Lipophilic bioactive compounds from thermophilic cyanobacterium Leptolyngbya sp. HNBGU-004: Implications for countering VRSA resistance.

Extremophiles thrive in extreme conditions, showcasing rich and unexplored diversity. This resilience hints at the existence of novel biochemical pathways and unique bioactive compounds. In contrast, the issue of drug resistance and excessive misuse of antibiotics in various settings, such as healthcare, agriculture, and veterinary medicine, has contributed to the emergence and spread of drug-resistant microorganisms. In the present research, Leptolyngbya sp. HNBGU-004, was obtained from an extreme location, a hot water spring in the Garhwal Himalayan region of India. The lipophilic fraction derived from Leptolyngbya sp. HNBGU-004 exhibited significant inhibitory effects against vancomycin-resistant Staphylococcus aureus (VRSA), displaying a bactericidal concentration of 0.5 mg mL-1. Furthermore, gas chromatography-mass spectrometry (GC-MS) analysis of the lipophilic extract unveiled the major constituents. Leptolyngbya sp. HNBGU-004 holds significant promise as a primary source of potent anti-vancomycin-resistant S. aureus components. These findings emphasize the importance of Leptolyngbya sp. HNBGU-004 as a foundational source for use as both a synergistic and alternative agent against VRSA.

An Insight into the Pathogenesis of Diabetic Cardiomyopathy Along with the Novel Potential Therapeutic Approaches.

BACKGROUND: The existence of aberrant myocardial activity and function in the exclusion of those other cardiovascular events, such as atherosclerosis, hypertension, and severe valve disease, is known as diabetic cardiomyopathy. Diabetes patients are much more prone to death from cardiovascular illnesses than from any other cause, and they also have a 2-5 fold higher likelihood of acquiring cardiac failure and other complications. OBJECTIVE: In this review, the pathophysiology of diabetic cardiomyopathy is discussed, with an emphasis on the molecular and cellular irregularities that arise as the condition progresses, as well as existing and prospective future treatments. METHOD: The literature for this topic was researched utilizing Google Scholar as a search engine. Before compiling the review article, several research and review publications from various publishers, including Bentham Science, Nature, Frontiers, and Elsevier, were investigated. RESULT: The abnormal cardiac remodelling, marked by left ventricular concentric thickening and interstitial fibrosis contributing to diastolic impairment, is mediated by hyperglycemia, and insulin sensitivity. The pathophysiology of diabetic cardiomyopathy has been linked to altered biochemical parameters, decreased calcium regulation and energy production, enhanced oxidative damage and inflammation, and a build-up of advanced glycation end products. CONCLUSION: Antihyperglycemic medications are essential for managing diabetes because they successfully lower microvascular problems. GLP-1 receptor agonists and sodium-glucose cotransporter 2 inhibitors have now been proven to benefit heart health by having a direct impact on the cardiomyocyte. To cure and avoid diabetic cardiomyopathy new medicines are being researched, including miRNA and stem cell therapies.

Detail-Oriented Capsule Network for classification of CT scan images performing the detection of COVID-19.

COVID-19 is one of the biggest pandemics that the world is facing today, and every day, we are coming up with new challenges in this area. Still, much research is already going on to overcome this pandemic, and we also get succeeded to some extent. Diverse sources such as MRI, CT scanning, blood samples, X-ray image, and many more are available to detect COVID-19. Thus, it can be easily said that through image processing, the classification of COVID-19 can be done. In this study, the COVID-19 detection is done by classifying with the use of a type of convolutional neural network termed a detail-oriented capsule network. Chest CT scan imaging for the prediction of COVID-19 and non-COVID-19 are classified in the present paper using a Detailed Oriented capsule network (DOCN). Accuracy, specificity, and sensitivity are parameters used for model evaluation. The proposed model has achieved 98% accuracy, 81% sensitivity, and 98.4% specificity.

A Strategic Investigation on Diabetic Nephropathy; Its Conceptual Model and clinical Manifestations: A Review.

