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Abstract Modern lens designs are capable of resolving greater than 10 gigapixels, while advances in camera frame-rate and hyperspectral imaging have made data acquisition rates of Terapixel/second a real possibility. The main bottlenecks preventing such high data-rate systems are power consumption and data storage. In this work, we show that analog photonic encoders could address this challenge, enabling high-speed image compression using orders-of-magnitude lower power than digital electronics. Our approach relies on a silicon-photonics front-end to compress raw image data, foregoing energy-intensive image conditioning and reducing data storage requirements. The compression scheme uses a passive disordered photonic structure to perform kernel-type random projections of the raw image data with minimal power consumption and low latency. A back-end neural network can then reconstruct the original images with structural similarity exceeding 90%. This scheme has the potential to process data streams exceeding Terapixel/second using less than 100 fJ/pixel, providing a path to ultra-high-resolution data and image acquisition systems.

Alzheimer's disease (AD), the major cause of dementia, is a multifactoral progressive neurodegenerative disorder that currently affects over 43 million people worldwide. The interaction betweengenetic and environmental factors decides pathogenesis and pathological development. The chemical drugs designed for clinical applications on AD have not reached the expected preventive effect so far.Here, we obtained a new evodiamine (Evo) derivative, LE-42, which exhibited lower cytotoxicity in SH-SY5Y cells and HepaG2 cells than that of Evo. The LD50 of LE-42 in SH-SY5Y cells and HepaG2 cells was increased by 9 folds and 14 folds than Evo, respectively. The LE-42 also exhibited much more potent effects on anti-oxidation and anti-cytotoxicity of AβOs than Evo. The LE-42 significantly improved the working memory, spatial learning, and memory of the 3×Tg AD mice, and the pharmacodynamic dose of LE-42 on AD mice was increased by 500 folds than that of Evo. LE-42 significantly improved the Tau hyperphosphorylation, a typical pathological feature in 3×Tg AD mice. The LE-42 restored the JAK2/STAT3 pathway's dysfunction and upregulated the expression of GluN1, GluA2, SYN, and PSD95, subsequentially improving the synaptic integrity in 3×Tg mice. The activation of the JAK2/STAT3 axis by LE-42 was a possible mechanism for a therapeutic effect on the AD mice.

Background Insulin resistance (IR) is closely linked to cardiometabolic diseases. Preventing and improving IR in nondiabetic populations is critically important. We aimed to investigate the relationship between Life's Essential 8 (LE8), the latest tool from the American Heart Association quantifying cardiovascular health, and IR among nondiabetic populations in the United States. Methods and Results This cross‐sectional study used data on 11 246 nondiabetic adults aged ≥20 years from the 2005 to 2018 the National Health and Nutrition Examination Survey. The LE8 score was classified into 2 subscale scores: health factor score and health behavior score. IR was measured by homeostasis model assessment of insulin resistance (HOMA‐IR). Weighted logistic and linear regression models analyzed associations among the LE8 score, health behavior score, health factor score, and IR. Restricted cubic spline models assessed dose–response relationships. Adjusted subgroup analyses and inverse probability of treatment weighting method also evaluated the LE8‐IR relationship. Of the 11 246 participants, 4860 (43.2%) had IR. The mean LE8 score was 70.07 (95% CI, 69.57–70.58). In fully adjusted models, higher LE8 scores were associated with lower IR odds (odds ratio per 10‐unit increase, 0.57 [95% CI, 0.54–0.61]). Nonlinear LE8‐IR dose–response was observed. Similar patterns were seen for health behavior and health factor subscores, with stronger IR correlations for health factors. The inverse LE8‐IR association was significantly more pronounced among White participants and those with higher education, higher income, and without hypertension, cardiovascular disease, or chronic kidney disease. Significant negative LE8‐IR associations persisted after inverse probability of treatment weighting. Conclusions LE8 and subscale scores are negatively associated with IR in a nonlinear relationship. Promoting optimal cardiovascular health adherence may improve IR in nondiabetic populations.

Abstract Background Findings from earlier research have established that insulin resistance (IR) is implicated in atherosclerosis progression, representing a noteworthy risk factor for cardiovascular disease (CVD). Recently, the triglyceride glucose-body mass index (TyG-BMI) has been introduced as a straightforward and robust alternative indicator for early detection of IR. Nevertheless, there is a scarcity of studies that have examined the capability of TyG-BMI for predicting incident CVD. Consequently, the core objective of this study was to determine whether the cumulative average TyG-BMI correlated with CVD incidence. Methods All data was sourced from the China Health and Retirement Longitudinal Study (CHARLS). The exposure was the cumulative average TyG-BMI, determined by the average of TyG-BMI values for the baseline and follow-up investigations (Wave 1 in 2011, Wave 3 in 2015, respectively). The calculation of TyG-BMI involved a combination of triglyceride, fasting blood glucose, and body mass index. The primary outcome was incident CVD. Logistic regression analyses as well as restricted cubic spline (RCS) regression analyses were performed for examining the association between the cumulative average TyG-BMI and CVD incidence. Results In all, 5,418 participants were enrolled in our analysis, with 2,904 (53.6%) being female, and a mean (standard deviation, SD) age of 59.6 (8.8) years. The mean (SD) cumulative average TyG-BMI among all participants was 204.9 (35.7). Totally, during a 4-year follow-up, 543 (10.0%) participants developed CVD. The fully adjusted logistic regression analysis revealed a significant association between the cumulative average TyG-BMI and incident CVD [odds ratio (OR), 95% confidence interval (CI): 1.168, 1.040–1.310, per 1 SD increase]. The RCS regression analysis displayed a positive, linear association of the cumulative average TyG-BMI with CVD incidence (P for overall = 0.038, P for nonlinear = 0.436). Conclusions Our study revealed a noteworthy correlation between the cumulative average TyG-BMI and incident CVD among the middle-aged and older population. The cumulative average TyG-BMI emerges as a valuable tool that may enhance the primary prevention and treatment of CVD.

