Gut microbes on the risk of advanced adenomas.

BACKGROUND: More than 90% of colorectal cancer (CRC) arises from advanced adenomas (AA) and gut microbes are closely associated with the initiation and progression of both AA and CRC. OBJECTIVE: To analyze the characteristic microbes in AA. METHODS: Fecal samples were collected from 92 AA and 184 negative control (NC). Illumina HiSeq X sequencing platform was used for high-throughput sequencing of microbial populations. The sequencing results were annotated and compared with NCBI RefSeq database to find the microbial characteristics of AA. R-vegan package was used to analyze α diversity and ß diversity. α diversity included box diagram, and ß diversity included Principal Component Analysis (PCA), principal co-ordinates analysis (PCoA), and non-metric multidimensional scaling (NMDS). The AA risk prediction models were constructed based on six kinds of machine learning algorithms. In addition, unsupervised clustering methods were used to classify bacteria and viruses. Finally, the characteristics of bacteria and viruses in different subtypes were analyzed. RESULTS: The abundance of Prevotella sp900557255, Alistipes putredinis, and Megamonas funiformis were higher in AA, while the abundance of Lilyvirus, Felixounavirus, and Drulisvirus were also higher in AA. The Catboost based model for predicting the risk of AA has the highest accuracy (bacteria test set: 87.27%; virus test set: 83.33%). In addition, 4 subtypes (B1V1, B1V2, B2V1, and B2V2) were distinguished based on the abundance of gut bacteria and enteroviruses (EVs). Escherichia coli D, Prevotella sp900557255, CAG-180 sp000432435, Phocaeicola plebeiuA, Teseptimavirus, Svunavirus, Felixounavirus, and Jiaodavirus are the characteristic bacteria and viruses of 4 subtypes. The results of Catboost model indicated that the accuracy of prediction improved after incorporating subtypes. The accuracy of discovery sets was 100%, 96.34%, 100%, and 98.46% in 4 subtypes, respectively. CONCLUSION: Prevotella sp900557255 and Felixounavirus have high value in early warning of AA. As promising non-invasive biomarkers, gut microbes can become potential diagnostic targets for AA, and the accuracy of predicting AA can be improved by typing.

Strategies for multi-case physics-informed neural networks for tube flows: a study using 2D flow scenarios.

Fluid dynamics computations for tube-like geometries are crucial in biomedical evaluations of vascular and airways fluid dynamics. Physics-Informed Neural Networks (PINNs) have emerged as a promising alternative to traditional computational fluid dynamics (CFD) methods. However, vanilla PINNs often demand longer training times than conventional CFD methods for each specific flow scenario, limiting their widespread use. To address this, multi-case PINN approach has been proposed, where varied geometry cases are parameterized and pre-trained on the PINN. This allows for quick generation of flow results in unseen geometries. In this study, we compare three network architectures to optimize the multi-case PINN through experiments on a series of idealized 2D stenotic tube flows. The evaluated architectures include the 'Mixed Network', treating case parameters as additional dimensions in the vanilla PINN architecture; the "Hypernetwork", incorporating case parameters into a side network that computes weights in the main PINN network; and the "Modes" network, where case parameters input into a side network contribute to the final output via an inner product, similar to DeepONet. Results confirm the viability of the multi-case parametric PINN approach, with the Modes network exhibiting superior performance in terms of accuracy, convergence efficiency, and computational speed. To further enhance the multi-case PINN, we explored two strategies. First, incorporating coordinate parameters relevant to tube geometry, such as distance to wall and centerline distance, as inputs to PINN, significantly enhanced accuracy and reduced computational burden. Second, the addition of extra loss terms, enforcing zero derivatives of existing physics constraints in the PINN (similar to gPINN), improved the performance of the Mixed Network and Hypernetwork, but not that of the Modes network. In conclusion, our work identified strategies crucial for future scaling up to 3D, wider geometry ranges, and additional flow conditions, ultimately aiming towards clinical utility.

Surface Lattice Modulation Enables Stable Cycling of High-Loading All-solid-state Batteries at High Voltages.

