Global epidemiology of severe fever with thrombocytopenia syndrome virus in human and animals: a systematic review and meta-analysis.

Background: Since the initial identification of the Severe Fever with Thrombocytopenia Syndrome (SFTS) in ticks in rural areas of China in 2009, the virus has been increasingly isolated from a diverse array of hosts globally, exhibiting a rising trend in incidence. This study aims to conduct a systematic analysis of the temporal and spatial distribution of SFTS cases, alongside an examination of the infection rates across various hosts, with the objective of addressing public concerns regarding the spread and impact of the disease. Methods: In this systematic review and meta-analysis, an exhaustive search was conducted across multiple databases, including PubMed, Web of Science, Embase, and Medline, CNKI, WanFang, and CQVIP. The literature search was confined to publications released between January 1, 2009, and May 29, 2023. The study focused on collating data pertaining to animal infections under natural conditions and human infection cases reported. Additionally, species names were unified using the National Center for Biotechnology Information (NCBI) database. The notification rate, notification death rate, case fatality rate, and infection rates (or MIR) were assessed for each study with available data. The proportions were pooled using a generalized linear mixed-effects model (GLMM). Meta-regressions were conducted for subgroup analysis. This research has been duly registered with PROSPERO, bearing the registration number CRD42023431010. Findings: We identified 5492 studies from database searches and assessed 238 full-text studies for eligibility, of which 234 studies were included in the meta-analysis. For human infection data, the overall pooled notification rate was 18.93 (95% CI 17.02-21.05) per ten million people, the overall pooled notification deaths rate was 3.49 (95% CI 2.97-4.10) per ten million people, and the overall pooled case fatality rate was 7.80% (95% CI 7.01%-8.69%). There was an increasing trend in notification rate and deaths rate, while the case fatality rate showed a significant decrease globally. Regarding animal infection data, among 94 species tested, 48 species were found to carry positive nucleic acid or antibodies. Out of these, 14 species were classified under Arthropoda, while 34 species fell under Chordata, comprising 27 Mammalia and 7 Aves. Interpretation: This systematic review and meta-analysis present the latest global report on SFTS. In terms of human infections, notification rates and notification deaths rates are on the rise, while the case fatality rate has significantly decreased. More SFTSV animal hosts have been discovered than before, particularly among birds, indicating a potentially broader transmission range for SFTSV. These findings provide crucial insights for the prevention and control of SFTS on a global scale. Funding: None.

Discrimination of apples from the surrounding Bohai Bay and the loess plateau: A combined study of ICP-MS and UPLC-Q-TOF-MS based element and metabolite fingerprints.

Apples are important fruits in China, and their authentication is beneficial for quality control. However, the differentiation between apples from two primary producing regions, the surrounding Bohai Bay (BHB) and the Loess Plateau (LP), has not been well studied. This study used element and metabolite fingerprints combined with mathematical recognition techniques to discriminate between BHB and LP apples. A total of 235 samples were collected from these regions during 2018-2019. The apple element and metabolite profiles were obtained via instrument analysis. Differential elements and metabolites between BHB and LP apples were identified, and linear and nonlinear discriminant models were constructed. Nonlinear models demonstrated higher accuracy and effectiveness in model optimization. The final random forest (RF) model, constructed with 11 elements and 51 metabolites, achieved a training accuracy of 91.51% and a validation accuracy of 98.57%. This study discriminated between BHB and LP apples, providing a foundation for apple authentication.

ELM2-SANT Domain-Containing Scaffolding Protein 1 Regulates Differentiation and Maturation of Cardiomyocytes Derived From Human-Induced Pluripotent Stem Cells.