Diabetes is a major health issue, and its complications can lead to various health problems. Nephropathy has been recognised since the 1930s, when Kimmelstiel and Wilson first reported the characteristic nodular glomerulosclerosis lesions in diabetic kidneys. Diabetic nephropathy (DN), commonly known as diabetic kidney disease, is a condition in which people with diabetes have excessive quantities of urine albumin excretion, diabetic glomerular lesions, and a reduction in their glomerular filtration rate (GFR). Type 1 diabetes (autoimmune -cell destruction and absolute insulin insufficiency), type 2 diabetes (relative insulin deficit and resistance), and others are the three forms of diabetes (e.g., pancreatic disease). Diabetes nephropathy is the leading cause of chronic kidney disease and end-stage renal failure worldwide. Much research has been conducted in both basic science and clinical therapies to enhance the understanding of the mechanism of diabetic nephropathy and expand available therapeutics. Diabetic nephropathy prevention continues to rely on screening for microalbuminuria and treating hyperglycemia. However, several studies suggest that managing diabetic kidney disease is more challenging. Despite comparable hyperglycemic management, some studies suggest that the incidence of renal problems varies by patient. As a result, there has been a great deal of interest in studying the inherent renal protective effects of various antihyperglycemic drugs. This study aims to provide information about the diabetic kidney disease conceptual model, pathogenesis, screening, and diagnosis. It will also address the treatment and prevention of diabetic nephropathy, focusing on comparing the mechanisms, safety profiles, and efficacy of different antihyperglycemic medications.

Porous zinc-discs as nanocatalysts for methylene blue dye treatment in water: sensing, adsorption and photocatalytic degradation.

This paper reports a zinc derived (ZD) porous nanosystem that has been used for selective sensing, adsorption, and photocatalytic degradation of the known hazardous dye, Methylene blue (MB). Using zinc nitrate and 2-aminoterphthalic acid as precursors, the synthesis has been optimized to yield disc-shaped nanoparticles. This luminescent ZD nanoparticles exhibit absorption and emission wavelengths of 328 nm and 427 nm, respectively at an excitation wavelength of 330 nm. In the presence of MB, there is a sharp decrease in the photoluminescence emission intensity of ZD nanoparticles. The detection limit, quenching constant and the binding constant of ZD nanoparticles with MB are found to be 0.31 × 10-9 M, 3.30 × 106 M-1 and 2.27 × 106 M-1 respectively. The impact of contact time, initial MB concentration, and pH on the adsorption process were investigated. The equilibrium data fit well with the Langmuir adsorption isotherm model (R 2 = 0.989) and superlatively fitted to the pseudo-second-order rate model (rate constant: 0.00011 g mg-1 min-1; adsorption capacity (q e, calc.): 386.1 mg g-1; R 2: 0.990). Further, the MB dye degradation was performed under ultra-violet irradiation and ∼95% MB degradation was achieved within 70 min. The experimental data are well fitted to the pseudo-first order kinetics (R 2: 0.99; rate constant: 0.015 min-1). These disc shaped ZD nanoparticles can not only facilitate the detection, but also the adsorption and photocatalytic degradation of MB, which can be further processed for environmental remediation applications.

Prognostic Diagnosis for Breast Cancer Patients Using Probabilistic Bayesian Classification.

The diagnosis and treatment of patients in the healthcare industry are greatly aided by data analytics. Massive amounts of data should be handled using machine learning approaches to provide tools for prediction and categorization to support practitioner decision-making. Based on the kind of tumor, disorders like breast cancer can be categorized. The difficulties associated with evaluating vast amounts of data should be overcome by discovering an efficient method for categorization. Based on the Bayesian method, we analyzed the influence of clinic pathological indicators on the prognosis and survival rate of breast cancer patients and compared the local resection value directly using the lymph node ratio (LNR) and the overall value using the LNR differences in effect between estimates. Logistic regression was used to estimate the overall LNR of patients. After that, a probabilistic Bayesian classifier-based dynamic regression model for prognosis analysis is built to capture the dynamic effect of multiple clinic pathological markers on patient prognosis. The dynamic regression model employing the total estimated value of LNR had the best fitting impact on the data, according to the simulation findings. In comparison to other models, this model has the greatest overall survival forecast accuracy. These prognostic techniques shed light on the nodal survival and status particular to the patient. Additionally, the framework is flexible and may be used with various cancer types and datasets.

