Safety and efficacy of PCSK9 inhibitor (evolocumab) in patients with non-ST segment elevation acute coronary syndrome and non-culprit artery critical lesions: a randomised controlled trial protocol (SPECIAL study).

INTRODUCTION: Patients with non-ST segment elevation acute coronary syndrome (NSTE-ACS) and concomitant multivessel coronary artery disease (CAD) are considered patients with extremely high-risk atherosclerotic cardiovascular disease (ASCVD), and current guidelines specify a lower low-density lipoprotein cholesterol (LDL-C) target for this population. Proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors have been shown to effectively reduce LDL-C levels on a statin background. Additionally, several studies have confirmed the role of PCSK9 inhibitors in plaque regression and reducing residual cardiovascular risk in patients with ACS. However, those studies included coronary lesions with a degree of stenosis <50%. Whether the application of PCSK9 inhibitors in patients with NSTE-ACS with non-culprit artery critical lesions (stenosis degree between 50% and 75%) has a similar effect on plaque regression and improvement of cardiovascular outcomes remains unknown, with a lack of relevant research. This study aims to further investigate the safety and efficacy of evolocumab in patients with NSTE-ACS and concomitant multivessel CAD (non-culprit artery stenosis between 50% and 75%). METHODS AND ANALYSIS: In this single-centre clinical randomised controlled trial, 122 patients with NSTE-ACS and concomitant multivessel CAD (non-culprit artery stenosis between 50% and 75%) will be randomly assigned to either the evolocumab treatment group or the standard treatment group after completing culprit vessel revascularisation. The evolocumab treatment group will receive evolocumab in addition to statin therapy, while the standard treatment group will receive standard statin therapy. At baseline and week 50, patients in the evolocumab treatment group will undergo coronary angiography and OCT imaging to visualise pre-existing non-lesional vessels. The primary end point is the absolute change in average minimum fibrous cap thickness (FCT) from baseline to week 50. Secondary end points include changes in plaque lipid arc, lipid length, macrophage grading, lipid levels and major adverse cardiovascular events during the 1-year follow-up period. ETHICS AND DISSEMINATION: Ethics: this study will adhere to the principles outlined in the Helsinki Declaration and other applicable ethical guidelines. This study protocol has received approval from the Medical Research Ethics Committee of the First Affiliated Hospital of the University of Science and Technology of China (Anhui Provincial Hospital), with approval number 2022-ky214. DISSEMINATION: we plan to disseminate the findings of this study through various channels. This includes publication in peer-reviewed academic journals, presentation at relevant academic conferences and communication to the public, policymakers and healthcare professionals. We will also share updates on the research progress through social media and other online platforms to facilitate the exchange and application of scientific knowledge. Efforts will be made to ensure widespread dissemination of the research results and to have a positive impact on society. TRIAL REGISTRATION NUMBER: ChiCTR2200066675.

Convergent and divergent transcriptional reprogramming of motor and sensory neurons underlying response to peripheral nerve injury.

INTRODUCTION: Motor neurons differ from sensory neurons in aspects including origins and surrounding environment. Understanding the similarities and differences in molecular response to peripheral nerve injury (PNI) and regeneration between sensory and motor neurons is crucial for developing effective drug targets for CNS regeneration. However, genome-wide comparisons of molecular changes between sensory and motor neurons following PNI remains limited. OBJECTIVES: This study aims to investigate genome-wide convergence and divergence of injury response between sensory and motor neurons to identify novel drug targets for neural repair. METHODS: We analyzed two large-scale RNA-seq datasets of in situ captured sensory neurons (SNs) and motoneurons (MNs) upon PNI, retinal ganglion cells and spinal cord upon CNS injury. Additionally, we integrated these with other related single-cell level datasets. Bootstrap DESeq2 and WGCNA were used to detect and explore co-expression modules of differentially expressed genes (DEGs). RESULTS: We found that SNs and MNs exhibited similar injury states, but with a delayed response in MNs. We identified a conserved regeneration-associated module (cRAM) with 274 shared DEGs. Of which, 47% of DEGs could be changed in injured neurons supported by single-cell resolution datasets. We also identified some less-studied candidates in cRAM, including genes associated with transcription, ubiquitination (Rnf122), and neuron-immune cells cross-talk. Further in vitro experiments confirmed a novel role of Rnf122 in axon growth. Analysis of the top 10% of DEGs with a large divergence suggested that both extrinsic (e.g., immune microenvironment) and intrinsic factors (e.g., development) contributed to expression divergence between SNs and MNs following injury. CONCLUSIONS: This comprehensive analysis revealed convergent and divergent injury response genes in SNs and MNs, providing new insights into transcriptional reprogramming of sensory and motor neurons responding to axonal injury and subsequent regeneration. It also identified some novel regeneration-associated candidates that may facilitate the development of strategies for axon regeneration.

