Enhanced analysis of tabular data through Multi-representation DeepInsight.

Tabular data analysis is a critical task in various domains, enabling us to uncover valuable insights from structured datasets. While traditional machine learning methods can be used for feature engineering and dimensionality reduction, they often struggle to capture the intricate relationships and dependencies within real-world datasets. In this paper, we present Multi-representation DeepInsight (MRep-DeepInsight), a novel extension of the DeepInsight method designed to enhance the analysis of tabular data. By generating multiple representations of samples using diverse feature extraction techniques, our approach is able to capture a broader range of features and reveal deeper insights. We demonstrate the effectiveness of MRep-DeepInsight on single-cell datasets, Alzheimer's data, and artificial data, showcasing an improved accuracy over the original DeepInsight approach and machine learning methods like random forest, XGBoost, LightGBM, FT-Transformer and L2-regularized logistic regression. Our results highlight the value of incorporating multiple representations for robust and accurate tabular data analysis. By leveraging the power of diverse representations, MRep-DeepInsight offers a promising new avenue for advancing decision-making and scientific discovery across a wide range of fields.

Abnormal Development of the Corpus Callosum in Autism Spectrum Disorder: An MRI Study.

BACKGROUND: Altered size in the corpus callosum (CC) has been reported in individuals with autism spectrum disorder (ASD), but few studies have investigated younger children. Moreover, knowledge about the age-related changes in CC size in individuals with ASD is limited. OBJECTIVES: Our objective was to investigate the age-related size of the CC and compare them with age-matched healthy controls between the ages of 2 and 18 years. METHODS: Structural-weighted images were acquired in 97 male patients diagnosed with ASD; published data were used for the control group. The CC was segmented into 7 distinct subregions (rostrum, genu, rostral body, anterior midbody, posterior midbody, isthmus, and splenium) as per Witelson's technique using ITK-SNAP software. We calculated both the total length and volume of the CC as well as the length and height of its 7 subregions. The length of the CC measures was studied as both continuous and categorical forms. For the continuous form, Pearson's correlation was used, while categorical forms were based on age ranges reflecting brain expansion during early postnatal years. Differences in CC measures between adjacent age groups in individuals with ASD were assessed using a Student t-test. Mean and standard deviation scores were compared between ASD and control groups using the Welch t-test. RESULTS: Age showed a moderate positive association with the total length of the CC (r = 0.43; Padj = 0.003) among individuals with ASD. Among the subregions, a positive association was observed only in the anterior midbody of the CC (r = 0.41; Padj = 0.01). No association was found between the age and the height of individual subregions or with the total volume of the CC. In comparison with healthy controls, individuals with ASD exhibited shorter lengths and heights of the genu and splenium of the CC across wide age ranges. CONCLUSION: Overall, our results highlight a distinct abnormal developmental trajectory of CC in ASD, particularly in the genu and splenium structures, potentially reflecting underlying pathophysiological mechanisms that warrant further investigation.

Neuroprotective Action of Selected Natural Drugs Against Neurological Diseases and Mental Disorders: Potential Use Against Radiation Damage.

Exposure to radiation, ionizing and non-ionizing radiation, is a significant concern in modern society. The brain is the organ that is most sensitive to radiation exposure. This review describes how exposure to radiation can affect neurotransmitters in different brain regions, affecting brain function. This review covers neurodegenerative diseases such as Alzheimer's, Parkinson's, and neuroinflammation due to changes in neurons in the central nervous system, and the effects thereon of medicinal plants such as Allium cepa, Allium sativum, Centella asiatica, Coriandrum sativum, and Crocus sativus plants, used for centuries in traditional medicine. These herbal medicines exert free radical scavenging, and antioxidant as well as anti-inflammatory properties which can be beneficial in managing neurological diseases. The present review compiles the neuroprotective effects of selected natural plants against neurological damage, as well as highlights the different mechanisms of action elicited to induce and produce beneficial effects. The current review describes recent studies on the pharmacological effects of neuroprotective herbs on various neurological and mental illnesses, and shows the way further studies can impact this field, including potential effects on radiation-induced damage.

SleepBoost: a multi-level tree-based ensemble model for automatic sleep stage classification.

