals with depression of heart and liver qi, the treatment focuses on soothing the heart and smoothing liver qi, and the modified Wangyou Powder and Xuanzhi Decoction is used. In cases where the heart and kidney function are compromised, the treatment involves nourishing both the heart and kidney while restoring interaction between the heart and the kidney, and modified Jihuo Yansi Elixir is used. To reduce the sensitivity of the glans penis, the patient′s body is washed with a traditional Chinese medicine formula, and a delicate fumigation formula is decocted for external washing. For those who are not in tune with their god, psychological counseling can be used to regulate their spirit and advocate "self-partner" and psychotherapy. If there are issues with intimacy, partners should focus on cooperating during foreplay, sexual intercourse, and post-coital interactions. Overall, the treatment aims to harmonize the body and spirit, addressing both physical and psychological factors through a comprehensive, multi-dimensional approach. This method provides new perspectives and ideas for the clinical diagnosis and treatment of this condition.

Diabetes mellitus is a complex metabolic disease involving multiple organ systems in the body.In recent years,its global incidence rate has increased year by year.In China,the blood glucose control of patients with diabetes mellitus who receive oral hypogly-cemic agents or insulin treatment remains poor.In the early disease stages,exercise is important to control blood glucose levels.Recently,many studies have found that the occurrence of type 2 diabetes mellitus was related to declining levels of irisin,an exercise-related muscle factor.Furthermore,studies have found that irisin improved insulin resistance,promoted the production of pancreatic isletβcells,and affected the body's glucose and lipid metabolism.In addition,its levels were also implicated in the occurrence of various complications,such as diabetic nephropathy and diabetes-related cardiovascular diseases.This article summarizes and analyzes the role of irisin in the occurrence and development of diabetes mellitus and further describes its impact and mechanism on various diabetic complications.

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.

Transcranial electrical stimulation (tES) is a non-invasive neural modulation technique known for its high safety, patient compliance, and portability. It holds promise as a potential non-pharmacological method for analgesia. However, challenges persist in utilizing tES for pain management, including inconsistent research findings and limited understanding of its analgesic mechanisms. Therefore, by summarizing the advances in the analgesic researches employing the 3 primary tES techniques, transcranial direct current stimulation (tDCS), transcranial alternating current stimulation (tACS), and transcranial random noise stimulation (tRNS), we reviewed the analgesic effects on both acute and chronic pain, as well as the neural mechanisms underlying the analgesic effect of each technique. Accumulating evidence suggests that the analgesic effects of tDCS are significant, but studies on analgesic effects of tACS and tRNS remain limited. And the exact mechanisms of pain relief through tES turned out to be not yet well established. Furthermore, we systematically discussed the limitations of analgesia-related studies employing tES techniques across various aspects, involving research design, stimulation protocol formulation, neural response observation, analgesic effect assessment, and safety considerations. To address these limitations and advance clinical translation, we emphasized utilizing promising stimulation techniques and offered practical suggestions for future research endeavors. Specifically, employing numerical simulation of electric field guided by magnetic resonance imaging (MRI) would reduce variability of outcomes due to individual differences in head anatomy. For this purpose, it is advisable to establish standardized head models based on MRI data from the Chinese populations and validate simulated electric field results in tES research to diminish confounding factors concerning anatomy. Meanwhile, novel techniques like multi-site brain stimulation and interferential stimulation (IFS) could broaden the range of stimulation sites in both scope and depth. Multi-site brain stimulation facilitates modulation of entire neural networks, enabling more sophisticated investigations into the complexity of pain. IFS can reach deep brain tissues without invasive surgical procedures, achieving more comprehensive modulation. Regarding neural response observations, establishing a tES-neuroimaging synchronized platform would enable revealing its mechanisms and personalizing protocols based on inter-subject neural response variability detected through recordings. By integrating tES with various neuroimaging techniques, such as functional MRI, electroencephalography (EEG) and magnetoencephalography, into one unified platform, researchers could examine brain activities in baseline before stimulation, dynamic changes in brain activities during stimulation, and sustained brain responses after stimulation. Additionally, collecting finer-grained data on participant characteristics and pain intensity would enhance the sensitivity of future studies. In designing clinical trials to evaluate chronic pain treatments and reporting the results, adopting the six core outcome domain measures recommended by the Initiative on Methods, Measurement, and Pain Assessment in Clinical Trials (IMMPACT) could prove beneficial. Lastly, safety considerations can never be overemphasized in future tES studies especially when combining tES with MRI and EEG techniques. These efforts may help to broaden the research scope, reconcile inconsistencies in findings and elucidate the analgesic mechanisms of tES, thus facilitating the development of pragmatic pain management strategies such as combination therapies and home therapies. Ultimately, these suggestions will maximize the clinical application value of tES in pain treatment to achieve pain relief for patients.