BACKGROUND: ELMSAN1 (ELM2-SANT domain-containing scaffolding protein 1) is a newly identified scaffolding protein of the MiDAC (mitotic deacetylase complex), playing a pivotal role in early embryonic development. Studies on Elmsan1 knockout mice showed that its absence results in embryo lethality and heart malformation. However, the precise function of ELMSAN1 in heart development and formation remains elusive. To study its potential role in cardiac lineage, we employed human-induced pluripotent stem cells (hiPSCs) to model early cardiogenesis and investigated the function of ELMSAN1. METHODS AND RESULTS: We generated ELMSAN1-deficient hiPSCs through knockdown and knockout techniques. During cardiac differentiation, ELMSAN1 depletion inhibited pluripotency deactivation, decreased the expression of cardiac-specific markers, and reduced differentiation efficiency. The impaired expression of genes associated with contractile sarcomere structure, calcium handling, and ion channels was also noted in ELMSAN1-deficient cardiomyocytes derived from hiPSCs. Additionally, through a series of structural and functional assessments, we found that ELMSAN1-null hiPSC cardiomyocytes are immature, exhibiting incomplete sarcomere Z-line structure, decreased calcium handling, and impaired electrophysiological properties. Of note, we found that the cardiac-specific role of ELMSAN1 is likely associated with histone H3K27 acetylation level. The transcriptome analysis provided additional insights, indicating maturation reduction with the energy metabolism switch and restored cell proliferation in ELMSAN1 knockout cardiomyocytes. CONCLUSIONS: In this study, we address the significance of the direct involvement of ELMSAN1 in the differentiation and maturation of hiPSC cardiomyocytes. We first report the impact of ELMSAN1 on multiple aspects of hiPSC cardiomyocyte generation, including cardiac differentiation, sarcomere formation, calcium handling, electrophysiological maturation, and proliferation.

Zoonotic spillover and extreme weather events drive the global outbreaks of airborne viral emerging infectious diseases.

Outbreaks of airborne viral emerging infectious diseases (EIDs) cause an increasing burden on global public health, particularly with a backdrop of intensified climate change. However, infection sources and drivers for outbreaks of airborne viral EIDs remain unknown. Here, we aim to explore the driving mechanisms of outbreaks based on the one health perspective. Outbreak information for 20 types of airborne viral EIDs was collected from the Global Infectious Disease and Epidemiology Network database and a systematic literature review. Four statistically significant and high-risk spatiotemporal clusters for airborne viral EID outbreaks were identified globally using multivariate scan statistic tests. There were 112 outbreaks with clear infection sources, and zoonotic spillover was the most common source (95.54%, 107/112). Since 1970, the majority of outbreaks occurred in healthcare facilities (24.82%), followed by schools (17.93%) and animal-related settings (15.93%). Significant associations were detected between the number of earthquakes, storms, duration of floods, and airborne viral EIDs' outbreaks using a case-crossover study design and multivariable conditional logistic regression. These findings implied that zoonotic spillover and extreme weather events are driving global outbreaks of airborne viral EIDs, and targeted prevention and control measures should be made to reduce the airborne viral EIDs burden.

Virtual Scribes and Physician Time Spent on Electronic Health Records.

Importance: Time on the electronic health record (EHR) is associated with burnout among physicians. Newer virtual scribe models, which enable support from either a real-time or asynchronous scribe, have the potential to reduce the burden of the EHR and EHR-related documentation. Objective: To characterize the association of use of virtual scribes with changes in physicians' EHR time and note and order composition and to identify the physician, scribe, and scribe response factors associated with changes in EHR time upon virtual scribe use. Design, Setting, and Participants: Retrospective, pre-post quality improvement study of 144 physicians across specialties who had used a scribe for at least 3 months from January 2020 to September 2022, were affiliated with Brigham and Women's Hospital and Massachusetts General Hospital, and cared for patients in the outpatient setting. Data were analyzed from November 2022 to January 2024. Exposure: Use of either a real-time or asynchronous virtual scribe. Main Outcomes: Total EHR time, time on notes, and pajama time (5:30 pm to 7:00 am on weekdays and nonscheduled weekends and holidays), all per appointment; proportion of the note written by the physician and team contribution to orders. Results: The main study sample included 144 unique physicians who had used a virtual scribe for at least 3 months in 152 unique scribe participation episodes (134 [88.2%] had used an asynchronous scribe service). Nearly two-thirds of the physicians (91 physicians [63.2%]) were female and more than half (86 physicians [59.7%]) were in primary care specialties. Use of a virtual scribe was associated with significant decreases in total EHR time per appointment (mean [SD] of 5.6 [16.4] minutes; P < .001) in the 3 months after vs the 3 months prior to scribe use. Scribe use was also associated with significant decreases in note time per appointment and pajama time per appointment (mean [SD] of 1.3 [3.3] minutes; P < .001 and 1.1 [4.0] minutes; P = .004). In a multivariable linear regression model, the following factors were associated with significant decreases in total EHR time per appointment with a scribe use at 3 months: practicing in a medical specialty (-7.8; 95% CI, -13.4 to -2.2 minutes), greater baseline EHR time per appointment (-0.3; 95% CI, -0.4 to -0.2 minutes per additional minute of baseline EHR time), and decrease in the percentage of the note contributed by the physician (-9.1; 95% CI, -17.3 to -0.8 minutes for every percentage point decrease). Conclusions and Relevance: In 2 academic medical centers, use of virtual scribes was associated with significant decreases in total EHR time, time spent on notes, and pajama time, all per appointment. Virtual scribes may be particularly effective among medical specialists and those physicians with greater baseline EHR time.

