An integrated machine learning model enhances delayed graft function prediction in pediatric renal transplantation from deceased donors.

BACKGROUND: Kidney transplantation is the optimal renal replacement therapy for children with end-stage renal disease; however, delayed graft function (DGF), a common post-operative complication, may negatively impact the long-term outcomes of both the graft and the pediatric recipient. However, there is limited research on DGF in pediatric kidney transplant recipients. This study aims to develop a predictive model for the risk of DGF occurrence after pediatric kidney transplantation by integrating donor and recipient characteristics and utilizing machine learning algorithms, ultimately providing guidance for clinical decision-making. METHODS: This single-center retrospective cohort study includes all recipients under 18 years of age who underwent single-donor kidney transplantation at our hospital between 2016 and 2023, along with their corresponding donors. Demographic, clinical, and laboratory examination data were collected from both donors and recipients. Univariate logistic regression models and differential analysis were employed to identify features associated with DGF. Subsequently, a risk score for predicting DGF occurrence (DGF-RS) was constructed based on machine learning combinations. Model performance was evaluated using the receiver operating characteristic curves, decision curve analysis (DCA), and other methods. RESULTS: The study included a total of 140 pediatric kidney transplant recipients, among whom 37 (26.4%) developed DGF. Univariate analysis revealed that high-density lipoprotein cholesterol (HDLC), donor after circulatory death (DCD), warm ischemia time (WIT), cold ischemia time (CIT), gender match, and donor creatinine were significantly associated with DGF (P < 0.05). Based on these six features, the random forest model (mtry = 5, 75%p) exhibited the best predictive performance among 97 machine learning models, with the area under the curve values reaching 0.983, 1, and 0.905 for the entire cohort, training set, and validation set, respectively. This model significantly outperformed single indicators. The DCA curve confirmed the clinical utility of this model. CONCLUSIONS: In this study, we developed a machine learning-based predictive model for DGF following pediatric kidney transplantation, termed DGF-RS, which integrates both donor and recipient characteristics. The model demonstrated excellent predictive accuracy and provides essential guidance for clinical decision-making. These findings contribute to our understanding of the pathogenesis of DGF.

First Report of Yellow Leaf Spots on Maize Caused by Colletotrichum siamense in Yunnan Province, China.

The southwest maize planting area is the third largest maize-producing region in China, including the entire provinces of Sichuan, Yunnan and Guizhou, parts of Guangxi and Hunan provinces. In June 2022, yellow leaf spot symptoms were observed commonly on maize in southern Yunnan province, including Pu'er City, Xishuangbanna Dai autonomous prefecture and Honghe Hani & Yi autonomous prefecture. The disease incidence on maize in Pu'er ranged from 10% to 20% from June to August. The initial symptoms appeared as needle-like spots scattered on the leaf surface with obvious yellow haloes, with a diameter ranging from 0.2 to 2 mm and were quite similar to maize Curvularia leaf spot. But the lesion size did not expand significantly and without reddish or dark brown margins. In July 2023, 30 diseased leaves were collected in Pu'er City, Yunnan Province. Leaf tissues (3×3 mm) were cut from the infected margins, surface disinfested with 75% ethanol for 30 s, 2% sodium hypochlorite for 2 min, and rinsed three times with sterile water, then placed on PDA at 25℃. Forty-eight isolates with the morphological characteristics of Colletotrichum ssp. were obtained by single-spore isolations (isolation frequency 42.5%). The fungal colonies on PDA were dense with white mycelia on the edges, and yellowish-white on the reverse side. The conidia were transparent, cylindrical, smooth-walled, and 6.8 to 17.5 × 3.8 to 6.5 µm. Two isolates (YNH-1 and YNH-2) were used for DNA extraction. The ribosomal internal transcribed spacer (ITS), actin (ACT), calmodulin (CAL), glyceraldehyde-3-phosphate dehydrogenase (GAPDH) and ß-tubulin 2 (TUB2) regions were amplified by PCR. The PCR primers in this study were as described previously (Weir et al. 2012). The sequences of both isolates were 100% identical, and all sequences showed >98% identity with Colletotrichum siamense in the GenBank. The sequences were deposited in GenBank (ITS, PP237394; ACT, PP265410; CAL, PP265411; GAPDH, PP265412; TUB2, PP265413). A phylogenetic tree was constructed by MEGA_v. 11.0.13 with the Maximum Likelihood (ML) method. The isolate YNH-1 and YNH-2 clustered with C. siamense DAR 76934 (97% bootstrap support) in the same branch. Pathogenicity tests were performed on the susceptible maize variety B73. Twelve healthy maize seedlings were inoculated with a conidial suspension (1×106 conidia/ml) of isolate YNH-1. All the seedlings were kept in an incubator at 26℃, with a 90% humidity and a 12 h light/dark cycle. After 5 days, yellow spots appeared on the leaves of the plants. The symptoms on inoculated leaves were similar to those observed in the field after 10 days, whereas no symptoms appeared in the control. The pathogen C. siamensis was re-isolated from the infected leaves, which fulfilled the Koch's postulates. C. siamense can cause leaf diseases on a wide range of hosts. It has been reported causing anthracnose on tea (Camellia sinensis) (Wang et al. 2016) and wax apple (Syzygium samarangense) (Yao et al. 2023) in Yunnan Province, China. To our knowledge, this is the first report of C. siamense causing yellow leaf spots on maize in China as well as a new host record for C. siamense causing leaf disease. However, how C. siamense spreads among different host plants in the region is still unknown. This study provides important information for epidemiological study and comprehensive management of yellow leaf spot on maize.

