Application of artificial intelligence in the diagnosis and treatment of cardiac arrhythmia.

The rapid growth in computational power, sensor technology, and wearable devices has provided a solid foundation for all aspects of cardiac arrhythmia care. Artificial intelligence (AI) has been instrumental in bringing about significant changes in the prevention, risk assessment, diagnosis, and treatment of arrhythmia. This review examines the current state of AI in the diagnosis and treatment of atrial fibrillation, supraventricular arrhythmia, ventricular arrhythmia, hereditary channelopathies, and cardiac pacing. Furthermore, ChatGPT, which has gained attention recently, is addressed in this paper along with its potential applications in the field of arrhythmia. Additionally, the accuracy of arrhythmia diagnosis can be improved by identifying electrode misplacement or erroneous swapping of electrode position using AI. Remote monitoring has expanded greatly due to the emergence of contactless monitoring technology as wearable devices continue to develop and flourish. Parallel advances in AI computing power, ChatGPT, availability of large data sets, and more have greatly expanded applications in arrhythmia diagnosis, risk assessment, and treatment. More precise algorithms based on big data, personalized risk assessment, telemedicine and mobile health, smart hardware and wearables, and the exploration of rare or complex types of arrhythmia are the future direction.

Microglial repopulation restricts ocular inflammation and choroidal neovascularization in mice.

Introduction: Age-related macular degeneration (AMD) is a prevalent, chronic and progressive retinal degenerative disease characterized by an inflammatory response mediated by activated microglia accumulating in the retina. In this study, we demonstrate the therapeutically effects and the underlying mechanisms of microglial repopulation in the laser-induced choroidal neovascularization (CNV) model of exudative AMD. Methods: The CSF1R inhibitor PLX3397 was used to establish a treatment paradigm for microglial repopulation in the retina. Neovascular leakage and neovascular area were examined by fundus fluorescein angiography (FFA) and immunostaining of whole-mount RPE-choroid-sclera complexes in CNV mice receiving PLX3397. Altered cellular senescence was measured by beta-galactosidase (SA-ß-gal) activity and p16INK4a expression. The effect and mechanisms of repopulated microglia on leukocyte infiltration and the inflammatory response in CNV lesions were analyzed. Results: We showed that ten days of the CSF1R inhibitor PLX3397 treatment followed by 11 days of drug withdrawal was sufficient to stimulate rapid repopulation of the retina with new microglia. Microglial repopulation attenuated pathological choroid neovascularization and dampened cellular senescence in CNV lesions. Repopulating microglia exhibited lower levels of activation markers, enhanced phagocytic function and produced fewer cytokines involved in the immune response, thereby ameliorating leukocyte infiltration and attenuating the inflammatory response in CNV lesions. Discussion: The microglial repopulation described herein are therefore a promising strategy for restricting inflammation and choroidal neovascularization, which are important players in the pathophysiology of AMD.

AudioGest: Gesture-based Interaction for Virtual Reality using Audio Devices.

Current virtual reality (VR) system takes gesture interaction based on camera, handle and touch screen as one of the mainstream interaction methods, which can provide accurate gesture input for it. However, limited by application forms and the volume of devices, these methods cannot extend the interaction area to such surfaces as walls and tables. To address the above challenge, we propose AudioGest, a portable, plug-and-play system that detects the audio signal generated by finger tapping and sliding on the surface through a set of microphone devices without extensive calibration. First, an audio synthesis-recognition pipeline based on micro-contact dynamics simulation is constructed to generate modal audio synthesis from different materials and physical properties. Then the accuracy and effectiveness of the synthetic audio are verified by mixing the synthetic audio with real audio proportionally as the training sets. Finally, a series of desktop office applications are developed to demonstrate the application potential of AudioGest's scalability and versatility in VR scenarios.

Temporal niche partitioning among sympatric wild and domestic ungulates between warm and cold seasons.

