Single-Particle Spectroscopic Chromatography Reveals Heterogeneous RNA Loading and Size Correlations in Lipid Nanoparticles.

Lipid nanoparticles (LNP) have emerged as pivotal delivery vehicles for RNA therapeutics. Previous research and development usually assumed that LNPs are homogeneous in population, loading density, and composition. Such perspectives are difficult to examine due to the lack of suitable tools to characterize these physicochemical properties at the single-nanoparticle level. Here, we report an integrated spectroscopy-chromatography approach as a generalizable strategy to dissect the complexities of multicomponent LNP assembly. Our platform couples cylindrical illumination confocal spectroscopy (CICS) with single-nanoparticle free solution hydrodynamic separation (SN-FSHS) to simultaneously profile population identity, hydrodynamic size, RNA loading levels, and distributions of helper lipid and PEGylated lipid of LNPs at the single-particle level and in a high-throughput manner. Using a benchmark siRNA LNP formulation, we demonstrate the capability of this platform by distinguishing seven distinct LNP populations, quantitatively characterizing size distribution and RNA loading level in wide ranges, and more importantly, resolving composition-size correlations. This SN-FSHS-CICS analysis provides critical insights into a substantial degree of heterogeneity in the packing density of RNA in LNPs and size-dependent loading-size correlations, explained by kinetics-driven assembly mechanisms of RNA LNPs.

Validity of Mobility-Based Exposure Assessment of Air Pollution: A Comparative Analysis with Home-Based Exposure Assessment.

Air pollution exposure is typically assessed at the front door where people live in large-scale epidemiological studies, overlooking individuals' daily mobility out-of-home. However, there is limited evidence that incorporating mobility data into personal air pollution assessment improves exposure assessment compared to home-based assessments. This study aimed to compare the agreement between mobility-based and home-based assessments with personal exposure measurements. We measured repeatedly particulate matter (PM2.5) and black carbon (BC) using a sample of 41 older adults in the Netherlands. In total, 104 valid 24 h average personal measurements were collected. Home-based exposures were estimated by combining participants' home locations and temporal-adjusted air pollution maps. Mobility-based estimates of air pollution were computed based on smartphone-based tracking data, temporal-adjusted air pollution maps, indoor-outdoor penetration, and travel mode adjustment. Intraclass correlation coefficients (ICC) revealed that mobility-based estimates significantly improved agreement with personal measurements compared to home-based assessments. For PM2.5, agreement increased by 64% (ICC: 0.39-0.64), and for BC, it increased by 21% (ICC: 0.43-0.52). Our findings suggest that adjusting for indoor-outdoor pollutant ratios in mobility-based assessments can provide more valid estimates of air pollution than the commonly used home-based assessments, with no added value observed from travel mode adjustments.

For Whom Does Education Convey Health Benefits? A Two-Generation and Life Course Approach.

Scholars of social determinants of health have long been interested in how parent's and own education influence health. However, the differing effects of parent's and own education on health-that is, for what socioeconomic group education conveys health benefits-are relatively less studied. Using multilevel marginal structural models, we estimate the heterogeneous effects of parent's and own education over the life course on two health measures. Our analysis considers both parent's and respondent's pre-education covariates, such as childhood health and socioeconomic conditions. We find that the protective effects of college completion against negative health outcomes are remarkably similar regardless of parent's (measured by father's or mother's) education. Meanwhile, parent's education has a larger effect when the average educational level is low in the population. Our results also reveal distinct life course patterns between health measures. We conclude by discussing the implications of our study for understanding the education-health relationship.

Meconopsis biluoensis (Papaveraceae), a new species revealed by population-level investigation.

Meconopsis biluoensis, a new species of Papaveraceae in an alpine meadow from Yunnan, Southwest China, is described and illustrated. Morphologically, it resembles Meconopsis georgei, while it is distinct in acaulescent and hispid with clearly expanded bases on the leaves. A genus-level molecular phylogenetic analysis supported the closest relationship between M. biluoensis and M. georgei. In a finer population-level molecular phylogenetic analysis using ribosomal DNA (rDNA) and the chloroplast genome, individuals from M. biluoensis and M. georgei were clearly separated, and the extremely short branch length indicated that the two species had a very short differentiation time. The species has currently been assessed as "endangered" (EN) due to its small-sized population and narrow distribution following the IUCN categories and criteria.

