BACKGROUND Intraoperative intraperitoneal chemotherapy is an emerging treatment modality for locally advanced rectal neoplasms. However, its impacts on postoperative complications remain unknown. Anastomotic leakage (...BACKGROUND Intraoperative intraperitoneal chemotherapy is an emerging treatment modality for locally advanced rectal neoplasms. However, its impacts on postoperative complications remain unknown. Anastomotic leakage (AL) is one of the most common and serious complications associated with the anterior resection of rectal tumors. Therefore, we designed this study to determine the effects of intraoperative intraperitoneal chemotherapy on AL. AIM To investigate whether intraoperative intraperitoneal chemotherapy increases the incidence of AL after the anterior resection of rectal neoplasms. METHODS This retrospective cohort study collected information from 477 consecutive patients who underwent an anterior resection of rectal carcinoma using the double stapling technique at our institution from September 2016 to September 2017. Based on the administration of intraoperative intraperitoneal chemotherapy or not, the patients were divided into a chemotherapy group (171 cases with intraperitoneal implantation of chemotherapy agents during the operation) or a control group (306 cases without intraoperative intraperitoneal chemotherapy). Clinicopathologic features, intraoperative treatment, and postoperative complications were recorded and analyzed to determine the effects of intraoperative intraperitoneal chemotherapy on the incidence of AL. The clinical outcomes of the two groups were also compared through survival analysis. RESULTS The univariate analysis showed a significantly higher incidence of AL in the patients who received intraoperative intraperitoneal chemotherapy, with 13 (7.6%) cases in the chemotherapy group and 5 (1.6%) cases in the control group (P = 0.001). As for the severity of AL, the AL patients who underwent intraoperative intraperitoneal chemotherapy tended to be more severe cases, and 12 (92.3%) out of 13 AL patients in the chemotherapy group and 2 (40.0%) out of 5 AL patients in the control group required a secondary operation (P = 0.044). A multivariate analysis was subsequently performed to adjust for the confounding factors and also showed that intraoperative intraperitoneal chemotherapy increased the incidence of AL (odds ratio = 5.386;95%CI: 1.808-16.042;P = 0.002). However, the survival analysis demonstrated that intraoperative intraperitoneal chemotherapy could also improve the disease-free survival rates for patients with locally advanced rectal cancer. CONCLUSION Intraoperative intraperitoneal chemotherapy can improve the prognosis of patients with locally advanced rectal carcinoma, but it also increases the risk of AL following the anterior resection of rectal neoplasms.展开更多
BACKGROUND Colorectal high-grade neuroendocrine neoplasms(HGNENs)are rare and constitute less than 1%of all colorectal malignancies.Based on their morphological differentiation and proliferation identity,these neoplas...BACKGROUND Colorectal high-grade neuroendocrine neoplasms(HGNENs)are rare and constitute less than 1%of all colorectal malignancies.Based on their morphological differentiation and proliferation identity,these neoplasms present heterogeneous clinicopathologic features.Opinions regarding treatment strategies for and improvement of the clinical outcomes of these patients remain controversial.AIM To delineate the clinicopathologic features of and explore the prognostic factors for this rare malignancy.METHODS This observational study reviewed the data of 72 consecutive patients with colorectal HGNENs from three Chinese hospitals between 2000 and 2019.The clinicopathologic characteristics and follow-up data were carefully collected from their medical records,outpatient reexaminations,and telephone interviews.A survival analysis was conducted to evaluate their outcomes and to identify the prognostic factors for this disease.RESULTS According to the latest recommendations for the classification and nomenclature of colorectal HGNENs,61(84.7%)patients in our cohort had poorly differentiated neoplasms,which were categorized as high-grade neuroendocrine carcinomas(HGNECs),and the remaining 11(15.3%)patients had well differentiated neoplasms,which were categorized as high-grade neuroendocrine tumors(HGNETs).Most of the neoplasms(63.9%)were located at the rectum.More than half of the patients(51.4%)presented with distant metastasis at the date of diagnosis.All patients were followed for a median duration of 15.5 mo.In the entire cohort,the median survival time was 31 mo,and the 3-year and 5-year survival rates were 44.3%and 36.3%,respectively.Both the univariate and multivariate analyses demonstrated that increasing age,HGNEC type,and distant metastasis were risk factors for poor clinical outcomes.CONCLUSION Colorectal HGNENs are rare and aggressive malignancies with poor clinical outcomes.However,patients with younger age,good morphological differentiation,and without metastatic disease can have a relatively favorable prognosis.展开更多
