ObjectiveTo establish a high-performance liquid chromatography（HPLC） for the quantitative analysis of multiple components in Gegen Qinlian tablets， and to comprehensively evaluate the quality of samples from different manufacturers by integrating chemical pattern recognition and technique for order preference by similarity to ideal solution（TOPSIS）， in order to provide a reference basis for quality evaluation and control of Gegen Qinlian tablets. MethodsHPLC was employed to determine the contents of 10 components in 28 batches of Gegen Qinlian tablets collected from 6 manufacturers， and taking the detection results as variables， SIMCA 14.1 and SPSS 26.0 were employed for cluster analysis（CA）， principal component analysis（PCA）， and orthogonal partial least squares-discriminant analysis（OPLS-DA） to identify key components affecting the quality. Then， TOPSIS analysis was employed to rank the quality of Gegen Qinlian tablets from the 6 manufacturers and establish a comprehensive quality evaluation method. ResultsA quantitative method for Gegen Qinlian tablets was established. After methodological validation， the method was found to be stable and reliable， and could be used for the quantitative analysis of this preparation. The contents of 3′-hydroxy puerarin， puerarin， 3′-methoxy puerarin， daidzein， coptisine hydrochloride， epiberberine， jatrorrhizine hydrochloride， berberine hydrochloride， palmatine hydrochloride and baicalin in 28 batches of samples were 3.58-7.35， 24.88-42.32， 4.20-9.36， 4.33-7.60， 2.52-6.44， 0.93-4.10， 0.58-3.05， 10.68-22.92， 0.82-4.82， 11.73-60.16 mg·g^-1， respectively. Among them， puerarin， berberine hydrochloride and baicalin all met the limit requirements for this preparation specified in the 2025 edition of the Pharmacopoeia of the People's Republic of China. CA and PCA clustered the 28 batches of samples into 5 categories， PCA extracted 2 principal components with a cumulative variance contribution rate of 90.588%， and OPLS-DA screened out 4 differential markers with variable importance in the projection（VIP） values>1.0， namely baicalin， 3′-hydroxy puerarin， coptisine hydrochloride and palmatine hydrochloride， which might be the main components affecting the quality of Gegen Qinlian tablets. TOPSIS analysis showed that the comprehensive score of each evaluation index（C_i） values of different manufacturers were different. Among them， the C_i of manufacturer B was ranked higher， indicating potentially superior quality， while the C_i of manufacturer A was ranked lower， suggesting potentially inferior quality. ConclusionThis study establishes a quantitative method for Gegen Qinlian tablets， and the content uniformity of the same manufacturer is good， while there are differences in the contents of active components among different manufacturers. Through the chemical pattern recognition analysis， it is found that the content differences of Gegen Qinlian tablets may be related to baicalin， 3′-hydroxy puerarin， coptisine hydrochloride and palmatine hydrochloride.

Based on previous research on the promoting effect of dendrobium officinale polysaccharides (DOP) on hair growth, this study aimed to regulate the skin keratin penetration and hair follicle targeting ability of DOP through molecular weight and nano-carriers to enhance its therapeutic effect on androgenetic alopecia (AGA). Three molecular weight polysaccharides, namely high (DOP), medium (MDOP), and low (LDOP), were prepared by mannanase hydrolysis, and the corresponding liposomes (DOP-lip/MDOP-lip/LDOP-lip) were constructed. Studies have shown that DOP liposomes can effectively achieve follicular targeted delivery and promote efficient uptake by human dermal papilla cells through caveolin-mediated pathways. In the testosterone-induced AGA mouse model, LDOP-lip demonstrated excellent therapeutic effects, restoring the number and morphology of hair follicles to nearly normal levels. In summary, DOP liposomes show significant potential for promoting hair follicle repair through precise delivery and efficient cellular uptake.