The coexistence of sympatric species with similar ecological niches has been a central issue in ecology. Clarifying the daily activity patterns of sympatric wild ungulates can help understand their temporal niche differentiation and the mechanisms of coexistence, providing information for their conservation. The Baotianman National Nature Reserve in northern China is rich in wild ungulates, but little is known about the daily activity patterns of wild ungulates in the area, making it difficult to develop effective conservation strategies. We studied five representative wild ungulates (i.e. forest musk deer, Chinese goral, Reeve's muntjac, Siberian roe deer, and wild boar) of the region using camera-trapping data, focusing on the seasonal daily activity patterns and effects of seasonal grazing of domestic sheep, to reveal their coexistence based on temporal ecological niche differentiation. Comparative analyses of the seasonal daily activity showed that forest musk deer exhibited a single-peak activity in the warm season. Other ungulates exhibited multipeak activity. All five ungulates differed significantly in daily activity patterns. Notably, wild boar and Reeve's muntjac showed high overlap coefficients between the cold and warm seasons. In both cold and warm seasons, the five wild ungulates and domestic sheep displayed low overlap in their daily activity rhythms potentially indicating temporal ecological niche differentiation. The results suggest that temporal isolation might be a strategy for wild ungulates to avoid domestic sheep and reduce interspecific competition, and that temporal ecological niche differentiation potentially promoted the coexistence among the studied sympatric ungulates. This understanding may provide new insights for the development of targeted conservation strategies.

Fuzheng Touxie Jiedu Huayu Decoction inhibits the MexAB-OprM efflux pump and Quorum Sensing-mediated biofilm formation in difficult-to-treat multidrug resistance Pseudomonas aeruginosa.

ETHNOPHARMACOLOGICAL RELEVANCE: Fuzheng Touxie Jiedu Huayu Decoction (FTJHD) is a commonly used clinical formula that has been found effective in resisting multidrug resistance-Pseudomonas aeruginosa in previous in vivo and in vitro studies. AIM OF THE STUDY: To investigate the antimicrobial effects of FTJHD and its drug-containing serum alone or in combination with ceftazidime on difficult-to-treat multidrug resistance-P. aeruginosa (DTMDR-P. aeruginosa). MATERIALS AND METHODS: The antibacterial effects of FTJHD and its drug-containing alone or in combination with ceftazidime against DTMDR-P. aeruginosa were examined by the tube dilution method and bacterial growth curves. The changes in the bacterial ultrastructure were examined by transmission electron microscopy. The biofilm formation ability of bacteria was examined by crystal violet staining and scanning electron microscopy. The expression of the MexAB-OprM efflux pump and quorum sensing system genes were validated through quantitative polymerase chain reaction. Molecular docking was used to evaluate the interaction between active components and the MexAB-OprM efflux pump. RESULTS: FTJHD-containing serums at 1-, 2-, 4-, and 8-fold concentrations reduced the minimal inhibitory concentration (MIC) of ceftazidime against DTMDR-P. aeruginosa from 128 µg/mL to 64 µg/mL. Sub-inhibitory concentrations of ceftazidime in combination with FTJHD and FTJHD-containing serum prolonged the lag period of bacterial growth and reduced bacterial numbers. Additionally, 1/2 MIC of ceftazidime combined with FTJHD-containing serum significantly inhibited the activity of the MexAB-OprM efflux pump and quorum sensing system, thus reducing biofilm formation while causing more severe damage to the bacteria. Molecular docking revealed a strong affinity of quercetin, baicalein, luteolin, kaempferol, and ß-sitosterol for the efflux pump regulatory proteins OprM and MexR. CONCLUSION: FTJHD can exert synergistic anti-DTMDR-P. aeruginosa effects with ceftazidime by inhibiting biofilm formation mediated by the MexAB-OprM efflux pump and quorum sensing.

Early-onset and later-onset cancer: trends, risk factors, and prevention in Northern China.