BACKGROUND Colorectal cancer(CRC)is a common malignant tumor of the gastrointestinal tract.Lipid metabolism,as an important part of material and energy circulation,is well known to play a crucial role in CRC.AIM To ex...BACKGROUND Colorectal cancer(CRC)is a common malignant tumor of the gastrointestinal tract.Lipid metabolism,as an important part of material and energy circulation,is well known to play a crucial role in CRC.AIM To explore the relationship between serum lipids and CRC development and identify aberrantly expressed cholesterol metabolism genes in CRC.METHODS We retrospectively collected 843 patients who had confirmed CRC and received surgical resection from 2013 to 2015 at the Cancer Hospital of the Chinese Academy of Medical Sciences as our research subjects.The levels of serum total cholesterol(TC),triglycerides,low-density lipoprotein cholesterol(LDL-C),highdensity lipoprotein cholesterol(HDL-C),LDL-C/HDL-C and clinical features were collected and statistically analyzed by SPSS.Then,we used the data from Oncomine to screen the differentially expressed genes(DEGs)of the cholesterol metabolism pathway in CRC and used Gene Expression Profiling Interactive Analysis to confirm the candidate DEGs.PrognoScan was used to analyze the prognostic value of the DEGs,and Search Tool for the Retrieval of Interacting Genes was used to construct the protein-protein interaction network of DEGs.RESULTS The serum HDL-C level in CRC patients was significantly correlated with tumor size,and patients whose tumor size was more than 5 cm had a lower serum HDL-C level(1.18±0.41 mmol/L vs 1.25±0.35 mmol/L,P<0.01)than their counterparts.In addition,TC/HDL(4.19±1.33 vs 3.93±1.26,P<0.01)and LDL-C/HDL-C(2.83±1.10 vs 2.61±0.96,P<0.01)were higher in patients with larger tumors.The levels of HDL-C(P<0.05),TC/HDL-C(P<0.01)and LDL-C/HDL-C(P<0.05)varied in different stages of CRC patients,and the differences were significant.We screened 14 differentially expressed genes(DEGs)of the cholesterol metabolism pathway in CRC and confirmed that lipoprotein receptor-related protein 8(LRP8),PCSK9,low-density lipoprotein receptor(LDLR),MBTPS2 and FDXR are upregulated,while ABCA1 and OSBPL1A are downregulated in cancer tissue.Higher expression of LDLR(HR=3.12,95%CI:1.77-5.49,P<0.001),ABCA1(HR=1.66,95%CI:1.11-2.48,P=0.012)and OSBPL1A(HR=1.38,95%CI:1.01-1.89,P=0.041)all yielded significantly poorer DFS outcomes.Higher expression of FDXR(HR=0.7,95%CI:0.47-1.05,P=0.002)was correlated with longer DFS.LDLR,ABCA1,OSBPL1A and FDXR were involved in many important cellular function pathways.CONCLUSION Serum HDL-C levels are associated with tumor size and stage in CRC patients.LRP8,PCSK9,LDLR,MBTPS2 and FDXR are upregulated,while ABCA1 and OSBPL1A are downregulated in CRC.Among them,LDLR,ABCA1,OSBPL1A and FDXR were valuable prognostic factors of DFS and were involved in important cellular function pathways.展开更多
Recently, deep learning processors have become one of the most promising solutions of accelerating deep learning algorithms. Currently, the only method of programming the deep learning processors is through writing as...Recently, deep learning processors have become one of the most promising solutions of accelerating deep learning algorithms. Currently, the only method of programming the deep learning processors is through writing assembly instructions by bare hands, which costs a lot of programming efforts and causes very low efficiency. One solution is to integrate the deep learning processors as a new back-end into one prevalent high-level deep learning framework （e.g., TPU （tensor processing unit） is integrated into Tensorflow directly）. However, this will obstruct other frameworks to profit from the programming interface, The alternative approach is to design a framework-independent low-level library for deep learning processors （e.g., the deep learning library for GPU, cuDNN）. In this fashion, the library could be conveniently invoked in high-level programming frameworks and provides more generality. In order to allow more deep