Infrared small target detection refers to the extraction of small targets in a complex, low signal-to-noise ratio background. Depthwise convolution makes it difficult to comprehensively characterize small infrared targets and ignores the importance of image background for the detection task. In this article, we propose the generative adversarial differential analysis (GADA) model for infrared small target detection, the core of which aims to weaken the reliance on target features and enhance the use of background information. Specifically, we first construct pseudobackground labels by the fast marching method. Then, the background-guided generative adversarial network is used to learn the background data distribution. On this basis, the differential image containing interest regions of small targets is obtained by differential analysis. Finally, the detection results are obtained by performing an elaborate characterization of the interest regions. The effectiveness of GADA is verified with three public datasets. Compared to several state-of-the-art methods, GADA achieves better performance in terms of $F1$, $IoU$, and $AUC$.

Abstract Background Increased susceptibility to malnutrition and inadequate glycemic control are frequently observed in diabetic patients with coronary artery disease. The assessment of malnutrition is performed using the prognosis nutritional index (PNI). The inadequate glycemic control is measured using glycated hemoglobin (HbA1c). However, the combined effect of PNI and HbA1c on the prognosis in diabetic patients with coronary artery disease remains unknown. Methods A study was conducted at Beijing Anzhen Hospital and included 2,005 patients diagnosed with type 2 diabetes mellitus (T2DM) accompanied by acute coronary syndrome (ACS) who underwent percutaneous coronary intervention (PCI) from September 2021 to January 2022. Based on the median PNI and HbA1c, we categorized the patients into four groups including high (H)-PNI/low (L)-HbA1c, H-PNI/H-HbA1c, L-PNI/L-HbA1c, and L-PNI/H-HbA1c. Major adverse cardiac and cerebrovascular events (MACCE) were the primary outcome, including all-cause mortality, nonfatal myocardial infarction (MI), and nonfatal strokes. Results Throughout a median follow-up of 16.3 months, 73 patients had MACCE, which comprised 36 cases of all-cause mortality. In comparison to the H-PNI, the L-PNI showed an obvious rise in MACCE and all-cause mortality (log-rank P = 0.048 and 0.021, respectively) among the H-HbA1c group. Compared to the other groups, the L-PNI/H-HbA1c group exhibited the greatest risk of MACCE (adjusted hazard ratio [aHR]: 2.50, 95% confidence interval [CI] 1.20–5.23, P = 0.014) and all-cause mortality (HR: 3.20, 95% CI 1.04–9.82, P = 0.042). With the addition of PNI, MACCE and all-cause mortality prediction models performed significantly better in patients with ACS and T2DM after PCI, particularly in those with H-HbA1c levels. Conclusions The combination of L-PNI and H-HbA1c is a prognostic marker for MACCE and all-cause mortality in patients diagnosed with ACS and T2DM who underwent PCI. The PNI can serve as an assessment tool of malnutrition in patients with ACS and T2DM accompanied by H-HbA1c who underwent PCI. Therefore, monitoring the long-term change of the PNI deserves attention in clinical practice.

Abstract Background The epididymis is a highly regionalized tubular organ possesses vectorial functions of sperm concentration, maturation, transport, and storage. The epididymis-expressed genes and proteins are characterized by regional and developmental dependent pattern. However, a systematic and comprehensive insight into the postnatal development dependent changes in gene and protein expressions of porcine epididymis is still lacking. Here, the RNA and protein of epididymis of Duroc pigs at different postnatal development stages were extracted by using commercial RNeasy Midi kit and extraction buffer (7 M Urea, 2 M thiourea, 3% CHAPS, and 1 mM PMSF) combined with sonication, respectively, which were further subjected to transcriptomic and proteomic profiling. Results Transcriptome analysis indicated that 198 and 163 differentially expressed genes (DEGs) were continuously up-regulated and down-regulated along with postnatal development stage changes, respectively. Most of the up-regulated DEGs linked to functions of endoplasmic reticulum and lysosome, while the down-regulated DEGs mainly related to molecular process of extracellular matrix. Moreover, the following key genes INSIG1, PGRMC1, NPC2, GBA, MMP2, MMP14, SFRP1, ELN, WNT-2, COL3A1, and SPARC were highlighted. A total of 49 differentially expressed proteins (DEPs) corresponding to postnatal development stages changes were uncovered by the proteome analysis. Several key proteins ACSL3 and ACADM, VDAC1 and VDAC2, and KNG1, SERPINB1, C3, and TF implicated in fatty acid metabolism, voltage-gated ion channel assembly, and apoptotic and immune processes were emphasized. In the integrative network, the key genes and proteins formed different clusters and showed strong interactions. Additionally, NPC2, COL3A1, C3, and VDAC1 are located at the hub position in each cluster. Conclusions The identified postnatal development dependent genes and proteins in the present study will pave the way for shedding light on the molecular basis of porcine epididymis functions and are useful for further studies on the specific regulation mechanisms responsible for epididymal sperm maturation.

