With the continuous development of society, a large number of new chemicals are continuously emerging, which presents a challenge to current risk assessment and safety management of chemicals. Traditional toxicology research methods have certain limitations in quickly, efficiently, and accurately assessing the toxicity of many chemicals, and cannot meet the actual needs. In response to this challenge, computational toxicology that use mathematical and computer models to achieve the prediction of chemical toxicity has emerged. In the meantime, as researchers increasingly pay attention to understanding the interaction mechanisms between exogenous chemical substances and the body from the system level, and multiomics technologies develop rapidly such as genomics, transcriptomics, proteomics, and metabolomics, huge amounts of data have been generated, providing rich information resources for studying the interactions between chemical substances and biological molecules. System toxicology and network toxicology have also developed accordingly. Of these, network toxicology can integrate these multiomics data to construct biomolecular networks, and then quickly predict the key toxicological targets and pathways of chemicals at the molecular level. This paper outlined the concept and development of network toxicology, summarized the main methods and supporting tools of network toxicology research, expounded the application status of network toxicology in studying potential toxicity of exogenous chemicals such as agricultural chemicals, environmental pollutants, industrial chemicals, and foodborne chemicals, and analyzed the development prospects and limitations of network toxicology research. This paper aimed to provide a reference for the application of network toxicology in other fields.

OBJECTIVE: To evaluate the efficacy and safety of DCAG (decitabine, cytarabine, anthracyclines, and granulocyte colony-stimulating factor) regimen in the treatment of patients with relapsed/refractory (R/R) acute myeloid leukemia (AML). METHODS: The clinical data of 64 R/R AML patients received treatment at Chinese PLA General Hospital from January 1st, 2012 to December 31st, 2022 were retrospectively analyzed. Primary endpoints included efficacy measured by overall response rate (ORR) and safety. Secondary endpoints included overall survival (OS), event-free survival (EFS) and duration of response (DOR). The patients were followed from enrollment until death, or the end of last follow-up (June 1st, 2023), whichever occurred first. RESULTS: Sixty-four patients who failed prior therapy were enrolled and completed 1 cycle, and 26 and 5 patients completed 2 and 3 cycles, respectively. Objective response rate was 67.2% ［39: complete remission (CR)/CR with incomplete hematologic recovery (CRi), 4: partial remission (PR)］. With a median follow-up of 62.0 months (1.0-120.9), the median overall survival (OS) was 23.3 and event-free survival was 10.6 months. The median OS was 51.7 months (3.4-100.0) in responders (CR/CRi/PR) while it was 8.4 months (6.1-10.7) in nonresponders ( P <0.001). Grade 3-4 hematologic toxicities were observed in all patients. Four patients died from rapid disease progression within 8 weeks after chemotherapy. CONCLUSION The DCAG regimen represents a feasible and effective treatment for R/R AML.
Humans ; Leukemia, Myeloid, Acute/drug therapy* ; Cytarabine/administration & dosage* ; Granulocyte Colony-Stimulating Factor/administration & dosage* ; Retrospective Studies ; Male ; Female ; Decitabine ; Antineoplastic Combined Chemotherapy Protocols/therapeutic use* ; Anthracyclines/administration & dosage* ; Middle Aged ; Adult ; Treatment Outcome ; Aged ; Recurrence