High-Flow Nasal Cannula Versus Noninvasive Ventilation as Initial Treatment in Acute Hypoxia: A Propensity Score-Matched Study.

IMPORTANCE: Patients presenting to the emergency department (ED) with hypoxemia often have mixed or uncertain causes of respiratory failure. The optimal treatment for such patients is unclear. Both high-flow nasal cannula (HFNC) and noninvasive ventilation (NIV) are used. OBJECTIVES: We sought to compare the effectiveness of initial treatment with HFNC versus NIV for acute hypoxemic respiratory failure. DESIGN SETTING AND PARTICIPANTS: We conducted a retrospective cohort study of patients with acute hypoxemic respiratory failure treated with HFNC or NIV within 24 hours of arrival to the University of Michigan adult ED from January 2018 to December 2022. We matched patients 1:1 using a propensity score for odds of receiving NIV. MAIN OUTCOMES AND MEASURES: The primary outcome was major adverse pulmonary events (28-d mortality, ventilator-free days, noninvasive respiratory support hours) calculated using a win ratio. RESULTS: A total of 1154 patients were included. Seven hundred twenty-six (62.9%) received HFNC and 428 (37.1%) received NIV. We propensity score matched 668 of 1154 (57.9%) patients. Patients on NIV versus HFNC had lower 28-day mortality (16.5% vs. 23.4%, p = 0.033) and required noninvasive treatment for fewer hours (median 7.5 vs. 13.5, p < 0.001), but had no difference in ventilator-free days (median [interquartile range]: 28 [26, 28] vs. 28 [10.5, 28], p = 0.199). Win ratio for composite major adverse pulmonary events favored NIV (1.38; 95% CI, 1.15-1.65; p < 0.001). CONCLUSIONS AND RELEVANCE: In this observational study of patients with acute hypoxemic respiratory failure, initial treatment with NIV compared with HFNC was associated with lower mortality and fewer composite major pulmonary adverse events calculated using a win ratio. These findings underscore the need for randomized controlled trials to further understand the impact of noninvasive respiratory support strategies.

Safety and efficacy of peptide receptor radionuclide therapy in neuroendocrine tumors: A single center experience.

Peptide receptor radionucleotide therapy (PRRT) with 177Lu-dotatate is widely used for the treatment of patients with neuroendocrine tumors (NETs). We analyzed data from 104 patients with NETs treated with 177Lu -dotatate at a US academic center between December 2017 and October 2020 to better understand patterns of long-term efficacy, safety, and toxicity in the real-world setting. 177Lu-dotatate (200 mCi) was administered every eight weeks for four doses. The most common sites of primary disease were small intestine NETs (n = 49, 47%), pancreatic NETs (n = 32, 31%), and lung NETs (n = 7, 7%). Twenty-seven percent had Ki-67 <3%, 49% had Ki-67 between 3-20%, and 13.5% had Ki-67 >20%. The cohort had been pretreated with a median of two prior lines of treatment. Forty percent had received prior liver-directed treatment. Seventy-four percent of patients completed all four doses of treatment. The objective response rate was 18%. The median time-to-treatment failure/death was significantly longer for small-bowel NETs when compared to pancreatic NETs (37.3 months vs. 13.2 months, p = 0.001). In a multivariate model, Ki-67, primary site, and liver tumor burden ≥50% were found to independently predict time-to-treatment failure/death. Around 40% of patients experienced adverse events of ≥grade 3 severity. Treatment-related adverse events leading to discontinuation of therapy happened in 10% of patients. Preexisting mesenteric/peritoneal disease was present in 33 patients; seven of these patients developed bowel-related toxicities including two grade 5 events. We also report two cases of delayed-onset minimal change nephrotic syndrome, which occurred 14 and 27 months after the last dose of PRRT. Lastly, we describe six patients who developed rapid tumor progression in the liver leading to terminal liver failure within 7.3 months from the start of PRRT, and identify potential risk factors associated with this occurrence, which will need further study.

Value of exhaled hydrogen sulfide in early diagnosis of esophagogastric junction adenocarcinoma.