The characteristics of early-onset (onset age <50 years) and later-onset (onset age ≽ 50 years) cancers differ significantly. Identifying novel risk factors for both types of cancer is crucial for increasing awareness of cancer prevention and for reducing its burden. This study aimed to analyze the trends in incidence and risk factors for early-onset and late-onset cancers. We conducted a prospective study by drawing data from the Kailuan Study. This study included 6,741 participants with cancer (624 with early-onset cancer and 6,117 with later-onset cancer) and 6,780 matched controls among the 186,249 participants who underwent Kailuan health examinations from 2006 to 2019. The primary outcomes were cancer incidence rates, and associated risk factors for early- and later-onset cancer. Weighted Cox regression was used to calculate hazard ratios and 95% confidence intervals of each exposure factor for early- and later-onset cancer by cancer type. Population-attributable risk proportions were used to estimate the number of cases that could be prevented by eliminating a risk factor from the population. Except for liver cancer, incidence rates for nearly all types of cancer increased during the study period. Smoking, alcohol consumption, lipid metabolism disorders, hypertension, diabetes mellitus, fatty liver, and inflammation were associated with a significantly increased risk of cancer at multiple sites, but risk factors for cancer incidence differed by site. Smoking, alcohol consumption, inflammation, and hypertension were the major contributors to preventable cancer. The incidence of several different types of cancer, including early-onset cancer, is increasing in northeastern China. Differences in risk factors between early-onset and later-onset malignancies may contribute to the divergence in the observed changes in incidence trends between these two specific types of cancer.

Anthropometrics and cancer prognosis: a multi-center cohort study.

BACKGROUND: Anthropometric indicators have been shown to be associated with the prognosis of patients with cancer. However, any single anthropometric index has limitation in predicting the prognosis. OBJECTIVE: This study aimed to observe the predictive role of seven anthropometric indicators based on body size on the prognosis of patients with cancer. DESIGN: A principal component analysis (PCA) on seven anthropometric measurements: height, weight, body mass index (BMI), hand grip strength (HGS), triceps skinfold thickness (TSF), mid-upper arm circumference (MAC), and calf circumference (CAC) was conducted. Principal components (PCs) were derived from this analysis. Cox regression analysis was used to investigate the association between the prognosis of patients with cancer and the PCs. Subgroups and sensitivity analyses were also conducted. RESULTS: Through PCA, four distinct PCs were identified, collectively explaining 88.3% of the variance. PC1, primarily characterized by general obesity, exhibited a significant inverse association with the risk of cancer death (adjusted HR=0.86, 95% CI (0.83, 0.88)). PC2 (short stature with high TSF) was not significantly associated with cancer prognosis. PC3 (high BMI coupled with low HGS) demonstrated a significant increase with the risk of cancer-related death (adjusted HR=1.08, 95% CI (1.05, 1.11)). PC4 (tall stature with high TSF) exhibited a significant association with increased cancer risk (adjusted HR=1.05, 95% CI (1.02, 1.07)). These associations varied across different cancer stages. The stability of the results was confirmed through sensitivity analyses. CONCLUSION: Different body sizes are associated with distinct prognostic outcomes in patients with cancer. The impact of BMI on prognosis is influenced by both HGS and subcutaneous fat. This finding may influence the clinical care of cancer and improve the survival of cancer patients.

A Small Wave Missed in Wide Complex Tachycardia.

This case report describes a patient in their 60s with intermittent palpitation, weakness, and irregular cardiac rhythm.

Deciphering the folate puzzle: Unraveling the impact of genetic variations and metabolites on cancer risk.

The C677T polymorphism in the MTHFR gene and its role in folate metabolism, impacting serum folate metabolites like THF and 5-MTHF, is a critical but underexplored area in cancer research. This nested case-control study utilized data from CHHRS, involving 87,492 hypertensive adults without prior cancer. During a median of 2.02 years, we identified 1332 cancer cases and matched controls based on age, sex, and residency. Serum levels of folate, THF, and 5-MTHF were measured, and the MTHFR C677T gene polymorphism was considered. Statistical analyses included restricted cubic spline regression and conditional logistic regression models. Serum THF levels were inversely associated with overall cancer risk (ORper SD = 0.90, 95% CI = 0.82-0.99), while 5-MTHF levels showed a negative association in the general cohort (ORQ3 vs. Q1 = 0.76, 95% CI = 0.60-0.96; ORQ4 vs. Q1 = 0.75, 95% CI = 0.58-0.98) and in individuals with MTHFR C677T (CC + CT) polymorphism (ORper SD = 0.87, 95% CI = 0.77-0.99; ORQ4 VS. Q1 = 0.79, 95% CI = 0.61-0.98), but a positive association in the MTHFR C677T (TT) subgroup (ORper SD = 1.89, 95% CI = 1.02-3.72; ORQ4 VS. Q1 = 2.17, 95% CI = 1.06-8.21). The impact of folate, THF, and 5-MTHF on cancer risk varied significantly across different cancer types and MTHFR C677T genotypes. This study provides novel insights into the variable effects of folate and its metabolites on cancer risk, influenced by genetic factors like the MTHFR C677T polymorphism and cancer type.