Comprehensive Lipidomic Analysis of Three Edible Microalgae Species Based on RPLC-Q-TOF-MS/MS.

Microalgae, integral to marine ecosystems for their rich nutrient content, notably lipids and proteins, were investigated by using reversed-phase liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (RPLC-Q-TOF-MS/MS). This study focused on lipid composition in three commonly used microalgae species (Spirulina platensis, Chlorella vulgaris, and Schizochytrium limacinum) for functional food applications. The analysis unveiled more than 700 lipid molecular species, including glycolipids (GLs), phospholipids (PLs), sphingolipids (SLs), glycerolipids, and betaine lipids (BLs). GLs (19.9-64.8%) and glycerolipids (24.1-70.4%) comprised the primary lipid. Some novel lipid content, such as acylated monogalactosyldiacylglycerols (acMGDG) and acylated digalactosyldiacylglycerols (acDGDG), ranged from 0.62 to 9.68%. The analysis revealed substantial GLs, PLs, and glycerolipid variations across microalgae species. Notably, S. platensis and C. vulgaris displayed a predominance of fatty acid (FA) 18:2 and FA 18:3 in GLs, while S. limacinum exhibited a prevalence of FA 16:0, collectively constituting over 60% of the FAs of GLs. In terms of PLs and glycerolipids, S. platensis and C. vulgaris displayed elevated levels of arachidonic acid (AA) and eicosapentaenoic acid (EPA), whereas S. limacinum exhibited a significant presence of docosahexaenoic acid (DHA). Principal component analysis (PCA) revealed MGDG (16:0/18:1), DG (16:0/22:5), Cer (d18:1/20:0), and LPC (16:1) as promising lipid markers for discriminating between these microalgae samples. This study contributes to a comprehensive understanding of lipid profiles in three microalgae species, emphasizing their distinct biochemical characteristics and potentially informing us of their high-value utilization in the food industry.

Global research hotspots and trends in constraint-induced movement therapy in rehabilitation over the past 30 years: a bibliometric and visualization study.

Background: Stroke is a cerebrovascular disease with high prevalence and mortality, and upper limb hemiparesis is a major factor limiting functional recovery in stroke patients. Improvement of motor function in stroke patients through various forms of constraint-induced movement therapy (CITM) has been recognized as safe and effective in recent years. This research field lacks a comprehensive systematic and clear vein combing analysis, analyzing the literature research of CIMT in the field of rehabilitation in the past three decades, summarizing the research hotspots and cutting-edge trends in this field, in an effort to offer ideas and references for subsequent researchers. Methods: Relevant literature on CIMT in rehabilitation was collected from 1996 to 2024 within the Web of Science database's core dataset by using CiteSpace6.1, VOSviewer1.6.18, R-bibliometrix4.6.1, Pajek5.16, Scimago Graphica 1.0.26 software for visualization and analysis. Results: There were 970 papers in all United States was ranked first with 401 papers. Alabama Univ was ranked first for institutions with 53 papers. Neurorehabilitation and Neural Repair was ranked first for journals with 78 papers, and Taub E was ranked first for author publications with 64 papers. Research keywords were CIMT, stroke rehabilitation, upper extremity function, lower extremity gait balance, randomized controlled trials, physical therapy techniques (transcranial magnetic stimulation and sensory amplitude electrical stimulation), primary motor cortex plasticity, lateral dominance (spatial behaviors), cerebral vascular accidents, activities of daily living, hand function, disability, functional restoration, bimanual training, aphasia, acquired invalidity, type A Botulinum toxin and joystick riding toys. Conclusion: The current state of research shows that CIMT still has a vast potential for development in the field of rehabilitation research. The research hotspots are the clinical efficacy of CIMT combined with other therapies (botulinum toxin type A, transcranial direct current stimulation, virtual reality, mirror therapy, robotic-assisted) to enhance the functionality of upper limb hemiparesis in stroke patients, the mechanism of CIMT to improve the plasticity of the motor cortex through electrophysiological and imaging methods, and improvement of lower limb gait balance function in stroke patients and aphasia applications, the optimal intervention time and dose, and exploration of CIMT in new settings such as robot-assisted, telemedicine, and home rehabilitation.

