The optimization method of wing plasma ice shape regulation based on quantitative assessment of flight risk.

Plasma ice shape regulation is a technology which uses plasma actuator to regulate the continuous ice into safer intermittent ice by its significant thermal effect with limited energy. Whether plasma ice shape regulation could reduce flight risk is a new problem under the wing with continuous ice. The 3D printed ice shapes were arranged on the leading edge of the wing based on NACA0012 airfoil, aiming to simulate the configuration after ice shape regulation. And the aerodynamic parameters were obtained by wind tunnel experiments. The experimental results showed that the ratio of signal regulation ice width d to chord length of the wing b A determined the aerodynamic characteristics, and the aerodynamic characteristics changed better compared with configuration of the continuous ice. However, the flight risk of the wing under given regulation ratio is unknown. Based on the straight and swept wing after regulating, the flight safety boundaries were simulated by the reachable set method. Further, a method of quantitative assessment of flight risk is proposed. Quantitative values of risk were calculated. The results show that the flight risk all decreases from level 2 to level 4 compared with configuration of the continuous ice when d / b A equals 0.15 under conditions of swept and straight wing.

T2-weighted imaging-based radiomic-clinical machine learning model for predicting the differentiation of colorectal adenocarcinoma.

BACKGROUND: The study on predicting the differentiation grade of colorectal cancer (CRC) based on magnetic resonance imaging (MRI) has not been reported yet. Developing a non-invasive model to predict the differentiation grade of CRC is of great value. AIM: To develop and validate machine learning-based models for predicting the differentiation grade of CRC based on T2-weighted images (T2WI). METHODS: We retrospectively collected the preoperative imaging and clinical data of 315 patients with CRC who underwent surgery from March 2018 to July 2023. Patients were randomly assigned to a training cohort (n = 220) or a validation cohort (n = 95) at a 7:3 ratio. Lesions were delineated layer by layer on high-resolution T2WI. Least absolute shrinkage and selection operator regression was applied to screen for radiomic features. Radiomics and clinical models were constructed using the multilayer perceptron (MLP) algorithm. These radiomic features and clinically relevant variables (selected based on a significance level of P < 0.05 in the training set) were used to construct radiomics-clinical models. The performance of the three models (clinical, radiomic, and radiomic-clinical model) were evaluated using the area under the curve (AUC), calibration curve and decision curve analysis (DCA). RESULTS: After feature selection, eight radiomic features were retained from the initial 1781 features to construct the radiomic model. Eight different classifiers, including logistic regression, support vector machine, k-nearest neighbours, random forest, extreme trees, extreme gradient boosting, light gradient boosting machine, and MLP, were used to construct the model, with MLP demonstrating the best diagnostic performance. The AUC of the radiomic-clinical model was 0.862 (95%CI: 0.796-0.927) in the training cohort and 0.761 (95%CI: 0.635-0.887) in the validation cohort. The AUC for the radiomic model was 0.796 (95%CI: 0.723-0.869) in the training cohort and 0.735 (95%CI: 0.604-0.866) in the validation cohort. The clinical model achieved an AUC of 0.751 (95%CI: 0.661-0.842) in the training cohort and 0.676 (95%CI: 0.525-0.827) in the validation cohort. All three models demonstrated good accuracy. In the training cohort, the AUC of the radiomic-clinical model was significantly greater than that of the clinical model (P = 0.005) and the radiomic model (P = 0.016). DCA confirmed the clinical practicality of incorporating radiomic features into the diagnostic process. CONCLUSION: In this study, we successfully developed and validated a T2WI-based machine learning model as an auxiliary tool for the preoperative differentiation between well/moderately and poorly differentiated CRC. This novel approach may assist clinicians in personalizing treatment strategies for patients and improving treatment efficacy.

The Effect of Antihyperglycemic Medications on COVID-19: A Meta-analysis and Systematic Review from Observational Studies.

