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Abstract Background Gastric cancer (GC), a molecularly heterogeneous disease, is the third leading cause of cancer death worldwide. The majority of GC cases worldwide occur in East Asia, predominantly China. Mutational Signature Framework offers an elegant approach to identify mutational processes present in tumors. Methods To identify mutational signature patterns, we conducted whole exome sequencing (WES) analysis in Chinese patients with GC. Mutect2 and MutsigCV were used to identify significantly mutated genes in 175 Chinese GC cases using paired tumor-normal tissues. We investigated mutational signatures using Catalogue of Somatic Mutations in Cancer (COSMIC) Version 2 (V2) and Version 3 (V3). Results We identified 104 mutated genes with P

Abstract During summer, ammonia emissions in Southeast Asia influence air pollution and cloud formation. Convective transport by the South Asian monsoon carries these pollutant air masses into the upper troposphere and lower stratosphere (UTLS), where they accumulate under anticyclonic flow conditions. This air mass accumulation is thought to contribute to particle formation and the development of the Asian Tropopause Aerosol Layer (ATAL). Despite the known influence of ammonia and particulate ammonium on air pollution, a comprehensive understanding of the ATAL is lacking. In this modelling study, the influence of ammonia on particle formation is assessed with emphasis on the ATAL. We use the EMAC chemistry-climate model, incorporating new particle formation parameterisations derived from experiments at the CERN CLOUD chamber. Our diurnal cycle analysis confirms that new particle formation mainly occurs during daylight, with a 10-fold enhancement in rate. This increase is prominent in the South Asian monsoon UTLS, where deep convection introduces high ammonia levels from the boundary layer, compared to a baseline scenario without ammonia. Our model simulations reveal that this ammonia-driven particle formation and growth contributes to an increase of up to 80% in cloud condensation nuclei (CCN) concentrations at cloud-forming heights in the South Asian monsoon region. We find that ammonia profoundly influences the aerosol mass and composition in the ATAL through particle growth, as indicated by an order of magnitude increase in nitrate levels linked to ammonia emissions. However, the effect of ammonia-driven new particle formation on aerosol mass in the ATAL is relatively small. Ammonia emissions enhance the regional aerosol optical depth (AOD) for shortwave solar radiation by up to 70%. We conclude that ammonia has a pronounced effect on the ATAL development, composition, the regional AOD, and CCN concentrations.

Abstract A highly sensitive and multi-functional pressure sensor capable of continuous pressure readings is greatly needed, particularly for precise gait pattern analysis. Here, we fabricate a sensitive and reliable pressure sensor by employing eutectic gallium indium (EGaIn) liquid metal as the sensing material and EcoFlex 00-30 silicone as the substrate, via a low-cost process. The device architecture features a microchannel, creating two independent sensing devices, and the mechanical properties of the substrate and sensing material contribute to high stretchability and flexibility, resulting in a sensitivity of 66.07 MPa−1 and a low measurement resolution of 0.056 kPa. The sensor detects applied pressure accurately and can distinguish pressure distribution across a wide area. We demonstrate high efficiency for monitoring human walking gait at various speeds when a single sensor is attached to the foot, and can differentiate between walking postures. This device has strong potential for clinical and rehabilitation applications in gait analysis.

Abstract Background Identification of potential drug-target interactions (DTIs) with high accuracy is a key step in drug discovery and repositioning, especially concerning specific drug targets. Traditional experimental methods for identifying the DTIs are arduous, time-intensive, and financially burdensome. In addition, robust computational methods have been developed for predicting the DTIs and are widely applied in drug discovery research. However, advancing more precise algorithms for predicting DTIs is essential to meet the stringent standards demanded by drug discovery. Results We proposed a novel method called GSRF-DTI, which integrates networks with a deep learning algorithm to identify DTIs. Firstly, GSRF-DTI learned the embedding representation of drugs and targets by integrating multiple drug association information and target association information, respectively. Then, GSRF-DTI considered the influence of drug-target pair (DTP) association on DTI prediction to construct a drug-target pair network (DTP-NET). Next, we utilized GraphSAGE on DTP-NET to learn the potential features of the network and applied random forest (RF) to predict the DTIs. Furthermore, we conducted ablation experiments to validate the necessity of integrating different types of network features for identifying DTIs. It is worth noting that GSRF-DTI proposed three novel DTIs. Conclusions GSRF-DTI not only considered the influence of the interaction relationship between drug and target but also considered the impact of DTP association relationship on DTI prediction. We initially use GraphSAGE to aggregate the neighbor information of nodes for better identification. Experimental analysis on Luo’s dataset and the newly constructed dataset revealed that the GSRF-DTI framework outperformed several state-of-the-art methods significantly.

Abstract Arterial stiffening is a critical risk factor contributing to the exponential rise in age‐associated cardiovascular disease incidence. This process involves age‐induced arterial proinflammation, collagen deposition, and calcification, which collectively contribute to arterial stiffening. The primary driver of proinflammatory processes leading to collagen deposition in the arterial wall is the transforming growth factor‐beta1 (TGF‐β1) signaling. Activation of this signaling is pivotal in driving vascular extracellular remodeling, eventually leading to arterial fibrosis and calcification. Interestingly, the glycosylated protein vasorin (VASN) physically interacts with TGF‐β1, and functionally restraining its proinflammatory fibrotic signaling in arterial walls and vascular smooth muscle cells (VSMCs). Notably, as age advances, matrix metalloproteinase type II (MMP‐2) is activated, which effectively cleaves VASN protein in both arterial walls and VSMCs. This age‐associated/MMP‐2‐mediated decrease in VASN levels exacerbates TGF‐β1 activation, amplifying arterial fibrosis and calcification in the arterial wall. Importantly, TGF‐β1 is a downstream molecule of the angiotensin II (Ang II) signaling pathway in the arterial wall and VSMCs, which is modulated by VASN. Indeed, chronic administration of Ang II to young rats significantly activates MMP‐2 and diminishes the VASN expression to levels comparable to untreated older control rats. This review highlights and discusses the role played by VASN in mitigating fibrosis and calcification by alleviating TGF‐β1 activation and signaling in arterial walls and VSMCs. Understanding these molecular physical and functional interactions may pave the way for establishing VASN‐based therapeutic strategies to counteract adverse age‐associated cardiovascular remodeling, eventually reducing the risk of cardiovascular diseases.

In-vivo flow cytometry is a noninvasive real-time diagnostic technique that facilitates continuous monitoring of cells without perturbing their natural biological environment, which renders it a valuable tool for both scientific research and clinical applications. However, the conventional approach for improving classification accuracy often involves labeling cells with fluorescence, which can lead to potential phototoxicity. This study proposes a label-free in-vivo flow cytometry technique, called dynamic YOLOv4 (D-YOLOv4), which improves classification accuracy by integrating absorption intensity fluctuation modulation (AIFM) into YOLOv4 to demodulate the temporal features of moving red blood cells (RBCs) and platelets. Using zebrafish as an experimental model, the D-YOLOv4 method achieved average precisions (APs) of 0.90 for RBCs and 0.64 for thrombocytes (similar to platelets in mammals), resulting in an overall AP of 0.77. These scores notably surpass those attained by alternative network models, thereby demonstrating that the combination of physical models with neural networks provides an innovative approach toward developing label-free in-vivo flow cytometry, which holds promise for diverse in-vivo cell classification applications.