Leveraging existing 16S rRNA gene surveys to decipher microbial signatures and dysbiosis in cervical carcinogenesis.

The presence of dysbiotic cervicovaginal microbiota has been observed to be linked to the persistent development of cervical carcinogenesis mediated by the human papillomavirus (HPV). Nevertheless, the characteristics of the cervical microbiome in individuals diagnosed with cervical cancer (CC) are still not well understood. Comprehensive analysis was conducted by re-analyzing the cervical 16S rRNA sequencing datasets of a total of 507 samples from six previously published studies. We observed significant alpha and beta diversity differences in between CC, cervical intraepithelial neoplasia (CIN) and normal controls (NC), but not between HPV and NC in the combined dataset. Meta-analysis revealed that opportunistic pernicious microbes Streptococcus, Fusobacterium, Pseudomonas and Anaerococcus were enriched in CC, while Lactobacillus was depleted compared to NC. Members of Gardnerella, Sneathia, Pseudomonas, and Fannyhessea have significantly increased relative abundance compared to other bacteria in the CIN group. Five newly identified bacterial genera were found to differentiate CC from NC, with an area under the curve (AUC) of 0.8947. Moreover, co-occurrence network analysis showed that the most commonly encountered Lactobacillus was strongly negatively correlated with Prevotella. Overall, our study identified a set of potential biomarkers for CC from samples across different geographic regions. Our meta-analysis provided significant insights into the characteristics of dysbiotic cervicovaginal microbiota undergoing CC, which may lead to the development of noninvasive CC diagnostic tools and therapeutic interventions.

Learning Micro-C from Hi-C with diffusion models.

In the last few years, Micro-C has shown itself as an improved alternative to Hi-C. It replaced the restriction enzymes in Hi-C assays with micrococcal nuclease (MNase), resulting in capturing nucleosome resolution chromatin interactions. The signal-to-noise improvement of Micro-C allows it to detect more chromatin loops than high-resolution Hi-C. However, compared with massive Hi-C datasets available in the literature, there are only a limited number of Micro-C datasets. To take full advantage of these Hi-C datasets, we present HiC2MicroC, a computational method learning and then predicting Micro-C from Hi-C based on the denoising diffusion probabilistic models (DDPM). We trained our DDPM and other regression models in human foreskin fibroblast (HFFc6) cell line and evaluated these methods in six different cell types at 5-kb and 1-kb resolution. Our evaluations demonstrate that both HiC2MicroC and regression methods can markedly improve Hi-C towards Micro-C, and our DDPM-based HiC2MicroC outperforms regression in various terms. First, HiC2MicroC successfully recovers most of the Micro-C loops even those not detected in Hi-C maps. Second, a majority of the HiC2MicroC-recovered loops anchor CTCF binding sites in a convergent orientation. Third, HiC2MicroC loops share genomic and epigenetic properties with Micro-C loops, including linking promoters and enhancers, and their anchors are enriched for structural proteins (CTCF and cohesin) and histone modifications. Lastly, we find our recovered loops are also consistent with the loops identified from promoter capture Micro-C (PCMicro-C) and Chromatin Interaction Analysis by Paired-End Tag Sequencing (ChIA-PET). Overall, HiC2MicroC is an effective tool for further studying Hi-C data with Micro-C as a template. HiC2MicroC is publicly available at https://github.com/zwang-bioinformatics/HiC2MicroC/.

Preparation and characterization of chitosan-based corn protein composites constructed with TG enzyme and their preservation performance on strawberries.

