Rubi Fructus has a long history of medicinal and edible use in China. It contains chemical components such as terpenes, flavonoids, phenolic acids, fatty acids, and alkaloids, and possesses various pharmacological activities, including antioxidant, anti-inflammatory, hypoglycemic, anti-tumor, anti-osteoporosis, and liver-protective effects. Rubi Fructus is widely applied in medical, health, and food fields. The quality of Rubi Fructus can directly affect the safety and effectiveness of clinical medication. Therefore, this article reviews the research progress on the chemical constituents and pharmacological effects of Rubi Fructus. Based on the concept of traditional Chinese medicine(TCM) quality markers(Q-markers), the article explores the screening and determination of Q-markers for Rubi Fructus from various aspects, including plant kinship, traditional efficacy, medicinal properties, measurability of chemical composition, different processing methods, producing areas, harvesting periods, and planting conditions. The components ellagic acid, kaempferol, quercetin, kaempferol-3-O-rutinoside, rutin, astragalin, tiliroside, and hyperoside are preliminarily proposed as Q-markers for Rubi Fructus, providing a reference for the quality control of Rubi Fructus.
Drugs, Chinese Herbal/pharmacology* ; Humans ; Rubus/chemistry* ; Fruit/chemistry* ; Quality Control ; Animals

Dipsaci Radix is a commonly used Chinese herbal medicine in China, with triterpenoid saponins as the main active components. β-Amyrin synthase, a member of the oxidosqualene cyclase superfamily, plays a crucial role in the biosynthesis of oleanane-type triterpenoid saponins. Asperosaponin Ⅵ is an oleanane-type triterpenoid saponin. To explore the β-amyrin synthase genes involved in the biosynthesis of asperosaponin Ⅵ in Dipsacus asper, this study screened the candidate genes from the transcriptome data of D. asper. Two β-amyrin synthase genes, Da OSC1 and Da OSC2, were identified by phylogenetic analysis and correlation analysis. The coding sequences of Da OSC1 and Da OSC2 were 2 286 bp and 2 295 bp in length, encoding 761 and 764 amino acids,respectively. Multiple sequence alignments showed that Da OSC1 and Da OSC2 had three conserved motifs( DCTAE, QW, and MWCYCR) unique to the oxidosqualene cyclase family. Real-time quantitative PCR results showed that Da OSC1 and Da OSC2 had the highest expression levels in the roots. Compared with normal growth conditions, the low-temperature treatment significantly upregulated the expression of Da OSC1 and Da OSC2. Agrobacterium-mediated transient expression of Da OSC1 and Da OSC2 in Nicotiana benthamiana resulted in the production of β-amyrin, which suggested that Da OSC1 and Da OSC2 were able to catalyze the synthesis of β-amyrin. This study clarified the catalytic functions of two β-amyrin synthases in D. asper, analyzed their expression patterns in different tissue and at low temperatures. The findings provide a foundation for further studying the biosynthetic pathway and regulatory mechanism of asperosaponin Ⅵ in D. asper.
Intramolecular Transferases/chemistry* ; Phylogeny ; Plant Proteins/chemistry* ; Gene Expression Regulation, Plant ; Dipsacaceae/classification* ; Saponins/metabolism* ; Oleanolic Acid/metabolism*

