ATF3-CBS signaling axis coordinates ferroptosis and tumorigenesis in colorectal cancer.

The induction of ferroptosis is promising for cancer therapy. However, the mechanisms enabling cancer cells to evade ferroptosis, particularly in low-cystine environments, remain elusive. Our study delves into the intricate regulatory mechanisms of Activating transcription factor 3 (ATF3) on Cystathionine ß-synthase (CBS) under cystine deprivation stress, conferring resistance to ferroptosis in colorectal cancer (CRC) cells. Additionally, our findings establish a positively correlation between this signaling axis and CRC progression, suggesting its potential as a therapeutic target. Mechanistically, ATF3 positively regulates CBS to resist ferroptosis under cystine deprivation stress. In contrast, the suppression of CBS sensitizes CRC cells to ferroptosis through targeting the mitochondrial tricarboxylic acid (TCA) cycle. Notably, our study highlights that the ATF3-CBS signaling axis enhances ferroptosis-based CRC cancer therapy. Collectively, the findings reveal that the ATF3-CBS signaling axis is the primary feedback pathway in ferroptosis, and blocking this axis could be a potential therapeutic approach for colorectal cancer.

RNA-binding proteins potentially regulate the alternative splicing of cell cycle-associated genes in proliferative diabetic retinopathy.

RNA-binding proteins (RBPs) contribute to the pathogenesis of proliferative diabetic retinopathy (PDR) by regulating gene expression through alternative splicing events (ASEs). However, the RBPs differentially expressed in PDR and the underlying mechanisms remain unclear. Thus, this study aimed to identify the differentially expressed genes in the neovascular membranes (NVM) and retinas of patients with PDR. The public transcriptome dataset GSE102485 was downloaded from the Gene Expression Omnibus database, and samples of PDR and normal retinas were analyzed. A mouse model of oxygen-induced retinopathy was used to confirm the results. The top 20 RBPs were screened for co-expression with alternative splicing genes (ASGs). A total of 403 RBPs were abnormally expressed in the NVM and retina samples. Functional analysis demonstrated that the ASGs were enriched in cell cycle pathways. Cell cycle-associated ASEs and an RBP-AS regulatory network, including 15 RBPs and their regulated ASGs, were extracted. Splicing factor proline/glutamine rich (SFPQ), microtubule-associated protein 1 B (MAP1B), heat-shock protein 90-alpha (HSP90AA1), microtubule-actin crosslinking factor 1 (MACF1), and CyclinH (CCNH) expression remarkably differed in the mouse model. This study provides novel insights into the RBP-AS interaction network in PDR and for developing screening and treatment options to prevent diabetic retinopathy-related blindness.

METTL17 coordinates ferroptosis and tumorigenesis by regulating mitochondrial translation in colorectal cancer.

Ferroptosis, an iron-dependent lipid peroxidation-induced form of regulated cell death, shows great promise as a cancer therapy strategy. Despite the critical role of mitochondria in ferroptosis regulation, the underlying mechanisms remain elusive. This study reveals that the mitochondrial protein METTL17 governs mitochondrial function in colorectal cancer (CRC) cells through epigenetic modulation. Bioinformatic analysis establishes that METTL17 expression positively correlates with ferroptosis resistance in cancer cells and is up-regulated in CRC. Depletion of METTL17 sensitizes CRC cells to ferroptosis, impairs cell proliferation, migration, invasion, xenograft tumor growth, and AOM/DSS-induced CRC tumorigenesis. Furthermore, suppression of METTL17 disrupts mitochondrial function, energy metabolism, and enhances intracellular and mitochondrial lipid peroxidation and ROS levels during ferroptotic stress. Mechanistically, METTL17 inhibition significantly reduces mitochondrial RNA methylation, including m4C, m5C, m3C, m7G, and m6A, leading to impaired translation of mitochondrial protein-coding genes. Additionally, the interacting proteins associated with METTL17 are essential for mitochondrial gene expression, and their knockdown sensitizes CRC cells to ferroptosis and inhibits cell proliferation. Notably, combined targeting of METTL17 and ferroptosis in a therapeutic approach effectively suppresses CRC xenograft growth in vivo. This study uncovers the METTL17-mediated defense mechanism for cell survival and ferroptosis in mitochondria, highlighting METTL17 as a potential therapeutic target for CRC.