The Internet of Things (IoT) serves as a crucial element in interconnecting diverse devices within the realm of smart technology. However, the energy consumption of IoT technology has become a notable challenge and an area of interest for researchers. With the aim of achieving an IoT with low power consumption, green IoT has been introduced. The use of unmanned aerial vehicles (UAVs) represents a highly innovative approach for creating a sustainable green IoT network. UAVs offer advantages in terms of flexibility, mobility, and cost. Moreover, device-to-device (D2D) communication is essential in emergency communications, due to its ability to support direct communication between devices. The intelligent reflecting surface (IRS) is also a hopeful technology which reconstructs the radio propagation environment and provides a possible solution to reduce co-channel interference resulting from spectrum sharing for D2D communications. The investigation in this paper hence focuses on energy-efficient UAV-IRS-assisted D2D communications for green IoT. In particular, a problem of optimization aimed at maximizing the system’s average energy efficiency (EE) is formulated, firstly, by simultaneously optimizing the power coefficients of all D2D transmitters, the UAV’s trajectory, and the base station (BS)’s active beamforming, along with the IRS’s phase shifts. Second, to address the problem, we develop a multi-agent twin delayed deep deterministic policy gradient (MATD3)-based scheme to find a near-optimal solution, where D2D transmitters, the BS, and the UAV cooperatively learn to improve EE and suppress the interference. To conclude, numerical simulations are conducted to assess the availability of the proposed scheme, and the simulation results demonstrate that the proposed scheme surpasses the baseline approaches in both convergence speed and EE performance.

BackgroundFulminant myocarditis (FM) is a critical disease with high early mortality. Low triiodothyronine syndrome (LT3S) was a strong predictor of poor prognosis of critical diseases. This study investigated whether LT3S was associated with 30-day mortality in FM patients.MethodsNinety-six FM patients were divided into LT3S (n=39, 40%) and normal free triiodothyronine (FT3) (n=57, 60%) groups based on serum FT3 level. Univariable and multivariable logistic regression analyses were performed to identify independent predictors of 30-day mortality. Kaplan–Meier curve was used to compare 30-day mortality between two groups. Receiver operating characteristic (ROC) curve and decision curve analysis (DCA) were used to assess the value of FT3 level for 30-day mortality prediction.ResultsCompared to normal FT3 group, LT3S group had higher incidence of ventricular arrhythmias, worse hemodynamics, worse cardiac function, more severe kidney impairment, and higher 30-day mortality (48.7% vs. 12.3%, P

IntroductionPollutant gas emissions in the current production system of the livestock industry have negative influences on environment as well as the health of farm staffs and animals. Although ammonia (NH3) is considered as the primary and harmful gas pollutant in the rabbit farm, less investigation has performed to determine the toxic effects of house ammonia exposure on rabbit in the commercial confined barn.MethodsIn this study, we performed multi-omics analysis on rabbits exposed to high and low concentration of house ammonia under similar environmental conditions to unravel the alterations in nasal and colonic microbiota, pulmonary and colonic gene expression, and muscular metabolic profile.Results and discussionThe results showed that house ammonia exposure notably affected microbial structure, composition, and functional capacity in both nasal and colon, which may impact on local immune responses and inflammatory processes. Transcriptome analysis indicated that genes related to cell death (MCL1, TMBIM6, HSPB1, and CD74) and immune response (CDC42, LAMTOR5, VAMP8, and CTSB) were differentially expressed in the lung, and colonic genes associated with redox state (CAT, SELENBP1, GLUD1, and ALDH1A1) were significantly up-regulated. Several key differentially abundant metabolites such as L-glutamic acid, L-glutamine, L-ornithine, oxoglutaric acid, and isocitric acid were identified in muscle metabolome, which could denote house ammonia exposure perturbed amino acids, nucleotides, and energy metabolism. In addition, the widespread and strong inter-system interplay were uncovered in the integrative correlation network, and central features were confirmed by in vitro experiments. Our findings disclose the comprehensive evidence for the deleterious effects of house ammonia exposure on rabbit and provide valuable information for understanding the underlying impairment mechanisms.