With the advent of the refractive era of cataract surgery, postoperative residual refractive error has become a key factor affecting visual quality. The accuracy of intraocular lens(IOL)power calculation is affected by multiple factors, including ocular biological parameters, calculation formulas, and lens constants. Currently, the lens constants widely used in clinical practice are mostly based on Western populations, which have a mismatch with the ocular characteristics of the Chinese population, such as shorter axial length and steeper cornea. Therefore, the personalized optimization of the constant has become a research hotspot. This review primarily summarizes the research progress on lens constant optimization in improving the accuracy of IOL power calculation. Currently, there is no consensus on lens constant optimization methods. Single-constant formulas can be optimized through iterative methods, while multi-constant formulas require the combination of linear or nonlinear strategies. Simplified gradient descent and data-driven techniques offer new optimization pathways, but cross-validation is needed to evaluate their performance. Segmented optimization based on axial length, corneal curvature, and anterior chamber depth has shown significant effectiveness in patients with special anatomical structures, effectively reducing postoperative refractive errors in different patient groups, but limitations remain in some extreme cases. The interaction of multiple parameters significantly impacts the predictive accuracy of complex cases. While new-generation formulas integrating multiple parameters or incorporating AI algorithms have improved accuracy, constant optimization still holds value. Currently, the complex relationships between multiple parameters and intraoperative dynamic changes require further in-depth research. Future research, including targeted population optimization studies, the development of real-time monitoring technologies, and innovative IOL designs, may make achieving zero postoperative refractive error a possibility.

ObjectiveTo analyze the epidemiological status, serotypes, and drug resistance characteristics of Vibrio parahaemolyticus in foodborne disease surveillance in Wenzhou from 2016 to 2024, and to provide scientific evidence and data support for the prevention and control of Vibrio parahaemolyticus infections. MethodsA total of 45 980 stool or anal swab samples were collected from patients with vomiting and diarrhea as the main symptoms and a history of consuming suspicious food at medical institutions at all levels in Wenzhou from 2016 to 2024. Isolation, identification, and drug susceptibility testing were performed. Case information was collected through the National Foodborne Disease Surveillance Reporting System. The Cochran-Mantel-Haenszel (CMH) chi-square test was used to analyze the detection rates among groups. ResultsAmong the 45 980 suspected samples, 2 821 were positive for Vibrio parahaemolyticus, with an overall detection rate of 6.14%. A comparison of detection rates across different population groups revealed that the highest rates were found among adults aged 20‒39 (8.57%,1 603/18 697) and among farmers and workers (7.93%, 994/12 537). A comparison of detection rates across different seasons revealed that the detection rates were higher from June to October (5.12%, 9.04%, 15.04%, 14.68%, and 7.80%, respectively), peaking in August. Analyses of the sampling results for suspect foodstuffs revealed that aquatic products and their derivatives accounted for the highest proportion (42.86%). Regarding the setting of food consumption, the household accounted for 44.53% (1 257/2 821). From 2016 to 2020, the predominant serotype was O3:K6 (28.82%, 813/2 821), followed by O10:K4 (28.25%, 797/2 821) and O4:KUT (23.61%, 666/2 821). In terms of drug resistance, the resistance rate to cefazolin was the highest at 84.15% (393/467), and the multi-drug resistance rate was 6.21% (29/467). ConclusionFrom 2016 to 2024, patients with suspected foodborne illnesses in Wenzhou City experienced a peak in Vibrio parahaemolyticus infections during the summer and autumn months (June to October). Young adults aged 20‒39, as well as farmers and manual workers, were the key target groups for the prevention and control of Vibrio parahaemolyticus infections. The predominant serotype of Vibrio parahaemolyticus shifted from O3:K6 to O10:K4. Vibrio parahaemolyticus exhibited a high level of resistance to cefazolin. It is essential to strengthen surveillance of the epidemiological trends of the predominant serotype, monitor changes in the antibiotic resistance of Vibrio parahaemolyticus, enhance health education for key populations, and intensify regulatory inspections of high-risk foods such as aquatic products and their derivatives.

