Drug development encompasses multiple processes, wherein protein subcellular localization is essential. It promotes target identification, treatment development, and the design of drug delivery systems. In this research, a deep learning framework called LocPro is presented for predicting protein subcellular localization. Specifically, LocPro is unique in (a) combining protein representations from the pre-trained large language model (LLM) ESM2 and the expert-driven tool PROFEAT, (b) implementing a hybrid deep neural network architecture that integrates convolutional neural network (CNN), fully connected (FC) layer, and bidirectional long short-term memory (BiLSTM) blocks, and (c) developing a multi-label framework for predicting protein subcellular localization at multiple granularity levels. Additionally, a dataset was curated and divided using a homology-based strategy for training and validation. Comparative analyses show that LocPro outperforms existing methods in sequence-based multi-label protein subcellular localization prediction. The practical utility of this framework is further demonstrated through case studies on drug target subcellular localization. All in all, LocPro serves as a valuable complement to existing protein localization prediction tools. The web server is freely accessible at https://idrblab.org/LocPro/.

OBJECTIVE: To identify the optimal machine learning algorithm for predicting post-stroke epilepsy (PSE) within one year following acute stroke, establish a nomogram model based on this algorithm, and perform external validation to achieve accurate prediction of secondary epilepsy. METHODS: A total of 870 acute stroke patients admitted to the emergency department of Xiang'an Hospital of Xiamen University from June 2019 to June 2023 were enrolled for model development (model group). An external validation cohort of 435 acute stroke patients admitted to the Fifth Hospital of Xiamen during the same period was used to validate the machine learning algorithms and nomogram model. Patients were classified into control and epilepsy groups based on the development of PSE within one year. Clinical and laboratory data, including baseline characteristics, stroke location, vascular status, complications, hematologic parameters, and National Institutes of Health Stroke Scale (NIHSS) score, were collected for analysis. Nine machine learning algorithms such as logistic regression, CN2 rule induction, K-nearest neighbors, adaptive boosting, random forest, gradient boosting, support vector machine, naive Bayes, and neural network were applied to evaluate predictive performance. The area under the curve (AUC) of receiver operator characteristic curve (ROC curve) was used to identify the optimal algorithm. Logistic regression was used to screen risk factors for PSE, and the top 10 predictors were selected to construct the nomogram model. The predictive performance of the model was evaluated using the ROC curve in both the model and validation groups. RESULTS: Among the 870 patients in the model group, 29 developed PSE within one year. Among the nine algorithms tested, logistic regression demonstrated the best performance and generalizability, with an AUC of 0.923. Univariate logistic regression identified several risk factors for PSE, including platelet count, white blood cell count, red blood cell count, glycated hemoglobin (HbA1c), C-reactive protein (CRP), triglycerides, high-density lipoprotein (HDL), aspartate aminotransferase (AST), alanine aminotransferase (ALT), activated partial thromboplastin time (APTT), thrombin time, D-dimer, fibrinogen, creatine kinase (CK), creatine kinase-MB (CK-MB), lactate dehydrogenase (LDH), serum sodium, lactic acid, anion gap, NIHSS score, brain herniation, periventricular stroke, and carotid artery plaque. Further multivariate logistic regression analysis showed that white blood cell count, HDL, fibrinogen, lactic acid and brain herniation were independent risk factors [odds ratio (OR) were 1.837, 198.039, 47.025, 11.559, 70.722, respectively, all P < 0.05]. In the external validation group, univariate logistic regression analysis showed that platelet count, white blood cell count, CRP, triacylglycerol, APTT, D-dimer, fibrinogen, CK, CK-MB, LDH, NIHSS score, and cerebral herniation were risk factors for PSE one year after acute stroke. Further multiple logistic regression analysis showed that APTT and cerebral herniation were independent predictors (OR were 0.587 and 116.193, respectively, both P < 0.05). The nomogram model, constructed using 10 key variables-brain herniation, periventricular stroke, carotid artery plaque, white blood cell count, triglycerides, thrombin time, D-dimer, serum sodium, lactic acid, and NIHSS score-achieved an AUC of 0.908 in the model group and 0.864 in the external validation group. CONCLUSIONS The logistic regression-based prediction model for epilepsy one year after acute stroke, developed using machine learning algorithms, showed optimal predictive performance. The nomogram model based on the logistic regression-derived predictors showed strong discriminative power and was successfully validated externally, suggesting favorable clinical applicability and generalizability.
Humans ; Machine Learning ; Stroke/complications* ; Nomograms ; Epilepsy/etiology* ; Algorithms ; Male ; Female ; Logistic Models ; Middle Aged ; Aged ; Risk Factors ; Bayes Theorem