OBJECTIVE: To investigate the clinical characteristics, treatment and prognosis of adult AML patients with NUP98::HOXA9 fusion gene. METHODS: From May 2017 to October 2023， among 2 113 AML patients who visited the Hematology Department of our hospital, patients with NUP98 rearrangements were screened. The clinical characteristics, chromosome karyotypes, immunophenotypes, gene mutations, treatment efficacy and prognosis of the patients with NUP98::HOXA9 positive were analyzed. RESULTS: Among the 2 113 AML patients, there were 18 cases with NUP98 rearrangement, including 14 NUP98::HOXA9 positive cases, with a detection rate of 0.66% (14/2 113). The median age of the NUP98::HOXA9 positive patients was 42.5 (23-64) years old. The most common chromosome karyotype was t(7; 11)(p15; p15). The immunophenotypes of all patients expressed CD13, CD33, CD117 and CD38, and most patients expressed CD34 and cMPO, while only a few expressed HLA-DR. Second-generation sequencing (NGS) was performed to detect genetic mutations associated with leukemia in all 14 patients, and the genes exhibiting a high frequency of mutation were WT1 (10/14), TET2 (7/14), and FLT3-ITD (6/14). Additionally, mutations were also observed in KRAS/NRAS, IDH1, and KIT. Of the 13 patients who received treatment, 9 achieved complete remission (CR), and all 3 patients who received azacytidine(AZA)+ venetoclax (VEN) regimen achieved CR after the first course of treatment. Within this cohort, 6 patients were classified as relapsed/refractory (6/13). 4 patients underwent allogeneic hematopoietic stem cell transplantation (allo-HSCT), of which two achieved long-term survival. The median follow-up time was 12 (2.1-65.0) months, while the median overall survival (OS) and relapse-free survival (RFS) were recorded as 11.4 months and 9.6 months, respectively. CONCLUSION The most common type of NUP98 rearrangement in adults AML patients is NUP98::HOXA9 , which is often accompanied by somatic mutations in WT1, TET2, and FLT3-ITD. These patients are prone to relapse, have short survival time, and generally face poor prognoses. Hopefully, utilization of the AZA+VEN regimen is anticipated to enhance the rate of induced remission in the patients, and some patients may prolong their survival through allo-HSCT. However, more effective treatment methods are still needed to improve the overall prognosis of these patients.
Humans ; Adult ; Leukemia, Myeloid, Acute/genetics* ; Middle Aged ; Prognosis ; Nuclear Pore Complex Proteins/genetics* ; Oncogene Proteins, Fusion/genetics* ; Mutation ; Male ; Female ; Young Adult ; Homeodomain Proteins/genetics*

OBJECTIVE: To analyze the clinical features of acute myeloid leukemia patients with DEK-NUP214 fusion gene positive. METHODS: The DEK-NUP214 fusion gene was amplified by multi-nested PCR in 26 patients admitted to the First Affiliated Hospital of Soochow University from January 2018 to October 2023, and the disease course and post-transplant survival data were obtained by searching outpatient and inpatient medical records and telephone follow-up. RESULTS: The median follow-up time of pateints was 21.25（0.9-60.2） months. Among 26 patients with DEK-NUP214 fusion gene positive AML, 15 patients had FLT3-ITD gene mutation positive. One patient died after abandoning treatment due to non-remission of induction chemotherapy, one died due to infection, and 23 patients received allo-HSCT after achieving CR, of which one patient died within one month after transplantation due to multiple infections and one died due to severe pulmonary infection that did not respond to treatment. One patient received allo-HSCT in non-remission state and later died due to recurrence. CONCLUSION DEK-NUP214 fusion gene positive AML is a type of acute leukemia subtype with high risk and poor prognosis. Allo-HSCT treatment at the early stage of disease remission is the most effective way to improve the prognosis of patients.
Humans ; Leukemia, Myeloid, Acute/genetics* ; Poly-ADP-Ribose Binding Proteins ; Oncogene Proteins, Fusion/genetics* ; Nuclear Pore Complex Proteins/genetics* ; Oncogene Proteins/genetics* ; Chromosomal Proteins, Non-Histone/genetics* ; Male ; Female ; Adult ; Mutation ; Hematopoietic Stem Cell Transplantation ; Middle Aged

OBJECTIVE: As an age-related neurodegenerative disease, the prevalence of mild cognitive impairment (MCI) increases with age. Within the framework of traditional Chinese medicine, spleen-kidney deficiency syndrome (SKDS) is recognized as the most frequent MCI subtype. Due to the covert and gradual onset of MCI, in community settings it poses a significant challenge for patients and their families to discern between typical aging and pathological changes. There exists an urgent need to devise a preliminary diagnostic tool designed for community-residing older adults with MCI attributed to SKDS (MCI-SKDS). METHODS: This investigation enrolled 312 elderly individuals diagnosed with MCI, who were randomly distributed into training and test datasets at a 3:1 ratio. Five machine learning methods, including logistic regression (LR), decision tree (DT), naive Bayes (NB), support vector machine (SVM), and gradient boosting (GB), were used to build a diagnostic prediction model for MCI-SKDS. Accuracy, sensitivity, specificity, precision, F1 score, and area under the curve were used to evaluate model performance. Furthermore, the clinical applicability of the model was evaluated through decision curve analysis (DCA). RESULTS: The accuracy, precision, specificity and F1 score of the DT model performed best in the training set (test set), with scores of 0.904 (0.845), 0.875 (0.795), 0.973 (0.875) and 0.973 (0.875). The sensitivity of the training set (test set) of the SVM model performed best among the five models with a score of 0.865 (0.821). The area under the curve of all five models was greater than 0.9 for the training dataset and greater than 0.8 for the test dataset. The DCA of all models showed good clinical application value. The study identified ten indicators that were significant predictors of MCI-SKDS. CONCLUSION The risk prediction index derived from machine learning for the MCI-SKDS prediction model is simple and practical; the model demonstrates good predictive value and clinical applicability, and the DT model had the best performance. Please cite this article as: Ai YT, Zhou S, Wang M, Zheng TY, Hu H, Wang YC, Li YC, Wang XT, Zhou PJ. Development of a machine learning-based risk prediction model for mild cognitive impairment with spleen-kidney deficiency syndrome in the elderly. J Integr Med. 2025; 23(4): 390-397.
Humans ; Cognitive Dysfunction/diagnosis* ; Aged ; Male ; Female ; Machine Learning ; Spleen ; Aged, 80 and over ; Kidney ; Medicine, Chinese Traditional

