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.

[Objective] To explore the key factors affecting the efficiency and safety of hematopoietic stem cell apheresis. [Methods] The clinical data of 59 healthy donors who underwent allogeneic hematopoietic stem cell donation in the First Affiliated Hospital of Anhui Medical University from January 2021 to June 2024 were retrospectively analyzed. The number of CD34⁺ cells was used to evaluate the eligibility of stem cell collection. The effects of donor gender, age, patient weight, as well as the number of WBC, MNC, RBC, Hb, HCT, PLT, CD34⁺ cells, CD34⁺ percentage and instrument operating parameters on collection efficiency were analyzed. [Results] A total of 59 donors were enrolled, and 68 occasions of stem cell apheresis were performed, with a qualified collection rate of 56%. Donor gender, age, patient weight, total blood circulation volume, anticoagulant dosage, collection time, calcium gluconate dosage and RBC, Hb, HCT levels were not significantly correlated with the collection effect (P>0.05). Multivariate logistic regression analysis showed that the number of MNC cells, CD34⁺ cells and stem cell product volume were the key factors affecting the efficiency and safety. A total of 12 donors had mild adverse reactions during the collection process, and all of them were improved after treatment. [Conclusion] Optimizing apheresis strategy based on the three factors of MNC, WBC count and stem cell product volume on the day of collection will help to achieve high-quality collection and improve the success rate of transplantation.

Objective To explore the differences in stress distribution and stability of the planta pedis in the patients with unilateral and bilateral plantar fasciitis(PF)through plantar stress and center of pressure(COP)analysis.Methods A total of 100 patients with PF visiting in this hospital were enrolled,among them 50 cases were unilateral heel pain(unilateral heel pain group)and 50 cases were bilateral heel pain(bilateral heel pain).Meanwhile,50 healthy subjects were included(healthy group).In the health group and bilateral heel pain groups,the average stress value of both planta pedis surfaces of each subject was taken and named as the J0 group and H2 group,respectively.In the unilateral heel pain group,the plantar stress in 50 healthy feet and 50 affected feet were named as the J1 group and H1 group,respectively.The plantar pedis was divided into 10 regions for analysis and comparison[the first foot toe(T1),T2-5,the first-fifth metatarsal bones(M1-M5),the mid foot(MF),heel medial side(MH),heel lateral side(LH)].The subjects in 3 groups conducted the static and dynamic tests respectively,and the differences in plantar stress distribution and COP parameters among the J1,H1,H2 and J0 groups were compared respectively.Results In the static tests,the maximum pressure of the LH regions in the group J1 was increased when compared with the group J0,the contact area of LH regions in the group H1 was reduced when compared with the group J0,the maximum pressure of the M2 and M3 regions in the H1 group was increased when compared with the group J0,the contact areas of the MH and LH regions in the H2 group were decreased when compared with the group J0,the maximum pressure of the M1 region was increased when compared with the group J0,and the differences were statistically significant(P<0.05).In the dynamic tests,the maximum pressure of the T2-5 regions in the J1 group was increased when compared with the J0 group,the maximum pressure of the M3 region in the group H1 was increased when compared with the group J0,the maximum pressure of the M3 and M4 region in the group H2 was in-creased when compared with the group J0,and the differences were statistically significant(P<0.05).The COP 95%confidence ellipse area in the health group was the smallest,followed by the bilateral heel pain group,and finally the unilateral heel pain group,and the differences among 3 groups were statistically signifi-cant(P<0.05),there was also statistically significant difference between pairwise comparisons in 3 groups(P<0.05).Conclusion In the static condition,the pressure of the healthy heel and affected forefoot in the patients with PF is increased;while in the dynamic condition,the pressure of the toes of the healthy foot and forefoot of the affected foot in the patients with PF is also increased.The distribution of plantar stress in the patients with PF has larger difference compared with the healthy population,and the stability is poor.Meas-ures can be taken to improve the abnormal force on the foot,reduce pain and reduce the risk of falling.

