Risk of pulmonary complications after video-assisted thoracoscopic pulmonary resection in children.

BACKGROUND: Postoperative pulmonary complications (PPCs) are associated with high mortality and morbidity rates. Children are more susceptible to PPCs owing to smaller functional residual capacity and greater closing volume. Risk factors of PPCs in children undergoing lung resection remain unclear. METHODS: This retrospective study enrolled children who underwent video-assisted thoracoscopic surgery between January 2018 and February 2023. The primary outcome was PPC occurrence. Multivariate logistic regression was used to analyze risk factors for PPCs. RESULTS: Overall, 640 children were analyzed; their median age was 7 (interquartile range: 5-11) months, and the median tidal volume was 7.66 (6.59-8.49) mL/kg. One hundred and seventeen (18.3%) developed PPCs. PPCs were independently associated with male sex (odds ratio [OR], 1.83; 95% confidence interval [CI], 1.17-2.88; P=0.008), longer OLV duration (OR, 1.01; 95% CI, 1.0-1.01; P=0.001), and less surgeon's experience (OR, 1.67; 95% CI, 1.03-2.7; P=0.036). When low-tidal-volume cutoff was defined as <8 mL/kg, PEEP level was a protective factor for PPCs (OR, 0.83; 95% CI, 0.69-1.00; P=0.046). Additionally, PPCs were associated with increased hospital stay (P<0.001). CONCLUSIONS: Male sex, longer OLV duration, less surgeon's experience, and lower PEEP were risk factors of PPCs in children undergoing video-assisted thoracoscopic surgery. Our findings may serve as targets for prospective studies investigating specific ventilation strategies for children.

Systemic delivery of tannic acid-ferric-masked oncolytic adenovirus reprograms tumor microenvironment for improved therapeutic efficacy in glioblastoma.

Glioblastoma (GBM) represents the most aggressive primary brain tumor, and urgently requires effective treatments. Oncolytic adenovirus (OA) shows promise as a potential candidate for clinical antitumor therapy, including in the treatment of GBM. Nevertheless, the systemic delivery of OA continues to face challenges, leading to significantly compromised antitumor efficacy. In this study, we developed an innovative approach by encapsulating CXCL11-armed OA with tannic acid and Fe3+ (TA-Fe3+) to realize the systemic delivery of OA. The nanocarrier's ability to protect the OA from elimination by host immune response was evaluated in vitro and in vivo. We evaluated the antitumor effect and safety profile of OA@TA-Fe3+ in a GBM-bearing mice model. OA@TA-Fe3+ effectively safeguarded the virus from host immune clearance and extended its circulation in vivo. After targeting tumor sites, TA-Fe3+ could dissolve and release Fe3+ and OA. Fe3+-induced O2 production from H2O2 relieved the hypoxic state, and promoted OA replication, leading to a remarkable alteration of tumor immune microenvironment and enhancement in antitumor efficacy. Moreover, the systemic delivery of OA@TA-Fe3+ was safe without inflammation or organ damage. Our findings demonstrated the promising potential of systemically delivering the engineered OA for effective oncolytic virotherapy against GBM.

Blind Quantum Machine Learning with Quantum Bipartite Correlator.

Distributed quantum computing is a promising computational paradigm for performing computations that are beyond the reach of individual quantum devices. Privacy in distributed quantum computing is critical for maintaining confidentiality and protecting the data in the presence of untrusted computing nodes. In this Letter, we introduce novel blind quantum machine learning protocols based on the quantum bipartite correlator algorithm. Our protocols have reduced communication overhead while preserving the privacy of data from untrusted parties. We introduce robust algorithm-specific privacy-preserving mechanisms with low computational overhead that do not require complex cryptographic techniques. We then validate the effectiveness of the proposed protocols through complexity and privacy analysis. Our findings pave the way for advancements in distributed quantum computing, opening up new possibilities for privacy-aware machine learning applications in the era of quantum technologies.

Trojan-Horse Strategy Targeting the Gut-Liver Axis Modulates Gut Microbiome and Reshapes Microenvironment for Orthotopic Hepatocellular Carcinoma Therapy.