Deep learning method can be used to automatically analyze electrocardiogram (ECG) data and rapidly implement arrhythmia classification, which provides significant clinical value for the early screening of arrhythmias. How to select arrhythmia features effectively under limited abnormal sample supervision is an urgent issue to address. This paper proposed an arrhythmia classification algorithm based on an adaptive multi-feature fusion network. The algorithm extracted RR interval features from ECG signals, employed one-dimensional convolutional neural network (1D-CNN) to extract time-domain deep features, employed Mel frequency cepstral coefficients (MFCC) and two-dimensional convolutional neural network (2D-CNN) to extract frequency-domain deep features. The features were fused using adaptive weighting strategy for arrhythmia classification. The paper used the arrhythmia database jointly developed by the Massachusetts Institute of Technology and Beth Israel Hospital (MIT-BIH) and evaluated the algorithm under the inter-patient paradigm. Experimental results demonstrated that the proposed algorithm achieved an average precision of 75.2%, an average recall of 70.1% and an average F ₁-score of 71.3%, demonstrating high classification accuracy and being able to provide algorithmic support for arrhythmia classification in wearable devices.
Humans ; Arrhythmias, Cardiac/diagnosis* ; Algorithms ; Electrocardiography/methods* ; Neural Networks, Computer ; Signal Processing, Computer-Assisted ; Deep Learning ; Classification Algorithms

OBJECTIVE: To evaluate the efficacy and safety of Shexiang Tongxin Dropping Pill (STDP) in treating stable angina patients with phlegm-heat and blood-stasis syndrome by exercise duration and metabolic equivalents. METHODS: This multicenter, randomized, double-blind, placebo-controlled clinical trial enrolled stable angina patients with phlegm-heat and blood-stasis syndrome from 22 hospitals. They were randomized 1:1 to STDP (35 mg/pill, 6 pills per day) or placebo for 56 days. The primary outcome was the exercise duration and metabolic equivalents (METs) assessed by the standard Bruce exercise treadmill test after 56 days of treatment. The secondary outcomes included the total angina symptom score, Chinese medicine (CM) symptom scores, Seattle Angina Questionnaire (SAQ) scores, changes in ST-T on electrocardiogram and adverse events (AEs). RESULTS: This trial enrolled 309 patients, including 155 and 154 in the STDP and placebo groups, respectively. STDP significantly prolonged exercise duration with an increase of 51.0 s, compared to a decrease of 12.0 s with placebo (change rate: -11.1% vs. 3.2%, P<0.01). The increase in METs was significantly greater in the STDP group than in the placebo group (change: -0.4 vs. 0.0, change rate: -5.0% vs. 0.0%, P<0.01). The improvement of total angina symptom scores (25.0% vs. 0.0%), CM symptom scores (38.7% vs. 11.8%), reduction of nitroglycerin consumption (100.0% vs. 11.3%), and all domains of SAQ, were significantly greater with STDP than placebo (all P<0.01). The changes in Q-T intervals at 28 and 56 days from baseline were similar between the two groups (both P>0.05). Twenty-five participants (16.3%) with STDP and 16 (10.5%) with placebo experienced AEs (P=0.131), with no serious AEs observed. CONCLUSION STDP could improve exercise tolerance in patients with stable angina and phlegm-heat and blood stasis syndrome, with a favorable safety profile. (Registration No. ChiCTR-IPR-15006020).
Humans ; Double-Blind Method ; Drugs, Chinese Herbal/adverse effects* ; Male ; Female ; Middle Aged ; Angina, Stable/physiopathology* ; Aged ; Syndrome ; Treatment Outcome ; Placebos ; Tablets

Type 2 diabetes (T2D) is an independent risk factor for cognitive impairment. The dysregulation of hypoxia inducible factor (HIF) signaling in T2D patients results in impaired adaptive responses to hypoxia, thereby accelerating the progression of complications. However, limited knowledge is available regarding its precise function in diabetes-associated cognitive impairment (DACI). Here, elevated HIF-1α levels were observed in brain endothelial cells (ECs) of db/db mice. Functionally, brain ECs-specific knockdown of H if1 a significantly ameliorated T2D-induced memory loss and neuronal damage. Glycolysis in brain ECs was inhibited in this process, as indicated by RNA-seq, leading to decreased hippocampal lactate production through reduced LDHA expression. Notably, T2D patients showed increased cerebrospinal fluid lactate levels, which were strongly associated with their cognitive dysfunction. Intrahippocampal injection of lactate accelerated cognitive dysfunction and impaired adult hippocampal neurogenesis (AHN) in db/db mice. Conversely, reducing hippocampal lactate levels through the intrahippocampal injection of oxamate delayed the onset of memory deficits. Furthermore, asiatic acid was discovered to protect db/db mice from cognitive impairment by decreasing brain endothelial HIF-1α expression and subsequently reducing hippocampal lactate-induced AHN damage. Overall, this study elucidates the inhibiting role played by endothelial HIF-1α-driven lactate in AHN and highlights a potential tactic of targeting HIF-1α in brain ECs for treating cognitive impairment.

