computers in biology and medicine

Pancreatic cancer is a fatal illness caused by mutations in multiple genes. Pancreatic cancer damages the organ that helps in digestion, resulting in symptoms including fatigue, bloating, and nausea. The use of medicinal plants has been crucial in the treatment of numerous disorders. The medicinal plant Calliandra Harrisi has been widely exploited for its possibilities in biology and medicine. The current study aimed to assess the biopotential of biologically active substances against pancreatic cancer. The GC-MS data of these phytochemicals from Calliandra Harrisi were further subjected to computational approaches with pancreatic cancer genes to evaluate their potential as therapeutic candidates...

The rise of pyrazinamide (PZA)-resistant strains of Mycobacterium tuberculosis (MTB) poses a major challenge to conventional tuberculosis (TB) treatments. PZA, a cornerstone of TB therapy, must be activated by the mycobacterial enzyme pyrazinamidase (PZase) to convert its active form, pyrazinoic acid, which targets the ribosomal protein S1. Resistance, often associated with mutations in the RpsA protein, complicates treatment and highlights a critical gap in the understanding of structural dynamics and mechanisms of resistance, particularly in the context of the G97D mutation...

PURPOSE: Smooth muscle cell (SMC) dysregulation is part of the pathological basis of pulmonary artery hypertension (PAH). We aimed to explore the heterogeneity of SMCs in PAH. METHODS: The profile GSE210248 was obtained from NCBI Gene Expression Omnibus, containing the scRNA-seq data of pulmonary arteries (PA) from three patients with PAH and three healthy donors. After quality control, normalization, and dimension reduction, cell clustering analysis was performed...

To report on a micro computed tomography (micro-CT) system capable of x-ray phase contrast imaging and of increasing spatial resolution at constant magnification. 

Approach: The micro-CT system implements the edge illumination (EI) method, which relies on two absorbing masks with periodically spaced transmitting apertures in the beam path; these split the beam into an array of beamlets and provide sensitivity to the beamlets' directionality, i.e., refraction. In EI, spatial resolution depends on the width of the beamlets rather than on the source/detector point spread function (PSF), meaning that resolution can be increased by decreasing the mask apertures, without changing the source/detector PSF or the magnification...

Cross-disease genome-wide association studies (GWASs) unveil pleiotropic loci, mostly situated within the non-coding genome, each of which exerts pleiotropic effects across multiple diseases. However, the challenge "W-H-W" (namely, whether, how, and in which specific diseases pleiotropy can inform clinical therapeutics) calls for effective and integrative approaches and tools. We here introduce a pleiotropy-driven approach specifically designed for therapeutic target prioritization and evaluation from cross-disease GWAS summary data, with its validity demonstrated through applications to two systems of disorders (neuropsychiatric and inflammatory)...

Several biomarkers have been proposed to identify frailty, a multisystemic age-related syndrome. However, the complex pathophysiology and the absence of a consensus on a comprehensive and universal definition make it challenging to pinpoint a singular biomarker or set of biomarkers that conclusively characterize frailty. This review delves into the main laboratory biomarkers, placing special emphasis on those associated with various pathways closely tied to the frailty condition, such as inflammation, oxidative stress, mitochondrial dysfunction, metabolic and endocrine alterations and microRNA...

OBJECTIVE: Depression and anxiety, prevalent coexisting mood disorders, pose a clinical challenge in accurate differentiation, hindering effective healthcare interventions. This research addressed this gap by employing a streamlined Symptom Checklist 90 (SCL-90) designed to minimize patient response burden. Utilizing machine learning algorithms, the study sought to construct classification models capable of distinguishing between depression and anxiety. METHODS: The study included 4262 individuals currently experiencing depression alone (n = 2998), anxiety alone (n = 716), or both depression and anxiety (n = 548)...

Diabetic retinopathy (DR) is a kind of ocular complication of diabetes, and its degree grade is an essential basis for early diagnosis of patients. Manual diagnosis is a long and expensive process with a specific risk of misdiagnosis. Computer-aided diagnosis can provide more accurate and practical treatment recommendations. In this paper, we propose a multi-view joint learning DR diagnostic model called RT2Net, which integrates the global features of fundus images and the local detailed features of vascular images to reduce the limitations of single fundus image learning...

In this research work, a novel fuzzy data transformation technique has been proposed and applied to the hormonal imbalance dataset. Hormonal imbalance is ubiquitously found principally in females of reproductive age which ultimately leads to numerous related medical conditions. Polycystic Ovary Syndrome (PCOS) is one of them. Treatment along with adopting a healthy lifestyle is advised to mitigate its consequences on the quality of life. The biological dataset of hormonal imbalance "PCOS" provides limited results that is whether the syndrome is present or not...

OBJECTIVE: Blurry medical images affect the accuracy and efficiency of multimodal image registration, whose existing methods require further improvement. METHODS: We propose an edge-based similarity registration method optimised for multimodal medical images, especially bone images, by a balance optimiser. First, we use a GPU (graphics processing unit) rendering simulation to convert computed tomography data into digitally reconstructed radiographs. Second, we introduce the improved cascaded edge network (ICENet), a convolutional neural network that extracts edge information of blurry medical images...

