The glucagon receptor (GCGR) is a critical target for the treatment of metabolic disorders such as Type 2 Diabetes Mellitus (T2DM) and obesity. Activation of GCGR enhances systemic insulin sensitivity through paracrine stimulation of insulin secretion, presenting a promising avenue for treatment. However, the discovery of effective GCGR agonists remains a challenging and resource-intensive process, often requiring time-consuming wet-lab experiments to synthesize and screen potential compounds. Recent advances in artificial intelligence technologies have demonstrated great potential in accelerating drug discovery by streamlining screening and efficiently predicting bioactivity. In the present work, we propose DeepGCGR, a two-layer deep learning model that leverages graph convolutional networks (GCN) integrated with a multiple attention mechanism to expedite the identification of GCGR agonists. In the first layer, the model predicts the bioactivity of various compounds against GCGR, efficiently filtering large chemical libraries to identify promising candidates. In the second layer, DeepGCGR classifies high bioactive compounds based on their functional effects on GCGR signaling, identifying those with potential agonistic or antagonistic effects. Moreover, DeepGCGR was specifically applied to identify novel GCGR-regulating compounds for the treatment of T2DM from natural products derived from traditional Chinese medicine (TCM). The proposed method will not only offer an effective strategy for discovering GCGR-targeting compounds with functional activation properties but also provide new insights into the development of T2DM therapeutics.
Deep Learning ; Drug Discovery/methods* ; Humans ; Diabetes Mellitus, Type 2/metabolism* ; Medicine, Chinese Traditional ; Drugs, Chinese Herbal/pharmacology*

Both primary (e.g. osteosarcoma and Ewing sarcoma) and secondary (e.g. metastatic) bone cancers cause severe health problems and can lead to death. In recent years, radiopharmaceuticals have shown significant potential in the treatment of refractory bone diseases due to their unique targeting properties and low toxicity. Radiopharmaceutical therapy for bone cancer utilizes bone-seeking radiopharmaceuticals that target lesions through the high affinity of ethylenediaminetetramethylenephosphonic acid (EDTMP) ligand for bone hydroxyapatite. Traditional therapeutic agents such as ⁸⁹Sr and ¹⁵³Sm-EDTMP, administered via intravenous injection, accumulate in bone metastases and release beta rays to kill tumor cells. These agents can relieve pain and inhibit bone destruction; however, they have limited ability to shrink tumor volume or slow tumor growth (tumor volume reduction rate < 30%). Furthermore, these agents may cause systemic side effects, and existing evidence does not support their effectiveness in prolonging survival. The development of palliative bone pain therapies based on novel radiopharmaceuticals may overcome these limitations and improve the quality of life for patients during their remaining lifespan. Researchers have investigated the combination of various beta- and alpha-emitters with novel radionuclide carrier systems, significantly enhancing treatment precision in bone tumor models. For instance, ¹⁷⁷Lu-EDTMP (beta ray 0.497 MeV, half-life 6.7 days) enabled 66% of patients to completely discontinue analgesics by the twelfth week. ¹⁸⁶Re- and ¹⁸⁸Re-hydroxyethylidene diphosphonate, by targeting hydroxyapatite, achieved a pain relief rate of up to 90% and significantly prolonged median survival. These agents caused only reversible hematological toxicity, with no Grade III/IV bone marrow suppression events, and significantly reduced tumor volume. Additionally, the alpha nuclide ²²³RaCl₂ induces DNA breaks in tumor cells and inhibits osteoblast-osteoclast imbalance. When combined with best supportive care, it can extend overall survival by 3.6 months (14.9 months vs. 11.3 months), reduce the risk of death by 30%, and lead to significant tumor volume reduction. However, bone marrow toxicity management, cost-effectiveness balance, and the design of multimodal combination regimens remain key challenges.