This article summarizes Professor Huang Guicheng's clinical experience in the syndrome differentiation and treatment of lumbar spinal stenosis using the theory of"diseases of tendons,bones and collaterals".It is believed that lumbar spinal stenosis be-longs to the syndrome of deficiency in the root and excess in the superficiality,and is closely related to the three zang organs of the liv-er,spleen and kidney.Deficiency of the liver and kidney leading to a lack of the source of qi and blood,insufficiency of the spleen and stomach giving rise to phlegm and blood stasis,and the invasion of wind,cold and dampness pathogens cause the disease.The key to the pathogenesis lies in the obstruction of the collaterals.Taking the principles of"nourishing the collaterals and strengthening the healthy qi,dredging the collaterals and expelling the pathogens"as the therapeutic principles,Professor Huang is proficient in using insect drugs.The medicinal power can directly reach the collaterals,so that the collaterals can be unobstructed and the qi and blood can flow smoothly,achieving the therapeutic effect of expelling the pathogens,unblocking the collaterals and restoring the healthy qi.

Objective To evaluate the performance of reconstruction networks with different sparse views under the condition of keeping the same number of model parameters.Methods The number of network channels and network layers were adjusted to make the parameter quantity of each network similar when keeping the structure of each image-domain network and dual-domain network unchanged.The reconstruction performance of each network at different sparsity levels was compared.The AAPM Low-Dose CT Grand Challenge datasets were used in the experiment,including 10 976 images for training,979 images for validation,and 4 256 images for testing.The performance of each model was evaluated visually in combination with objective metrics such as peak signal-to-noise ratio,structural similarity and root mean square error.Results Before adjusting the model parameters,the hybrid domain network Tensor-Net obtained the best visual evaluation and objective evaluation metrics.After parament adjustment,with a similar number of parameters,Tensor-Net outperformed the other models at various projection angles in image anatomical detail recovery,but its structural similarity was slightly lower than that of RED-CNN.The parameters of the hybrid domain model Dual-FBPConvNet were all worse than those of FBPConvNet.Conclusion The hybrid domain model is advantageous in sparse-view CT reconstruction,but it faces more serious overfitting problems.Using a larger image domain model can achieve results similar to those of hybrid domain model.

OBJECTIVE To analyze the blood components of Suanzaoren Decoction after oral administration using UHPLC-Q Exactive Orbitrap-MS technology.METHODS Female Sprague-Dawley(SD)rats were used as experimental subjects,and Suanza-oren Decoction was administered orally.Serum samples were collected,and the aqueous extract of Suanzaoren Decoction and the serum were analyzed using UHPLC-Q Exactive Orbitrap-MS technology to identify the prototype components and metabolites absorbed into the blood by comparing and analyzing with the LuMet-TCM database.RESULTS It showed that a total of 458 components were iden-tified in the aqueous extract of Suanzaoren Decoction,and 26 chemical components were identified in the blood,including 23 prototype components and 3 metabolites.CONCLUSION The prototype components absorbed into the blood discovered in this study may be the active ingredients of Suanzaoren Decoction,providing a reference for the research on the pharmacodynamic material basis of Suanza-oren Decoction.