In this study, we investigated the variations in production performance, health status, and gut microbiota of meat rabbits raised in the semi-confined barn during summer and winter. Compared to summer, rabbits reared in winter possessed significantly higher slaughter weight and carcass weight. Rabbits fed in the summer were more vulnerable to different stressors, which led to increased protein levels of HSP90, IL-1α, IL-1β, IL-2, and concentrations of MDA, but declined GSH and SOD activities. Additionally, significant differences in gut microbial communities were observed. Compared to the winter, rabbits fed in the summer had significantly lower and higher alpha and beta diversity. Both Firmicutes and Verrucomicrobiota were the dominant phyla, and they accounted for greater proportions in the winter than in the summer. At lower microbial taxa levels, several seasonal differentially enriched microbes were identified, such as Akkermansia muciniphila, the Oscillospiraceae NK4A214 group, the Christensenellaceae R-7 group, Alistipes, and Muribaculaceae. Functional capacities linked to microbial proliferation, nutrient metabolism, and environmental adaptive responses exhibited significantly different abundances between summer and winter. Moreover, strong interactions among different indicators were presented. Based on our findings, we not only proposed several potential strategies to ameliorate the undesirable effects of seasonal changes on the productivity and health of meat rabbits but also underscored the directions for future mechanistic studies of adaptation physiology.

ObjectiveWe aimed to investigate the association between coffee consumption and frailty in older American adults. We focused on individuals at higher frailty risk, such as women, ethnic minorities, smokers, and those with obesity and insufficient physical activity.MethodsThe data of 8,087 individuals aged over 60 years from the 2007–2018 National Health and Nutrition Examination Surveys were used for this cross-sectional study. The coffee drinks were classified into two categories: caffeinated and decaffeinated. Frailty was measured using the 53-item frailty index. Weighted binary logistic regression was used to evaluate the association between coffee intake and frailty risk. Restricted cubic spline models were used to assess the dose–response relationship between caffeinated coffee intake and frailty.ResultsAmong the 8,087 participants, 2,458 (30.4%) had frailty. Compared with those who reported no coffee consumption, the odds ratios [ORs; 95% confidence intervals (CIs)] of total coffee consumption > 498.9 (g/day) were 0.65 (0.52, 0.79) in the fully adjusted model. Compared with those who reported no caffeinated coffee consumption, the ORs (95% CIs) of total coffee consumption > 488.4 (g/day) were 0.68 (0.54, 0.85) in the fully adjusted model. Compared with those who reported no decaffeinated coffee consumption, the ORs (95% CIs) of total coffee consumption > 0 (g/day) were 0.87 (0.71, 1.06) in the fully adjusted model. Nonlinear associations were detected between total coffee and caffeinated coffee consumption and frailty. In the subgroup analyses by smoking status, the association between coffee consumption and the risk of frailty was more pronounced in non-smokers (P for interaction = 0.031).ConclusionCaffeinated coffee consumption was independently and nonlinearly associated with frailty, especially in non-smokers. However, decaffeinated coffee consumption was not associated with frailty.

Alzheimer's disease (AD) is a neurodegenerative disease characterized by progressive neurodegeneration and cognitive decline. Evodiamine, a main component in Chinese medicine, was found to improve cognitive impairment in AD model mice based on several intensive studies. However, evodiamine has high cytotoxicity and poor bioactivity. In this study, several evodiamine derivatives were synthesized via heterocyclic substitution and amide introduction and screened for cytotoxicity and antioxidant capacity. Under the same concentrations, compound 4c was found to exhibit lower cytotoxicity and higher activity against H2O2 and amyloid β oligomers (AβOs) than evodiamine in vitro and significantly improve the working memory and spatial memory of 3 x Tg and APP/PS1 AD mice. Subsequent RNA sequencing and pathway enrichment analysis showed that 4c affected AD-related genes and the AMPK and insulin signaling pathways. Furthermore, we confirmed that 4c recovered PI3K/AKT/GSK3β/Tau dysfunction in vivo and in vitro. In conclusion, 4c represents a potential lead compound for AD therapy based on the recovery of PI3K/AKT/GSK3β pathway dysfunction.

BackgroundVentricular septal rupture (VSR) is a type of cardiac rupture, usually complicated by acute myocardial infarction (AMI), with a high mortality rate and often poor prognosis. The aim of our study was to investigate the factors influencing the long-term prognosis of patients with VSR from different aspects, comparing the evaluation performance of the Gensini score, Sequential Organ Failure Assessment (SOFA) score and European Heart Surgery Risk Assessment System II (EuroSCORE II) score systems.MethodsThis study retrospectively enrolled 188 patients with VSR between Dec 9, 2011 and Nov 21, 2021at the First Affiliated Hospital of Zhengzhou University. All patients were followed up until Jan 27, 2022 for clinical data, angiographic characteristics, echocardiogram outcomes, intraoperative, postoperative characteristics and major adverse cardiac events (MACEs) (30-day mortality, cardiac readmission). Cox proportional hazard regression analysis was used to explore the predictors of long-term mortality.ResultsThe median age of 188 VSR patients was 66.2 ± 9.1 years and 97 (51.6%) were males, and there were 103 (54.8%) patients in the medication group, 34 (18.1%) patients in the percutaneous transcatheter closure (TCC) group, and 51 (27.1%) patients in the surgical repair group. The average follow-up time was 857.4 days. The long-term mortality of the medically managed group, the percutaneous TCC group, and the surgical repair group was 94.2, 32.4, and 35.3%, respectively. Whether combined with cardiogenic shock (OR 0.023, 95% CI 0.001–0.054, P = 0.019), NT-pro BNP level (OR 0.027, 95% CI 0.002–0.34, P = 0.005), EuroSCORE II (OR 0.530, 95% CI 0.305–0.918, P = 0.024) and therapy group (OR 3.518, 95% CI 1.079–11.463, P = 0.037) were independently associated with long-term mortality in patients with VSR, and this seems to be independent of the therapy group. The mortality rate of surgical repair after 2 weeks of VSR was much lower than within 2 weeks (P = 0.025). The cut-off point of EuroSCORE II was determined to be 14, and there were statistically significant differences between the EuroSCORE II < 14 group and EuroSCORE II≥14 group (HR = 0.2596, 95%CI: 0.1800–0.3744, Logrank P < 0.001).ConclusionPatients with AMI combined with VSR have a poor prognosis if not treated surgically, surgical repair after 2 weeks of VSR is a better time. In addition, EuroSCORE II can be used as a scoring system to assess the prognosis of patients with VSR.