Taking full advantage of 'low-quality' datasets in watershed modeling and management: From a perspective of parameter calibration.

The quality of calibration datasets is critical for establishing well-calibrated models for reliable decision-making support. However, the analysis of the influence of calibration dataset quality and the discussion on how to use flawed and/or incomplete datasets are still far from sufficient. An evaluation framework for the impact of model calibration data on parameter identifiability, sensitivity, and uncertainty (ISU) was established. Three quantitative and normalized indicators were designed to describe the magnitude of ISU. With the case study of the upper Daqing River watershed, China and the model SWAT (Soil and Water Assessment Tool), one ideal dataset without quality flaws and 79 datasets with different types of flaws including observation error, low monitoring frequency, short data duration and low data resolution were evaluated. The result showed that 4 of 13 parameters that control canopy, groundwater and channel processes have higher ISU values, indicating the high identifiability, high sensitivity, and low uncertainty. The largest gap of parameter ISU between dataset with quality flaw and ideal dataset was 0.61 due to short data duration, while the smallest gap was -0.28 due to low monitoring data frequency. Although some defective datasets caused unacceptable calibration results and model output, some defective datasets can still be valuable for model calibration which depends on the hydrological processes of interest when applying the model. Equivalent calibration results were yielded by the datasets with similar statistical properties. When using datasets with traditional defective issues for calibration, a new step checking the consistency among decision goal, representative system process, determinative parameters and calibration datasets is suggested. Practices including process-related data selection, dataset regrouping and risk self-reporting when using low-quality datasets are encouraged to increase the reliability of model-based watershed management.

Asperosaponin VI facilitates the regeneration of skeletal muscle injury by suppressing GSK-3ß-mediated cell apoptosis.

Asperosaponin VI (ASA VI) is a bioactive triterpenoid saponin extracted from Diptychus roots, of Diptyl, and has previously shown protective functions in rheumatoid arthritis and sepsis. This study investigates the effects and molecular mechanisms of ASA VI on skeletal muscle regeneration in a cardiotoxin (CTX)-induced skeletal muscle injury mouse model. Mice were subjected to CTX-induced injury in the tibialis anterior and C2C12 myotubes were treated with CTX. Muscle fiber histology was analyzed at 7 and 14 days postinjury. Apoptosis and autophagy-related protein expression were evaluated t s by Western blot, and muscle regeneration markers were quantified by quantitative polymerase chain reaction. Docking studies, cell viability assessments, and glycogen synthase kinase-3ß (GSK-3ß) activation analyses were performed to elucidate the mechanism. ASA VI was observed to improve muscle interstitial fibrosis, remodeling, and performance in CTX-treated mice, thereby increased skeletal muscle size, weight, and locomotion. Furthermore, ASA VI modulated the expression of apoptosis and autophagy-related proteins through GSK-3ß inhibition and activated the transcription of regeneration genes. Our results suggest that ASA VI mitigates skeletal muscle injury by modulating apoptosis and autophagy via GSK-3ß signaling and promotes regeneration, thus presenting a probable therapeutic agent for skeletal muscle injury.

Big Data-Enabled Analysis of Factors Affecting Medical Expenditure in the Cerebral Infarction of a Developing City in Western China.