OBJECTIVE: To explore the clinical features of patients with necrotizing soft tissue infection (NSTI) and the related factors for sepsis, so as to provide a basis for early intervention and improvement of patients' prognosis. METHODS: A retrospective case series study was conducted to analyze the clinical data of NSTI patients admitted to the department of burns and wound repair surgery of Guangdong Provincial People's Hospital from October 2021 to December 2024. Demographic information, underlying diseases, infection characteristics, laboratory test results and etiological findings at admission, treatment status, occurrence of complications (including sepsis) and prognosis were collected. Univariate and multivariate Logistic regression analyses were used to identify the associated factors for sepsis in NSTI patients. Receiver operator characteristic curves (ROC curves) were plotted to evaluate the predictive value of individual and combined factors for sepsis. RESULTS: A total of 159 NSTI patients were enrolled, mainly middle-aged and elderly males. Most patients had comorbidities, including diabetes mellitus (110 cases, 69.2%) and hypertension (67 cases, 42.1%). The main infection site was the lower extremities (104 cases, 65.4%). Common symptoms included redness (96 cases, 60.4%), swelling (129 cases, 81.1%), local heat (60 cases, 37.7%), pain (100 cases, 62.9%), and skin ulceration or necrosis (9 cases, 5.7%). Imaging findings included soft tissue swelling (66 cases, 57.9%), gas accumulation (41 cases, 36.0%), and abnormal signal/density shadows (50 cases, 43.9%). Staphylococcus aureus was the main pathogenic bacterium [12.0% (31/259)], and drug-resistant Escherichia coli had the highest detection rate among drug-resistant bacteria [35.1% (13/37)]. Regarding debridement and repair, most patients (80 cases, 50.3%) underwent debridement ≥ 72 hours after admission, while only 10.1% (16 cases) received debridement within 6 hours. Most patients underwent multiple debridements, with 2 times of debridements being the most common (68 cases, 42.8%), and the maximum times of debridements reached 6. The largest number of patients received secondary suture (44 cases, 27.7%). In terms of complications, sepsis was the most common (66 cases, 41.51%), followed by acute kidney injury, respiratory failure requiring mechanical ventilation, and multiple organ dysfunction syndrome (MODS), while disseminated intravascular coagulation (DIC) was the least common. During the follow-up period, 9 patients (5.66%) were readmitted within 90 days, and 11 patients died, with a mortality rate of 6.92%. Univariate analysis showed that diabetes, coronary heart disease, gout, body temperature, heart rate, C-reactive protein, platelet count, total bilirubin, albumin, creatinine, out-of-hospital treatment, and out-of-hospital use of antimicrobial agents were significantly associated with sepsis in NSTI patients (all P < 0.05). Multivariate Logistic regression analysis showed that coronary heart disease [odds ratio (OR) = 30.085, 95% confidence interval (95%CI) was 2.105-956.935], C-reactive protein (OR = 1.026, 95%CI was 1.009-1.054), and total bilirubin (OR = 1.436, 95%CI was 1.188-1.948) were independent associated factors for sepsis in NSTI patients (all P < 0.05). ROC curve analysis revealed that the combination of the three predictors yielded the highest AUC for predicting sepsis in NSTI patients compared to any individual predictor [area under the curve (AUC) = 0.799 (95%CI was 0.721-0.878)]. CONCLUSIONS The clinical features of NSTI patients show certain regularity. Coronary heart disease, C-reactive protein, and total bilirubin are independent associated factors for sepsis in NSTI patients.
Humans ; Retrospective Studies ; Male ; Sepsis ; Soft Tissue Infections/microbiology* ; Female ; Middle Aged ; Aged ; Adult ; Prognosis ; Risk Factors ; Necrosis ; Logistic Models ; Fasciitis, Necrotizing

This study aims to explore the mechanism of Jiaotai Pills in treating depression based on metabolomics and network pharmacology. The chemical constituents of Jiaotai Pills were identified by UHPLC-Orbitrap Exploris 480, and the targets of Jiaotai Pills and depression were retrieved from online databases. STRING and Cytoscape 3.7.2 were used to construct the protein-protein interaction network of core targets of Jiaotai Pills in treating depression and the "compound-target-pathway" network. DAVID was used for Gene Ontology(GO) function and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analyses of the core targets. The mouse model of depression was established with chronic unpredictable mild stress(CUMS) and treated with different doses of Jiaotai Pills. The behavioral changes and pathological changes in the hippocampus were observed. UHPLC-Orbitrap Exploris 120 was used for metabolic profiling of the serum, from which the differential metabolites and related metabolic pathways were screened. A "metabolite-reaction-enzyme-gene" network was constructed for the integrated analysis of metabolomics and network pharmacology. A total of 34 chemical components of Jiaotai Pills were identified, and 143 core targets of Jiaotai Pills in treating depression were predicted, which were mainly involved in the arginine and proline, sphingolipid, and neurotrophin metabolism signaling pathways. The results of animal experiments showed that Jiaotai Pills alleviated the depression behaviors and pathological changes in the hippocampus of the mouse model of CUMS-induced depression. In addition, Jiaotai Pills reversed the levels of 32 metabolites involved in various pathways such as arginine and proline metabolism, sphingolipid metabolism, and porphyrin metabolism in the serum of model mice. The integrated analysis showed that arginine and proline metabolism, cysteine and methionine metabolism, and porphyrin metabolism might be the key pathways in the treatment of depression with Jiaotai Pills. In conclusion, metabolomics combined with network pharmacology clarifies the antidepressant mechanism of Jiaotai Pills, which may provide a basis for the clinical application of Jiaotai Pills in treating depression.
Animals ; Drugs, Chinese Herbal/chemistry* ; Depression/genetics* ; Mice ; Network Pharmacology ; Metabolomics ; Male ; Disease Models, Animal ; Humans ; Protein Interaction Maps/drug effects* ; Antidepressive Agents

