Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection. Septic shock is the primary cause of mortality in sepsis, with its core pathophysiological mechanism being severe ischemia and hypoxia in critical units—composed of microcirculation and the mitochondria of functional cells—resulting from disruptions in blood flow and oxygen flow following a dysregulated host response. Due to the systemically convergent yet clinically heterogeneous nature of the host response, current understanding and management strategies for hemodynamics remain inconsistent, often leading to inadequate resuscitation or overtreatment. To improve the quality of care, based on a systematic review of the "blood flow-oxygen flow" theory, an expert panel emphasizes reevaluating septic shock from an integrated perspective of blood flow and oxygen flow, and has formulated the Expert Consensus on Blood Flow and Oxygen Delivery Phenotyping and Clinical Management of Septic Shock (2025). The consensus proposes that clinical typing of blood flow-oxygen flow should comprehensively consider cardiac function, vascular tone, oxygen flow utilization status in critical units, and disease trajectory, while optimizing subtype identification by integrating host response phenotypes and artificial intelligence technologies. It advocates establishing a continuous assessment system through multi-site oxygen flow monitoring for organ perfusion, peripheral perfusion monitoring, and critical care ultrasound. Under the framework of the "critical care triangle", the consensus promotes the implementation of individualized, bundled management strategies, providing guidance for multiple management points to restore blood flow-oxygen flow matching, reduce the risk of organ failure, and decrease patient mortality.

This article describes a new species of Genus Xenodaeria Jordan(1932)(Siphonaptera: Ctenophthalmidae), collected from the southern slope of Cangshan mountain in Dali, Yunnan. The new species is similar to Xenodayia telios, Jordan 1932, and X. laxiproceria Wu, Gu et Liu,1996, but more like X. telios. However, it can be distinguished from X. telios and other known species in the genus based on the following characteristics: The movable process of the male gripper is bent finger shaped, with a blunt end and no angular protrusion extending forward; The posterior St. VII in females has a semi-circular deep depression, with blunt rounded ends of the dorsal and ventral lobes, and the dorsal lobes are wider and longer than the ventral lobes. The type specimen was collected on November 2,1994 from the shrubbery at an altitude of approximately 2 450 m in the southern end of Cangshan Mountain in Dali City, Yunnan Province. The host species were Anourosorex squamipes and Crocidura rapax.

The advancement of microbiome technologies has facilitated a growing interest in the interactions between urinary microbiota and urinary stone formation. This article systematically reviews the technological evolution, and the reciprocal mechanism of microbiota involvement in lithogenesis and its clinical significance. It specifically highlights the changes within the urinary microbiota of calcium oxalate stone patients, notably a depletion of Lactobacillus populations and an enrichment of pathogenic taxa such as Enterobacteriaceae. Furthermore, it delineates the mechanisms whereby microbes participate in stone formation through metabolic regulation, physical adhesion, and inflammatory processes. The article also explores the influence exerted by distinct stone types on the structural composition and functional dynamics of the urinary microbiota. Integrated multi-omics analyses offer novel perspectives for unraveling the intricate microbiome-host interaction network. This approach is anticipated to facilitate significant advances in developing precision-focused prophylactic and therapeutic strategies for urinary stones from a microecological standpoint.

The traditional Chinese medicine(TCM) industry is a crucial part of China's pharmaceutical sector and plays a strategic role in ensuring public health and promoting economic and social development. In response to the practical demand for high-quality development of the TCM industry, this paper focused on the bottlenecks encountered during the digital and intelligent transformation of TCM production systems. Specifically, it explored technical strategies and methodologies for constructing the best TCM production mode. An innovative artificial intelligence(AI)-centered technical architecture for TCM production was proposed, focusing on key aspects of production management including process modeling, state evaluation, and decision optimization. Furthermore, a series of critical technologies were developed to realize the best TCM production mode. Finally, a novel AI-driven TCM production mode characterized by a closed-loop system of "measurement-modeling-decision-execution" was presented through engineering case studies. This study is expected to provide a technological pathway for developing new quality productive forces within the TCM industry.
Artificial Intelligence ; Drugs, Chinese Herbal ; Medicine, Chinese Traditional/methods* ; Humans