Exploration of exciton dynamics in GaTe nanoflakes via temperature- and power-dependent time-resolved photoluminescence spectra.

GaTe nanoflakes have been receiving much research attention recently due to their applications in optoelectronic devices, such as anisotropic non-volatile memory, solar cells, and high-sensitivity photodetectors from the ultraviolet to the visible region. Further applications, however, have been impeded due to the limited understanding of their exciton dynamics. In this work we perform temperature- and power-dependent time-resolved photoluminescence (PL) spectra to comprehensively investigate the exciton dynamics of GaTe nanoflakes. Temperature-dependent PL measurements manifest that spectral profiles of GaTe nanoflakes change dramatically from cryogenic to room temperature, where the bound exciton and donor-to-acceptor pair transition normally disappear above 100 K, while the charged exciton survives to room temperature. The lifetimes of these excitons and their evolution vs temperature have been uncovered by time-resolved PL spectra. Further measurements reveal the entirely different power-dependent exciton behaviors of GaTe nanoflakes between room and cryogenic temperatures. The underlying mechanisms have been proposed to explore the sophisticated exciton dynamics within GaTe nanoflakes. Our results offer a more thorough understanding of the exciton dynamics of GaTe nanoflakes, enabling further progress in engineering GaTe-based applications, such as photodetectors, light-emitting diodes, and nanoelectronics.

Great enhancement on two-photon photoluminescence imaging contrast of Au nanoparticles via double-pulse femtosecond laser excitation with controlled phase differences.

Au nanoparticles are attractive contrast agents for noninvasive living tissue imaging with deep penetration because of their strong two-photon photoluminescence (TPPL) intensity and excellent biocompatibility. However, the inevitable phototoxicity and huge auto-fluorescence are consistently associated with laser excitation. Therefore, enhancement of TPPL intensity and suppression of backgrounds are always highly desired under the demand of reducing excitation powers. In this work, we develop a double-pulse TPPL (DP-TPPL) scheme with controlled phase differences (Δφ) between the double pulses to significantly improve the signal-to-noise ratio (SNR) of TPPL imaging. Under the modulated phase (Δφ periodically varying between 0-2π), our results show that SNR can be improved from 4.3 to 1715, with an enhancement of up to 400 folds at the integration of 50 ms. More importantly, this enhancement can be unlimitedly lifted by increasing the number of photons or integration times in principle. Further boosting has been achieved by reducing the magnitude of background noises; subsequently, SNR is improved by more than 104 times. Our schemes offer great potential for reducing phototoxicity and extracting extremely weak signals from huge backgrounds and open up a new possibility for a rapid, flexible, and reliable medical diagnosis by TPPL imaging with diminished laser powers.