This study aimed to investigate the correlation between changes in intestinal toxicity and compositional alterations of Euphorbiae Ebracteolatae Radix(commonly known as Langdu) before and after milk processing, and to explore the detoxification mechanism of milk processing. Mice were intragastrically administered the 95% ethanol extract of raw Euphorbiae Ebracteolatae Radix, milk-decocted(milk-processed), and water-decocted(water-processed) Euphorbiae Ebracteolatae Radix. Fecal morphology, fecal water content, and the release levels of inflammatory cytokines tumor necrosis factor-α(TNF-α) and interleukin-1β(IL-1β) in different intestinal segments were used as indicators to evaluate the effects of different processing methods on the cathartic effect and intestinal inflammatory toxicity of Euphorbiae Ebracteolatae Radix. LC-MS/MS was employed to analyze the small-molecule components in the raw product, the 95% ethanol extract of the milk-processed product, and the milky waste(precipitate) formed during milk processing, to assess the impact of milk processing on the chemical composition of Euphorbiae Ebracteolatae Radix. The results showed that compared with the blank group, both the raw and water-processed Euphorbiae Ebracteolatae Radix significantly increased the fecal morphology score, fecal water content, and the release levels of TNF-α and IL-1β in various intestinal segments(P<0.05). Compared with the raw group, all indicators in the milk-processed group significantly decreased(P<0.05), while no significant differences were observed in the water-processed group, indicating that milk, as an adjuvant in processing, plays a key role in reducing the intestinal toxicity of Euphorbiae Ebracteolatae Radix. Mass spectrometry results revealed that 29 components were identified in the raw product, including 28 terpenoids and 1 acetophenone. The content of these components decreased to varying extents after milk processing. A total of 28 components derived from Euphorbiae Ebracteolatae Radix were identified in the milky precipitate, of which 27 were terpenoids, suggesting that milk processing promotes the transfer of toxic components from Euphorbiae Ebracteolatae Radix into milk. To further investigate the effect of milk adjuvant processing on the toxic terpenoid components of Euphorbiae Ebracteolatae Radix, transmission electron microscopy(TEM) was used to observe the morphology of self-assembled casein micelles(the main protein in milk) in the milky precipitate. The micelles formed in casein-terpenoid solutions were characterized using particle size analysis, fluorescence spectroscopy, ultraviolet spectroscopy, and Fourier-transform infrared(FTIR) spectroscopy. TEM observations confirmed the presence of casein micelles in the milky precipitate. Characterization results showed that with increasing concentrations of toxic terpenoids, the average particle size of casein micelles increased, fluorescence intensity of the solution decreased, the maximum absorption wavelength in the UV spectrum shifted, and significant changes occurred in the infrared spectrum, indicating that interactions occurred between casein micelles and toxic terpenoid components. These findings indicate that the cathartic effect of Euphorbiae Ebracteolatae Radix becomes milder and its intestinal inflammatory toxicity is reduced after milk processing. The detoxification mechanism is that terpenoid components in Euphorbiae Ebracteolatae Radix reassemble with casein in milk to form micelles, promoting the transfer of some terpenoids into the milky precipitate.
Animals ; Mice ; Milk/chemistry* ; Drugs, Chinese Herbal/chemistry* ; Male ; Tumor Necrosis Factor-alpha/immunology* ; Intestines/drug effects* ; Interleukin-1beta/immunology* ; Tandem Mass Spectrometry ; Female