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.

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 design and implement a high-precision ear pulse wave physiological signal detection device for human centrifuge training to solve the problems in measurement and calibration of pilot ear pulse wave signal during human centrifuge training.Methods The high-precision ear pulse wave physiological signal detection device was composed of an ear pulse wave acquisition sensor,a signal acquisition and control unit and a host signal processing module.The ear pulse wave acquisition sensor had an ear-clip-like shape and consisted of an outer shell,an inner shell and an elastic steel plate;the signal acquisition and control unit was made up of an power supply module,a constant voltage module for the light source,a signal acquisition module,a master control module and a data transmission module,which had its software developed with an embedded system;the host signal processing module divided the signal processing into 2 phases of signal pre-processing and pulse wave signal monitoring and display.The detection performance of the device was verified by using a physiological electrical signal calibrator to test the ear pulse wave signals detected with the device;the effectiveness and stability of the device were validated by implementing human centrifuge training experiments with different loads.Results The voltage measurement error,amplitude-frequency characteristics and common mode rejection ratio detected by this device were all within the permitted ranges of JJG 760-2003 Verification Regulation for Electro Cardiac Monitor and JJG 954-2019 Verification Regulation of Digital Electroencephalographs;the device was capable of detecting the ear pulse wave signals of pilot during human centrifuge training in real time with little interference from motion and stable signal quality.Conclusion The device can accurately clarify the changes in the amplitude of the pilot's ear pulse wave during human centrifuge training and effectively reflect the changes in the pilot's cerebral blood flow under positive acceleration.[Chinese Medical Equipment Journal,2024,45(9):35-40]

Objective To analyze the hot spots,rules and distribution on safety research of inhalation preparations at home and abroad in the past 20 years,and to summarize the current status of safety and risk control research on inhalation preparations.Methods This reaserch is based on the literature related to the safety and risk control of inhalation preparations in the core collection database of the Web of Science.With the help of Excel 2021 and CiteSpace6.1.R3,visualized processing and analysis were carried out on the annual number of publications,countries,institutions,authors,co-occurrence of keywords,clustering and prominence.Results A total of 365 articles were included,the annual publication number in the field of the safety and risk control of inhalation preparations was less than 30 per year from 2002 to 2018.But since 2019,the number of articles published this year has exceeded 30.Through the analysis of the cooperation network of countries and institutions,the top four countries in terms of publication volume are the United States,the United Kingdom,Germany,and China,and the top three institutions are AstraZeneca,GlaxoSmithKline and Pfizer.Through the analysis of the author cooperation network,the cooperation network between European and American authors was formed earlier,and a certain research group has appeared in 2002.In contrast,a more concentrated cooperation network has been formed in China in 2020.Conclusions In the past 20 years,the research on inhalation preparations has mainly focused on their safety and efficacy,while there are few studies on their risk control.There is a disconnect between safety assessment and risk assessment,and the future focus maybe focused on the adverse reaction assessment and risk management research of inhalation preparations.

