As a distinctive resource of Chinese civilization， traditional Chinese medicine （TCM） technology transfer faces significant opportunities under the background of digital and intelligent transformation， while also being constrained by unique challenges such as the complexity of its theoretical system， lengthy industrial chains， and multidimensional policy restrictions， resulting in a "high-value-high-threshold" paradox. At present， TCM technology transfer is deeply trapped in a "threefold reluctance" dilemma， i.e.， unwillingness to transfer， inability to transfer， and lack of capacity to transfer. Specifically， the disconnection between scientific research evaluation systems and market demand leads to low conversion rates of research achievements， unclear ownership and compliance risks suppress innovation incentives， and the absence of professional services intensifies supply-demand mismatches. This article systematically analyzes the specific characteristics of TCM technology transfer and proposes a breakthrough pathway centered on full-chain digital and intelligent transformation. By integrating technologies such as intelligent sorting systems， blockchain-based traceability， and AI diagnostic models， the TCM ecosystem spanning "cultivation-production-service" can be reconstructed. In terms of standardization， promoting the progression from "experience-based data conversion" to "data standardization" and further to "intelligent standardization" is advocated to resolve quality control challenges. For example， a "three-no-one-full" certification system can strengthen quality trust. Policy coordination should focus on optimizing mechanisms for the transformation of scientific and technological achievements， while exploring intellectual property securitization and risk-sharing models to stimulate research momentum. In terms of internationalization， reliance on the Belt and Road Initiative platform to promote the export of geo-authentic medicinal material brands and standards is recommended to build a dual-driven model of "technology plus culture". Looking ahead， through the construction of national-level databases， the cultivation of interdisciplinary talent， and the mutual recognition of international standards， a new paradigm of "scientific intelligent manufacturing" can be formed， providing systematic solutions for the modernization of TCM and global health governance.

Diabetic nephropathy（DN） is a common and severe microvascular complication of diabetes. In recent years， the classical herbal formula Shenqi dihuang decoction has demonstrated unique advantages in the clinical treatment of DN. This article conducts a systematic review of the mechanisms of action and clinical applications of Shenqi dihuang decoction in the treatment of DN. It reveals that the mechanism by which this formula improves DN involves multi-target synergistic regulation. For instance, Shenqi dihuang decoction exerts multiple pharmacological effects by regulating signaling pathways including phosphatidy linostiol 3-kinase/protein kinase B， AMP-activated protein kinase/silent information regulator 1/forkhead box O1， and nuclear factor erythroid 2-related factor 2/heme oxygenase-1 pathways.These effects include regulating glucose and lipid metabolism， inhibiting oxidative stress， reducing inflammation， improving insulin resistance， modulating cell death （apoptosis/autophagy/ferroptosis/pyroptosis）， and preventing renal fibrosis. Existing clinical studies indicate that Shenqi dihuang decoction and its modified formulas， alone or in combination with other therapeutic methods， can significantly improve glucose and lipid metabolism， reduce proteinuria， and delay renal function decline in patients with DN. These effects are superior to those of Western medicines such as irbesartan， valsartan， and empagliflozin， and the treatment demonstrates good safety. Future research should leverage systems biology and artificial intelligence technologies to further elucidate the integrated mechanisms in the treatment of DN by Shenqi dihuang decoction， thereby advancing the precision and standardization of its clinical application.

ObjectiveTo explore the 28-day mortality risk of Klebsiella pneumoniae (KP) bloodstream infections (BSI) and its related influencing factors, thereby providing a scientific basis for the effective control of KP-BSI and improvement of patient prognosis. MethodsFrom January 2018 to December 2024, a retrospective review was conducted on hospitalized patients aged >18 years old treated for KP-BSI at a tertiary hospital in Hangzhou. Logistic and Cox regression analyses were performed to identify the epidemiological characteristics and the risk factors for the 28-day mortality associated with KP-BSI. ResultsA total of 123 patients with KP-BSI were included in this study, comprising 64 cases infected with carbapenem-resistant Klebsiella pneumoniae (CRKP) and 59 cases infected with carbapenem-susceptible Klebsiella pneumoniae (CSKP). Compared with CSKP-BSI, patients with CRKP-BSI more frequently presented with chronic pulmonary disease (χ²=4.29, P=0.038), concomitant infections at other sites (χ²=10.90, P=0.001), and a higher frequency of invasive procedures prior to infection (central venous catheterization, mechanical ventilation, and indwelling urinary catheter), as well as glucocorticoid use, hemodialysis, and blood transfusion (all P<0.05). The 28-day mortality was significantly higher in BSI cases caused by CRKP compared to that caused by CSKP (37.50% vs 5.08%, P<0.001). Cox regression analyses revealed that carbapenem resistance (HR=6.67, 95%CI: 1.48‒30.08, P=0.014) and blood transfusion (HR=3.58, 95%CI: 1.15‒11.19, P=0.028) were risk factors for the 28-day mortality in KP-BSI, while removal of central venous catheters after infection (HR=0.24, 95%CI: 0.08‒0.67, P=0.006) was associated with a reduced risk for the 28-day mortality. ConclusionCarbapenem resistance is associated with mortality outcomes in patients with KP-BSI. Strengthening infection control measures targeting the identified risk factors for CRKP-BSI may improve patient prognosis.

