The Biomedical Applications of Artificial Intelligence: An Overview of Decades of Research.

A significant area of computer science called artificial intelligence (AI) is successfully applied to the analysis of intricate biological data and the extraction of substantial associations from datasets for a variety of biomedical uses. AI has attracted significant interest in biomedical research due to its features: (i) better patient care through early diagnosis and detection; (ii) enhanced workflow; (iii) lowering medical errors; (v) lowering medical costs; (vi) reducing morbidity and mortality; (vii) enhancing performance; (viii) enhancing precision; and (ix) time efficiency. Quantitative metrics are crucial for evaluating AI implementations, providing insights, enabling informed decisions, and measuring the impact of AI-driven initiatives, thereby enhancing transparency, accountability, and overall impact.

Segregation of Constitutional Isomers of Some Aromatic Amines Exploiting the Changes of Photo-Luminescence Behaviour of Isoreticular Metal-Organic Frameworks.

Three different two dimensional Cd(II)-based metal-organic frameworks (MOFs) have been synthesized by utilizing same N,N'-donor ligand and three different functionalized dicarboxylate linkers namely isophthalate, 5-nitroisophthalate and 5-hydroxyisophthalate for compound 1, 2 and 3 respectively. The compounds that are isoreticular bi-walled 2D frameworks, show dual fluorescence emission spectra for their π-π* and n-π* excitation. Compound 1 is consists of unsubstituted bridging isophthalate whereas 2 and 3 are made with bridging isophthalate that are substituted by electron withdrawing -NO2 group and electron donating -OH group respectively.

Medium molecular weight chitosan and magnetite based bead as a nanocomposite for delivery of anticancer drug: Development, evaluation and biocompatibility study.

Aim & Background: Increased efficacy with reduced side effects in cancer treatment is achieved through targeted distribution of anti-cancer medications. Because of their biocompatibility, biodegradability, low toxicity, and target ability under magnetic field, magnetic nanoparticles (MNP) based chitosan nanocomposite have attracted attention among other delivery technologies.

Methodology: MNPs were synthesised using the co-precipitation method.

The ATP-dependent DEAD-box RNA Helicase Dbp2 regulates the glucose/nitrogen stress response in baker's yeast by modulating reversible nuclear retention and decay of SKS1 mRNA.

In Saccharomyces cerevisiae, SKS1 mRNA encoding a glucose-sensing serine/threonine kinase belongs to "nucleus-retained" (NR) mRNAs representing a subset of otherwise normal transcripts, which exhibits slow nuclear export and excessively long nuclear dwell time. Nuclear retention of the SKS1 mRNA triggered by a 202 nt "export-retarding" nuclear zip code (NZ) element promotes its rapid degradation in the nucleus by the nuclear exosome/CTEXT. In this investigation, we demonstrate that Dbp2p, an ATP-dependent DEAD-box RNA helicase binds to SKS1 and other NR-mRNAs and thereby inhibits their export by antagonizing with the binding of the export factors Mex67p/Yra1p.

Efficient and visual detention of ammonia and TNP vapors by a sustainable highly luminescent 1D Zn(II) coordination polymer.

To realize the aim of easy and accurate detection of ammonia and picric acid (PA) in both aqueous and vapor phases based on function-oriented investigation principles, in the present study, we include a luminescent performance with recognition performance, taking into account the application conditions. Zn(II) ions with luminescence qualities and an amine-substituted imidazole moiety with selective recognition properties towards picric acid and ammonia are coupled to generate a novel 1D luminous Zn(II) coordination polymer, Zn-CP [{Zn(II)( 2-ABZ)2(2-BDC)}].MeOH]∞, where 2-ABZ and 2-BDC stand for terephthalic acid and protonated 2 aminobenzimidazole, respectively.

Nanomaterials impact in phytohormone signaling networks of plants-A critical review.

Nanotechnology offers a transformative approach to augment plant growth and crop productivity under abiotic and biotic stress conditions. Nanomaterials interact with key phytohormones, triggering the synthesis of stress-associated metabolites, activating antioxidant defense mechanisms, and modulating gene expression networks that regulate diverse physiological, biochemical, and molecular processes within plant systems. This review critically examines the impact of nanoparticles on both conventional and genetically modified crops, focusing on their role in nutrient delivery systems and the modulation of plant cellular machinery.

Intelligent consensus-based predictions of early life stage toxicity in fish tested in compliance with OECD Test Guideline 210.

Early life stage (ELS) toxicity testing in fish is a crucial test procedure used to evaluate the long-term effects of a wide range of chemicals, including pesticides, industrial chemicals, pharmaceuticals, and food additives. This test is particularly important for screening and prioritizing thousands of chemicals under the Registration, Evaluation, Authorization, and Restriction of Chemicals (REACH) regulation. In silico methods can be used to estimate the toxicity of a chemical when no experimental data is available and to reduce the cost, time, and resources involved in the experimentation process.