Purpose: Cerebral infarction (CI) has been one of the leading causes of death in China since 2017, and controlling the medical expenses of this disease is an urgent issue for the Chinese government. This study aims to explore the important factors that affect the hospitalization expenses of CI patients and to provide a scientific basis for establishing a reasonable reimbursement mechanism and hospitalization expense standard for CI patients. Methods: Data from 109,314 inpatients from the Healthcare Security Administration of Chengdu in western China from January 2016 to December 2018 were utilized. Descriptive statistical analysis was used for variable characteristic analysis. The Mann-Whitney test and Kruskal-Wallis test were used for single-factor analysis, and multiple linear stepwise regression was used for single-factor analysis and multiple-factor analysis. Results: This study found that the average direct economic burden of CI in Chengdu was approximately 10,569 Chinese yuan (CNY), about 1450 US dollars, the average length of stay (LOS) was 14.47 days, the indirect economic burden was approximately 2817 CNY, and the total economic burden was 13,386 CNY for a CI inpatient. Gender, insurance type, grade of medical institution, the level of payment type, age, LOS, and complications and comorbidities (CCs) are the most important factors affecting CI medical costs. Conclusion: Citizens should improve their lifestyle habits to reduce disease risk to avoid the associated medical and economic burdens. Hospitals should improve their medical technology to decrease the LOS and reduce direct medical costs. The government should actively promote the hierarchical diagnosis and treatment policy to reduce the waste of medical resources caused by low-acuity patients going to high-level hospitals for treatment. The National Healthcare Security Administration should optimize the medical insurance payment method and establish a corresponding mechanism to reduce the occurrence of excessive medical treatments such as overuse.

CREG Protects Retinal Ganglion Cells loss and Retinal Function Impairment Against ischemia-reperfusion Injury in mice via Akt Signaling Pathway.

PURPOSE: The irreversible death of retinal ganglion cells (RGCs) plays an important role in the pathogenesis of glaucoma. Cellular repressor of E1A-stimulated genes (CREG), a secreted glycoprotein involved in cellular proliferation and differentiation, has been shown to protect against myocardial and renal ischemia-reperfusion damage. However, the role of CREG in retinal ischemia-reperfusion injury (RIRI) remains unknown. In this study, we aimed to explore the effect of CREG on RGCs apoptosis after RIRI. METHODS: We used male C57BL/6J mice to establish the RIRI model. Recombinant CREG was injected at 1 day before RIRI. The expression and distribution of CREG were examined by immunofluorescence staining and western blotting. RGCs survival was assessed by immunofluorescence staining of flat-mounted retinas. Retinal apoptosis was measured by the staining of TdT-mediated dUTP nick-end labeling and cleaved caspase-3. Electroretinogram (ERG) analysis and optomotor response were conducted to evaluate retinal function and visual acuity. The expressions of Akt, phospho-Akt (p-Akt), Bax, and Bcl-2 were analyzed by western blotting to determine the signaling pathways of CREG. RESULTS: We found that CREG expression was decreased after RIRI, and intravitreal injection of CREG attenuated RGCs loss and retinal apoptosis. Besides, the amplitudes of a-wave, b-wave, and photopic negative response (PhNR) in ERG, as well as visual function, were significantly restored after treatment with CERG. Furthermore, intravitreal injection of CREG upregulated p-Akt and Bcl-2 expression and downregulated Bax expression. CONCLUSION: Our results demonstrated that CREG protected RGCs from RIRI and alleviated retinal apoptosis by activating Akt signaling. In addition, CREG also improved retinal function and visual acuity.

Wastewater reuse and energy saving require a more decentralized urban wastewater system? Evidence from multi-objective optimal design at the city scale.

Decentralization is recognized as an emerging solution for a more sustainable urban wastewater system (UWS) for the future. However, the debate of centralization vs. decentralization at the system's planning stage remains unresolved, mainly due to the complexity of the system's spatial structure and the multiple design objectives, such as water reuse and energy conservation. This paper presents the Sustainable Urban Wastewater System Generator (SUWStor) as a tool to address this issue. Integrating a graph representation of the system structure and the ant colony algorithm, SUWStor can produce Pareto optimal solutions for system design under three objectives: minimizing the capital cost, minimizing the operational energy consumption, and maximizing the water reuse capacity. The model is used for system design in a 100-square-km new city, the Xiong'an New District in China. Compared to the solution based on human experience, the model can reduce the system's capital cost by 7% and the operational energy in the pipe network by 26%, while maintaining the water reuse capacity at 100%. With this model, the relation between the optimal system layout and the choice over different design objectives can be discussed for any given area. In our case study, the optimal capacity of WWTPs for the lowest-cost solution is 48,000 m3 per day, leading to a total number of WWTPs of 5. As the water reuse level increases to maximum, the optimal capacity reduces to 15,000 m3 per day, where the number of WWTPs is 16. The model is also able to perform significantly better than the locally optimized results, in which only the WWTP locations are fixed at their optimal values. This demonstrates the importance of a global optimization model in designing the integrated UWS.

