Objective:To explore the construction and validation of a nomogram model for predicting poor survival prognosis in patients with clear cell renal cell carcinoma（ccRCC）based on deep learning of pathological images.Methods:This study was an observational cohort study. The original pathological images and clinicopathological data（TCGA cohort）of 378 patients with ccRCC were obtained from the Cancer Genome Atlas Database（TCGA）for model training. A total of 301 patients with ccRCC who underwent surgical treatment at Renji Hospital Affiliated to Shanghai Jiaotong University School of Medicine from January 2010 to December 2020（Renji cohort）and 214 patients with ccRCC who underwent surgical treatment at the First People’s Hospital Affiliated to Shanghai Jiaotong University School of Medicine from January 2012 to December 2018（General cohort）were included for model validation. Their original pathological images and clinical pathological data were collected. A clustering-constrained attention and multi-instance learning method was used to accurately identify sub-regions of the images to classify and extract features of the pathological images. A deep learning-based disease-free survival prognosis prediction model（DL-DFS）was constructed through a weakly supervised learning strategy. The clinical pathological features and DL-DFS were further combined to construct a nomogram model for the clinical prognosis of ccRCC patients. Univariate and multivariate Cox regression analyses were employed to evaluate the independent risk factors for disease-free survival（DFS）. The efficacy of the predictive model were evaluated by the receiver operating characteristic curve（ROC）with area under the curve（AUC），respectively. Survival analysis was conducted using the Kaplan-Meier curve.Results:DL-DFS could accurately predict the DFS status of ccRCC patients in 5 years after surgery. Through ROC analysis in the training cohort，the AUC value reached 0.75（ P < 0.001）. In the Renji cohort and the General cohort，the AUC values were 0.65（ P < 0.001）and 0.81（ P < 0.001），respectively. Through Kaplan-Meier survival analysis，we found that DL-DFS could identify ccRCC patients with high survival risks. The hazard ratio in the training cohort was 3.86（95% CI 2.36-6.30， P < 0.001）. The hazard ratio in the Renji cohort and General cohort were 1.97（95% CI 1.03-3.80， P = 0.009）and 4.66（95% CI 1.80-12.06， P = 0.008），respectively. Univariate and multivariate Cox regression analyses indicated that DL-DFS risk score，tumor grade，and tumor stage could act as prognostic risk factors for patients with ccRCC（ P < 0.05）. Considering that age was a common prognostic risk factor for patients with renal cancer，a nomogram model was constructed by combining the DL-DFS risk score with patient age，tumor grade，and tumor stage. The AUC of this model for predicting the 5-year DFS of ccRCC patients after surgery was 0.87，which was significantly higher than that of DL-DFS（AUC = 0.74），tumor stage（AUC = 0.84），tumor grade（AUC = 0.72），and patient age（AUC = 0.56）in the TCGA cohort（all P<0.05）. In the Renji cohort and the General cohort，the AUC of the nomogram model were 0.78 and 0.86 respectively，which was significantly higher than that of DL-DFS（0.65 and 0.81），tumor stage（0.72 and 0.69），tumor grade（0.64 and 0.77），and patient age（0.56 and 0.63）. Conclusions:In this study a DL-DFS for ccRCC patients was constructed. Then a nomogram model was constructed by combining the DL-DFS risk value with patient age，tumor grade，and tumor stage. This nomogram model demonstrated superior predictive performance compared to DL-DFS alone in evaluating the DFS prognosis of ccRCC patients，which still needs to be further verified in prospective clinical studies.