The joint association of lipoprotein(a) and Lp-PLA2 with the risk of stroke recurrence.

BACKGROUND AND PURPOSE: Currently little is known about the joint association of lipoprotein (a) [Lp(a)] and Lipoprotein-associated phospholipase A2 (Lp-PLA2) with stroke recurrence. METHODS: In this prospective multicenter cohort study, 10,675 consecutive acute ischemic stroke (IS) and transient ischemic attack patients (TIA) with Lp(a) and Lp-PLA2 were enrolled. The association of stroke recurrence within 1 year with Lp(a) and Lp-PLA2 was assessed using Cox proportional hazards models and Kaplan-Meier curves. The interaction between Lp(a) and Lp-PLA2 with stroke recurrence was evaluated by multiplicative and additive scales. RESULTS: A significant joint association of Lp(a) and Lp-PLA2 with the risk of stroke recurrence was observed. Multivariate cox regression analysis demonstrated that the combination of elevated Lp(a) (≥ 50 mg/dL) and Lp-PLA2 (≥175.1 ng/ml) was independently associated with the risk of stroke recurrence (adjusted hazard ratio: 1.42; 95 % CI: 1.15-1.76). Both significant multiplicative [(exp(ß3):1.63, 95 % CI: 1.17-2.29, P = 0.004] and additive interaction (RERI:0.55, 95 % CI: 0.20-0.90, P = 0.002; AP: 0.39, 95 %CI, 0.24-0.53) were observed between Lp(a) and Lp-PLA2. CONCLUSIONS: Our results indicated that Lp(a) and Lp-PLA2 have a joint association with the risk of stroke recurrence in IS/TIA patients. Patients with concomitant presence of elevated Lp(a) and Lp-PLA2 have greater risk of stroke recurrence.

Phagocytic Plasma Cells in Teleost Fish Provide Insights into the Origin and Evolution of B Cells in Vertebrates.

Teleost IgM+ B cells can phagocytose, like mammalian B1 cells, and secrete Ag-specific IgM, like mammalian B2 cells. Therefore, teleost IgM+ B cells may have the functions of both mammalian B1 and B2 cells. To support this view, we initially found that grass carp (Ctenopharyngodon idella) IgM+ plasma cells (PCs) exhibit robust phagocytic ability, akin to IgM+ naive B cells. Subsequently, we sorted grass carp IgM+ PCs into two subpopulations: nonphagocytic (Pha-IgM+ PCs) and phagocytic IgM+ PCs (Pha+IgM+ PCs), both of which demonstrated the capacity to secrete natural IgM with LPS and peptidoglycan binding capacity. Remarkably, following immunization of grass carp with an Ag, we observed that both Pha-IgM+ PCs and Pha+IgM+ PCs could secrete Ag-specific IgM. Furthermore, in vitro concatenated phagocytosis experiments in which Pha-IgM+ PCs from an initial phagocytosis experiment were sorted and exposed again to beads confirmed that these cells also have phagocytic capabilities, thereby suggesting that all teleost IgM+ B cells have phagocytic potential. Additionally, we found that grass carp IgM+ PCs display classical phenotypic features of macrophages, providing support for the hypothesis that vertebrate B cells evolved from ancient phagocytes. These findings together reveal that teleost B cells are a primitive B cell type with functions reminiscent of both mammalian B1 and B2 cells, providing insights into the origin and evolution of B cells in vertebrates.

Combined UPLC-QqQ-MS/MS and AP-MALDI Mass Spectrometry Imaging Method for Phospholipidomics in Obese Mouse Kidneys: Alleviation by Feeding Sea Cucumber Phospholipids.