Abstract Background Due to its enormous biomass, Antarctic krill (Euphausia superba) plays a crucial role in the Antarctic Ocean ecosystem. In recent years, Antarctic krill has found extensive application in aquaculture, emerging as a sustainable source of aquafeed with ideal nutritional profiles. However, a comprehensive study focused on the detailed effects of dietary Antarctic krill on aquaculture animals, especially farmed marine fishes, is yet to be demonstrated. Results In this study, a comparative experiment was performed using juvenile P. leopardus, fed with diets supplemented with Antarctic krill (the krill group) or without Antarctic krill (the control group). Histological observation revealed that dietary Antarctic krill could reduce lipid accumulation in the liver while the intestine exhibited no obvious changes. Enzyme activity measurements demonstrated that dietary Antarctic krill had an inhibitory effect on oxidative stress in both the intestine and the liver. By comparative transcriptome analysis, a total of 1,597 and 1,161 differentially expressed genes (DEGs) were identified in the intestine and liver, respectively. Functional analysis of the DEGs showed multiple enriched terms significantly related to cholesterol metabolism, antioxidants, and immunity. Furthermore, the expression profiles of representative DEGs, such as dhcr7, apoa4, sc5d, and scarf1, were validated by qRT-PCR and fluorescence in situ hybridization. Finally, a comparative transcriptome analysis was performed to demonstrate the biased effects of dietary Antarctic krill and astaxanthin on the liver of P. leopardus. Conclusions Our study demonstrated that dietary Antarctic krill could reduce lipid accumulation in the liver of P. leopardus, enhance antioxidant capacities in both the intestine and liver, and exhibit molecular-level improvements in lipid metabolism, immunity, and antioxidants. It will contribute to understanding the protective effects of Antarctic krill in P. leopardus and provide insights into aquaculture nutritional strategies.

Although adaptive cancer therapy shows promise in integrating evolutionary dynamics into treatment scheduling, the stochastic nature of cancer evolution has seldom been taken into account. Various sources of random perturbations can impact the evolution of heterogeneous tumors, making performance metrics of any treatment policy random as well. In this paper, we propose an efficient method for selecting optimal adaptive treatment policies under randomly evolving tumor dynamics. The goal is to improve the cumulative "cost" of treatment, a combination of the total amount of drugs used and the total treatment time. As this cost also becomes random in any stochastic setting, we maximize the probability of reaching the treatment goals (tumor stabilization or eradication) without exceeding a pre-specified cost threshold (or a "budget"). We use a novel Stochastic Optimal Control formulation and Dynamic Programming to find such "threshold-aware" optimal treatment policies. Our approach enables an efficient algorithm to compute these policies for a range of threshold values simultaneously. Compared to treatment plans shown to be optimal in a deterministic setting, the new "threshold-aware" policies significantly improve the chances of the therapy succeeding under the budget, which is correlated with a lower general drug usage. We illustrate this method using two specific examples, but our approach is far more general and provides a new tool for optimizing adaptive therapies based on a broad range of stochastic cancer models.

Utilizing image-based computer vision techniques, many high-throughput phenotyping methods have been employed to capture intricate growth trait characteristics, offering reliable estimates of phenotypic traits crucial for breeding programs. In this study, we explored the application of partial differential equation (PDE)-based level set approaches to introduce image-based body area percentage (IBAP) as a novel growth trait in Plectropomus leopardus, as a substitution for the traditional growth trait body weight (BW). Assessing the genetic parameters essential for robust growth trait improvement in P. leopardus breeding programs, we estimated SNP-based heritability for IBAP and BW using a comprehensive set of SNPs (673,039 SNPs with MAF >2%). Results revealed heritability estimates of 0.515 (S.E. 0.06) for IBAP and 0.542 (S.E. 0.06) for BW. Moreover, strong phenotypic and genetic correlations of 0.812 (S.E. 0.001) and 0.903 (S.E 0.021) between IBAP and BW, respectively, underscored the potential for IBAP as a surrogate trait of BW for the genetic improvement of P. leopardus. We established a linear regression model of IBAP and BW (y ​= ​−730 ​+ ​1700×, (R2 ​= ​0.71)), after rigorous assessments of linearity, normality, and homoscedasticity, to confirm model fit. Evaluation of breeding value prediction accuracies using two linear models (rr-GBLUP and Bayes B) and a non-linear (RKHS) model demonstrated the superior performance of RKHS across IBAP and BW. Exploring the impact of varied marker densities for SNP selection on genomic prediction accuracy for IBAP and BW demonstrated a threshold of 10,000 SNPs for maximal model accuracy. These findings provide essential reference information and methodological groundwork for leveraging image-based traits in P. leopardus breeding endeavors, facilitating more efficient and precise genetic improvement programs.

Cancer development is driven by an accumulation of a small number of driver genetic mutations that confer the selective growth advantage to the cell, while most passenger mutations do not contribute to tumor progression. The identification of these driver genes responsible for tumorigenesis is a crucial step in designing effective cancer treatments. Although many computational methods have been developed with this purpose, the majority of existing methods solely provided a single driver gene list for the entire cohort of patients, ignoring the high heterogeneity of driver events across patients. It remains challenging to identify the personalized driver genes. Here, we propose a novel method (PDRWH), which aims to prioritize the mutated genes of a single patient based on their impact on the abnormal expression of downstream genes across a group of patients who share the co-mutation genes and similar gene expression profiles. The wide experimental results on 16 cancer datasets from TCGA showed that PDRWH excels in identifying known general driver genes and tumor-specific drivers. In the comparative testing across five cancer types, PDRWH outperformed existing individual-level methods as well as cohort-level methods. Our results also demonstrated that PDRWH could identify both common and rare drivers. The personalized driver profiles could improve tumor stratification, providing new insights into understanding tumor heterogeneity and taking a further step toward personalized treatment. We also validated one of our predicted novel personalized driver genes on tumor cell proliferation by vitro cell-based assays, the promoting effect of the high expression of Low-density lipoprotein receptor-related protein 1 (LRP1) on tumor cell proliferation.

Abstract Relativistic Weyl fermion quasiparticles in Weyl semimetal bring the electron’s chirality degree of freedom into the electrical transport and give rise to exotic phenomena. A topological phase transition from a topological trivial phase to a topological non-trivial phase offers a route to control electronic devices through its topological properties. Here, we report the Weyl semimetal phase in hydrothermally grown two-dimensional Tellurium (2D Te) induced by high hydrostatic pressure (up to 2.47 GPa). The unique chiral crystal structure gives rise to chiral fermions with different topological chiral charges ( $${{C}}=-{{1}},+{{1}},{{and}}-{{2}}$$ C = − 1 , + 1 , a n d − 2 ). The highly tunable chemical potential in 2D Te provides comprehensive information for understanding the pressure-dependent electron band structure. The pressure-induced insulator-to-metal transition, two-carrier transport, and the non-trivial π Berry phase shift in quantum oscillations are observed in the 2D Te Weyl semimetal phase. Our work demonstrates the pressure-induced bandgap closing in the inversion asymmetric narrow bandgap semiconductor 2D Te.

High spatial resolution (HSR) remote sensing imagery presents a rich tapestry of foreground-background intricacies, rendering semantic segmentation in aerial contexts a formidable and vital undertaking. At its core, this challenge revolves around two pivotal questions: 1) Mitigating Background Interference and Enhancing Foreground Clarity. 2) Accurate Segmentation in Dense Small Object Cluster. Conventional semantic segmentation methods primarily cater to the segmentation of large-scale objects in natural scenes, yet they often falter when confronted with aerial imagery’s characteristic traits such as vast background areas, diminutive foreground objects, and densely clustered targets. In response, we propose a novel semantic segmentation framework tailored to overcome these obstacles. To address the first challenge, we leverage PointFlow modules in tandem with the Foreground-Scene (F-S) module. PointFlow modules act as a barrier against extraneous background information, while the F-S module fosters a symbiotic relationship between the scene and foreground, enhancing clarity. For the second challenge, we adopt a dual-branch structure termed disentangled learning, comprising Foreground Precedence Estimation and Small Object Edge Alignment (SOEA). Our foreground saliency guided loss optimally directs the training process by prioritizing foreground examples and challenging background instances. Extensive experimentation on the iSAID and Vaihingen datasets validates the efficacy of our approach. Not only does our method surpass prevailing generic semantic segmentation techniques, but it also outperforms state-of-the-art remote sensing segmentation methods.