Objective:To explore the construction and validation of a nomogram model for predicting poor survival prognosis in patients with clear cell renal cell carcinoma（ccRCC）based on deep learning of pathological images.Methods:This study was an observational cohort study. The original pathological images and clinicopathological data（TCGA cohort）of 378 patients with ccRCC were obtained from the Cancer Genome Atlas Database（TCGA）for model training. A total of 301 patients with ccRCC who underwent surgical treatment at Renji Hospital Affiliated to Shanghai Jiaotong University School of Medicine from January 2010 to December 2020（Renji cohort）and 214 patients with ccRCC who underwent surgical treatment at the First People’s Hospital Affiliated to Shanghai Jiaotong University School of Medicine from January 2012 to December 2018（General cohort）were included for model validation. Their original pathological images and clinical pathological data were collected. A clustering-constrained attention and multi-instance learning method was used to accurately identify sub-regions of the images to classify and extract features of the pathological images. A deep learning-based disease-free survival prognosis prediction model（DL-DFS）was constructed through a weakly supervised learning strategy. The clinical pathological features and DL-DFS were further combined to construct a nomogram model for the clinical prognosis of ccRCC patients. Univariate and multivariate Cox regression analyses were employed to evaluate the independent risk factors for disease-free survival（DFS）. The efficacy of the predictive model were evaluated by the receiver operating characteristic curve（ROC）with area under the curve（AUC），respectively. Survival analysis was conducted using the Kaplan-Meier curve.Results:DL-DFS could accurately predict the DFS status of ccRCC patients in 5 years after surgery. Through ROC analysis in the training cohort，the AUC value reached 0.75（ P < 0.001）. In the Renji cohort and the General cohort，the AUC values were 0.65（ P < 0.001）and 0.81（ P < 0.001），respectively. Through Kaplan-Meier survival analysis，we found that DL-DFS could identify ccRCC patients with high survival risks. The hazard ratio in the training cohort was 3.86（95% CI 2.36-6.30， P < 0.001）. The hazard ratio in the Renji cohort and General cohort were 1.97（95% CI 1.03-3.80， P = 0.009）and 4.66（95% CI 1.80-12.06， P = 0.008），respectively. Univariate and multivariate Cox regression analyses indicated that DL-DFS risk score，tumor grade，and tumor stage could act as prognostic risk factors for patients with ccRCC（ P < 0.05）. Considering that age was a common prognostic risk factor for patients with renal cancer，a nomogram model was constructed by combining the DL-DFS risk score with patient age，tumor grade，and tumor stage. The AUC of this model for predicting the 5-year DFS of ccRCC patients after surgery was 0.87，which was significantly higher than that of DL-DFS（AUC = 0.74），tumor stage（AUC = 0.84），tumor grade（AUC = 0.72），and patient age（AUC = 0.56）in the TCGA cohort（all P<0.05）. In the Renji cohort and the General cohort，the AUC of the nomogram model were 0.78 and 0.86 respectively，which was significantly higher than that of DL-DFS（0.65 and 0.81），tumor stage（0.72 and 0.69），tumor grade（0.64 and 0.77），and patient age（0.56 and 0.63）. Conclusions:In this study a DL-DFS for ccRCC patients was constructed. Then a nomogram model was constructed by combining the DL-DFS risk value with patient age，tumor grade，and tumor stage. This nomogram model demonstrated superior predictive performance compared to DL-DFS alone in evaluating the DFS prognosis of ccRCC patients，which still needs to be further verified in prospective clinical studies.

ObjectiveTo investigate the tumor-suppressing effect of Shenqi Yiliu prescription combined with cisplatin in hepatoma H22-bearing mice based on the phosphatase and tensin homolog deleted on chromosome ten （PTEN）/phosphatidylinositol-3-kinase （PI3K）/protein kinase B （Akt） pathway. MethodH22-bearing mice were prepared and randomized into model group， cisplatin group， and cisplatin combined with high-， medium-， and low-dose Shenqi Yiliu prescription groups， with 10 mice in each group. Another 10 healthy mice were randomly selected as normal group. Shenqi Yiliu prescription was given by gavage with the high， medium， low dose of 54.06， 27.03， 13.515 g·kg^-1·d^-1， respectively， and cisplatin （2.5 mg·kg^-1） was administered by intraperitoneal injection， twice a week. Normal group and model group received normal saline. After 13 days of treatment， mice were killed and the tumor inhibition rate was calculated. The pathomorphological changes of tumor were observed based on hematoxylin-eosin （HE） staining， and enzyme-linked immunosorbent assay （ELISA） and immunofluorescence method were used to detect the content of cyclin-dependent kinase inhibitor 1A （p21） and cyclin-dependent kinase inhibitor 1B （p27） in tumor tissue of mice. The levels of PTEN， PI3K and phosphorylated protein kinase B （p-Akt） in tumor tissue were measured by Western blot. ResultCompared with the model group， cisplatin alone and cisplatin in combination with the high-， medium-， and low-dose Shenqi Yiliu prescription decreased tumor mass （P<0.05）， particularly the cisplatin in combination with the high-dose Shenqi Yiliu prescription. Necrosis of the tumor tissue was observed in each group， especially the cisplatin combined with high-dose Shenqi Yiliu prescription group. As compared with the model group， cisplatin alone and cisplatin in combination with the high-， medium-， and low-dose Shenqi Yiliu prescription raised the expression of p21， p27， and PTEN （P<0.05） and lowered the expression of PI3K and p-Akt （P<0.05）， particularly the cisplatin in combination with high-dose Shenqi Yiliu prescription. ConclusionShenqi Yiliu prescription may regulate the expression of key molecules in PTEN/PI3K/Akt signaling pathway， thereby upregulating the expression of downstream proliferation inhibitors p21 and p27， further suppressing the tumor in H22-bearing mice， and enhancing the effect of chemotherapy.