Cell-Cycle-Specific Autoencoding Improves Cluster Analysis of Cycling Cardiomyocytes.

BACKGROUND: Our previous analyses of cardiomyocyte single-nucleus RNA sequencing (snRNAseq) data from the hearts of fetal pigs and pigs that underwent apical resection surgery on postnatal day (P) 1 (ARP1), myocardial infarction (MI) surgery on P28 (MIP28), both ARP1 and MIP28 (ARP1MIP28), or controls (no surgical procedure or CTL) identified 10 cardiomyocyte subpopulations (clusters), one of which appeared to be primed to proliferate in response to MI. However, the clusters composed of primarily proliferating cardiomyocytes still contained noncycling cells, and we were unable to distinguish between cardiomyocytes in different phases of the cell cycle. Here, we improved the precision of our assessments by conducting similar analyses with snRNAseq data for only the 1646 genes included under the Gene Ontology term "cell cycle." METHODS: Two cardiac snRNAseq datasets, one from mice (GEO dataset number GSE130699) and one from pigs (GEO dataset number GSE185289), were evaluated via our cell-cycle-specific analytical pipeline. Cycling cells were identified via the co-expression of 5 proliferation markers (AURKB, MKI67, INCENP, CDCA8, and BIRC5). RESULTS: The cell-cycle-specific autoencoder (CSA) algorithm identified 7 cardiomyocyte clusters in mouse hearts (mCM1 and mCM3-mCM8), including one prominent cluster of cycling cardiomyocytes in animals that underwent MI or Sham surgery on P1. Five cardiomyocyte clusters (pCM1, pCM3-pCM6) were identified in pig hearts, 2 of which (pCM1 and pCM4) displayed evidence of cell cycle activity; pCM4 was found primarily in hearts from fetal pigs, while pCM1 comprised a small proportion of cardiomyocytes in both fetal hearts and hearts from ARP1MIP28 pigs during the 2 weeks after MI induction, but was nearly undetectable in all other experimental groups and at all other time points. Furthermore, pseudotime trajectory analysis of snRNAseq data from fetal pig cardiomyocytes identified a pathway that began at pCM3, passed through pCM2, and ended at pCM1, whereas pCM3 was enriched for the expression of a cell cycle activator that regulates the G1/S phase transition (cyclin D2), pCM2 was enriched for an S-phase regulator (CCNE2), and pCM1 was enriched for the expression of a gene that regulates the G2M phase transition and mitosis (cyclin B2). We also identified 4 transcription factors (E2F8, FOXM1, GLI3, and RAD51) that were more abundantly expressed in cardiomyocytes from regenerative mouse hearts than from nonregenerative mouse hearts, from the hearts of fetal pigs than from CTL pig hearts, and from ARP1MIP28 pig hearts than from MIP28 pig hearts during the 2 weeks after MI induction. CONCLUSIONS: The CSA algorithm improved the precision of our assessments of cell cycle activity in cardiomyocyte subpopulations and enabled us to identify a trajectory across 3 clusters that appeared to track the onset and progression of cell cycle activity in cardiomyocytes from fetal pigs.