Occupational disease diagnostician (ODD) is the core technology professional who is responsible for occupational disease diagnosis and identification and the main inspection work for occupational medical examination. The implementation of regular assessment management for ODDs is a key component of standardized workforce management, which facilitates dynamic evaluation of professional competence, regulation of medical practice, and assurance of medical safety. Since January 2025, Guangdong Province has implemented regular assessment management for ODDs within its administrative region. The assessment adopts an integrated model consisting of three components including professional competency evaluation, performance appraisal, and professional ethics evaluation, with each assessment cycle lasting three years. ODDs who passed all three components are classified as qualified ODD, whereas those who failed to pass any one of the three components result in an unqualified assessment outcome. In the implementation of ODD regular assessment management, Guangdong Province has emphasized integrating assessment with quality evaluation, strengthening full-cycle supervision of ODDs′ professional conduct, optimizing assessment strategies for special groups of ODDs, and reinforcing the primary management responsibility of medical institutions. Meanwhile, ODDs′ professional competence, service quality, and professional integrity have been continuously promoted by adopting human-computer interactive assessments, information-based assessment management, and "elimination" mechanism.

OBJECTIVE To establish a high-performance liquid chromatography（HPLC） fingerprint and a multi-component content determination method for Ziziphus jujuba stir-fried with Coptis chinensis juice， a characteristic processed product of Longsha Medical School， and to provide a basis for the inheritance and clinical application of this distinctive variety. METHODS HPLC method was employed to establish the fingerprints of 12 batches of Z. jujuba stir-fried with C. chinensis juice. Similarity evaluation and common peak identification were subsequently carried out. Quantitative determination was performed on coclaurine， magnoflorine， coptisine hydrochloride， epiberberine， jatrorrhizine hydrochloride， spinosin， berberine hydrochloride， palmatine hydrochloride， 6"'-feruloylspinosin， and jujuboside A of samples. RESULTS The fingerprint similarities of all 12 batches of samples were higher than 0.960. A total of 17 common peaks were calibrated， among which 9 peaks were identified as coclaurine， magnoflorine， coptisine hydrochloride， epiberberine， jatrorrhizine hydrochloride， spinosin， berberine hydrochloride， palmatine hydrochloride， and 6"'-feruloylspinosin， respectively. The quantitative results showed that the mass fractions of coclaurine， magnoflorine， coptisine hydrochloride， epiberberine， jatrorrhizine hydrochloride， spinosin， berberine hydrochloride， palmatine hydrochloride， 6"'-feruloylspinosin， and jujuboside A in the 12 batches of samples were 0.044-0.091， 0.908-1.698， 0.325-0.549， 0.163-0.287， 0.103-0.172， 0.712-0.952， 1.185-1.843， 0.341-0.598， 0.228-0.405， and 0.050-0.091 mg/g， respectively. CONCLUSIONS The established HPLC fingerprint and multi-component determination method is stable and reliable， and can provide a basis for the quality standard formulation and clinical application of Z. jujuba stir-fried with C. chinensis juice.

Objective: To analyze the characteristics and key risk factors of abnormal blood disposal throughout the 2024-2025 blood collection and supply process based on nationwide multi-site monitoring data, develop a comprehensive prevention and control strategy across the entire chain, reduce preventable blood waste, and ensure clinical blood safety. Methods: According to the Guidelines for Haemovigilance (T/CSBT 001-2026), we extracted 74 cases of abnormal blood disposal events reported by the China Blood Transfusion Association′s Blood Safety Monitoring System from January 1 2024, to December 31 2025, and conducted descriptive statistical analysis on the distribution of events, types of deviations, root causes, and classifications of disposal manifestations. Results: A total of 664 adverse events related to blood collection and supply were reported over two years, with 74 cases involving discarded abnormal blood units, accounting for 11.1% of the total. Among these, blood component preparation (40.5%) and blood collection (37.8%) remained traditional high-risk stages. The proportion of blood waste occurring during storage, distribution, and transportation increased from 7.7% in 2024 to 34.3% in 2025. Deviations from standard operating procedures (SOP) by personnel were the primary cause, accounting for 74.3% of cases. Discarded blood units were categorized into four types: compromised closed blood bag systems (40 cases), mainly due to inadequate heat sealing, physical damage, or dropped bags; blood out of the cold chain (12 cases), primarily resulting from blood being left at work sites; imbalanced proportion of preservation solution (10 cases), mostly caused by blood collection volumes exceeding the standard capacity of blood bags; and other causes (12 cases). Conclusion: Human operational errors are the core cause of abnormal blood waste. The collection and preparation stages have long been at high-risk, and the risks in the storage and transportation stages have been increasing year by year. We should focus on standardizing personnel management, improving specialized operation norms such as heat sealing, transportation, and storage, establishing a full-process intelligent cold chain monitoring and multi-node visual verification mechanism, and systematically reducing the occurrence rate of abnormal blood waste through a closed-loop quality intervention system, thereby improving the utilization efficiency of voluntary blood donation resources.