Abstract The interaction between nitrogen monoxide (NO) and organic peroxy radicals (RO2) greatly impacts the formation of highly oxygenated organic molecules (HOM), the key precursors of secondary organic aerosols. It has been thought that HOM production can be significantly suppressed by NO even at low concentrations. Here, we perform dedicated experiments focusing on HOM formation from monoterpenes at low NO concentrations (0 – 82 pptv). We demonstrate that such low NO can enhance HOM production by modulating the RO2 loss and favoring the formation of alkoxy radicals that can continue to autoxidize through isomerization. These insights suggest that HOM yields from typical boreal forest emissions can vary between 2.5%-6.5%, and HOM formation will not be completely inhibited even at high NO concentrations. Our findings challenge the notion that NO monotonically reduces HOM yields by extending the knowledge of RO2-NO interactions to the low-NO regime. This represents a major advance towards an accurate assessment of HOM budgets, especially in low-NO environments, which prevails in the pre-industrial atmosphere, pristine areas, and the upper boundary layer.

To ensure precise positioning of the macro–micro platform with a symmetrical structure, it is crucial to mitigate the impact of various perturbations, including disturbances, as well as complex factors such as external loads, electrical noise, and model parameter variations. This paper proposes a novel macro–micro master–slave control structure that incorporates adaptive fuzzy linear active disturbance rejection control (AFLADRC). The Kp and Kd parameters of the linear state error feedback (LSEF) are dynamically tuned and adjusted using fuzzy reasoning. This approach enhances the robustness of the system and simplifies the tuning process. In addition, this paper also analyzes the symmetry of the coupling effect between macro and micro, as the coupling will affect the motor force and the reaction potential of the motor. The macro–micro platform adopts a symmetric design; the macro stage is driven by a permanent magnet synchronous linear motor (PMLSM), and the micro stage is driven by a voice coil motor. Finally, we built the macro–micro linear motion experimental platform to verify the control effect of the proposed method by conducting trajectory tracking experiments and comparison experiments.

Abstract Plectropomus leopardus, as known as leopard coral grouper, is a valuable marine fish that has gradually been bred artificially. To promote future conservation, molecular breeding, and comparative studies, we generated an improved high-quality chromosomal-level genome assembly of leopard coral grouper using Nanopore long-reads, Illumina short reads, and the Hi-C sequencing data. The draft genome is 849.74 Mb with 45 contigs and N50 of 35.59 Mb. Finally, a total of 846.49 Mb corresponding to 99.6% of the contig sequences was anchored to 24 pseudo-chromosomes using Hi-C technology. A final set of 25,965 genes is annotated after manual curation of the predicted gene models, and BUSCO analysis yielded a completeness score of 99.5%. This study significantly improves the utility of the grouper genome and provided a reference for the study of molecular breeding, genomics and biology in this species.

CO2 carboxylation is an important and attractive way of CO2 resourceful utilization, which could synthesize carboxylic acids. As the most promising alternative to terephthalic acid, 2,5-furandicarboxylic acid (FDCA) could be produced by direct carboxylation of the biomass-derived 2-furoic acid (FA) and CO2 promoted by Cs2CO3, but the high cost of cesium limits the development of the route. Herein, low-cost K2CO3 was only used to promote the carboxylation of FA and CO2 for the synthesis of FDCA, whose feasibility was demonstrated by theoretical calculations and experiments. However, the reaction system was strongly influenced by temperature only using K2CO3. The addition of low-cost HCOOK could effectively decrease the reaction temperature, and thus enhance the practicality of the reaction system. Based on experimental and theoretical simulations, it was revealed that the addition of HCOOK not only significantly lowered the melting temperature of the reaction system, but also effectively reduced the activation energy barrier of the hydrogen capture step. The investigation would provide potentiality for a large production of FDCA.

Senescent vascular smooth muscle cells (VSMCs) accumulate in the vasculature with age and tissue damage and secrete factors that promote atherosclerotic plaque vulnerability and disease. Here, we report increased levels and activity of dipeptidyl peptidase 4 (DPP4), a serine protease, in senescent VSMCs. Analysis of the conditioned media from senescent VSMCs revealed a unique senescence-associated secretory phenotype (SASP) signature comprising many complement and coagulation factors; silencing or inhibiting DPP4 reduced these factors and increased cell death. Serum samples from persons with high risk for cardiovascular disease contained high levels of DPP4-regulated complement and coagulation factors. Importantly, DPP4 inhibition reduced senescent cell burden and coagulation and improved plaque stability, while single-cell resolution of senescent VSMCs reflected the senomorphic and senolytic effects of DPP4 inhibition in murine atherosclerosis. We propose that DPP4-regulated factors could be exploited therapeutically to reduce senescent cell function, reverse senohemostasis, and improve vascular disease.

The study of circulating cells in the blood stream is critical, as it covers many fields of biomedicine, including immunology, cell biology, oncology, and reproductive medicine. In-vivo flow cytometry (IVFC) is a new tool to monitor and count cells in real time for long durations in their native biological environment. This review describes two main categories of IVFC, i.e., labeled and label-free IVFC. It focuses on label-free IVFC and introduces its technological development and related biological applications. Because cell recognition is the basis of flow cytometry counting, this review also describes various methods for the classification of unlabeled cells, including the latest machine learning-based technologies.

Objective. To determine the exposure to aflatoxin B1 (AFB1) in southern Mexico and the presence of the aflatoxin signature mutation in hepatocellular carcinoma (HCC) tissue from patients from a cancer referral center. Materials and methods. We estimated the prevalence and distribution of AFB1 in a representative sample of 100 women and men from Chiapas using the National Health and Nutrition Survey 2018-19. We also examined the presence of the aflatoxin signature mutation in codon 249 (R249S), and other relevant mutations of the TP53 gene in HCC tissue blocks from 24 women and 26 men treated in a national cancer referral center. Results. The prevalence of AFB1 in serum samples was 85.5% (95%CI 72.1-93.1) and the median AFB1 was 0.117 pg/μL (IQR, 0.050–0.350). We detected TP53 R249S in three of the 50 HCCs (6.0%) and observed four other G>T transversions potentially induced by AFB1. Conclusion. Our analysis provides evidence that AFB1 may have a relevant role on HCC etiology in Mexico.

Because the breast cancer is an important factor that threatens women’s lives and health, early diagnosis is helpful for disease screening and a good prognosis. Exosomes are nanovesicles, secreted from cells and other body fluids, which can reflect the genetic and phenotypic status of parental cells. Compared with other methods for early diagnosis of cancer (such as circulating tumor cells (CTCs) and circulating tumor DNA), exosomes have a richer number and stronger biological stability, and have great potential in early diagnosis. Thus, it has been proposed as promising biomarkers for diagnosis of early-stage cancer. However, distinguishing different exosomes remain is a major biomedical challenge. In this paper, we used predictive Convolutional Neural model to detect and analyze exosomes of normal and cancer cells with surface-enhanced Raman scattering (SERS). As a result, it can be seen from the SERS spectra that the exosomes of MCF-7, MDA-MB-231 and MCF-10A cells have similar peaks (939, 1145 and 1380 cm[Formula: see text]). Based on this dataset, the predictive model can achieve 95% accuracy. Compared with principal component analysis (PCA), the trained CNN can classify exosomes from different breast cancer cells with a superior performance. The results indicate that using the sensitivity of Raman detection and exosomes stable presence in the incubation period of cancer cells, SERS detection combined with CNN screening may be used for the early diagnosis of breast cancer in the future.