DNA methylation,a crucial biochemical process within the human body,fundamentally alters gene expression without modifying the DNA sequence,resulting in stable changes.The changes in DNA methylation are closely related to numerous biological processes including cellular proliferation and differentiation,embryonic development,and the occurrence of immune diseases and tumor.Specifically,abnormal DNA methylation plays a crucial role in the formation,progression,and prognosis of chronic myeloid leukemia(CML).Moreover,DNA methylation offers substantial potential for diagnosing and treating CML.Accordingly,understanding the precise mechanism of DNA methylation,particularly abnormal changes in the methylation of specific genes in CML,can potentially promote the development of novel targeted therapeutic strategies.Such strategies could transform into clinical practice,effectively aiding diagnosis and treatment of CML patients.

Objective: QL1604 is a highly selective, humanized monoclonal antibody against programmed death protein 1. We assessed the efficacy and safety of QL1604 plus chemotherapy as first-line treatment in patients with advanced cervical cancer. Methods: This was a multicenter, open-label, single-arm, phase II study. Patients with advanced cervical cancer and not previously treated with systemic chemotherapy were enrolled to receive QL1604 plus paclitaxel and cisplatin/carboplatin on day 1 of each 21-day cycle for up to 6 cycles, followed by QL1604 maintenance treatment. Results: Forty-six patients were enrolled and the median follow-up duration was 16.5 months. An 84.8% of patients had recurrent disease and 13.0% had stage IVB disease. The objective response rate (ORR) per Response Evaluation Criteria in Advanced Solid Tumors (RECIST) v1.1 was 58.7% (27/46). The immune ORR per immune RECIST was 60.9% (28/46).The median duration of response was 9.6 months (95% confidence interval [CI]=5.5–not estimable). The median progression-free survival was 8.1 months (95% CI=5.7–14.0). Fortyfive (97.8%) patients experienced treatment-related adverse events (TRAEs). The most common grade≥3 TRAEs (>30%) were neutrophil count decrease (50.0%), anemia (32.6%), and white blood cell count decrease (30.4%). Conclusion QL1604 plus paclitaxel-cisplatin/carboplatin showed promising antitumor activity and manageable safety profile as first-line treatment in patients with advanced cervical cancer. Programmed cell death protein 1 inhibitor plus chemotherapy may be a potential treatment option for the patient population who have contraindications or can’t tolerate bevacizumab, which needs to be further verified in phase III confirmatory study.

With the progress of society and the continuous improvement of people′s living standards in China, the public′s demand for medical services is becoming increasingly diversified. How to move hospital services forward and improve medical services centered on patients has become a key consideration for hospitals to enhance patients′ sense of medical satisfaction. A certain hospital has established a one-stop patient service hotline, integrating functions such as number inquiry, medical consultation, appointment registration, appointment examination, praise and suggestions, complaint follow-up, etc., injecting a complaint handling management mode, and responding to and solving patient feedback problems in a timely manner. Since the launch of the patient service hotline, it has effectively solved the problems that patients encountered during their visits, effectively reduced the hospital′s complaint rate, and initially formed a service closed-loop management. From March to October 2023, the demand ratio of the 12345 hotline in the hospital has continuously decreased, and was significantly lower than the average level of 22 municipal hospitals in Beijing. In the future, we should further improve the communication skills between doctors and patients, focus on managing appeals and services, and continue to strengthen proactive governance.

