ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

Objectives:To investigate the association between the triglyceride-glucose(TyG)index and risk of non-alcoholic fatty liver disease(NAFLD)in young and middle-aged(<60 years)adults.Methods:From June 2006 to October 2007,47 675 employees of Kailuan Group with no liver disease were selected as the study objects.Based on the TyG index quartile,participants were divided into Q1 group(TyG index≤8.08,n=11 924),Q2 group(8.0836.46,n=11 919),the association between TyG index,cum-TyG and cumulative exposure time and the risk of NAFLD was analyzed.Results:The average age of the study population was(44.3±8.7)years,36 345 participants were males(76.23%).During a median follow-up period of 11.55(7.28,13.89)years,4 635(9.72%)participants developed new-onset NAFLD.After adjusting for confounders,cox regression analysis showed that compared with the Q1 group,the HR(95%CI)for NAFLD in the Q2 to Q4 groups were 1.328(1.191-1.480),1.591(1.430-1.770),and 2.106(1.861-2.384),respectively,Ptrend<0.001.Compared with the cum-Q1 group,the HR(95%CI)for NAFLD in the cum-Q2 to cum-Q4 groups were 1.571(1.426-1.730),2.123(1.935-2.330)and 2.593(2.367-2.840),respectively,Ptrend<0.001.Compared with the TyG index for 0 year,the HR(95%CI)of NAFLD for 2,4 and 6 years was 1.333(1.196-1.486),1.879(1.690-2.088)and 3.184(2.860-3.545),respectively,Ptrend<0.001.Conclusions:Increased TyG index is an independent risk factor for the new-onset NAFLD in young and middle-aged population.

This study was aimed at analyzing the biotypes and genetic diversity characteristics of five non-major Brucella species,to provide a scientific basis for understanding the species diversity of Brucella and strengthening pathogen monitoring and control.According to the biotypes(species,hosts,isolation locations,and time)and MLVA-16 genotypes(MLVA-16 lo-cus data,MLVA-11 genotypes)of five non-major pathogenic Brucella in the international MLVA database,we used Bionu-merics 8.0 software and PHYLOVIZ2.0 online software to analyze the geographical origin and genetic diversity characteristics of strains.A total of 227 strains were studied,including 121 Brucella ceti,47 B.pinnipedialis,37 Brucella ovis,11 B.mi-croti,and Brucella neotomae.The greatest host diversity was observed for B.ceti,followed by B.pinnipedialis and B.mi-croti.B.ceti was distributed in European and South American countries;B.pinnipedialiswas distributed in Europe;and B.microti.was distributed in the Czech Republic,Austria,and Hungary in Central Europe.B.ovis was widely distributed in Af-rica,Argentina,Australia,Brazil,Greece,the United States,Spain,and France.The MLVA-11 genotypes of different types of Brucella showed high polymorphism and large differences,thus suggesting that the strains have different geographical ori-gins.MST analysis indicated that the studied strains were divided into four branches(BCⅠ-Ⅳ),among which B.ceti was di-vided into two different branches(BC-Ⅰ and BC-Ⅱ),the strains of other types formed different branches(or sub-branches),and the strains of different types showed clear regional and dominant host characteristics.Genetic correlation analysis of strains of the Brucella genus revealed that non-major pathogenic Brucella had clear genetic,distribution,and host spectrum differ-ences with respect to four classical pathogenic Brucella species.Five non-major pathogenic Brucella strains presented unique genetic evolutionary patterns,geographical distributions,and host tropism characteristics,thereby providing new insight for understanding the biological and genetic diversity of those Brucella strains.

Apolipoprotein D(APOD)is a protein that is widely present in animal tissues and is in-volved in the reproductive regulation of the body.In order to investigate the expression regularity of APOD in bactrian camel epididymis and its regulation effect on sperm maturation,this study took the epididymis of bactrian camel during estrus and anestrus as materials,and first cloned the complete sequence of APOD coding sequence(CDS)region.The physicochemical properties of AP-OD were analyzed by ProParam,SOPMA,SWISS-MODEL and MEGA7.0 software.Meanwhile,the expression and distribution of APOD in epididymis were detected by qRT-PCR,Western blot and IHC.The cloning results showed that:the length of the CDS region of APOD gene was 624 bp,encoding 207 amino acids.The APOD sequence of Bactrian camel was highly conserved with the nucleotide and amino acid sequence of alpaca,and the homology of APOD sequence with elk was the lowest.The results of qRT-PCR showed that the mRNA levels of APOD in the head,body and tail of epididymis in estrus were significantly higher than those in estrus(P＜0.01).Western blot results showed that the APOD protein expression and mRNA expression trend was similar in the head and body of the epididymis during anestrus,but the APOD expression level in the tail of the epididymis during anestrus was opposite to the mRNA expression level(P＜0.05).The results of H&E and IHC showed that there were significant differences in epididymal tissue between estrus and anestrus.In addition,APOD showed positive reactions in epididymal epithelial cells,smooth muscle cells,sperm and connective tissue to varying degrees,suggesting that APOD may be in-volved in the maturation of sperm during estrus and anestrus,providing evidence for further explo-ring the regulatory mechanism of APOD's involvement in seasonal estrus.