The correlations of psychological status, quality of life, self-esteem, social support and body image disturbance in Chinese patients with Systemic Lupus Erythematosus.

This study aimed (i) to complement existing research by focusing on body image disturbance issues in Chinese Systemic Lupus Erythematosus (SLE) patients; (ii) to investigate how Chinese patients make sense of disease diagnosis and perceived cultural influences within the context of their SLE. A total of 118 SLE patients underwent standardized laboratory examinations and completed several questionnaires. Independent sample t-test, Mann-Whitney U-test, Chi-square test, and multivariate analysis using backward stepwise logistic regression model were used to analyze these data. We found 18.3% SLE patients had BID, which were significantly higher than the control group (.8%). SLE patients are more concerned about their physical changes caused by disease. There were significant correlations among personal health insurance, complication of diabetes, appearance of new rash, depression, anxiety, self-esteem and BID in patients with SLE. Meanwhile, logistic regression analysis revealed that appearance of new rash and high anxiety were significantly associated with BID in SLE patients. In conclusion, it is beneficial to pay attention to the physical and mental health of patients with rheumatic disease from the perspective of body image, to understand their needs and to provide effective and effective service for them.

Inter-rater reliability of three most commonly used pressure ulcer risk assessment scales in clinical practice.

The objective of this study was to evaluate inter-rater reliability of Braden Scale, Norton Scale and Waterlow Scale for pressure ulcer risk assessment in clinical practice. The design of the study was cross-sectional. A total of 23 patients at pressure ulcer risk were included in the study, and 6 best registered nurses conducted three subsequent risk assessments for all included patients. They assessed alone and independently from each other. An intra-class correlation coefficient (ICC) was used to determine the inter-rater reliability. For the Braden Scale, the ICC values ranged between 0·603 (95% CI: 0·435-0·770) for the item 'moisture' and a maximum of 0·964 (95% CI: 0·936-0·982) for the item 'activity'; for the Norton Scale, the ICC values ranged between 0·595 (95% CI: 0·426-0·764) for the item 'physical condition' and a maximum of 0·975 (95% CI: 0·955-0·988) for the item 'activity'; and for the Waterlow Scale, the ICC values ranged between 0·592 (95% CI: 0·422-0·762) for the item 'skin type' and a maximum of 0·990 (95% CI: 0·982-0·995) for the item 'activity'. The ICC values of total score for three scales of were 0·955 (95% CI: 0·922-0·978), 0·967 (95% CI: 0·943-0·984), and 0·915 (95% CI: 0·855-0·958) for Braden, Norton, and Waterlow scales, respectively. Although the inter-rater reliability of Braden Scale, Norton Scale and Waterlow Scale total scores were all substantial, the reliability of some items was not so good. The items of 'moisture', 'physical condition' and 'skin type' should be paid more attention. However, some studies are needed to find out high reliable quantitative items to replace these ambiguous items in new designed scales.

Meiotic actin rings are essential for proper sporulation in fission yeast.

Sporulation is a unique form of cytokinesis that occurs following meiosis II in many yeasts, during which four daughter cells (spores) are generated within a single mother cell. Here we characterize the role of F-actin in the process of sporulation in the fission yeast Schizosaccharomyces pombe. As shown previously, we find that F-actin assembles into four ring structures per ascus, referred to as the meiotic actin ring (MeiAR). The actin nucleators Arp2/3 and formin For3 assemble into ring structures that overlap with Meu14, a protein known to assemble into the so-called leading edge, a ring structure that is known to guide forespore membrane assembly. Interestingly, F-actin makes rings that occupy a larger region behind the leading edge ring. Time-lapse microscopy showed that the MeiAR assembles near the spindle pole bodies and undergoes an expansion in diameter during the early stages of meiosis II, followed by closure in later stages of meiosis II. MeiAR closure completes the process of forespore membrane assembly. Loss of the MeiAR leads to excessive assembly of forespore membranes with a deformed appearance. The rate of closure of the MeiAR is dictated by the function of the septation initiation network (SIN). We conclude that the MeiAR ensures proper targeting of the membrane biogenesis machinery to the leading edge, thereby ensuring the formation of spherical spores.

