Miracle-dz/UniFAR-FTUs huggingface dataset:
A Novel Approach for Multi-Lead ECG Classification Using DL-CCANet and TL-CCANet

Cardiovascular disease (CVD) has become one of the most serious diseases that threaten human health. Over the past decades, over 150 million humans have died of CVDs. Hence, timely prediction of CVDs is especially important. Currently, deep learning algorithm-based CVD diagnosis methods are extensively employed, however, most such algorithms can only utilize one-lead ECGs. Hence, the potential information in other-lead ECGs was not utilized. To address this issue, we have developed novel methods for diagnosing arrhythmia. In this work, DL-CCANet and TL-CCANet are proposed to extract abstract discriminating features from dual-lead and three-lead ECGs, respectively. Then, the linear support vector machine specializing in high-dimensional features is used as the classifier model. On the MIT-BIH database, a 95.2% overall accuracy is obtained by detecting 15 types of heartbeats using DL-CCANet. On the INCART database, overall accuracies of 94.01% (II and V1 leads), 93.90% (V1 and V5 leads) and 94.07% (II and V5 leads) are achieved by detecting seven types of heartbeat using DL-CCANet, while TL-CCANet yields a higher overall accuracy of 95.52% using the above three leads. In addition, all of the above experiments are implemented using noisy ECG data. The proposed methods have potential to be applied in the clinic and mobile devices.
Golgi Fragmentation in Neurodegenerative Diseases: Is There a Common Cause?

In most mammalian cells, the Golgi complex forms a continuous ribbon. In neurodegenerative diseases, the Golgi ribbon of a specific group of neurons is typically broken into isolated elements, a very early event which happens before clinical and other pathological symptoms become evident. It is not known whether this phenomenon is caused by mechanisms associated with cell death or if, conversely, it triggers apoptosis. When the phenomenon was studied in diseases such as Parkinson’s and Alzheimer’s or amyotrophic lateral sclerosis, it was attributed to a variety of causes, including the presence of cytoplasmatic protein aggregates, malfunctioning of intracellular traffic and/or alterations in the cytoskeleton. In the present review, we summarize the current findings related to these and other neurodegenerative diseases and try to search for clues on putative common causes.
Religious Attendance, Religious Importance, and the Pathways to Depressive Symptoms in Men and Women Aged 50 and Over Living in Ireland

Objectives: We aimed to explore the relationship between religiosity and depressive symptoms longitudinally. Method: We used four waves (2009–2016) of the Irish Longitudinal Study on Ageing (TILDA) to create growth curve models (GCM) of depressive symptoms and religious attendance/importance in a sample aged 50+ in Ireland and structural models to assess the longitudinal associations between religious attendance/importance and depressive symptoms. We tested whether this relationship was mediated by social connectedness. Results: GCM showed that higher religious attendance at baseline was associated with lower baseline depressive symptoms, while higher religious importance was associated with higher baseline depressive symptoms. Social connectedness partially mediated the baseline associations between religious attendance and lower depressive symptoms. There were no associations between religious factors and the development of depressive symptoms over time. Discussion: This study found that the relationship between religion and depressive symptoms is complex, and any protective effect was driven by religious attendance.
Evaluation of selected cardiopulmonary and perceived exertion responses to four infant carrying methods utilised by African Mothers

Abstract Various infant carrying methods (ICMs) are utilised for childcare. Effects of these ICMs on the cardiopulmonary system are not known. This study evaluated cardiopulmonary and perceptual responses to four ICMs (back, front, side and in-arms) among 30 young females (18–35 years) while walking with a 6 kg simulated infant. Diastolic blood pressure (BP) responses were significantly different (p = .009) across the four ICMs, with the back ICM eliciting highest response. Heart rate, respiratory rate and systolic BP responses were not significantly different (p > .05) across the ICMs. Participants perceived the in-arms ICM as the most exerting. Body weight (p = .036) and body mass index (BMI) (p = .011) significantly correlated with systolic BP responses during the side ICM while age significantly (p = .036) correlated with heart rate changes during the in-arms ICM. Back ICM may pose more risk of diastolic BP dysfunctions. Increased body weight and BMI result in decreased systolic BP responses. IMPACT STATEMENT What is already known on this subject? Infant carrying (IC) has been associated with increased energy cost, biomechanical changes and musculoskeletal injuries. There is paucity of data on the cardiopulmonary responses to IC. What do the results of this study add? Back ICM resulted in higher responses in diastolic blood pressure. During the side ICM, participants’ systolic BP decreased with increasing body weight and BMI values. Increased age resulted to decreased heart rate responses during the in-arms ICM. What are the implications of these findings for clinical practice and/or further research? There is need for effective monitoring of the cardiopulmonary parameters during IC tasks, especially among women with cardiopulmonary dysfunctions. Women with diastolic dysfunctions should be discouraged from utilising the back ICM. It is necessary for further studies to evaluate infant carrying-related cardiopulmonary responses relative to various components of IC practices, including weight of infant, maternal anthropometric characteristics and duration of IC tasks during each infant carrying method.
Control Synthesis of Hidden Semi-Markov Uncertain Fuzzy Systems via Observations of Hidden Modes