The extraction process of traditional Chinese medicine(TCM) is an important part in the production and processing of TCM products. The modeling of this process is of great significance for achieving intelligent production. This paper summarizes the modeling methods for the extraction process of TCM, which mainly include mechanism modeling, empirical formula modeling, data-driven modeling, and mixed modeling. Among them, mechanism modeling and data-driven modeling are widely used. Furthermore, this paper suggests that the future research on the modeling of the extraction process of TCM can be carried out from the following five aspects: in-depth research and development of the extraction process of TCM compound prescriptions, complete description of the whole extraction process of TCM, development of methods for accurate determination of the properties of TCM decoction pieces before extraction, development of adaptive self-optimization technology for models, and construction of models based on a new generation of artificial intelligence methods.
Drugs, Chinese Herbal/chemistry* ; Medicine, Chinese Traditional/methods* ; Models, Theoretical ; Artificial Intelligence ; Humans

Trauma is an important cause of death in young- and middle-aged people. Trauma is comprehensive and includes many surgical specialties, and the surgical techniques of these specialties have long been mature. To reduce the mortality and disability rate of trauma patients, it is necessary to improve trauma management. Trauma has attracted attention in China and trauma treatment and care developed rapidly in recent years. To decrease traumatic mortality and disability rates, our team is committed to building an efficient trauma system in Shaanxi province and has successfully developed a trauma limb salvage map to address the high rates of amputation and disability in patients with limb injuries. This article elaborates on the construction experience of a trauma limb salvage map and its application details in Shaanxi province of China.
Humans ; China ; Limb Salvage/methods* ; Wounds and Injuries/surgery* ; Male ; Extremities/injuries* ; Adult ; Amputation, Surgical ; Middle Aged ; Female

The present study employed UPLC-MS/MS to analyze and identify compounds in the raw powder of Tongluo Shenggu capsules. An HPLC method for the determination of vitexin content was established. The analysis of this drug was performed on a 30 ℃ thermostatic Acquity UPLC® BEH C18 (2.1 mm×100 mm,1.7 μm) column, with the mobile phase comprising 0.2% formic acid-methanol flowing at 0.3 mL /min in a gradient elution manner. Mass spectrometry was detected by ESI sources in both positive and negative ion modes for qualitative identification of chemical constituents. 12 flavonoid and 3 stilbenes compounds in the raw powder of Tongluo Shenggu capsules were successfully identified. Additionally, an HPLC method for the determination of vitexin content was established using a XBridge C18 column (4.6 mm × 250 mm, 5 µm) with a mobile phase of 0.05% glacial acetic acid in methanol for gradient elution, at a column temperature of 30 °C, a flow rate of 1.0 mL/min, and an injection volume of 20 μL. The method demonstrated good linearity in the concentration range of 10 µg/mL to 40 µg/mL (R=1.000) with an average recovery rate of 96.7%. The establishment of these methods provides a scientific basis for the quality control and development of the raw powder of Tongluo Shenggu capsules.

Objective: To construct a hypertension risk prediction model for residents aged 18-79 years, so as to provide an assessment tool for early screening and prevention of hypertension in high-risk groups. Methods: The permanent residents aged 18-79 years from 6 townships (streets) in Fangshan District of Beijing Municipality were selected as the study subjects using a multi-stage stratified random sampling method from March to June 2023. Demographic information, lifestyle, body mass index (BMI), blood pressure, fasting blood glucose, and blood lipid were collected through questionnaire survey, physical examination, and laboratory tests. Subjects were randomly divided into training and validation sets at a 7∶3 ratio. The logistic regression model was used to screen the risk factors of hypertension, and a hypertension risk prediction nomogram was constructed. Receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis were used to verify the discrimination, fit, and clinical application value of the model. Results: A total of 4 438 subjects were included, including 2 365 males (53.29%) and 2 073 females (46.71%), with a mean age of (44.99±14.90) years. The prevalence of hypertension was 35.29% (1 566 cases), and the standardized prevalence was 24.74%. The logistic regression model screened out 9 influencing factors of hypertension. The nomogram was established as ln[p/ (1-p)]= -2.873 + 0.935×40-<50 years + 1.463×50-<60 years + 1.908×60-<70 years + 2.346×70-79 years + 0.298×male-0.675×college degree or above + 0.384×smoking + 0.227×drinking + 0.572×overweight + 1.449×obesity + 0.557×heart rate ≥80 beats/min + 0.428×diabetes + 0.484×dyslipidemia. The area under the ROC curve of the validation set was 0.821 (95%CI: 0.798-0.843), and the calibration curve results showed that the calibration curve fitted the actual curve well. Decision curve analysis showed that the threshold probability was in the range of 0.10 to 0.70, and the model had good predictive value and clinical application value. Conclusion The nomogram based on age, gender, educational level, smoking, drinking, body mass index, heart rate, diabetes, and dyslipidemia can be used to predict the risk of hypertension among residents aged 18-79 years.