Objective:To explore the mechanism of long non-coding RNA RP11-79H23.3 in the development and progression of prostate cancer.Methods:The lnCAR database was used to analyze the RP11-79H23.3 content in prostate cancer tissues and adjacent tissues. RP11-79H23.3 content in prostate cancer cell lines C4-2B, LNCaP, DU-145, and 22Rv1 was detected by real-time fluorescence quantitative polymerase chain reaction (RT-qPCR). Taking 22Rv1 as the research target, colony formation experiments and scratch experiments were used to detect the effects of overexpression of RP11-79H23.3 on the proliferation and migration of 22Rv1 cells. The LncRNome and lncACTdb databases were used to predict the downstream gene and binding sequences of RP11-79H23.3. The Cancer Genome Atlas (TCGA) database was used to analyze the correlation between RP11-79H23.3 and miR-410 expression in prostate cancer tissues. The binding of RP11-79H23.3 and miR-410 was confirmed by dual-luciferase reporter gene experiment. The effect of RP11-79H23.3 on the expression of miR-410 was detected by RT-qPCR. Western blotting was used to detect the effect of RP11-79H23.3 on the expression of phosphatase and tensin homolog/protein kinase B/mammalian target of rapamycin (PTEN/AKT/mTOR) signaling pathway proteins in 22Rv1 cells. The measurement data were expressed as mean ± standard deviation ( ± s), paired sample t-test was used for comparison between two groups, and one-way analysis of variance was used for comparison between multiple groups. Results:Compared with adjacent tissues, RP11-79H23.3 was lowly expressed in prostate cancer tissues ( P<0.01). Compared with normal prostate epithelial cells RWPE-1, RP11-79H23.3 was lowly expressed in prostate cancer cell lines C4-2B, LNCaP, DU-145, and 22Rv1 ( P<0.05). The expression of RP11-79H23.3 in 22Rv1 cells in the control group and RP11-79H23.3 group were 1.02 ± 0.30 and 8.94±1.95, respectively. 22Rv1 cells were successfully overexpressed RP11-79H23.3 compared with the control group ( t=4.04, P<0.01). The number of 22Rv1 cell clones in the control group and RP11-79H23.3 group were 166.10 ± 18.35 and 35.03±6.98, respectively. Overexpression of RP11-79H23.3 could inhibit the proliferation of 22Rv1 cells compared with the control group ( t=6.67, P<0.01). The migration rates of 22Rv1 cells in the control group and RP11-79H23.3 group were (67.40 ± 6.29)% and (26.42 ± 6.24)%, respectively. Overexpression of RP11-79H23.3 could inhibit the migration of 22Rv1 cells compared with the control group ( t=5.71, P<0.01) .Dual-luciferase reporter gene experiment showed that RP11-79H23.3 directly binds to miR-410 ( t=6.20, P<0.01). The expression of miR-410 in 22Rv1 cells in the control group and RP11-79H23.3 group were 6.22±1.39 and 1.05±0.23, respectively. RP11-79H23.3 could inhibit the expression of miR-410 in 22Rv1 cells compared with the control group ( t=3.68, P<0.01). At the same time, RP11-79H23.3 can inhibit the transduction of the PTEN/AKT/mTOR signaling pathway in 22Rv1 cells. Conclusion:RP11-79H23.3 blocks the PTEN/AKT/mTOR signaling pathway by inhibiting the expression of miR-410, thereby inhibiting the proliferation and migration of prostate cancer 22Rv1 cells.

Background::Although overnight fasting is recommended prior to endoscopic retrograde cholangiopancreatography (ERCP), the benefits and safety of high-carbohydrate fluid diet (CFD) intake 2 h before ERCP remain unclear. This study aimed to analyze whether high-CFD intake 2 h before ERCP can be safe and accelerate patients’ recovery.Methods::This prospective, multicenter, randomized controlled trial involved 15 tertiary ERCP centers. A total of 1330 patients were randomized into CFD group ( n = 665) and fasting group ( n = 665). The CFD group received 400 mL of maltodextrin orally 2 h before ERCP, while the control group abstained from food/water overnight (>6 h) before ERCP. All ERCP procedures were performed using deep sedation with intravenous propofol. The investigators were blinded but not the patients. The primary outcomes included postoperative fatigue and abdominal pain score, and the secondary outcomes included complications and changes in metabolic indicators. The outcomes were analyzed according to a modified intention-to-treat principle. Results::The post-ERCP fatigue scores were significantly lower at 4 h (4.1 ± 2.6 vs. 4.8 ± 2.8, t = 4.23, P <0.001) and 20 h (2.4 ± 2.1 vs. 3.4 ± 2.4, t= 7.94, P <0.001) in the CFD group, with least-squares mean differences of 0.48 (95% confidence interval [CI]: 0.26–0.71, P <0.001) and 0.76 (95% CI: 0.57–0.95, P <0.001), respectively. The 4-h pain scores (2.1 ± 1.7 vs. 2.2 ± 1.7, t = 2.60, P = 0.009, with a least-squares mean difference of 0.21 [95% CI: 0.05–0.37]) and positive urine ketone levels (7.7% [39/509] vs. 15.4% [82/533], χ2 = 15.13, P <0.001) were lower in the CFD group. The CFD group had significantly less cholangitis (2.1% [13/634] vs. 4.0% [26/658], χ2 = 3.99, P = 0.046) but not pancreatitis (5.5% [35/634] vs. 6.5% [43/658], χ2 = 0.59, P = 0.444). Subgroup analysis revealed that CFD reduced the incidence of complications in patients with native papilla (odds ratio [OR]: 0.61, 95% CI: 0.39–0.95, P = 0.028) in the multivariable models. Conclusion::Ingesting 400 mL of CFD 2 h before ERCP is safe, with a reduction in post-ERCP fatigue, abdominal pain, and cholangitis during recovery.Trail Registration::ClinicalTrials.gov, No. NCT03075280.