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Aim: The aim of this study was to investigate the lived experience of people with diabetic retinopathy and to understand the impact of the disease on them including the practical problems faced in the day‐to‐day life. Design: Descriptive qualitative research. Methods: A convenience sample of 11 patients with diabetic retinopathy who were hospitalized in a tertiary hospitals in Shandong province of China were enrolled. Data were collected using semi‐structured in‐depth interviews. The six‐stage thematic analysis of Braun and Clarke was used for data analysis. Results: Three themes and 12 sub‐themes were extracted, namely: countdown to darkness (lack of disease knowledge, bystander's perspective, distrust of grassroots hospitals); Endless abyss (action restrictions, social isolation, stigma, lost of meaning in life, catastrophizing explanations, a heavy burden); Light chaser (craving for light, turning points in behaviour, self‐adjustment). [ABSTRACT FROM AUTHOR]

Fifth-generation (5G) communication technologies and artificial intelligence enable the design and deployment of sophisticated solutions for enhanced user experience and superior network-based service delivery. However, the performance of the systems offering 5G-based services depends on various factors. In this paper, we consider the case of the online railway ticketing system in China that serves the needs of hundreds of millions of people daily. This system's online access rates vary over time, and fluctuations are experienced, affecting its overall dependability and service quality. We use long short-term memory network, particle swarm optimization, and differential evolution to construct DP-LSTM—a hybridly optimized model to predict network flow for dependable and quality-enhanced service delivery. We evaluate the proposed model using real data collected over six months from the "12306 online ticketing" system. We compare the performance of the proposed model with mainstream network traffic prediction models. We use mean absolute percentage error, mean absolute error, and root mean square error for performance evaluation. Experimental results show the superiority of the proposed model. [ABSTRACT FROM AUTHOR]

Background: Non-small cell lung cancer (NSCLC) accounts for approximately 80% of diagnosed lung cancer patients. RAD52 has been reported to be associated with the development of squamous cell lung carcinoma. In this study, we assessed the relationships of RAD52 genetic polymorphisms and NSCLC risk among the Chinese population at high altitude. Methods: Eight single nucleotide polymorphisms (SNPs) of RAD52 were genotyped in the Agena MassARRAY platform among 506 NSCLC patients and 510 healthy controls. We examined the association of RAD52 polymorphisms with NSCLC risk using odds ratios (ORs) and 95% confidence intervals (CIs) via multiple genetic models. Results: The rs10774474 A allele was related to a decreased risk of NSCLC in a high altitude population of China (OR = 0.82, 95% CI = 0.69–0.98, p = 0.032), whereas mutant alleles of rs1051672, rs7310449, rs1051669, rs6413436, rs4766377 and rs10849605 significantly increased NSCLC risk. Haplotype analysis showed that four haplotypes of RAD52 polymorphisms conferred an enhanced susceptibility to NSCLC (Ars1051672Grs7310449Trs1051669Ars6413436: OR = 1.29, p = 0.021; Grs1051672Ars7310449Crs1051669Grs6413436: OR = 1.21, p = 0.027; Grs4766377Crs12822733Trs10774474Crs10849605: OR = 1.26, p = 0.032; Ars4766377Crs12822733Ars10774474Trs10849605: OR = 1.21, p = 0.032). Conclusions: Our findings suggested the remarkable association of RAD52 polymorphisms with NSCLC risk among the Chinese population in a high altitude area. The reviews of this paper are available via the supplemental material section. [ABSTRACT FROM AUTHOR]

Cancer is one of the leading causes of human death worldwide. Treatment of cancer exhausts significant medical resources, and the morbidity and mortality caused by cancer is a huge social burden. Cancer has therefore become a serious economic and social problem shared globally. As an increasingly prevalent disease in China, cancer is a huge challenge for the country's healthcare system. Based on recent data published in the Journal of the National Cancer Center on cancer incidence and mortality in China in 2016, we analyzed the current trends in cancer incidence and changes in cancer mortality and survival rate in China. And also, we examined several key risk factors for cancer pathogenesis and discussed potential countermeasures for cancer prevention and treatment in China., (© 2023. Science China Press.)

Non‑small cell lung cancer (NSCLC) is the leading cause of cancer‑related deaths worldwide. Cisplatin‑based chemotherapy currently represents the main treatment option for patients with NSCLC. The aim of the present study was to evaluate effect of single nucleotide polymorphisms (SNPs) within the excision repair cross‑complementing group 5 (ERCC5) gene on susceptibility to NSCLC, as well as the responsiveness to and toxicity of cisplatin chemotherapy. A total of 506 patients with NSCLC and 510 healthy controls were recruited for the present study. All DNA samples were genotyped by the Agena MassARRAY platform. Logistic regression analysis was carried out to assess the relationship between ERCC5 polymorphisms with NSCLC susceptibility and responsiveness to chemotherapy. The rs4771436 TG‑GG genotype was associated with increased NSCLC risk. When the data were stratified according to age, sex, tobacco smoking, body mass index and histological type, ERCC5 polymorphisms (rs2016073, rs4771436, rs11069498 and rs4150330) were associated with NSCLC risk. Furthermore, the A allele and GA‑AA genotype of rs11069498 were related to the response to chemotherapy. ERCC5 (rs11069498 and rs4150330) polymorphisms were associated with the increased risk of toxicity. However, rs4771436 in ERCC5 gene was significantly correlated with the reduced risk of toxicity. These results suggested a potential relationship between ERCC5 polymorphisms, the risk of NSCLC and the sensitivity to cisplatin‑based chemotherapy among Chinese populations.