Evaluation of uncertain signals' impact on deep reinforcement learning-based real-time control strategy of urban drainage systems.

Real-time control (RTC) is a recognized technology to enhance the efficiency of urban drainage systems (UDS). Deep reinforcement learning (DRL) has recently provided a new solution for RTC. However, the practice of DRL-based RTC has been impeded by different sources of uncertainties. The present study aimed to evaluate the impact caused by the uncertainties on DRL-based RTC to promote its application. The impact of uncertainties in the measurement of water level signals was evaluated through large-scale simulation experiments and quantified using measures of statistical dispersion of control performance distribution and relative change of control performance compared to the baseline scenario with no uncertainty. Results show that the statistical dispersion of DRL-based RTC was reduced by 15.48%-81.93% concerning random and systematic uncertainties compared to the conventional rule-based control (RBC) strategy. The findings indicated that DRL-based RTC is robust and could be reliably applied to safety-critical real-world UDS.

A Novel Bioflocculant Produced by Cobetia marina MCCC1113: Optimization of Fermentation Conditions by Response Surface Methodology and Evaluation of Flocculation Performance when Harvesting Microalgae.

A preliminary study was carried out to optimize the culture medium conditions for producing a novel microbial flocculant from the marine bacterial species Cobetia marina. The optimal glucose, yeast extract, and glutamate contents were 30, 10, and 2 g/l, respectively, while the optimal initial pH of the culture medium was determined to be 8. Following response surface optimization, the maximum bioflocculant production level of 1.36 g/l was achieved, which was 43.40% higher than the original culture medium. Within 5 min, a 20.0% (v/v) dosage of the yielded bioflocculant applied to algal cultures resulted in the highest flocculating efficiency of 93.9% with Spirulina platensis. The bioflocculant from C. marina MCCC1113 may have promising application potential for highly productive microalgae collection, according to the findings of this study.

The structure design of integrated urban drainage systems: A view of robust optimization.

Rapid urbanization puts a lot of pressure on urban water pollution from point and non-point sources, calling for the practical, specific, and integrated management of urban drainage systems (UDS). The structural design of an integrated UDS is essential for highly complex and uncertain urban water management. In this study, we developed a multi-objective robust optimization model to explore the optimal structures of UDS considering system uncertainty. We applied this model to City B, northern China, to illustrate its effectiveness. The results show that the model can produce optimal designs with a more robust performance in terms of structural uncertainty. When the uncertainty degree ranges from 5% to 20%, a considerable extra cost (increased by 1.10-2.68 times) is required to improve the robustness of UDS. With the increase in structural uncertainty, the fraction of the cost invested in the stormwater subsystem increased from 10.2% to 27.2%. The findings showed that stormwater management is efficient in coping with system uncertainty. The research results promote an understanding of robust urban drainage systems.

What Promotes Medical Overuse: Perspective on Evolutionary Game between Administration and Medical Institutions.

Medical overuse is the leading cause of high expenditure among healthcare systems worldwide, with the degree varying from region to region. There is increasing evidence to indicate that in China, National Healthcare Security Administration (NHSA) supervision plays the most crucial role in decreasing medical overuse. For medical overuse, traditional studies focus on empirical researches and qualitative analysis, most of which ignore how the two important participants, i.e., medical institutions and NHSA, affect the strategy of each other. To reduce the losses incurred by insufficient supervision, this study starts from bounded rationality, builds an evolutionary game model to study the relations between the NHSA and medical institutions, and reveals the dynamic evolution process of the supervision of NHSA and overuse of medical institutions. Through stable evolutionary strategy analysis, numerical simulation results, and sensitive experiments under diverse scenarios, we found that when profit gap of medical overuse is high or low, medical institution will adopt fixed strategy, which is medical overuse or appropriate medical use. Only when the profit gap is at a medium level will NHSA's choice affects medical institutions' strategy. Furthermore, NHSA's strategy is affected by the profit gap between medical use and supervision cost. Our work enriches the understanding of supervision for medical overuse and provides theoretical support for the NHSA to make decisions to reach an ideal condition, i.e., to supervise without exertion.

