Objective To understand the epidemiological characteristics of a clustered outbreak of severe fever with thrombocytopenia syndrome(SFTS)as well as the ecological tick monitoring results for Zibo City, and to provide a scientific basis for formulating prevention and control strategies. Methods A case definition was cited before epidemic investigations were performed. Epidemiological investigations were performed on the index cases and their close contacts. Blood samples were collected from cases and close contacts, and quantitative real-time RT-PCR was used to detect SFTS virus(SFTSV)nucleic acid sequences. A retrospective cohort study was conducted to analyze risk factors and develop prevention and control strategies. Results This clustered outbreak involved two index cases and six close contacts with no deaths. Case A exhibited symptom onset on July 26. SFTS was confirmed on August 2. Case B exhibited symptom onset on August 1, and SFTS was confirmed on August 3. Patient B reported a recent history of tick bites. In both index cases, the incubation period for SFTS was inferred to be 7-12 days. The time interval from symptom onset to clinical diagnosis in the two cases ranged from 2-8 days, with an average period of 5 days. SFTSV nucleic acid test result were positive for both patients, whereas all six close contacts tested negative. All captured ticks tested negative for SFTSV using quantitative real-time RT-PCR. The densities of parasitic and free-living ticks in the emergency monitoring area around the cases were 12.60 and 4.65 ticks/(flag·100 m). In 2024, the average parasitic tick index and free-living tick density index were 4.21 and 2.43 ticks/(flag ·100 m)in Yiyuan County, respectively. Conclusions No evidence of human-to-human transmission was found in the assessed SFTS clusters. The infections were likely acquired through tick bites during fieldwork, and the risk of a subsequent outbreak spreading was low.

Process analytical technology(PAT) is a key means for digital transformation and upgrading of the traditional Chinese medicine(TCM) manufacturing process, serving as an important guarantee for consistent and controllable TCM product quality. Near-infrared(NIR) spectroscopy has become the core technology for measuring the TCM manufacturing process. By incorporating NIR spectroscopy into PAT and starting from the construction of a smart platform for the TCM manufacturing process, this paper systematically described the development history and innovative application of the combination of NIR spectroscopy with chemometrics in measuring the TCM manufacturing process by the research team over the past two decades. Additionally, it explored the application of a validation method based on accuracy profile(AP) in the practice of NIR spectroscopy. Furthermore, the software development progress driven by NIR spectroscopy supported by modeling technology was analyzed, and the prospect of integrating NIR spectroscopy in smart factory control platforms was exemplified with the construction practices of related platforms. By integrating with the smart platform, NIR spectroscopy could improve production efficiency and guarantee product quality. Finally, the prospect of the smart platform application in measuring the TCM manufacturing process was projected. It is believed that the software development for NIR spectroscopy and the smart manufacturing platform will provide strong technical support for TCM digitalization and industrialization.
Spectroscopy, Near-Infrared/methods* ; Drugs, Chinese Herbal/analysis* ; Software ; Medicine, Chinese Traditional ; Quality Control

This study explored the potential therapeutic targets and mechanisms of Danggui Shaoyao San(DSS) in the prevention and treatment of Alzheimer's disease(AD) through transcriptomics and metabolomics, combined with animal experiments. Fifty male C57BL/6J mice, aged seven weeks, were randomly divided into the following five groups: control, model, positive drug, low-dose DSS, and high-dose DSS groups. After the intervention, the Morris water maze was used to assess learning and memory abilities of mice, and Nissl staining and hematoxylin-eosin(HE) staining were performed to observe pathological changes in the hippocampal tissue. Transcriptomics and metabolomics were employed to sequence brain tissue and identify differential metabolites, analyzing key genes and metabolites related to disease progression. Reverse transcription-quantitative polymerase chain reaction(RT-qPCR) was employed to validate the expression of key genes. The Morris water maze results indicated that DSS significantly improved learning and cognitive function in scopolamine(SCOP)-induced model mice, with the high-dose DSS group showing the best results. Pathological staining showed that DSS effectively reduced hippocampal neuronal damage, increased Nissl body numbers, and reduced nuclear pyknosis and neuronal loss. Transcriptomics identified seven key genes, including neurexin 1(Nrxn1) and sodium voltage-gated channel α subunit 1(Scn1a), and metabolomics revealed 113 differential metabolites, all of which were closely associated with synaptic function, oxidative stress, and metabolic regulation. RT-qPCR experiments confirmed that the expression of these seven key genes was consistent with the transcriptomics results. This study suggests that DSS significantly improves learning and memory in SCOP model mice and alleviates hippocampal neuronal pathological damage. The mechanisms likely involve the modulation of synaptic function, reduction of oxidative stress, and metabolic balance, with these seven key genes serving as important targets for DSS in the treatment of AD.
Animals ; Alzheimer Disease/genetics* ; Male ; Drugs, Chinese Herbal/administration & dosage* ; Mice ; Mice, Inbred C57BL ; Metabolomics ; Transcriptome/drug effects* ; Maze Learning/drug effects* ; Hippocampus/metabolism* ; Humans ; Disease Models, Animal ; Memory/drug effects*