Objective:To investigate the role of p-AKT-mTOR-P70S6K signaling pathway in radiation therapy for polyploid cervical cancer cells.Methods:Human cervical cancer HeLa cell lines were selected and HeLa cells were radiated under 7 Gy of 6 MV X-ray. The morphological changes of the cells were observed with an inverted microscope on day 5 after radiation induction. All cells were divided into the 7 Gy group (7 Gy X-ray radiation but not transfected polyploidy HeLa cells) and the control group (the non-radiation-induced and not transfected HeLa cells). In addition, the plasmid carrying pcDNA3 negative control sequence and the plasmid carrying pcDNA3-TT-AKT sequence were transfected into HeLa cells, respectively, which were induced by 7 Gy X-ray radiation after 48 h of transfection, and then they were recorded as the pcDNA3 + 7 Gy group and the pcDNA3-TT-AKT + 7 Gy group. Cell proliferation ability was detected by using CCK-8 assay, cell cycle was detected by using flow cytometry, cell apoptosis was detected by using mitochondrial membrane potential assay, the relative expression levels of cell proliferation, cell cycle, apoptosis and autophagy related proteins were tested by using Western blot.Results:Most of the normal HeLa cells in the 7 Gy group died on day 5 after radiation induction, and only a few surviving cells increased in size with multiple nuclei. The results of Western blot showed that the relative expression levels of p-AKT, p-mTOR and p-P70S6K in HeLa cells of the 7 Gy group were lower than those of the control group (all P < 0.05). CCK-8 assay showed that the absorbance ( A) values were 0.45±0.06, 0.65±0.06 after 48 h of culture and 0.75±0.05, 1.05±0.02 after 72 h of culture, respectively in the pcDNA3 + 7 Gy group and the pcDNA3-TT-AKT + 7 Gy group, and the differences were statistically significant (all P < 0.05), and the A values in the pcDNA3-TT-AKT + 7 Gy group were all higher than those in the pcDNA3 +7 Gy group. Flow cytometry results showed that the proportion of cells was (29.2±3.6)%, (26.7±1.7)% in G 0/G 1 phase and (29.6±1.6)%, (30.3±0.6)% in G 2/M phase, respectively in the pcDNA3 + 7 Gy group and the pcDNA3-TT-AKT + 7 Gy group, and the differences were not statistically significant (all P > 0.05); the proportion of cells in S phase was (10.2±0.9)% and (14.6±1.5)%, respectively in the pcDNA3 + 7 Gy group and the pcDNA3-TT-AKT + 7 Gy group, and the differences were statistically significant ( t = 2.86, P = 0.043). Mitochondrial membrane potential assay showed that the green fluorescence proportion was (23.1±2.5)% and (14.3±1.9)%, respectively in the pcDNA3 + 7 Gy group and the pcDNA3-TT-AKT + 7 Gy group, and the different was statistically significant ( t = 4.82, P = 0.009). Western blot results showed that the relative expression level of p-cdc25c (Ser216) in the pcDNA3-TT-AKT+7 Gy group was higher than that in the pcDNA3+7 Gy group ( P < 0.001); and the relative expression levels of Bak and LC3-Ⅱ/Ⅰ in the pcDNA3-TT-AKT+7Gy group were lower than those in the pcDNA3 +7 Gy group, respectively (all P < 0.05). Conclusions:The p-AKT-mTOR-P70S6K signaling pathway may be involved in the regulation of radiation-induced polyploidy HeLa cell proliferation, cell cycle and cell apoptosis.