BACKGROUND: Diabetes, a chronic disease worldwide, may be associated with a poorer prognosis in patients with coronavirus disease 2019 (COVID-19). While some antihyperglycemic medications may be beneficial, others may increase the risk of adverse clinical outcomes of COVID-19. We aimed to analyze the effect of antihyperglycemic medications on COVID-19. METHODS: We searched the Web of Science, Cochrane Library, EMBASE, PubMed, and Scopus databases from December 2019 to June 2022 to identify literature related to patients with COVID-19 and type 2 diabetes mellitus (T2DM) treated with antihyperglycemic medications. RESULTS: 56 studies were included in the analysis. Metformin (OR 0.66; 95% CI 0.58-0.74; p < 0.05), Glucagon-like peptide-1 receptor agonist (GLP-1ra) (OR 0.73; 95% CI 0.59-0.91; p < 0.05), and sodium-dependent glucose transporters 2 inhibitor (SGLT 2i) (OR 0.77; 95% CI 0.69-0.87; p < 0.05) were associated with lower mortality risk, while insulin was associated with increased mortality risk (OR 1.40; 95% CI 1.26-1.55; p < 0.05). Meanwhile, metformin (OR 0.65; 95% CI 0.50-0.85; p < 0.05) and GLP-1ra (OR 0.84; 95% CI 0.76-0.94; p < 0.05) were significantly associated with decreased severe manifestation risk. What's more, metformin (OR 0.77; 95% CI 0.62-0.96; p < 0.05), GLP-1ra (OR 0.86; 95% CI 0.81-0.92; p < 0.05), and SGLT 2i (OR 0.87; 95% CI 0.79-0.97; p < 0.05) were also associated with a decreased risk of hospitalization, but insulin were associated with an increased risk of hospitalization (OR 1.31; 95% CI 1.12-1.52; p < 0.05). Nevertheless, the results of the subgroup analyses showed that the effects of different glucose-lowering agents on COVID-19 may be related to in-hospital use or out-hospital use, elderly or non-elderly patients use, and different geography. CONCLUSION: Metformin, GLP-1ra, and SGLT 2i have shown a positive effect on clinical outcomes in COVID-19, particularly in non-elderly individuals. However, insulin use may pose a higher risk, especially in elderly patients, so need with caution. Meanwhile, DPP-4i, TZD, α-GLUi, and sulfonylureas appeared to have a neutral effect. These results need to be validated in future clinical studies.

Changes in disease burden and global inequalities in bladder, kidney and prostate cancers from 1990 to 2019: a comparative analysis based on the global burden of disease study 2019.

BACKGROUND: Bladder, kidney and prostate cancers make significant contributors to cancer burdens. Exploring their cross-country inequalities may inform equitable strategies to meet the 17 sustainable development goals before 2030. METHODS: We analyzed age-standardized disability-adjusted life-years (ASDALY) rates for the three cancers based on Global Burden of Diseases Study 2019. We quantified the inequalities using slope index of inequality (SII, absolute measure) and concentration index (relative measure) associated with national sociodemographic index. RESULTS: Varied ASDALY rates were observed in the three cancers across 204 regions. The SII decreased from 35.15 (95% confidence interval, CI: 29.34 to 39.17) in 1990 to 15.81 (95% CI: 7.99 to 21.79) in 2019 for bladder cancers, from 78.94 (95% CI: 75.97 to 81.31) in 1990 to 59.79 (95% CI: 55.32 to 63.83) in 2019 for kidney cancer, and from 192.27 (95% CI: 137.00 to 241.05) in 1990 to - 103.99 (95% CI: - 183.82 to 51.75) in 2019 for prostate cancer. Moreover, the concentration index changed from 12.44 (95% CI, 11.86 to 12.74) in 1990 to 15.72 (95% CI, 15.14 to 16.01) in 2019 for bladder cancer, from 33.88 (95% CI: 33.35 to 34.17) in 1990 to 31.13 (95% CI: 30.36 to 31.43) in 2019 for kidney cancer, and from 14.61 (95% CI: 13.89 to 14.84) in 1990 to 5.89 (95% CI: 5.16 to 6.26) in 2019 for prostate cancer. Notably, the males presented higher inequality than females in both bladder and kidney cancer from 1990 to 2019. CONCLUSIONS: Different patterns of inequality were observed in the three cancers, necessitating tailored national cancer control strategies to mitigate disparities. Priority interventions for bladder and kidney cancer should target higher socioeconomic regions, whereas interventions for prostate cancer should prioritize the lowest socioeconomic regions. Additionally, addressing higher inequality in males requires more intensive interventions among males from higher socioeconomic regions.

