The prognostic value of negative lymph node count for patients with cervical cancer after radical surgery

Negative lymph node (NLN) count has been recognized as a prognostic indicator in various cancers. However, the relationship between NLN count and the prognosis of cervical cancer is still unknown. In this study, 10, 500 cervical cancer patients after radical surgery were selected from Epidemiology and End Results Program (SEER) data. Clinicopathological characteristics were collected for analysis, including year of diagnosis, age, race, grade, primary site, FIGO stage and cause specific survival (CSS). Univariate and multivariate Cox proportional hazards model was used to assess risk factors for survival of patients. X-tile plots identified 6 as the optimal cutoff value of NLN count to divide patients into high and low risk subsets in terms of CSS (χ2 = 183.95, P < 0.001). The rate of 5-year CCS of cervical cancer patients was improved with an increase in NLN count from 0 to 23 (all P < 0.001). NLN count was validated as an independently prognostic factor by the multivariate Cox analysis (HR: 1.571, 95% CI: 1.370~1.801, P < 0.001). Subgroup analysis showed that NLN count was a prognosis factor in FIGO stage I (χ2=35.023, P < 0.001), stage II (χ2 = 12.910, P < 0.001), stage III + IV (χ2 = 9.732, P = 0.002) and unknown stage (χ2 = 16.654, P < 0.001). Conclusively, this study demonstrated the NLN count was an independent prognostic factor for cervical cancer patients

Age-specific impact on the survival of gastric cancer patients with distant metastasis: an analysis of SEER database

The age-specific impact on the survival of gastric cancer patients with distant metastasis is still unclear. In this study, we identified 11, 299 gastric cancer patients with distant metastasis between 2004 and 2013 from Surveillance, Epidemiology, and End Results population-based dataset. Patients were divided into young (≤60) and elderly groups (>60). Kaplan-Meier methods and multivariable Cox regression were used for the analysis of long-term survival outcomes and risk factors. There were significant differences between the two groups in terms of race, primary site, grade, histologic type, surgery, marital status and clinical T stage (

TROP2 promotes proliferation, migration and metastasis of gallbladder cancer cells by regulating PI3K/AKT pathway and inducing EMT

The human trophoblast cell surface antigen 2 (TROP2) is overexpressed in many cancers. However, its effect on proliferation, migration and metastasis of gallbladder cancer remains unclear. In this study, we found that TROP2 was highly expressed in gallbladder cancer. Overexpression of TROP2 was associated with poor prognosis. Knockdown of TROP2 in gallbladder cancer cell lines strongly inhibited the cell proliferation, clone formation, invasion and migration in vitro, while TROP2 overexpression had opposite effects. In addition, knockdown of TROP2 increased the expression of total PTEN, p-PTEN and PDK-1 but reduced p-AKT via PI3K/AKT pathway. TROP2 downregulation also inhibited vimentin and increased E-cadherin expression during epithelial-mesenchymal transition (EMT). Moreover, gallbladder cancer cells with TROP2 knockdown formed smaller xenografted tumors in vivo. In consistent with in vitro results, TROP2 inhibition decreased Akt phosphorylation, increased PTEN expression and postponed EMT of gallbladder cancer cells in vivo. In conclusion, we revealed that TROP2 promoted the proliferation, migration and metastasis of gallbladder cancer cells by regulating PI3K/ AKT pathway and inducing EMT. TROP2 could serve as a potential prognostic biomarker and therapeutic target for the clinical management of gallbladder cancer

Off-line evaluation of indoor positioning systems in different scenarios: the experiences from IPIN 2020 competition