Sea cucumber phospholipids have ameliorative effects on various diseases related to lipid metabolism. However, it is unclear whether it can ameliorate obesity-associated glomerulopathy (ORG) induced by a high-fat diet (HFD). The present study applied UPLC-QqQ-MS/MS and atmospheric pressure matrix-assisted laser desorption ionization mass spectrometry imaging (AP-MALDI MSI) to investigate the effects of sea cucumber phospholipids, including plasmalogen PlsEtn and plasmanylcholine PakCho, on phospholipid profiles in the HFD-induced ORG mouse kidney. Quantitative analysis of 135 phospholipids revealed that PlsEtn and PakCho significantly modulated phospholipid levels. Notably, PlsEtn modulated kidney overall phospholipids better than PakCho. Imaging the "space-content" of 9 phospholipids indicated that HFD significantly increased phospholipid content within the renal cortex. Furthermore, PlsEtn and PakCho significantly decreased the expression of transport-related proteins CD36, while elevating the expression of fatty acid ß-oxidation-related protein PPAR-α in the renal cortex. In conclusion, sea cucumber phospholipids reduced renal lipid accumulation, ameliorated renal damage, effectively regulated the content and distribution of renal phospholipids, and improved phospholipid homeostasis, exerting an anti-OGR effect.

Hepatic IL22RA1 deficiency promotes hepatic steatosis by modulating oxysterol in the liver.

BACKGROUND AIMS: Imbalance in lipid metabolism is the main cause of nonalcoholic fatty liver disease (NAFLD). While the pathogenesis of lipid accumulation mediated by extrahepatic regulators has been extensively studied, the intrahepatic regulators modulating lipid homeostasis remain unclear. Previous studies have shown that systemic administration of interleukin-22 (IL-22) protects against NAFLD; however, the role of IL-22/IL22RA1 signaling in modulating hepatic lipid metabolism remains uncertain. APPROACH RESULTS: This study shows hepatic IL22RA1 is vital in hepatic lipid regulation. IL22RA1 is downregulated in palmitic acid-treated mouse primary hepatocytes, as well as in the livers of NAFLD model mice and patients. Hepatocyte-specific Il22ra1 knockout (HKO) mice display diet-induced hepatic steatosis, insulin resistance, impaired glucose tolerance, increased inflammation, and fibrosis compared with flox/flox mice. This is attributed to increased lipogenesis mediated by the accumulation of hepatic oxysterols, particularly, 3 beta-hydroxy-5-cholestenoic acid (3ß HCA). Mechanistically, hepatic IL22RA1 deficiency facilitates 3ß HCA deposition via the activating transcription factor 3 (ATF3)/oxysterol 7 alpha-hydroxylase (CYP7B1) axis. Notably, 3ß HCA facilitates lipogenesis in MPHs and human liver organoids (HLOs) by activating LXR-alpha signaling, but IL-22 treatment attenuates this effect. Additionally, restoring CYP7B1 or silencing hepatic ATF3 reduces both hepatic 3ß HCA and lipid contents in HKO mice. CONCLUSIONS: These findings indicate that IL22RA1 plays a crucial role in maintaining hepatic lipid homeostasis in an ATF3/CYP7B1-dependent manner, and establish a link between 3ß HCA and hepatic lipid homeostasis.

Inclusion Strategy for Constructing S/N Orbital Hybridization-Regulated sp3/sp2 Carbon toward Boost Electrocatalysis.

Metal-free carbon-based electrocatalysts have gained significant attention in the field of zinc-air batteries (ZABs) due to their affordability, good conductivity and chemical stability. However, unmodified carbon materials typically fall short in adsorbing and activating the substrates and intermediates involved in oxygen reduction reactions (ORR). Here, a metal-free carbon-based electrocatalyst with S atom p orbital hybrid modified N-sp3/sp2 carbon structure (C/NS) were prepared by cyclodextrins inclusion. The catalyst demonstrates impressive ORR activity (E1/2=0.885 V vs. RHE) and robust ZABs performance with a power density of 171.3 mW cm-2 and a specific capacity of 781.2 mAh g-1. Density functional theory (DFT) calculation reveals that S atom effectively regulates the charge distribution and p-band center of active site carbon atom in the N-sp3/sp2 carbon structure. This modification prompts the adsorption and dissociation of O2 and intermediates, resulting in higher reactive activity. This work provides a valuable and practical strategy for preparing cost-effective metal-free carbon-based electrocatalysts for ORR with high performance.

Identification of Parkinson's disease PACE subtypes and repurposing treatments through integrative analyses of multimodal data.