BackgroundThere is a lack of large randomized controlled trials (RCTs) that comprehensively evaluate the effects of venoarterial extracorporeal membrane oxygenation (V-A ECMO)- assisted treatment of patients with ST-segment elevation myocardial infarction (STEMI) combined with Cardiogenic shock (CS). This meta-analysis aims to identify predictors of short-term mortality, and the incidence of various complications in patients with STEMI and CS treated with V-A ECMO.MethodsWe searched PubMed, Cochrane Library, Web of Science, Embase, China National Knowledge Infrastructure (CNKI), and the Wanfang Database from 2008 to January 2022 for studies evaluating patients with STEMI and CS treated with V-A ECMO. Studies that reported on mortality in ≥ 10 adult (>18 years) patients were included. Newcastle-Ottawa Scale was used by two independent reviewers to assess methodological quality. Mantel-Haenszel models were used to pool the data for meta-analysis.ResultsSixteen studies (1,162 patients) were included with a pooled mortality estimate of 50.9%. Age > 65 years, BMI > 25 kg/m2, lactate > 8 mmol/L, anterior wall infarction, longer CPR time, and longer time from arrest to extracorporeal cardiopulmonary resuscitation (ECPR) were risk predictors of mortality. Achieving TIMI-3 flow after percutaneous coronary intervention (PCI) was a protective factor of mortality. The prevalence of bleeding, cerebral infarction, leg ischemia, and renal failure were 22, 9.9, 7.4, and 49.4%, respectively.ConclusionOur study identified Age, BMI, lactate, anterior wall infarction, TIMI-3 flow after PCI, CPR time, and time from arrest to ECPR significantly influence mortality in STEMI patients with CS requiring V-A ECMO. These factors may help clinicians to detect patients with poor prognoses earlier and develop new mortality prediction models.

BackgroundThe Global Registry of Acute Coronary Events (GRACE) score is a widely recognized tool for predicting adverse cardiovascular events in patients with non-ST-segment elevation acute coronary syndrome (NSTE-ACS). The triglyceride-glucose index (TyG index) is a new biomarker of insulin resistance and has a close association with the occurrence of adverse cardiovascular events. We investigated whether the addition of the TyG index to the GRACE score could improve prognosis prediction in patients with NSTE-ACS undergoing percutaneous coronary intervention (PCI).MethodsIn total, 515 patients with NSTE-ACS undergoing PCI were included in this retrospective study. Kaplan-Meier analysis was performed to describe the cumulative incidence of the primary endpoint based on the median TyG index. The relationship between the TyG index and GRACE score was analyzed using Spearman's rank correlation. Univariate and multivariate Cox proportional hazards analyses were used to identify independent risk factors. Based on the receiver operating characteristic curve, net reclassification improvement (NRI), integrated differentiation improvement (IDI), and decision curve analysis, the TyG index was evaluated for its predictive value when added to the GRACE score. ROC curve analyses, NRI, and IDI were used to compare the gain effect of the TyG index and the levels of HbA1C, FBG, TG, and LDL-C on the GRACE score for predicting adverse cardiovascular events.ResultsThe TyG index was an independent predictor of 2-year adverse cardiovascular events in patients with NSTE-ACS undergoing PCI. The addition of the TyG index to the GRACE score demonstrated an improved ability to predict 2-year adverse cardiovascular events compared with the GRACE score alone (AUCs: GRACE score 0.798 vs. GRACE score+TyG index 0.849, P = 0.043; NRI = 0.718, P < 0.001; IDI = 0.086, P < 0.001). The decision curve analysis suggested that the clinical net benefit of the new model (GRACE score+TyG index) was superior to that of the GRACE score alone, with a probability range of 0.04 to 0.32. When including the TyG index, HbA1C, FBG, TG, and LDL-C in the GRACE score system, we found that the TyG index had a greater incremental impact on risk prediction and stratification compared to the other parameters.ConclusionCombining the TyG index and GRACE score could improve the prediction of 2-year adverse cardiovascular events. This new risk model could identify patients with NSTE-ACS at higher risk of adverse events following PCI so that they can be monitored more carefully.