OBJECTIVE: This study examines utilizes the advantages of machine learning algorithms to discern key determinants in prognosticate postoperative circulatory complications (PCCs) for older patients. METHODS: This secondary analysis of data from a randomized controlled trial involved 1,720 elderly participants in five tertiary hospitals in Beijing, China. Participants aged 60-90 years undergoing major non-cardiac surgery under general anesthesia. The primary outcome metric of the study was the occurrence of PCCs, according to the European Society of Cardiology and the European Society of Anaesthesiology diagnostic criteria. The analysis metrics contained 67 candidate variables, including baseline characteristics, laboratory tests, and scale assessments. RESULTS: Our feature selection process identified key variables that significantly impact patient outcomes, including the duration of ICU stay, surgery, and anesthesia; APACHE-II score; intraoperative average heart rate and blood loss; cumulative opioid use during surgery; patient age; VAS-Move-Median score on the 1st to 3rd day; Charlson comorbidity score; volumes of intraoperative plasma, crystalloid, and colloid fluids; cumulative red blood cell transfusion during surgery; and endotracheal intubation duration. Notably, our Random Forest model demonstrated exceptional performance with an accuracy of 0.9872. CONCLUSION We have developed and validated an algorithm for predicting PCCs in elderly patients by identifying key risk factors.
Aged ; Aged, 80 and over ; Female ; Humans ; Male ; Middle Aged ; Cardiovascular Diseases/etiology* ; Machine Learning ; Postoperative Complications/etiology* ; Risk Factors ; Randomized Controlled Trials as Topic ; Secondary Data Analysis

OBJECTIVE: To identify the key features of facial and tongue images associated with anemia in female populations, establish anemia risk-screening models, and evaluate their performance. METHODS: A total of 533 female participants (anemic and healthy) were recruited from Shuguang Hospital. Facial and tongue images were collected using the TFDA-1 tongue and face diagnosis instrument. Color and texture features from various parts of facial and tongue images were extracted using Face Diagnosis Analysis System (FDAS) and Tongue Diagnosis Analysis System version 2.0 (TDAS v2.0). Least Absolute Shrinkage and Selection Operator (LASSO) regression was used for feature selection. Ten machine learning models and one deep learning model (ResNet50V2 + Conv1D) were developed and evaluated. RESULTS: Anemic women showed lower a-values, higher L- and b-values across all age groups. Texture features analysis showed that women aged 30-39 with anemia had higher angular second moment (ASM)and lower entropy (ENT) values in facial images, while those aged 40-49 had lower contrast (CON), ENT, and MEAN values in tongue images but higher ASM. Anemic women exhibited age-related trends similar to healthy women, with decreasing L-values and increasing a-, b-, and ASM-values. LASSO identified 19 key features from 62. Among classifiers, the Artificial Neural Network (ANN) model achieved the best performance [area under the curve (AUC): 0.849, accuracy: 0.781]. The ResNet50V2 model achieved comparable results [AUC: 0.846, accuracy: 0.818]. CONCLUSION Differences in facial and tongue images suggest that color and texture features can serve as potential TCM phenotype and auxiliary diagnostic indicators for female anemia.
Humans ; Female ; Tongue/diagnostic imaging* ; Adult ; Anemia/diagnosis* ; Middle Aged ; Face/diagnostic imaging* ; Young Adult ; Machine Learning