Neurodegenerative diseases often exhibit a strong link with sleep disruption, highlighting the importance of effective sleep stage monitoring. In this light, automatic sleep stage classification (ASSC) plays a pivotal role, now more streamlined than ever due to the advancements in deep learning (DL). However, the opaque nature of DL models can be a barrier in their clinical adoption, due to trust concerns among medical practitioners. To bridge this gap, we introduce SleepBoost, a transparent multi-level tree-based ensemble model specifically designed for ASSC. Our approach includes a crafted feature engineering block (FEB) that extracts 41 time and frequency domain features, out of which 23 are selected based on their high mutual information score (> 0.23). Uniquely, SleepBoost integrates three fundamental linear models into a cohesive multi-level tree structure, further enhanced by a novel reward-based adaptive weight allocation mechanism. Tested on the Sleep-EDF-20 dataset, SleepBoost demonstrates superior performance with an accuracy of 86.3%, F1-score of 80.9%, and Cohen kappa score of 0.807, outperforming leading DL models in ASSC. An ablation study underscores the critical role of our selective feature extraction in enhancing model accuracy and interpretability, crucial for clinical settings. This innovative approach not only offers a more transparent alternative to traditional DL models but also extends potential implications for monitoring and understanding sleep patterns in the context of neurodegenerative disorders. The open-source availability of SleepBoost's implementation at https://github.com/akibzaman/SleepBoost can further facilitate its accessibility and potential for widespread clinical adoption.

Nephrotic Syndrome and Posterior Reversible Encephalopathy Syndrome as Clinical Presentations of Gemcitabine-Induced Thrombotic Micro-Angiopathy.

Gemcitabine-induced thrombotic micro-angiopathy (GiTMA) is a very rare pathology of micro-vascular occlusion with a poor prognosis. In this case report, we present a young male with pancreatic carcinoma who received gemcitabine as adjuvant chemotherapy and developed thrombotic micro-angiopathy (TMA) manifesting as nephrotic syndrome with renal dysfunction and posterior reversible encephalopathy syndrome (PRES). The case was successfully managed with discontinuation of the drug and conservative management. The pathogenesis of GiTMA might be direct endothelial dysfunction with consequent activation of the clotting system. The role of plasma exchanges and monoclonal antibodies is unclear in drug-induced TMA.

Predicting lysine methylation sites using a convolutional neural network.

Protein lysine methylation is a particular type of post translational modification that plays an important role in both histone and non-histone function regulation in proteins. Deregulation caused by lysine methyltransferases has been identified as the cause of several diseases including cancer as well as both mental and developmental disorders. Identifying lysine methylation sites is a critical step in both early diagnosis and drug design. This study proposes a new Machine Learning method called CNN-Meth for predicting lysine methylation sites using a convolutional neural network (CNN). Our model is trained using evolutionary, structural, and physicochemical-based presentation along with binary encoding. Unlike previous studies, instead of extracting handcrafted features, we use CNN to automatically extract features from different presentations of amino acids to avoid information loss. Automated feature extraction from these representations of amino acids as well as CNN as a classifier have never been used for this problem. Our results demonstrate that CNN-Meth can significantly outperform previous methods for predicting methylation sites. It achieves 96.0%, 85.1%, 96.4%, and 0.65 in terms of Accuracy, Sensitivity, Specificity, and Matthew's Correlation Coefficient (MCC), respectively. CNN-Meth and its source code are publicly available at https://github.com/MLBC-lab/CNN-Meth.

Promising Potential of Curcumin and Related Compounds for Antiviral Drug Discovery.

Viruses are acellular, microscopic, and mobile particles containing genetic particles, either DNA/RNA strands as nucleoproteins, responsible for 69,53,743 deaths till the year 2023. Curcumin and related compounds are among the areas of pivotal interest for researchers because of their versatile pharmacological profile. Chemically known as diferuloylmethane, which is a main constituent of turmeric along with demethoxycurcumin and bisdemethoxycurcumin, they have a broad spectrum of antiviral activity against viruses such as human immunodeficiency virus, herpes simplex virus, influenza virus (Avian influenza) and Hepatitis C virus HIV. The possible role of curcumin as an antiviral agent may be attributed to the activation of the 20S proteasome, a cellular machinery responsible for degrading unfolded or misfolded proteins in a ubiquitin-independent manner. It shows suppression of HBV entry at various infection stages by inhibiting cccDNA replication by inhibiting the Wnt/ß-catenin signaling pathway to attenuate IAV-induced myocarditis.