This study describes the synthesis of Chitosan - corn protein (CSZ-TG) composites using TG enzyme (TG) as a cross-linking agent and the preparation of chitosan-based composite membrane material (CSZEO-TG) by blending citrus essential oil (EO) with the synthesized CSZ-TG. The prepared composite membrane material was used for fresh strawberry preservation and characterized by scanning electron microscopy, Fourier transform infrared spectroscopy, X-spectral diffraction, tensile properties, and water vapor and CO2 permeability. Scanning electron microscopy results showed a smooth surface of the composite membrane material after the addition of TG enzyme, while Fourier transforms infrared spectroscopy results showed a structural change of the composite membrane material after the addition of corn protein (Z). The tensile results showed an increase in the tensile strength of the composite membrane material after the addition of TG enzyme, while the flexibility of the composite membrane material was enhanced after the addition of EO. Compared with the pure chitosan membrane (CS), the water vapor and CO2 barrier properties of the composite membrane material after the addition of Z, TG, and EO did not change much, and they all showed better water vapor barrier properties. The results of the antioxidant analysis of the solution of the CSZEO-TG composite membrane material showed that the composite membrane material had efficient antioxidant properties. The effects of the composite film material on the storage period and quality of strawberries were evaluated by the indicators of weight loss, hardness, decay rate, soluble solids, titratable acid content, MDA content, and the content of four enzymes, SOD, POD, PPO and CAT. Comprehensive freshness data analysis showed that CSZEO-TG had the best freshness preservation performance and effectively extended the shelf life of strawberries.

Cardiovascular adverse events associated with immune checkpoint inhibitors: A retrospective multicenter cohort study.

BACKGROUND: Over the past decade, immune checkpoint inhibitors (ICIs) have significantly transformed cancer treatment. However, ICIs inevitably may cause a spectrum of immune-related adverse events, among which cardiovascular toxicity, particularly myocarditis, while infrequent, has garnered increasing attention due to its high fatality rate. METHODS: We conducted a multicenter retrospective study to characterize ICI-associated cardiovascular adverse events. Logistic regression was performed to explore the risk factors for the development of myocarditis and severe myocarditis. Receiver operating characteristic curves were conducted to assess the diagnostic abilities of cardiac biomarkers to distinguish different cardiovascular toxicities, and the performance and calibration were evaluated using Hosmer-Lemeshow test. RESULTS: Forty-four patients were identified, including thirty-five myocarditis, five heart failure, three arrhythmias, and one myocardial infarction. Compared with other patients, myocarditis patients had higher cardiac troponin-I (cTnI) levels (p < 0.001), higher creatine kinase levels (p = 0.003), higher creatine kinase isoenzyme-MB (CK-MB) levels (p = 0.013), and shorter time to the incidence of adverse cardiovascular events (p = 0.022) after ICI treatment. Twenty-one patients (60%) were classified as severe myocarditis, and they presented higher cardiac troponin I (cTnI) levels (p = 0.013), higher N-terminal pro-B-type natriuretic peptide levels (p = 0.031), higher creatine kinase levels (p = 0.018), higher CK-MB levels (p = 0.026), and higher neutrophil to lymphocyte ratio (NLR) levels (p = 0.016) compared to non-severe myocarditis patients after ICI treatment. Multivariate logistic regression showed that CK-MB (adjusted odds ratio [OR]: 1.775, 95% confidence interval [CI]: 1.055-2.984, p = 0.031) was the independent risk factor of the development of ICI-associated myocarditis, and cTnI (adjusted OR: 1.021, 95% CI: 1.002-1.039, p = 0.03) and NLR (adjusted OR: 1.890, 95% CI: 1.026-3.483, p = 0.041) were the independent risk factors of ICI-associated severe myocarditis. The receiver operating characteristic curve showed an area under curve of 0.785 (95% CI: 0.642 to 0.928, p = 0.013) for CK-MB, 0.765 (95% CI: 0.601 to 0.929, p = 0.013) for cTnI, and 0.773 for NLR (95% CI: 0.597 to 0.948, p = 0.016). CONCLUSIONS: Elevated CK-MB after ICI treatment is the independent risk factor for the incidence of ICI-associated myocarditis, and elevated cTnI and NLR after ICI treatment are the independent risk factors for the development of ICI-associated severe myocarditis. CK-MB, cTnI, and NLR demonstrated a promising predictive utility for the identification of ICI-associated myocarditis and severe myocarditis.