A dielectric barrier discharge ionization source with rapid evaporation and self-aspiration sampling(RE-SADBDI)was developed,integrating a rapid evaporation(RE)module and a dielectric barrier discharge ionization(DBDI)module.The sample was introduced into the RE module via a sampling swab and rapidly vaporized within it.The sealed design of the ionization source could enable the sample to be self-aspirated into the ionization region without the need of additional inert gas.All vaporized sample was efficiently directed into the ionization region due to the relatively enclosed environment for sample transfer and ionization,resulting in improved transfer and ionization efficiencies.Experimental results showed that the limit of detection(LOD)under ion isolation mode reached 0.05 ng/mL(caffeine),with a relative standard deviation(RSD)of 6.9%.Furthermore,when coupled with a miniaturized linear ion trap mass spectrometer,the source enabled real-time analysis of various sample types.The developed RE-SADBDI source was suitable for on-site analysis with miniaturized mass spectrometers.

The traditional detection methods for monitoring the biomass,protein,chlorophyll content and other key indicators in the growth of chlorella have some problems,including complicated operation,slow detection speed and difficult large-scale application.In this study,a fast and efficient monitoring method for the key indicators in the growth of chlorella was established using near infrared spectroscopy and chemometrics.Near-infrared spectroscopy was used to collect near-infrared spectra of chlorella algal fluid at different growth stages,and standard methods were used to detect the biomass,protein and chlorophyll contents of corresponding samples.A quantitative analysis model was established based on partial least squares regression(PLSR).To improve the prediction ability of the model,multiplicative scatter correction(MSC)was used to reduce the interference of scattering on the raw spectrum(RS),standard normal variate(SNV)was used to normalize the original spectral data to eliminate differences between samples,continuous wavelet transform(CWT)was used to obtain the key features of spectral data,the first derivative(1st)was used to enhance the differentiation of the original spectral features,and monte carlo-uninformative variable elimination(MC-UVE)and randomization test(RT)were used to screen the valid variables in the wavelength.By evaluating the prediction ability of different models,the quantitative analysis models of chlorella biomass,protein and chlorophyll content were finally determined.The results showed that the model based on 1st combined with RT spectra had better predictive ability for chlorella nutrient content detection,and the root mean square errors of prediction(RMSEP)and coefficients of determination(R2)were 0.041 and 0.933 for biomass,0.012 and 0.973 for protein,and 0.517 and 0.962 for chlorophyll,respectively.This model showed practical application value,and could realize the rapid and accurate detection of chlorella biomass,protein and chlorophyll content at the same time.

In this study,a sensitive lateral flow immunoassay(LFIA)platform based on carbon dots-mesoporous silica nanocomposite(CD-MSNs)fluorescent probes was constructed for high-performance detection of inflammatory marker interleukin-6(IL-6).Green fluorescent carbon dots(CDs)were prepared by hydrothermal method with 3,9-perylenic acid and 3-aminopropyltriethoxysilane(APTES)as raw materials,and highly fluorescent CD-MSNs composites were then constructed by encapsulating the prepared CDs in mesoporous silica nanoparticles(MSNs).Fluorescent probes were prepared by covalent coupling of CD-MSNs with IL-6 antibody.Fluorescent immunochromatographic test strips were constructed by spraying IL-6 capture antibody and goat anti-mouse IgG on nitrocellulose membrane as detection line(T-line)and quality control line(C-line),respectively.The fluorescence immunoassay analyzer was used to quantitatively detect the fluorescence intensity of T-line,and the experimental results showed that the LFIA platform based on this probe had a good linear relationship in IL-6 concentration range of 102-106 pg/mL,and the detection limit was 64 pg/mL,which was two orders of magnitude more sensitive than that of the traditional colloidal gold test strips.This method effectively solved the issue of insufficient sensitivity of traditional LFIA technique,and provided a rapid and highly sensitive detection method for early diagnosis of inflammatory diseases.