Objective By combining biological detection and imaging evaluation, a clinical prediction model is constructed based on a large cohort to improve the accuracy of distinguishing between benign and malignant pulmonary nodules. Methods A retrospective analysis was conducted on the clinical data of the 32 627 patients with pulmonary nodules who underwent chest CT and testing for 7 types of lung cancer-related serum autoantibodies (7-AABs) at our hospital from January 2020 to April 2024. The univariate and multivariate logistic regression models were performed to screen independent risk factors for benign and malignant pulmonary nodules, based on which a nomogram model was established. The performance of the model was evaluated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Results A total of 1 017 patients with pulmonary nodules were included in the study. The training set consisted of 712 patients, including 291 males and 421 females, with a mean age of (58±12) years. The validation set included 305 patients, comprising 129 males and 176 females, with a mean age of (58±13) years. Univariate ROC curve analysis indicated that the combination of CT and 7-AABs testing achieved the highest area under the curve (AUC) value (0.794), surpassing the diagnostic efficacy of CT alone (AUC=0.667) or 7-AABs alone (AUC=0.514). Multivariate logistic regression analysis showed that radiological nodule diameter, nodule nature, and CT combined with 7-AABs detection were independent predictors, which were used to construct a nomogram prediction model. The AUC values for this model were 0.826 and 0.862 in the training and validation sets, respectively, demonstrating excellent performance in DCA. Conclusion The combination of 7-AABs with CT significantly enhances the accuracy of distinguishing between benign and malignant pulmonary nodules. The developed predictive model provides strong support for clinical decision-making and contributes to achieving precise diagnosis and treatment of pulmonary nodules.

Serine protease inhibitor Kazal-type (SPINK) is a skin keratinizing protease inhibitor, which was initially found in animal serum and is widely present in plants, animals, bacteria, and viruses, and they act as key regulators of skin keratinizing proteases and are involved in the regulation of keratinocyte proliferation and inflammation, primarily through the inhibition of deregulated tissue kinin-releasing enzymes (KLKs) in skin response. This process plays a crucial role in alleviating various skin problems caused by hyperkeratinization and inflammation, and can greatly improve the overall condition of the skin. Specifically, the different members of the SPINK family, such as SPINK5, SPINK6, SPINK7, and SPINK9, each have unique biological functions and mechanisms of action. The existence of these members demonstrates the diversity and complexity of skin health and disease. First, SPINK5 mutations are closely associated with the development of various skin diseases, such as Netherton’s syndrome and atopic dermatitis, and SPINK5 is able to inhibit the activation of the STAT3 signaling pathway, thereby effectively preventing the metastasis of melanoma cells, which is important in preventing the invasion and migration of malignant tumors. Secondly, SPINK6 is mainly distributed in the epidermis and contains lysine and glutamate residues, which can act as a substrate for epidermal transglutaminase to maintain the normal structure and function of the skin. In addition, SPINK6 can activate the intracellular ERK1/2 and AKT signaling pathways through the activation of epidermal growth factor receptor and protease receptor-2 (EphA2), which can promote the migration of melanoma cells, and SPINK6 further deepens its role in stimulating the migration of malignant tumor cells by inhibiting the activation of STAT3 signaling pathway. This process further deepens its potential impact in stimulating tumor invasive migration. Furthermore, SPINK7 plays a role in the pathology of some inflammatory skin diseases, and is likely to be an important factor contributing to the exacerbation of skin diseases by promoting aberrant proliferation of keratinocytes and local inflammatory responses. Finally, SPINK9 can induce cell migration and promote skin wound healing by activating purinergic receptor 2 (P2R) to induce phosphorylation of epidermal growth factor and further activating the downstream ERK1/2 signaling pathway. In addition, SPINK9 also plays an antimicrobial role, preventing the interference of some pathogenic microorganisms. Taken as a whole, some members of the SPINK family may be potential targets for the treatment of dermatological disorders by regulating multiple biological processes such as keratinization metabolism and immuno-inflammatory processes in the skin. The development of drugs such as small molecule inhibitors and monoclonal antibodies has great potential for the treatment of dermatologic diseases, and future research on SPINK will help to gain a deeper understanding of the physiopathologic processes of the skin. Through its functions and regulatory mechanisms, the formation and maintenance of the skin barrier and the occurrence and development of inflammatory responses can be better understood, which will provide novel ideas and methods for the prevention and treatment of skin diseases.