Esophagogastric junction adenocarcinoma (EJA) has increased in recent years, and it exhibits a poor prognosis and a short survival period for patients. Hydrogen sulfide (H2S) plays an important role in the pathogenesis of cancer and has been studied as a diagnostic factor in some tumor diseases. However, few studies have explored the diagnostic value of H2S for EJA. In the present study, a total of 56 patients with early-stage EJA were enrolled while 57 healthy individuals were selected as the healthy control group. Clinical features were recorded, and exhaled H2S and blood samples were collected from both groups. Exhaled H2S and serum interleukin-8 (IL-8) expression levels were detected in both groups. The correlation between exhaled H2S and serum IL-8 levels was analyzed using Pearson's correlation method. Receiver operating characteristic (ROC) curve was used to evaluate the diagnostic value of exhaled H2S combined with IL-8 detection in EJA. The results showed that patients with EJA exhaled more H2S than healthy individuals. In addition, exhaled H2S was positively correlated with increased IL-8 expression. The ROC curve revealed that the exhaled H2S test had an acceptable diagnostic effect and could be used to diagnose EJA. The increase in H2S exhaled by patients with EJA indicated that H2S may be related to the occurrence and development of EJA; however, the in vivo mechanism needs to be further explored. Collectively, it was determined in the present study that exhaled H2S was significantly higher in patients with early-stage EJA than in healthy controls and combined diagnosis with patient serum IL-8 could improve diagnostic accuracy, which has potential diagnostic value for early diagnosis and screening of EJA.

Motion Tracking of Daily Living and Physical Activities in Health Care: Systematic Review From Designers' Perspective.

BACKGROUND: Motion tracking technologies serve as crucial links between physical activities and health care insights, facilitating data acquisition essential for analyzing and intervening in physical activity. Yet, systematic methodologies for evaluating motion tracking data, especially concerning user activity recognition in health care applications, remain underreported. OBJECTIVE: This study aims to systematically review motion tracking in daily living and physical activities, emphasizing the critical interaction among devices, users, and environments from a design perspective, and to analyze the process involved in health care application research. It intends to delineate the design and application intricacies in health care contexts, focusing on enhancing motion tracking data's accuracy and applicability for health monitoring and intervention strategies. METHODS: Using a systematic review, this research scrutinized motion tracking data and their application in health care and wellness, examining studies from Scopus, Web of Science, EBSCO, and PubMed databases. The review used actor network theory and data-enabled design to understand the complex interplay between humans, devices, and environments within these applications. RESULTS: Out of 1501 initially identified studies, 54 (3.66%) were included for in-depth analysis. These articles predominantly used accelerometer and gyroscope sensors (n=43, 80%) to monitor and analyze motion, demonstrating a strong preference for these technologies in capturing both dynamic and static activities. While incorporating portable devices (n=11, 20%) and multisensor configurations (n=16, 30%), the application of sensors across the body (n=15, 28%) and within physical spaces (n=17, 31%) highlights the diverse applications of motion tracking technologies in health care research. This diversity reflects the application's alignment with activity types ranging from daily movements to specialized scenarios. The results also reveal a diverse participant pool, including the general public, athletes, and specialized groups, with a focus on healthy individuals (n=31, 57%) and athletes (n=14, 26%). Despite this extensive application range, the focus primarily on laboratory-based studies (n=39, 72%) aimed at professional uses, such as precise activity identification and joint functionality assessment, emphasizes a significant challenge in translating findings from controlled environments to the dynamic conditions of everyday physical activities. CONCLUSIONS: This study's comprehensive investigation of motion tracking technology in health care research reveals a significant gap between the methods used for data collection and their practical application in real-world scenarios. It proposes an innovative approach that includes designers in the research process, emphasizing the importance of incorporating data-enabled design framework. This ensures that motion data collection is aligned with the dynamic and varied nature of daily living and physical activities. Such integration is crucial for developing health applications that are accessible, intuitive, and tailored to meet diverse user needs. By leveraging a multidisciplinary approach that combines design, engineering, and health sciences, the research opens new pathways for enhancing the usability and effectiveness of health technologies.