Objective:To compare the safety and efficacy of the " step-up approach" versus the " step-jump approach" in treatment of infected pancreatic necrosis (IPN).Method:The clinical data of IPN patients who underwent step-up strategy or step-jump strategy treatment at the Department of Pancreatic and Biliary Surgery of the First Affiliated Hospital of Harbin Medical University from December 2018 to November 2022 were analyzed retrospectively. Propensity score matching (PSM) was done based on the nearest neighbor matching method (1: 1 ratio). After matching the baseline data (the caliper value was 0.01), a total of 62 patients with IPN were included, including 41 males and 21 females, aged (41.1±13.1) years old. Patients who were treated with the step-up strategy were included in the step-up group, while patients who were treated with the step-jump strategy were included in the step-jump group. There were 31 patients in each group after PSM, and the treatment effect of the two groups were compared.Results:Of the 62 patients with IPN, 43 received surgical intervention, and 19 were managed successfully using symptomatic anti-inflammatory treatment or percutaneous catheter drainage. The total hospitalization cost of patients in the step-jump group was significantly higher than that in the step-up group [122 000 (73 000, 179 000) yuan vs. 88 000 (46 000, 144 000) yuan, P=0.034]. The overall cure rate of IPN patients in the step-jump group was 93.5%(29/31). The 2 patients who died had type Ⅲ IPN. In the IPN patients in the step-up group were all cured, and the overall cure rate was 100%(31/31), with no death. There were no statistical differences between the two groups in the rates of death, postoperative complications, residual infection, debridement ≥2 times, and positive bacterial culture in blood or drainage fluid (all P>0.05). A total of 19.4% (12/62) patients had postoperative complications, including 4 patients with abdominal bleeding, 3 patients with new organ dysfunction, 2 patients with gastrointestinal bleeding, 2 patients with gastrointestinal fistula, and 1 patient with venous thrombosis in both lower limbs. Conclusion:Both the step-up treatment strategy and the step-jump treatment strategy were safe and effective for treatment of IPN patients.

Objective:To demonstrate the concept of planning target volume (PTV) is not suitable for intensity proton therapy (IMPT) in lung cancer, plan differences were compared based on the concept of PTV and Internal target volume (ITV), aiming to provide clinical reference.Methods:Six patients were retrospectively selected and approved by the local ethics committee. Each of the six patients received two IMPT plans based on a synchronous accelerator model, developed by SINAP team (Shanghai Institute of Applied Physics, China Academy Science University) and commercial treatment system: one with the PTV-based robust IMPT (PTV-IMPT) plan and the other with ITV-based robust IMPT (ITV-IMPT) plan. Three beams were set in all plans, and the final dose was calculated using Monte Carlo dose algorithm. The plan quality and robustness of PTV-IMPT and ITV-IMPT plans were evaluated quantitatively.Results:Compared to the PTV-IMPT plan, ITV-IMPT plan showed better target conformity index (conformability index: 0.58 vs.0.43), better homogeneity index (homogeneity index: 0.96 vs.0.92), lower V 5Gy in normal lung tissue (13.1% vs.13.5%) and maximum dose in spinal cord (8.9 Gy vs. 9.5 Gy) as well as plan monitor unit (MU: 338 vs. 401) . In addition, ITV-IMPT plan showed more robust in target coverage (0.003-0.032 vs. 0.02-0.28), and normal lung tissue was also found a bit robust in the ITV-IMPT plan ( 0.06-0.11, 0.07-0.13). Conclusions:Compared with the PTV-IMPT plan, ITV-IMPT plan has the advantages of high planning quality, well robustness and better tumor motion mitigation. Therefore, ITV concept is recommended to be applied in the IMPT plan for lung cancer.