Reversing the hepatic inflammatory and immunosuppressive microenvironment caused by gut microbiota-derived lipopolysaccharides (LPS), accumulating to the liver through the gut-liver axis, is crucial for suppressing hepatocellular carcinoma (HCC) and metastasis. However, synergistically manipulating LPS-induced inflammation and gut microbiota remains a daunting task. Herein, a Trojan-horse strategy is proposed using an oral dextran-carbenoxolone (DEX-CBX) conjugate, which combines prebiotic and glycyrrhetinic acid (GA) homologs, to targeted delivery GA to HCC through the gut-liver axis for simultaneous modulation of hepatic inflammation and gut microbiota. In the orthotopic HCC model, a 95-45% reduction in the relative abundances of LPS-associated microbiota is observed, especially Helicobacter, caused by DEX-CBX treatment over phosphate-buffered saline (PBS) treatment. Notably, a dramatic increase (37-fold over PBS) in the abundance of Akkermansia, which is known to strengthen systemic immune response, is detected. Furthermore, DEX-CBX significantly increased natural killer T cells (5.7-fold) and CD8+ T cells (3.9-fold) as well as decreased M2 macrophages (59% reduction) over PBS treatment, resulting in a tumor suppression rate of 85.4%. DEX-CBX is anticipated to offer a novel strategy to precisely modulate hepatic inflammation and the gut microbiota to address both the symptoms and root causes of LPS-induced immunosuppression in HCC.

MREDTA: A BERT and transformer-based molecular representation encoder for predicting drug-target binding affinity.

Drug-target binding affinity (DTA) prediction is vital for drug repositioning. The accuracy and generalizability of DTA models remain a major challenge. Here, we develop a model composed of BERT-Trans Block, Multi-Trans Block, and DTI Learning modules, referred to as Molecular Representation Encoder-based DTA prediction (MREDTA). MREDTA has three advantages: (1) extraction of both local and global molecular features simultaneously through skip connections; (2) improved sensitivity to molecular structures through the Multi-Trans Block; (3) enhanced generalizability through the introduction of BERT. Compared with 12 advanced models, benchmark testing of KIBA and Davis datasets demonstrated optimal performance of MREDTA. In case study, we applied MREDTA to 2034 FDA-approved drugs for treating non-small-cell lung cancer (NSCLC), all of which act on mutant EGFRT790M protein. The corresponding molecular docking results demonstrated the robustness of MREDTA.

Serum calcium improves the relationship between fluoride exposure and hypothalamic-pituitary-testicular axis hormones levels in males-a cross-sectional study on farmers in the lower reaches of the Yellow River.

Numerous studies have reported the toxicity of fluoride to the male reproductive system, but epidemiological evidence is limited. We conducted a cross-sectional study in Kaifeng City, Henan Province in 2011 to explore the association between fluoride exposure and hypothalamic-pituitary-testicular (HPT) axis hormones in men. Morning urinary fluoride (UF), serum HPT axis hormones and serum calcium (SC) concentrations were detected. Percent changes and 95% confidence intervals in HPT axis hormones associated with UF were estimated using adjusted linear regression models, and performed subgroup analysis based on SC levels. The restricted cubic spline model was used to fit nonlinear relationships. For every 10% increase in UF, the concentrations of serum GnRH, T, SHBG and TSI decreased by 2.13%, 2.39%, 2.19% and 1.96%, while E2 and FEI increased by 1.11% and 3.33%. Subgroup analysis showed that for every 10% increase in UF, the levels of GnRH, T, TSI and FTI decreased by approximately 3.15%, 5.49%, 4.47% and 5.14%, while the E2 level increased by 2.92% in low-serum-calcium group (LCG). The levels of GnRH and T decreased by approximately 2.97% and 1.82% in medium-serum-calcium group (MCG). In high-serum-calcium group (HCG), serum SHBG levels decreased by 4.70%, while FTI and FEI levels increased by 4.93% and 4.20% as UF concentration increased (P < 0.05, respectively). The non-linear relationship between serum GnRH and UF concentrations presented an approximately inverted U-shaped curve, with a turning point UF concentration of 1.164 mg/L (P < 0.001), and their nonlinear relationship in LCG and MCG were similar to that in the overall subjects. In conclusion, excessive exposure to fluoride can interfere with male serum HPT axis hormones, and a moderate increase in SC alleviates the effect of fluoride. Prospective cohort studies are essential to confirm the causality.