This paper investigates the stability analysis and fuzzy control problems for a class of discrete-time fuzzy systems with hidden semi-Markov stochastic uncertainties. The nonlinear plant is described via the Takagi–Sugeno (T–S) fuzzy model, and the parameter uncertainties are represented by a hidden semi-Markov chain. Owing to the semi-Markov kernel (SMK), the probability density functions (PDFs) of sojourn time for different modes in describing the stochastic uncertainties can address different types of distributions according to different target modes. A novel Lyapunov function that depends on the hidden mode and the observed mode with the elapsed time is proposed to analyze the stability and the <inline-formula> <tex-math notation="LaTeX">$\mathcal {H}_{\infty }$ </tex-math></inline-formula> performance of the fuzzy system. Then, the sufficient criteria for the elapsed-time-dependent and observed-mode-dependent fuzzy controller are achieved by exploiting the observations of hidden modes, ensuring that the closed-loop system is <inline-formula> <tex-math notation="LaTeX">$\sigma $ </tex-math></inline-formula>-error mean square stable with guaranteed <inline-formula> <tex-math notation="LaTeX">$\mathcal {H}_{\infty }$ </tex-math></inline-formula> performance. A cart–pendulum system is used to demonstrate the effectiveness and applicability of the proposed theoretical results.
Separate vmPFC Ensembles Control Cocaine Self-Administration Versus Extinction in Rats

Recent studies suggest that the ventral medial prefrontal cortex (vmPFC) encodes both operant drug self-administration and extinction memories. Here, we examined whether these opposing memories are encoded by distinct neuronal ensembles within the vmPFC with different outputs to the nucleus accumbens (NAc) in male and female rats. Using cocaine self-administration (3 h/d for 14 d) and extinction procedures, we demonstrated that vmPFC was similarly activated (indexed by Fos) during cocaine-seeking tests after 0 (no-extinction) or 7 extinction sessions. Selective Daun02 lesioning of the self-administration ensemble (no-extinction) decreased cocaine seeking, whereas Daun02 lesioning of the extinction ensemble increased cocaine seeking. Retrograde tracing with fluorescent cholera toxin subunit B injected into NAc combined with Fos colabeling in vmPFC indicated that vmPFC self-administration ensembles project to NAc core while extinction ensembles project to NAc shell. Functional disconnection experiments (Daun02 lesioning of vmPFC and acute dopamine D1-receptor blockade with SCH39166 in NAc core or shell) confirm that vmPFC ensembles interact with NAc core versus shell to play dissociable roles in cocaine self-administration versus extinction, respectively. Our results demonstrate that neuronal ensembles mediating cocaine self-administration and extinction comingle in vmPFC but have distinct outputs to the NAc core and shell that promote or inhibit cocaine seeking. SIGNIFICANCE STATEMENT Neuronal ensembles within the vmPFC have recently been shown to play a role in self-administration and extinction of food seeking. Here, we used the Daun02 chemogenetic inactivation procedure, which allows selective inhibition of neuronal ensembles identified by the activity marker Fos, to demonstrate that different ensembles for cocaine self-administration and extinction memories coexist in the ventral mPFC and interact with distinct subregions of the nucleus accumbens.
Human species-specific loss of CMP-N-acetylneuraminic acid hydroxylase enhances atherosclerosis via intrinsic and extrinsic mechanisms