Understanding the Disparities of PM2.5 Air Pollution in Urban Areas via Deep Support Vector Regression.

In densely populated urban areas, PM2.5 has a direct impact on the health and quality of residents' life. Thus, understanding the disparities of PM2.5 is crucial for ensuring urban sustainability and public health. Traditional prediction models often overlook the spillover effects within urban areas and the complexity of the data, leading to inaccurate spatial predictions of PM2.5. We propose Deep Support Vector Regression (DSVR) that models the urban areas as a graph, with grid center points as the nodes and the connections between grids as the edges. Nature and human activity features of each grid are initialized as the representation of each node. Based on the graph, DSVR uses random diffusion-based deep learning to quantify the spillover effects of PM2.5. It leverages random walk to uncover more extensive spillover relationships between nodes, thereby capturing both the local and nonlocal spillover effects of PM2.5. And then it engages in predictive learning using the feature vectors that encapsulate spillover effects, enhancing the understanding of PM2.5 disparities and connections across different regions. By applying our proposed model in the northern region of New York for predictive performance analysis, we found that DSVR consistently outperforms other models. During periods of PM2.5 surges, the R-square of DSVR reaches as high as 0.729, outperforming non-spillover models by 2.5 to 5.7 times and traditional spatial metric models by 2.2 to 4.6 times. Therefore, our proposed model holds significant importance for understanding disparities of PM2.5 air pollution in urban areas, taking the first steps toward a new method that considers both the spillover effects and nonlinear feature of data for prediction.

Association of inflammatory markers based on routine blood with prognosis in patients underwent percutaneous coronary intervention.

Inflammation contributes to the pathophysiological processes of coronary artery disease. We evaluated the association between inflammatory biomarkers, neutrophil-to-lymphocyte ratio (NLR), red cell distribution width (RDW), systemic inflammatory index, platelet-lymphocyte ratio, and 1-year all-cause mortality in patients underwent percutaneous coronary intervention (PCI). In this retrospective cohort, we consecutively enrolled 4651 patients who underwent PCI. Baseline demographic details, clinical data, and laboratory parameters on admission were analyzed. The primary outcome was 1-year all-cause mortality after PCI. We performed Cox regression and restricted cubic spline analysis to assessed the association between the inflammatory biomarkers and the clinical outcome. The area under the curve from receiver operating characteristic analysis was determined for the ability to classify mortality outcomes. A total of 4651 patients were included. Of these, 198 (4.26%) died on follow-up. Univariate Cox regression showed that NLR (heart rate [HR]: 1.070, 95% confidence interval [CI]: 1.060-1.082, P < .001), RDW (HR: 1.441, 95% CI 1.368-1.518, P < .001), systemic inflammatory index (HR: 1.000, 95% CI 1.000-3.180, P < .001), platelet-lymphocyte ratio (HR: 3.812, 95% CI 1.901-3.364, P < .001) were significant predictors of 1-year all-cause mortality. After adjusting for other confounders in multivariate analysis, NLR (HR: 01.038, 95% CI 1.022-1.054, P < .001) and RDW (HR: 1.437, 95% CI 1.346-1.535, P < .001) remained significant predictors. Restricted cubic spline analysis showed the relationship between RDW, NLR, and 1-year all-cause mortality was linear after adjusting for the covariables (P for non-linearity < 0.001). The multivariable adjusted model led to improvement in the area under the curve to 0.83 (P < .05). Nomogram was created to predict the probability of 1 year mortality. Among the laboratory indices, RDW and NLR showed the best performance for mortality risk prediction. Multivariate predictive models significantly improved risk stratification.

Involvement of Chemosensory Protein CrufCSP3 in Perception of the Host Location in a Parasitic Wasp Cotesia ruficrus.