The use of publicly available sequencing datasets as controls (hereafter, "public controls") in studies of rare variant disease associations has great promise but can increase the risk of false-positive discovery. The specific factors that could contribute to inflated distribution of test statistics have not been systematically examined. Here, we leveraged both public controls, gnomAD v2.1 and several datasets sequenced in our laboratory to systematically investigate factors that could contribute to the false-positive discovery, as measured by λΔ95, a measure to quantify the degree of inflation in statistical significance. Analyses of datasets in this investigation found that 1) the significantly inflated distribution of test statistics decreased substantially when the same variant caller and filtering pipelines were employed, 2) differences in library prep kits and sequencers did not affect the false-positive discovery rate and, 3) joint vs. separate variant-calling of cases and controls did not contribute to the inflation of test statistics. Currently available methods do not adequately adjust for the high false-positive discovery. These results, especially if replicated, emphasize the risks of using public controls for rare-variant association tests in which individual-level data and the computational pipeline are not readily accessible, which prevents the use of the same variant-calling and filtering pipelines on both cases and controls. A plausible solution exists with the emergence of cloud-based computing, which can make it possible to bring containerized analytical pipelines to the data (rather than the data to the pipeline) and could avert or minimize these issues. It is suggested that future reports account for this issue and provide this as a limitation in reporting new findings based on studies that cannot practically analyze all data on a single pipeline.

BackgroundAging is associated with increased levels of reactive oxygen species and inflammation that disrupt proteostasis and mitochondrial function and leads to organism-wide frailty later in life. ARA290 (cibinetide), an 11-aa non-hematopoietic peptide sequence within the cardioprotective domain of erythropoietin, mediates tissue protection by reducing inflammation and fibrosis. Age-associated cardiac inflammation is linked to structural and functional changes in the heart, including mitochondrial dysfunction, impaired proteostasis, hypertrophic cardiac remodeling, and contractile dysfunction. Can ARA290 ameliorate these age-associated cardiac changes and the severity of frailty in advanced age?MethodsWe conducted an integrated longitudinal (n = 48) and cross-sectional (n = 144) 15 months randomized controlled trial in which 18-month-old Fischer 344 x Brown Norway rats were randomly assigned to either receive chronic ARA290 treatment or saline. Serial echocardiography, tail blood pressure and body weight were evaluated repeatedly at 4-month intervals. A frailty index was calculated at the final timepoint (33 months of age). Tissues were harvested at 4-month intervals to define inflammatory markers and left ventricular tissue remodeling. Mitochondrial and myocardial cell health was assessed in isolated left ventricular myocytes. Kaplan–Meier survival curves were established. Mixed ANOVA tests and linear mixed regression analysis were employed to determine the effects of age, treatment, and age-treatment interactions.ResultsChronic ARA290 treatment mitigated age-related increases in the cardiac non-myocyte to myocyte ratio, infiltrating leukocytes and monocytes, pro-inflammatory cytokines, total NF-κB, and p-NF-κB. Additionally, ARA290 treatment enhanced cardiomyocyte autophagy flux and reduced cellular accumulation of lipofuscin. The cardiomyocyte mitochondrial permeability transition pore response to oxidant stress was desensitized following chronic ARA290 treatment. Concurrently, ARA290 significantly blunted the age-associated elevation in blood pressure and preserved the LV ejection fraction. Finally, ARA290 preserved body weight and significantly reduced other markers of organism-wide frailty at the end of life.ConclusionAdministration of ARA290 reduces cell and tissue inflammation, mitigates structural and functional changes within the cardiovascular system leading to amelioration of frailty and preserved healthspan.

Abstract Age‐associated increases in physical and mental stress, known as allostatic load, could lead to a chronic low‐grade inflammation in the heart, brain, and arteries. This low‐grade inflammation potentially contributes to adverse structural and functional remodeling, such as intimal medial thickening, endothelial dysfunction, arterial stiffening, cardiac hypertrophy and ischemia, and cognitive decline. These cellular and tissue remodeling is the fertile soil for the development of age‐associated structural and functional disorders in the cardiovascular and cerebrovascular systems in the pathogenesis of obesity, type II diabetes, hypertension, atherosclerosis, heart dysfunction, and cognitive decline. Growing evidence indicates that puerarin, a polyphenol, extracted from Puerara Labota, efficiently alleviates the initiation and progression of obesity, type II diabetes, hypertension, atherosclerosis, cardiac ischemia, cardiac arrythmia, cardiac hypertrophy, ischemic stroke, and cognition decline via suppression of oxidative stress and inflammation. This mini review focuses on recent advances in the effects of puerarin on the oxidative and inflammatory molecular, cellular, tissue events in the heart, brain, and arteries.

Adult (3 month) mice with cardiac-specific overexpression of adenylyl cyclase (AC) type VIII (TGAC8) adapt to an increased cAMP-induced cardiac workload (~30% increases in heart rate, ejection fraction and cardiac output) for up to a year without signs of heart failure or excessive mortality. Here, we show classical cardiac hypertrophy markers were absent in TGAC8, and that total left ventricular (LV) mass was not increased: a reduced LV cavity volume in TGAC8 was encased by thicker LV walls harboring an increased number of small cardiac myocytes, and a network of small interstitial proliferative non-cardiac myocytes compared to wild type (WT) littermates; Protein synthesis, proteosome activity, and autophagy were enhanced in TGAC8 vs WT, and Nrf-2, Hsp90α, and ACC2 protein levels were increased. Despite increased energy demands in vivo LV ATP and phosphocreatine levels in TGAC8 did not differ from WT. Unbiased omics analyses identified more than 2,000 transcripts and proteins, comprising a broad array of biological processes across multiple cellular compartments, which differed by genotype; compared to WT, in TGAC8 there was a shift from fatty acid oxidation to aerobic glycolysis in the context of increased utilization of the pentose phosphate shunt and nucleotide synthesis. Thus, marked overexpression of AC8 engages complex, coordinate adaptation "circuity" that has evolved in mammalian cells to defend against stress that threatens health or life (elements of which have already been shown to be central to cardiac ischemic pre-conditioning and exercise endurance cardiac conditioning) that may be of biological significance to allow for proper healing in disease states such as infarction or failure of the heart.

Soil proteinase and proteinase-producing microbial community are closely associated with soil fertility and soil health. Sea rice has been planted in the coastal beach of Jiaozhou Bay, China, in an effort to transform saline-alkali soil into arable land. However, the knowledge regarding the bacterial degradation of organic nitrogen in sea rice soils is limited. This study aims to investigate the physicochemical characteristics and enzymatic activities of the sea rice soils, as well as the microbial communities by both the Illumina sequencing-based culture-independent technology and culture-dependent methods. Sea rice soils exhibited a lower salinity and higher organic matter content and proteinase activity, as well as an increase in both the richness and diversity of the proteinase-producing bacterial community, compared to the adjacent non-rice soils. The Proteobacteria phylum and the Gammaproteobacteria class were dominant in sea rice soils, showing higher abundance than in the reference soils. The Planococcus genus and Bacillus-like bacterial communities were abundant in the cultivable proteinase-producing bacteria isolated from sea rice soils. Furthermore, a significant proportion of the extracellular proteinase produced by the isolated soil bacteria consisted of serine proteinases and metalloproteinases. These findings provided new insights into the degradation of soil organic nitrogen in coastal agricultural regions.