Significance Cardiovascular disease (CVD) events like heart attacks and strokes due to atherosclerotic narrowing of arteries are the commonest cause of worldwide deaths, but many first-time events occur in individuals without known risk factors. In contrast, such events are extremely rare in other animals despite some of the same risk factors. While environmental and behavioral factors likely contribute to the difference, we show here that a human-specific genetic mutation affecting cell-surface molecules called sialic acids may be one other factor. We also show that the same mutation can help explain the apparently human-specific increased risk of CVD events associated with red meat consumption. The humanized mouse systems we present could be explored as models for future studies of atherosclerosis. Cardiovascular disease (CVD) events due to atherosclerosis cause one-third of worldwide deaths and risk factors include physical inactivity, age, dyslipidemia, hypertension, diabetes, obesity, smoking, and red meat consumption. However, ∼15% of first-time events occur without such factors. In contrast, coronary events are extremely rare even in closely related chimpanzees in captivity, despite human-like CVD–risk-prone blood lipid profiles, hypertension, and mild atherosclerosis. Similarly, red meat-associated enhancement of CVD event risk does not seem to occur in other carnivorous mammals. Thus, heightened CVD risk may be intrinsic to humans, and genetic changes during our evolution need consideration. Humans exhibit a species-specific deficiency of the sialic acid N-glycolylneuraminic acid (Neu5Gc), due to pseudogenization of cytidine monophosphate-N-acetylneuraminic acid (Neu5Ac) hydroxylase (CMAH), which occurred in hominin ancestors ∼2 to 3 Mya. Ldlr−/− mice with human-like Cmah deficiency fed a sialic acids (Sias)-free high-fat diet (HFD) showed ∼1.9-fold increased atherogenesis over Cmah wild-type Ldlr−/− mice, associated with elevated macrophage cytokine expression and enhanced hyperglycemia. Human consumption of Neu5Gc (from red meat) acts as a “xeno-autoantigen” via metabolic incorporation into endogenous glycoconjugates, as interactions with circulating anti-Neu5Gc “xeno-autoantibodies” potentiate chronic inflammation (“xenosialitis”). Cmah−/−Ldlr−/− mice immunized with Neu5Gc-bearing antigens to generate human-like anti-Neu5Gc antibodies suffered a ∼2.4-fold increased atherosclerosis on a Neu5Gc-rich HFD, compared with Neu5Ac-rich or Sias-free HFD. Lesions in Neu5Gc-immunized and Neu5Gc-rich HFD-fed Cmah−/−Ldlr−/− mice were more advanced but unexplained by lipoprotein or glucose changes. Human evolutionary loss of CMAH likely contributes to atherosclerosis predisposition via multiple intrinsic and extrinsic mechanisms, and future studies could consider this more human-like model.
Genome-Wide Identification and Expression Profiling of CBL-CIPK Gene Family in Pineapple (Ananas comosus) and the Role of AcCBL1 in Abiotic and Biotic Stress Response

Ca2+ serves as a ubiquitous second messenger regulating several aspects of plant growth and development. A group of unique calcium sensor proteins, calcineurin B-like (CBL), interact with CBL-interacting protein kinases (CIPKs) to decode the Ca2+ signature inside the cell. Although CBL-CIPK signaling toolkit has been shown to play significant roles in the responses to numerous stresses in different plants, the information about pineapple CBL-CIPK remains obscure. In the present study, a total of eight AcCBL and 21 AcCIPK genes were identified genome-wide in pineapple. The identified genes were renamed on the basis of gene ID in ascending order and phylogenetic analysis divided into five groups. Transcriptomic data analysis showed that AcCBL and AcCIPK genes were expressed differentially in different tissues. Further, the expression analysis of AcCBL1 in different tissues showed significant changes under various abiotic stimuli. Additionally, the ectopic expression of AcCBL1 in Arabidopsis resulted in enhanced tolerance to salinity, osmotic, and fungal stress. The present study revealed the crucial contribution of the CBL-CIPK gene in various biological and physiological processes in pineapple.
Identification of Patients in Need of Advanced Care for Depression Using Data Extracted From a Statewide Health Information Exchange: A Machine Learning Approach