The quality of traditional Chinese medicine(TCM) is a critical foundation for ensuring the stability of its efficacy, as well as the safety and effectiveness of its clinical use. The identification of critical quality attributes(CQAs) is one of the core components of TCM preparation quality control. This study focuses on Jianwei Xiaoshi Tablets and explores their CQAs related to property and flavor from the perspective of taste receptor proteins. Three taste receptor proteins, T1R2, T1R3, and TRPV1, were selected, and a biosensor based on high-electron-mobility transistor(HEMT) was constructed to detect the interactions between Jianwei Xiaoshi Tablets and taste receptor proteins. Simultaneously, liquid chromatography-mass spectrometry(LC-MS) technology was used to analyze the chemical composition of Jianwei Xiaoshi Tablets. In examining the interaction strength, the results indicated that the interaction between Jianwei Xiaoshi Tablets and TRPV1 protein was the strongest, followed by T1R3, with the interaction with T1R2 being relatively weaker. By combining biosensing technology with LC-MS, 16 chemical components were identified from Jianwei Xiaoshi Tablets, among which six were selected as CQAs for sweetness and seven for pungency. Further validation experiments demonstrated that CQAs such as hesperidin and hesperetin had strong interactions with their corresponding taste receptor proteins. Through the combined use of multiple technological approaches, this study successfully determined the property and flavor-related CQAs of Jianwei Xiaoshi Tablets. It provides novel ideas and approach for the identification of CQAs in TCM preparations and offers comprehensive theoretical support for TCM quality control, contributing to the improvement and development of TCM preparation quality control systems.
Drugs, Chinese Herbal/chemistry* ; Biosensing Techniques/methods* ; TRPV Cation Channels/chemistry* ; Tablets/chemistry* ; Receptors, G-Protein-Coupled/genetics* ; Quality Control ; Taste ; Humans ; Mass Spectrometry

This study established the HPLC fingerprints, characteristic chromatograms, and a multi-component content determination method for Bidens bipinnata and B. biternata. The chemical pattern recognition analysis was then employed to clarify the characteristic indexes of quality differences between the two original plants of Bidentis Herba, providing a reference for establishing the quality standards of Bidentis Herba. HPLC was launched on an Agilent Poroshell 120 EC-C_(18) chromatographic column(4.6 mm×250 mm, 4 μm) by gradient elution with a mobile phase of 0.1% aqueous phosphoric acid-acetonitrile at a flow rate of 0.7 mL·min~(-1), detection wavelength of 270 nm, column temperature of 25 ℃, and an injection volume of 5 μL. The similarity between the fingerprints of 18 batches of Bidentis Herba samples and the common pattern(R) ranged from 0.572 to 0.933. A total of 23 chromatographic peaks were calibrated. Through comparison with the reference substances, six components(neochlorogenic acid, chlorogenic acid, isochlorogenic acid A, isochlorogenic acid B, rutin, and hyperoside) were identified and subjected to quantitative analysis. The characteristic fingerprints of B. bipinnata and B. biternata were calibrated with 20 and 17 characteristic peaks, respectively. Among them, peaks 8, 9, 22, and 23 were the characteristic peaks of B. bipinnata, and peak 7 was the characteristic peak of B. biternata, which can be used to distinguish the two original plants of Bidentis Herba. The relative standard deviation of the content of the above-mentioned six components ranged from 36% to 123%. The cluster analysis, principal component analysis, and orthogonal partial least squares-discriminant analysis(OPLS-DA) classified the 18 batches of Bidentis Herba samples into two categories. Additionally, through the analysis of variable importance in projection(VIP) under OPLS-DA, three characteristic indexes, rutin, isochlorogenic acid A, and isochlorogenic acid B, were identified. The analytical method established in this study can comprehensively evaluate the consistency of Bidentis Herba samples derived from different original plants, specifically identify the differential components between them, and effectively distinguish the two original plants of Bidentis Herba, providing a basis for the differentiation between different original plants and the quality control of Bidentis Herba.
Chromatography, High Pressure Liquid/methods* ; Drugs, Chinese Herbal/chemistry* ; Quality Control ; Bidens/chemistry*

The innate immune response is the first line of defense for the host against viral infections. Targeted degradation of pathogenic microorganisms through autophagy, in conjunction with pattern recognition receptors synergistically inducing the production of interferon (IFN), constitutes an important pathway for the body to resist viral infections. Rubicon, a Run domain Beclin 1-interacting and cysteine-rich domain protein, has an inhibitory effect on autophagy and IFN production. On the one hand, Rubicon, as a component of the phosphoinositide 3-kinase (PI3K) complex, interacts with different domains of vacuolar protein sorting 34 (Vps34), ultraviolet radiation resistance associated gene (UVRAG), guanosine triphosphate (GTP) kinase, and RAS oncogene family member 7 (Rab7) to mediate the inhibition of autophagy maturation; on the other hand, Rubicon inhibits the ubiquitination of nuclear factor κB essential modulator (NEMO) and the dimerization of interferon regulatory factor 3 (IRF3), thereby blocking the signal transduction related to IFN production. Research has revealed that various viruses, such as Kaposi's sarcoma-associated herpesvirus (KSHV), hepatitis B virus (HBV), Sendai virus (SeV), and hepatitis C virus (HCV), achieve innate immune evasion by regulating the expression or function of Rubicon. Rubicon is expected to be a new target for antiviral therapy.
Humans ; Autophagy/immunology* ; Immunity, Innate ; Interferons/immunology* ; Immune Evasion ; Animals ; Virus Diseases/virology* ; Signal Transduction ; Viruses/immunology* ; Intracellular Signaling Peptides and Proteins/immunology* ; Autophagy-Related Proteins