Objective:To construct an evidence-based prediction model for early recurrence after surgery of hepatocellular carcinoma (HCC) based on Meta-analysis and to do external validation study.Methods:The literatures in Chinese National Knowledge Infrastructure, Wanfang, VIP, Chinese Science Citation Database (CSCD), Chinese Social Science Citation System (CCSCI), PubMed, Web of Science and IEEE databases between January 2019 and December 2023 were searched based on the subject words. According to the inclusion and exclusion criteria, 9 literatures were included to screen the risk factors affecting the early recurrence of HCC. When the same risk factor was found in ≥5 included literatures, Meta-analysis was performed by using Review Manager 5.4.1 software. External validation data were collected from 401 patients with primary HCC who underwent surgery in Liaoning Cancer Hospital between March 2014 and March 2017. The patients were divided into early recurrence group (176 cases) and early non-recurrence group (225 cases) according to whether they relapsed 2 years after surgery. The OR values of all risk factors obtained in the Meta-analysis were converted into modeling, and postoperative early recurrence rate of HCC in the Meta-analysis was used to calculate β 0, and finally the logistic model was obtained. The OR value was incorporated into the logit (P) model, and the morbidity (P) of the external validation data was calculated. Taking the recurrence 2 years after surgery or not as the dependent variable and P as the independent variable, the receiver operating characteristic (ROC) curve was drawn to calculate the area under the curve (AUC). Results:A total of 8 risk factors for early HCC recurrence were screened out from 9 literatures (x 1: alpha-fetoprotein ≥ 400 ng/ml; x 2: tumor number ≥ 2; x 3: the longest tumor diameter ≥ 5 cm; x 4: Barcelona staging B-C; x 5: microvascular invasion; x 6: moderate to low differentiation; x 7: incomplete capsule; x 8: nonanatomic hepatectomy). The Meta-analysis included 1 757 HCC cases, with 960 postoperative early recurrences and an early recurrence rate of 45.36%, finally the β 0 value was -0.201. The predictive model for 2-year recurrence of HCC was constructed and calculated as logit (P) = -0.201+0.835x 1+0.905x 2+0.783x 3+1.008x 4+0.765x 5+0.831x 6+1.533x 7+0.940x 8. Analysis of variance by external validation data showed that the differences in ascites, alpha-fetoprotein, tumor number, tumor diameter, Barcelona staging, microvascular invasion, tumor differentiation degree, capsule invasion, resection type, and systemic inflammation index were statistically significant between early recurrence group and early non-recurrence group (all P < 0.05). ROC curve analysis showed that AUC of postoperative early recurrence of HCC predicted by the model was 0.718, (95% CI: 0.689-0.753), the optimal cut-off value was 3.11, the Yoden index was 0.288, the sensitivity was 69.32%, and the specificity was 69.56%. Conclusions:The evidence-based prediction model constructed based on Meta-analysis for postoperative early recurrence of HCC has a high predictive value. However, further verification and optimization with big data is still needed.

Objective: QL1604 is a highly selective, humanized monoclonal antibody against programmed death protein 1. We assessed the efficacy and safety of QL1604 plus chemotherapy as first-line treatment in patients with advanced cervical cancer. Methods: This was a multicenter, open-label, single-arm, phase II study. Patients with advanced cervical cancer and not previously treated with systemic chemotherapy were enrolled to receive QL1604 plus paclitaxel and cisplatin/carboplatin on day 1 of each 21-day cycle for up to 6 cycles, followed by QL1604 maintenance treatment. Results: Forty-six patients were enrolled and the median follow-up duration was 16.5 months. An 84.8% of patients had recurrent disease and 13.0% had stage IVB disease. The objective response rate (ORR) per Response Evaluation Criteria in Advanced Solid Tumors (RECIST) v1.1 was 58.7% (27/46). The immune ORR per immune RECIST was 60.9% (28/46).The median duration of response was 9.6 months (95% confidence interval [CI]=5.5–not estimable). The median progression-free survival was 8.1 months (95% CI=5.7–14.0). Fortyfive (97.8%) patients experienced treatment-related adverse events (TRAEs). The most common grade≥3 TRAEs (>30%) were neutrophil count decrease (50.0%), anemia (32.6%), and white blood cell count decrease (30.4%). Conclusion QL1604 plus paclitaxel-cisplatin/carboplatin showed promising antitumor activity and manageable safety profile as first-line treatment in patients with advanced cervical cancer. Programmed cell death protein 1 inhibitor plus chemotherapy may be a potential treatment option for the patient population who have contraindications or can’t tolerate bevacizumab, which needs to be further verified in phase III confirmatory study.