Background Asthma poses a serious threat to children's growth, development, and mental health, thus there has been an increasing focus on the control of asthma morbidity in children and the assessment of its risk factors. A growing body of research has found that exposure to ambient air pollutants an significatly increase the risk of childhood asthma. Objective To understand the changes of ambient air pollutant concentrations in Nanjing and asthma outpatient visits to Nanjing Children's Hospital, and to quantitatively analyze the effects of exposure to different ambient air pollutants on children's asthma outpatient visits. Methods Daily data of ambient air pollutants fine particulate matter (PM_2.5), inhalable particle (PM₁₀), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), carbon monoxide (CO), ozone (O₃), meteorological factors (air temperature & relative humidity), and outpatient visits due to asthma in the hospital from January 1, 2019 to December 31, 2023 were collected, and a generalized additive model based on quasi poisson distributions was used to quantitatively analyze the short-term effects of ambient air pollutant exposure on outpatient visits due to asthma in the hospital. Results The annual average concentrations of PM_2.5, PM₁₀, SO₂, and NO₂ in Nanjing from 2019 to 2023 did not exceed the national limits. For single-day lagged effects, the single-pollutant model showed that the effects of PM_2.5, PM₁₀, NO₂, and CO on children's asthma outpatient visits were greatest for every 10 units increase at lag0, with excess risk (ER) of 1.39% (95%CI: 0.65%, 2.14%), 1.46% (95%CI: 0.97%, 1.95%), 5.46% (95%CI: 4.36%, 6.57%), and 0.18% (95%CI: 0.11%, 0.26%), respectively, and SO₂ reached the maximum effect at lag1, with an ER of 23.15% (95%CI: 13.57%, 33.53%) for each 10 units increase in concentration. Different pollutants reached their maximum cumulative lag effects at different time. The PM₁₀, PM_2.5, SO₂, NO₂, and CO showed the largest cumulative lag effects at lag01, lag01, lag02, lag02, and lag03, respectively, with ERs of 1.35% (95%CI: 0.77%, 1.92%), 0.96% (95%CI: 0.10%, 1.83%), 28.50% (95%CI: 15.49%, 42.98%), 6.92% (95%CI: 5.53%, 8.33%), and 0.31% (95%CI: 0.20%, 0.42%), respectively. The influences of PM_2.5 and PM₁₀ on outpatient visits due to asthma in the hospital became more pronounced with advancing age, while the associations with NO₂, SO₂, and CO were weakened as children grew older. Conclusion Ambient air pollutants (PM_2.5, PM₁₀, SO₂, NO₂, CO) can increase childhood asthma visits, and different pollutants have varied effects on the number of asthmatic children's visits at different ages.

Immobilized enzyme-based enzyme electrode biosensors, characterized by high sensitivity and efficiency, strong specificity, and compact size, demonstrate broad application prospects in life science research, disease diagnosis and monitoring, etc. Immobilization of enzyme is a critical step in determining the performance (stability, sensitivity, and reproducibility) of the biosensors. Random immobilization (physical adsorption, covalent cross-linking, etc.) can easily bring about problems, such as decreased enzyme activity and relatively unstable immobilization. Whereas, directional immobilization utilizing amino acid residue mutation, affinity peptide fusion, or nucleotide-specific binding to restrict the orientation of the enzymes provides new possibilities to solve the problems caused by random immobilization. In this paper, the principles, advantages and disadvantages and the application progress of enzyme electrode biosensors of different directional immobilization strategies for enzyme molecular sensing elements by specific amino acids (lysine, histidine, cysteine, unnatural amino acid) with functional groups introduced based on site-specific mutation, affinity peptides (gold binding peptides, carbon binding peptides, carbohydrate binding domains) fused through genetic engineering, and specific binding between nucleotides and target enzymes (proteins) were reviewed, and the application fields, advantages and limitations of various immobilized enzyme interface characterization techniques were discussed, hoping to provide theoretical and technical guidance for the creation of high-performance enzyme sensing elements and the manufacture of enzyme electrode sensors.