Halide solid electrolytes, known for their high ionic conductivity at room temperature and good oxidative stability, face notable challenges in all-solid-state Li-ion batteries (ASSBs), especially with unstable cathode/solid electrolyte (SE) interface and increasing interfacial resistance during cycling. In this work, we have developed an Al3+-doped, cation-disordered epitaxial nanolayer on the LiCoO2 surface by reacting it with an artificially constructed AlPO4 nanoshell; this lithium-deficient layer featuring a rock-salt-like phase effectively suppresses oxidative decomposition of Li3InCl6 electrolyte and stabilizes the cathode/SE interface at 4.5 V. The ASSBs with the halide electrolyte Li3InCl6 and a high-loading LiCoO2 cathode demonstrated high discharge capacity and long cycling life from 3 to 4.5 V. Our findings emphasize the importance of specialized cathode surface modification in preventing SE degradation and achieving stable cycling of halide-based ASSBs at high voltages.

Clinical efficacy of robotic spine surgery: an updated systematic review of 20 randomized controlled trials.

Purpose: To determine whether using robots in spine surgery results in more clinical advantages and fewer adverse consequences. Methods: Between October 1990 and October 2022, a computer-based search was conducted through the databases of PubMed, Cochrane Library, Embase, Web of Science, China National Knowledge Infrastructure, China Biology Medicine, VIP databases, and WAN FANG. The study only included randomized controlled trials (RCTs) comparing the clinical efficacy and safety of robot-assisted surgery with those of conventional spine surgery. The review was conducted following PRISMA 2020, and AMSTAR-2 was used to evaluate the methodological quality. R version 4.2.1 was used in the meta-analysis. The Cochrane Collaboration Tool was used for evaluating the risk of bias. Results: This study analyzed 954 participants from 20 RCTs involving cervical spondylosis, lumbar degenerative disease, scoliosis, etc. The robot-assisted group outperformed the freehand group in terms of intraoperative blood loss, number of screws in grade A position, grade A + B position, radiation dose, and hospital stay. Operation duration, visual analog scale scores of low back pain, Oswestry disability index, and radiation exposure time did not significantly differ between the two groups. Conclusions: Although robotic spine surgery is more accurate in pedicle screw placement than conventional methods, the robot group did not demonstrate an advantage in terms of clinical efficacy. Studies of complications and cost-effectiveness are still very rare.

Apelin-13 alleviates contrast-induced acute kidney injury by inhibiting endoplasmic reticulum stress.

Contrast-induced acute kidney injury (CI-AKI) is a severe complication associated with significant morbidity and mortality, and effective therapeutic strategies are still lacking. Apelin is an endogenous physiological regulator with antioxidative, anti-inflammatory and antiapoptotic properties. However, the role of apelin-13 in CI-AKI remains unclear. In our study, we found that the protein expression levels of apelin were significantly downregulated in rat kidney tissues and HK-2 cells during contrast media treatment. Moreover, we explored the protective effect of apelin-13 on renal tubule damage using in vitro and in vivo models of CI-AKI. Exogenous apelin-13 ameliorated endoplasmic reticulum stress, reactive oxygen species and apoptosis protein expression in contrast media-treated cells and rat kidney tissues. Mechanistically, the downregulation of endoplasmic reticulum stress contributed critically to the antiapoptotic effect of apelin-13. Collectively, our findings reveal the inherent mechanisms by which apelin-13 regulates CI-AKI and provide a prospective target for the prevention of CI-AKI.

Machine learning in predicting T-score in the Oxford classification system of IgA nephropathy.