Objective To investigate the effects and potential mechanisms of Marsdeniae Tenacissimae Caulis(Tongguanteng)injection and extract in human osteosarcoma cells proliferation,migration,invasion,and apoptosis.Methods MNNG/HOS,Saos-2 osteosarcoma cells,and normal bone marrow mesenchymal stem cells(BMSC)were cultured in vitro.Cells were incubated with different concentrations of Tongguanteng injection and Tongguanteng extract(40,60,80 mg/mL).Cell proliferation was evaluated by CCK-8 assay and plate colony formation assay.Cell migration and invasion were evaluated by scratch assay and Transwell assay.Cell apoptosis was evaluated by Hoechst33342 staining and Annexin-V/PI double staining assay.Bax,Bcl-2 and Caspase-3 mRNA expression were detected using RT-qPCR.The protein expressions of JAK1,p-JAK1,STAT3,p-STAT3 and MMP9 were detected by Western blot.Results Compared with the control group,both Tongguanteng injection and extract significantly decreased the survival rate of MNNG/HOS and Saos-2 cells,inhibited cell clone formation,migration,and invasion,induced cell apoptosis(P<0.05,P<0.01),promoted Bax mRNA and protein expression,inhibited Bcl-2 mRNA and protein expression,and up-regulated Caspase-3 mRNA and Cleaved Caspase-3 protein expression.Tongguanteng injection could significantly down-regulate the expressions of p-JAK1,p-STAT3 and MMP9 protein expression in Saos-2 cells(P<0.05,P<0.01).Conclusion Both Tongguanteng injection and Tongguanteng extract can significantly inhibit proliferation,migration and invasion of human osteosarcoma MNNG/HOS and Saos-2 cells,and induce apoptosis,with no significant difference in anti-tumor effect.The mechanism may be related to the inhibition of the activation of JAK1/STAT3 signaling pathway.

Objective: QL1604 is a highly selective, humanized monoclonal antibody against programmed death protein 1. We assessed the efficacy and safety of QL1604 plus chemotherapy as first-line treatment in patients with advanced cervical cancer. Methods: This was a multicenter, open-label, single-arm, phase II study. Patients with advanced cervical cancer and not previously treated with systemic chemotherapy were enrolled to receive QL1604 plus paclitaxel and cisplatin/carboplatin on day 1 of each 21-day cycle for up to 6 cycles, followed by QL1604 maintenance treatment. Results: Forty-six patients were enrolled and the median follow-up duration was 16.5 months. An 84.8% of patients had recurrent disease and 13.0% had stage IVB disease. The objective response rate (ORR) per Response Evaluation Criteria in Advanced Solid Tumors (RECIST) v1.1 was 58.7% (27/46). The immune ORR per immune RECIST was 60.9% (28/46).The median duration of response was 9.6 months (95% confidence interval [CI]=5.5–not estimable). The median progression-free survival was 8.1 months (95% CI=5.7–14.0). Fortyfive (97.8%) patients experienced treatment-related adverse events (TRAEs). The most common grade≥3 TRAEs (>30%) were neutrophil count decrease (50.0%), anemia (32.6%), and white blood cell count decrease (30.4%). Conclusion QL1604 plus paclitaxel-cisplatin/carboplatin showed promising antitumor activity and manageable safety profile as first-line treatment in patients with advanced cervical cancer. Programmed cell death protein 1 inhibitor plus chemotherapy may be a potential treatment option for the patient population who have contraindications or can’t tolerate bevacizumab, which needs to be further verified in phase III confirmatory study.