ObjectiveGastrointestinal bleeding (GIB) post acute myocardial infarction (AMI) is a severe clinical condition with a poor prognosis. The purpose of the study was to evaluate the rate of in-hospital mortality in patients with GIB post-AMI and to identify the potential risk factors of this situation.MethodsIn this single-center retrospective study, a total of 154 patients diagnosed with AMI who subsequently suffered GIB were enrolled from October 2013 to December 2021. Demographic, laboratory, and clinical data were collected. The in-hospital mortality was the outcome of interest. Logistic regression analysis was used to investigate the potential risk factors of in-hospital mortality.ResultsAmong the 154 subjects included in the final analysis, the mean age was 65.58 ± 11.20 years, and 104 (67.53%) were males. GIB occurred in 11 patients after thrombolytic therapy, 50 patients after percutaneous coronary intervention (PCI), and 93 patients during drug conservative treatment. A total of 41 patients died in the hospital. The in-hospital mortality rate of the thrombolysis group, PCI group, and drug conservative treatment group was 27.27% (3/11), 28.00% (14/50), and 25.81% (24/93), respectively. There was no difference in the in-hospital mortality among the three groups. The multivariate logistic regression analysis showed that the peak levels of TnI (OR 1.07, 95% CI 1.02–1.12, P = 0.011), condition of cardiogenic shock after admission (OR 14.52, 95% CI 3.36–62.62, P < 0.001), and the use of the mechanical ventilator (OR 8.14, 95% CI 2.03–32.59, P = 0.003) were significantly associated with in-hospital mortality.ConclusionRegardless of the treatment strategy for AMI, once GIB occurred, the prognosis was poor. High in-hospital mortality in patients with GIB post-AMI was independently associated with the peak levels of TnI, condition of cardiogenic shock, and the use of a mechanical ventilator.

Abstract Receptor tyrosine kinase (RTK) inhibitors, such as sunitinib and sorafenib, remain the first-line drugs for the treatment of mRCC. Acquired drug resistance and metastasis are the main causes of treatment failure. However, in the case of metastasis Renal Cell Cancer (mRCC), which showed a good response to sunitinib, we found that long-term treatment with sunitinib could promote lysosome biosynthesis and exocytosis, thereby triggering the metastasis of RCC. By constructing sunitinib-resistant cell lines in vivo, we confirmed that TFE3 plays a key role in the acquired resistance to sunitinib in RCC. Under the stimulation of sunitinib, TFE3 continued to enter the nucleus, promoting the expression of endoplasmic reticulum (ER) protein E-Syt1. E-Syt1 and the lysosomal membrane protein Syt7 form a heterodimer, which induces ER fragmentation, Ca2+ release, and lysosomal exocytosis. Lysosomal exocytosis has two functions: pumping sunitinib out from the cytoplasm, which promotes resistance to sunitinib in RCC, releasing cathepsin B (CTSB) into the extracellular matrix (ECM), which can degrade the ECM to enhance the invasion and metastasis ability of RCC. Our study found that although sunitinib is an effective drug for the treatment of mRCC, once RCC has acquired resistance to sunitinib, sunitinib treatment will promote metastasis.

Analog computing paradigms are promising solutions to the growing computational demands of machine learning applications. Despite being susceptible to errors, analog and mixed-signal platforms have the potential to achieve higher speed and power efficiency for artificial neural network (ANN) applications than digital computers. Driven by the development of digital fixed-point ANN accelerators, low-precision ANN models have proven to be successful in compressing the size of ANNs and conforming the models to the data format of digital accelerators. While the inputs and weights of these digital, fixed-point ANN models can have low bit widths, the intermediate results (e.g., activations) must be preserved in high precision. As a result, these digital fixed-point models and training algorithms cannot be migrated easily to analog accelerators, because the analog intermediate results typically suffer from reduced precision due to noises and device imperfections. Here, we report on a training method for mixed-signal ANNs that considers two types of analog impairments, namely, random noise and distortion (deterministic in nature). The results show that mixed-signal ANN trained with our method can achieve the same classification accuracy as the digital fixed-point model with noise levels up to 50% of the ideal quantization step size. We demonstrate our training method on a mixed-signal, convolutional neural network based on diffractive optics.

This paper presents a novel control scheme for the three-dimensional (3D) path following of underactuated Autonomous Underwater Vehicle (AUVs) subject to unknown internal and external disturbances, in term of the time scale decomposition method. As illustration, two-time scale motions are first artificially forced into the closed-loop control system, by appropriately selecting the control gain of the integrator. Using the singular perturbation theory, the integrator is considered as a fast dynamical control law that designed to shape the space configuration of fast variable. And then the stabilizing controller is designed in the reduced model independently, based on the time scale decomposition method, leading to a relatively simple control law. The stability of the resultant closed-loop system is demonstrated by constructing a composite Lyapunov function. Finally, simulation results are provided to prove the efficacy of the proposed controller for path following of underactuated AUVs under internal and external disturbances.