learning frameworks to gain benefits from this environment, we envision it as a low-level library which could be easily embedded into current high-level frameworks and provide high performance. Three major issues of designing such a library are discussed. The first one is the design of data structures. Data structures should be as few as possible while being able to support all possible operations. This will allow us to optimize the data structures easier without compromising the generality. The second one is the selection of operations, which should provide a rather wide range of operations to support various types of networks with high efficiency. The third is the design of the API, which should provide a flexible and user-friendly programming model and should be easy to be embedded into existing deep learning frameworks. Considering all the above issues, we propose DLPIib, a tensor-filter based library designed specific for deep learning processors. It contains two major data structures, tensor and filter, and a set of operators including basic neural network primitives and matrix/vector operations. It provides a descriptor-based API exposed as a C＋＋ interface. The library achieves a speedup of 0.79x compared with the performance of hand-written assembly instructions.展开更多
The increasing attention on deep learning has tremendously spurred the design of intelligence processing hardware. The variety of emerging intelligence processors requires standard benchmarks for fair comparison and s...The increasing attention on deep learning has tremendously spurred the design of intelligence processing hardware. The variety of emerging intelligence processors requires standard benchmarks for fair comparison and system optimization （in both software and hardware）. However, existing benchmarks are unsuitable for benchmarking intelligence processors due to their non-diversity and nonrepresentativeness. Also, the lack of a standard benchmarking methodology further exacerbates this problem. In this paper, we propose BENCHIP, a benchmark suite and benchmarking methodology for intelligence processors. The benchmark suite in BENCHIP consists of two sets of benchmarks： microbenchmarks and macrobenchmarks. The microbenchmarks consist of single-layer networks, They are mainly designed for bottleneck analysis and system optimization. The macrobenchmarks contain state-of-the-art industrial networks, so as to offer a realistic comparison of different platforms. We also propose a standard benchmarking methodology built upon an industrial software stack and evaluation metrics that comprehensively reflect various characteristics of the evaluated intelligence processors, BENCHIP is utilized for evaluating various hardware platforms, including CPUs, GPUs, and accelerators. BENCHIP will be open-sourced soon.展开更多
Objective To investigate the metabolic routes and metabolites of Rehmannia glutinosa and Cornus officinalis herb pair produced by gut microbiome from rats.Methods A rapid and sensitive ultra-performance liquid chromat...Objective To investigate the metabolic routes and metabolites of Rehmannia glutinosa and Cornus officinalis herb pair produced by gut microbiome from rats.Methods A rapid and sensitive ultra-performance liquid chromatography/quadrupole-time-offlight mass spectrometry（UPLC-Q-TOF/MS） technique combined with Metabolynx？software was established and successfully applied to identify the metabolites of the main bioactive components in the herb pair extract by rat intestinal bacteria.Results Four parent compounds（loganin,morroniside,catalpol,and acteoside） and their eight corresponding metabolites were detected and tentatively identified by the characteristics of their protonated ions.Hydrogenated and demethylated loganetin,dehydroxylated morronisid aglycone,caffeic acid,and its methylated product were the main metabolites.These metabolites suggested that the glycosides were firstly hydrolyzed to their aglycones by hydrolytic enzymes of the enteric microbial flora and subsequently to the other metabolites through hydrogenation,（de）-methylation,and de-hydroxylation.Conclusion The results may be helpful for the further investigation of the pharmacokinetic study of R.glutinosa and C.officinalis herb pair in vivo.展开更多
基金Medicine and Health Technology Innovation Project of Chinese Academy of Medical Sciences,No.2017-12M-1-006