Development and validation of a lung cancer polygenic risk score incorporating susceptibility variants for risk factors.

Incorporating susceptibility genetic variants of risk factors has been reported to enhance the risk prediction of polygenic risk score (PRS). However, it remains unclear whether this approach is effective for lung cancer. Hence, we aimed to construct a meta polygenic risk score (metaPRS) of lung cancer and assess its prediction of lung cancer risk and implication for risk stratification. Here, a total of 2180 genetic variants were used to develop nine PRSs for lung cancer, three PRSs for different histopathologic subtypes, and 17 PRSs for lung cancer-related risk factors, respectively. These PRSs were then integrated into a metaPRS for lung cancer using the elastic-net Cox regression model in the UK Biobank (N = 442,508). Furthermore, the predictive effects of the metaPRS were assessed in the prostate, lung, colorectal, and ovarian (PLCO) cancer screening trial (N = 108,665). The metaPRS was associated with lung cancer risk with a hazard ratio of 1.33 (95% confidence interval: 1.27-1.39) per standard deviation increased. The metaPRS showed the highest C-index (0.580) compared with the previous nine PRSs (C-index: 0.513-0.564) in PLCO. Besides, smokers in the intermediate risk group predicted by the clinical risk model (1.34%-1.51%) with the intermediate-high genetic risk had a 6-year average absolute lung cancer risk that exceeded the clinical risk model threshold (≥1.51%). The addition of metaPRS to the clinical risk model showed continuous net reclassification improvement (continuous NRI = 6.50%) in PLCO. These findings suggest the metaPRS can improve the predictive efficiency of lung cancer compared with the previous PRSs and refine risk stratification for lung cancer.

Research on Pipeline Stress Detection Method Based on Double Magnetic Coupling Technology.

Oil and gas pipelines are subject to soil corrosion and medium pressure factors, resulting in stress concentration and pipe rupture and explosion. Non-destructive testing technology can identify the stress concentration and defect corrosion area of the pipeline to ensure the safety of pipeline transportation. In view of the problem that the traditional pipeline inspection cannot identify the stress signal at the defect, this paper proposes a detection method using strong and weak magnetic coupling technology. Based on the traditional J-A (Jiles-Atherton) model, the pinning coefficient is optimized and the stress demagnetization factor is added to establish the defect of the ferromagnetic material. The force-magnetic relationship optimization model is used to calculate the best detection magnetic field strength. The force-magnetic coupling simulation of Q235 steel material is carried out by ANSYS 2019 R1 software based on the improved J-A force-magnetic model. The results show that the effect of the stress on the pipe on the magnetic induction increases first and then decreases with the increase in the excitation magnetic field strength, and the magnetic signal has the maximum proportion of the stress signal during the excitation process; the magnetic induction at the pipe defect increases linearly with the increase in the stress trend. Through the strong and weak magnetic scanning detection of cracked pipeline materials, the correctness of the theoretical analysis and the validity of the engineering application of the strong and weak magnetic detection method are verified.

Predicting soil ecological criteria of 17 metal(loid)s in China based on quantitative ion character-activity relationship - Species sensitivity distribution (QICAR-SSD) coupled model.

Soil pollution caused by metal(loid)s is increasingly serious and poses unexpected risks to terrestrial organisms. Establishing soil quality standards is essential for assessing ecological risks of metal(loid)s and protecting soil ecosystems. However, the limited availability of metal(loid) ecotoxicological data has hampered the development of soil quality standards due to financial and practical constraints on toxicity testing. This study collected 77 normalization equations and 58 cross-species extrapolation equations to calculate the normalized EC10 (the added concentration causing a 10 % inhibition effect) of metal(loid)s under a representative scenario. A set of quantitative ion character-activity relationship (QICAR) models were then constructed using normalized EC10 and nine critical ionic characters (AR, AR/AW, BP, MP, Z/r2, Z/r, Xm, σp, and |Log(KOH)|). Subsequently, these QICAR models were employed to predict ecotoxicological EC10 of 17 metal(loid)s to 12 soil species and coupled with species sensitivity distribution (SSD) to determine Predicted No Effect Concentration (PNEC). The results demonstrated the coupled QICAR-SSD model could effectively derive terrestrial PNEC for data-poor metal(loid)s, with errors between the predicted PNEC and reported soil standards (excluding soil background levels) from different countries mostly <0.3 orders of magnitude. Finally, soil ecological criteria (SEC) for 17 metal(loid)s were calculated using an added risk approach based on PNEC and national soil background concentration. Overall, the coupled model proposed here can provide a valuable supplement to the development of soil quality standards for numerous metal(loid)s in soil components.