This article presents two new chemical plume tracing (CPT) algorithms for using on autonomous underwater vehicles (AUVs) to locate hydrothermal vents. We aim to design effective CPT navigation algorithms that direct AUVs to trace emitted hydrothermal plumes to the hydrothermal vent. Traditional CPT algorithms can be grouped into two categories, including bio-inspired and engineering-based methods, but they are limited by either search inefficiency in turbulent flow environments or high computational costs. To approach this problem, we design a new CPT algorithm by fusing traditional CPT methods. Specifically, two deep reinforcement learning (RL) algorithms, including double deep Q-network (DDQN) and deep deterministic policy gradient (DDPG), are employed to train a customized deep neural network that dynamically combines two traditional CPT algorithms during the search process. Simulation experiments show that both DDQN- and DDPG-based CPT algorithms achieve a high success rate (>90%) in either laminar or turbulent flow environments. Moreover, compared to traditional moth-inspired method, the averaged search time is improved by 67% for the DDQN- and 44% for the DDPG-based CPT algorithms in turbulent flow environments.

Abstract Background Alzheimer's disease (AD) is a complex neurodegenerative disease. Due to the complexity of its molecular pathogenesis and the interaction of the numerous factors involved, the etiology and pathogenesis of AD have not been fully elucidated. Therefore, effective treatment for AD remains to be developed. Evodiamine, a quinolone alkaloid, has been found to improve learning and memory ability to in the APPswe/PS1△E9 mouse model of dementia. However, the cytotoxicity and physicochemical properties of evodiamine have limited its use in the treatment of AD. Methods Evodiamine and its derivatives were effectively synthesized by EDCI‐mediated condensation at room temperature. These target compounds contained 1 thio‐ and 21 oxo‐evodiamine derivatives with different substituted groups. The cytotoxicity of evodiamine and its derivatives and the neuroprotective effects of the evodiamine derivatives against H2O2‐induced cell loss in SH‐SY5Y cells were investigated using the WST‐8 assay. The Morris water‐maze test was used to detect the effect of evodiamine and its derivatives on improving learning and memory in APPswe/PS1△E9 mice. Results In this study, a series of oxo‐ and thio‐evodiamine derivatives was synthesized. Several derivatives showed lower cytotoxicity and stronger neuroprotective effects than evodiamine and elicited enhanced cognitive improvement, especially in the test of spatial memory in APPswe/PS1△E9 mice. Conclusion Our study provides insights for developing novel evodiamine derivatives for chemical intervention and treatment of AD.

Signal retrieval from a series of indirect measurements is a common task in many imaging, metrology, and characterization platforms in science and engineering. Because most of the indirect measurement processes are well-described by physical models, signal retrieval can be solved with an iterative optimization that enforces measurement consistency and prior knowledge on the signal. These iterative algorithms are time-consuming and only accommodate a linear measurement process and convex signal constraints. Recently, neural networks have been widely adopted to supersede iterative methods by directly approximating the inverse mapping of the measurement process. However, such vanilla network with a deterministic multi-layer structure is unable to distinguish signal ambiguities in ill-posed measurement systems, and the retrieved signals often lack consistency with the measurement. In this work, we incorporate the known measurement process into a customized variational generative model to capture the distribution of all possible signals given a measurement, which can be either a linear or nonlinear process. Our signal retrieval framework resolves the ambiguity in the measurement process, and retrieves high-fidelity signals that satisfy the physical model in a variety of nonlinear, ill-posed systems, such as image retrieval from Fresnel hologram and ultrafast pulse retrieval.

Underwater target classification methods based on deep learning suffer from obvious model overfitting and low recognition accuracy in the case of small samples and complex underwater environments. This paper proposes a novel classification network (EfficientNet-S) based on EfficientNet-V2S. After optimization with model scaling, EfficientNet-S significantly improves the recognition accuracy of the test set. As deep learning models typically require very large datasets to train millions of model parameter, the number of underwater target echo samples is far more insufficient. We propose a deep convolutional generative adversarial network (SGAN) based on the idea of group padding and even-size convolution kernel for high-quality data augmentation. The results of anechoic pool experiments show that our algorithm effectively suppresses the overfitting phenomenon, achieves the best recognition accuracy of 92.5%, and accurately classifies underwater targets based on active echo datasets with small samples.

The long-range autonomous underwater vehicle is a new underwater vehicle with capability of stereoscopic observation of the ocean over a wide range of time series. This article proposed a novel control strategy for the long-range autonomous underwater vehicle considering the energy consumption. The vertical motion model of long-range autonomous underwater vehicle and the mathematical model of energy consumption of motion actuators are established in this article, and the maneuverability simulation experiments were carried out to analyze its motion and energy consumption characteristics. A hybrid controller based on human simulating intelligent control and S-plane control is designed. Considering the moment caused by the asymmetry of the hull in motion, an adaptive dynamic control allocation strategy is designed. Simulation experiments are conducted to demonstrate the performance of the scheme proposed.