The quality of life in Chinese patients with systemic lupus erythematosus is associated with disease activity and psychiatric disorders: a path analysis.

OBJECTIVES: To identify the socioeconomic status, disease activity and psychiatric disorders that contribute to the health-related quality of life (HRQOL) in systemic lupus erythematosus (SLE) patients. METHODS: Data were collected from 170 SLE patients and 210 healthy individuals. All of the patients fulfilled the criteria for the classification of SLE and underwent disease activity assessment according to the SLE disease activity index (SLEDAI). Self-rated scales for anxiety (SAS) and depression (SDS) were used to evaluate the levels of anxiety and depression. The patients' general health status was measured using the Short Form (SF)-36 questionnaire. To provide greater clarity regarding the determinants of HRQOL, path analysis was used to explore the relationships between the various predictors and the health-related quality of life (HRQoL). RESULTS: SLE patients who have depression and anxiety are more likely to have a lower quality of life compared to those who are not depressed (r=-0.735, p<0.01; r=-0.684, p<0.01). All of the variables were significantly correlated with depression except age, gender and marital status. Education was negatively correlated with disease activity (r=-0.272, p<0.05) and anxiety (r=-0.312, p<0.01). Disease activity was positively correlated with anxiety (r=0.198, p<0.05). In addition, work status also correlated with anxiety (r=-0.294, p<0.01). A path-analytic models analysis suggested that the main influencing factors of HRQoL are the following: depression, anxiety, education level, income/family, disease activity, age, and work status. A χ2 test (χ215=17.71, p=0.28>0.05) indicated that the path analysis model had an adequate goodness of fit value. Depression (ß=-0.616, p<0.05) contributed the most to HRQOL. Depression, anxiety and disease activity contributed to HRQoL both directly and indirectly through other factors. Socioeconomic factors such as education, income/family and work status, however, did not contribute directly to HRQoL. CONCLUSIONS: HRQoL in SLE is influenced by disease activity and psychiatric disorders. Socioeconomic status has no direct influence on the quality of life of lupus patients, while disease activity has a direct impact on the quality of life. Anxiety and depression were significant predictors of poor HRQoL. Understanding how these factors are inter-related may help clinicians focus their assessments and develop strategies to improve the HRQoL of lupus patients.

Electrophotocatalytic Tellurosulfonylation of Alkynes for the Synthesis of ß-(Telluro)vinyl Sulfones.

Difunctionalization of alkynes has gained a lot of interest in current organic chemistry. Herein, we developed an electrophotocatalytic multicomponent cascade reaction of alkynes and indoles with sulfinic acid sodium salts using elemental tellurium as the tellurium source. Using synergistic anodic oxidation and visible-light irradiation, various ß-(telluro)vinyl sulfones have been prepared. This strategy features mild reaction conditions, excellent substrate scope, readily available starting materials, and great functional group tolerance.

Optimizing the Probabilistic Neural Network Model with the Improved Manta Ray Foraging Optimization Algorithm to Identify Pressure Fluctuation Signal Features.

To improve the identification accuracy of pressure fluctuation signals in the draft tube of hydraulic turbines, this study proposes an improved manta ray foraging optimization (ITMRFO) algorithm to optimize the identification method of a probabilistic neural network (PNN). Specifically, first, discrete wavelet transform was used to extract features from vibration signals, and then, fuzzy c-means algorithm (FCM) clustering was used to automatically classify the collected information. In order to solve the local optimization problem of the manta ray foraging optimization (MRFO) algorithm, four optimization strategies were proposed. These included optimizing the initial population of the MRFO algorithm based on the elite opposition learning algorithm and using adaptive t distribution to replace its chain factor to optimize individual update strategies and other improvement strategies. The ITMRFO algorithm was compared with three algorithms on 23 test functions to verify its superiority. In order to improve the classification accuracy of the probabilistic neural network (PNN) affected by smoothing factors, an improved manta ray foraging optimization (ITMRFO) algorithm was used to optimize them. An ITMRFO-PNN model was established and compared with the PNN and MRFO-PNN models to evaluate their performance in identifying pressure fluctuation signals in turbine draft tubes. The evaluation indicators include confusion matrix, accuracy, precision, recall rate, F1-score, and accuracy and error rate. The experimental results confirm the correctness and effectiveness of the ITMRFO-PNN model, providing a solid theoretical foundation for identifying pressure fluctuation signals in hydraulic turbine draft tubes.