Forensic medicine has been designated as a first-level discipline,presenting new opportunities and challenges for the development of forensic medicine.Since the 1980s,the establishment of foren-sic medicine discipline and the cultivation of high-level forensic talents have become hot topics in the development of forensic medicine in China.Since the 13th Five-Year Plan,the forensic team of Shanxi Medical University has been aiming at the forefront,proposing the development goals of"Five First-class"and the discipline development path"Six Major Achievements".It has selected benchmark disci-plines,identified gaps in disciplinary development,unified thoughts,formulated completion timelines,concentrated superior resources,assigned tasks to individuals,and created an"Organized Fill-in-the-Blank Format"forensic medicine discipline construction model with the characteristics of the new era.The construction model of forensic medicine has achieved good results in the goals,discipline frame-work,scientific research,talent cultivation,discipline team and platform construction,forming a rela-tively complete discipline construction and management system,and accumulating valuable experience for the construction of first-level discipline and high-level talent cultivation of forensic medicine.

Objective To explore the correlation between the actual age and the pulp chamber volume(PCV)and pulp dentinal index(PDI)of the right first molars based on cone beam computed tomog-raphy(CBCT)technology,and to construct an accurate and convenient model for age estimation.Methods CBCT image data of 1 857 Han adults(883 males and 974 females)from the Department of Stomatology,Affiliated Hospital of North Sichuan Medical College were collected.The data were di-vided into training and validation sets at a ratio of 8∶2.A total of 1 485 training samples were used to construct the age estimation model,and 372 samples were used to validate the accuracy of the model.The Mimics 21.0 software was used to measure the PCV and calculate the PDI of the right first molars.Their correlations with age and the differences between different sexes and tooth positions were analyzed.Results Both the PCV and the PDI of the first molars showed strong negative correla-tions with the actual age(r values ranged from 0.82 to 0.89).The differences in PCV and PDI be-tween different sexes and tooth positions were statistically significant(P<0.05).The age estimation model based on PDI was superior to that based on PCV.The model based on the PDI values of the two right first molars(y=73.72-44.15 x3-28.27 x4,where x3 and x4 are the PDI values of the right maxil-lary and mandibular first molars,respectively)was the best,with the R2 of 0.79 and the mean abso-lute error of 4.90 years.Conclusion Both PCV and PDI of the first molars are effective indicators for age estimation.The age estimation model based on the PDI is more convenient and accurate than that based on the PCV,providing a more effective method for age estimation in forensic practice.

The FCHO1 protein, encoded by the FCHO1 gene, is a pioneer protein that plays an important role in the initial stage of clathrin-mediated endocytosis. In recent years, it has been found that defects in the FCHO1 gene or abnormal expression levels of the FCHO1 protein are closely related to certain human diseases. This article will review the latest research results of FCHO1 in malignant tumors, immunodeficiency diseases, neurodegenerative diseases of the nervous system, and cardiovascular diseases, providing a theoretical basis for the development of new targets for the diagnosis and treatment of related diseases.

Methods: Seventy-five patients with atlas fracture were included from January 2015 to December 2020. Based on the anatomy of the fracture line, atlas fractures were divided into three types. Each type was divided into two subtypes according to the fracture displacement. Unweighted Cohen kappa coefficients were applied to evaluate the reliability and reproducibility. Results: According to the new classification, 17 cases of type A1, 12 of type A2, seven of type B1, 13 of type B2, 12 of type C1, and 14 of type C2 were identified. The K-values of the interobserver and intraobserver reliability were 0.846 and 0.912, respectively, for the new classification. The K-values of interobserver reliability for types A, B, and C were 0.843, 0.799, and 0.898, respectively. The K-values of intraobserver reliability for types A, B, and C were 0.888, 0.910, and 0.935, respectively. The mean K-values of the interobserver and intraobserver reliability for subtypes were 0.687 and 0.829, respectively. Conclusions The new classification of atlas fractures can cover nearly all atlas fractures. This system is the first to evaluate the severity of fractures based on the C1 articular facet and fracture displacement and strengthen the anatomy ring of the atlas. It is concise, easy to remember, reliable, and reproducible.