Plasmonic circular dichroism-based metal ion detection using gold nanorod-DNA complexes.

We report that complexes formed between gold nanorods (AuNRs) and metal-mediated DNA exhibit plasmonic circular dichroism (CD) signals up to ∼400 times stronger than the molecular CD signal of DNA. This substantial enhancement enables the detection of metal ions, offering a promising approach to analytical applications in chiral biochemistry.

Construction of amine-rich coating utilizing amine curing reaction of triglycidyl isocyanate with triethylenetetramine on the surface of poly(styrene-divinylbenzene) microspheres for preparation of anion exchange stationary phase.

Epoxy resins, as important thermosetting polymers, exhibit excellent adhesion to various substrates. In view of this, reticulate coating of triglycidyl isocyanate with triethylenetetramine was introduced onto the surface of poly(styrene-divinylbenzene) utilizing amine curing reaction to obtain poly(styrene-divinylbenzene)@triglycidyl isocyanate-triethylenetetramine composite microspheres. The amino groups and epoxy groups of triglycidyl isocyanate-triethylenetetramine endowed poly(styrene-divinylbenzene) with good reactivity, which could be quaternized under mild conditions to obtain an anion exchange chromatographic stationary phase. The quaternized poly(styrene-divinylbenzene)@triglycidyl isocyanate-triethylenetetramine was characterized by scanning electron microscope, Fourier-transform infrared spectroscopy, N2 adsorption-desorption experiment, et al. The chromatographic performance of the customized column was evaluated by separating seven conventional anions, organic weak acids, and carbohydrates. Poly(styrene-divinylbenzene)@triglycidyl isocyanate-triethylenetetramine possesses the uniform size of poly(styrene-divinylbenzene) microspheres and good reactivity of triglycidyl isocyanate-triethylenetetramine, which offers a flexible strategy for the preparation of anion exchange stationary phase. The column exhibits excellent chemical and mechanical stability and chromatographic performance. Finally, the column was successfully applied for the determination of nitrite in pickles.

Ribosomal modification protein rimK-like family member A activates betaine-homocysteine S-methyltransferase 1 to ameliorate hepatic steatosis.

Nonalcoholic fatty liver disease (NAFLD) is a serious threat to public health, but its underlying mechanism remains poorly understood. In screening important genes using Gene Importance Calculator (GIC) we developed previously, ribosomal modification protein rimK-like family member A (RIMKLA) was predicted as one essential gene but its functions remained largely unknown. The current study determined the roles of RIMKLA in regulating glucose and lipid metabolism. RIMKLA expression was reduced in livers of human and mouse with NAFLD. Hepatic RIMKLA overexpression ameliorated steatosis and hyperglycemia in obese mice. Hepatocyte-specific RIMKLA knockout aggravated high-fat diet (HFD)-induced dysregulated glucose/lipid metabolism in mice. Mechanistically, RIMKLA is a new protein kinase that phosphorylates betaine-homocysteine S-methyltransferase 1 (BHMT1) at threonine 45 (Thr45) site. Upon phosphorylation at Thr45 and activation, BHMT1 eliminated homocysteine (Hcy) to inhibit the activity of transcription factor activator protein 1 (AP1) and its induction on fatty acid synthase (FASn) and cluster of differentiation 36 (CD36) gene transcriptions, concurrently repressing lipid synthesis and uptake in hepatocytes. Thr45 to alanine (T45A) mutation inactivated BHMT1 to abolish RIMKLA's repression on Hcy level, AP1 activity, FASn/CD36 expressions, and lipid deposition. BHMT1 overexpression rescued the dysregulated lipid metabolism in RIMKLA-deficient hepatocytes. In summary, RIMKLA is a novel protein kinase that phosphorylates BHMT1 at Thr45 to repress lipid synthesis and uptake. Under obese condition, inhibition of RIMKLA impairs BHMT1 activity to promote hepatic lipid deposition.