Bladder cancer is one of the most prevalent cancers worldwide, with a high rate of recurrence and mortality, which is the ninth most common malignancy globally. Cystoscopy remains the gold standard for clinical bladder cancer diagnosis, but its invasive nature can lead to bacterial infection and inflammation. Urine cytology is a non-invasive and simple diagnostic method, but it has lower sensitivity in detecting low-grade bladder cancer and may yield false negative results. Therefore, identifying ideal diagnostic and prognostic biomarkers is crucial for accurate diagnosis and effective treatment of bladder cancer. Aptamers, characterized as single-stranded DNA or RNA with unique three-dimensional conformations, exhibit the ability to identify various targets, ranging from small molecules to tumor cells. Aptamers, also known as chemical antibodies, are generated by systematic evolution of ligands by exponential enrichment (SELEX) process and can function similarly to traditional antibodies. They hold numerous advantages over antibodies, such as ease of modification, low immunogenicity, and rapid tissue penetration and cell internalization due to their nucleic acid molecule structure. Since their discovery in the 1990s, aptamers have been widely used in biochemical analysis, disease detection, new drug research and other fields. This article provides an overview of aptamer selection and characterization for bladder cancer, discussing the research advancements involving aptamers in diagnosing and treating this disease. It covers aptamers obtained through different SELEX methods, including protein-SELEX, cell-SELEX, tissue-SELEX, and aptamers from other cancer SELEX; the detection in blood samples and urine samples; and application in targeted therapy and immunotherapy for bladder cancer. Currently, several aptamers capable of identifying bladder cancer have been generated, serving as molecular probes that have played a pivotal role in the early detection and treatment of bladder cancer. Bladder cancer perfusion therapy is well-suited for aptamer drug therapy because it does not require internal circulation, making it a suitable clinical indication for aptamer drug development. In addition, bladder cancer can be detected and monitored by collecting urine samples from patients, making it a preferred disease for clinical conversion of aptamers. While aptamers show promise, there is still much room for development compared with antibodies. There are still many clinically applied cancer biomarkers without corresponding aptamers, and more aptamers targeting different biomarkers should be selected and optimized to improve the sensitivity and accuracy for cancer detection and therapy. The field of aptamers urgently needs successful commercial products to promote its development, and home rapid detection/monitoring, imaging and targeted therapy of bladder cancer by infusion may be the breakthrough point for future application of aptamers.

Crossmodal transfer is the ability to apply the knowledge acquired in one sensory modality to another. Researches on crossmodal transfer investigate how the brain represents information from different sensory modalities, and provide new insights to improve cognitive processing efficiency and reduce repeated learning. To clarify the characteristics and mechanism of crossmodal transfer, this article first introduced the crossmodal transfer effect in different field of research, such as object recognition, category learning, and time perception. After that, the theoretical researches on the representation type of crossmodal transfer were reviewed, mainly including multisensory theory and multisensory mental imagery theory as well as the supportive and opposite findings. The research progresses on the neural mechanism of crossmodal transfer using ERP and fMRI techniques were introduced, mainly including metamodal theory, and multisensory reverse hierarchy theory as well as the supportive and opposite findings. The objective and subjective factors which influenced crossmodal transfer effect were sorted out, in which we suggested that the modality dominance phenomenon supports the metamodal theory, while other factors such as sensory experience, age, setting of learning tasks and stimulus features support theories such as the multisensory hypothesis. Finally, we described the potential applications of the current research findings on crossmodal transfer and pointed out future research questions in this field.

Pharmacokinetics of traditional Chinese medicine(TCM)is a discipline that adopts pharmacokinetic research methods and techniques under the guidance of TCM theories to elucidate the dynamic changes in the absorption,distribution,metabolism and excretion of active ingredients,active sites,single-flavour Chinese medicinal and compounded formulas of TCM in vivo.However,the sources and components of TCM are complex,and the pharmacodynamic substances and mechanisms of action of the majority of TCM are not yet clear,so the pharmacokinetic study of TCM is later than that of chemical medicines,and is far more complex than that of chemical medicines,and its development also confronts with challenges.The pharmacokinetic study of TCM originated in the 1950s and has experienced more than 70 years of development from the initial in vivo study of a single active ingredient,to the pharmacokinetic and pharmacodynamic study of active ingredients,to the pharmacokinetic study of compound and multi-component of Chinese medicine.In recent years,with the help of advanced extraction,separation and analysis technologies,gene-editing animals and cell models,multi-omics technologies,protein purification and structure analysis technologies,and artificial intelligence,etc.,the pharmacokinetics of TCM has been substantially applied in revealing and elucidating the pharmacodynamic substances and mechanisms of action of Chinese medicines,research and development of new drugs of TCM,scientific and technological upgrading of large varieties of Chinese patent medicines,as well as guiding the rational use of medicines in clinics.Pharmacokinetic studies of TCM have made remarkable breakthroughs and significant development in theory,methodology,technology and application.In this paper,the history of the development of pharmacokinetics of TCM and the progress of cutting-edge research was reviewed,with the aim of providing ideas and references for the pharmacokinetics of TCM and related research.