Dual treatment with kynurenine pathway inhibitors and NAD+ precursors synergistically extends life span in Drosophila.

Tryptophan catabolism is highly conserved and generates important bioactive metabolites, including kynurenines, and in some animals, NAD+. Aging and inflammation are associated with increased levels of kynurenine pathway (KP) metabolites and depleted NAD+, factors which are implicated as contributors to frailty and morbidity. Contrastingly, KP suppression and NAD+ supplementation are associated with increased life span in some animals. Here, we used DGRP_229 Drosophila to elucidate the effects of KP elevation, KP suppression, and NAD+ supplementation on physical performance and survivorship. Flies were chronically fed kynurenines, KP inhibitors, NAD+ precursors, or a combination of KP inhibitors with NAD+ precursors. Flies with elevated kynurenines had reduced climbing speed, endurance, and life span. Treatment with a combination of KP inhibitors and NAD+ precursors preserved physical function and synergistically increased maximum life span. We conclude that KP flux can regulate health span and life span in Drosophila and that targeting KP and NAD+ metabolism can synergistically increase life span.

Efficacy and safety of drug-coated balloon for de novo lesions of large coronary arteries: Systematic review and meta-analysis of randomized controlled trials.

Background: Drug-coated balloon (DCB) is a novel approach to avoiding stent-related complications and has proven effective for the treatment of in-stent restenosis (ISR) and small vessels. However, its role in the treatment of de novo lesions in large vessels is less settled. Aims: To estimate the efficacy and safety of drug-coated balloon versus stent in the treatment of de novo lesions in large coronary arteries. Methods: We searched the literature until April 2023. We judged the safety of DCB based on major adverse cardiovascular events (MACEs), cardiac death, all-cause mortality, non-fatal myocardial infarction, target lesion revascularization (TLR), and bleeding event; and efficacy according to late lumen loss (LLL), minimum lumen diameter (MLD). We conducted subgroup analyses according to stent type and whether urgent PCI was required. Results: A total of 10 RCTs were included. Overall, LLL (mean difference (MD) = -0.19, 95 % confidence interval (CI): -0.32 to -0.06, P = 0.003) was lower in the DCB group than in the Stent arm. This effect was consistent in subgroup analysis regardless of stent type and disease type. In terms of safety indicators, there were no significant differences between DCB and stent. The subgroup analyses found that safety indicators showed no significant differences between DCB and drug-eluting stent (DES), but TLR was lower in the DCB than in the bare metal stent (BMS). Moreover, in ST-elevation myocardial infarction (STEMI), safety indicators and LLL showed no significant differences between DCB and DES, but MLD in the DCB was smaller. While in patients with excluded STEMI, MACE and TLR was lower in the DCB compared with the overall stent. Conclusions: DCB could be a promising alternative for treating de novo lesions in large coronary arteries with satisfactory efficacy and low risk, superior to BMS and not inferior to DES, with a trend toward lower late lumen loss.

Synergistic binding mechanisms of co-contaminants in soil profiles: Influence of iron-bearing minerals and microbial communities.

In contaminated soil sites, the coexistence of inorganic and organic contaminants poses a significant threat to both the surrounding ecosystem and public health. However, the migration characteristics of these co-contaminants within the soil and their interactions with key components, including Fe-bearing minerals, organic matter, and microorganisms, remain unclear. This study involved the collection of a 4.3-m-depth co-contaminated soil profile to investigate the vertical distribution patterns of co-contaminants (namely, arsenic, cadmium, and polychlorinated biphenyls (PCBs)) and their binding mechanisms with environmental factors. The results indicated a notable downward accumulation of inorganic contaminants with increasing soil depth, whereas PCBs were predominantly concentrated in the uppermost layer. Chemical extraction and synchrotron radiation analysis highlighted a positive correlation between the abundance of reactive iron (FeCBD) and both co-contaminants and microbial communities in the contaminated site. Furthermore, Mantel tests and structural equation modeling (SEM) demonstrated the direct impacts of FeCBD and microbial communities on co-contaminants within the soil profile. Overall, these results provided valuable insights into the migration and transformation characteristics of co-contaminants and their binding mechanisms mediated by minerals, organic matter, and microorganisms.