In recent years, the prevalence of metabolic diseases, including obesity, diabetes, nonalcoholic fatty liver disease, and metabolic syndrome, increased significantly. Fatigue is common in metabolic diseases and may lead to functional disability. This complicated feeling imposes a huge influence on patients with metabolic diseases physically and psychologically, which seriously affects the quality of life and brings serious burden to the social economy. There were an increasing number of researches on fatigue and metabolic diseases. This article reviews the evidences of the linkages between fatigue and metabolic diseases.

OBJECTIVETo explore clinicopathologic characteristics, surgical features and prognostic factors in patients with primary gastrointestinal lymphoma(PGIL) in order to provide evidence for optimizing surgical treatment.

METHODSClinicopathological data of 57 PGIL patients undergoing abdominal surgery in Sun Yat-sen University Cancer Center between October 1990 and January 2015 were retrospectively collected. The survival rates were compared among patients with different clinicopathologic characteristics by Kaplan-Meier method, while Cox regression model was employed to analyze the prognostic factors.

RESULTSAmong 57 patients, 43 were male and 14 were female, with a median age of 48 (range 16 to 80) years. Seventeen (29.8%) cases were classified as Musshoff I( stage, 19 (33.3%) cases as II( stage, 9 (15.8%) cases as III( stage, and 12(21.1%) cases as IIII( stage. Forty-four (77.2%) cases underwent selective operation, 13(22.8%) cases underwent emergent operation due to acute abdomen. Thirty-two(56.1%) cases had radical resection, 18 (31.6%) cases had partial resection and the rest 7(12.3%) cases failed to perform resection. Four (7.0%) cases received simple surgical operation, and 53 (93.0%) cases received comprehensive treatment, including 5(8.8%) cases with preoperative chemotherapy and surgery, 40 (70.2%) cases with surgery and postoperative chemotherapy, and 8 (14.0%) cases with surgery and perioperative chemotherapy. Stage III( and IIII( accounted for 76.9%(10/13) in patients undergoing emergent operation and accounted for 25.0%(11/44) in patients undergoing selective operation, whose difference was statistically significant (χ=9.503, P=0.002). Univariate prognostic analysis showed that T lymphocyte source pathological cell phenotype (P=0.000), clinical Musshoff stage III( and IIII((P=0.001), emergent operation (P=0.000) and incomplete tumor resection(P=0.007) had worse 5-year overall survival. Multivariate Cox regression analysis indicated that tumor pathological cell phenotype (HR=13.75, 95%CI:3.546-53.308, P=0.000) and surgical timing (HR=7.497, 95%CI:1.163-48.313, P=0.034) were independent prognostic risk factors of patients with stage I( and II(.

CONCLUSIONSSurgical operation is an important part of comprehensive treatment for PGIL. T lymphocyte source and ulcerative lymphoma indicates poorer prognosis.

Objective To investigate the efficacy and toxicities of neoadjuvant chemoradiotherapy (neoCRT) in the management of unresectable locally advanced adherent colon cancer (LAACC).Methods A retrospective analysis was performed on the clinical records of 40 patients with initially diagnosed unresectable LAACC who received preoperative neoCRT in our center from October 2010 to December 2015.Results Thirty-nine patients completed the preoperative neoCRT.Thirty-four patients underwent radical resection after neoCRT, and the R0 resection rate, pathological complete response rate (pCR), tumor downstaging rate, nodal downstaging rate, and clinical downstaging rate were 91%, 24%(8/34patients), 76%(26/34patients),100%(32/32patients), and 94%(32/34patients), respectively.Among the 21 patients with bladder invasion, the full bladder was preserved in 7 patients (33%) and partial cystectomy was performed in 11 patients (52%).During the course of neoCRT, the grade 3-4 hematologic toxicity rate, grade 3 hand-foot syndrome rate, grade 3 radiodermatitis, and incomplete intestinal obstruction rate were 23%, 3%, 3%, and 5%, respectively.The 3-year sample size was 25 patients.For all the patients, the 3-year overall survival (OS) and progression-free survival (PFS) rates were 75% and 80%, respectively.Of the 34 patients who received surgical radical resection, the 3-year OS and disease-free survival (DFS) rates were 87% and 81%, respectively.In addition, local tumor recurrence was identified in 3 patients, and distant metastasis was identified in 6 patients.Conclusions NeoCRT is an effective treatment for unresectable LAACC that results in significant tumor downstaging and enhanced R0 resection rate without an increase in surgical complications.The patients treated with radical surgical resection after neoCRT show a satisfactory short-term outcome.Further studies will be required to determine the clinical value of neoCRT in treating LAACC.