A Systematic review of various in-vivo screening models as well as the mechanisms involved in Parkinson's disease screening procedures.

BACKGROUND: Parkinson's disease is the second most common neurological ailment. It is also known that it affects practically all other brain components, although only gradually. Animal models are mostly used to test the efficacy of treatment against a specific enzyme and to aid in the creation of a new drug dose. OBJECTIVE: The purpose of this review paper is to highlight in vivo Parkinson's disease screening approaches, as well as the mechanism of action of each drug involved in Parkinson's disease development, and discuss the limitations of each model. In addition, also sheds light on Parkinson's disease genetic models. METHOD: The data for the publication was gathered from databases such as PubMed, Bentham Science, Elsevier, Springer Nature, Wiley, and Research Gate after a thorough examination of diverse research findings linked to Parkinson's disease and its screening models. RESULT: Each chemical or drug has a unique mechanism for causing disease, whether it's through the production of reactive oxygen species or the blockage of the dopamine receptor. Almost every symptom of the disease, whether physical or behavioral, is covered by each of the constructed models' unique set of indicators and symptoms. CONCLUSION: Animal models are typically used to assess a medicine's activity against a specific enzyme and to aid in the creation of a new drug dose. The process, restrictions, and mechanisms interfering with the screening, as well as the level of animal suffering, must all be thoroughly reviewed before any model for screening for Parkinson's disease can be implemented.

Anti-enterococcal and anti-oxidative potential of a thermophilic cyanobacterium, Leptolyngbya sp. HNBGU 003.

Enterococci, the opportunistic pathogens, pose several serious and life-threatening infections such as urinary tract infections, sepsis, and endocarditis. The situation is worsening due to the development of drug resistance in these pathogens against several antibiotics. The addition of anti-enterococcal compounds with antioxidant activity in fermented and packaged food may help prevent the transmission of food-borne enterococcal infections. Scientists are in continuous search of such compounds from various sources. Hence, the present study has tested the diethyl ether extracts of thermophilic cyanobacteria, selected based on a previous study, against the multidrug-resistant and -sensitive strains of Enterococcus faecium. Out of the eleven tested extracts, 72% have shown anti-enterococcal activity against both strains. Among the extracts with anti-enterococcal activity, the diethyl ether extract of Leptolyngbya sp. (DEEL-3) inhibited the growth of VRE in a dose-dependent manner with a minimum inhibitory concentration of 2.0 mg mL-1. The DEEL-3 has also shown its antioxidant potential in terms of DPPH scavenging with an IC50 of 3.16 mg mL-1. The organism was named Leptolyngbya sp. HNBGU 003 based on 16SrRNA sequence homology analysis and morphological features. Further, the GC-MS analysis of the DEEL-3 has revealed the predominance of two phenolic compounds, phenol, 2,4-bis(1,1-dimethylethyl)-, phosphite (3:1) and tris(2,4-di-tert-butylphenyl) phosphate, in it. Thus, the anti-enterococcal and antioxidant activity of DEEL-3 may be attributed to these phenolics, which may be isolated and developed as food additives.

Development of Biocompatible Iron-Carboxylate Metal Organic Frameworks for pH-Responsive Drug Delivery Application.