Utilizing Machine Learning Models for Predicting Diamagnetic Susceptibility of Organic Compounds.

This research is centered on examining the magnetic characteristics of organic molecules, with a particular emphasis on magnetic susceptibility, an essential physical property that provides insights into molecular microstructures and reaction processes. Traditional approaches for determining and calculating magnetic susceptibility are generally inefficient and demanding. To overcome these challenges, we have introduced a novel approach using quantitative structure-property relationships, which efficiently elucidates the relationship between the structural properties of molecules and their molar magnetic susceptibility. In our study, we utilized a comprehensive database comprising molar magnetic susceptibility data for 382 organic molecules. We applied six distinct molecular fingerprinting methods-RDKit Fingerprint, Morgan Fingerprint, MACCS Keys, atom pair fingerprint, Avalon Fingerprint, and topology fingerprint-as feature inputs for training seven different machine learning models, namely random forest, AdaBoost, gradient boosting, extra trees, elastic net, support vector machine, and multilayer perceptron (MLP). Our findings revealed that the integration of the atom pair fingerprint with the MLP model yielded R2 values of 0.88 and 0.90 in the validation and test sets, respectively, showcasing exceptional predictive accuracy. This advancement significantly expedites research and development processes related to the magnetic properties of organic molecules. Moreover, by employing this effective predictive method, it is expected to considerably reduce both experimental and computational expenses while maintaining high accuracy. This development represents a breakthrough in the rapid screening and prediction of properties for various compounds, offering a new and efficient pathway in this field of study.

Sex- and Age-Specific Prevalence of Osteopenia and Osteoporosis: Sampling Survey.

BACKGROUND: Osteopenia and osteoporosis are posing a long-term influence on the aging population's health contributing to a higher risk of mortality, loss of autonomy, hospitalization, and huge health system costs and social burden. Therefore, more pertinent data are needed to demonstrate the current state of osteoporosis. OBJECTIVE: This sampling survey seeks to assess the trends in the prevalence of osteopenia and osteoporosis in a Chinese Han population. METHODS: A community-based cross-sectional study involving 16,377 participants used a multistage sampling method. Bone mineral density was measured using the quantitative ultrasonic densitometry. Student t test and Mann-Whitney U test were used to test the difference between normally and nonnormally distributed quantitative variables between male and female participants. A chi-square (χ2) test was used to compare categorized variables. Stratified analysis was conducted to describe the prevalence rates of osteoporosis (T score ≤-2.5) and osteopenia (T score -2.5 to -1.0) across age, sex, calcium intake, and menopause. A direct standardization method was used to calculate the age-standardized prevalence rates of osteoporosis and osteopenia. T-score was further categorized into quartiles (T1-T4) by age- and sex-specified groups. RESULTS: The prevalence rates of osteopenia and osteoporosis were 40.5% (6633/16,377) and 7.93% (1299/16,377), respectively, and the age-standardized prevalence rates were 27.32% (287,877,129.4/1,053,861,940) and 3.51% (36,974,582.3/1,053,861,940), respectively. There was an increase in osteopenia and osteoporosis prevalence from 21.47% (120/559) to 56.23% (754/1341) and 0.89% (5/559) to 17.23% (231/1341), respectively, as age increased from 18 years to 75 years old. The prevalence rates of osteopenia and osteoporosis were significantly higher in female participants (4238/9645, 43.94% and 1130/9645, 11.72%) than in male participants (2395/6732, 35.58% and 169/6732, 2.51%; P<.001), and in postmenopausal female participants (3638/7493, 48.55% and 1053/7493, 14.05%) than in premenopausal female participants (538/2026, 26.55% and 53/2026, 2.62%; P<.001). In addition, female participants with a history of calcium intake had a lower osteoporosis prevalence rate than female participants without any history of calcium intake in all age groups (P=.004). From low quartile to high quartile of T-score, the prevalence of diabetes mellitus (752/4037, 18.63%; 779/4029, 19.33%; 769/3894, 19.75%; and 869/3879, 22.4%) and dyslipidemia (2228/4036, 55.2%; 2304/4027, 57.21%; 2306/3891, 59.26%; and 2379/3878, 61.35%) were linearly increased (P<.001), while the prevalence of cancer (112/4037, 2.77%; 110/4029, 2.73%; 103/3894, 2.65%; and 77/3879, 1.99%) was decreased (P=.03). CONCLUSIONS: Our data imply that as people age, osteopenia and osteoporosis are more common in females than in males, particularly in postmenopausal females than in premenopausal females, and bone mineral density significantly affects the prevalence of chronic diseases. These findings offer information that can be applied to intervention programs meant to prevent or lessen the burden of osteoporosis in China.