PGK1 Is Involved in the HIF-1 Signaling Pathway as a Hub Gene for Ferroptosis After Traumatic Brain Injury.

The pathogenesis of ferroptosis in traumatic brain injury (TBI) is unclear; therefore, we aimed to identify key molecules associated with ferroptosis in TBI using bioinformatics analysis to determine its underlying mechanisms. GSE128543 dataset was downloaded from the Gene Expression Omnibus (GEO) database, and TBI-associated modules were obtained by weighted gene co-expression network analysis (WGCNA). We identified 60 differentially expressed genes (DEGs) by intersecting the modules with ferroptosis and glycolysis/gluconeogenesis gene libraries. The hypoxia-inducible factor-1 (HIF-1) signaling pathway was identified to be critical for ferroptosis post-TBI, and protein-protein interaction (PPI) network identified 20 hub genes, including phosphoglycerate kinase 1 (PGK1), ribosomal protein (RP) family, pyruvate kinase M1/2 (PKM), hypoxia-inducible factor 1α subunit (HIF-1α), and MYC genes. In this study, we further explored the role of PGK1, a gene involved in HIF-1 signaling pathway; however, its role and mechanism in TBI are still unclear. Moreover, we constructed a TBI mouse model and examined PGK1 and HIF-1α expression levels, and the results revealed their expressions increased after cortical injury in mice and they co-localized in the same cells. Furthermore, we examined the expressions of PGK1 in the cerebrospinal fluid of 20 clinical patients with different degrees of brain injuries within 48 h of surgery and examined the cognitive function of patients according to the Glasgow Coma Scale (GCS). The results revealed that PGK1 expression level was negatively correlated with the severity of the brain injury. These findings suggest that PGK1 may become a potential hub gene for ferroptosis via the HIF-1 signaling pathway, second to neurological injury after TBI, thereby affecting patient prognosis.

Posttransplant complications: molecular mechanisms and therapeutic interventions.

Posttransplantation complications pose a major challenge to the long-term survival and quality of life of organ transplant recipients. These complications encompass immune-mediated complications, infectious complications, metabolic complications, and malignancies, with each type influenced by various risk factors and pathological mechanisms. The molecular mechanisms underlying posttransplantation complications involve a complex interplay of immunological, metabolic, and oncogenic processes, including innate and adaptive immune activation, immunosuppressant side effects, and viral reactivation. Here, we provide a comprehensive overview of the clinical features, risk factors, and molecular mechanisms of major posttransplantation complications. We systematically summarize the current understanding of the immunological basis of allograft rejection and graft-versus-host disease, the metabolic dysregulation associated with immunosuppressive agents, and the role of oncogenic viruses in posttransplantation malignancies. Furthermore, we discuss potential prevention and intervention strategies based on these mechanistic insights, highlighting the importance of optimizing immunosuppressive regimens, enhancing infection prophylaxis, and implementing targeted therapies. We also emphasize the need for future research to develop individualized complication control strategies under the guidance of precision medicine, ultimately improving the prognosis and quality of life of transplant recipients.

Ant colony optimization-based adjusted PID parameters: a proposed method.

The ant colony algorithm (ACA) is a heuristic algorithm that resolves the optimality problem by simulating an ant's foraging process, which finds the shortest path. The connotation of the ACA is to find the optimal solution. The Proportional Integral Derivative (PID) parameter tuning is an essential tool in the control field and includes three parameters, Kp, Ki, and Kd, to achieve the best control effect. Besides, tuning the PID parameters is closely related to finding the "optimal" solution that can be attained based on the feasible combination of the two. This article transforms the PID parameter tuning problem into an ACA that finds the optimal solution called ACA-based PID parameters tuning. Furthermore, PID control is simulated by setting the parameters of ACA, such as ant colony size, iteration times, nodes, paths, path evaluation criteria, pheromone concentration, heuristic function, weight factor, and decision function. Eventually, the two PID controller parameter tuning strategies are compared and analyzed, and the advantages and disadvantages of each are obtained. Compared with the 4:1 attenuation curve method, the proposed method can significantly reduce the MP score of the overshoot of the system, increase the time, and improve the dynamic and steady-state performance of the system, but reduce the steady-state error of the system. Therefore, the feasibility and effectiveness of the proposed method is verified.

