Taste is a sensation produced by the reaction of substances in the mouth with taste receptor cells， and a normal taste function is essential for our daily life and health. As receivers of taste molecules， taste receptors include sour， bitter， sweet， salty， and umami receptors， which are mainly distributed in the oral cavity， gastrointestinal tract， respiratory tract epithelium and other organs and play a physiological role. Traditional Chinese medicine （TCM） has five flavors （sour， bitter， sweet， pungent， and salty）， which are closely related to the efficacy. Except the pungent flavor and umami taste receptors， the other five taste receptors correspond to the five flavors in the TCM theory， while the correlations between them have not been studied， such as those between bitter receptors and bitter TCM and between sweet receptors and sweet TCM. This article reviews the research reports on taste receptors in recent years. By analyzing the relationships of taste receptors with five flavors of TCM， signaling mechanisms， and diseases based on "receptor-TCM" correlations， this article puts forward the possibility of combining the TCM theory of five flavors with modern biomedical research， providing a reference for the research on "flavors" in TCM and the correlations between TCM and taste receptors.

Taste is a sensation produced by the reaction of substances in the mouth with taste receptor cells， and a normal taste function is essential for our daily life and health. As receivers of taste molecules， taste receptors include sour， bitter， sweet， salty， and umami receptors， which are mainly distributed in the oral cavity， gastrointestinal tract， respiratory tract epithelium and other organs and play a physiological role. Traditional Chinese medicine （TCM） has five flavors （sour， bitter， sweet， pungent， and salty）， which are closely related to the efficacy. Except the pungent flavor and umami taste receptors， the other five taste receptors correspond to the five flavors in the TCM theory， while the correlations between them have not been studied， such as those between bitter receptors and bitter TCM and between sweet receptors and sweet TCM. This article reviews the research reports on taste receptors in recent years. By analyzing the relationships of taste receptors with five flavors of TCM， signaling mechanisms， and diseases based on "receptor-TCM" correlations， this article puts forward the possibility of combining the TCM theory of five flavors with modern biomedical research， providing a reference for the research on "flavors" in TCM and the correlations between TCM and taste receptors.

ObjectiveTo establish fingerprint profiles and a quantitative determination method for Lycii Cortex， providing a scientific basis for the formulation of quality standards for Lycii Cortex and its roasted products. MethodsHigh performance liquid chromatography（HPLC） was developed for the quantitative method for determining kukoamine B in Lycii Cortex and its roasted products on an Alphasil XD-C₁₈ CH column（4.6 mm×250 mm， 5 μm）. HPLC fingerprint profiles were established for 10 batches of Lycii Cortex and its roasted products， and ultra-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS） was used to identify the common peaks based on reference standards， literature and MS information. Quality evaluation indicators included yield of decoction pieces， appearance properties， content of kukoamine B， and fingerprint profiles. The temperature and time of the roasting process were investigated to select the optimal preparation process， which was then verified. Additionally， chemical pattern recognition was combined to assess the differences in the chemical composition of Lycii Cortex before and after roasting， as well as among samples from different origins. ResultsQuantitative analysis indicated that the contents of kukoamine B in Lycii Cortex and its roasted products were 0.35%-5.51% and 0.24%-4.15%， respectively. The transfer rate of kukoamine B was 58.6%-78.9% after roasting. The fingerprint profile analysis demonstrated that the method established in this study effectively separated kukoamine B from other components in the samples and distinctly differentiated it from its impurity peak， cis-N-caffeoylputrescine. The HPLC fingerprint profiles of Lycii Cortex and its roasted products showed high similarity（all above 0.95）， with 7 common peaks identified and five common components， including kukoamine B， cis-N-caffeoylputrescine， N-coumaroyl tyramine， feruloyltyramine， and glucosyringic acid， confirmed. Process optimization confirmed that baking at 110 ℃ for 20 min was a stable and feasible method for roasting Lycii Cortex. Principal component analysis and cluster analysis showed that there was little difference in the chemical composition between raw and roasted Lycii Cortex， but the quality of Lycii Cortex from different origins differed greatly. ConclusionThis study successfully established the fingerprint profiles and a quantitative method for the effective component kukoamine B in Lycii Cortex and roasted Lycii Cortex. The qualitative and quantitative analyses clarified that the impact of the roasting process on the chemical composition of Lycii Cortex was less significant than the variations due to its geographical origin. The findings of this study offer a reference for the development of quality evaluation methods and the establishment of quality standards for Lycii Cortex and its processed products.