Mortality Burden of Liver Cancer in China: An Observational Study From 2008 to 2020.

Background and Aims: China accounts for nearly half of liver cancer deaths globally. A better understanding of the current liver cancer mortality will be helpful to establishing priorities for intervention and to decreasing the disease burden of liver cancer. The study aimed to explore and predict the mortality burden of liver cancer in China. Methods: Data were extracted from the Disease Surveillance Point system of the Chinese Center for Disease Control and Prevention from 2008 to 2020. Crude and age-standardized liver cancer mortality rates were reported by sex, urban or rural residence, and region. Trends in liver cancer mortality rates from 2008 to 2020 were estimated as average annual percentage change (AAPC). The changing trend of live cancer mortality in the future is also predicted. Results: In 2020, the crude mortality of liver cancer was 25.57/100,000, and males and people lived in rural areas had higher age-standardized liver cancer mortality rates than females and people lived in people in urban areas. Crude mortality and age-standardized mortality rates in southwest provinces (Guangxi, Sichuan, Tibet) and in a northeast province (Heilongjiang) were higher than that in other provinces, and age-specific mortality rates increased with age. From 2008 to 2020, liver cancer mortality rates decreased, but people under 50 years of age had a higher AAPC than those over 50 years of age, possibly because of the adoption of hepatitis B virus vaccination in newborns and children. Furthermore, the mortality of liver cancer in 2021-2030 is predicted to have a downward trend. Conclusions: Liver cancer mortality rates declined in China from 2008 to 2020. Future interventions to control liver cancer mortality need to focus on people of male sex, older age, and living in rural areas or less developed provinces.

LiF/Li3N-Rich Electrode-Electrolyte Interfaces Enabled by Multi-Functional Electrolyte Additive to Achieve High-Performance Li/LiNi0.8Co0.1Mn0.1O2 Batteries.

LiPF6-based carbonate electrolytes have been extensively employed in commercial Li-ion batteries, but they face numerous interfacial stability challenges while applicating in high-energy-density lithium-metal batteries (LMBs). Herein, this work proposes N-succinimidyl trifluoroacetate (NST) as a multifunctional electrolyte additive to address these challenges. NST additive could optimize Li+ solvation structure and eliminate HF/H2O in the electrolyte, and preferentially be decomposed on the Ni-rich cathode (LiNi0.8Co0.1Mn0.1O2, NCM811) to generate LiF/Li3N-rich cathode-electrolyte interphase (CEI) with high conductivity. The synergistic effect reduces the electrolyte decomposition and inhibits the transition metal (TM) dissolution. Meanwhile, NST promotes the creation of solid electrolyte interphase (SEI) rich in inorganics on the Li metal anode (LMA), which restrains the growth of Li dendrites, minimizes parasitic reactions, and fosters rapid Li+ transport. As a result, compared with the reference, the Li/LiNi0.8Co0.1Mn0.1O2 cell with 1.0 wt.% NST exhibits higher capacity retention after 200 cycles at 1C (86.4% vs. 64.8%) and better rate performance, even at 9C. In the presence of NST, the Li/Li symmetrical cell shows a super-stable cyclic performance beyond 500 h at 0.5 mA cm-2/0.5 mAh cm-2. These unique features of NST are a promising solution for addressing the interfacial deterioration issue of high-capacity Ni-rich cathodes paired with LMA.

Pretreatment and analysis techniques development of TKIs in biological samples for pharmacokinetic studies and therapeutic drug monitoring.