Objective: To estimate the epidemic threshold and graded intensity thresholds of influenza in Zhejiang Province from 2012 to 2023 using the moving epidemic method (MEM), and evaluate the intensity of influenza epidemics, so as to provide the reference for influenza prevention and control in Zhejiang Province. Methods: The positive rates of influenza virus per week during the influenza epidemic seasons (from 40th week to 20th week of the following year) in Zhejiang Province from 2012 to 2022 were collected through the Chinese Influenza Surveillance Information System. A MEM model was established and optimized using cross-validation. The maximum accumulated rates percentage was used to divide the epidemic into pre-epidemic, epidemic, and post-epidemic periods, and to estimate the epidemic thresholds and graded intensity thresholds. The intensity of influenza epidemics in Zhejiang Province during the 2022-2023 epidemic season were assessed. Results: The positive rates of influenza virus in five epidemic seasons from 2012 to 2022 were included in the model. The MEM model performed best when the parameter δ was set to 1.5, with a sensitivity of 0.971, a specificity of 0.745, and a Youden's index of 0.716. According to the model analysis, the epidemic beginning and ending thresholds of influenza in Zhejiang Province during the 2022-2023 epidemic season were 19.32% and 10.92%, respectively, and the medium, high, and extremely high intensity thresholds were 48.65%, 63.49%, and 68.47%, respectively. During 2022-2023, the influenza epidemic was in the pre-epidemic period from the 40th week in 2022 to the 7th week in 2023; the epidemic period was from the 8th to the 18th week, the epidemic intensity was low in the 8th week and increased to a high level in the 9th week, and reached to a extremely high level from the 10th to the 13th week, then fell to the high and the medium level in the 14th week and 15th week, respectively, and fell to a low level from the 16th to the 18th week; the influenza epidemic entered the post-epidemic period since the 19th week. Conclusion MEM could be applied for evaluation of influenza epidemic intensity, providing the reference for early identification and taking graded preventive and control measures.

Objective:To evaluate the impact of colonoscopy on the incidence of colorectal cancer (CRC).Methods:This study was based on the Screening Project of Early Diagnosis and Treatment of CRC in Jiashan county, Zhejiang province. After excluding participants with incomplete information, these with individual history of CRC, those with CRC, enteritis or ulcer, noticed through colonoscopy exam at baseline, a total of 25 894 participants were finally included. Cox proportional hazards regression model was used to analyze the association between colonoscopy and the incidence of CRC.Results:This study was followed up for 160 113 person-years with a median of 5.67 years. During the follow-up period, 127 of them developed the CRC. The incidence rates of CRC in participants, were 202.35 per 100 000 person-years, 40.93 per 100 000 person-years and 63.62 per 100 000 person-years, respectively among the following three groups: who did not take the colonoscopy, without colorectal lesions or with benign colorectal lesions noticed by the colonoscopy and the differences were statistically significant ( P<0.05). After adjusting for potential confounding factors, the HRs(95 %CI) of CRC were 0.24 (0.16-0.36) and 0.29 (0.17-0.49), among those who did not have or had colorectal lesions in the participants who underwent the colonoscopy. Stratified by anatomic site, age and sex, results showed that the associations among the aforementioned groups were relatively stable. Conclusion:Colonoscopy could effectively contribute to the reduction of CRC incidence in the high-risk population.

Objective:To analysis clinical curative effect of laparoscopic radical prostatectomy bladder cancer and influence on serum levels of ferritin (SF),soluble interleukin-2 receptor (SIL-2 R) and rumor specific growth factor (TSGF).Methods:98 cases of bladder cancer who were treated in our hospital from August 2012 to February 2016 were selected and randomly divided into the control group 0=49) and the research group (n=49).The patients in the control group were treated with open radical radical cystectomy,while the patients in the research group were treated with laparoscopic radical cystectomy.Then the operation time,intraoperative blood loss,anal exhaust time,hospitalization,the lymph node cleaning,the serum levels of SF,SIL-2R,TSGF,white blood cells and cortisol,the complications and recurrence rate in the two groups were observed and compared.Results:The operation time of research group was longer than that of the control group,while the intraoperative blood loss,the hospitalization and the anal exhaust time were less than those of the control group,and the differences were statistically significant (P＜0.05).There was no statistically significant difference about the numbers of the lymph node and the recurrence rate between two groups (P＜0.05).After treatment,the serum levels of SF,SIL-2R and TSGF in the two groups decreased,while there was no statistically significant difference between the two groups (P＞0.05);After treatment,the white blood cell count and cortisol rise in the two groups increased,while the research group was lower than that of the control group (P＜0.05).Conclusion:LRC and ORC clinical efficacy similar,both of which can reduce the serum levels of SF,SIL-2R and TSGF of patients with laparoscopic radical prostatectomy bladder cancer.