The notion of “agent bookkeeping” was proposed when the “Accounting Law of the People’s Republic of China” was updated in 1993. Since their business is specialized in serving small and micro-enterprises, this has created the industry characteristic of generally small in the size of company and low in the salary of employees in Chinese agent bookkeeping companies. Such characteristic results in a series of problems including negative work attitude of employees in the development process, which seriously limit the development of Chinese agent bookkeeping companies. However, issues occurred in the development of agent bookkeeping, such as negative employee attitudes, which severely hampered the growth of Chinese agent bookkeeping companies. Therefore, a model of three dimensions of work attitude has been set up in this paper to demonstrate the working attitude of the staff of the agent bookkeeping companies in China’s Guangdong-Hong Kong-Macao Greater Bay Area, including emotional dimension, behavioral dimension, and cognitive dimension which consists of eight factors: work environment, career satisfaction, interpersonal relationship, role engagement, work vitality, responsibility attitude, emotional identity, and retention attitude. The result indicates that (1) female employees outnumber male ones in agent bookkeeping companies, (2) most employees have a low sense of belonging to the company, (3) limited career development affects employees’ enthusiasm for work, (4) work attitudes are influenced by mediocre work performance among employees with a graduate degree or higher.

Background Age‐associated aortic remodeling includes a marked increase in intimal medial thickness (IMT), associated with signs of inflammation. Although aortic wall milk fat globule–epidermal growth factor VIII (MFG‐E8) increases with age, and is associated with aortic inflammation, it is not known whether MFG‐E8 is required for the age‐associated increase in aortic IMT. Here, we tested whether MFG‐E8 is required for the age‐associated increase in aortic IMT. Methods and Results To determine the role of MFG‐E8 in the age‐associated increase of IMT, we compared aortic remodeling in adult (20‐week) and aged (96‐week) MFG‐E8 (−/−) knockout and age matched wild‐type (WT) littermate mice. The average aortic IMT increased with age in the WT from 50±10 to 70±20 μm (P

Full-field optical angiography (FFOA) has considerable potential for clinical applications in the prevention and diagnosis of various diseases. However, owing to the limited depth of focus attainable using optical lenses, only information about blood flow in the plane within the depth of field can be acquired using existing FFOA imaging techniques, resulting in partially unclear images. To produce fully focused FFOA images, an FFOA image fusion method based on the nonsubsampled contourlet transform and contrast spatial frequency is proposed. Firstly, an imaging system is constructed, and the FFOA images are acquired by intensity-fluctuation modulation effect. Secondly, we decompose the source images into low-pass and bandpass images by performing nonsubsampled contourlet transform. A sparse representation-based rule is introduced to fuse the lowpass images to effectively retain the useful energy information. Meanwhile, a contrast spatial frequency rule is proposed to fuse bandpass images, which considers the neighborhood correlation and gradient relationships of pixels. Finally, the fully focused image is produced by reconstruction. The proposed method significantly expands the range of focus of optical angiography and can be effectively extended to public multi-focused datasets. Experimental results confirm that the proposed method outperformed some state-of-the-art methods in both qualitative and quantitative evaluations.

Abstract Background Microbes are closely related to human health and diseases. Identification of disease-related microbes is of great significance for revealing the pathological mechanism of human diseases and understanding the interaction mechanisms between microbes and humans, which is also useful for the prevention, diagnosis and treatment of human diseases. Considering the known disease-related microbes are still insufficient, it is necessary to develop effective computational methods and reduce the time and cost of biological experiments. Methods In this work, we developed a novel computational method called MDAKRLS to discover potential microbe-disease associations (MDAs) based on the Kronecker regularized least squares. Specifically, we introduced the Hamming interaction profile similarity to measure the similarities of microbes and diseases besides Gaussian interaction profile kernel similarity. In addition, we introduced the Kronecker product to construct two kinds of Kronecker similarities between microbe-disease pairs. Then, we designed the Kronecker regularized least squares with different Kronecker similarities to obtain prediction scores, respectively, and calculated the final prediction scores by integrating the contributions of different similarities. Results The AUCs value of global leave-one-out cross-validation and 5-fold cross-validation achieved by MDAKRLS were 0.9327 and 0.9023 ± 0.0015, which were significantly higher than five state-of-the-art methods used for comparison. Comparison results demonstrate that MDAKRLS has faster computing speed under two kinds of frameworks. In addition, case studies of inflammatory bowel disease (IBD) and asthma further showed 19 (IBD), 19 (asthma) of the top 20 prediction disease-related microbes could be verified by previously published biological or medical literature. Conclusions All the evaluation results adequately demonstrated that MDAKRLS has an effective and reliable prediction performance. It may be a useful tool to seek disease-related new microbes and help biomedical researchers to carry out follow-up studies.

Skull base chordomas are treated with surgery and chemotherapy but often recur due to incomplete resection, understanding the molecular underpinnings of the tumours may provide additional therapeutic strategies. Here, the authors carry out whole genome sequencing of 80 skull base chordoma tumours and identify the SWI/SNF component—PBRM1—as a frequently mutated gene.

Raw coal is used by many suburban and rural households for cooking and heating and results in severe air pollution, especially problematic SO2 emissions. A source treatment strategy was proposed to reduce SO2 emissions, which used the co-pyrolysis of raw coal with a CaCO3 additive to produce clean coke. The effect of Ca/S molar ratio on the SO2 capture efficiency of clean coke was investigated, and the SO2 retention efficiency was optimized at a Ca/S molar ratio of 1.5. The sulfur retention mechanism of clean coke was attributed to: (1) CaCO3 decomposition to CaO and partial reaction of CaO with H2S to generate CaS during pyrolysis. (2) Transformation of the remaining sulfur in the clean coke to SO2 during combustion, capture by unreacted CaO to form CaSO4, and direct oxidation of CaS to CaSO4. The feasibility of SO2 emission reduction by clean coke in a practical household stove was verified.

We propose a novel retinal layer segmentation method to accurately segment 10 retinal layers in optical coherence tomography (OCT) images with intraretinal fluid. The method used a fan filter to enhance the linear information pertaining to retinal boundaries in an OCT image by reducing the effect of vessel shadows and fluid regions. A random forest classifier was employed to predict the location of the boundaries. Two novel methods of boundary redirection (SR) and similarity correction (SC) were combined to carry out boundary tracking and thereby accurately locate retinal layer boundaries. Experiments were performed on healthy controls and subjects with diabetic macular edema (DME). The proposed method required an average of 415[Formula: see text]s for healthy controls and of 482[Formula: see text]s for subjects with DME and achieved high accuracy for both groups of subjects. The proposed method requires a shorter running time than previous methods and also provides high accuracy. Thus, the proposed method may be a better choice for small training datasets.

Abstract Aging is a major risk factor for quintessential cardiovascular diseases, which are closely related to arterial proinflammation. The age‐related alterations of the amount, distribution, and properties of the collagen fibers, such as cross‐links and degradation in the arterial wall, are the major sequelae of proinflammation. In the aging arterial wall, collagen types I, II, and III are predominant, and are mainly produced by stiffened vascular smooth muscle cells (VSMCs) governed by proinflammatory signaling, leading to profibrosis. Profibrosis is regulated by an increase in the proinflammatory molecules angiotensin II, milk fat globule‐EGF‐VIII, and transforming growth factor‐beta 1 (TGF‐β1) signaling and a decrease in the vasorin signaling cascade. The release of these proinflammatory factors triggers the activation of matrix metalloproteinase type II (MMP‐2) and activates profibrogenic TGF‐β1 signaling, contributing to profibrosis. The age‐associated increase in activated MMP‐2 cleaves latent TGF‐β and subsequently increases TGF‐β1 activity leading to collagen deposition in the arterial wall. Furthermore, a blockade of the proinflammatory signaling pathway alleviates the fibrogenic signaling, reduces profibrosis, and prevents arterial stiffening with aging. Thus, age‐associated proinflammatory‐profibrosis coupling is the underlying molecular mechanism of arterial stiffening with advancing age.