Objective To observe the efficacy and safety of Morinda officinalis oligosaccharides in the continuation treatment of mild and moderate depression.Methods An open,single-arm,multi-center design was adopted in our study.Adult patients with mild and moderate depression who had received acute treatment of Morinda officinalis oligosaccharides were enrolled and continue to receive Morinda officinalis oligosaccharides capsules for 24 weeks,the dose remained unchanged during continuation treatment.The remission rate,recurrence rate,recurrence time,and the change from baseline to endpoint of Hamilton Depression Scale(HAMD),Hamilton Anxiety Scale(HAMA),Clinical Global Impression-Severity(CGI-S)and Arizona Sexual Experience Scale(ASEX)were evaluated.The incidence of treatment-related adverse events was reported.Results The scores of HAMD-17 at baseline and after treatment were 6.60±1.87 and 5.85±4.18,scores of HAMA were 6.36±3.02 and 4.93±3.09,scores of CGI-S were 1.49±0.56 and 1.29±0.81,scores of ASEX were 15.92±4.72 and 15.57±5.26,with significant difference(P＜0.05).After continuation treatment,the remission rate was 54.59％(202 cases/370 cases),and the recurrence rate was 6.49％(24 cases/370 cases),the recurrence time was(64.67±42.47)days.The incidence of treatment-related adverse events was 15.35％(64 cases/417 cases).Conclusion Morinda officinalis oligosaccharides capsules can be effectively used for the continuation treatment of mild and moderate depression,and are well tolerated and safe.

Objective Viral encephalitis is an infectious disease severely affecting human health.It is caused by a wide variety of viral pathogens,including herpes viruses,flaviviruses,enteroviruses,and other viruses.The laboratory diagnosis of viral encephalitis is a worldwide challenge.Recently,high-throughput sequencing technology has provided new tools for diagnosing central nervous system infections.Thus,In this study,we established a multipathogen detection platform for viral encephalitis based on amplicon sequencing. Methods We designed nine pairs of specific polymerase chain reaction(PCR)primers for the 12 viruses by reviewing the relevant literature.The detection ability of the primers was verified by software simulation and the detection of known positive samples.Amplicon sequencing was used to validate the samples,and consistency was compared with Sanger sequencing. Results The results showed that the target sequences of various pathogens were obtained at a coverage depth level greater than 20×,and the sequence lengths were consistent with the sizes of the predicted amplicons.The sequences were verified using the National Center for Biotechnology Information BLAST,and all results were consistent with the results of Sanger sequencing. Conclusion Amplicon-based high-throughput sequencing technology is feasible as a supplementary method for the pathogenic detection of viral encephalitis.It is also a useful tool for the high-volume screening of clinical samples.

OBJECTIVE: To determine the role of Tripterygium wilfordii multiglycoside (TGW) in the treatment of psoriatic dermatitis from a cellular immunological perspective. METHODS: Mouse models of psoriatic dermatitis were established by imiquimod (IMQ). Twelve male BALB/c mice were assigned to IMQ or IMQ₊TGW groups according to a random number table. Histopathological changes in vivo were assessed by hematoxylin and eosin staining. Ratios of immune cells and cytokines in mice, as well as PAM212 cell proliferation in vitro were assessed by flow cytometry. Pro-inflammatory cytokine expression was determined using reverse transcription quantitative polymerase chain reaction. RESULTS: TGW significantly ameliorated the severity of IMQ-induced psoriasis-like mouse skin lesions and restrained the activation of CD45⁺ cells, neutrophils and T lymphocytes (all P<0.01). Moreover, TGW significantly attenuated keratinocytes (KCs) proliferation and downregulated the mRNA levels of inflammatory cytokines including interleukin (IL)-17A, IL-23, tumor necrosis factor α, and chemokine (C-X-C motif) ligand 1 (P<0.01 or P<0.05). Furthermore, it reduced the number of γ δ T17 cells in skin lesion of mice and draining lymph nodes (P<0.01). CONCLUSIONS TGW improved psoriasis-like inflammation by inhibiting KCs proliferation, as well as the associated immune cells and cytokine expression. It inhibited IL-17 secretion from γ δ T cells, which improved the immune-inflammatory microenvironment of psoriasis.
Male ; Animals ; Mice ; Tripterygium ; Psoriasis/drug therapy* ; Keratinocytes ; Skin Diseases/metabolism* ; Cytokines/metabolism* ; Imiquimod/metabolism* ; Dermatitis/pathology* ; Disease Models, Animal ; Mice, Inbred BALB C ; Skin/metabolism*