The Maillard reaction is a complex process in which amine compounds such as amino acids， peptides， and proteins undergo condensation， polymerization， and other reactions with carbonyl compounds such as reducing sugars， ketones， and aldehydes at room temperature or under heating conditions， ultimately producing substances such as melanoidins and aromatic compounds. The processing of traditional Chinese medicine（TCM） often involves heating and the addition of auxiliary materials， providing complete conditions for the occurrence of the Maillard reaction. The Maillard reaction is affected by various factors such as temperature， pH， moisture， substrate， reaction time and pressure， the progress of the reaction also affected by different processing technologies of TCM and the addition of different excipients. The Maillard reaction involves multiple substances， most of which have significant physiological activity or toxicity， affecting the efficacy and pharmacological effects of TCM. It can also produce various flavor substances and browning products that change the flavor and color of TCM. The Maillard reaction mechanism， influencing factors， related components， and the impact of Maillard reaction on various aspects of TCM processing are reviewed from multiple perspectives in this article， providing reference for the further improvement of processing mechanism and quality control of TCM.

OBJECTIVE To provide a reference for the quality control of Hypericum perforatum. METHODS High- performance liquid chromatography （HPLC） was used to establish fingerprints for 20 batches of H. perforatum and determine the contents of its main components： chlorogenic acid， rutin， hyperin， isoquercitrin， avicularin， quercitrin and quercetin. Cluster analysis was conducted using SPSS 26.0 software. The chromaticity values （luminance value L*， red-green value a*， and yellow- blue value b*） of H. perforatum powder were measured using electronic eye. A prediction model for the contents of seven components in H. perforatum based on its appearance chromaticity values was established using machine learning algorithms. The predictive performance of the models was evaluated using root-mean-square-error （RMSE）. RESULTS A total of 16 common peaks were calibrated in the fingerprints of 20 batches of H. perforatum， and 9 peaks were identified， which were chlorogenic acid， rutin， hyperin， isoquercitrin， avicularin， quercitrin， quercetin， hypericin and hyperforin； the similarities of the 20 batches of samples and reference fingerprint ranged from 0.889-0.987. The contents of chlorogenic acid， rutin， hyperin， isoquercitrin， avicularin， quercitrin and quercetin were 0.025%-0.166%， 0.048%-0.339%， 0.082%-0.419%， 0.017%-0.209%， 0.011%-0.134%， 0.020%-0.135%， 0.041%-0.235%， respectively. Cluster analysis results showed that 18 batches of qualified H. perforatum were grouped into three categories， when the Euclidean distance was set to 1.4. L* of the 20 batches of H. perforatum ranged from 62.814 to 75.668， a* ranged from 1.409 to 3.490， and b* ranged from 25.249 to 30.759. RMSE of three prediction models， namely XGBoost， LightGBM， and AdaBoost， ranged from 0.008 to 0.070， indicating good fitting performance. XGBoost model predicted the contents of the other six components with high accuracy， except for rutin. CONCLUSIONS The established fingerprints and content determination methods are accurate， reproducible， and reliable. The content prediction model based on appearance chromaticity values， combined with machine learning algorithms， can be used for the quality control of H. perforatum.

