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Abstract Introduction Emerging infectious diseases (EIDs) can disrupt the healthcare system, causing regulatory changes that affect the healthcare-seeking process and potentially increase patient-physician dissatisfaction. This study aimed to collect and analyze patients’ and physicians’ complaints during an EID outbreak to inform potential clues regarding medical quality and patient safety enhancement in future dealing with EIDs, employing text mining methodologies. Methods In this descriptive study, complaint records from January 2020 to February 2023 at West China Hospital, a national medical facility in China, were analyzed. Patient and physician complaints have been retrospectively retrieved from the record from the medical department, and then categorized into distinct groups based on reporting reasons, encompassing COVID-19-related policies, healthcare access, availability of medical resources, and financial concerns. Results During the COVID-19 pandemic, 541 COVID-19-related complaints were identified: 330 (61.00%) from patients and 211 (39.00%) from physicians. The monthly volume of complaints fluctuated, starting at 10 in 2020, peaking at 21 in 2022, and dropping to 14 in 2023. Most complaints from inpatients were expressed by older males aged 40 to 65 (38.82%, 210/541). The primary source of complaints was related to mandatory COVID-19 policies (79.30%, 429/541), followed by concerns regarding timely healthcare services (31.61%, 171/541). Few complaints were expressed regarding the insufficiency of medical resources (2.77%, 15/541) and the high costs (4.25%, 23/541). The frequency of complaints expressed by doctors and patients in the emergency department was higher compared with other departments (24.58%, 133/541). Conclusions Increased complaints may serve as a primitive and timely resource for investigating the potential hazards and drawbacks associated with policies pertaining to EIDs. Prompt collection and systematical analysis of patient and physician feedback could help us accurately evaluate the efficacy and repercussions of these policies. Implementing complaints-based assessment might improve care standards in forthcoming healthcare environments grappling with EIDs.

Abstract Background Surgery in geriatric patients often poses risk of major postoperative complications. Acute kidney injury (AKI) is a common complication following noncardiac surgery and is associated with increased mortality. Early identification of geriatric patients at high risk of AKI could facilitate preventive measures and improve patient prognosis. This study used machine learning methods to identify important features and predict AKI following noncardiac surgery in geriatric patients. Methods The data for this study were obtained from a prospective cohort. Patients aged ≥ 65 years who received noncardiac surgery from June 2019 to December 2021 were enrolled. Data were split into training set (from June 2019 to March 2021) and internal validation set (from April 2021 to December 2021) by time. The least absolute shrinkage and selection operator (LASSO) regularization algorithm and the random forest recursive feature elimination algorithm (RF-RFE) were used to screen important predictors. Models were trained through extreme gradient boosting (XGBoost), random forest, and LASSO. The SHapley Additive exPlanations (SHAP) package was used to interpret the machine learning model. Results The training set included 6753 geriatric patients. Of these, 250 (3.70%) patients developed AKI. The XGBoost model with RF-RFE selected features outperformed other models with an area under the precision-recall curve (AUPRC) of 0.505 (95% confidence interval [CI]: 0.369–0.626) and an area under the receiver operating characteristic curve (AUROC) of 0.806 (95%CI: 0.733–0.875). The model incorporated ten predictors, including operation site and hypertension. The internal validation set included 3808 geriatric patients, and 96 (2.52%) patients developed AKI. The model maintained good predictive performance with an AUPRC of 0.431 (95%CI: 0.331–0.524) and an AUROC of 0.845 (95%CI: 0.796–0.888) in the internal validation. Conclusions This study developed a simple machine learning model and a web calculator for predicting AKI following noncardiac surgery in geriatric patients. This model may be a valuable tool for guiding preventive measures and improving patient prognosis. Trial registration The protocol of this study was approved by the Committee of Ethics from West China Hospital of Sichuan University (2019–473) with a waiver of informed consent and registered at www.chictr.org.cn (ChiCTR1900025160, 15/08/2019).

Abstract Aim This study aimed to explore a novel subtype classification method based on the stemness characteristics of patients with non-small cell lung cancer (NSCLC). Methods Based on the Cancer Genome Atlas database to calculate the stemness index (mRNAsi) of NSCLC patients, an unsupervised consensus clustering method was used to classify patients into two subtypes and analyze the survival differences, somatic mutational load, copy number variation, and immune characteristics differences between them. Subsequently, four machine learning methods were used to construct and validate a stemness subtype classification model, and cell function experiments were performed to verify the effect of the signature gene ARTN on NSCLC. Results Patients with Stemness Subtype I had better PFS and a higher somatic mutational burden and copy number alteration than patients with Stemness Subtype II. In addition, the two stemness subtypes have different patterns of tumor immune microenvironment. The immune score and stromal score and overall score of Stemness Subtype II were higher than those of Stemness Subtype I, suggesting a relatively small benefit to immune checkpoints. Four machine learning methods constructed and validated classification model for stemness subtypes and obtained multiple logistic regression equations for 22 characteristic genes. The results of cell function experiments showed that ARTN can promote the proliferation, invasion, and migration of NSCLC and is closely related to cancer stem cell properties. Conclusion This new classification method based on stemness characteristics can effectively distinguish patients' characteristics and thus provide possible directions for the selection and optimization of clinical treatment plans.