Background As the most commonly occurring form of mental illness worldwide, depression poses significant health and economic burdens to both the individual and community. Different types of depression pose different levels of risk. Individuals who suffer from mild forms of depression may recover without any assistance or be effectively managed by primary care or family practitioners. However, other forms of depression are far more severe and require advanced care by certified mental health providers. However, identifying cases of depression that require advanced care may be challenging to primary care providers and health care team members whose skill sets run broad rather than deep. Objective This study aimed to leverage a comprehensive range of patient-level diagnostic, behavioral, and demographic data, as well as past visit history data from a statewide health information exchange to build decision models capable of predicting the need of advanced care for depression across patients presenting at Eskenazi Health, the public safety net health system for Marion County, Indianapolis, Indiana. Methods Patient-level diagnostic, behavioral, demographic, and past visit history data extracted from structured datasets were merged with outcome variables extracted from unstructured free-text datasets and were used to train random forest decision models that predicted the need of advanced care for depression across (1) the overall patient population and (2) various subsets of patients at higher risk for depression-related adverse events; patients with a past diagnosis of depression; patients with a Charlson comorbidity index of ≥1; patients with a Charlson comorbidity index of ≥2; and all unique patients identified across the 3 above-mentioned high-risk groups. Results The overall patient population consisted of 84,317 adult (aged ≥18 years) patients. A total of 6992 (8.29%) of these patients were in need of advanced care for depression. Decision models for high-risk patient groups yielded area under the curve (AUC) scores between 86.31% and 94.43%. The decision model for the overall patient population yielded a comparatively lower AUC score of 78.87%. The variance of optimal sensitivity and specificity for all decision models, as identified using Youden J Index, is as follows: sensitivity=68.79% to 83.91% and specificity=76.03% to 92.18%. Conclusions This study demonstrates the ability to automate screening for patients in need of advanced care for depression across (1) an overall patient population or (2) various high-risk patient groups using structured datasets covering acute and chronic conditions, patient demographics, behaviors, and past visit history. Furthermore, these results show considerable potential to enable preventative care and can be easily integrated into existing clinical workflows to improve access to wraparound health care services.
Synthesis of Nano-Paramagnetic Oleuropein to Induce KRAS Over-Expression: A New Mechanism to Inhibit AGS Cancer Cells

Background and objectives: Human gastric adenocarcinoma (AGS) is one of the most common malignant cancers worldwide. The present study aimed to transfer oleuropein into cancer cells using synthetic paramagnetic nanoparticles and study their effect on the AGS (ATCC® CRL1739™) cell line. Materials and Methods: Paramagnetic nano-oleuropein was synthesized using four-stage co-precipitation by developing NH-connected bridges and was evaluated by EDS, SEM and FTIR methods. Different concentrations of magnetic oleuropein (0, 0.15, 0.45, 1.37, 4.12, 12.35, 37.04, 111.11, 333.33, 1000 µg/mL) were used to treat the AGS cell line in a completely randomized design using a statistical framework with three replicates. The relative expression rate of miR-200 and KRAS oncogenes was evaluated using real-time PCR. The inhibition rate of the AGS cells was assessed using the MTT test at 24, 48 and 72 h intervals. Results: The results showed that there was a significant difference between the inhibition rates of magnetic nano-oleuropein at IC50-24h (23.6 µg/mL), IC50-48h (15.2 µg/mL) and IC50-72h (9.2 µg/mL). Real-time PCR indicated that the relative expression of KRAS and miR-200 genes was highest at IC50 at these intervals. Conclusions: Magnetic nano-oleuropein can be subjected to objective testing and clinical evaluations as a natural antioxidant to prevent and treat gastric adenocarcinoma.
3D Rigid Motion Segmentation with Mixed and Unknown Number of Models

Many real-world video sequences cannot be conveniently categorized as general or degenerate; in such cases, imposing a false dichotomy in using the fundamental matrix or homography model for motion segmentation on video sequences would lead to difficulty. Even when we are confronted with a general scene-motion, the fundamental matrix approach as a model for motion segmentation still suffers from several defects, which we discuss in this paper. The full potential of the fundamental matrix approach could only be realized if we judiciously harness information from the simpler homography model. From these considerations, we propose a multi-model spectral clustering framework that synergistically combines multiple models (homography and fundamental matrix) together. We show that the performance can be substantially improved in this way. For general motion segmentation tasks, the number of independently moving objects is often unknown a priori and needs to be estimated from the observations. This is referred to as model selection and it is essentially still an open research problem. In this work, we propose a set of model selection criteria balancing data fidelity and model complexity. We perform extensive testing on existing motion segmentation datasets with both segmentation and model selection tasks, achieving state-of-the-art performance on all of them; we also put forth a more realistic and challenging dataset adapted from the KITTI benchmark, containing real-world effects such as strong perspectives and strong forward translations not seen in the traditional datasets.
Sirtuin 7 promotes 45S pre-rRNA cleavage at site 2 and determines the processing pathway