ObjectiveTransfer RNA-derived fragments (tRFs) are a recently characterized and rapidly expanding class of small non-coding RNAs, typically ranging from 13 to 50 nucleotides in length. They are derived from mature or precursor tRNA molecules through specific cleavage events and have been implicated in a wide range of cellular processes. Increasing evidence indicates that tRFs play important regulatory roles in gene expression, primarily by interacting with target messenger RNAs (mRNAs) to induce transcript degradation, in a manner partially analogous to microRNAs (miRNAs). However, despite their emerging biological relevance and potential roles in disease mechanisms, there remains a significant lack of computational tools capable of systematically predicting the interaction landscape between tRFs and their target mRNAs. Existing databases often rely on limited interaction features and lack the flexibility to accommodate novel or user-defined tRF sequences. The primary goal of this study was to develop a machine learning based prediction algorithm that enables high-throughput, accurate identification of tRF:mRNA binding events, thereby facilitating the functional analysis of tRF regulatory networks. MethodsWe began by assembling a manually curated dataset of 38 687 experimentally verified tRF:mRNA interaction pairs and extracting seven biologically informed features for each pair: (1) AU content of the binding site, (2) site pairing status, (3) binding region location, (4) number of binding sites per mRNA, (5) length of the longest consecutive complementary stretch, (6) total binding region length, and (7) seed sequence complementarity. Using this dataset and feature set, we trained 4 distinct machine learning classifiers—logistic regression, random forest, decision tree, and a multilayer perceptron (MLP)—to compare their ability to discriminate true interactions from non-interactions. Each model’s performance was evaluated using overall accuracy, receiver operating characteristic (ROC) curves, and the corresponding area under the ROC curve (AUC). The MLP consistently achieved the highest AUC among the four, and was therefore selected as the backbone of our prediction framework, which we named tRF Prospect. For biological validation, we retrieved 3 high-throughput RNA-seq datasets from the gene expression omnibus (GEO) in which individual tRFs were overexpressed: AS-tDR-007333 (GSE184690), tRF-3004b (GSE197091), and tRF-20-S998LO9D (GSE208381). Differential expression analysis of each dataset identified genes downregulated upon tRF overexpression, which we designated as putative targets. We then compared the predictions generated by tRF Prospect against those from three established tools—tRFTar, tRForest, and tRFTarget—by quantifying the number of predicted targets for each tRF and assessing concordance with the experimentally derived gene sets. ResultsThe proposed algorithm achieved high predictive accuracy, with an AUC of 0.934. Functional validation was conducted using transcriptome-wide RNA-seq datasets from cells overexpressing specific tRFs, confirming the model’s ability to accurately predict biologically relevant downregulation of mRNA targets. When benchmarked against established tools such as tRFTar, tRForest, and tRFTarget, tRF Prospect consistently demonstrated superior performance, both in terms of predictive precision and sensitivity, as well as in identifying a higher number of true-positive interactions. Moreover, unlike static databases that are limited to precomputed results, tRF Prospect supports real-time prediction for any user-defined tRF sequence, enhancing its applicability in exploratory and hypothesis-driven research. ConclusionThis study introduces tRF Prospect as a powerful and flexible computational tool for investigating tRF:mRNA interactions. By leveraging the predictive strength of deep learning and incorporating a broad spectrum of interaction-relevant features, it addresses key limitations of existing platforms. Specifically, tRF Prospect: (1) expands the range of detectable tRF and target types; (2) improves prediction accuracy through multilayer perceptron model; and (3) allows for dynamic, user-driven analysis beyond database constraints. Although the current version emphasizes miRNA-like repression mechanisms and faces challenges in accurately capturing 5'UTR-associated binding events, it nonetheless provides a critical foundation for future studies aiming to unravel the complex roles of tRFs in gene regulation, cellular function, and disease pathogenesis.

Background::Cardiovascular disease (CVD) has emerged as the leading cause of death from prostate cancer (PCa) in recent decades, bringing a great disease burden worldwide. Men with preexisting CVD have an increased risk for major adverse cardiovascular events when treated with androgen deprivation therapy (ADT). The present study aimed to explore the prevalence and risk evaluation of CVD among people with newly diagnosed PCa in China.Methods::Clinical data of newly diagnosed PCa patients were retrospectively collected from 34 centers in China from 2010 to 2022 through convenience sampling. CVD was defined as myocardial infarction, arrhythmia, heart failure, stroke, ischemic heart disease, and others. CVD risk was estimated by calculating Framingham risk scores (FRS). Patients were accordingly divided into low-, medium-, and high-risk groups. χ2 or Fisher’s exact test was used for comparison of categorical variables. Results::A total of 4253 patients were enrolled in the present study. A total of 27.0% (1147/4253) of patients had comorbid PCa and CVD, and 7.2% (307/4253) had two or more CVDs. The enrolled population was distributed in six regions of China, and approximately 71.0% (3019/4253) of patients lived in urban areas. With imaging and pathological evaluation, most PCa patients were diagnosed at an advanced stage, with 20.5% (871/4253) locally progressing and 20.5% (871/4253) showing metastasis. Most of them initiated prostatectomy (46.6%, 1983/4253) or regimens involving ADT therapy (45.7%, 1944/4253) for prostate cancer. In the present PCa cohort, 43.1% (1832/4253) of patients had hypertension, and half of them had poorly controlled blood pressure. With FRS stratification, as expected, a higher risk of CVD was related to aging and metabolic disturbance. However, we also found that patients with treatment involving ADT presented an originally higher risk of CVD than those without ADT. This was in accordance with clinical practice, i.e., aged patients or patients at advanced oncological stages were inclined to accept systematic integrative therapy instead of surgery. Among patients who underwent medical castration, only 4.0% (45/1118) received gonadotropin releasing hormone antagonists, in stark contrast to the grim situation of CVD prevalence and risk.Conclusions::PCa patients in China are diagnosed at an advanced stage. A heavy CVD burden was present at the initiation of treatment. Patients who accepted ADT-related therapy showed an original higher risk of CVD, but the awareness of cardiovascular protection was far from sufficient.