Objective: This study aimed to evaluate the clinical and angiographic outcomes of aneurysms that were completely or near-completely embolized and ascertain whether complete embolization is important in the stent-assisted coiling (SAC) of intracranial aneurysms. Methods: This retrospective study enrolled 390 patients (417 aneurysms). Among them, complete (100%) or near-complete (>90%) angiographic obliteration of the aneurysms on immediate angiography was accomplished. Baseline characteristics, complications, angiography follow-up results, and clinical outcomes were analyzed. Results: Cumulative adverse events occurred in 30 patients (7.7%), including thromboembolic complications in 17 (4.4%), intraoperative rupture in 10 (2.6%), and others in 3 (0.8%). Statistical analyses revealed an increased intraprocedural rupture rate in the initial completely occluded aneurysms (5.6% compared with 1.0%). The incidence of cumulative adverse events was higher in patients with completely occluded aneurysms (11.1%) than in those with near-completely occluded aneurysms (5.5%). Angiography follow-up was available for 173 aneurysms. Aneurysm occlusion status at follow-up was correlated with stent placement (p ​= ​0.000, odds ratio ​= ​5.847), size (p ​= ​0.000, odds ratio ​= ​6.446 for tiny aneurysms; and p ​= ​0.001, odds ratio ​= ​5.616 for small aneurysms), and initial aneurysm occlusion status (p ​= ​0.001, odds ratio ​= ​3.436). Complete occlusion at follow-up was seen in 82.6% of the initial complete occlusion group versus 63.0% of the initial near-complete occlusion group. The incidence of complete occlusion at follow-up was higher in the initial completely occluded aneurysms with SAC (100%) than in the initial completely occluded aneurysms with non-SAC (65.2%). Conclusions: Initial complete treatment may lead to higher complication rates and good clinical outcomes at follow-up. Stent placement may enhance progressive aneurysm occlusion. Initial complete occlusion with SAC can provide durable closure at follow-up.

Many tumours are heterogenous, which calls into question whether multiple biopsies are required to accurately assess the cancer. Here, the authors show that papillary renal cell carcinoma is clonal in nature, suggesting that in this cancer one biopsy is sufficient for diagnosis and molecular analyses.

Many tumors are known to be heterogeneous. Here, the authors examined multiple samples from 84 patients with lung adenocarcinoma and demonstrate that the intratumor heterogeneity of methylation and copy number associates with poor prognosis.

Summary: Recent genomic studies suggest that Asian breast cancer (BC) may have distinct somatic features; however, most comparisons of BC genomic features across populations did not account for differences in age, subtype, and sequencing methods. In this study, we analyzed whole-exome sequencing (WES) data to characterize somatic copy number alterations (SCNAs) and mutation profiles in 98 Hong Kong BC (HKBC) patients and compared with those from The Cancer Genome Atlas of European ancestry (TCGA-EA, N = 686), which had similar distributions of age at diagnosis and PAM50 subtypes as in HKBC. We developed a two-sample Poisson model to compare driver gene selection pressure, which reflects the effect sizes of cancer driver genes, while accounting for differences in sample size, sequencing platforms, depths, and mutation calling methods. We found that somatic mutation and SCNA profiles were overall very similar between HKBC and TCGA-EA. The selection pressure for small insertions and deletions (indels) in GATA3 (false discovery rate (FDR) corrected p < 0.01) and single-nucleotide variants (SNVs) in TP53 (nominal p = 0.02, FDR corrected p = 0.28) was lower in HKBC than in TCGA-EA. Among the 13 signatures of single-base substitutions (SBS) that are common in BC, we found a suggestively higher contribution of SBS18 and a lower contribution of SBS1 in HKBC than in TCGA-EA, while the two APOBEC-induced signatures showed similar prevalence. Our results suggest that the genomic landscape of BC was largely very similar between HKBC and TCGA-EA, despite suggestive differences in some driver genes and mutational signatures that warrant future investigations in large and diverse Asian populations.

In order to improve the safety and reliability of airborne power supply and distribution system, a digital twin of a phase-shift full-bridge current doubling rectifier converter based on gallium nitride metal-oxide-semiconductor field-effect transistor (GaN MOSFET) is built. The digital twin can be regarded as virtual symmetry of the real converter. The particle swarm optimization (PSO) algorithm is applied to compare the voltage and current waveforms of the real converter with relative waveforms of its digital model established in simulation software, and the interior parameters of the model are constantly updated until the waveforms of the digital twin coincide with that of the converter. Applications of this digital twin are discussed through experimental verification, and the results show that the digital twin can deduce the parameter value of key components of the converter in the case of soft faults. In the case of hard faults, a back propagating artificial neural net (BP ANN) is trained by data collected from the digital twin, and the BP ANN is able to identify different running states of the converter. The outcomes of this paper present a non-intrusive and high real-time method of condition monitoring and fault diagnosis, which is beneficial to improve the reliability of airborne HVDC power supply system.

In recent years, the model compression technique is very effective for deep neural network compression. However, many existing model compression methods rely heavily on human experience to explore a compression strategy between network structure, speed, and accuracy, which is usually suboptimal and time-consuming. In this paper, we propose a framework for automatically compressing models through the actor–critic structured deep reinforcement learning (DRL) which interacts with each layer in the neural network, where the actor network determines the compression strategy and the critic network ensures the decision accuracy of the actor network through predicted values, thus improving the compression quality of the network. To enhance the prediction performance of the critic network, we impose the L1 norm regularizer on the weights of the critic network to obtain a distinct activation output feature on the representation, thus enhancing the prediction accuracy of the critic network. Moreover, to improve the decision performance of the actor network, we impose the L1 norm regularizer on the weights of the actor network to improve the decision accuracy of the actor network by removing the redundant weights in the actor network. Furthermore, to improve the training efficiency, we use the proximal gradient method to optimize the weights of the actor network and the critic network, which can obtain an effective weight solution and thus improve the compression performance. In the experiment, in MNIST datasets, the proposed method has only a 0.2% loss of accuracy when compressing more than 70% of neurons. Similarly, in CIFAR-10 datasets, the proposed method compresses more than 60% of neurons, with only 7.1% accuracy loss, which is superior to other existing methods. In terms of efficiency, the proposed method also cost the lowest time among the existing methods.

Medin, a small 50-amino acid peptide, is an internal cleaved product from the second discoidin domain of milk fat globule epidermal growth factor VIII (MFG-E8) protein. Medin has been reported as the most common amylogenic protein in the upper part of the arterial system, including aortic, temporal, and cerebral arterial walls in the elderly. Medin has a high affinity to elastic fibers and is closely associated with arterial degenerative inflammation, elastic fiber fragmentation, calcification, and amyloidosis. In vitro, treating with the medin peptide promotes the inflammatory phenotypic shift of both endothelial cells and vascular smooth muscle cells. In vitro, ex vivo, and in vivo studies demonstrate that medin enhances the abundance of reactive oxygen species and reactive nitrogen species produced by both endothelial cells and vascular smooth muscle cells and promotes vascular endothelial dysfunction and arterial stiffening. Immunostaining and immunoblotting analyses of human samples indicate that the levels of medin are increased in the pathogenesis of aortic aneurysm/dissection, temporal arteritis, and cerebrovascular dementia. Thus, medin peptide could be targeted as a biomarker diagnostic tool or as a potential molecular approach to curbing the arterial degenerative inflammatory remodeling that accompanies aging and disease.