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective To determine the acute effects of blood flow restriction(BFR)running warm-up on Achilles tendon morphology and function in basketball players in order to provide a theoretical basis for optimizing warm-up protocols for military personnel and athletes susceptible to Achilles tendon injuries.Methods Twenty-seven male basketball players were subjected and asked to participate in 3 different running warm-up protocols:low-speed running(LSR),high-speed running(HSR),and BFR combined with LSR(BFR-LSR).The acute changes in Achilles tendon morphology,mechanical properties,and functional performance across the 3 testing sessions were analyzed and compared.Results Immediately after training,both HSR warm-up and BFR-LSR warm-up significantly improved Achilles tendon thickness,blood flow,stiffness,and gastrocnemius maximal voluntary isometric contraction(MVIC)when compared with LSR warm-up(P<0.05).No statistical differences were observed in above indicators between the BFR-LSR and HSR warm-ups(P>0.05).24 hours after training,compared with LSR warm-up,HSR warm-up still significantly improved Achilles tendon thickness,blood flow,stiffness,and gastrocnemius MVIC(P<0.05).Although BFR-LSR warm-up did not show statistically significant differences in these parameters compared to LSR warm-up,it still demonstrated positive trends.Immediately and 24 h after training,no obvious difference were found in jump performance among the 3 warm-up protocols(P>0.05),but,both BFR-LSR and HSR warm-ups exhibited superior performance than LSR warm-up.Conclusion Immediately after training,BFR-LSR warm-up demonstrates comparable effects to the HSR warm-up on improving Achilles tendon morphology and performance,as well as enhancing jump performance.However,its sustained and long-term effects require further investigation.

With the increasing demand for dynamic,real-time and rapid qualitative analysis of chemical composition in areas such as emergency response and space exploration,chip-scale mass spectrometers have attracted significant attention.These devices are expected to drive the integration of mass spectrometry with micro/nano-fabrication and intelligent sensing technologies,fostering profound innovation and breakthroughs in analytical chemistry.As an excellent mass analyzer,the ion trap exhibits numerous advantages,and its miniaturization creates favorable conditions for the high-density integration of miniature mass spectrometers.However,the reduction in ion storage capacity may compromise its sensitivity and dynamic range,rendering the study of ion unidirectional ejection in highly miniaturized ion traps of significant practical importance.In this work,a research was conducted on achieving efficient ion unidirectional ejection while maintaining high mass resolution in the extremely miniature hyperbolic linear ion trap(M-HLIT)with a field radius of 1 mm,and an electric field compensation method was proposed,which combined asymmetric electrode stretching and unbalanced RF voltage to achieve high-precision optimization of the electric field composition.Simulations showed that in an ideal structure,this method achieved 100％unidirectional ejection efficiency with the mass resolution of 518,significantly outperforming traditional asymmetric structure method(365)and unbalanced voltage method(321).Following the introduction of ion ejection slots,further optimization through bidirectional stretching and electrical parameters improved the resolution to 790 while maintaining a unidirectional ejection efficiency of 93％.This method eliminated the requirement for additional excitation voltage,offering an ideal solution for the miniature mass analyzer with high detection performance of chip-level mass spectrometers.

Colorimetric analysis is a detection and quantification method based on observable color changes in response to analytes,which offers significant advantages including visually detectable signals,straightforward operation,rapid response,and low cost.Consequently,it plays a crucial role in a variety of fields.With increasingly diverse and complex application,colorimetric analysis requires continuous improvement in sensitivity,adaptability to diverse detection environments,and complex data handling capabilities.In recent years,the development of artificial intelligence technology,particularly within its core domain of machine learning(ML),has led to significant advancements in colorimetric analysis.The ML-assisted colorimetric analysis enables high-throughput and high-sensitivity detection,alongside automated analysis,thereby providing novel strategies to overcome the inherent limitations.This review categorized machine learning techniques and summarized their application in colorimetric analysis,introducing two fundamental categories of supervised learning,and unsupervised learning based on the division of core learning paradigms.The research progress of ML-assisted colorimetric analysis in the fields of environmental monitoring,biochemical detection,and food safety were summarized.Finally,the current challenges facing by this research area were analyzed and the research prospect of ML-assisted colorimetric analysis was outlined.