Background: Immunoglobulin A nephropathy (IgAN) is one of the leading causes of end-stage kidney disease (ESKD). Many studies have shown the significance of pathological manifestations in predicting the outcome of patients with IgAN, especially T-score of Oxford classification. Evaluating prognosis may be hampered in patients without renal biopsy. Methods: A baseline dataset of 690 patients with IgAN and an independent follow-up dataset of 1,168 patients were used as training and testing sets to develop the pathology T-score prediction (T pre) model based on the stacking algorithm, respectively. The 5-year ESKD prediction models using clinical variables (base model), clinical variables and real pathological T-score (base model plus T bio), and clinical variables and T pre (base model plus T pre) were developed separately in 1,168 patients with regular follow-up to evaluate whether T pre could assist in predicting ESKD. In addition, an external validation set consisting of 355 patients was used to evaluate the performance of the 5-year ESKD prediction model using T pre. Results: The features selected by AUCRF for the T pre model included age, systolic arterial pressure, diastolic arterial pressure, proteinuria, eGFR, serum IgA, and uric acid. The AUC of the T pre was 0.82 (95% CI: 0.80-0.85) in an independent testing set. For the 5-year ESKD prediction model, the AUC of the base model was 0.86 (95% CI: 0.75-0.97). When the T bio was added to the base model, there was an increase in AUC [from 0.86 (95% CI: 0.75-0.97) to 0.92 (95% CI: 0.85-0.98); P = 0.03]. There was no difference in AUC between the base model plus T pre and the base model plus T bio [0.90 (95% CI: 0.82-0.99) vs. 0.92 (95% CI: 0.85-0.98), P = 0.52]. The AUC of the 5-year ESKD prediction model using T pre was 0.93 (95% CI: 0.87-0.99) in the external validation set. Conclusion: A pathology T-score prediction (T pre) model using routine clinical characteristics was constructed, which could predict the pathological severity and assist clinicians to predict the prognosis of IgAN patients lacking kidney pathology scores.

Machine learning algorithm as a prognostic tool for Epstein-Barr virus reactivation after haploidentical hematopoietic stem cell transplantation.

Epstein-Barr virus (EBV) reactivation is one of the most important infections after hematopoietic stem cell transplantation (HSCT) using haplo-identical related donors (HID). We aimed to establish a comprehensive model with machine learning, which could predict EBV reactivation after HID HSCT with anti-thymocyte globulin (ATG) for graft-versus-host disease (GVHD) prophylaxis. We enrolled 470 consecutive acute leukemia patients, 60% of them (n = 282) randomly selected as a training cohort, the remaining 40% (n = 188) as a validation cohort. The equation was as follows: Probability (EBV reactivation) =   1 1       +       e x p ( - Y ) , where Y = 0.0250 × (age) - 0.3614 × (gender) + 0.0668 × (underlying disease) - 0.6297 × (disease status before HSCT) - 0.0726 × (disease risk index) - 0.0118 × (hematopoietic cell transplantation-specific comorbidity index [HCT-CI] score) + 1.2037 × (human leukocyte antigen disparity) + 0.5347 × (EBV serostatus) + 0.1605 × (conditioning regimen) - 0.2270 × (donor/recipient gender matched) + 0.2304 × (donor/recipient relation) - 0.0170 × (mononuclear cell counts in graft) + 0.0395 × (CD34+ cell count in graft) - 2.4510. The threshold of probability was 0.4623, which separated patients into low- and high-risk groups. The 1-year cumulative incidence of EBV reactivation in the low- and high-risk groups was 11.0% versus 24.5% (P < .001), 10.7% versus 19.3% (P = .046), and 11.4% versus 31.6% (P = .001), respectively, in total, training and validation cohorts. The model could also predict relapse and survival after HID HSCT. We established a comprehensive model that could predict EBV reactivation in HID HSCT recipients using ATG for GVHD prophylaxis.

Detection of Breast Cancer-Specific Extracellular Vesicles with Fiber-Optic SPR Biosensor.