ABSTRACT In humans, ribosome biogenesis mainly occurs in nucleoli following two alternative pre-rRNA processing pathways differing in the order in which cleavages take place but not by the sites of cleavage. To uncover the role of the nucleolar NAD+-dependent deacetylase sirtuin 7 in the synthesis of ribosomal subunits, pre-rRNA processing was analyzed after sirtinol-mediated inhibition of sirtuin 7 activity or depletion of sirtuin 7 protein. We thus reveal that sirtuin 7 activity is a critical regulator of processing of 45S, 32S and 30S pre-rRNAs. Sirtuin 7 protein is primarily essential to 45S pre-rRNA cleavage at site 2, which is the first step of processing pathway 2. Furthermore, we demonstrate that sirtuin 7 physically interacts with Nop56 and the GAR domain of fibrillarin, and propose that this could interfere with fibrillarin-dependent cleavage. Sirtuin 7 depletion results in the accumulation of 5′ extended forms of 32S pre-rRNA, and also influences the localization of fibrillarin. Thus, we establish a close relationship between sirtuin 7 and fibrillarin, which might determine the processing pathway used for ribosome biogenesis. Summary: In humans, sirtuin 7 plays a key role in the synthesis of ribosomal subunits by controlling critical endonucleolytic cleavages of precursor ribosomal RNAs.
Epidermal Growth Factor is Effective in the Treatment of Diabetic Foot Ulcers: Meta-Analysis and Systematic Review

Diabetic foot ulcers (DFUs) are one the common complications of diabetes mellitus. Many trials were performed to evaluate the effect of recombinant human epidermal growth factor (rhEGF) in healing DFUs. This meta-analysis was performed to synthesize the evidence of rhEGF treatment in DFUs in comparison to placebo. Databases included for the search were PubMed, EMBASE, the Cochrane Library, Web of Science, EBSCOhost, ScienceDirect, and Scopus (up to January 2019). The outcome of interest was the complete healing rate of DFUs. We performed random effects meta-analysis stratified by the types of administration route (intralesional injection and topical apply) by calculating the odds ratios (OR) and 95% confidence interval (95% CI). A total of six studies involving 530 patients were eligible for analysis. The combined OR (intralesional injection and topical apply) was 4.005 (95% CI: (2.248; 7.135), p < 0.001). The ORs for intralesional injection and topical application were 3.599 (95% CI: (1.213; 10.677), p = 0.021) and 4.176 (95% CI: (2.112; 8.256), p < 0.001), respectively. Statistical heterogeneity might not be important in overall treatment (I2 = 15.17, p = 0.317) and both of the subgroups (I2: 24.56, p = 0.25 and I2: 33.26, p = 0.213, respectively). Our results support the use of rhEGF in the treatment of DFUs.
Re-Caption: Saliency-Enhanced Image Captioning Through Two-Phase Learning

Visual saliency and semantic saliency are important in image captioning. However, a single-phase image captioning model benefits little from limited saliency information without a saliency predictor. In this paper, a novel saliency-enhanced re-captioning framework via two-phase learning is proposed to enhance single-phase image captioning. In the framework, both visual and semantic saliency cues are distilled from the first-phase model and fused with the second-phase model for model self-boosting. The visual saliency mechanism can generate a saliency map and a saliency mask for an image without learning a saliency predictor. The semantic saliency mechanism sheds some lights on the properties of those words with the part-of-speech Noun in a caption. Besides, another type of saliency, sample saliency is proposed to compute the saliency degree of each sample, which is helpful for more robust image captioning. In addition, how to combine the three types of saliency for further performance boost is also examined. Our framework can treat an image captioning model as a saliency extractor, which may benefit other captioning models and the related tasks. The experimental results on both the Flickr30k and MSCOCO datasets show that the saliency-enhanced models can obtain promising performance gains.