Lin28a cardiomyocyte-specific modified mRNA translation system induces cardiomyocyte cell division and cardiac repair.

The mammalian heart has a limited regenerative capacity. Previous work suggested the heart can regenerate during development and immediately after birth by inducing cardiomyocyte (CM) proliferation; however, this capacity is lost seven days after birth. modRNA gene delivery, the same technology used successfully in the two mRNA vaccines against SARS-CoV-2, can prompt cardiac regeneration, cardiovascular regeneration and cardiac protection. We recently established a novel CM-specific modRNA translational system (SMRTs) that allows modRNA translation only in CMs. We demonstrated that this system delivers potent intracellular genes (e.g., cell cyclepromoting Pkm2), which are beneficial when expressed in one cell type (i.e., CMs) but not others (non-CMs). Here, we identify Lin28a as an important regulator of the CM cell cycle. We show that Lin28a is expressed in CMs during development and immediately after birth, but not during adulthood. We describe that specific delivery of Lin28a into CM, using CM SMRTs, enables CM cell division and proliferation. Further, we determine that this proliferation leads to cardiac repair and better outcome post MI. Moreover, we identify the molecular pathway of Lin28a in CMs. We also demonstrate that Lin28a suppress Let-7 which is vital for CM proliferation, partially due to its suppressive role on cMYC, HMGA2 and K-RAS.

Detection of peach soluble solids based on near-infrared spectroscopy with High Order Spatial Interaction network.

BACKGROUND: Due to the scalability of deep learning technology, researchers have applied it to the non-destructive testing of peach internal quality. In addition, the soluble solids content (SSC) is an important internal quality indicator that determines the quality of peaches. Peaches with high SSC have a sweeter taste and better texture, making them popular in the market. Therefore, SSC is an important indicator for measuring peach internal quality and making harvesting decisions. RESULTS: This article presents the High Order Spatial Interaction Network (HOSINet), which combines the Position Attention Module (PAM) and Channel Attention Module (CAM). Additionally, a feature wavelength selection algorithm similar to the Group-based Clustering Subspace Representation (GCSR-C) is used to establish the Position and Channel Attention Module-High Order Spatial Interaction (PC-HOSI) model for peach SSC prediction. The accuracy of this model is compared with traditional machine learning and traditional deep learning models. Finally, the permutation algorithm is combined with deep learning models to visually evaluate the importance of feature wavelengths. Increasing the order of the PC-HOSI model enhances its ability to learn spatial correlations in the dataset, thus improving its predictive performance. CONCLUSION: The optimal model, PC-HOSI model, performed well with an order of 3 (PC-HOSI-3), with a root mean square error of 0.421 °Brix and a coefficient of determination of 0.864. Compared with traditional machine learning and deep learning algorithms, the coefficient of determination for the prediction set was improved by 0.07 and 0.39, respectively. The permutation algorithm also provided interpretability analysis for the predictions of the deep learning model, offering insights into the importance of spectral bands. These results contribute to the accurate prediction of SSC in peaches and support research on interpretability of neural network models for prediction. © 2024 Society of Chemical Industry.

Proformer: a hybrid macaron transformer model predicts expression values from promoter sequences.

The breakthrough high-throughput measurement of the cis-regulatory activity of millions of randomly generated promoters provides an unprecedented opportunity to systematically decode the cis-regulatory logic that determines the expression values. We developed an end-to-end transformer encoder architecture named Proformer to predict the expression values from DNA sequences. Proformer used a Macaron-like Transformer encoder architecture, where two half-step feed forward (FFN) layers were placed at the beginning and the end of each encoder block, and a separable 1D convolution layer was inserted after the first FFN layer and in front of the multi-head attention layer. The sliding k-mers from one-hot encoded sequences were mapped onto a continuous embedding, combined with the learned positional embedding and strand embedding (forward strand vs. reverse complemented strand) as the sequence input. Moreover, Proformer introduced multiple expression heads with mask filling to prevent the transformer models from collapsing when training on relatively small amount of data. We empirically determined that this design had significantly better performance than the conventional design such as using the global pooling layer as the output layer for the regression task. These analyses support the notion that Proformer provides a novel method of learning and enhances our understanding of how cis-regulatory sequences determine the expression values.