Objective To investigate the distribution and antimicrobial resistance profiles of clinically isolated Haemophilus influenzae and Moraxella catarrhalis in hospitals across China from 2015 to 2021,and provide evidence for rational use of antimicrobial agents.Methods Data of H.influenzae and M.catarrhalis strains isolated from 2015 to 2021 in CHINET program were collected for analysis,and antimicrobial susceptibility testing was performed by disc diffusion method or automated systems according to the uniform protocol of CHINET.The results were interpreted according to the CLSI breakpoints in 2022.Beta-lactamases was detected by using nitrocefin disk.Results From 2015 to 2021,a total of 43 642 strains of Haemophilus species were isolated,accounting for 2.91％of the total clinical isolates and 4.07％of Gram-negative bacteria in CHINET program.Among the 40 437 strains of H.influenzae,66.89％were isolated from children and 33.11％were isolated from adults.More than 90％of the H.influenzae strains were isolated from respiratory tract specimens.The prevalence of β-lactamase was 53.79％in H.influenzae strains.The H.influenzae strains isolated from children showed higher resistance rate than the strains isolated from adults.Overall,779 strains of H.influenzae did not produce β-lactamase but were resistant to ampicillin(BLNAR).Beta-lactamase-producing strains showed significantly higher resistance rates to these antimicrobial agents than the β-lactamase-nonproducing strains.Of the 16 191 M.catarrhalis strains,80.06％were isolated from children and 19.94％isolated from adults.M.catarrhalis strains were mostly susceptible to both amoxicillin-clavulanic acid and cefuroxime,evidenced by resistance rate lower than 2.0％.Conclusions The emergence of antibiotic-resistant H.influenzae due to β-lactamase production poses a challenge for clinical anti-infective treatment.Therefore,it is very important to implement antibiotic resistance surveillance for H.influenzae and guide rational antibiotic use.All local clinical microbiology laboratories should actively improve antibiotic susceptibility testing and strengthen antibiotic resistance surveillance for H.influenzae.

Transformer models have emerged as pivotal tools within the realm of drug discovery, distinguished by their unique architectural features and exceptional performance in managing intricate data landscapes. Leveraging the innate capabilities of transformer architectures to comprehend intricate hierarchical dependencies inherent in sequential data, these models showcase remarkable efficacy across various tasks, including new drug design and drug target identification. The adaptability of pre-trained transformer-based models renders them indispensable assets for driving data-centric advancements in drug discovery, chemistry, and biology, furnishing a robust framework that expedites innovation and discovery within these domains. Beyond their technical prowess, the success of transformer-based models in drug discovery, chemistry, and biology extends to their interdisciplinary potential, seamlessly combining biological, physical, chemical, and pharmacological insights to bridge gaps across diverse disciplines. This integrative approach not only enhances the depth and breadth of research endeavors but also fosters synergistic collaborations and exchange of ideas among disparate fields. In our review, we elucidate the myriad applications of transformers in drug discovery, as well as chemistry and biology, spanning from protein design and protein engineering, to molecular dynamics (MD), drug target identification, transformer-enabled drug virtual screening (VS), drug lead optimization, drug addiction, small data set challenges, chemical and biological image analysis, chemical language understanding, and single cell data. Finally, we conclude the survey by deliberating on promising trends in transformer models within the context of drug discovery and other sciences.