Tyrosine kinase inhibitors (TKIs) have emerged as the first-line small molecule drugs in many cancer therapies, exerting their effects by impeding aberrant cell growth and proliferation through the modulation of tyrosine kinase-mediated signaling pathways. However, there exists a substantial inter-individual variability in the concentrations of certain TKIs and their metabolites, which may render patients with compromised immune function susceptible to diverse infections despite receiving theoretically efficacious anticancer treatments, alongside other potential side effects or adverse reactions. Therefore, an urgent need exists for an up-to-date review concerning the biological matrices relevant to bioanalysis and the sampling methods, clinical pharmacokinetics, and therapeutic drug monitoring of different TKIs. This paper provides a comprehensive overview of the advancements in pretreatment methods, such as protein precipitation (PPT), liquid-liquid extraction (LLE), solid-phase extraction (SPE), micro-SPE (µ-SPE), magnetic SPE (MSPE), and vortex-assisted dispersive SPE (VA-DSPE) achieved since 2017. It also highlights the latest analysis techniques such as newly developed high performance liquid chromatography (HPLC) and high-resolution mass spectrometry (HRMS) methods, capillary electrophoresis (CE), gas chromatography (GC), supercritical fluid chromatography (SFC) procedures, surface plasmon resonance (SPR) assays as well as novel nanoprobes-based biosensing techniques. In addition, a comparison is made between the advantages and disadvantages of different approaches while presenting critical challenges and prospects in pharmacokinetic studies and therapeutic drug monitoring.

Clinical Application of Different Liquid Biopsy Components in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is the most common form of primary liver cancer, usually occurring in the background of chronic liver disease. HCC lethality rate is in the third highest place in the world. Patients with HCC have concealed early symptoms and possess a high-level of heterogeneity. Once diagnosed, most of the tumors are in advanced stages and have a poor prognosis. The sensitivity and specificity of existing detection modalities and protocols are suboptimal. HCC calls for more sophisticated and individualized therapeutic regimens. Liquid biopsy is non-invasive, repeatable, unaffected by location, and can be monitored dynamically. It has emerged as a useable aid in achieving precision malignant tumor treatment. Circulating tumor cells (CTCs), circulating nucleic acids, exosomes and tumor-educated platelets are the commonest components of a liquid biopsy. It possesses the theoretical ability to conquer the high heterogeneity and the difficulty of early detection for HCC patients. In this review, we summarize the common enrichment techniques and the clinical applications in HCC for different liquid biopsy components. Tumor recurrence after HCC-related liver transplantation is more insidious and difficult to treat. The clinical use of liquid biopsy in HCC-related liver transplantation is also summarized in this review.

Spatiotemporal control over self-assembly of supramolecular hydrogels through reaction-diffusion.

Supramolecular self-assembly is ubiquitous in living system and is usually controlled to proceed in time and space through sophisticated reaction-diffusion processes, underpinning various vital cellular functions. In this contribution, we demonstrate how spatiotemporal self-assembly of supramolecular hydrogels can be realized through a simple reaction-diffusion-mediated transient transduction of pH signal. In the reaction-diffusion system, a relatively faster diffusion of acid followed by delayed enzymatic production and diffusion of base from the opposite site enables a transient transduction of pH signal in the substrate. By coupling such reaction-diffusion system with pH-sensitive gelators, dynamic supramolecular hydrogels with tunable lifetimes are formed at defined locations. The hydrogel fibers show interesting dynamic growing behaviors under the regulation of transient pH signal, reminiscent of their biological counterpart. We further demonstrate a proof-of-concept application of the developed methodology for dynamic information encoding in a soft substrate. We envision that this work may provide a potent approach to enable transient transduction of various chemical signals for the construction of new colloidal materials with the capability to evolve their structures and functionalities in time and space.

Estuarine environmental flow assessment based on the flow-ecological health index relation model: a case study in Yangtze River Estuary, China.