Chemosensory proteins (CSPs) constitute a class of olfactory proteins localized in insect sensory organs that serve a crucial function in decoding external chemical stimuli. This study aims to elucidate the involvement of CrufCSP3 in olfactory perception within the context of Cotesia ruficrus, an indigenous endoparasitoid targeting the invasive pest Spodoptera frugiperda. Through fluorescence-competitive binding assays and site-directed mutagenesis, we pinpointed four amino acids as pivotal residues involved in the interaction between CrufCSP3 and five host-related compounds. Subsequent RNA interference experiments targeting CrufCSP3 unveiled a reduced sensitivity to specific host-related compounds and a decline in the parasitism rate of the FAW larvae. These findings unequivocally indicate the essential role of CrufCSP3 in the chemoreception process of C. ruficrus. Consequently, our study not only sheds light on the functional importance of CSPs in parasitic wasp behavior but also contributes to the development of eco-friendly and efficacious wasp behavior modifiers for effectively mitigating pest population surges.

A "food insecurity poverty line" to replace the official threshold in Canadian rural and urban settings? A single-person household perspective.

Household food insecurity is associated with both low income and high cost of living, it is a potentially better measure for consumption compared to income. We use data on food insecurity and income from 10 years of the Canadian Community Health Survey (2007-2017) of single-person households (n = 145,044) to estimate the probability of being food insecure at the Canadian poverty thresholds (Market Basket Measure thresholds, or MBMs), and determine the income required to reach that probability in each MBM region, aggregated by province and rural/urban status. A regression model shows the probability of being food insecure at the MBM is approximately 30% which we call the Food Insecurity Poverty Line (FIPL). The income required to meet the FIPL is substantially different from the MBM, sometimes 1.25 times the MBM. This implies that food insecurity is a potential sentinel measure for poverty.

Glycerol Triacetate-Based Flame Retardant High-Temperature Electrolyte for the Lithium-Ion Battery.

Rechargeable batteries that can operate at elevated temperatures (>70 °C) with high energy density are long-awaited for industrial applications including mining, grid stabilization, naval, aerospace, and medical devices. However, the safety, cycle life, energy density, and cost of the available high-temperature battery technologies remain an obstacle primarily owing to the limited electrolyte options available. We introduce a flame-retardant electrolyte that can enable stable battery cycling at 100 °C by incorporating triacetin into the electrolyte system. Triacetin has excellent chemical stability with lithium metal, and conventional cathode materials can effectively reduce parasitic reactions and promises a good battery performance at elevated temperatures. Our findings reveal that Li-metal half-cells can be made that have high energy density, high Coulombic efficiency, and good cycle life with triacetin-based electrolytes and three different cathode chemistries. Moreover, the nail penetration test in a commercial-scale pouch battery using this new electrolyte demonstrated suppressed heat generation when the cell was damaged and excellent safety when using the triacetin-based electrolyte.

Dual-Step Redox Engineering of 2D CoNi-Alloy Embedded B, N-Doped Carbon Layers Toward Tunable Electromagnetic Wave Absorption and Light-Weight Infrared Stealth Heat Insulation Devices.

2D layered metallic graphite composites are promising electromagnetic wave absorption materials (EWAMs) for their combined properties of abundant interlayer free spaces, rich metallic polarized sites, and high conductivity, but the controllable synthesis remains rather challenging. Herein, a dual-step redox engineering strategy is developed by employing cobalt boron imidazolate framework (Co-BIF) to construct 2D CoNi-alloy embedded B, N-doped carbon layers (2D-CNC) as a promising EWAM. In the first step, a chemical etching oxidation process on Co-BIF is used to obtain an optimized 2D-CoNi-layered double hydroxide (2D-CoNi-LDH) intermediate and in the second, high-temperature calcination reduction is implemented to modify graphitization of the degree of the 2D-CNC. The obtained sample delivers superior reflection loss (RLmin) of -60.1 dB and wide effective absorption bandwidth (EAB) of 6.24 GHz. The synergy mechanisms of interfacial/dipole polarization and magnetic coupling are in-depth evidenced by the hologram and Lorentz electron microscopy, revealing its significant contribution on multireflection and impedance matching. Further theoretical evaluation by COMSOL simulation in different fields based on the dynamic loss process toward the test ring reveals the in situ EW attenuation process. This work presents a strategy to develop multifunctional light-weight infrared stealthy aerogel with superior pressure-resistant, anti-corrosion, and heat-insulating properties for future applications.