Extracellular vesicles (EVs) have attracted great attention as potential biomarkers for cancer diagnostics. Although several technologies have been developed for EV detection, many of them are still not applicable to clinical settings as they rely on complex EV isolation processes, while lacking sensitivity, specificity or standardization. To solve this problem, we have developed a sensitive breast cancer-specific EV detection bioassay directly in blood plasma using a fiber-optic surface plasmon resonance (FO-SPR) biosensor, previously calibrated with recombinant EVs. First, we established a sandwich bioassay to detect SK-BR-3 EVs by functionalizing the FO-SPR probes with anti-HER2 antibodies. A calibration curve was built using an anti-HER2/Banti-CD9 combination, resulting in an LOD of 2.1 × 107 particles/mL in buffer and 7 × 108 particles/mL in blood plasma. Next, we investigated the potential of the bioassay to detect MCF7 EVs in blood plasma using an anti-EpCAM/Banti-mix combination, obtaining an LOD of 1.1 × 10 8 particles/mL. Finally, the specificity of the bioassay was proven by the absence of signal when testing plasma samples from 10 healthy people unknown to be diagnosed with breast cancer. The remarkable sensitivity and specificity of the developed sandwich bioassay together with the advantages of the standardized FO-SPR biosensor highlight outstanding potential for the future of EV analysis.

Fluid Mechanical Effects of Fetal Aortic Valvuloplasty for Cases of Critical Aortic Stenosis with Evolving Hypoplastic Left Heart Syndrome.

Fetuses with critical aortic stenosis (FAS) are at high risk of progression to HLHS by the time of birth (and are thus termed "evolving HLHS"). An in-utero catheter-based intervention, fetal aortic valvuloplasty (FAV), has shown promise as an intervention strategy to circumvent the progression, but its impact on the heart's biomechanics is not well understood. We performed patient-specific computational fluid dynamic (CFD) simulations based on 4D fetal echocardiography to assess the changes in the fluid mechanical environment in the FAS left ventricle (LV) directly before and 2 days after FAV. Echocardiograms of five FAS cases with technically successful FAV were retrospectively analysed. FAS compromised LV stroke volume and ejection fraction, but FAV rescued it significantly. Calculations to match simulations to clinical measurements showed that FAV approximately doubled aortic valve orifice area, but it remained much smaller than in healthy hearts. Diseased LVs had mildly stenotic mitral valves, which generated fast and narrow diastolic mitral inflow jet and vortex rings that remained unresolved directly after FAV. FAV further caused aortic valve damage and high-velocity regurgitation. The high-velocity aortic regurgitation jet and vortex ring caused a chaotic flow field upon impinging the apex, which drastically exacerbated the already high energy losses and poor flow energy efficiency of FAS LVs. Two days after the procedure, FAV did not alter wall shear stress (WSS) spatial patterns of diseased LV but elevated WSS magnitudes, and the poor blood turnover in pre-FAV LVs did not significantly improve directly after FAV. FAV improved FAS LV's flow function, but it also led to highly chaotic flow patterns and excessively high energy losses due to the introduction of aortic regurgitation directly after the intervention. Further studies analysing the effects several weeks after FAV are needed to understand the effects of such biomechanics on morphological development.

LncRNA LINC01018/miR-942-5p/KNG1 axis regulates the malignant development of glioma in vitro and in vivo.

AIMS: Since the inhibitory effect of KNG1 on glioma has been proved, this study further explores the regulation of the lncRNA/miRNA axis on KNG1 in glioma. METHODS: The miRNAs that target KNG1 and the lncRNA that targets miR-942-5p were predicted by bioinformatics analysis and verified by experiments. The correlations between miR-942-5p and the survival of patients and between KNG1 and miR-942-5p were analyzed. After transfection, cell migration, invasion, proliferation, and cell cycle were detected through wound healing, Transwell, colony formation, and flow cytometry assays. A mouse subcutaneous xenotransplanted tumor model was established. The expressions of miR-942-5p, KNG1, LINC01018, and related genes were evaluated by quantitative real-time reverse transcription polymerase chain reaction (RT-qPCR), Western blot, or immunohistochemistry. RESULTS: MiR-942-5p targeted KNG1, and LINC01018 sponged miR-942-5p. The high survival rate of patients was related to low miR-942-5p level. MiR-942-5p was highly expressed, whereas KNG1 was lowly expressed in glioma. MiR-942-5p was negatively correlated with KNG1. Silent LINC01018 or KNG1 and miR-942-5p mimic enhanced the migration, invasion, and proliferation of glioma cells, and regulated the expressions of metastasis-related and proliferation-related genes. LINC01018 knockdown and miR-942-5p mimic promoted glioma tumor growth in mice. The levels of miR-942-5p and KNG1 were decreased by LINC01018 knockdown, and LINC01018 expression was suppressed by miR-942-5p mimic. MiR-942-5p inhibitor, KNG1, and LINC01018 had the opposite effect to miR-942-5p mimic. CONCLUSION: LINC01018/miR-942-5p/KNG1 pathway regulates the development of glioma cells in vitro and in vivo.