Objective To understand family function ,social support ,preoperative anxiety and depression status among elder‐ly operative patients ,and to explore their relationship .Methods 295 elderly preoperative patients were investigated by family AP‐GAR index (APGAR) ,social support rating scale (SSRS) ,self‐rating anxiety scale (SAS) and self‐rating depression scale(SDS) , descriptive and inferential analysis .Results Among 295 elderly preoperative patients ,there were 208 people with good family func‐tion ,accounting for 70 .51% ,67 people with moderate disability family function ,accounting for 22 .71% ,and 20 people with severe disability family function ,accounting for 6 .78% ;The total score of social support was 40 .42 ± 9 .03 and the scores of subjective support was 23 .32 ± 5 .42 ,objective support with 9 .45 ± 3 .73 and support availability with 7 .65 ± 1 .86 ;152 people were preoper‐ative anxiety ,accounting for 51 .53% ,98 people were preoperative depression ,accounting for 33 .22% .The rate of anxiety and de‐pression good family function group was lower than a family dysfunction group(P<0 .05) .The incidence of depression high social support group is higher than low group (P<0 .05);Among the scores of social support ,subjective support ,objective support and support availability ,we find that patients with family well‐functioning group was higher than patients with family dysfunction group (P<0 .05) .Multiple logistic regression analysis showed that influence factors of preoperative psychological abnormality had educa‐tion level ,whether the tumor diseases ,the total score of social support and family functioning condition .Conclusion Elderly preop‐erative patients have anxiety and depression to a certain extent .The anxiety and depression of patients were related to the family function and social support .We Should pay attention to the effect of farmily function and social support on mental health of elderly patients with operation ,and effective use .

Objective To investigate the changes in Wnt/β-catenin,bone morphogenic protein (BMP),estrogen receptor (ER) and insulin-like growth factor (IGF) signaling pathways in bone marrow mesenchymal stem cells (BMSCs) differentiation to the osteoblasts after spinal cord injury (SCI) and understand the mechanism of osteoporosis after SCI.Methods Forty 6-week-old male rats were divided into SCI group (n =20) and control group (n =20) according to the random number table.Rats in SCI group were submitted to laminar osteotomy at T10-12 and given lower thoracic cord sharp transection.In control group,rat lower thoracic cord was only exposed without transaction.Femoral bone marrow density (BMD) of rat right side was determined at postoperative 3 months.Femoral bone marrow was harvested from rat left side.After BMSCs osteoblast differentiation,cells were harvested and used for examining expression of genes associated with the signaling pathways in the two groups using microarray technology and real-time PCR analysis.Results BMD in SCI group was significantly lower in the ephiphyses and metaphyses[(0.176 ± 0.017)g/cm2 and (0.170 ±0.016)g/cm2] compared to that in control group [(0.257 ± 0.023) g/cm2 and (0.196 ± 0.013) g/cm2,P ＜0.05].Microarray and PCR analysis revealed Wnt/β-catenin (eg.Wnt1,Wnt3a,Wnt5a,Lrp5,Ctnnb1,Lef1 and Axin),BMP (Tgfb1 and Bmpr1),IGF -1 (eg.IGF1 R,c-fos and c-Jun),and ER (eg.Esr1) signaling pathways in osteoblasts were significantly down-regulated in SCI group compared to these in control group (P ＜ 0.05).Conclusions The Wnt/β-catenin,BMP,ER,and IGF-1 signaling pathways in osteoblasts are significantly down-regulated after SCI,resulting in profound BMD loss.This indicates that these signaling pathways are implicated in the osteoporosis after SCI.