Antimicrobial Potential of Polyphenols: An Update on Alternative for Combating Antimicrobial Resistance.

The last decade has encountered an increasing demand for plant-based natural antibiotics. This demand has led to more research-based investigations for natural sources of antimicrobial agents and published reports demonstrating that plant extracts are widely applied in modern medicine, reporting potential activity that may be due to polyphenol compounds. Interestingly, the effects of polyphenols on the sensitivity of bacteria to antibiotics have not been well-studied. Hence, the current review encompasses the prospective application of plant-based phenolic extracts from plants of Indian origin. The emergence of resistance to antimicrobial agents has increased the inefficacy of many antimicrobial drugs. Several strategies have been developed in recent times to overcome this issue. A combination of antimicrobial agents is employed for the failing antibiotics, which restores the desirable effect but may have toxicity-related issues. Phytochemicals such as some polyphenols have demonstrated their potent activity as antimicrobial agents of natural origin to work against resistance issues. These agents alone or in combination with certain antibiotics have been shown to enhance the antimicrobial activity against a spectrum of microbes. However, the information regarding the mechanisms and structure-activity relationships remains elusive. The present review also focuses on the possible mechanisms of natural compounds based on their structure- activity relationships for incorporating polyphenolic compounds in the drug-development processes. Besides this work, polyphenols could reduce drug dosage and may diminish the unhidden or hidden side effects of antibiotics. Pre-clinical findings have provided strong evidence that polyphenolic compounds, individually and in combination with already approved antibiotics, work well against the development of resistance. However, more studies must focus on in vivo results, and clinical research needs to specify the importance of polyphenol-based antibacterials in clinical trials.

Successful Reversal of Refractory Posttransplant Thrombotic Microangiopathy with Eculizumab.

Posttransplant thrombotic microangiopathy (PT-TMA) can be caused by calcineurin inhibitors (CNIs), ischemic injury, infections, or antibody-mediated rejection (ABMR). Delayed recognition can result in allograft loss. We describe the first reported case of successful reversal of refractory PT-TMA with eculizumab in India. It highlights the importance of prompt diagnosis and benefit from an early initiation of eculizumab therapy in refractory cases.

Human Activity Recognition Based on Deep Learning and Micro-Doppler Radar Data.

Activity recognition is one of the significant technologies accompanying the development of the Internet of Things (IoT). It can help in recording daily life activities or reporting emergencies, thus improving the user's quality of life and safety, and even easing the workload of caregivers. This study proposes a human activity recognition (HAR) system based on activity data obtained via the micro-Doppler effect, combining a two-stream one-dimensional convolutional neural network (1D-CNN) with a bidirectional gated recurrent unit (BiGRU). Initially, radar sensor data are used to generate information related to time and frequency responses using short-time Fourier transform (STFT). Subsequently, the magnitudes and phase values are calculated and fed into the 1D-CNN and Bi-GRU models to extract spatial and temporal features for subsequent model training and activity recognition. Additionally, we propose a simple cross-channel operation (CCO) to facilitate the exchange of magnitude and phase features between parallel convolutional layers. An open dataset collected through radar, named Rad-HAR, is employed for model training and performance evaluation. Experimental results demonstrate that the proposed 1D-CNN+CCO-BiGRU model demonstrated superior performance, achieving an impressive accuracy rate of 98.2%. This outperformance of existing systems with the radar sensor underscores the proposed model's potential applicability in real-world scenarios, marking a significant advancement in the field of HAR within the IoT framework.

Apolipoprotein E is enriched in dense deposits and is a marker for dense deposit disease in C3 glomerulopathy.