Development and Exploration of the Effectiveness and Feasibility of a Digital Intervention for Type 2 Diabetes Mellitus (DEsireD): Protocol for a Clinical Nonrandomized Pilot Trial in Brunei Darussalam.

BACKGROUND: The prevalence of type 2 diabetes mellitus (T2DM) is increasing worldwide. Digital interventions that incorporate the use of mobile phones and wearables have been getting popular. A combination of a digital intervention with support from professional management can enhance users' self-efficacy better than a digital intervention alone and provide better accessibility to a lifestyle intervention. However, there are limited studies exploring the feasibility and efficacy of applying a digital intervention in Muslim-majority countries, and none have been conducted in Brunei Darussalam. OBJECTIVE: The study aims to determine the effectiveness and feasibility of a proposed 16-week digital intervention program for T2DM self-management and to guide the rollout of a mobile app as part of a population health solution for adults with T2DM in Brunei. The primary outcome of this study is to measure the proportion of participants with a hemoglobin A1c (HbA1c) reduction of at least 0.6% from baseline, and the secondary outcomes include a change in HbA1c, BMI, lipid profile, and EQ-5D-5L score. METHODS: This single-arm nonrandomized pilot study will recruit participants using web-based (with the national health care app [BruHealth] and official social media platforms being used for outreach) and offline (in-person recruitment at health centers) approaches. A target of 180 individuals with T2DM aged between 20 and 70 years that meet the inclusion criteria will be enrolled in a 16-week digital intervention program. Baseline and postintervention markers will be evaluated. RESULTS: The study received approval from the Medical and Health Research & Ethics Committee of the Brunei Darussalam Ministry of Health (MHREC/MOH/2022/4(1)). The recruitment process is ongoing, and we anticipate that the study will conclude by April 2023. This will be followed by data analysis and the reporting of outcomes with the intention to publish. The results of this study will be disseminated through scientific publications and conferences. This study will serve as a guide to launch T2DM digital therapeutic programs and extend to other noncommunicable diseases (NCDs) if proven as an effective and feasible approach in Brunei. CONCLUSIONS: The Development and Exploration of the Effectiveness and Feasibility of a Digital Intervention for Type 2 Diabetes Mellitus (DEsireD) study will be the first study to investigate the clinical effectiveness and feasibility of the proposed 16-week T2DM digital intervention program tailored for Brunei, a Muslim-majority country. The findings of this study can potentially scale up the proposed model of care to other NCDs as a national approach for health management solutions. TRIAL REGISTRATION: ClinicalTrials.gov NCT05364476; https://clinicaltrials.gov/ct2/show/NCT05364476. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/43208.

Effects of mesenchymal stem cells in renovascular disease of preclinical and clinical studies: a systematic review and meta-analysis.