文摘BACKGROUND Intraoperative intraperitoneal chemotherapy is an emerging treatment modality for locally advanced rectal neoplasms. However, its impacts on postoperative complications remain unknown. Anastomotic leakage (AL) is one of the most common and serious complications associated with the anterior resection of rectal tumors. Therefore, we designed this study to determine the effects of intraoperative intraperitoneal chemotherapy on AL. AIM To investigate whether intraoperative intraperitoneal chemotherapy increases the incidence of AL after the anterior resection of rectal neoplasms. METHODS This retrospective cohort study collected information from 477 consecutive patients who underwent an anterior resection of rectal carcinoma using the double stapling technique at our institution from September 2016 to September 2017. Based on the administration of intraoperative intraperitoneal chemotherapy or not, the patients were divided into a chemotherapy group (171 cases with intraperitoneal implantation of chemotherapy agents during the operation) or a control group (306 cases without intraoperative intraperitoneal chemotherapy). Clinicopathologic features, intraoperative treatment, and postoperative complications were recorded and analyzed to determine the effects of intraoperative intraperitoneal chemotherapy on the incidence of AL. The clinical outcomes of the two groups were also compared through survival analysis. RESULTS The univariate analysis showed a significantly higher incidence of AL in the patients who received intraoperative intraperitoneal chemotherapy, with 13 (7.6%) cases in the chemotherapy group and 5 (1.6%) cases in the control group (P = 0.001). As for the severity of AL, the AL patients who underwent intraoperative intraperitoneal chemotherapy tended to be more severe cases, and 12 (92.3%) out of 13 AL patients in the chemotherapy group and 2 (40.0%) out of 5 AL patients in the control group required a secondary operation (P = 0.044). A multivariate analysis was subsequently performed to adjust for the confounding factors and also showed that intraoperative intraperitoneal chemotherapy increased the incidence of AL (odds ratio = 5.386;95%CI: 1.808-16.042;P = 0.002). However, the survival analysis demonstrated that intraoperative intraperitoneal chemotherapy could also improve the disease-free survival rates for patients with locally advanced rectal cancer. CONCLUSION Intraoperative intraperitoneal chemotherapy can improve the prognosis of patients with locally advanced rectal carcinoma, but it also increases the risk of AL following the anterior resection of rectal neoplasms.
基金Supported by the Medicine and Health Technology Innovation Project of Chinese Academy of Medical Sciences,No.2017-12M-1-006
文摘BACKGROUND Colorectal high-grade neuroendocrine neoplasms(HGNENs)are rare and constitute less than 1%of all colorectal malignancies.Based on their morphological differentiation and proliferation identity,these neoplasms present heterogeneous clinicopathologic features.Opinions regarding treatment strategies for and improvement of the clinical outcomes of these patients remain controversial.AIM To delineate the clinicopathologic features of and explore the prognostic factors for this rare malignancy.METHODS This observational study reviewed the data of 72 consecutive patients with colorectal HGNENs from three Chinese hospitals between 2000 and 2019.The clinicopathologic characteristics and follow-up data were carefully collected from their medical records,outpatient reexaminations,and telephone interviews.A survival analysis was conducted to evaluate their outcomes and to identify the prognostic factors for this disease.RESULTS According to the latest recommendations for the classification and nomenclature of colorectal HGNENs,61(84.7%)patients in our cohort had poorly differentiated neoplasms,which were categorized as high-grade neuroendocrine carcinomas(HGNECs),and the remaining 11(15.3%)patients had well differentiated neoplasms,which were categorized as high-grade neuroendocrine tumors(HGNETs).Most of the neoplasms(63.9%)were located at the rectum.More than half of the patients(51.4%)presented with distant metastasis at the date of diagnosis.All patients were followed for a median duration of 15.5 mo.In the entire cohort,the median survival time was 31 mo,and the 3-year and 5-year survival rates were 44.3%and 36.3%,respectively.Both the univariate and multivariate analyses demonstrated that increasing age,HGNEC type,and distant metastasis were risk factors for poor clinical outcomes.CONCLUSION Colorectal HGNENs are rare and aggressive malignancies with poor clinical outcomes.However,patients with younger age,good morphological differentiation,and without metastatic disease can have a relatively favorable prognosis.