The Different Classification of Hospitals Impact on Medical Outcomes of Patients in China.

Background: In China, different classification of hospitals (COH) provide treatment for patients with different degrees of illness. COH play an important role in Chinese medical outcomes, but there is a lack of quantitative description of how much impact the results have. The objective of this study is to examine the correlation between COH on medical outcomes with the hope of providing insights into appropriate care and resource allocation. Methods: From the perspective of the COH framework, using the Urban Employee Basic Medical Insurance (UEBMI) data of Chengdu City from 2011 to 2015, with a sample size of 512,658 hospitalized patients, this study used the nested multinomial logit model (NMNL) to estimate the impact of COH on the medical outcomes. Results: The patients were mainly elderly, with an average age of 66.28 years old. The average length of stay was 9.61 days. The female and male gender were split evenly. A high level of hospitals is positively and significantly associated with the death and transfer rates (p < 0.001), which may be related to more severe illness among patients in high COH. Conclusion: The COH made a difference in the medical outcomes significantly. COH should be reasonably selected according to disease types to achieve the optimal medical outcome. So, China should promote the construction of a tiered delivery system.

Exploring the discharge characteristics of personal care behaviors for high precision estimation of microplastic emission.

Microplastics (MPs) from personal care and cosmetic products (PCCPs) pose a threat to aquatic environment due to the small size and the complexity of composition. Although the habits of personal care behaviors (PCBs) vary from individuals affecting MPs emissions, quantitative research is not sufficient to support high-precision emission estimates and targeted management decisions. Based on a questionnaire survey about PCBs and laboratory experiments on corresponding PCCPs utilization, this study proposed a bottom-up micro-simulation method to quantify MPs emissions combining multinomial logit model and categorized emission coefficients, and identified the impact of individual attributes on the emissions. The results show that the annual PCBs-derived MPs emissions amounted to 2931.8 trillion particles in China, of which teeth brushing, face washing, and bathing behavior accounted for 29%, 36% and 35%, respectively. The residents discharged an average of 2.18 million particles per capita per year with 95% confidence interval of 0.58-4.34 million particles. Gender, age and living region had greater impacts on PCBs-derived MPs emissions. The effect of living region was significantly related to local temperature and humidity. The estimation based on the MPs discharge characteristics of PCBs provides high-precision method regarding the MPs emission from people's daily life and contributes to further understanding the source of MPs and initiating environmental control strategies.

Asperosaponin VI protects mice from sepsis by regulating Hippo and Rho signaling pathway.

OBJECTIVE: To explore the novel protective effect of Asperosaponin VI (AVI) on sepsis and its potential mechanism. METHODS: In in vitro experiments, bone marrow mononuclear cells and THP-1-derived cells were used to evaluate the viability of AVI treatment. Besides, the quantitative real-time PCR and Western blot were adopted to explore the protective effect of AVI on LPS-induced inflammation. For in vivo work, the effect of AVI on mice was evaluated by using both CLP-induced and the LPS-induced sepsis mice model. The fluctuation of anal temperature and the behavior of mice were recorded after surgery. Further, the content of bacteria in peritoneal lavage fluid was detected, as well as the levels of ALT, AST, LD and LDH in serum with ELISA. H&E staining and real-time PCR were used to evaluate the histopathology of liver, spleen and lung. Finally, relevant signaling pathways were detected by Western blot, real-time PCR and immunohistochemistry. RESULTS: AVI inhibited the expression of inflammatory factors in both CLP-induced and LPS-induced sepsis mice models, and reduced the number of bacteria in abdominal lavage fluid. The preventive treatment with AVI alleviated sepsis-induced organ injuries, reduced inflammatory responses, which was through inhibiting Hippo and Rho signaling pathway. CONCLUSIONS: This study indicated that AVI effectively protected mice from sepsis by down-regulating the activation of Hippo signaling and Rho family, and reducing inflammation and organ damage. However, conventional treatment was using antibiotics, and its mechanism was different with AVI.