Renal artery stenosis (RAS) causes severe renovascular hypertension, worsening kidney function, and increased cardiovascular morbidity. According to recent studies, mesenchymal stem cells (MSCs) administration is a promising therapy for the improvement of RAS outcomes. The meta-analysis aims to evaluate the therapeutic effects of MSC therapy on RAS. We performed a search in MEDLINE, Web of Science, Embase, and Cochrane Library from inception to 5, October 2022. We included 16 preclinical and 3 clinical studies in this meta-analysis. In preclinical studies, the pooled results indicated that animals treated with MSCs had lower levels of systolic blood pressure (SBP) (SMD = - 1.019, 95% CI - 1.434 to - 0.604, I2 = 37.2%, P = 0.000), serum creatinine (Scr) (SMD = - 1.112, 95% CI - 1.932 to - 0.293, I2 = 72.0%, P = 0.008), and plasma renin activity (PRA) (SMD = - 0.477, 95% CI - 0.913 to 0.042, I2 = 43.4%, P = 0.032). The studies also revealed increased levels of renal blood flow (RBF) in stenotic kidney (STK) (SMD = 0.774, 95% CI - 0.351 to 1.197, I2 = 0%, P = 0.000) and the glomerular filtration rate (GFR) of STK (SMD = 1.825, 95% CI 0.963 to 2.688, I2 = 72.6%, P = 0.000). In clinical studies, the cortical perfusion and fractional hypoxia of the contralateral kidney (CLK) were alleviated by MSC therapy. Taken together, this meta-analysis revealed that MSCs therapy might be a promising treatment for RAS. However, due to the discrepancy between preclinical studies and early clinical trials outcomes, MSC therapy couldn't be recommended in clinical care for the moment, more high-quality randomized controlled clinical trials are needed to validate our conclusions and standardize MSCs protocols.

Technology-assisted adaptive recruitment strategy for a large nation-wide COVID-19 vaccine immunogenicity study in Brunei.

A national study was conducted in Brunei to assess and compare the immunogenicity of the various brands of COVID-19 vaccines administered to the population as part of the National COVID-19 Vaccination Programme. Most of the population have had received at least 2 doses of BBIBP-CorV, AZD1222 or MRNA-1273 vaccines. Neutralising antibodies against SARS-CoV-2 induced by these vaccines will be analysed to infer population-level immune protection against COVID-19. During the 5-week recruitment period, 24,260 eligible individuals were invited to the study via SMS, out of which 2,712 participants were enrolled into the study. This paper describes the novel adaptive strategy used to recruit the study participants. Digital technology was leveraged to perform targeted online recruitment to circumvent the limitations of traditional recruitment methods. Technology also enabled stratified random selection of these eligible individuals who were stratified based on age, gender and vaccine brand. Data was extracted from the electronic health records, the national mobile health application and a third-party survey platform and integrated into a dedicated research platform called EVYDResearch. The instant availability and access to up-to-date data on EVYDResearch enabled the study team to meet weekly and adopt an adaptive recruitment strategy informed by behavioural science, where interventions could be quickly implemented to improve response rates. Some examples of these include incorporating nudge messaging into SMS invitations, involving the Minister of Health to make press announcements on this study, media coverage, setting up an enquiries hotline and reaching out to foreign language speaking expatriates of a local multinational company to participate in this study. Data integration from various data sources, real time information sharing and a strong teamwork led to good outcomes adaptable to the progress of recruitment, compared to the more time-consuming and static traditional recruitment methods.

Meta-analysis of the clinical efficacy and safety of oblique lateral interbody fusion and transforaminal interbody fusion in the treatment of degenerative lumbar spondylolisthesis.

Objective: The aim of this study was to comprehensively evaluate the efficacy of oblique lateral interbody fusion (OLIF) and transforaminal lumbar interbody fusion (TLIF) in the treatment of degenerative lumbar spondylolisthesis by meta-analysis. Methods: A computer-based search of PubMed, Cochrane Library, Embase, Web of Science Core Collection databases, the China National Knowledge Infrastructure, China Biology Medicine, and Wanfang Digital Periodicals was conducted from the time of inception of each database to December 2021. The review process was conducted according to the PRISMA guidelines and registered in the PROSPERO database. Meta-analysis was performed using RevMan 5.4 software provided by the Cochrane Library. Results: Thirteen studies were included in the statistical analysis. One randomized controlled study and 12 cohort studies with 954 patients were included. In terms of operation time, intraoperative blood loss, Oswestry disability index score, intervertebral height, and complications, the OLIF group was better than the TLIF group, and the difference was statistically significant (P < 0.05). There was no significant difference between the two groups in terms of visual analogue scale score, lumbar lordosis or fused segment lordosis (P > 0.05). Conclusion: Both OLIF and TLIF are effective surgical modalities in the treatment of degenerative lumbar spondylolisthesis. They achieve similar therapeutic effects, but OLIF is superior to TLIF in restoring intervertebral height. At the same time, OLIF has the advantages of short operation time and less intraoperative blood loss.