Alzheimer’s disease (AD) is a chronic neurodegenerative disorder that severely affects the health of the elderly, marked by its incurability, high prevalence, and extended latency period. The current approach to AD prevention and treatment emphasizes early detection and intervention, particularly during the pre-AD stage of mild cognitive impairment (MCI), which provides an optimal “window of opportunity” for intervention. Clinical detection methods for MCI, such as cerebrospinal fluid monitoring, genetic testing, and imaging diagnostics, are invasive and costly, limiting their broad clinical application. Speech, as a vital cognitive output, offers a new perspective and tool for computer-assisted analysis and screening of cognitive decline. This is because elderly individuals with cognitive decline exhibit distinct characteristics in semantic and audio information, such as reduced lexical richness, decreased speech coherence and conciseness, and declines in speech rate, voice rhythm, and hesitation rates. The objective presence of these semantic and audio characteristics lays the groundwork for computer-based screening of cognitive decline. Speech information is primarily sourced from databases or collected through tasks involving spontaneous speech, semantic fluency, and reading, followed by analysis using computer models. Spontaneous language tasks include dialogues/interviews, event descriptions, narrative recall, and picture descriptions. Semantic fluency tasks assess controlled retrieval of vocabulary items, requiring participants to extract information at the word level during lexical search. Reading tasks involve participants reading a passage aloud. Summarizing past research, the speech characteristics of the elderly can be divided into two major categories: semantic information and audio information. Semantic information focuses on the meaning of speech across different tasks, highlighting differences in vocabulary and text content in cognitive impairment. Overall, discourse pragmatic disorders in AD can be studied along three dimensions: cohesion, coherence, and conciseness. Cohesion mainly examines the use of vocabulary by participants, with a reduction in the use of nouns, pronouns, verbs, and adjectives in AD patients. Coherence assesses the ability of participants to maintain topics, with a decrease in the number of subordinate clauses in AD patients. Conciseness evaluates the information density of participants, with AD patients producing shorter texts with less information compared to normal elderly individuals. Audio information focuses on acoustic features that are difficult for the human ear to detect. There is a significant degradation in temporal parameters in the later stages of cognitive impairment; AD patients require more time to read the same paragraph, have longer vocalization times, and produce more pauses or silent parts in their spontaneous speech signals compared to normal individuals. Researchers have extracted audio and speech features, developing independent systems for each set of features, achieving an accuracy rate of 82% for both, which increases to 86% when both types of features are combined, demonstrating the advantage of integrating audio and speech information. Currently, deep learning and machine learning are the main methods used for information analysis. The overall diagnostic accuracy rate for AD exceeds 80%, and the diagnostic accuracy rate for MCI also exceeds 80%, indicating significant potential. Deep learning techniques require substantial data support, necessitating future expansion of database scale and continuous algorithm upgrades to transition from laboratory research to practical product implementation.