With the emergence of deep learning techniques based on convolutional neural networks, artificial intelligence (AI) has driven transformative developments in the field of medical image analysis. Recently, large language models (LLMs) such as ChatGPT have also started to achieve distinction in this domain. Increasing research shows the undeniable role of AI in reshaping various aspects of medical image analysis, including processes such as image enhancement, segmentation, detection in image preprocessing, and postprocessing related to medical diagnosis and prognosis in clinical settings. However, despite the significant progress in AI research, studies investigating the recent advances in AI technology in the aforementioned aspects, the changes in research hotspot trajectories, and the performance of studies in addressing key clinical challenges in this field are limited. This article provides an overview of recent advances in AI for medical image analysis and discusses the methodological profiles, advantages, disadvantages, and future trends of AI technologies.
Artificial Intelligence ; Humans ; Image Processing, Computer-Assisted/methods* ; Neural Networks, Computer ; Deep Learning ; Diagnostic Imaging/methods*

Microbial detection and control of traditional Chinese medicine(TCM) decoction pieces are crucial for the quality control of TCM preparations. It is also a key area of research in the measurement technology and equipment development for TCM manufacturing. Guided by TCM manufacturing measurement methodologies, this study presented a design of a novel portable microbial detection device, using Atractylodis Macrocephalae Rhizoma decoction pieces as a demonstration. Immunomagnetic separation technology was employed for specific isolation and labeling of target microorganisms. Enzymatic signal amplification was utilized to convert weak biological signals into colorimetric signals, constructing an optical biosensor. A self-developed smartphone APP was further applied to analyze the colorimetric signals and quantify target concentrations. A portable and automated detection system based on Arduino microcontroller was developed to automatically perform target microbial separation/extraction, as well as mimetic enzyme labeling and catalytic reactions. The developed equipment specifically focuses on the rapid and quantitative microbial analysis of TCM active pharmaceutical ingredients, intermediates in TCM manufacturing, and final TCM products. Experimental results demonstrate that the equipment could detect Salmonella in samples within 2 h, with a detection limit as low as 5.1 × 10~3 CFU·mL~(-1). The equipment enables the rapid detection of microorganisms in TCM decoction pieces, providing a potential technical solution for on-site rapid screening of microbial contamination indicators in TCM. It has broad application prospects in measurement technology for TCM manufacturing and offers strong technical support for the modernization, industrialization, and intelligent development of TCM.
Drugs, Chinese Herbal/analysis* ; Atractylodes/microbiology* ; Rhizome/microbiology* ; Biosensing Techniques/methods* ; Medicine, Chinese Traditional ; Colorimetry/instrumentation* ; Quality Control

Objective To establish a stable,reliable,and clinically relevant porcine model of endotoxin-induced acute respiratory distress syndrome(ARDS).Methods Ten 8-month-old male Bama minipigs were deeply sedated,followed by invasive mechanical ventilation and electrocardiographic monitoring.Lipopolysaccharide(LPS)was intravenously pumped at 600 μg/(kg·h)for 3 hours,then maintained at 15 μg/(kg·h)thereafter.Dynamic monitoring was performed at five time points after LPS injection(LPS 0,1,3,5,and 8 h),including arterial blood gas analysis and chest computed tomography(CT)scans.Pathological examination of lung tissues obtained via bronchoscopic biopsy(HE staining and transmission electron microscopy)was conducted.These indicators were comprehensively used to evaluate the success of the animal model.Results At 5 hours after LPS administration,8 minipigs developed symptoms such as skin cyanosis,elevated body temperature,and respiratory distress.The oxygenation index decreased to<300 mmHg.Chest CT scans showed diffuse pulmonary infiltrates.Histopathology revealed alveolar edema and hyaline membrane formation.Transmission electron microscopy demonstrated disruption of pulmonary blood-air barrier,depletion of lamellar bodies in type Ⅱ pneumocytes,inflammatory cell infiltration,and exudation of plasma proteins and fibrin.Compared with LPS 0 h,at LPS 8 h,the oxygenation index and arterial blood pH were significantly decreased(P<0.001),while blood lactic acid and serum potassium were significantly increased(P<0.05);serum calcium and base excess were significantly decreased(P<0.05),and the lung injury score based on HE-stained lung sections was significantly increased(P<0.01).Conclusion The porcine ARDS model established by continuous LPS injection can dynamically simulate the pathophysiological characteristics and typical pathological manifestations of clinical septic ARDS,making it an effective tool to study the pathogenesis,prevention,and treatment strategies of septic ARDS.