Macular edema, a prevalent ocular complication observed in various retinal diseases, can lead to significant vision loss or blindness, necessitating accurate and timely diagnosis. Despite the potential of deep learning for segmentation of macular edema, challenges persist in accurately identifying lesion boundaries, especially in low-contrast and noisy regions, and in distinguishing between Inner Retinal Fluid (IRF), Sub-Retinal Fluid (SRF), and Pigment Epithelial Detachment (PED) lesions. To address these challenges, we present a novel approach, termed Semantic Uncertainty Guided Cross-Transformer Network (SuGCTNet), for the simultaneous segmentation of multi-class macular edema...

Revealing protein binding sites with other molecules, such as nucleic acids, peptides, or small ligands, sheds light on disease mechanism elucidation and novel drug design. With the explosive growth of proteins in sequence databases, how to accurately and efficiently identify these binding sites from sequences becomes essential. However, current methods mostly rely on expensive multiple sequence alignments or experimental protein structures, limiting their genome-scale applications. Besides, these methods haven't fully explored the geometry of the protein structures...

BACKGROUND: Recurrent malignant pleural effusion (MPE) resulting from non-small-cell lung cancer (NSCLC) is easily refractory to conventional therapeutics and lacks predictive markers. The cellular or genetic signatures of recurrent MPE still remain largely uncertain. METHODS: 16 NSCLC patients with pleural effusions were recruited, followed by corresponding treatments based on primary tumours. Non-recurrent or recurrent MPE was determined after 3-6 weeks of treatments...

OBJECTIVES: MicroRNAs, which are micro-coordinators of gene expression, have been recently investigated as a potential treatment for cancer. The study used computational techniques to identify microRNAs that could target a set of genes simultaneously. Due to their multi-target-directed nature, microRNAs have the potential to impact multiple key pathways and their pathogenic cross-talk. MATERIALS AND METHODS: We identified microRNAs that target a prostate cancer-associated gene set using integrated bioinformatics analyses and experimental validation...

BACKGROUND: Predicting of future blood glucose (BG) concentration is important for diabetes control. Many automatic BG monitoring or controlling systems use BG predictors. The accuracy of the prediction for long prediction time is a major factor affecting the performance of the control system. The predicted BG can be used for glycemia management in the form of early hypoglycemic/hyperglycemic alarms or adjusting insulin injections. Recent developments in continuous glucose monitoring (CGM) devices open new opportunities for glycemia management of diabetic patients...

Uyghur medicine is one of the four major ethnic medicines in China and is a component of traditional Chinese medicine. The intrinsic quality of Uyghur medicinal materials will directly affect the clinical efficacy of Uyghur medicinal preparations. However, in recent years, problems such as adulteration of Uyghur medicinal materials and foreign bodies with the same name still exist, so it is necessary to strengthen the quality control of Uyghur medicines to guarantee Uyghur medicinal efficacy. Identifying the components of Uyghur medicines can clarify the types of medicinal materials used, is a crucial step to realizing the quality control of Uyghur medicines, and is also an important step in screening the effective components of Uyghur medicines...

Epigenetic regulation and mitochondrial dysfunction are essential to the progression of idiopathic pulmonary fibrosis (IPF). Curcumin (CCM) in inhibits the progression of pulmonary fibrosis by regulating the expression of specific miRNAs and pulmonary fibroblast mitochondrial function; however, the underlying mechanism is unclear. C57BL/6 mice were intratracheally injected with bleomycin (5 mg/kg) and treated with CCM (25 mg/kg body weight/3 times per week, intraperitoneal injection) for 28 days...

Spatial transcriptomics (ST), containing gene expression with fine-grained (i.e., different windows) spatial location within tissue samples, has become vital in developing innovative treatments. Traditional ST technology, however, rely on costly specialized commercial equipment. Addressing this, our article aims to creates a cost-effective, virtual ST approach using standard tissue images for gene expression prediction, eliminating the need for expensive equipment. Conventional approaches in this field often overlook the long-distance spatial dependencies between different sample windows or need prior gene expression data...

BACKGROUND: Cardiovascular patients experience high rates of adverse outcomes following discharge from hospital, which may be preventable through early identification and targeted action. This study aimed to investigate the effectiveness and explainability of machine learning algorithms in predicting unplanned readmission and death in cardiovascular patients at 30 days and 180 days from discharge. METHODS: Gradient boosting machines were trained and evaluated using data from hospital electronic medical records linked to hospital administrative and mortality data for 39,255 patients admitted to four hospitals in New South Wales, Australia between 2017 and 2021...

BACKGROUND: Clinical trials (CTs) are foundational to the advancement of evidence-based medicine and recruiting a sufficient number of participants is one of the crucial steps to their successful conduct. Yet, poor recruitment remains the most frequent reason for premature discontinuation or costly extension of clinical trials. METHODS: We designed and implemented a novel, open-source software system to support the recruitment process in clinical trials by generating automatic recruitment recommendations...