C3 glomerulopathy (C3G) is a rare disease resulting from dysregulation of the alternative pathway of complement. C3G includes C3 glomerulonephritis (C3GN) and dense deposit disease (DDD), both of which are characterized by bright glomerular C3 staining on immunofluorescence studies. However, on electron microscopy (EM), DDD is characterized by dense osmiophilic mesangial and intramembranous deposits along the glomerular basement membranes (GBM), while the deposits of C3GN are not dense. Why the deposits appear dense in DDD and not in C3GN is not known. We performed laser microdissection (LCM) of glomeruli followed by mass spectrometry (MS) in 12 cases each of DDD, C3GN, and pretransplant kidney control biopsies. LCM/MS showed marked accumulation of complement proteins C3, C5, C6, C7, C8, C9 and complement regulating proteins CFHR5, CFHR1, and CFH in C3GN and DDD compared to controls. C3, CFH and CFHR proteins were comparable in C3GN and DDD. Yet, there were significant differences. First, there was a six-to-nine-fold increase of C5-9 in DDD compared to C3GN. Secondly, an unexpected finding was a nine-fold increase in apolipoprotein E (ApoE) in DDD compared to C3GN. Most importantly, immunohistochemical and confocal staining for ApoE mirrored the dense deposit staining in the GBM in DDD but not in C3GN or control cases. Validation studies using 31 C3G cases confirmed the diagnosis of C3GN and DDD in 80.6 % based on ApoE staining. Overall, there is a higher burden of terminal complement pathway proteins in DDD compared to C3GN. Thus, our study shows that dense deposits in DDD are enriched with ApoE compared to C3GN and control cases. Hence, ApoE staining may be used as an adjunct to EM for the diagnosis of DDD and might be valuable when EM is not available.

Exploring role of natural compounds in molecular alterations associated with brain ageing: A perspective towards nutrition for ageing brain.

Aging refers to complete deterioration of physiological integrity and function. By midcentury, adults over 60 years of age and children under 15 years will begin to outnumber people in working age. This shift will bring multiple global challenges for economy, health, and society. Eventually, aging is a natural process playing a vital function in growth and development during pediatric stage, maturation during adult stage, and functional depletion. Tissues experience negative consequences with enhanced genomic instability, deregulated nutrient sensing, mitochondrial dysfunction, and decline in performance on cognitive tasks. As brain ages, its volume decreases, neurons & glia get inflamed, vasculature becomes less developed, blood pressure increases with a risk of stroke, ischemia, and cognitive deficits. Diminished cellular functions leads to progressive reduction in functional and emotional capacity with higher possibility of disease and finally death. This review overviews cellular as well as molecular aspects of aging, biological pathway related to accelerated brain aging, and strategies minimizing cognitive aging. Age-related changes include altered bioenergetics, decreased neuroplasticity and flexibility, aberrant neural activity, deregulated Ca2+ homeostasis in neurons, buildup of reactive oxygen species, and neuro-inflammation. Unprecedented progress has been achieved in recent studies, particularly in terms of how herbal or natural substances affect genetic pathways and biological functions that have been preserved through evolution. Herein, the present work provides an overview of ageing and age-related disorders and explore the molecular mechanisms that underlie therapeutic effects of herbal and natural chemicals on neuropathological signs of brain aging.

Investigation of two-pore K+ (TPK) channels in Triticum aestivum L. suggests their role in stress response.

Two-pore K+ (TPK) channels are voltage-independent and involved in stress response in plants. Herein, we identified 12 TaTPK genes located on nine chromosomes in the Triticum aestivum genome. The majority of TaTPK genes comprised two exons. Each TaTPK channel comprised four transmembrane (TM) helices, N- and C-terminal ion-channel domains, two EF-hand domains and one 14-3-3 binding site. Additionally, highly conserved 'GYGD' motif responsible for K+ ion specificity, was found in between the TMs in both the ion-channel domains. Nine TaTPK channels were predicted to be localised at the plasma membrane, while three were vacuolar. The protein-protein and protein-chemical interactions indicated the coordinated functioning of the TaTPK channels with the other K+ transporters and their possible interaction with the Ca2+-signaling pathway. Expression studies suggested their importance in both vegetative and reproductive tissues development. Significantly modulated expression of various TaTPK genes during heat, drought, combined heat and drought and salt stresses, and after fungal infestation, depicted their function in stress responses. The miRNAs and transcription factors interaction analyses suggested their role in the hormone, light, growth and development-related, and stress-responsive signaling cascades. The current study suggested vital functions of various TaTPK genes, especially in stress response, and would provide an opportunity for their detailed characterization in future studies.

Severity of muscle impairment and its progression assessed using musculoskeletal magnetic resonance imaging and diffusion tension imaging in 78 boys with Duchenne muscular dystrophy: a retrospective study.