Parkinson's disease (PD) is a serious neurodegenerative disorder marked by significant clinical and progression heterogeneity. This study aimed at addressing heterogeneity of PD through integrative analysis of various data modalities. We analyzed clinical progression data (≥5 years) of individuals with de novo PD using machine learning and deep learning, to characterize individuals' phenotypic progression trajectories for PD subtyping. We discovered three pace subtypes of PD exhibiting distinct progression patterns: the Inching Pace subtype (PD-I) with mild baseline severity and mild progression speed; the Moderate Pace subtype (PD-M) with mild baseline severity but advancing at a moderate progression rate; and the Rapid Pace subtype (PD-R) with the most rapid symptom progression rate. We found cerebrospinal fluid P-tau/α-synuclein ratio and atrophy in certain brain regions as potential markers of these subtypes. Analyses of genetic and transcriptomic profiles with network-based approaches identified molecular modules associated with each subtype. For instance, the PD-R-specific module suggested STAT3, FYN, BECN1, APOA1, NEDD4, and GATA2 as potential driver genes of PD-R. It also suggested neuroinflammation, oxidative stress, metabolism, PI3K/AKT, and angiogenesis pathways as potential drivers for rapid PD progression (i.e., PD-R). Moreover, we identified repurposable drug candidates by targeting these subtype-specific molecular modules using network-based approach and cell line drug-gene signature data. We further estimated their treatment effects using two large-scale real-world patient databases; the real-world evidence we gained highlighted the potential of metformin in ameliorating PD progression. In conclusion, this work helps better understand clinical and pathophysiological complexity of PD progression and accelerate precision medicine.

Identification of risk factors of Long COVID and predictive modeling in the RECOVER EHR cohorts.

BACKGROUND: SARS-CoV-2-infected patients may develop new conditions in the period after the acute infection. These conditions, the post-acute sequelae of SARS-CoV-2 infection (PASC, or Long COVID), involve a diverse set of organ systems. Limited studies have investigated the predictability of Long COVID development and its associated risk factors. METHODS: In this retrospective cohort study, we used electronic healthcare records from two large-scale PCORnet clinical research networks, INSIGHT (~1.4 million patients from New York) and OneFlorida+ (~0.7 million patients from Florida), to identify factors associated with having Long COVID, and to develop machine learning-based models for predicting Long COVID development. Both SARS-CoV-2-infected and non-infected adults were analysed during the period of March 2020 to November 2021. Factors associated with Long COVID risk were identified by removing background associations and correcting for multiple tests. RESULTS: We observed complex association patterns between baseline factors and a variety of Long COVID conditions, and we highlight that severe acute SARS-CoV-2 infection, being underweight, and having baseline comorbidities (e.g., cancer and cirrhosis) are likely associated with increased risk of developing Long COVID. Several Long COVID conditions, e.g., dementia, malnutrition, chronic obstructive pulmonary disease, heart failure, PASC diagnosis U099, and acute kidney failure are well predicted (C-index > 0.8). Moderately predictable conditions include atelectasis, pulmonary embolism, diabetes, pulmonary fibrosis, and thromboembolic disease (C-index 0.7-0.8). Less predictable conditions include fatigue, anxiety, sleep disorders, and depression (C-index around 0.6). CONCLUSIONS: This observational study suggests that association patterns between investigated factors and Long COVID are complex, and the predictability of different Long COVID conditions varies. However, machine learning-based predictive models can help in identifying patients who are at risk of developing a variety of Long COVID conditions.

Most people who develop COVID-19 make a full recovery, but some go on to develop post-acute sequelae of SARS-CoV-2 infection, commonly known as Long COVID. Up to now, we did not know why some people are affected by Long COVID whilst others are not. We conducted a study to identify risk factors for Long COVID and developed a mathematical modeling approach to predict those at risk. We find that Long COVID is associated with some factors such as experiencing severe acute COVID-19, being underweight, and having conditions including cancer or cirrhosis. Due to the wide variety of symptoms defined as Long COVID, it may be challenging to come up with a set of risk factors that can predict the whole spectrum of Long COVID. However, our approach could be used to predict a variety of Long COVID conditions.

An adult with hemorrhagic varicella co-infects with cytomegalovirus: a case report.