Lithium-Ion Charged Polymer Channels Flattening Lithium Metal Anode.

The concentration difference in the near-surface region of lithium metal is the main cause of lithium dendrite growth. Resolving this issue will be key to achieving high-performance lithium metal batteries (LMBs). Herein, we construct a lithium nitrate (LiNO3)-implanted electroactive ß phase polyvinylidene fluoride-co-hexafluoropropylene (PVDF-HFP) crystalline polymorph layer (PHL). The electronegatively charged polymer chains attain lithium ions on the surface to form lithium-ion charged channels. These channels act as reservoirs to sustainably release Li ions to recompense the ionic flux of electrolytes, decreasing the growth of lithium dendrites. The stretched molecular channels can also accelerate the transport of Li ions. The combined effects enable a high Coulombic efficiency of 97.0% for 250 cycles in lithium (Li)||copper (Cu) cell and a stable symmetric plating/stripping behavior over 2000 h at 3 mA cm-2 with ultrahigh Li utilization of 50%. Furthermore, the full cell coupled with PHL-Cu@Li anode and LiFePO4 cathode exhibits long-term cycle stability with high-capacity retention of 95.9% after 900 cycles. Impressively, the full cell paired with LiNi0.87Co0.1Mn0.03O2 maintains a discharge capacity of 170.0 mAh g-1 with a capacity retention of 84.3% after 100 cycles even under harsh condition of ultralow N/P ratio of 0.83. This facile strategy will widen the potential application of LiNO3 in ester-based electrolyte for practical high-voltage LMBs.

Network pharmacology combined with experimental verification to explore the potential mechanism of naringenin in the treatment of cervical cancer.

Cervical cancer is the second leading cause of morbidity and mortality in women worldwide. Traditional treatment methods have become limited. Naringenin, a flavonoid abundant in various fruits and herbal medicines, has demonstrated anti-tumor properties among other effects. This research undertook to elucidate the mechanism of naringenin in the context of cervical cancer treatment by leveraging network pharmacology and performing experimental validation. Initial steps involved predicting potential naringenin targets and subsequently screening for overlaps between these targets and those related to cervical cancer, followed by analysis of their interrelationships. Molecular docking was subsequently utilized to verify the binding effect of the central target. Within the framework of network pharmacology, it was discovered that naringenin might possess anti-cancer properties specific to cervical cancer. Following this, the anti-tumor effects of naringenin on Hela cell viability, migration, and invasion were assessed employing CCK-8, transwell, wound healing assays, and western blotting. Experimental data indicated that naringenin attenuates the migration and invasion of Hela cells via downregulation EGFR/PI3K/AKT signaling pathway. Thus, our findings suggest that naringenin has therapeutic impacts on cervical cancer via multiple mechanisms, primarily by inhibiting the migration and invasion through the EGFR/PI3K/AKT/mTOR pathway. This study offers fresh insights for future clinical studies.

Sustained Release-Driven Interface Engineering Enables Fast Charging Lithium Metal Batteries.

LiNO3 has attracted intensive attention as a promising electrolyte additive to regulate Li deposition behavior as it can form favorable Li3 N, LiNx Oy species to improve the interfacial stability. However, the inferior solubility in carbonate-based electrolyte restricts its application in high-voltage Li metal batteries. Herein, an artificial composite layer (referred to as PML) composed of LiNO3 and PMMA is rationally designed on Li surface. The PML layer serves as a reservoir for LiNO3 release gradually to the electrolyte during cycling, guaranteeing the stability of SEI layer for uniform Li deposition. The PMMA matrix not only links the nitrogen-containing species for uniform ionic conductivity but also can be coordinated with Li for rapid Li ions migration, resulting in homogenous Li-ion flux and dendrite-free morphology. As a result, stable and dendrite-free plating/stripping behaviors of Li metal anodes are achieved even at an ultrahigh current density of 20 mA cm-2 (>570 h) and large areal capacity of 10 mAh cm-2 (>1200 h). Moreover, the Li||LiFePO4 full cell using PML-Li anode undergoes stable cycling for 2000 cycles with high-capacity retention of 94.8%. This facile strategy will widen the potential application of LiNO3 in carbonate-based electrolyte for practical LMBs.