Purpose: Duchenne muscular dystrophy (DMD) is the most common and severe form of muscular dystrophy. Current diagnostic tests like genetic testing, needle electromyography, and muscle biopsy are either not easily available or invasive, and they are impractical for assessing disease progression and treatment outcomes. Therefore, there is a need for a non-invasive and accurate investigative modality for DMD. In recent years, musculoskeletal magnetic resonance imaging (MRI-MSK) along with fractional anisotropy (FA) and diffusion tensor imaging (DTI) have become major non-invasive tools. Material and methods: T1-weighted MRI-MSK and FA measures of DTI of 78 DMD patients were retrospectively studied to identify the distinct pattern of muscle involvement and fatty infiltration as age and/or disease progresses. Correlation analysis was performed between MRI-MSK grade score vs. age, muscle strength, and Vignos scale. Spearman's rank correlation coefficient was used. Results: As age increased, the MRI grade score and Vignos score increased. There was a statistically significant high positive correlation between MRI-MSK grade score and age, and low positive correlation with Vignos scores. With increasing age, the muscle strength on manual muscle testing (MMT) and FA value decreased. There was high negative correlation with muscle strength on MMT and low positive correlation between FA values and MMT score. Conclusions: On T1-weighted MRI, a distinct pattern, extent, and distribution of lower limb muscle involvement can be seen. MRI-MSK grade score worsens with progressing age, reducing strength, and increasing functional impairment. FA alone may not be an accurate marker in assessing progression of DMD. MRI-MSK and other DTI measures should be further explored as diagnostic and prognostic tools for DMD.

Exploring Trachyspermum ammi and Foeniculum vulgare in Hydroponic System and Compare its Chemical Constituents with Soil-Based Method: A Prospective in Agriculture.

BACKGROUND: The forthcoming problems will be of food, and soil due to environmental alteration, growing populations, pollution, and exhaustion of natural resources among other factors. Hydroponic farming has the capacity to alleviate the intimidation of these con-cerned issues in the agricultural system. Hydroponics is recommended as an alternative way to enhance product yield compared to conventional agriculture. OBJECTIVE: The present study aimed to determine the different growth parameters and constituents of soil-grown and hydroponically grown Trachyspermum ammi and Foeniculum vulgare for the first time, which could be a patentable in future. METHODS: In this study, extraction was carried out by maceration method using methanol as a solvent whereas, growth parameters were performed by the leaves number, plant height, and leaf area. Chlorophyll content was also performed in both sources. Further, a comparison of chemical constituents from different sources was analyzed by GC-MS. RESULTS: The bioactive components in hydroponically grown T. ammi were found more as compared to soil-grown T. ammi. The GC-MS analysis revealed the presence of various compounds in the methanolic extract of plant materials. CONCLUSION: Hence, hydroponics could be an alternative in agriculture and this system is now accepted globally. This method provides diverse perspectives for farmers to harvest high-yield, better quality, and enhanced bioactive compounds.

IgG4-Related Kidney Disease: A Diagnostic Conundrum Successfully Treated With Steroids and Rituximab.

IgG4-related disease (IgG4-RD) is an immune-mediated fibroinflammatory condition that has been recognized as a unified systemic disease that links many individual organ conditions that were previously considered to be unrelated. The pathological hallmark of the disease is an abundant IgG4-positive plasma cell infiltration in the affected tissues and fibrosis. It is a great mimicker of neoplastic, inflammatory, and infectious conditions. We report a 72-year-old man who presented to our hospital with dyspnea and oliguria. Detailed evaluation revealed that he was treated at multiple places for right-sided loin pain over the past 10 months and was found to have right-sided hydronephrosis, renal dysfunction, and multiple enlarged lymph nodes. A search for underlying malignancy previously was unyielding and he had rapid worsening of renal function prior to the current presentation. He was uremic and was initiated on hemodialysis. Kidney biopsy revealed features of IgG4-related tubulointerstitial nephritis. Despite tubular atrophy and interstitial fibrosis involving more than 50% of the sampled cortex, he showed a good response to steroids and rituximab (RTX) and became dialysis-independent. This report underscores the masquerading presentation of IgG4-RD which can hinder timely diagnosis and demonstrates the usefulness of a regimen of steroids and RTX in its treatment.