Promoting cardiomyocyte proliferation for myocardial regeneration in large mammals.

From molecular and cellular perspectives, heart failure is caused by the loss of cardiomyocytes-the fundamental contractile units of the heart. Because mammalian cardiomyocytes exit the cell cycle shortly after birth, the cardiomyocyte damage induced by myocardial infarction (MI) typically leads to dilatation of the left ventricle (LV) and often progresses to heart failure. However, recent findings indicate that the hearts of neonatal pigs completely regenerated the cardiomyocytes that were lost to MI when the injury occurred on postnatal day 1 (P1). This recovery was accompanied by increases in the expression of markers for cell-cycle activity in cardiomyocytes. These results suggest that the repair process was driven by cardiomyocyte proliferation. This review summarizes findings from recent studies that found evidence of cardiomyocyte proliferation in 1) the uninjured hearts of newborn pigs on P1, 2) neonatal pig hearts after myocardial injury on P1, and 3) the hearts of pigs that underwent apical resection surgery (AR) on P1 followed by MI on postnatal day 28 (P28). Analyses of cardiomyocyte single-nucleus RNA sequencing data collected from the hearts of animals in these three experimental groups, their corresponding control groups, and fetal pigs suggested that although the check-point regulators and other molecules that direct cardiomyocyte cell-cycle progression and proliferation in fetal, newborn, and postnatal pigs were identical, the mechanisms that activated cardiomyocyte proliferation in response to injury may differ from those that regulate cardiomyocyte proliferation during development.

Grand Challenges at the Interface of Engineering and Medicine.

Over the past two decades Biomedical Engineering has emerged as a major discipline that bridges societal needs of human health care with the development of novel technologies. Every medical institution is now equipped at varying degrees of sophistication with the ability to monitor human health in both non-invasive and invasive modes. The multiple scales at which human physiology can be interrogated provide a profound perspective on health and disease. We are at the nexus of creating "avatars" (herein defined as an extension of "digital twins") of human patho/physiology to serve as paradigms for interrogation and potential intervention. Motivated by the emergence of these new capabilities, the IEEE Engineering in Medicine and Biology Society, the Departments of Biomedical Engineering at Johns Hopkins University and Bioengineering at University of California at San Diego sponsored an interdisciplinary workshop to define the grand challenges that face biomedical engineering and the mechanisms to address these challenges. The Workshop identified five grand challenges with cross-cutting themes and provided a roadmap for new technologies, identified new training needs, and defined the types of interdisciplinary teams needed for addressing these challenges. The themes presented in this paper include: 1) accumedicine through creation of avatars of cells, tissues, organs and whole human; 2) development of smart and responsive devices for human function augmentation; 3) exocortical technologies to understand brain function and treat neuropathologies; 4) the development of approaches to harness the human immune system for health and wellness; and 5) new strategies to engineer genomes and cells.

Scleroglucan protects the intestine from irradiation-induced injury by targeting the IL-17 signaling pathway.