Dynamic patterns in herding predator-prey system: Analyzing the impact of inertial delays and harvesting.

This study expands traditional reaction-diffusion models by incorporating hyperbolic dynamics to explore the effects of inertial delays on pattern formation. The kinetic system considers a harvested predator-prey model where predator and prey populations gather in herds. Diffusion and inertial effects are subsequently introduced.

Nitrogen-containing heterocycles as important scaffold for selective and potent HDAC8 inhibition: a step towards effective, non-toxic and selective HDAC8 inhibitor discovery.

Selective inhibition of histone deacetylase 8 (HDAC8) has emerged as a promising approach for treating various diseases, including cancer. However, finding key structural features for HDAC8 inhibition and developing effective and selective HDAC8 inhibitors (HDAC8s) pose significant challenges. In the past few years, the development of various scaffolds for inhibiting HDAC8 has significantly risen and the quest continues.

Visible-Light-Driven CO₂ Reduction Using Imidazole-Based Metal-Organic Frameworks as Heterogeneous Photocatalysts.

The development of robust, efficient, and cost-effective heterogeneous photocatalysts for visible light-driven CO2 reduction continues to be a significant challenge in the quest for sustainable energy solutions. As a result, increasing attention is being directed towards the exploration of high-performance photocatalysts capable of converting CO2 into chemical feedstocks. Imidazolate Frameworks Potsdam (IFPs) can be a promising candidate for CO2 photoreduction due to their ease of synthesis, use of low-cost, earth-abundant metals, and high chemical and thermal stability.

An overview of matrix metalloproteinase-12 in multiple disease conditions, potential selective inhibitors, and drug designing strategies.

Matrix metalloproteases (MMPs) are the proteolytic enzymes accountable for extracellular matrix (ECM) modification through their Zn-dependent catalytic activity. Among these, MMP-12 is one of the crucial MMPs that contributes to various disease states including different types of cancers and other major pathophysiological conditions including COPD, asthma, emphysema, skin diseases, arthritis, vascular diseases, and neurological disorders. The majority of the MMP-12 inhibitors should have three constitutional pharmacophoric features (i.

Beyond predation: Fish-coral interactions can tip the scales of coral disease.

Coral reefs are critical ecosystems, fostering biodiversity and sustaining the livelihoods of millions globally. Nonetheless, they confront escalating threats, with infectious diseases emerging as primary catalysts for extensive damage, surpassing the impacts of other human-induced stressors. Disease transmission via biotic factors, particularly during fish predation, is a crucial yet often overlooked pathway.

Derivatives of D(-)-glutamine-based MMP-2 inhibitors as an effective remedy for the management of chronic myeloid leukemia-Part-III: Synthesis, biological screening and in silico binding interaction analysis.

Tyrosine kinase inhibitors (TKIs) have markedly improved the overall survival rate of patients with chronic myeloid leukemia (CML), enabling them to achieve a normal life expectancy. However, toxicity, relapse, and drug resistance continue to pose major challenges in the clinical treatment of CML. The progression of leukemia is directly connected to higher expression levels and enzymatic actions of matrix metalloproteinase-2 (MMP-2).

Dithiocarbamate as a Carbonyl Alternative in Pd-Catalyzed Carbonylative Homocoupling of Organoboronic Acids.

We have developed a novel protocol for carbonylative homocoupling of arylboronic acids using dithiocarbamate esters as the carbonyl alternative. A series of arylboronic acids underwent smooth reaction with dithiocarbamate ester (MeNCSMe) in the presence of Pd(PPh)Cl catalyst, Cu(OAc)·HO additive, and NaCO in DCE solvent, producing the biaryl ketones efficiently. The mechanism has been studied with the help of several control experiments that reveal the probability of thioamide intermediacy.

Extraction of polycyclic aromatic hydrocarbons (PAHs) from surface soils of East Kolkata wetland, India, and its distribution, sources, and risk assessment.

The East Kolkata wetland (EKW) in West Bengal, India is a Ramsar site and has ecological importance to the city. The booming urbanization history of Kolkata city causes increase in concentration of persistent air pollutants like polycyclic aromatic hydrocarbons (PAHs) which got adsorbed eventually in the wetland soil due to their hydrophobicity and lipophilicity. Therefore, current study aims to investigate PAHs pollution level along with associated ecological health risk and optimization of PAHs extraction to develop standard analysis protocol.

Decoding skin cancer classification: perspectives, insights, and advances through researchers' lens.

Skin cancer is a significant global health concern, with timely and accurate diagnosis playing a critical role in improving patient outcomes. In recent years, computer-aided diagnosis systems have emerged as powerful tools for automated skin cancer classification, revolutionizing the field of dermatology. This survey analyzes 107 research papers published over the last 18 years, providing a thorough evaluation of advancements in classification techniques, with a focus on the growing integration of computer vision and artificial intelligence (AI) in enhancing diagnostic accuracy and reliability.