MicroRNA397 promotes rice flowering by regulating the photorespiration pathway.

The precise timing of flowering plays a pivotal role in ensuring successful plant reproduction and seed production. This process is intricately governed by complex genetic networks that integrate internal and external signals. This study delved into the regulatory function of microRNA397 (miR397) and its target gene LACCASE-15 (OsLAC15) in modulating flowering traits in rice (Oryza sativa). Overexpression of miR397 led to earlier heading dates, decreased number of leaves on the main stem, and accelerated differentiation of the spikelet meristem. Conversely, overexpression of OsLAC15 resulted in delayed flowering and prolonged vegetative growth. Through biochemical and physiological assays, we uncovered that miR397-OsLAC15 had a profound impact on carbohydrate accumulation and photosynthetic assimilation, consequently enhancing the photosynthetic intensity in miR397-overexpressing rice plants. Notably, we identified that OsLAC15 is at least partially localized within the peroxisome organelle, where it regulates the photorespiration pathway. Moreover, we observed that a high CO2 concentration could rescue the late flowering phenotype in OsLAC15-overexpressing plants. These findings shed valuable insights into the regulatory mechanisms of miR397-OsLAC15 in rice flowering and provided potential strategies for developing crop varieties with early flowering and high-yield traits through genetic breeding.

Development and validation of a clinical model to predict preconception risk of gestational diabetes mellitus in nulliparous women: A retrospective cohort study.

OBJECTIVE: To develop and validate a model to predict the preconception risk of gestational diabetes mellitus (GDM) in nulliparous women. METHODS: This was a retrospective cohort study. A total of 1565 women in early pregnancy who underwent preconception health examinations in the Women and Children's Hospital of Chongqing Medical University between January 2020 and June 2021 were invited to participate in a questionnaire survey. Logistic regression analysis was performed to determine the preconception risk factors for GDM. These factors were used to construct a model to predict GDM risk in nulliparous women. Then, the model was used to assess the preconception risk of GDM in 1060 nulliparous women. RESULTS: Independent preconception risk factors for GDM included the following: age 35 years or greater, diastolic blood pressure 80 mm Hg or greater, fasting plasma glucose 5.1 mmol/L or greater, body mass index (BMI, calculated as weight in kilograms divided by the square of height in meters) 24 or greater, weight gain 10 kg or greater in the year before pregnancy, age of menarche 15 years or greater, three or more previous pregnancies, daily staple food intake 300 g or greater, fondness for sweets, and family history of diabetes. BMI less than 18.5, daily physical activity duration 1 h or greater, and high-intensity physical activity were protective factors. These factors were used to construct a model to predict GDM risk in nulliparous women, and the incidence of GDM significantly increased as the risk score increased. The area under the curve of the prediction model was 0.82 (95% confidence interval 0.80-0.85). CONCLUSION: The preconception GDM risk prediction model demonstrated good predictive efficacy and can be used to identify populations at high risk of GDM before pregnancy, which provides the possibility for preconception intervention.

Boosting the Cycle Performance of Iron Trifluoride Based Solid State Batteries at Elevated Temperatures by Engineering the Cathode Solid Electrolyte Interface.

Iron trifluoride (FeF3) is attracting tremendous interest due to its lower cost and the possibility to enable higher energy density in lithium-ion batteries. However, its cycle performance deteriorates rapidly in less than 50 cycles at elevated temperatures due to cracking of the unstable cathode solid electrolyte interface (CEI) followed by active materials dissolution in liquid electrolyte. Herein, by engineering the salt composition, the Fe3O4-type CEI with the doping of boron (B) atoms in a polymer electrolyte at 60 °C is successfully stabilized. The cycle life of the well-designed FeF3-based composite cathode exceeds an unprecedented 1000 cycles and utilizes up to 70% of its theoretical capacities. Advanced electron microscopy combined with density functional theory (DFT) calculations reveal that the B in lithium salt migrates into the cathode and promotes the formation of an elastic and mechanic robust boron-contained CEI (BOR-CEI) during cycling, by which the durability of the CEI to frequent cyclic large volume changes is significantly enhanced. To this end, the notorious active materials dissolution is largely prohibited, resulting in a superior cycle life. The results suggest that engineering the CEI such as tuning its composition is a viable approach to achieving FeF3 cathode-based batteries with enhanced performance.