Application of Platelet-Rich Fibrin Transplantation for Large Macular Hole.

Purpose Large idiopathic macular hole (MH) has a lower closure rate and poor visual prognosis. To increase the closure rate and the visual outcome in patients with large MH, we evaluate a technique of platelet-rich fibrin (PRF) membrane transplantation for the treatment of large MH.Methods This was a prospective interventional study. Seventeen eyes of 17 patients (8 males and 9 females) with large MH (654.94 ± 188.08 µm) underwent pars plana vitrectomy and internal limiting membrane peeling followed by PRF transplantation between January 2019 and December 2020. The patients were followed up for at least 6 months. Preoperatively and postoperatively, all patients underwent comprehensive ophthalmic examinations, including best-corrected visual acuity (BCVA), intraocular pressure, slit-lamp biomicroscopy, indirect ophthalmoscopy, ultra-widefield retinal imaging, optical coherent tomography, and optical coherent tomography angiography.Results All the patients achieved complete and consistent hole closure after the surgery (100%). At 6 months follow-up, the external limiting membrane defects were observed in 3 eyes (17.64%), and the ellipsoid zone defects were observed in 10 eyes (58.82%). The preoperative BCVA was 1.21 ± 0.33 in logMAR. Postoperatively, the BCVA was significantly improved to 0.64 ± 0.22 in logMAR at 6 months (p < 0.001). The foveal avascular zone reduced significantly from 0.41 ± 0.08 mm2 to 0.26 ± 0.07 mm2 (p < 0.001). No complications were observed during or after the operation.Conclusions All patients in this study have achieved good anatomic and functional results, which indicate that the application of PRF transplantation is an effective and safe technique for large MH.

Synthesis of Bitopic Ligands as Potent Dopamine D2 Receptor Agonists.

In this study, we designed and synthesized twelve bitopic ligands as dopamine D2 receptor (D2 R) agonists. The forskolin-induced cAMP accumulation assay revealed that all the finial compounds are able to activate D2 R. Furthermore, bitopic ligand N-((trans)-4-(((2,3-dihydro-1H-inden-2-yl)(propyl)amino)methyl)cyclo-hexyl)-1H-pyrrolo[2,3-b]pyridine-2-carboxamide (11 b) showed 21-fold higher potency than lead compound propyl aminoindane (2) and 17-fold higher subtype selectivity for D2 R over D4 R, indicating that the optimal length of spacer affects the D2 R functionality. Molecular modeling study exhibited that 11 b formed an electrostatic interaction and two H-bonds with amino acid Asp114, which contributes significantly to the D2 R functional activity. Taken together, we discovered a bitopic ligand 11 b as potent D2 R agonist, which may be used as a tool compound for further study.

Machine learning approaches for the prediction of postoperative complication risk in liver resection patients.

BACKGROUND: For liver cancer patients, the occurrence of postoperative complications increases the difficulty of perioperative nursing, prolongs the hospitalization time of patients, and leads to large increases in hospitalization costs. The ability to identify influencing factors and to predict the risk of complications in patients with liver cancer after surgery could assist doctors to make better clinical decisions. OBJECTIVE: The aim of the study was to develop a postoperative complication risk prediction model based on machine learning algorithms, which utilizes variables obtained before or during the liver cancer surgery, to predict when complications present with clinical symptoms and the ways of reducing the risk of complications. METHODS: The study subjects were liver cancer patients who had undergone liver resection. There were 175 individuals, and 13 variables were recorded. 70% of the data were used for the training set, and 30% for the test set. The performance of five machine learning models, logistic regression, decision trees-C5.0, decision trees-CART, support vector machines, and random forests, for predicting postoperative complication risk in liver resection patients were compared. The significant influencing factors were selected by combining results of multiple methods, based on which the prediction model of postoperative complications risk was created. The results were analyzed to give suggestions of how to reduce the risk of complications. RESULTS: Random Forest gave the best performance from the decision curves analysis. The decision tree-C5.0 algorithm had the best performance of the five machine learning algorithms if ACC and AUC were used as evaluation indicators, producing an area under the receiver operating characteristic curve value of 0.91 (95% CI 0.77-1), with an accuracy of 92.45% (95% CI 85-100%), the sensitivity of 87.5%, and specificity of 94.59%. The duration of operation, patient's BMI, and length of incision were significant influencing factors of postoperative complication risk in liver resection patients. CONCLUSIONS: To reduce the risk of complications, it appears to be important that the patient's BMI should be above 22.96 before the operation, and the duration of the operation should be minimized.