[The prevalence and distributing feature of atrial fibrillation in Xinjiang Uygur Autonomous Region Kazaks adult population].

OBJECTIVE: To investigate the prevalence and distributing feature of atrial fibrillation (AF) in Xinjiang Kazaks adult population. METHODS: Four-stage selected random samples aged 30-89 years from Tacheng, Yili and Aletai were analyzed. An epidemical study of AF was performed including inquiring medical history, recording electrocardiogram and auscultation. RESULTS: A total of 22 514 adults were surveyed. The prevalence of AF in Xinjiang Kazaks adult population was 0.37%, which was increasing with aging. The prevalence was higher in men than in women (0.5% vs 0.2%, P < 0.01). In AF patients, 23 was valvular AF. Ischemic stroke was the most frequent type and the stroke rate in the patients with AF was significantly higher than that without AF (6.0% vs 1.2%, P < 0.01). CONCLUSIONS: The prevalence of AF in Xinjiang Kazaks adult population is lower than the reported national prevalence but patients with AF in this population would not like to take the necessary medicine. Therefore, the control of AF need to be reinforced.

Is Resilient Transportation Infrastructure Low-Carbon? Evidence from High-Speed Railway Projects in China.

Establishing resilient transport infrastructure is an effective way for cities to deal with external disturbances and uncertainties during rapid urbanization. However, human society is presently facing a series of sustainable development obstacles, where the energy shortage and environmental pollution are catching significant concerns. Hence, it is imperative to investigate the carbon emission of the growing number of resilient transportation infrastructure (RTI) projects. Through extracting the carbon emission factor (CEF), this study built the carbon emission measurement model (CEMM) to evaluate the carbon emission of 26 resilient high-speed railway construction projects in China. The results indicated that the carbon emissions of the entire high-speed railway infrastructure projects in China show regional and social environmental differences. Meanwhile, there are potential correlations and positive relationships between the resilience of the high-speed railway infrastructure projects and their carbon emission. Suggestions and recommendations for governments and construction enterprises are put forward to further improve the resilient and low-carbon development of transportation infrastructure in China.

Empirical Research on the Critical Success Factors of Construction Program.

Scientific identification of the factors that underpin the success of construction program can effectively promote the success of construction program. Based on literature statistics, this paper developed the measurement items of key success factors of construction program in Chinese context. Based on exploratory factor analysis, seven key success factors of construction program were extracted. Then, the excellence model of construction program was constructed by referring to the ideas, concepts, and theoretical mechanisms of EFQM model. The research conclusions of this paper provide a systematic and holistic guidance for the successful implementation of the program by the construction program organization and promote the success of the program.

TTC7B Is a Novel Prognostic-Related Biomarker in Glioma Correlating with Immune Infiltrates and Response to Oxidative Stress by Temozolomide.