BACKGROUND: Intestinal tissue is extremely sensitive to ionizing radiation (IR), which is easy to cause intestinal radiation sickness, and the mortality rate is very high after exposure. Recent studies have found that intestinal immune cells and intestinal stem cells (ISCs) may play a key role in IR-induced intestinal injury. METHODS: C57BL6 mice matched for age, sex and weight were randomly grouped and intraperitoneal injected with PBS, Scleroglucan (125.0 mg/kg) or Anti-mouse IL-17A -InVivo (10 mg/kg), the number of mice in each group was n ≥ 3.Survival time, body weight, pathology, organoids and immune cell markers of the mice after IR (10.0 Gy) were compared, and the mechanism of action in intestinal tissues was verified by transcriptome sequencing. RESULTS: Scleroglucan has significant radiation protective effects on the intestine, including improving the survival rate of irradiated mice, inhibiting the radiation damage of intestinal tissue, and promoting the proliferation and differentiation of intestinal stem cells (ISCs). The results of RNA sequencing suggested that Scleroglucan could significantly activate the immune system and up-regulate the IL-17 and NF-κB signaling pathways. Flow cytometry showed that Scleroglucan could significantly up-regulate the number of Th17 cells and the level of IL-17A in the gut. IL-17A provides radiation protection. After intraperitoneal injection of Scleroglucan and Anti-mouse IL-17A -InVivo, mice can significantly reverse the radiation protection effect of Scleroglucan, down-regulate the molecular markers of intestinal stem cells and the associated markers of DC, Th1 and Th17 cells, and up-regulate the associated markers of Treg and Macrophage cells. CONCLUSION: Scleroglucan may promote the proliferation and regeneration of ISCs by regulating the activation of intestinal immune function mediated by IL-17 signaling pathway and play a protective role in IR-induced injury.

GAN-based medical image small region forgery detection via a two-stage cascade framework.

Using generative adversarial network (GAN) Goodfellow et al. (2014) for data enhancement of medical images is significantly helpful for many computer-aided diagnosis (CAD) tasks. A new GAN-based automated tampering attack, like CT-GAN Mirsky et al. (2019), has emerged. It can inject or remove lung cancer lesions to CT scans. Because the tampering region may even account for less than 1% of the original image, even state-of-the-art methods are challenging to detect the traces of such tampering. This paper proposes a two-stage cascade framework to detect GAN-based medical image small region forgery like CT-GAN. In the local detection stage, we train the detector network with small sub-images so that interference information in authentic regions will not affect the detector. We use depthwise separable convolution and residual networks to prevent the detector from over-fitting and enhance the ability to find forged regions through the attention mechanism. The detection results of all sub-images in the same image will be combined into a heatmap. In the global classification stage, using gray-level co-occurrence matrix (GLCM) can better extract features of the heatmap. Because the shape and size of the tampered region are uncertain, we use hyperplanes in an infinite-dimensional space for classification. Our method can classify whether a CT image has been tampered and locate the tampered position. Sufficient experiments show that our method can achieve excellent performance than the state-of-the-art detection methods.

Experimental analysis of low-dip reverse fault dislocation effects on tunnel site models with different soil properties.

The fortification system of the tunnel structure spanning the active fault, such as the failure mechanism and fault-resistant design (measures), has not been thoroughly established. In this study, the self-developed cross-fault large-scale bedrock dislocation loading device platform is utilized to carry out the model test of the tunnel structure and soil site of sand and cohesive soil when the low-angle reverse fault dislocation occurs, based on the earthquake damage. The results demonstrate that: (1) When the fault is staggered, the segmented flexible joint tunnel segment is more favorable in the cohesive soil site. (2) When compared to the cohesive soil tunnel structure site, the strain change of the tunnel structure in the sandy soil site is greater, with the vault increasing by roughly two times and the arch bottom increasing by nearly six times. After the tunnel is buried, the uplift range of the sand cover layer grows, revealing uneven deformation, and the rupture zone migrates to the footwall; hence, the sand site plays a "add seismic" role in the cross-fault tunnel structure. (3) Knowing the location and shape of the rupture range of the overburden soil caused by bedrock dislocation under different inclination angles and soil properties is required in the design in order to place the buried depth and segment length of the tunnel reasonably and take fault-resistant measures.

How prices and income influence global patterns in saturated fat intake by age, sex and world region: a cross-sectional analysis of 160 countries.