Every year, for ten years now, the IPIN competition has aimed at evaluating real-world indoor localisation systems by testing them in a realistic environment, with realistic movement, using the EvAAL framework. The competition provided a unique overview of the state-of-the-art of systems, technologies, and methods for indoor positioning and navigation purposes. Through fair comparison of the performance achieved by each system, the competition was able to identify the most promising approaches and to pinpoint the most critical working conditions. In 2020, the competition included 5 diverse off-site off-site Tracks, each resembling real use cases and challenges for indoor positioning. The results in terms of participation and accuracy of the proposed systems have been encouraging. The best performing competitors obtained a third quartile of error of 1 m for the Smartphone Track and 0.5 m for the Foot-mounted IMU Track. While not running on physical systems, but only as algorithms, these results represent impressive achievements.Track 3 organizers were supported by the European Union’s Horizon 2020 Research and Innovation programme under the Marie Skłodowska Curie Grant 813278 (A-WEAR: A network for dynamic WEarable Applications with pRivacy constraints), MICROCEBUS (MICINN, ref. RTI2018-095168-B-C55, MCIU/AEI/FEDER UE), INSIGNIA (MICINN ref. PTQ2018-009981), and REPNIN+ (MICINN, ref. TEC2017-90808-REDT). We would like to thanks the UJI’s Library managers and employees for their support while collecting the required datasets for Track 3. Track 5 organizers were supported by JST-OPERA Program, Japan, under Grant JPMJOP1612. Track 7 organizers were supported by the Bavarian Ministry for Economic Affairs, Infrastructure, Transport and Technology through the Center for Analytics-Data-Applications (ADA-Center) within the framework of “BAYERN DIGITAL II. ” Team UMinho (Track 3) was supported by FCT—Fundação para a Ciência e Tecnologia within the R&D Units Project Scope under Grant UIDB/00319/2020, and the Ph.D. Fellowship under Grant PD/BD/137401/2018. Team YAI (Track 3) was supported by the Ministry of Science and Technology (MOST) of Taiwan under Grant MOST 109-2221-E-197-026. Team Indora (Track 3) was supported in part by the Slovak Grant Agency, Ministry of Education and Academy of Science, Slovakia, under Grant 1/0177/21, and in part by the Slovak Research and Development Agency under Contract APVV-15-0091. Team TJU (Track 3) was supported in part by the National Natural Science Foundation of China under Grant 61771338 and in part by the Tianjin Research Funding under Grant 18ZXRHSY00190. Team Next-Newbie Reckoners (Track 3) were supported by the Singapore Government through the Industry Alignment Fund—Industry Collaboration Projects Grant. This research was conducted at Singtel Cognitive and Artificial Intelligence Lab for Enterprises (SCALE@NTU), which is a collaboration between Singapore Telecommunications Limited (Singtel) and Nanyang Technological University (NTU). Team KawaguchiLab (Track 5) was supported by JSPS KAKENHI under Grant JP17H01762. Team WHU&AutoNavi (Track 6) was supported by the National Key Research and Development Program of China under Grant 2016YFB0502202. Team YAI (Tracks 6 and 7) was supported by the Ministry of Science and Technology (MOST) of Taiwan under Grant MOST 110-2634-F-155-001

Off-Line Evaluation of Indoor Positioning Systems in Different Scenarios: The Experiences From IPIN 2020 Competition

Every year, for ten years now, the IPIN competition has aimed at evaluating real-world indoor localisation systems by testing them in a realistic environment, with realistic movement, using the EvAAL framework. The competition provided a unique overview of the state-of-the-art of systems, technologies, and methods for indoor positioning and navigation purposes. Through fair comparison of the performance achieved by each system, the competition was able to identify the most promising approaches and to pinpoint the most critical working conditions. In 2020, the competition included 5 diverse off-site off-site Tracks, each resembling real use cases and challenges for indoor positioning. The results in terms of participation and accuracy of the proposed systems have been encouraging. The best performing competitors obtained a third quartile of error of 1 m for the Smartphone Track and 0.5 m for the Foot-mounted IMU Track. While not running on physical systems, but only as algorithms, these results represent impressive achievements.Track 3 organizers were supported by the European Union’s Horizon 2020 Research and Innovation programme under the Marie Skłodowska Curie Grant 813278 (A-WEAR: A network for dynamic WEarable Applications with pRivacy constraints), MICROCEBUS (MICINN, ref. RTI2018-095168-B-C55, MCIU/AEI/FEDER UE), INSIGNIA (MICINN ref. PTQ2018-009981), and REPNIN+ (MICINN, ref. TEC2017-90808-REDT). We would like to thanks the UJI’s Library managers and employees for their support while collecting the required datasets for Track 3. Track 5 organizers were supported by JST-OPERA Program, Japan, under Grant JPMJOP1612. Track 7 organizers were supported by the Bavarian Ministry for Economic Affairs, Infrastructure, Transport and Technology through the Center for Analytics-Data-Applications (ADA-Center) within the framework of “BAYERN DIGITAL II. ” Team UMinho (Track 3) was supported by FCT—Fundação para a Ciência e Tecnologia within the R&D Units Project Scope under Grant UIDB/00319/2020, and the Ph.D. Fellowship under Grant PD/BD/137401/2018. Team YAI (Track 3) was supported by the Ministry of Science and Technology (MOST) of Taiwan under Grant MOST 109-2221-E-197-026. Team Indora (Track 3) was supported in part by the Slovak Grant Agency, Ministry of Education and Academy of Science, Slovakia, under Grant 1/0177/21, and in part by the Slovak Research and Development Agency under Contract APVV-15-0091. Team TJU (Track 3) was supported in part by the National Natural Science Foundation of China under Grant 61771338 and in part by the Tianjin Research Funding under Grant 18ZXRHSY00190. Team Next-Newbie Reckoners (Track 3) were supported by the Singapore Government through the Industry Alignment Fund—Industry Collaboration Projects Grant. This research was conducted at Singtel Cognitive and Artificial Intelligence Lab for Enterprises (SCALE@NTU), which is a collaboration between Singapore Telecommunications Limited (Singtel) and Nanyang Technological University (NTU). Team KawaguchiLab (Track 5) was supported by JSPS KAKENHI under Grant JP17H01762. Team WHU&AutoNavi (Track 6) was supported by the National Key Research and Development Program of China under Grant 2016YFB0502202. Team YAI (Tracks 6 and 7) was supported by the Ministry of Science and Technology (MOST) of Taiwan under Grant MOST 110-2634-F-155-001.Peer reviewe

A survey on public acceptance of automated vehicles across COVID-19 pandemic periods in China