Metabolomics and network pharmacology-guided analysis of TNF-α expression by (Linn) targeting NF-kB the signalling pathway in cancer cell lines.

Introduction: Cancer has emerged as one of the leading causes of fatality all over the world. Phytoconstituents are being studied for their synergistic effects, which include disease prevention by altering molecular pathways and immunomodulation without side effects. The present experiment aims to explore the cancer preventive activities of Linn leaves extract in skin cancer cell lines (A431) and colon cancer cell lines (COLO 320DM)).

Convective heat transport in a porous wavy enclosure: Nonuniform multi-frequency heating with hybrid nanofluid and magnetic field.

This work investigates the dynamics of the hybrid nanofluidic convective heat transfer in a permeable thermal system under the influence of multifrequency heating and a magnetic field. The geometry comprises a wavy-walled cavity filled with a water-based hybrid nanoliquid (AlO-Cu-HO) in a saturated porous medium. The finite volume approach is applied to scrutinize the hydro-thermal characteristics resulting from bottom heating and side cooling, considering various flow-controlling parameters.

Potato Late Blight Outbreak: A Study on Advanced Classification Models Based on Meteorological Data.

While past research has emphasized the importance of late blight infection detection and classification, anticipating the potato late blight infection is crucial from the economic point of view as it helps to significantly reduce the production cost. Furthermore, it is necessary to minimize the exposure of potatoes to harmful chemicals and pesticides due to their potential adverse effects on the human immune system. Our work is based on the precise classification of late blight infections in potatoes in European countries using real-time data from 1980 to 2000.

Schizophrenia Detection and Classification: A Systematic Review of the Last Decade.

Background/objectives: Artificial Intelligence (AI) in healthcare employs advanced algorithms to analyze complex and large-scale datasets, mimicking aspects of human cognition. By automating decision-making processes based on predefined thresholds, AI enhances the accuracy and reliability of healthcare data analysis, reducing the need for human intervention. Schizophrenia (SZ), a chronic mental health disorder affecting millions globally, is characterized by symptoms such as auditory hallucinations, paranoia, and disruptions in thought, behavior, and perception.

Evaluation of gum odina/carbopol composite mucoadhesive hydrogel on pharmaceutical performance: Focusing on potential periodontal treatment.

Antimicrobial buccal hydrogel made of polymers have gained tremendous utilisation in biomedical field. Dual drug loaded, porous materials are important areas of research for medical and pharmaceutical industries. In this regard, a series of hydrogels (F1, F2, F3) were prepared with gum odina and carbopol 940 in aqueous solution with calcium chloride as the cross linker and glycerol as plasticizer by ionotropic gelation method.

Sorcin: mechanisms of action in cancer hallmarks, drug resistance and opportunities in therapeutics.

Soluble resistant related calcium binding protein (Sorcin) plays an important role in tumor progression, angiogenesis, metastasis, and multidrug resistance. Differential expression of Sorcin across different cancers significantly correlates with key clinicopathological characteristics and survival outcomes, underscoring its potential as a prognostic marker. Its involvement in drug-resistant cancers further advert Sorcin as a promising therapeutic target.

Pan-Ret: a semi-supervised framework for scalable detection of pan-retinal diseases.

It has been shown in recent years that a range of optical diseases have early manifestation in retinal fundus images. It is becoming increasingly important to separate the regions of interest (RoI) upfront in the automated classification pipeline in order to ensure the alignment of the disease diagnosis with clinically relevant visual features. In this work, we introduce Pan-Ret, a semi-supervised framework which starts with locating the abnormalities in the biomedically relevant RoIs of a retinal image in an "annotation-agnostic" fashion.

Hybrid model development through the integration of quantitative read-across (qRA) hypothesis with the QSAR framework: An alternative risk assessment of acute inhalation toxicity testing in rats.

Regulatory authorities frequently need information on a chemical's capacity to produce acute systemic toxicity in humans. Due to concerns about animal welfare, human relevance, and reproducibility, numerous international initiatives have centered on finding a substitute for using animals in acute systemic lethality testing. These substitutes include the more current in-silico and in vitro techniques.

Topology andPTsymmetry in a non-Hermitian Su-Schrieffer-Heeger chain with periodic hopping modulation.

We study the effect of periodic hopping modulation in a Su-Schrieffer-Heeger (SSH) chain with an additional onsite staggered imaginary potential (of strength). Such dissipative, non-Hermitian (NH) extension amply modifies the features of the topological trivial phase (TTP) and the topological nontrivial phase (TNP) of the SSH chain, more so with the periodic hopping distribution. Generally a weak NH potential can respect the parity-time (PT) symmetry keeping the energy eigenvalues real, while a strong potential breaksPTconservation leading to imaginary edge state and complex bulk state energies in the system.