Objective To establish the energy expenditure(EE)prediction models of health Qigong Wuqinxi based on heart rate combined with accelerometer counts in different body parts,so to provide a reference for monitoring EE of Wuqinxi.Methods Seventy-four healthy college students aged 18-30 were selected as the research objects.They were divided into a skilled group of 39(21 males and 18 females)and a primary group of 35(17 males and 18 females)according to their level of practice,with 55 in the model group and 19 in the validation group.When performing a set of Wuqinxi,all subjects were recorded heart rate(HR),accelerometer counts[the average counts of X-axis,Y-axis,Z-axis and vector magnitude(VM)],and EE-related indicators by wearing the Polar heart rate moni-tor,ActiGraph-GT3X+accelerometers(9 parts:waist,both arms,both wrists,both thighs,and both ankles)and CORTEX Meta Max3B-R2 portable indirect calorimeter.Based on the accurate EE mea-sured by the gas metabolism meter,linear regression models of only HR,only accelerometer counts,or HR combined accelerometer counts were established,and their accuracy was analyzed and com-pared.Results The EE of Wuqinxi was significantly correlated with gender,height,weight,muscle mass,HR-related indicators,and accelerometer counts in different parts(X-axis counts of the waist,VM values of the left thigh and counts of the X-axis and Y-axis,VM values of the right thigh and the Y-axis,Z-axis count value,left ankle VM value and Y-axis count value,right ankle VM value and Y-axis,Z-axis count value)(P<0.05).Moreover,the adjusted R2 of the prediction model of only HR,only accelerometer counts,and the both were 0.582,0.508 and 0.678,respectively(P<0.05).The correlation between the predicted and measured values ranged between 0.706 and 0.817.Accord-ing to the Bland-Altman analysis,for each model,all except one error value fell outside the 95%confidence interval.That is,all models had an excellent fitting effect and high accuracy.Among them,the combined model was of the best prediction effect:EE(kcal)=-20.089+0.279×body weight(kg)+0.243×ΔHR(exercise HR-quiet HR,bpm)+0.001×Right thigh Y-axis count value+0.181×exer-cise HR(bpm)-4.202×gender(male=0,female=1).Conclusion The EE prediction model of Wuqinxi es-tablished on HR combined with accelerometer counts has the best effect and can calculate the EE more accurately.

As a metabolic disease,obesity increases the risk of many chronic metabolic diseases;in fact,it is an epidemic in the 21st cen-tury.Exercise is an important means of controlling and treating obesity.Irisin,a myocyte cytokine,was discovered and reported in 2012;it is regulated by exercise and involved in the browning of adipose tissue.A recent discovery is irisin's ability to improve obesity,which is embodied in its effect on glucose and lipid metabolism.Irisin can induce the browning of white fat;promote glucose homeostasis;resist the damage of fat cells caused by inflammation,oxidative stress,and other factors;inhibit insulin resistance;and improve glucose,lipid metabolism,and obesity.This review addresses the role of irisin in improving glucose levels,lipid metabolism,and obesity,as well its role in regulating exercise.Further,the prospect of future research is discussed.

Objective:To investigate the change of collagen fibers in locally recurrent esophageal squamous cell carcinoma after radical chemoradiotherapy and the discrepancy of adverse effects and survival outcomes among groups with different salvage treatments, provide references for the options of salvage therapy.Methods:Medical records of 137 patients with esophageal squamous cell carcinoma who received radical chemoradiotherapy and had local recurrence admitted to Cancer Center of Renmin Hospital of Wuhan University from January 2015 to September 2022 were retrospectively collected. The expression of collagen fibers in paraffin samples of cases with different recurrence time was determined by Masson staining, and the differences of the average optical density were calculated. According to the salvage treatment after local recurrence, all cases were divided into the salvage surgery group, second-course chemoradiotherapy group and immunochemotherapy group. The differences of survival outcomes and incidence rates of esophageal tracheal fistula, hemorrhage, pericardial effusion, radiation pneumonitis, radiation esophagitis were analyzed among the three groups. The differences of survival rates were analyzed by Kaplan-Meier method and compared by log-rank test among groups.Results:The expression of collagen fibers in recurrent esophageal squamous cell carcinoma was significantly higher than that in primary esophageal squamous cell carcinoma. Collagen fiber expression was gradually down-regulated with the prolongation of recurrence time. The expression of collagen fibers in recurrent cases after 7 years was similar to that of primary esophageal squamous cell carcinoma. The 1-, 2- and 3-year survival rates of patients in the salvage surgery group, the second-course chemoradiotherapy group and the immunochemotherapy group were 47%, 30%, 20%; 50%, 27%, 15% and 72.5%, 50%, 50%, respectively; Immunochemotherapy was more effective in salvage treatment for recurrent esophageal squamous cell carcinoma, but there was no statistical difference.Conclusions:Collagen fibers are abundant in recurrent esophageal squamous cell carcinoma after radical chemoradiotherapy. With prolongation of recurrent interval, the expression of collagen fibers is down-regulated. The survival outcomes of patients in the immunochemotherapy group, salvage surgery group and second-course chemoradiotherapy group were comparable.