Objective:To observe the efficacy and safety of polatuzumab vedotin(pola)combined with chemotherapy in the treatment of relapsed and refractory diffuse large B-cell lymphoma(R/R DLBCL).Methods:A total of 23 patients with R/R DLBCL treated at the First Affiliated Hospital of Zhejiang University and its Liangzhu Branch from April 2023 to March 2024 were retrospectively collected.All patients were treated with pola combined with chemotherapy regimens such as BR,R-GDP,R-CHOP,or other regimens.Results:All 23 patients were evaluable for efficacy,with 10 achieving complete response(CR),7 partial response(PR),3 stable disease(SD),and 3 progressive disease(PD).The most common adverse events included myelosuppression,fever,and pulmonary infection.No severe adverse events resulted in drug withdrawal.Conclusion:Pola combined with chemotherapy demonstrates promising efficacy and a favorable safety profile in the treatment of R/R DLBCL.

Transformer models have emerged as pivotal tools within the realm of drug discovery,distinguished by their unique architectural features and exceptional performance in managing intricate data landscapes.Leveraging the innate capabilities of transformer architectures to comprehend intricate hierarchical dependencies inherent in sequential data,these models showcase remarkable efficacy across various tasks,including new drug design and drug target identification.The adaptability of pre-trained trans-former-based models renders them indispensable assets for driving data-centric advancements in drug discovery,chemistry,and biology,furnishing a robust framework that expedites innovation and dis-covery within these domains.Beyond their technical prowess,the success of transformer-based models in drug discovery,chemistry,and biology extends to their interdisciplinary potential,seamlessly combining biological,physical,chemical,and pharmacological insights to bridge gaps across diverse disciplines.This integrative approach not only enhances the depth and breadth of research endeavors but also fosters synergistic collaborations and exchange of ideas among disparate fields.In our review,we elucidate the myriad applications of transformers in drug discovery,as well as chemistry and biology,spanning from protein design and protein engineering,to molecular dynamics(MD),drug target iden-tification,transformer-enabled drug virtual screening(VS),drug lead optimization,drug addiction,small data set challenges,chemical and biological image analysis,chemical language understanding,and single cell data.Finally,we conclude the survey by deliberating on promising trends in transformer models within the context of drug discovery and other sciences.

Objective To evaluate the safety and efficacy of valve-in-valve transcatheter mitral valve replacement(ViV-TMVR)in patients with bioprosthetic valve degeneration who are at high surgical risk.Methods This study is a multi-center,retrospective cohort analysis of 20 consecutive patients who underwent transseptal ViV-TMVR using the Edwards SAPIEN 3 transcatheter heart valve(THV).The primary endpoints include technical success and procedural success,both defined according to the Mitral Valve Academic Research Consortium(MVARC)criteria,as well as mortality and functional change assessed based on New York Heart Association(NYHA)classification at 30-days and six months post-procedure.Clinical follow-up assessments are conducted at 30-days and six months.Results From February 2021 to October 2022,a total of 20 patients with symptoms of bioprosthetic valve degeneration were enrolled across nine sites in China.The patients had a mean age of(73.5±5.5)years,with 85.0％being females and 70.0％classified as NYHA class Ⅲ/Ⅳ.The study achieved a 100.0％technical success rate and a 90.0％procedural success rate finally.All patients remained alive during the 30-day follow-up period.However,six months post-intervention,two patients(10.0％)were re-hospitalized due to heart failure,and sadly,one of them(5.0％)died.None of the patients reported any adverse events related to ViV-TMVR during the follow-up period.Notably,there was a significant improvement in NYHA class compared to baseline(P=0.0004)at six-month follow-ups.Conclusions The transseptal ViV-TMVR technique proved to be highly successful and was associated with significant improvement in NYHA class function.These findings strongly suggest that it serves as a safe and efficient treatment alternative for high-risk patients suffering from bioprosthetic valve degeneration.