Background: SDF-1/CXCR4 axis plays a critical role in the mobilization and regeneration of host-derived cells. Little is known around the role of SDF-1 gene on bone regeneration. This study was conceptualized to create a 2-in-1 strategy by identifying potential role of SDF-1 on promoting endogenous osteoblast migration and synergizing with magnesium doped calcium phosphate scaffold (MCPC) on osteogenic differentiation. Method: ADSCs were transfected with Lenti-SDF-1. Cell proliferation, osteogenic gene expression and ALP/ARS staining were investigated. Osteoblast migration was studied. MCPC construct was employed as carrier of Lenti-SDF-1 ADSCs. Osteogenic gene expressions of BMSCs were determined in MCPC + ADSCs medium. MCPC + Lenti-SDF-1 ADSCs scaffolds were implanted into rats and bone regeneration efficacy was evaluated by micro-CT and histological analysis. Result: SDF-1 transduction neither impacted ADSCs' proliferation, nor osteogenic differentiation. Lenti-SDF-1 ADSCs promoted migration of BMSCs/osteoblasts. MCPC facilitated osteogenic differentiation of BMSCs. Bone formation was significantly increased in MCPC + Lenti-SDF-1 group. Conclusion: Overexpressed SDF-1 gene promotes the homing of endogenous osteoblasts. MCPC + Lenti-SDF-1 facilitated robust in situ bone regeneration via dual mechanisms by recruiting endogenous BMSCs' and enhancing homing cell's differentiation. This advanced design combines gene therapy and osteoinductive tissue scaffolds, which is proved to be a promising strategy to achieve satisfied clinical bone repair efficacy.

Current models stipulate that B cells and antibodies function during atherosclerosis in two distinct ways based on antibody isotype, where IgM is protective and IgG is inflammatory. To examine this model, we generated ApoE-/- Aid-/- mice, which are unable to produce IgG antibodies due to the absence of activation-induced deaminase (AID) but maintain high plasma cholesterol due to the absence of apolipoprotein E (APOE). We saw a dramatic decrease in plaque formation in ApoE-/- Aid-/- mice compared to ApoE-/- mice. Rigorous analysis of serum antibodies revealed both ApoE-/- and ApoE-/- Aid-/- mice had substantially elevated titers of IgM antibodies compared to C57BL/6J controls, suggesting a more complex dynamic than previously described. Analysis of antigen specificity demonstrated that ApoE-/- Aid-/- mice had elevated titers of antibodies specific to malondialdehyde-oxidized low density lipoprotein (MDA-oxLDL), which has been shown to block macrophage recruitment into plaques. Conversely, ApoE-/- mice showed low levels of MDA-oxLDL specificity, but had antibodies specific to numerous self-proteins. We provide evidence for a hierarchical order of antibody specificity, where elevated levels of MDA-oxLDL specific IgM antibodies inhibit plaque formation. If the level of MDA-oxLDL specific IgM is insufficient, self-reactive IgM and IgG antibodies are generated against debris within the arterial plaque, resulting in increased inflammation and further plaque expansion.

Probe-assisted integration of imaging and therapy into a single modality provides tremendous opportunities in biological applications. In this study, phase-transition-mediated cavitation was used for simultaneous photoacoustic imaging (PA) and triggering drug release. For this purpose, we developed unique phase-transition mesoporous silicon nanoprobes (ICG/PFC/PTX@MSNs) consisting of indocyanine green (ICG), perfluorocarbon (PFC), and paclitaxel (PTX). For high-dose laser irradiation, the encapsulated ICG absorbs laser energy, providing localized heating well over the supercritical temperature of PFC. Then, liquid PFC was subjected to a liquid-to-gas phase transition, which generated stronger PA signals and promoted fast drug release. The enhancement of ICG/PFC/PTX@MSNs for PA imaging was demonstrated in in vitro and in vivo experiments. The average PA signal based on the phase-transition mechanism was ∼3 times higher than that of the traditionally used thermal expansion mechanism. Furthermore, the rapid drug release based on the same phase-transition-mediated cavitation mechanism can be achieved simultaneously; eventually, ∼80.4% of the total encapsulated drug were released. The hematoxylin–eosin stained section of tumor tissues from the ICG/PFC/PTX@MSN group showed many dead cells with condensed nuclei and pyknosis. This method not only promotes efficacy of chemotherapy but also makes accurate imaging-guided chemotherapy possible.

Abstract Background Heterogeneity of immune gene expression patterns of luminal breast cancer (BC), which is clinically heterogeneous and overall considered as low immunogenic, has not been well studied especially in non-European populations. Here, we aimed at characterizing the immune gene expression profile of luminal BC in an Asian population and associating it with patient characteristics and tumor genomic features. Methods We performed immune gene expression profiling of tumor and adjacent normal tissue in 92 luminal BC patients from Hong Kong using RNA-sequencing data and used unsupervised consensus clustering to stratify tumors. We then used luminal patients from The Cancer Genome Atlas (TCGA, N = 564) and a Korean breast cancer study (KBC, N = 112) as replication datasets. Results Based on the expression of 130 immune-related genes, luminal tumors were stratified into three distinct immune subtypes. Tumors in one subtype showed higher level of tumor-infiltrating lymphocytes (TILs), characterized by T cell gene activation, higher expression of immune checkpoint genes, higher nonsynonymous mutation burden, and higher APOBEC-signature mutations, compared with other luminal tumors. The high-TIL subtype was also associated with lower ESR1/ESR2 expression ratio and increasing body mass index. The comparison of the immune profile in tumor and matched normal tissue suggested a tumor-derived activation of specific immune responses, which was only seen in high-TIL patients. Tumors in a second subtype were characterized by increased expression of interferon-stimulated genes and enrichment for TP53 somatic mutations. The presence of three immune subtypes within luminal BC was replicated in TCGA and KBC, although the pattern was more similar in Asian populations. The germline APOBEC3B deletion polymorphism, which is prevalent in East Asian populations and was previously linked to immune activation, was not associated with immune subtypes in our study. This result does not support the hypothesis that the germline APOBEC3B deletion polymorphism is the driving force for immune activation in breast tumors in Asian populations. Conclusion Our findings suggest that immune gene expression and associated genomic features could be useful to further stratify luminal BC beyond the current luminal A/B classification and a subset of luminal BC patients may benefit from checkpoint immunotherapy, at least in Asian populations.