文摘BACKGROUND Colorectal cancer(CRC)is a common malignant tumor of the gastrointestinal tract.Lipid metabolism,as an important part of material and energy circulation,is well known to play a crucial role in CRC.AIM To explore the relationship between serum lipids and CRC development and identify aberrantly expressed cholesterol metabolism genes in CRC.METHODS We retrospectively collected 843 patients who had confirmed CRC and received surgical resection from 2013 to 2015 at the Cancer Hospital of the Chinese Academy of Medical Sciences as our research subjects.The levels of serum total cholesterol(TC),triglycerides,low-density lipoprotein cholesterol(LDL-C),highdensity lipoprotein cholesterol(HDL-C),LDL-C/HDL-C and clinical features were collected and statistically analyzed by SPSS.Then,we used the data from Oncomine to screen the differentially expressed genes(DEGs)of the cholesterol metabolism pathway in CRC and used Gene Expression Profiling Interactive Analysis to confirm the candidate DEGs.PrognoScan was used to analyze the prognostic value of the DEGs,and Search Tool for the Retrieval of Interacting Genes was used to construct the protein-protein interaction network of DEGs.RESULTS The serum HDL-C level in CRC patients was significantly correlated with tumor size,and patients whose tumor size was more than 5 cm had a lower serum HDL-C level(1.18±0.41 mmol/L vs 1.25±0.35 mmol/L,P<0.01)than their counterparts.In addition,TC/HDL(4.19±1.33 vs 3.93±1.26,P<0.01)and LDL-C/HDL-C(2.83±1.10 vs 2.61±0.96,P<0.01)were higher in patients with larger tumors.The levels of HDL-C(P<0.05),TC/HDL-C(P<0.01)and LDL-C/HDL-C(P<0.05)varied in different stages of CRC patients,and the differences were significant.We screened 14 differentially expressed genes(DEGs)of the cholesterol metabolism pathway in CRC and confirmed that lipoprotein receptor-related protein 8(LRP8),PCSK9,low-density lipoprotein receptor(LDLR),MBTPS2 and FDXR are upregulated,while ABCA1 and OSBPL1A are downregulated in cancer tissue.Higher expression of LDLR(HR=3.12,95%CI:1.77-5.49,P<0.001),ABCA1(HR=1.66,95%CI:1.11-2.48,P=0.012)and OSBPL1A(HR=1.38,95%CI:1.01-1.89,P=0.041)all yielded significantly poorer DFS outcomes.Higher expression of FDXR(HR=0.7,95%CI:0.47-1.05,P=0.002)was correlated with longer DFS.LDLR,ABCA1,OSBPL1A and FDXR were involved in many important cellular function pathways.CONCLUSION Serum HDL-C levels are associated with tumor size and stage in CRC patients.LRP8,PCSK9,LDLR,MBTPS2 and FDXR are upregulated,while ABCA1 and OSBPL1A are downregulated in CRC.Among them,LDLR,ABCA1,OSBPL1A and FDXR were valuable prognostic factors of DFS and were involved in important cellular function pathways.
基金This work is partially supported by the National Natural Science Foundation of China under Grant Nos. 61432016, 61472396, 61473275, 61522211, 61532016, 61521092, 61502446, 61672491, 61602441, and 61602446, the National Basic Research 973 Program of China under Grant No. 2015CB358800, and the Strategic Priority Research Program of the Chinese Academy of Sciences under Grant No. XDB02040009.