Predicting Cd accumulation in crops and identifying nonlinear effects of multiple environmental factors based on machine learning models.

The traditional prediction of the Cd content in grains (Cdg) of crops primarily relies on the multiple linear regression models based on soil Cd content (Cds) and pH, neglecting inter-factorial interactions and nonlinear causal links between external environmental factors and Cdg. In this study, a comprehensive index system of multi-type environmental factors including soil properties, geology, climate, and anthropogenic activity was constructed. The machine learning models of the tree-based ensemble, support vector regression, artificial neural network for predicting Cdg of rice and wheat based on the environmental factor indexes significantly improved the accuracy than the traditional models of linear regression based on soil properties. Among them, the tree-based ensemble models of XGboost and random forest exhibited highest accuracies for predicting Cdg of rice and wheat, with R2 in the test dataset of 0.349 and 0.546, respectively. This study found that soil properties, including Cds, pH, and clay, have greater impacts on Cdg of rice and wheat, with combined contribution rates accounting for 65.2 % and 29.7 % respectively. Since wheat sampling areas are located in central and northern China, they are more constrained by precipitation and temperature than rice sampling areas in the south. Geologic and climate factors have a greater impact on Cdg of wheat, with a combined contribution rate of 49.9 %, which is higher than the corresponding rate of 20.9 % in rice. Furthermore, the Cdg of rice and wheat did not exhibit an absolute linear relationship with Cds, and excessively high Cds can reduce the bioconcentration factor of Cd accumulation in crops. Meanwhile, other environmental factors such as temperature, precipitation, elevation have marginal effects on the increase of Cdg of crops. This study provides a novel framework to optimize traditional soil plant transfer models, as well as offer a step towards realizing high precision prediction of Cd content in crops.

Care preparedness of family caregivers of maintenance hemodialysis patients: a cross-sectional study.

With the increasing number of maintenance hemodialysis (MHD) patients, growing attention has been paid to the quality of care. Strengthening care preparedness of family caregivers is essential to improving the nursing quality. The purpose of this study is to explore the care preparedness level of family caregivers of MHD patients and its influencing factors, so as to provide guidance for the development of targeted care interventions. A total of 237 family caregivers of MHD patients were recruited from the hemodialysis room of two tertiary hospitals in Wuhan using the Convenience sampling method. They were surveyed by the general data questionnaire, Care Preparedness Scale and Positive Aspects of Caregiving. Statistical analysis was conducted using IBM SPSS software, version 21.0. The statistical tests conducted in this study were two-tailed, and a significance level of P < 0.05 was deemed as statistically significant. The care preparedness and positive aspects of caregiving scores of family caregivers of MHD patients were 19.05 ± 5.64 and 31.28 ± 7.28 points, respectively. The care preparedness level of family caregivers was significantly positively correlated with positive aspects of caregiving (P < 0.01). The results of multiple linear regression analysis showed that the total nursing time and whether family caregivers had chronic diseases and positive aspects of caregiving were the main factors influencing their care preparedness (all P < 0.05). These three factors accounted for 49.6% of the variance. The care preparedness of family caregivers of MHD patients remains to be continuously improved. Medical staff should emphasize the important role of total nursing time, whether the caregiver has a chronic disease, and positive aspects of caregiving in improving care preparedness in this population. To achieve this end, medical staff can provide targeted support and guidance for caregivers according to the influencing factors, such as implementing group psychological education, strengthening the training, offering social support, remote intervention (including family caregivers' education through the media), and so on. Meanwhile, caregivers should be evaluated dynamically, and information and emotional support should be provided for them.

Application of artificial intelligence in lung cancer screening: A real-world study in a Chinese physical examination population.