Environmental flow (e-flow) is the water demand of one given ecosystem, which can become the flow regulation target for protection and restoration of river or estuarine ecosystems. In this study, an e-flow assessment based on the flow-ecological health index (EHI) relation model was conducted to improve ecosystem health of the Yangtze River Estuary (YRE). Monitoring data of hydrology, biology, and water environment in the last decades were used for the model establishment. For the description of the YRE ecosystem, an EHI system was developed by cumulative frequency distribution curves and adaption of national standards. After preprocessing original flow values into proportional flow values, the generalized additive model and Monte Carlo random sampling were used for the establishment of the flow-EHI relation model. From the model calculation, the e-flow assessment results were that, in proportional flow values, the suitable flow range was 1.05-1.35, and the optimum flow range was 1.15-1.25 (flows in Yangtze River Datong Station). For flow regulation in two crucial periods, flows of 42,630-65,545 m3/s or over 14,675 m3/s are needed for the suitable flow of YRE in summer (June-August) or January, respectively. An adaptive management framework of ecological health-based estuarine e-flow assessment for YRE was contrived due to the limitation of current established model when facing the extreme drought in summer, 2022. The methodology and framework in this study are expected to provide valuable management and data support for the sustainable development of estuarine ecosystems and to bring inspiration for further studies at even continental or global levels.

Predicting long-term outcomes for acute ischemic stroke using multi-model MRI radiomics and clinical variables.

Purpose: The objective of this study was to create and validate a novel prediction model that incorporated both multi-modal radiomics features and multi-clinical features, with the aim of accurately identifying acute ischemic stroke (AIS) patients who faced a higher risk of poor outcomes. Methods: A cohort of 461 patients diagnosed with AIS from four centers was divided into a training cohort and a validation cohort. Radiomics features were extracted and selected from diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC) images to create a radiomic signature. Prediction models were developed using multi-clinical and selected radiomics features from DWI and ADC. Results: A total of 49 radiomics features were selected from DWI and ADC images by the least absolute shrinkage and selection operator (LASSO). Additionally, 20 variables were collected as multi-clinical features. In terms of predicting poor outcomes in validation set, the area under the curve (AUC) was 0.727 for the DWI radiomics model, 0.821 for the ADC radiomics model, 0.825 for the DWI + ADC radiomics model, and 0.808 for the multi-clinical model. Furthermore, a prediction model was built using all selected features, the AUC for predicting poor outcomes increased to 0.86. Conclusion: Radiomics features extracted from DWI and ADC images can serve as valuable biomarkers for predicting poor clinical outcomes in patients with AIS. Furthermore, when these radiomics features were combined with multi-clinical features, the predictive performance was enhanced. The prediction model has the potential to provide guidance for tailoring rehabilitation therapies based on individual patient risks for poor outcomes.

Analysis and experimental validation of IL-17 pathway and key genes as central roles associated with inflammation in hepatic ischemia-reperfusion injury.

Hepatic ischemia-reperfusion injury (HIRI) elicits an immune-inflammatory response that may result in hepatocyte necrosis and apoptosis, ultimately culminating in postoperative hepatic dysfunction and hepatic failure. The precise mechanisms governing the pathophysiology of HIRI remain incompletely understood, necessitating further investigation into key molecules and pathways implicated in disease progression to guide drug discovery and potential therapeutic interventions. Gene microarray data was downloaded from the GEO expression profile database. Integrated bioinformatic analyses were performed to identify HIRI signature genes, which were subsequently validated for expression levels and diagnostic efficacy. Finally, the gene expression was verified in an experimental HIRI model and the effect of anti-IL17A antibody intervention in three time points (including pre-ischemic, post-ischemic, and at 1 h of reperfusion) on HIRI and the expression of these genes was investigated. Bioinformatic analyses of the screened characterized genes revealed that inflammation, immune response, and cell death modulation were significantly associated with HIRI pathophysiology. CCL2, BTG2, GADD45A, FOS, CXCL10, TNFRSF12A, and IL-17 pathway were identified as key components involved in the HIRI. Serum and liver IL-17A expression were significantly upregulated during the initial phase of HIRI. Pretreatment with anti-IL-17A antibody effectively alleviated the damage of liver tissue, suppressed inflammatory factors, and serum transaminase levels, and downregulated the mRNA expression of CCL2, GADD45A, FOS, CXCL10, and TNFRSF12A. Injection of anti-IL17A antibody after ischemia and at 1 h of reperfusion failed to demonstrate anti-inflammatory and attenuating HIRI benefits relative to earlier intervention. Our study reveals that the IL-17 pathway and related genes may be involved in the proinflammatory mechanism of HIRI, which may provide a new perspective and theoretical basis for the prevention and treatment of HIRI.