OBJECTIVES: Multiple myeloma (MM) is a hematologic malignancy characterized by clonal proliferation of plasma cells and remains incurable. Patients with primary refractory multiple myeloma (PRMM) show poor response to initial induction therapy. This study aims to develop a machine learning-based model to predict treatment response in newly diagnosed multiple myeloma (NDMM) patients, in order to optimize therapeutic strategies. METHODS: NDMM and post-treatment MM patients hospitalized in the Department of Hematology, Third Xiangya Hospital, Central South University, between August 2022 and July 2023 were enrolled. Post-treatment MM patients were categorized into PRMM patients and treatment-responsive MM (TRMM) patients based on therapeutic efficacy. Serum metabolites were detected and analyzed via metabolomics. Based on the metabolomics analysis results and combined with transcriptomic sequencing data of NDMM patients from databases, differentially expressed amino acid metabolism-related genes (AAMGs) among post-treatment NDMM patients with varying therapeutic outcomes were screened. Using bioinformatics analyses and machine learning algorithms, a predictive model for treatment response in NDMM was constructed and used to identify patients at risk for PRMM. RESULTS: A total of 61 patients were included: 22 NDMM, 23 TRMM, and 16 PRMM patients. Significant differences in metabolite levels were observed among the 3 groups, with differential metabolites mainly enriched in amino acid metabolism pathways. Follow-up data were available for 16 of the 22 NDMM patients, including 12 treatment responders (ND_TR group) and 4 with PRMM (ND_PR group). A total of 23 differential metabolites were identified between these 2 groups: 6 metabolites (e.g., tryptophan) were upregulated and 17 (e.g., citric acid) were downregulated in the ND_TR group. Transcriptomic data from 108 TRMM and 77 PRMM patients were analyzed to identify differentially expressed AAMGs, which were then used to construct a prediction model. The area under the receiver operating characteristic curve (AUC) for the model exceeded 0.8, and AUC values in 3 external validation cohorts were all above 0.7. CONCLUSIONS This study delineated the metabolic alterations in MM patients with different treatment response, suggesting that dysregulated amino acid metabolism may be associated with poor treatment response in PRMM. By integrating metabolomics and transcriptomics, a machine learning-based predictive model was successfully established to forecast treatment response in NDMM patients.
Humans ; Multiple Myeloma/drug therapy* ; Machine Learning ; Male ; Female ; Metabolomics/methods* ; Middle Aged ; Aged ; Treatment Outcome ; Transcriptome ; Computational Biology ; Adult ; Multiomics

Abstract: Objective To analyze the correlation between the thromboelastography (TEG) indexes and the indexes related to liver injury in patients with heat stroke, and explore the diagnostic value of TEG indexes for liver injury in patients with heat stroke. Methods A total of 95 patients with exertional heat stroke (EHS) admitted to 924 Hospital of the Joint Service Support Force of the People's Liberation Army of China from August 2020 to July 22 were selected, and divided into a non-liver injury group (55 cases) and a liver injury group (40 cases) according to whether there was liver injury. TEG instrument was used for the detection of thromboelastography to record the TEG parameters, including reaction time (R), agglutination time (K), α angle, maximum amplitude (MA value), and coagulation complex index (CI). The levels of glutamic transaminase (AST), alanine aminotransferase (ALT), total bilirubin (TBil), albumin (ALB) were detected by automatic biochemical analyzer. Pearson's method was applied to analyze the correlation between thromboelastography indexes R, K, α angle, CI and liver function indexes AST, ALT, TBil, ALB in patients with heat stroke after liver injury. Receiver operating characteristic curve (ROC) was applied to analyze the predictive value of thromboelastography indexes R, K, α angle, CI and combined detection for liver injury in patients with heat stroke. Results Compared with the non-liver injury group, the AST, ALT and TBil levels in patients with heat stroke in the liver injury group were higher (t=26.174, 16.923, 18.414, P<0.05), while the ALB level was lower (t=24.596, P<0.05); compared with the non-liver injury group, the R and K of patients with heat stroke in the liver injury group were higher (t=58.014, 52.862, P<0.05), and the α angle and CI were lower (t=46.853, 60.717, P<0.05); R was positively correlated with AST and ALT (r=0.532, 0.610, P<0.001), and negatively correlated with ALB (r=-0.551, P<0.001) in patients with heat stroke complicated with liver injury; K was positively correlated with AST, ALT and TBil (r=0.661, 0.531, 0.504, P<0.001); α angle was negatively correlated with AST and ALT (r=-0.473, -0.448, P<0.01), and positively correlated with ALB (r=0.539, P<0.001); CI was negatively correlated with AST, ALT and TBil (r=-0.458, -0.505, -0.549, P<0.001); the area under the curve (AUC) of thromboelastography indexes R, K, α angle and CI in predicting liver injury in patients with heat stroke was 0.807 (sensitivity of 70.0%, specificity of 81.6%), 0.831 (sensitivity of 77.5%, specificity of 85.5%), 0.747 (sensitivity of 67.5%, specificity of 74.5%), and 0.788 (sensitivity of 77.5%, specificity of 83.6%), respectively. The AUC of combined detection to predict liver injury in patients with heat stroke was 0.967 (sensitivity of 92.5%, specificity of 91.9%). Conclusions The thromboelastography indexes are correlated with the indexes related to liver injury in patients with heat stroke, and the thromboelastography indexes are helpful to diagnose liver injury in patients with heat stroke.