BACKGROUND: With the rapid increase of chest computed tomography (CT) images, the workload faced by radiologists has increased dramatically. It is undeniable that the use of artificial intelligence (AI) image-assisted diagnosis system in clinical treatment is a major trend in medical development. Therefore, in order to explore the value and diagnostic accuracy of the current AI system in clinical application, we aim to compare the detection and differentiation of benign and malignant pulmonary nodules between AI system and physicians, so as to provide a theoretical basis for clinical application. METHODS: Our study encompassed a cohort of 23 336 patients who underwent chest low-dose spiral CT screening for lung cancer at the Health Management Center of West China Hospital. We conducted a comparative analysis between AI-assisted reading and manual interpretation, focusing on the detection and differentiation of benign and malignant pulmonary nodules. RESULTS: The AI-assisted reading exhibited a significantly higher screening positive rate and probability of diagnosing malignant pulmonary nodules compared with manual interpretation (p < 0.001). Moreover, AI scanning demonstrated a markedly superior detection rate of malignant pulmonary nodules compared with manual scanning (97.2% vs. 86.4%, p < 0.001). Additionally, the lung cancer detection rate was substantially higher in the AI reading group compared with the manual reading group (98.9% vs. 90.3%, p < 0.001). CONCLUSIONS: Our findings underscore the superior screening positive rate and lung cancer detection rate achieved through AI-assisted reading compared with manual interpretation. Thus, AI exhibits considerable potential as an adjunctive tool in lung cancer screening within clinical practice settings.

Elucidation of hemilabile-coordination-induced tunable regioselectivity in single-site Rh-catalyzed heterogeneous hydroformylation.

Revealing key factors that modulate the regioselectivity in heterogeneous hydroformylation requires identifying and monitoring the dynamic evolution of the truly active center under real reaction conditions. However, unambiguous in situ characterizations are still lacking. Herein, we elaborately construct a series of Rh-POPs catalysts for propylene hydroformylation which exhibited tunable regioselectivity. Multi-technique approaches reveal the unique microenvironment of the diverse HRh(CO)(PPh3-frame)2 sites with distinct P-Rh-P bite angles ranging from 90° to 120° and 158° to 168°, respectively. In situ time-resolved XAFS, FT-IR, and quasi-in situ Solid-state NMR experiments combined with DFT calculations explain the dynamic evolution of the electronic and coordinate state of the distinct active sites induced by hemilabile PPh3-frame ligands and further disclose the regulatory mechanism of regioselectivity. These state-of-the-art techniques and multiscale analysis advance the understanding of how hemilabile coordination influences regioselectivity and will provide a new thought to modulate the regioselectivity in future industrial processes.

Zinc(ii)-mediated stereoselective construction of 1,2-cis 2-azido-2-deoxy glycosidic linkage: assembly of Acinetobacter baumannii K48 capsular pentasaccharide derivative.

The capsular polysaccharide (CPS) is a major virulence factor of the pathogenic Acinetobacter baumannii and a promising target for vaccine development. However, the synthesis of the 1,2-cis-2-amino-2-deoxyglycoside core of CPS remains challenging to date. Here we develop a highly α-selective ZnI2-mediated 1,2-cis 2-azido-2-deoxy chemical glycosylation strategy using 2-azido-2-deoxy glucosyl donors equipped with various 4,6-O-tethered groups. Among them the tetraisopropyldisiloxane (TIPDS)-protected 2-azido-2-deoxy-d-glucosyl donor afforded predominantly α-glycoside (α : ß = >20 : 1) in maximum yield. This novel approach applies to a wide acceptor substrate scope, including various aliphatic alcohols, sugar alcohols, and natural products. We demonstrated the versatility and effectiveness of this strategy by the synthesis of A. baumannii K48 capsular pentasaccharide repeating fragments, employing the developed reaction as the key step for constructing the 1,2-cis 2-azido-2-deoxy glycosidic linkage. The reaction mechanism was explored with combined experimental variable-temperature NMR (VT-NMR) studies and mass spectroscopy (MS) analysis, and theoretical density functional theory calculations, which suggested the formation of covalent α-C1GlcN-iodide intermediate in equilibrium with separated oxocarbenium-counter ion pair, followed by an SN1-like α-nucleophilic attack most likely from separated ion pairs by the ZnI2-activated acceptor complex under the influence of the 2-azido gauche effect.