Automated vehicles (AVs) are not yet widely accepted by the public, and the COVID-19 pandemic has the potential to lead to a shift in attitudes toward travel modes and vehicles because of travel restrictions and the risk of viral transmission. Therefore, it is necessary to understand how AVs are being accepted by the public during the pandemic. This study investigated public acceptance of AVs across two periods of the COVID-19 epidemic prevention and control in China via 19-question online surveys, including the travel modes, AVs acceptance, and sociodemographic. A total of 429 responses were collected. Results showed that the public acceptance of AVs was on the positive side, but was diverse in items: the average extra cost willing to pay for a fully AV was 28,855.88 CNY (4116.39 USD), and 26.8% of respondents were not willing to pay for it. Respondents agreed on the benefits of AVs and are concerned about legal liability for drivers and fuel economy, and had a positive attitude of commercial AVs. Most acceptance items had differences between the pandemic periods, indicating that people were more willing to accept AVs during period with higher risk of infection. However, only the difference in perceived benefits of AV of ensuring social distance was statistically significant. Gender, age, and ownership of vehicle had greater effects on AVs acceptance, while driving ability and driving experience had small effects on it. This survey can provide insights for studies examining the acceptance of AVs across time, and exploring factors influencing AVs acceptance

Interaction between the intestinal flora and the severity of diversion colitis after low anterior resection of rectal cancer

BackgroundDiversion colitis (DC) is nonspecific inflammation of the distal intestinal mucosa following disruption of colonic continuity with colonic dysfunction. The colonscopic score is a good tool for differentiating the severity of patients with DC. At present, no studies have analyzed the pathogenesis of DC from the perspective of the diversity and and differences of intestinal flora.MethodsRetrospective study: Clinical information were collected from patients with low rectal cancer admitted to the Department of Anorectal Surgery, Changzheng Hospital, from April 2017 to April 2019. These patients underwent laparoscopic low anterior resection (LAR) combined with terminal ileum enterostomy (dual-chamber). We used chi-square test to comparethe clinical baseline information, clinical symptoms, and colonscopic characteristics between different severity of DC. Propsective oberservational study: We recruited 40 patients with laparoscopic anterior low resection combined with terminal ileum enterostomy and they were further classified into mild group and severe group according to the scores of colonscopic examinations for DC. 16s-rDNA sequencing was carried out to analyze the diversity and and differences of intestinal flora in the intestinal lavage fluid of the two groups.ResultsIn retrospective study, we found that age, BMI, history of diabetes, and symptoms associated with the stoma state were the independent risk factors that affect DC severity (P&lt;0.05). Meanwhile, age, BMI, history of diabetes and colonscopic score were found to be independent risk factors affecting the severity of diarrhea after ileostomy closure surgery(P&lt;0.05), which was consistent with our results of differentiating the severity of DC under endoscopy; In propsective oberservational study, 40 patients with low rectal cancer recruited by sample size calculation, 23 were in the mild group and 17 in the severe group. The results of 16s-rDNA sequencing showed that intestinal flora with high enrichment values primarily consisted of Bifidobacteriales and Prevotella in mild group, whereas that in the severe group consisted of Providencia and Dorea. The functional predictions on such two types of intestinal flora were mainly focused on lipid synthesis, glycan synthesis, metabolism, and amino acid metabolism pathways.ConclusionAfter ileostomy closure surgery, a series of severe clinical symptoms might appear in DC patients. There are significant differences in local and systemic inflammatory responses, composition of intestinal flora between DC patients with different colonscopic scores, which provide a basis for the clinical interventional treatment for DC in patients with permanent stoma

Novel Gene Signatures Predictive of Patient Recurrence-Free Survival and Castration Resistance in Prostate Cancer

Molecular signatures predictive of recurrence-free survival (RFS) and castration resistance are critical for treatment decision-making in prostate cancer (PCa), but the robustness of current signatures is limited. Here, we applied the Robust Rank Aggregation (RRA) method to PCa transcriptome profiles and identified 287 genes differentially expressed between localized castration-resistant PCa (CRPC) and hormone-sensitive PCa (HSPC). Least absolute shrinkage and selection operator (LASSO) and stepwise Cox regression analyses of the 287 genes developed a 6-gene signature predictive of RFS in PCa. This signature included NPEPL1, VWF, LMO7, ALDH2, NUAK1, and TPT1, and was named CRPC-derived prognosis signature (CRPCPS). Interestingly, three of these 6 genes constituted another signature capable of distinguishing CRPC from HSPC. The CRPCPS predicted RFS in 5/9 cohorts in the multivariate analysis and remained valid in patients stratified by tumor stage, Gleason score, and lymph node status. The signature also predicted overall survival and metastasis-free survival. The signature’s robustness was demonstrated by the C-index (0.55–0.74) and the calibration plot in all nine cohorts and the 3-, 5-, and 8-year area under the receiver operating characteristic curve (0.67–0.77) in three cohorts. The nomogram analyses demonstrated CRPCPS’ clinical applicability. The CRPCPS thus appears useful for RFS prediction in PCa