Background: Gliomas are one of the most prevalent malignant brain tumors. Hence, identifying biological markers for glioma is imperative. TTC7B (Tetratricopeptide Repeat Domain 7B) is a gene whose role in cancer in currently identified. To this end, we examined the TTC7B expression as well as its prognostic significance, biological roles, and immune system impacts in patients with glioma. Methods: We evaluated the function of TTC7B in GBM and LGG through the published CGGA (Chinese Glioma Genome Atlas) and TCGA (The Cancer Genome Atlas) databases. CIBERSORT and TIMER were used to analyze the link between TTC7B and immune cells, while R was used for statistical analysis. In addition, Transwell analysis, including migration and invasion assays, was performed to identify the relationship between TTC7B and temozolomide. Results: Low expression of TTC7B was observed in GBM and LGG. 1p/19q codeletion, IDH mutation, chemotherapy, and grade were found to have a significant correlation with TTC7B. Besides, low TTC7B expression was linked with low overall survival (OS) in both GBM and LGG. In the Cox analysis, TTC7B was found to independently function as a risk element for OS of patients with glioma. Furthermore, CIBERSORT analysis demonstrated a positive link between TTC7B and multiple immune cells, especially activated NK cells. Transwell analysis, including migration and invasion assays, revealed that temozolomide reduced the migration and invasion capacity of glioma cells and increased the expression of TTC7B. Conclusion: In all, TTC7B could serve as a promising prognostic indicator of LGG and GBM, and is closely associated with immune infiltration and response to oxidative stress by temozolomide.

Meta-Analysis on the Application Value of Collaborative Nursing in Postcolostomy Nursing of Patients with Colorectal Cancer.

OBJECTIVE: To systematically evaluate the effect of collaborative nursing on self-care ability of postcolostomy patients with colorectal cancer (CRC). METHODS: PubMed, Web of Science, Embase, China National Knowledge Infrastructure, and Wanfang databases were searched to collect relevant literatures on randomized controlled trials of postcolostomy patients with CRC. The search period was started from 2010 to 2021. Statistical analysis was performed on the data extracted from the comprehensive meta-analysis with STATA 16.0 analysis software. RESULTS: As a result, it was found that the incidence of adverse reactions in the control group was higher than that in the treatment group. Seven studies included the preintervention self-care concept and preintervention self-care skills. Six studies included preintervention self-care responsibility and preintervention exercise of self-care agency (ESCA) scale. In the comparison among the concept of self-care after intervention, self-care skills, self-care responsibility, and ESCA scale, all of them had higher scores in the treatment group than in the control group (P < 0.05). It fully explains that collaborative nursing can significantly improve the evaluation indicators of patients' self-care ability and reduce patient complications. CONCLUSION: The application of collaborative nursing in the nursing work of patients with CRC after colostomy can significantly reduce the incidence of adverse nursing reactions.

Study on the Behavior of Electrochemical Extraction of Cobalt from Spent Lithium Cobalt Oxide Cathode Materials.

The molten salt electrochemical method was used to reduce the Co in spent LiCoO2. The reduction mechanism of Co (III) in LiCoO2 was analyzed by cyclic voltammetry, square wave voltammetry, and open circuit potential. The reduction process of Co (III) on Fe electrode was studied in NaCl-CaCl2-LiCoO2 molten salt system at 750 °C. The results show that the reduction process of Co (III) is a two-step reduction: Co (III) → Co (II) → Co (0) and they are all quasi-reversible processes controlled by diffusion. Phase analysis (XRD) shows that Li+ and Cl2- in the molten salt form LiCl electrolysis experiments with different voltages were carried out, which proved the stepwise reduction of Co in LiCoO2.

Electrochemical Mechanism of Recovery of Nickel Metal from Waste Lithium Ion Batteries by Molten Salt Electrolysis.

With the widespread use of lithium-ion batteries, the cumulative amount of used lithium-ion batteries is also increasing year by year. Since waste lithium-ion batteries contain a large amount of valuable metals, the recovery of valuable metals has become one of the current research hotspots. The research uses electrometallurgical technology, and the main methods used are cyclic voltammetry, square wave voltammetry, chronoamperometry and open circuit potential. The electrochemical reduction behavior of Ni3+ in NaCl-CaCl2 molten salt was studied, and the electrochemical reduction behavior was further verified by using a Mo cavity electrode. It is determined that the reduction process of Ni3+ in LiNiO2 is mainly divided into two steps: LiNiO2 → NiO → Ni. Through the analysis of electrolysis products under different conditions, when the current value of LiNiO2 is not less than 0.03 A, the electrolysis product after 10 h is metallic Ni. When the current reaches 0.07 A, the current efficiency is 77.9%, while the Li+ in LiNiO2 is enriched in NaCl-CaCl2 molten salt. The method realizes the separation and extraction of the valuable metal Ni in the waste lithium-ion battery.