Abstract We present a randomly disordered silica-air optical fiber featuring a 28.5% air filling fraction in the structured region, and low attenuation below 1 dB per meter at visible wavelengths. The quality of images transported through this fiber is shown to be comparable to, or even better than, that of images sent through commercial multicore imaging fiber. We demonstrate robust high-quality optical image transfer through 90 cm-long fibers with disordered silica-air structure, more than an order of magnitude improvement compared to previous disordered fiber imaging distances. The effects of variations of wavelength and feature size on transported image quality are investigated experimentally.

To meet the mission requirements of long-endurance and unmanned marine environment observation, the natural energy-driven unmanned surface vehicle (NSV) usually takes special sailing paths to increase energy capture to achieve the purpose of improving endurance. Aiming at the route planning problems of the “Wave Rider” NSV in the time-varying ocean wind field, this paper is organized as follows. Firstly, a visual modeling method of the real-time-varying ocean wind field for NSV is proposed. Then, through the wind energy capture experiment, the NSV system energy net output model is calculated, and a Dynamic Dijkstra algorithm considering wind energy capture (DW–Dijkstra) has been proposed in this paper based on a Dijkstra algorithm, of which weight function has been improved. Accordingly, the NSV long-endurance dynamic path planning method is designed. Finally, the DW–Dijkstra algorithm has been verified through a set of comparison simulations and a set of semi-physical comparison simulations. The results show that the DW–Dijkstra algorithm can plan a collision-free and high-efficiency energy capture path in the real-time-varying ocean wind field environment in the southern waters of China. Compared with the traditional A* algorithm and the Wind_A* algorithm, the proposed method can save energy by between 15.07% and 6.50%, respectively, which effectively increases the endurance of the NSV.

The three-dimensional (3D) path following problem of an underactuated autonomous underwater vehicle with ocean currents disturbances is addressed in this paper. Firstly, the motion equation under the ocean currents disturbance is established, and the dynamic model of 3D tracking error is constructed based on virtual guidance method. Then, a finite-time control scheme based on super-twisting observer and command filtered backstepping technology is proposed. We adopt super-twisting observer based on finite-time theory to observe the ocean currents disturbances for improving the system robust. A command filtered backstepping is proposed to replace the differential process in the conventional backstepping method for avoiding the differential expansion problem. The filter compensation loop is designed to ensure the accuracy of the filtered signal, and the anti-integration saturation link is designed considering the influence of integral saturation. Lyapunov stability theory is used to prove the stability of the underactuated AUV. Simulation studies are conducted to show the effectiveness and robustness of the controller.

The design, control, and implementation of an autonomous underwater vehicle (AUV) for collecting hydrological information from plateau rivers and lakes are presented in this paper. The hardware and software structures of the control system were previously described. A novel sliding mode controller (SMC) with combinational reaching law of vertical hovering motion is proposed to improve the robustness and stability. The S-plane control, a nonlinear controller with little parameters, is used in the horizontal motion. Besides, the navigation strategy based on the dead-reckoning algorithm, a path tracking based on the light-of-sight (LOS) algorithm, and a control allocation strategy considering saturation are present. Finally, experiments were performed in a tank and in a river in the Qinghai−Tibet Plateau to prove the feasibility and reliability of the AUV system.

Polarizer, as an indispensable optical element, has been widely used in various optical systems, which splits a beam into two beams of orthogonal linear polarizations. Due to the appearance of the vector optical field (VOF) and its unique properties, the vector polarizer also meets the requirement in a wide variety of applications. Here we present and demonstrate the realization of dielectric broadband vector polarizer, being in fact a liquid-crystal-based space-variant uniaxial crystal (LC-SV-UAC), which is made by a wedged thin cell adhered with space-variant photo-aligned dichroic dye films and filled with the nematic liquid crystal with a thickness of tens of microns. The vector polarizer works based on the birefringent mechanism to spatially separate the orthogonally polarized ordinary and extraordinary beams. The vector polarizers via a LC-SV-UAC have the advantages of mass-production and easy fabrication of large-size and complex structures. In particular, the high-performance broadband vector polarizers we presented and fabricated can not only flexibly tailor the polarization structures and the intensity patterns of optical fields but also act as a high-efficiency generator of VOF, and a key element for realizing the VOF laser and for fabricating the novel photon states in the future.

Bismuth oxide (Bi2O3) and its composites have good electrocatalytic performance. Quartz column is a good kind of catalyst carrier with the characteristics of high mechanical strength and good stability. A novel Bi-modified quartz column particle electrode (BQP) was prepared by the dipping-calcination method. The characterization results revealed that Bi2O3 was successfully loaded on quartz column. The optimum preparation condition was calcining at 550°C for 4 h. Electrocatalytic performance was evaluated by the degradation of phenol and the results indicated that the triclinic phase of Bi2O3 showed the best electrocatalytic property. Besides, when the dosage concentration of the particle electrode was 125 g/L and the electrolytic voltage was 12 V, the degradation rate of phenol (200 mg/L) reached the highest (94.25%), compared with 70.00% of that in two-dimensional (2D) system. In addition, the removal rate of chemical oxygen demand (COD) was 75.50%, compared with 53.30% of that in 2D system. The reusability and regeneration of BQP were investigated and the results were good. Mechanism of enhanced electrochemical oxidation by BQP was evaluated by the capture of hydroxyl radical.