Fecal incontinence is a very common problem in critically ill and elderly patients and long-term hospitalized bedridden patients, which can easily cause complications such as perianal dermatitis, pressure ulcers and infections, increase patient suffering, and increase medical expenses. Devices that effectively transfer or drain feces are critical to reducing complications after fecal incontinence. This article uses this as a starting point to summarize the main components, current status of use and evaluation indicators of built-in drainage devices at home and abroad, which provides a reference for the development of more scientific and feasible auxiliary tools for fecal incontinence.

Objective: To investigate the roles and anti-cancer mechanism of artificially synthesized EGF-containing fibulin-like extracellular matrix protein (EFEMP1) derived tumor suppressor ZR30 protein in glioma (GBM). Methods: ZR30 protein were in vitro expressed using a wheat germ cell-free system. GBM cell lines (U251, U251NS, and U87) were cultured for 2-3 days in the presence or absence of ZR30 treatment. MMP-2 level was detected by gelatin zymography assay, moreover, the expression of EGFR, Notch-1 and p-Akt/Akt levels were determined by western blot. Additionally, MTT assay was used to measure ZR30′s effect on the cell proliferation of U251 and U251NS cells. Furthermore, pre-mixed U251-GFP and U251NS-RFP cells (1∶9) were injected into the brain of nude mice, and then ZR30 or PBS was injected into the intra-tumor after 10 and 21 days, respectively. Then DNA was extracted from the right brain of nude mice in each group. Comparative quantitative polymerase chain reaction (CQ-PCR) was used to examine the copy numbers of human gene hSPAG16, mouse gene mSpag16, GFP and RFP. The survival status of each group of nude mice was also observed. Results: The levels of activated MMP-2 in U87 and U251 cells were lower after 10, 50 and 100 ng/ml ZR30 treatment for 2-3 days. Western blot analysis showed that ZR30 treatment reduced the expression of EGFR, Notch-1 and p-Akt/Akt in U251 cells, and inhibited Notch-1 and p-Akt/Akt expression in U251NS cells, and then decreased the response of U251 cells to EGF stimulation. Moreover, ZR30 inhibited the cell proliferation of U251 and U251NS two days after exposure. The in vivo orthotopic GBM xenografts were successfully constructed. CQ-PCR results indicated that the hSPAG16/mSpag16 ratios of mice in PBS group and ZR30 treatment groups at 180, 700, and 1 800 ng dosages were 3.67±2.82, 1.18±0.97, 1.75±1.55 and 1.38±1.17, respectively, and ZR30 treatment groups showed significantly lower ratios than the PBS group (P<0.05 for all). Correspondingly, the ratios of GFP/RFP in each group were 1.97±0.80, 1.97±0.85, 1.48±0.71 and 1.73±0.77, respectively, showing no statistical significance (P>0.05 for all). When treatment was performed 10 d after cell implantation, and the median survival time of mice in PBS group and ZR30 group was 40.5 days and 59.0 days, respectively. When treatment was performed 21 d after cell implantation, the median survival time of mice in PBS group and ZR30 group was extended to 57.0 days and 74.5 days, respectively. The median survival time of ZR30 treatment groups significantly prolonged (P<0.05 for all). Conclusions ZR30 inhibits in vitro cell growth, invasion, angiogenesis and stemness maintenance in glioma via suppressing activated MMP-2, EGFR, p-Akt/Akt and Notch-1 proteins. In vivo, ZR30 markedly increased survival of mice harboring glioma xenografts, even for only one intra-tumoral injection at the time of early tumor formation. Overall, the in vivo and in vitro experiments supported the therapeutic potential of ZR30 for GBM.

Objective To study cervical human papillomavirus (HPV) infection and genotype distribution characteristics in patients with vaginal disease.Methods The PCR dot blot was used to carry out HPV detection of cervical exfoliated cells in 816 women with cervical lesions in the hospital, and 23 kinds of HPV genotypes were identified.Results Among the 816 cases receiving HPV type detection, HPV of 532 cases (65.20%) was positive, including 371 cases (69.74%) with low-risk HPV (HR-HPV) infection, 161 cases (30.26%) with low-risk HPV infection (LR-HPV) (P<0.05).The HPV infection rate below 45 years old was relatively higher.The HPV infection rate in patients with cervical cancer (97.10%) was higher than that in patients with cervical intraepithelial neoplasia (CIN) II -III (80.54%), patients with CIN Ⅰ(41.55%) and patients with cervicitis (17.20%) (P<0.05).The top five types of HPV infection were HPV16, 58, 18, 11 and 56 type, respectively.The single infection rate (79.70%) was higher than multiple infection rate (20.30%) (P<0.05); HR-HPV infection was the main infection in single infection, and double infection was the main infection in multiple infection.Conclusion Below 45 years old women are the high-risk groups of HPV infection.16, 58, 18, 11 and 56 are the main types of HPV infection.The infection rates of patients with cervical cancer and precancerous lesions are relatively higher.Paying attention to the screening of HPV infection has positive significance in the prevention and treatment of cervical cancer.