Abstract Genetic susceptibility is likely involved in nasopharyngeal carcinoma (NPC), a cancer caused by Epstein-Barr virus (EBV) infection. Understanding of genetic factors involved in NPC and how they contribute to EBV-induced carcinogenesis is limited. We conducted whole-exome capture/sequencing among 251 individuals from 97 multiplex families from Taiwan (205 affected, 21 obligate carriers, and 25 unaffected) using SeqCap EZ Human Exome Library v3.0 and Illumina HiSeq. Aligned sequences were filtered to identify likely-to-be-functional deleterious variants that co-segregated with disease. Ingenuity Pathway analysis was performed. Circulating magnesium levels were measured in 13 individuals in 2 families with NIPAL1 mutations and in 197 sporadic NPC cases and 237 controls. We identified variants in 12 genes likely involved in cancer pathogenesis, viral infection or immune responses to infection. These included genes postulated to be involved in magnesium transport (NIPAL1), EBV cell entry (ITGB6), modulation of EBV infection (BCL2L12, NEDD4L), telomere biology (CLPTM1L, BRD2, HNRNPU), modulation of cAMP signaling (RAPGEF3), DNA repair (PRKDC, MLH1), and Notch signaling (NOTCH1, DLL3). Pathway based analysis demonstrated enrichment for Notch signaling genes (p-value = 0.0006). Evaluation of individuals within NIPAL1 families suggested lower serum magnesium in NPC compared to unaffected members. A significant reduction in serum magnesium levels was observed among sporadic NPC cases compared to controls (7.1% NPC/1.7% controls below normal range; OR = 4.5; 95% CI = 1.4,14) and is consistent with findings demonstrating a role for magnesium channeling in T-cell responses to EBV. We identified novel genes associated with NPC that point to new areas of inquiry to better understand genetic factors that determine the fate of viral infections and/or otherwise predisposes to NPC.

The current study mainly explored the influence of fluid intelligence (IQ) and emotional intelligence (EI) on affective decision-making from a developmental perspective, specifically, during the transition from childhood into early adolescence. Meanwhile, their age-related differences in affective decision-making were explored. A total of 198 participants aged 8–12 completed the Iowa Gambling Task (IGT), the Cattell’s Culture Fair Intelligence Test and the Trait Emotional Intelligence Questionnaire-Child Form. Based on the net scores of IGT, the development of affective decision-making ability did not increase monotonically with age, and there was a developmental trend of an impaired IGT performance in early adolescence (aged 11–12), especially in the early learning phase (first 40 trials) of the IGT. More importantly, IQ and EI played different roles for children and early adolescents: IQ and EI jointly predicted the IGT performance for 8–10 years old children, whereas only EI contributed to the IGT performance of 11–12 years old early adolescents. The present study extends the evidence how cognitive processing and emotional processing interact in affective decision-making from the developmental perspective. Furthermore, it provides insights of future research and intervention with early adolescents’ poor affective decision-making.

Abstract Background and aims Guatemala has the highest incidence of hepatocellular carcinoma (HCC) in the Western hemisphere. The major risk factors in Guatemala are not well characterized, but the prevalence of hepatitis B virus (HBV) and hepatitis C virus (HCV) appears to be low, while the prevalence of aflatoxin (AFB1) exposure appears to be high. To examine whether AFB1 may contribute to the elevated incidence of HCC in Guatemala, this study examined the frequency of the AFB1‐signature mutation in the TP53 gene (R249S) as well as other somatic mutations. In addition, we assessed whether the frequency of the TP53 mutation differed by sex. Methods Formalin‐fixed, paraffin‐embedded (FFPE) HCC tissues were obtained from three hospitals in Guatemala City between 2016 and 2017. In addition, tumor tissues preserved in RNAlater were also obtained. Sociodemographic and clinical information including HBV and HCV status were collected. Targeted sequencing of TP53 was performed in the FFPE samples, and a panel of 253 cancer‐related genes was sequenced in the RNAlater samples. Results Ninety‐one FFPE tissues were examined, from 52 men and 39 women. Median (IQR) age at diagnosis was 62 (51‐70). Among those with known HBV and HCV status, two were HBV+ and three were HCV+. Overall, 47% of the HCCs had a TP53 mutation. The AFB1‐signature R249S mutation was present in 24%. No overlap between the R249S mutation and HBV+ was observed in this cohort. Among 18 RNAlater samples examined, 44% had any TP53 mutation and 33% had the R249S mutation. Other somatic mutations were identified in known HCC driver genes. Conclusions The presence of the TP53 R249S mutation in the samples studied suggests that AFB1 may contribute to the high incidence of HCC in Guatemala. The proportion of HBV+ tumors was low, suggesting that AFB1 may be associated with HCC in the absence of concomitant HBV infection. Further investigation of AFB1 and other risk factors for HCC in Guatemala is warranted.

Abstract Background Prior research has established that the prevalence of pathogenic/likely pathogenic (P/LP) variants across all of the American College of Medical Genetics (ACMG) Secondary Findings (SF) genes is approximately 0.8–5%. We investigated the prevalence of P/LP variants in the 24 ACMG SF v2.0 cancer genes in a family-based cancer research cohort (n = 1173) and in cancer-free ethnicity-matched controls (n = 982). Methods We used InterVar to classify variants and subsequently conducted a manual review to further examine variants of unknown significance (VUS). Results In the 24 genes on the ACMG SF v2.0 list associated with a cancer phenotype, we observed 8 P/LP unique variants (8 individuals; 0.8%) in controls and 11 P/LP unique variants (14 individuals; 1.2%) in cases, a non-significant difference. We reviewed 115 VUS. The median estimated per-variant review time required was 30 min; the first variant within a gene took significantly (p = 0.0009) longer to review (median = 60 min) compared with subsequent variants (median = 30 min). The concordance rate was 83.3% for the variants examined by two reviewers. Conclusion The 115 VUS required database and literature review, a time- and labor-intensive process hampered by the difficulty in interpreting conflicting P/LP determinations. By rigorously investigating the 24 ACMG SF v2.0 cancer genes, our work establishes a benchmark P/LP variant prevalence rate in a familial cancer cohort and controls.

Abstract Background High-throughput sequencing has rapidly become an essential part of precision cancer medicine. But validating results obtained from analyzing and interpreting genomic data remains a rate-limiting factor. The gold standard, of course, remains manual validation by expert panels, which is not without its weaknesses, namely high costs in both funding and time as well as the necessarily selective nature of manual validation. But it may be possible to develop more economical, complementary means of validation. In this study we employed four synthetic data sets (variants with known mutations spiked into specific genomic locations) of increasing complexity to assess the sensitivity, specificity, and balanced accuracy of five open-source variant callers: FreeBayes v1.0, VarDict v11.5.1, MuTect v1.1.7, MuTect2, and MuSE v1.0rc. FreeBayes, VarDict, and MuTect were run in bcbio-next gen, and the results were integrated into a single Ensemble call set. The known mutations provided a level of “ground truth” against which we evaluated variant-caller performance. We further facilitated the comparison and evaluation by segmenting the whole genome into 10,000,000 base-pair fragments which yielded 316 segments. Results Differences among the numbers of true positives were small among the callers, but the numbers of false positives varied much more when the tools were used to analyze sets one through three. Both FreeBayes and VarDict produced strikingly more false positives than did the others, although VarDict, somewhat paradoxically also produced the highest number of true positives. The Ensemble approach yielded results characterized by higher specificity and balanced accuracy and fewer false positives than did any of the five tools used alone. Sensitivity and specificity, however, declined for all five callers as the complexity of the data sets increased, but we did not uncover anything more than limited, weak correlations between caller performance and certain DNA structural features: gene density and guanine-cytosine content. Altogether, MuTect2 performed the best among the callers tested, followed by MuSE and MuTect. Conclusions Spiking data sets with specific mutations –single-nucleotide variations (SNVs), single-nucleotide polymorphisms (SNPs), or structural variations (SVs) in this study—at known locations in the genome provides an effective and economical way to compare data analyzed by variant callers with ground truth. The method constitutes a viable alternative to the prolonged, expensive, and noncomprehensive assessment by expert panels. It should be further developed and refined, as should other comparatively “lightweight” methods of assessing accuracy. Given that the scientific community has not yet established gold standards for validating NGS-related technologies such as variant callers, developing multiple alternative means for verifying variant-caller accuracy will eventually lead to the establishment of higher-quality standards than could be achieved by prematurely limiting the range of innovative methods explored by members of the community.