Facile Construction of Nanofilms from a Dip-Coating Process to Enable High-Performance Solid-State Batteries.

The use of solid-state electrolytes (SSEs) instead of those liquid ones has found promising potential to achieve both high energy density and high safety for their applications in the next-generation energy storage devices. Unfortunately, SSEs also bring forth challenges related to solid-to-solid contact, making the stability of the electrode/electrolyte interface a formidable concern. Herein, using a garnet-type Li6.5La3Zr1.5Ta0.5O12 (LLZT) electrolyte as an example, we demonstrated a facile treatment based on the dip-coating technique, which is highly efficient in modifying the LLZT/Li interface by forming a MgO interlayer. Using polyvinyl pyrrolidone (PVP) as a coordination polymer, uniform and crack-free nanofilms are fabricated on the LLZT pellet with good control of the morphological parameters. We found that the MgO interlayer was highly effective to reduce the interfacial resistance to 6 Ω cm2 as compared to 1652 Ω cm2 of the unmodified interface. The assembled Li symmetrical cell was able to achieve a high critical current density of 1.2 mA cm-2 at room temperature, and it has a long cycling capability for over 4000 h. Using the commercialized materials of LiFePO4 and LiNi0.83Co0.07Mn0.1O2 as the cathode materials, the full cells based on the LLZT@MgO electrolyte showed excellent cyclability and high rate performance at 25 °C. Our study shows the feasibility of precise and controllable surface modification based on a simple liquid phase method and highlights the essential importance of interface control for the future application of high-performance solid-state batteries.

Butter-Derived Ruminant Trans Fatty Acids Do Not Alleviate Atherosclerotic Lesions in High-Fat Diet-Fed ApoE-/- Mice.

Atherosclerosis (AS) is the most common cardiovascular disease (CVD). Currently, it is widely believed that R-TFA and I-TFA may cause different biological effects. In the present study, we aim to elucidate the effect of mixed R-TFA derived from butter on the development of AS in high-fat diet-fed ApoE-/- mice and find the possible mechanism. It was shown that butter-derived R-TFA promoted dyslipidemia, reduced thoracic and abdominal aorta diameters, and induced aortic lipid deposition and atherosclerotic lesions in high-fat diet-fed ApoE-/- mice. Meanwhile, butter-derived R-TFA affected the serum lipid profile of high-fat diet-fed ApoE-/- mice and the lipid metabolism of human umbilical vein endothelial cells (HUVECs). Through lipidomic techniques, we found that butter-derived R-TFA had a significant effect on the glycerophospholipid metabolic pathway. In conclusion, our results demonstrated that butter-derived R-TFA does not alleviate but promotes atherosclerotic lesions in high-fat diet-fed ApoE-/- mice and that the glycerophospholipid metabolic pathway plays a major role in this pro-atherosclerotic effect.

Fluid Mechanics of Fetal Left Ventricle During Aortic Stenosis with Evolving Hypoplastic Left Heart Syndrome.

In cases of fetal aortic stenosis and evolving Hypoplastic Left Heart Syndrome (feHLHS), aortic stenosis is associated with specific abnormalities such as retrograde or bidirectional systolic transverse arch flow. Many cases progressed to hypoplastic left heart syndrome (HLHS) malformation at birth, but fetal aortic valvuloplasty can prevent the progression in many cases. Since both disease and intervention involve drastic changes to the biomechanical environment, in-vivo biomechanics likely play a role in inducing and preventing disease progression. However, the fluid mechanics of feHLHS is not well-characterized. Here, we conduct patient-specific echocardiography-based flow simulations of normal and feHLHS left ventricles (LV), to understand the essential fluid dynamics distinction between the two cohorts. We found high variability across feHLHS cases, but also the following unifying features. Firstly, feHLHS diastole mitral inflow was in the form of a narrowed and fast jet that impinged onto the apical region, rather than a wide and gentle inflow in normal LVs. This was likely due to a malformed mitral valve with impaired opening dynamics. This altered inflow caused elevated vorticity dynamics and wall shear stresses (WSS) and reduced oscillatory shear index at the apical zone rather than mid-ventricle. Secondly, feHLHS LV also featured elevated systolic and diastolic energy losses, intraventricular pressure gradients, and vortex formation numbers, suggesting energy inefficiency of flow and additional burden on the LV. Thirdly, feHLHS LV had poor blood turnover, suggesting a hypoxic environment, which could be associated with endocardial fibroelastosis that is often observed in these patients.