Cost Control of Treatment for Cerebrovascular Patients Using a Machine Learning Model in Western China.

Background: Cerebrovascular disease has been the leading cause of death in China since 2017, and the control of medical expenses for these diseases is an urgent issue. Diagnosis-related groups (DRG) are increasingly being used to decrease the costs of healthcare worldwide. However, the classification variables and rules used vary from region to region. Of these variables, the question of whether the length of stay (LOS) should be used as a grouping variable is controversial. Aim: To identify the factors influencing inpatient medical expenditure in cerebrovascular disease patients. The performance of two sets of classification rules, and the effects of the extent of control of unreasonable medical treatment, were compared, to investigate whether the classification variables should include LOS. Methods: Data from 45,575 inpatients from a Healthcare Security Administration of a city in western China were used. Kruskal-Wallis H tests were used for single-factor analysis, and multiple linear stepwise regression was used to determine the main factors. A chi-squared automatic interaction detector (CHAID) algorithm was built as a decision tree model for grouping related data. The intensity of oversupply of service was controlled step by step from 10% to 100%, and the performance was calculated for each group. Results: The average hospitalization cost was 1,284 US dollars, and the total was 51.17 million US dollars. Of this, 43.42 million were paid by the government, and 7.75 million were paid by individuals. Factors including gender, age, type of insurance, level of hospital, LOS, surgery, therapeutic outcomes, main concomitant disease, and hypertension significantly influenced inpatient expenditure (P < 0.05). Incorporating LOS, the patients were divided into seven DRG groups, while without LOS, the patients were divided into eight DRG groups. More clinical variables were needed to achieve good results without LOS. Of the two rule sets, smaller coefficient of variation (CV) and a lower upper limit for patient costs were found in the group including LOS. Using this type of economic control, 3.35 million US dollars could be saved in one year.

Risk factors associated with postoperative complications after liver cancer resection surgery in western China.

OBJECTIVES: Postoperative complications increase the workload of nursing staff as well as the financial and mental distress suffered by patients. The objective of this study is to identify clinical factors associated with postoperative complications after liver cancer resection surgery. METHODS: Data from liver cancer resections occurring between January 1st, 2019 to December 31st, 2019 was collected from the Department of Liver Surgery in West China Hospital of Sichuan University. The Kruskal-Wallis test and logistic regression were used to perform single-factor analysis. Stepwise logistic regression was used for multivariate analysis. Models were established using R 4.0.2 software. RESULTS: Based on data collected from 593 cases, the single-factor analysis determined that there were statistically significant differences in BMI, incision type, incision length, duration, incision range, and bleeding between cases that experienced complications within 30 days after surgery and those did not. Stepwise logistic regression models based on Kruskal-Wallis test and single-factor logistic regression determined that BMI, incision length, and duration were the primary factors causing complications after liver resection. The adjust OR of overweight patients and patients with obesity (stage 1) compared to low weight patients were 0.12 (95% CI:0.02-0.72) with p = 0.043 and 0.18 (95% CI:0.03-1.00) with p = 0.04, respectively. An increase of 1 cm in incision length increased the relative risk by 13%, while an increase of 10 min in surgical duration increased the relative risk by 15%. CONCLUSIONS: The risk of postoperative complications after liver resection can be significantly reduced by controlling factors such as bleeding, incision length, and duration of the surgery.