Discovery of α-Ketoamide inhibitors of SARS-CoV-2 main protease derived from quaternized P1 groups.

Although the SARS-CoV-2 pandemic has ended, multiple sporadic cases still exist, posing a request for more antivirals. The main protease (Mpro) of SARS-CoV-2, a key enzyme for viral replication, is an attractive target for drug development. Here, we report the discovery of a new potent α-ketoamide-containing Mpro inhibitor, N-((R)-1-cyclohexyl-2-(((R)-3-methoxy-1-oxo-1-((1-(2-oxo-2-((thiazol-2-ylmethyl)amino)acetyl)cyclobutyl)amino)propan-2-yl)amino)-2-oxoethyl)-4,4-difluorocyclohexane-1-carboxamide (20j). This compound presented promising enzymatic inhibitory activity against SARS-CoV-2 Mpro with an IC50 value of 19.0 nM, and an excellent antiviral activity in cell-based assay with an EC50 value of 138.1 nM. This novel covalent inhibitor may be used as a lead compound for subsequent drug discovery against SARS-CoV-2.

Latest advances in the study of non-coding RNA-mediated circadian rhythm disorders causing endometrial cancer.

Endometrial cancer (EC) is one of the most common gynecological cancers, and its risk factors include obesity and metabolic, genetic, and other factors. Recently, the circadian rhythm has also been shown to be associated with EC, as the severity of EC was found to be related to night work and rhythm disorders. Therefore, circadian rhythm disorders (CRDs) may be one of the metabolic diseases underlying EC. Changes in the circadian rhythm are regulated by clock genes (CGs), which in turn are regulated by non-coding RNAs (ncRNAs). More importantly, the mechanism of EC caused by ncRNA-mediated CRDs is gradually being unraveled. Here, we review existing studies and reports and explore the relationship between EC, CRDs, and ncRNAs.

Hetrombopag plus recombinant human thrombopoietin for chemotherapy-induced thrombocytopenia in patients with solid tumors.

Background: Chemotherapy-induced thrombocytopenia (CIT) is a common hematological complication in patients with cancer. Hetrombopag is a novel thrombopoietin receptor agonist that has shown an additive effect in stimulating platelet production when combined with recombinant human thrombopoietin (rhTPO). Objectives: This multicenter retrospective cohort study aimed to evaluate the efficacy and safety of hetrombopag plus rhTPO compared with rhTPO alone for CIT. Methods: A total of 294 patients with solid tumors and CIT (platelet count, <50 × 109/L) who received either rhTPO plus hetrombopag (146 patients) or rhTPO alone (148 patients) at 3 centers from January to December 2022 were included in the study. The primary outcome was a platelet count at least 50 × 109/L higher than the baseline value within 14 days. Chemotherapy dose reductions/delays, bleeding, and adverse events were reported. Results: One hundred twenty patients (82.2%) in the rhTPO-hetrombopag group vs 100 patients (67.6%) in the rhTPO group achieved the primary outcome (P = .005). This significant difference persisted in adjusted analysis (odds ratio, 2.01; 95% CI, 1.12-3.60). A total of 115 patients (78.8%) in the rhTPO-hetrombopag group and 101 patients (68.2%) in the rhTPO group avoided chemotherapy dose reductions/delays (P = .041). There was no significant difference in bleeding rates, and adverse events were mild and similar between the 2 groups. No deaths occurred. Conclusion: Compared to rhTPO alone, our findings suggest that the combination of hetrombopag and rhTPO is safe and more effective in patients with CIT.

Causal relationships between plasma lipids and sepsis: A Mendelian randomization study.