Abstract Background The association between anemia and depression has been demonstrated in previous studies, but it's still unclear whether depressive symptoms as a hazard factor for anemia. The findings of a large-scale cross-sectional and longitudinal examination of such an association of among the middle-aged and elderly individuals in China were presented in our study. Methods The data from China Health and Retirement Longitudinal Study in 2011 and 2015 were evaluated. 10,179 and 5,887 participants were included in cross-sectional and longitudinal study, respectively. According to the World Health Organization, hemoglobin concentrations below 13 g/dL for males and 12 g/dL for females are considered anemia. The research population was separated into two groups based on scores of the 10-item short form of the Center for Epidemiologic Studies Depression Scale (CES-D-10): the group with depressed symptoms had a score of more than 10 points, and the group with depressive disorder had a score of more than 20 points. Multilevel logistic regression analyses were conducted to explore the relationship between anemia and varying degrees of depressive symptoms, utilizing three models based on adjusting for different types of covariates. Results In our cross-sectional investigation, depression disorders were more likely to link to the occurrence of anemia (OR, 1.34; 95% CI, 1.02–1.77; P = 0.035). Additionally, there seems a linear connection between depression questionnaire scores and hemoglobin concentrations (r = - 0.053, P

Abstract Background Postherpetic neuralgia (PHN) is one of the most common types of chronic neuropathic pain, which seriously affects quality of the life because of pain severity and poor response to the currently available treatments. The main strategies for PHN management are medication and invasive interventional therapies; however, these approaches have many adverse effects, so it is important to find another effective and safe treatment for PHN. Methods A single-center, single-blind randomized clinical trial will evaluate 98 study participants randomized in a 1:1 ratio into control and experimental groups. The control group will receive conventional treatment including medication therapy and invasive interventional therapy. The experimental group will receive extracorporeal shockwave therapy (ESWT) in addition to conventional therapy. The primary outcome is pain intensity assessed on a visual analogue scale (VAS); the secondary outcomes are the following: quality of life assessed by the 36-Item Short-Form Health Survey (SF-36), psychological state for anxiety and depression measured by the Self-Rating Anxiety Scale (SAS) and Self-Rating Depression Scale (SDS), and sleep quality measured by the Pittsburgh Sleep Quality Index (PSQI). Assessors blinded to the randomization will collect data during the intervention period at baseline and weeks 1, 4, and 12. The plasma levels of tumor necrosis factor-α and interleukin-6 will be assessed before and after ESWT to explore the biochemical mechanisms of ESWT in the treatment of PHN. Discussion This randomized controlled trial will evaluate the effectiveness and safety of ESWT in patients with PHN and thus will provide clinical evidence for its use in the management of PHN and explore the potential biochemical mechanisms of this treatment. Trial registration www.ChiCTR.org.cn , identifier: ChiCTR1900025828. Registered on 10 September 2019

Abstract Background Long non-coding RNA (lncRNA) SNHG5 has been found to play an important role in tumors. Nevertheless, the function and mechanism of lncRNA SNHG5 in osteosarcoma (OS) remains unclear. The purpose of this study was to investigate whether lncRNA SNHG5 can regulate the occurrence and development of OS cells. Methods We performed quantitative real time PCR to detect the expression of lncRNA SNHG5 in OS cells. 143B, MG63 (knockdown) and U2OS, U2R (overexpression) cell lines were chosen for the function study of SNHG5. The effect of SNHG5, miR-212-3p, and SGK3 in OS cells was explored by MTT assays, clony formation, flow cytometry, transwell assays, wound healing assays, and cell spreading assays. Quantitative real-time PCR, Western blot analysis and luciferase assays were used to detect the interaction between lncRNA SNHG5 and miR-212-3p. Results In this study, knockdown of lncRNA SNHG5 suppressed the growth and metastasis of OS cells, whereas the overexpression of SNHG5 produced an opposite result. Mechanistically, lncRNA SNHG5 functions as a sponger against miR-212-3p and suppresses the miR-212-3p/SGK3 signaling pathway. Introduction of miR-212-3p mimics or inhibitors reverses SNHG5 overexpression or silences the exerted tumor promoting or suppressing effect. In addition, our results showed that the function of SNHG5 can be rescued by miR-212-3p and can regulate the growth and metastasis of OS cells via SGK3, the downstream target of miR-212-3p. Conclusions In summary, our study demonstrated that lncRNA SNHG5 can regulate the proliferation and metastasis of OS cells through the miR-212-3p/SGK3 axis. This axis may provide a new target for future clinical treatment.

Abstract Exosomes have emerged as a novel approach for the treatment and diagnosis of cancer after RNA content was discovered in exosomes in 2007. As important meditators of intercellular communication, exosomes have become a strong focus of investigation for researchers in the past decade, as witnessed through the exponential increase of research on exosomes. The capability of exosomes to transfer functionally active cargo highlights their importance as promising biomarkers and diagnostic molecules, as well as prospective drug delivery systems. The accessibility of exosomes in nearly all biofluids additionally alludes to its unprecedented ability in various types of cancers due to its extensive impact on tumor formation and progression. This review analyzes the role of exosomal long RNA species, which is comprised of mRNA, lncRNA, and circRNA, in tumor formation and progression, with an emphasis on their potential as future diagnostic biomarkers and treatment vectors in cancer biology. Their alignment with the development of exosomal databases is further examined in this review, in view of the accumulation of studies published on exosomes in the past decade.