BACKGROUND: Hemorrhagic varicella (HV) is a particular form of chicken pox.,with high mortality in adults. This form of the disease is rare, to date, approximately 4 cases have been reported. Occasional cases of HV have been documented in adults with hematologic disorders or other diseases. While there is one reported case of simultaneous reactivation of cytomegalovirus in an adult with chickenpox, there is a lack of information regarding changes in liver function indicators for such patients. This is unfortunate, as CMV reactivation can further exacerbate liver failure and increase mortality. In this report, we present a case of hemorrhagic varicella reactivation with cytomegalovirus and provide some relevant discussions. CASE PRESENTATION: We present the case of a 25-year-old male with HV, who had a history of nephrotic syndrome generally controlled with orally administered prednisone at a dosage of 50 mg per day for two months. The patient arrived at the emergency room with complaints of abdominal pain and the presence of hemorrhagic vesicles on his body for the past 3 days. Despite medical evaluation, a clear diagnosis was not immediately determined. Upon admission, the leukocyte count was recorded as 20.96 × 109/L on the first day, leading to the initiation of broad-spectrum antibiotic treatment. Despite the general interpretation that a positive IgG and a negative IgM indicate a previous infection, the patient's extraordinarily elevated IgG levels, coupled with a markedly increased CMV DNA quantification, prompted us to suspect a reactivation of the CMV virus. In light of these findings, we opted for the intravenous administration of ganciclovir as part of the treatment strategy. Unfortunately,,the patient succumbed to rapidly worsening symptoms and passed away. Within one week of the patient's demise, chickenpox gradually developed in the medical staff who had been in contact with him. In such instances, we speculate that the patient's diagnosis should be classified as a rare case of hemorrhagic varicella. CONCLUSION: Swift identification and timely administration of suitable treatment for adult HV are imperative to enhance prognosis.

Phenolic endocrine-disrupting compounds in the Xiangjiang River: occurrence and risk assessment.

The levels of three phenolic endocrine-disrupting compounds (EDCs), NP, BPA and 4-t-OP were determined in water and sediment collected from sites along the Xiangjiang River, Zunyi, China. The NP, BPA and 4-t-OP concentrations ranged from 18.02 to 311.79 ng/L in the surface water, 16.04-408.12 ng/L in the submerged water, and 21.13-892.37 µg/kg dw in the sediment. NP contamination was most severe in both the river water and sediment. The ranges of the three phenolic EDCs were slightly greater in the submerged water than in the surface water (p > 0.05). The concentrations in the middle reaches were greater than those in the upstream and downstream reaches in both the water and sediment, and significant differences in content were detected in some reaches. The levels of three phenolic EDCs in the water and sediment had a positive correlation. In addition, the distribution coefficient (Kd) indicated that NP was more likely to adsorb to the sediment, and BPA and 4-t-OP were more likely to adsorb to river water. Moreover, the risk quotient (RQ) and hazard quotients (HQ) were used to reveal the environmental and health risks caused by coexposure to the three phenolic pollutants. The results showed that the current pollution is a threat to the environment of the study area and not a threat to the health of the local population.

Develop and validate a computable phenotype for the identification of Alzheimer's disease patients using electronic health record data.

INTRODUCTION: Alzheimer's disease (AD) is often misclassified in electronic health records (EHRs) when relying solely on diagnosis codes. This study aimed to develop a more accurate, computable phenotype (CP) for identifying AD patients using structured and unstructured EHR data. METHODS: We used EHRs from the University of Florida Health (UFHealth) system and created rule-based CPs iteratively through manual chart reviews. The CPs were then validated using data from the University of Texas Health Science Center at Houston (UTHealth) and the University of Minnesota (UMN). RESULTS: Our best-performing CP was "patient has at least 2 AD diagnoses and AD-related keywords in AD encounters," with an F1-score of 0.817 at UF, 0.961 at UTHealth, and 0.623 at UMN, respectively. DISCUSSION: We developed and validated rule-based CPs for AD identification with good performance, which will be crucial for studies that aim to use real-world data like EHRs. Highlights: Developed a computable phenotype (CP) to identify Alzheimer's disease (AD) patients using EHR data.Utilized both structured and unstructured EHR data to enhance CP accuracy.Achieved a high F1-score of 0.817 at UFHealth, and 0.961 and 0.623 at UTHealth and UMN.Validated the CP across different demographics, ensuring robustness and fairness.

Anti-hepatoma immunotherapy of Pholiota adiposa polysaccharide-coated selenium nanoparticles by reversing M2-like tumor-associated macrophage polarization.