OBJECTIVE: When considering proposals to improve diets, it is important to understand how factors like price and income can affect saturated fat (SF) intake and demand. In this study, we examine and estimate the influence of price and income on intake across 160 countries, by age and sex, and derive sensitivity measures (price elasticities) that vary by age, sex and world region. DESIGN: We econometrically estimate intake responsiveness to income and prices across countries, accounting for differences by world region, age and sex. Intake data by age, sex and country were obtained from the 2018 Global Dietary Database. These data were then linked to global price data for select food groups from the World Bank International Comparison Programme and income data from the World Development Indicators Databank (World Bank). RESULTS: Intake differences due to price were highly significant, with a 1% increase in price associated with a lower SF intake (% energy/d) of about 4.3 percentage points. We also find significant differences across regions. In high-income countries, median (age 40) intake reductions were 1.4, 0.8 and 0.2 percentage points, given a 1% increase in the price of meat, dairy, and oils and fats, respectively. Price elasticities varied with age but not sex. Intake differences due to income were insignificant when regional binary variables were included in the analysis. CONCLUSION: The results of this study show heterogeneous associations among prices and intake within and across countries. Policymakers should consider these heterogeneous effects as they address global nutrition and health challenges.

An image-driven micromechanical approach to characterize multiscale remodeling in infarcted myocardium.

Myocardial infarction (MI) is accompanied by the formation of a fibrotic scar in the left ventricle (LV) and initiates significant alterations in the architecture and constituents of the LV free wall (LVFW). Previous studies have shown that LV adaptation is highly individual, indicating that the identification of remodeling mechanisms post-MI demands a fully subject-specific approach that can integrate a host of structural alterations at the fiber-level to changes in bulk biomechanical adaptation at the tissue-level. We present an image-driven micromechanical approach to characterize remodeling, assimilating new biaxial mechanical data, histological studies, and digital image correlation data within an in-silico framework to elucidate the fiber-level remodeling mechanisms that drive tissue-level adaptation for each subject. We found that a progressively diffused collagen fiber structure combined with similarly disorganized myofiber architecture in the healthy region leads to the loss of LVFW anisotropy post-MI, offering an important tissue-level hallmark for LV maladaptation. In contrast, our results suggest that reductions in collagen undulation are an adaptive mechanism competing against LVFW thinning. Additionally, we show that the inclusion of subject-specific geometry when modeling myocardial tissue is essential for accurate prediction of tissue kinematics. Our approach serves as an essential step toward identifying fiber-level remodeling indices that govern the transition of MI to systolic heart failure. These indices complement the traditional, organ-level measures of LV anatomy and function that often fall short of early prognostication of heart failure in MI. In addition, our approach offers an integrated methodology to advance the design of personalized interventions, such as hydrogel injection, to reinforce and suppress native adaptive and maladaptive mechanisms, respectively, to prevent the transition of MI to heart failure. STATEMENT OF SIGNIFICANCE: Biomechanical and architectural adaptation of the LVFW remains a central, yet overlooked, remodeling process post-MI. Our study indicates the biomechanical adaptation of the LVFW post-MI is highly individual and driven by altered fiber network architecture and collective changes in collagen fiber content, undulation, and stiffness. Our findings demonstrate the possibility of using cardiac strains to infer such fiber-level remodeling events through in-silico modeling, paving the way for in-vivo characterization of multiscale biomechanical indices in humans. Such indices will complement the traditional, organ-level measures of LV anatomy and function that often fall short of early prognostication of heart failure in MI.

Authentication of apples from the Loess Plateau in China based on interannual element fingerprints and multidimensional modelling.

Apple is an important fruit, and fruit authentication is significant for quality and safety control. The Loess Plateau (LP) in China is an important apple-producing region. However, the geographic authentication of LP apples has not been well studied. In this study, we discriminated LP apples based on multielement analysis. We analysed the differences in 29 elements of 522 samples collected from LP and others in 2018-2020 and constructed discriminant models for LP apple authentication. Linear discriminant analysis, partial least square-discriminant analysis, back-propagation artificial neural networks, and random forest (RF) showed different rates in training and validation accuracy. RF showed better tolerance to the removal of the less-important elements in model optimization. The final RF was optimized on 11 elements, which obtained 95.30% training accuracy for the 2018-2019 samples and 97.29% validation accuracy for the 2020 samples. The multielement-based authentication of LP apples could aid further studies of geographical origins.