A Line-Search-Based Algorithm for Multiphase Flash Calculations with CO2-Hydrocarbon System.

Multiphase flash calculations are pivotal in compositional simulation, necessitating a robust and efficient computational algorithm. In this work, we have developed a line-search-based algorithm framework for stability analysis and multiphase flash calculations. This algorithm is rooted in the modified Newton step and line-search method. The modified Newton step, derived from modified Cholesky factorization, ensures a descent direction, while the line search determines the degree of decrease. This combination facilitates convergence even in challenging regions for phase stability analysis and multiphase flash calculations, exhibiting superlinear convergence speed. Unlike traditional approaches that rely on successive substitution iteration and may resort to Newton iteration only if the Hessian matrix is positive definite, our algorithm incorporates modification via modified Cholesky factorization upon encountering a nonpositive definite Hessian matrix. We tested our algorithm with several classical fluids, demonstrating its efficiency and robustness. Furthermore, we assessed the algorithm's performance by computing the pressure-composition diagram for the CO2-hydrocarbon system, where all calculations achieved rapid convergence without failure. This newly developed algorithm for phase stability analysis and multiphase flash calculations represents a significant advancement for compositional or chemical process simulations.

The successful experience of gymnastics world champion coach: an interview analysis.

Objectives: The role of a coach in enhancing athletes' performance and achieving success is well-documented across numerous studies. However, the strategies employed by Chinese coaches in developing world champion gymnasts remain under explored. Methods: This research involved a single case study focusing on a coach from the Chinese National Men's Gymnastics Team, credited with nurturing eight world champion gymnasts. Results: The inductive content analysis leads to that 6 subthemes, "international perspective and collaborative ability," "ability to control and regulate training loads," "identifying athletes' needs and transforming them into motivation," "goal setting aligned with athletes' abilities," "adopting authoritative democratic coaching style," and "establishing hierarchical-style friendship", and 3 themes, "training management and planning," "motivation and goal setting," and "interpersonal communication" are manifested. An overarching theme "the successful experience of gymnastics world champion coach," is derived from the analysis. Conclusion: This research bridges the gap between theoretical knowledge and practical application, offering valuable insights into the successful experiences of gymnastics world champion coaches. The findings have the potential to influence coaching methodologies globally, fostering the development of resilient, motivated, and high-performing athletes. Future research should focus on sport-specific studies, longitudinal analyses, and cross-cultural comparisons to further advance the field of sports coaching and validate the effectiveness of these innovative coaching strategies.

Anxiety and sleep quality in patients receiving maintenance hemodialysis: multiple mediating roles of hope and family function.

The objective of this cross-sectional study was to examine the extent of sleep quality among individuals undergoing maintenance hemodialysis (MHD) and to scrutinize whether hope and family function serve as mediators in the association between anxiety and sleep quality in this cohort. A convenience sampling method was used to recruit 227 patients receiving maintenance hemodialysis from two tertiary hospitals in Wuhan. Participants completed several self-report questionnaires, including the Sociodemographic questionnaire, Hospital Anxiety and Depression Scale, Athens Insomnia Scale, Herth Hope Index, and Family APGAR Index. As per the findings of the chain mediation analysis, it was observed that the sleep quality scores were directly predicted by anxiety. Moreover, anxiety positively predicted sleep quality scores through hope and family function as mediators. The observed types of mediation were partial mediation. The total indirect effect value was 0.354, indicating the mediating effect of hope and family function, while the total effect value was 0.481, representing the overall effect of anxiety on sleep quality. The total effect size was 73.60% (0.354/0.481), indicating that the mediation accounted for a significant portion of the relationship. This study established the chain mediating effect of hope and family function between anxiety and sleep quality in patients receiving maintenance hemodialysis. The findings highlight the importance of addressing anxiety and promoting hope and family function to improve sleep quality in this population. The findings suggest that healthcare professionals should be attentive to the anxiety levels of these patients and implement targeted interventions to help alleviate anxiety, enhance hope, and improve family functioning, with the ultimate goal of improving sleep quality in this population.