Objective To investigate the effects of pulsed radiofrequency(PRF)with intercostal nerve block on analgesia analgesia effect,cognitive function and postoperative delirium in elderly patients undergoing thoracoscopic lung surgery.Methods Ninety elderly patients undergoing thoracoscopic lung surgery in our hospital were randomly divided into the control group(intercostal nerve block with local anesthetic drugs)and the PRF group(PRF with intercostal nerve block).The pain score,analgesic effect,cognitive function,postoperative delirium and neurological dysfunction of the two groups were compared.Results The pain scores of resting and coughing state 48 hours and 72 hours after surgery in the PRF group were significantly lower than those in the control group(P<0.05).The number of analgesic pump compression and proportion of supplemental analgesia within 72 hours after surgery and perioperative sufentanil dosage in the PRF group were significantly less than those in the control group(P<0.05).The cognitive function scores 48 hours and 72 hours after surgery in the PRF group were significantly higher than those in the control group(P<0.05).The incidence of delirium 72 hours after surgery in the PRF group was significantly lower than that in the control group(P<0.05).There was no significant difference in the incidence of intercostal nerve dysfunction 1 month,2 months and 3 months after surgery between the two groups(P>0.05).Conclusion PRF with intercostal nerve block can effectively relieve pain after elderly thoracoscopic lung surgery,reduce postoperative opioid consumption,improve postoperative cognitive function,and decrease postoperative delirium incidence without affecting the intercostal nerve function,which is safe and reliable.

Objective:To summarize the content and effects of exercise interventions for stroke survivors, providing references for medical and nursing personnel in formulating exercise intervention plans for these patients.Methods:Literature on exercise interventions for stroke survivors was searched in databases such as China National Knowledge Infrastructure, Wanfang, VIP, China Biology Medicine disc, Cochrane Library, PubMed, Embase, and Web of Science up to May 1, 2023. Data extraction and summarization were conducted on the included literature.Results:Twenty-two articles were included in the review. The exercise types for stroke survivors primarily involved aerobic and resistance training; the intensity was mainly moderate to high; the frequency was mostly 3-5 times per week, with each session lasting 30-60 minutes; and the duration of interventions ranged from as short as two weeks to as long as one year. Exercise interventions improved stroke survivors' functional mobility, quality of life, cardiopulmonary function, mental state, cognitive function, fatigue, sleep, and compliance to varying degrees.Conclusions:Exercise interventions have achieved positive outcomes in stroke survivors. In the future, medical and nursing personnel can incorporate patient preferences into exercise intervention plans while ensuring patient safety to promote rehabilitation.

Objective:To conduct an overview of systematic reviews on the safety and effectiveness of early mobilization in stroke patients.Methods:Systematic reviews of early mobilization in stroke were electronically searched on China National Knowledge Infrastructure, WanFang Data, VIP, Chinese Biology Medicine, Cochrane Library, PubMed, Web of Science, CINAHL, Embase, and the Joanna Briggs Institute Evidence-Based Health Care Center Database. The search period was from database establishment to May 2023. Two researchers independently conducted literature screening, data extraction, and methodological quality evaluation of the included literature, as well as evidence summary and grading.Results:A total of 10 systematic reviews were included. The methodological quality evaluation showed that one article was of medium quality, two articles were of low quality, and seven articles were of extremely low quality. The evidence quality evaluation indicated that there were three pieces of high-quality evidence, 17 pieces of medium-quality evidence, 21 pieces of low-quality evidence, and 17 pieces of extremely low-quality evidence.Conclusions:Early mobilization is beneficial for improving the daily living ability and limb motor function of stroke patients, reducing the incidence of complications, shortening hospital stay, and enhancing their walking ability in the short term. However, the quality of evidence in the systematic review is relatively low, and further improvement is needed in the research design of early mobilization intervention measures to provide strong support for clinical practice.