Although observational studies have indicated that plasma lipids are associated with an increased risk of sepsis, due to confounders and reverse causality, the causal relationship remains unclear. This study was designed to assess the causal effects of plasma lipid levels on sepsis. We used a 2-sample Mendelian randomization (MR) method to evaluate the causal effect of plasma lipids on sepsis. MR analysis employs methods such as inverse variance weighted, MR-Egger regression, weighted median regression (WME), simple mode and weighted mode. The inverse variance weighted (IVW) method was predominantly utilized to assess causality. Heterogeneity was affirmed by Cochran Q test, while pleiotropy was corroborated by MR-Egger regression analysis. The robustness and reliability of the results were demonstrated through "leave-one-out" sensitivity analysis. Instrumental variables included 226 single-nucleotide polymorphisms (SNPs), comprising of 7 for triglyceride (TG), 169 for high-density lipoprotein cholesterol (HDL-C), and 50 for low-density lipoprotein cholesterol (LDL-C). The risk of sepsis appeared to increase with rising LDL-C levels, as indicated by the inverse variance weighted analysis (OR 1.11, 95% CI from0.99 to1.24, P = 0.068). However, no causality existed between LDL-C, HDL-C, TG and sepsis. Two-sample MR analysis indicated that increased LDL-C level is a risk factor for sepsis, while TG and HDL-C levels have protective effects against sepsis. However, no significant causal relationship was found between TG, HDL-C, and LDL-C levels and sepsis.

The Application of Computer Technology to Clinical Practice Guideline Implementation: A Scoping Review.

Implementation of clinical practice guidelines (CPG) is a complex and challenging task. Computer technology, including artificial intelligence (AI), has been explored to promote the CPG implementation. This study has reviewed the main domains where computer technology and AI has been applied to CPG implementation. PubMed, Embase, Web of science, the Cochrane Library, China National Knowledge Infrastructure database, WanFang DATA, VIP database, and China Biology Medicine disc database were searched from inception to December 2021. Studies involving the utilization of computer technology and AI to promote the implementation of CPGs were eligible for review. A total of 10429 published articles were identified, 117 met the inclusion criteria. 21 (17.9%) focused on the utilization of AI techniques to classify or extract the relative content of CPGs, such as recommendation sentence, condition-action sentences. 47 (40.2%) focused on the utilization of computer technology to represent guideline knowledge to make it understandable by computer. 15 (12.8%) focused on the utilization of AI techniques to verify the relative content of CPGs, such as conciliation of multiple single-disease guidelines for comorbid patients. 34 (29.1%) focused on the utilization of AI techniques to integrate guideline knowledge into different resources, such as clinical decision support systems. We conclude that the application of computer technology and AI to CPG implementation mainly concentrated on the guideline content classification and extraction, guideline knowledge representation, guideline knowledge verification, and guideline knowledge integration. The AI methods used for guideline content classification and extraction were pattern-based algorithm and machine learning. In guideline knowledge representation, guideline knowledge verification, and guideline knowledge integration, computer techniques of knowledge representation were the most used.

Effects of treatment with stem cell-derived extracellular vesicles in preclinical rodent models of intrauterine adhesion: A meta-analysis.

Background: Intrauterine adhesion (IUA) results from serious complications of intrauterine surgery or infection and mostly remains incurable. Small extracellular vesicles (sEVs) derived from mesenchymal stem cells (MSCs) have emerged as a potential new approach for the treatment of IUA; however, their impact is not fully understood. Here, we performed a meta-analysis summarizing the effects of sEVs on IUA in preclinical rodent models. Methods: This meta-analysis included searches of PubMed, EMBASE, Cochrane, and the Web of Science databases from January 1, 1997, to April 1, 2022, to identify studies reporting the therapeutic effect of sEVs on rodent preclinical animal models of IUA. We compared improvements in endometrial thickness, endometrial gland number, fibrosis area, embryo number, vascular endothelial growth factor (VEGF), transforming growth factor ß1 (TGFß1), and leukemia inhibitory factor (LIF) levels after treatment. Results: Our search included 100 citations, of which 7 met the inclusion criteria, representing 231 animals. Compared with that in the control group, the fibrosis area in the sEV-treated group was significantly reduced (standardized mean difference (SMD) = -6.87，95 % confidence interval (CI) = -9.67 to -4.07). The number of glands increased after the intervention (95 % CI, 3.72-7.68; P = 0.000). Endometrial thickness was significantly improved in the sEV-treated group (SMD = 2.57, 95 % CI, 1.62-3.52). Conclusions: This meta-analysis is highlighting that sEV treatment can improve the area of endometrial fibrosis, as well as VEGF, and LIF level, in a mouse IUA model. This knowledge of these findings will provide new insights into future preclinical research.