Targeting macrophages to regulate the tumor microenvironment is a promising strategy for treating cancer. This study developed a stable nano drug (PAP-SeNPs) using Se nanoparticles (SeNPs) and the Pholiota adiposa polysaccharide component (PAP-1a) and reported their physical stability, M2-like macrophages targeting efficacy and anti-hepatoma immunotherapy potential, as well as their molecular mechanisms. Furthermore, the zero-valent and well-dispersed spherical PAP-SeNPs were also successfully synthesized with an average size of 55.84 nm and a negative ζ-potential of -51.45 mV. Moreover, it was observed that the prepared PAP-SeNPs were stable for 28 days at 4 °C. Intravital imaging highlighted that PAP-SeNPs had the dual effect of targeting desirable immune organs and tumors. In vitro analyses showed that the PAP-SeNPs polarized M2-like macrophages towards the M1 phenotype to induce hepatoma cell death, triggered by the time-dependent lysosomal endocytosis in macrophages. Mechanistically, PAP-SeNPs significantly activated the Tlr4/Myd88/NF-κB axis to transform tumor-promoting macrophages into tumor-inhibiting macrophages and successfully initiated antitumor immunotherapy. Furthermore, PAP-SeNPs also enhanced CD3+CD4+ T cells and CD3+CD8+ T cells, thereby further stimulating anti-hepatoma immune responses. These results suggest that the developed PAP-SeNPs is a promising immunostimulant that can assist hepatoma therapy.

KKL-35 inhibits growth of Staphylococcus aureus by systematically changing bacterial phenotypes.

KKL-35 is a new oxadiazole compound with potent broad-spectrum antibacterial activity against a number of gram-positive and gram-negative bacteria. However, its influences on bacterial growth are unclear. This study is to investigate phenotypic changes of Staphylococcus aureus (SA) caused by KKL-35 and evaluate antibacterial activity of combinations of KKL-35 with 7 class of antibiotics available in medical facilities. KKL-35-treated SA showed significantly lower survival under stresses of NaCl and H2O2 than DMSO (21.03 ± 2.60% vs. 68.21 ± 5.31% for NaCl, 4.91 ± 3.14% vs. 74.78 ± 2.88% for H2O2). UV exposure significantly decreased survival of SA treated with KKL-35 than DMSO-treated ones (23.91 ± 0.71% vs. 55.45 ± 4.70% for 4.2 J/m2, 12.80 ± 1.03% vs. 31.99 ± 5.99% for 7.0 J/m2, 1.52 ± 0.63% vs. 6.49 ± 0.51% for 14.0 J/m2). KKL-35 significantly decreased biofilm formation (0.47 ± 0.12 vs. 1.45 ± 0.21) and bacterial survival in the serum resistance assay (42.27 ± 2.77% vs. 78.31 ± 5.64%) than DMSO. KKL-35 significantly decreased ethidium bromide uptake and efflux, as well as the cell membrane integrity. KKL-35 had low cytotoxicity and low propensity for resistance. KKL-35 inhibited SA growth in concentration-independent and time-dependent manners, and showed additivity when combined with the majority class of available antibiotics. Antibiotic combinations of KKL-35 with ciprofloxacin, rifampicin, or linezolid significantly decreased bacterial loads than the most active antibiotic in the corresponding combination. Thus, KKL-35 inhibits growth of SA by decreasing bacterial environmental adaptations, biofilm formation, membrane uptake and efflux, as well as increasing antibiotic sensitivity. Its potent antibacterial activity, low cytotoxicity, low propensity for resistance, and wide choices in antibiotic combinations make KKL-35 a promising leading compound to design new antibiotics in monotherapies and combination therapies to treat bacterial infections.

Mn-doped CeO2 derived from Ce-MOF porous nanoribbons as highly active catalysts for the synthesis of dimethyl carbonate from CO2 and methanol.

It is desirable but challenging to develop highly-efficient catalysts for the direct synthesis of dimethyl carbonate (DMC) from methanol and CO2. The vacancy-mediated incorporation of heteroatom into surface reconstruction is an efficient method of defect engineering for enhancing the catalytic properties. In this work, manganese-doped cerium oxide porous nanoribbons (Mn/CeO2-BTC) were prepared derived from a Ce-BTC by a sacrificial template approach. It is found that the catalytic activity of Mn/CeO2-BTC catalysts can be readily controlled by varying the amount of Mn dopants and the as-synthesized 0.1-Mn/CeO2-BTC exhibited an outstanding activity for the synthesis of DMC from CO2 and methanol, which reached a high DMC yield (6.53 mmolDMC/gcat.) without any dehydrating agents. Based on characterization results, the enhanced performance may be attributed to the defective structures caused by Mn doping and the porous nanoribbons of the CeO2 crystals, which provide more surface oxygen vacancies and acidic-basic sites, favoring adsorption and activation of CO2 and methanol.