文摘Recently, deep learning processors have become one of the most promising solutions of accelerating deep learning algorithms. Currently, the only method of programming the deep learning processors is through writing assembly instructions by bare hands, which costs a lot of programming efforts and causes very low efficiency. One solution is to integrate the deep learning processors as a new back-end into one prevalent high-level deep learning framework （e.g., TPU （tensor processing unit） is integrated into Tensorflow directly）. However, this will obstruct other frameworks to profit from the programming interface, The alternative approach is to design a framework-independent low-level library for deep learning processors （e.g., the deep learning library for GPU, cuDNN）. In this fashion, the library could be conveniently invoked in high-level programming frameworks and provides more generality. In order to allow more deep learning frameworks to gain benefits from this environment, we envision it as a low-level library which could be easily embedded into current high-level frameworks and provide high performance. Three major issues of designing such a library are discussed. The first one is the design of data structures. Data structures should be as few as possible while being able to support all possible operations. This will allow us to optimize the data structures easier without compromising the generality. The second one is the selection of operations, which should provide a rather wide range of operations to support various types of networks with high efficiency. The third is the design of the API, which should provide a flexible and user-friendly programming model and should be easy to be embedded into existing deep learning frameworks. Considering all the above issues, we propose DLPIib, a tensor-filter based library designed specific for deep learning processors. It contains two major data structures, tensor and filter, and a set of operators including basic neural network primitives and matrix/vector operations. It provides a descriptor-based API exposed as a C＋＋ interface. The library achieves a speedup of 0.79x compared with the performance of hand-written assembly instructions.
基金This work is partially supported by the National Key Research and Development Program of China under Grant No. 2017YFB1003101, the National Natural Science Foundation of China under Grant Nos. 61472396, 61432016, 61473275, 61522211, 61532016, 61521092, 61502446, 61672491, 61602441, 61602446, 61732002, and 61702478, Beijing Science and Technology Projects under Grant No. Z151100000915072, the Science and Technology Service Network Initiative （STS） Projects of Chinese Academy of Sciences, and the National Basic Research 973 Program of China under Grant No. 2015CB358800.
文摘The increasing attention on deep learning has tremendously spurred the design of intelligence processing hardware. The variety of emerging intelligence processors requires standard benchmarks for fair comparison and system optimization （in both software and hardware）. However, existing benchmarks are unsuitable for benchmarking intelligence processors due to their non-diversity and nonrepresentativeness. Also, the lack of a standard benchmarking methodology further exacerbates this problem. In this paper, we propose BENCHIP, a benchmark suite and benchmarking methodology for intelligence processors. The benchmark suite in BENCHIP consists of two sets of benchmarks： microbenchmarks and macrobenchmarks. The microbenchmarks consist of single-layer networks, They are mainly designed for bottleneck analysis and system optimization. The macrobenchmarks contain state-of-the-art industrial networks, so as to offer a realistic comparison of different platforms. We also propose a standard benchmarking methodology built upon an industrial software stack and evaluation metrics that comprehensively reflect various characteristics of the evaluated intelligence processors, BENCHIP is utilized for evaluating various hardware platforms, including CPUs, GPUs, and accelerators. BENCHIP will be open-sourced soon.
基金National Natural Science Foundation of China(No.81072996,81102743)Priority Academic Programs Development of Jiangsu Higher Education Institutions(PAPD)
文摘Objective To investigate the metabolic routes and metabolites of Rehmannia glutinosa and Cornus officinalis herb pair produced by gut microbiome from rats.Methods A rapid and sensitive ultra-performance liquid chromatography/quadrupole-time-offlight mass spectrometry（UPLC-Q-TOF/MS） technique combined with Metabolynx？software was established and successfully applied to identify the metabolites of the main bioactive components in the herb pair extract by rat intestinal bacteria.Results Four parent compounds（loganin,morroniside,catalpol,and acteoside） and their eight corresponding metabolites were detected and tentatively identified by the characteristics of their protonated ions.Hydrogenated and demethylated loganetin,dehydroxylated morronisid aglycone,caffeic acid,and its methylated product were the main metabolites.These metabolites suggested that the glycosides were firstly hydrolyzed to their aglycones by hydrolytic enzymes of the enteric microbial flora and subsequently to the other metabolites through hydrogenation,（de）-methylation,and de-hydroxylation.Conclusion The results may be helpful for the further investigation of the pharmacokinetic study of R.glutinosa and C.officinalis herb pair in vivo.