Background Polystyrene microplastics (PS-MPs) attract widespread public attention due to their adverse effects on mammalian reproductive systems. However, it is currently unclear whether ferroptosis is related to testicular damage and decreased sperm quality in mice exposed to PS-MPs. Objective To clarify the reproductive damage in male mice exposed to PS-MPs and investigate the mechanism of ferroptotic effects. Methods Five-week-old male BALB/c mice were randomly divided into four experimental groups, including one control group and three PS-MPs groups at low dose (0.5 mg·kg⁻¹), medium dose (5 mg·kg⁻¹), and high dose (50 mg·kg⁻¹), respectively, with 6 mice in each group. The treatment was delivered by gavage for 35 consecutive days (one time per day). After the mice were neutralized, the wet weights of testis and epididymis were measured, and organ coefficients were then calculated. Sperm was counted by hematimetry, and sperm motility and adenosine triphosphate (ATP) level were evaluated using CCK-8 and CellTiter Glo ® Kit 2.0 Assay respectively. In addition, serum testosterone, follicle-stimulating hormone, and luteinizing hormone were determined using ELISA kit, total testicular iron content was measured using tissue iron kit, and pathological changes in testicular tissue were observed after hematoxylin-eosin (HE) staining. We also used glutathione (GSH), malondialdehyde (MDA), and superoxide dismutase (SOD) assays to examine their changes to better understand the physiological status of testicular tissue. Finally, the expression levels of ferroptosis-associated proteins glutathione peroxidase 4 (GPX4) and solute carrier family 7 member 11 (SLC7A11) were detected by Western blotting. Results Compared with the control group, the testicular index in the high dose group decreased, and the epididymal index decreased in all dose groups (P<0.05). The results of sperm quality analysis showed that the sperm count in each dose group was lower than that of the control group; the sperm motility decreased, sperm malformation rate increased, and ATP level in sperm decreased in the medium and high dose groups. The results of HE staining showed that the spermatogenic epithelium was disordered and the arrangement of spermatogenic cells were loose in the low dose group, the spermatogenic gap was enlarged in the middle dose group, and the cells in the high dose group were vacuolated and even azoospermic. The results of serum sex hormone levels showed that the serum testosterone levels decreased in each dose group, the serum follicle-stimulating hormone levels decreased in the medium and high dose groups, and the serum luteinizing hormone levels decreased in the high dose group (P<0.05). The iron content in the testicular tissue homogenate of the high dose group increased (P<0.05). The levels of GSH and SOD in the homogenate of testicular tissue decreased in the medium and high dose groups, while the levels of MDA increased (P<0.05). The results of Western blotting showed that the protein expression level of GPX4 in the testis in the high dose group was lower than that in the control group. The protein expression levels of SLC7A11 in the medium and high dose groups were lower than that in the control group. The results of correlation analysis showed that the expression level of GPX4 was positively correlated with sperm count, and negatively correlated with MDA level (P<0.05). SLC7A11 expression level was positively correlated with sperm count, and negatively correlated with sperm malformation rate and MDA level (P<0.05). Conclusion PS-MPs exposure leads to decreased sperm quality, testicular damage, and decreased serum sex hormone levels in male mice, and its mechanism of action may involve ferroptosis.

Poloxamer， as a non-ionic surfactant， exhibits a unique triblock [polyethylene oxide-poly （propylene oxide）-polyethylene oxide] structure， which endows it with broad application potential in various fields， including solid dispersion technology， nanotechnology， gel technology， biologics， gene engineering and 3D printing. As a carrier， it enhances the solubility and bioavailability of poorly soluble drugs. In the field of nanotechnology， it serves as a stabilizer etc.， enriching preparation methods. In gel technology， its self-assembly behavior and thermosensitive properties facilitate controlled drug release. In biologics， it improves targeting efficiency and reduces side effects. In gene engineering， it enhances delivery efficiency and expression levels. In 3D printing， it provides novel strategies for precise drug release control and the production of high-quality biological products. As a versatile material， poloxamer holds promising prospects in the pharmaceutical field.