Optical genome mapping improves the accuracy of classification, risk stratification, and personalized treatment strategies for patients with acute myeloid leukemia.

Cytogenomic characterization is crucial for the classification and risk stratification of acute myeloid leukemia (AML), thereby facilitating therapeutic decision-making. We examined the clinical utility of optical genome mapping (OGM) in 159 AML patients (103 newly diagnosed and 56 refractory/relapsed), all of whom also underwent chromosomal banding analysis (CBA), fluorescence in situ hybridization, and targeted next-generation sequencing. OGM detected nearly all clinically relevant cytogenetic abnormalities that SCG identified with >99% sensitivity, provided the clonal burden was above 20%. OGM identified additional cytogenomic aberrations and/or provided information on fusion genes in 77 (48%) patients, including eight patients with normal karyotypes and four with failed karyotyping. The most common additional alterations identified by OGM included chromoanagenesis (n = 23), KMT2A partial tandem duplication (n = 11), rearrangements involving MECOM (n = 7), NUP98 (n = 2), KMT2A (n = 2), JAK2 (n = 2), and other gene fusions in 17 patients, with 10 showing novel fusion gene partners. OGM also pinpointed fusion genes in 17 (11%) patients where chromosomal rearrangements were concurrently detected by OGM and CBA. Overall, 24 (15%) aberrations were identified exclusively by OGM and had the potential to alter AML classification, risk stratification, and/or clinical trial eligibility. OGM emerges as a powerful tool for identifying fusion genes and detecting subtle or cryptic cytogenomic aberrations that may otherwise remain undetectable by CBA.

Data Set and Benchmark (MedGPTEval) to Evaluate Responses From Large Language Models in Medicine: Evaluation Development and Validation.

Background: Large language models (LLMs) have achieved great progress in natural language processing tasks and demonstrated the potential for use in clinical applications. Despite their capabilities, LLMs in the medical domain are prone to generating hallucinations (not fully reliable responses). Hallucinations in LLMs' responses create substantial risks, potentially threatening patients' physical safety. Thus, to perceive and prevent this safety risk, it is essential to evaluate LLMs in the medical domain and build a systematic evaluation. Objective: We developed a comprehensive evaluation system, MedGPTEval, composed of criteria, medical data sets in Chinese, and publicly available benchmarks. Methods: First, a set of evaluation criteria was designed based on a comprehensive literature review. Second, existing candidate criteria were optimized by using a Delphi method with 5 experts in medicine and engineering. Third, 3 clinical experts designed medical data sets to interact with LLMs. Finally, benchmarking experiments were conducted on the data sets. The responses generated by chatbots based on LLMs were recorded for blind evaluations by 5 licensed medical experts. The evaluation criteria that were obtained covered medical professional capabilities, social comprehensive capabilities, contextual capabilities, and computational robustness, with 16 detailed indicators. The medical data sets include 27 medical dialogues and 7 case reports in Chinese. Three chatbots were evaluated: ChatGPT by OpenAI; ERNIE Bot by Baidu, Inc; and Doctor PuJiang (Dr PJ) by Shanghai Artificial Intelligence Laboratory. Results: Dr PJ outperformed ChatGPT and ERNIE Bot in the multiple-turn medical dialogues and case report scenarios. Dr PJ also outperformed ChatGPT in the semantic consistency rate and complete error rate category, indicating better robustness. However, Dr PJ had slightly lower scores in medical professional capabilities compared with ChatGPT in the multiple-turn dialogue scenario. Conclusions: MedGPTEval provides comprehensive criteria to evaluate chatbots by LLMs in the medical domain, open-source data sets, and benchmarks assessing 3 LLMs. Experimental results demonstrate that Dr PJ outperforms ChatGPT and ERNIE Bot in social and professional contexts. Therefore, such an assessment system can be easily adopted by researchers in this community to augment an open-source data set.