A comprehensive model to predict severe acute graft-versus-host disease in acute leukemia patients after haploidentical hematopoietic stem cell transplantation.

BACKGROUND: Acute graft-versus-host disease (aGVHD) remains the major cause of early mortality after haploidentical related donor (HID) hematopoietic stem cell transplantation (HSCT). We aimed to establish a comprehensive model which could predict severe aGVHD after HID HSCT. METHODS: Consecutive 470 acute leukemia patients receiving HID HSCT according to the protocol registered at https://clinicaltrials.gov (NCT03756675) were enrolled, 70% of them (n = 335) were randomly selected as training cohort and the remains 30% (n = 135) were used as validation cohort. RESULTS: The equation was as follows: Probability (grade III-IV aGVHD) = [Formula: see text], where Y = -0.0288 × (age) + 0.7965 × (gender) + 0.8371 × (CD3 + /CD14 + cells ratio in graft) + 0.5829 × (donor/recipient relation) - 0.0089 × (CD8 + cell counts in graft) - 2.9046. The threshold of probability was 0.057392 which helped separate patients into high- and low-risk groups. The 100-day cumulative incidence of grade III-IV aGVHD in the low- and high-risk groups was 4.1% (95% CI 1.9-6.3%) versus 12.8% (95% CI 7.4-18.2%) (P = 0.001), 3.2% (95% CI 1.2-5.1%) versus 10.6% (95% CI 4.7-16.5%) (P = 0.006), and 6.1% (95% CI 1.3-10.9%) versus 19.4% (95% CI 6.3-32.5%) (P = 0.017), respectively, in total, training, and validation cohort. The rates of grade III-IV skin and gut aGVHD in high-risk group were both significantly higher than those of low-risk group. This model could also predict grade II-IV and grade I-IV aGVHD. CONCLUSIONS: We established a model which could predict the development of severe aGVHD in HID HSCT recipients.

A Predicted Model for Refractory/Recurrent Cytomegalovirus Infection in Acute Leukemia Patients After Haploidentical Hematopoietic Stem Cell Transplantation.

Objective: We aimed to establish a model that can predict refractory/recurrent cytomegalovirus (CMV) infection after haploidentical donor (HID) hematopoietic stem cell transplantation (HSCT). Methods: Consecutive acute leukemia patients receiving HID HSCT were enrolled (n = 289). We randomly selected 60% of the entire population (n = 170) as the training cohort, and the remaining 40% comprised the validation cohort (n = 119). Patients were treated according to the protocol registered at https://clinicaltrials.gov (NCT03756675). Results: The model was as follows: Y = 0.0322 × (age) - 0.0696 × (gender) + 0.5492 × (underlying disease) + 0.0963 × (the cumulative dose of prednisone during pre-engraftment phase) - 0.0771 × (CD34+ cell counts in graft) - 1.2926. The threshold of probability was 0.5243, which helped to separate patients into high- and low-risk groups. In the low- and high-risk groups, the 100-day cumulative incidence of refractory/recurrent CMV was 42.0% [95% confidence interval (CI), 34.7%-49.4%] vs. 63.7% (95% CI, 54.8%-72.6%) (P < 0.001) for total patients and was 50.5% (95% confidence interval (CI), 40.9%-60.1%) vs. 71.0% (95% CI, 59.5%-82.4%) (P = 0.024) for those with acute graft-versus-host disease. It could also predict posttransplant mortality and survival. Conclusion: We established a comprehensive model that could predict the refractory/recurrent CMV infection after HID HSCT. Clinical Trial Registration: https://clinicaltrials.gov, identifier NCT03756675.