Metal organic frameworks (MOFs), MIL-101-Fe (Materials of Institute Lavoisier), have been synthesized by solvothermal method. The as-synthesized MIL-101-Fe particles are observed to have hexagonal shaped morphology with average particle size ranging from 480 to 500 nm. The functionalization of the surface of as-synthesized MIL-101-Fe particles was done with the integration of amine group into the framework to facilitate the conjugation of the drug and other entities. Further, the drug conjugated MOF particles were coated with polyethyleneglycol (PEG) layer so as to extend the drug release time by controlling the faster pH mediated MOF degradation in biological buffers. pH dependent drug release study of the MOF particles was carried out at 3 different pH values, i.e., 5, 6 and 7.4. The drug release profiles showed that the drug released from NH2-MIL-101-Fe takes less time which was further increased after coating the NH2-MIL-101-Fe with polyethyleneglycol (PEG@Drug@NH2-MIL-101-Fe). This confirmed that PEG coated particles have great stability for drug delivery application.

Fluorescent Sensing Assay for Trinitrotoluene Using Fluorescein Isothiocyanate Conjugated Mesoporous MCM-41 Particles.

In the present study, Trinitrotoluene (TNT) has been detected by the formation of Meisenheimer complex using Fluorescein isothiocyanate (FITC) dye loaded Mesoporous silica particles (MCM-41). FITC dye loaded mesoporous silica particles (MCM-41/FITC) have been synthesized using (3-Aminopropyl)trimethoxysilane, APTMS (λex = 490 nm and λem = 512 nm). TNT forms Meisenheimer complex with the amine group of APTMS present on MCM-41 particles. The loading of FITC in the pores of MCM-41 particles has been confirmed by different advanced characterization techniques. The average diameter of mesoporous MCM-41 particles was found about 130 nm. Pore volume is observed to decrease from 1.06 cm3/g to 0.49 cm3/g after FITC loading. The selective detection of TNT up to 0.1 ppb level makes MCM-41/FITC particles a potential sensing material for TNT detection.

A "Turn-On" thiol functionalized fluorescent carbon quantum dot based chemosensory system for arsenite detection.

Carbon quantum dots (CQDs) have emerged out as promising fluorescent probes for hazardous heavy metals detection in recent past. In this study, water soluble CQDs were synthesized by facile microwave pyrolysis of citric acid & cysteamine, and functionalized with ditheritheritol to impart thiol functionalities at surface for selective detection of toxic arsenite in water. Microscopic analysis reveals that the synthesized CQDs are of uniform size (diameter ∼5nm) and confirmed to have surface SH groups by FT-IR. The functionalized probe is then demonstrated for arsenite detection in water by "Turn-On" read out mechanism, which reduces the possibility of false positive signals associated with "turn off' probes reported earlier. The blue luminescent functionalized CQDs exhibit increase in fluorescence intensity on arsenite addition in 5-100ppb wide detection range. The probe can be used for sensitive detection of arsenite in environmental water to a theoretical detection limit (3s) of 0.086ppb (R2=0.9547) with good reproducibility at 2.6% relative standard deviation. The presented reliable, sensitive, rapid fCQDs probe demonstrated to exhibit high selectivity towards arsenite and exemplified for real water samples as well. The analytical performance of the presented probe is comparable to existing organic & semiconductor based optical probes.

Metal-free intramolecular aziridination of alkenes using hypervalent iodine based sulfonyliminoiodanes.

Intramolecular aziridination of alkenyl sulfonyliminoiodanes occurs thermally in the absence of conventional metal catalysts such as Rh(II) and Cu(II). In rigid molecular systems, conversions are near quantitative. The scope of the nonmetal process is related to the conformational flexibility of the alkenyl sulfonyliminoiodane. A mechanism is proposed involving formal 2 + 2 cycloaddition of the RSO(2)N=IPh group to the double bond followed by reductive elimination of PhI to yield the sulfonylaziridine. Green chemistry aspects of the process are highlighted.

The mechanism of 1,4 alkyl group migration in hypervalent halonium ylides: the stereochemical course.

Rhodium(II)-acetate-catalyzed decomposition of either 1,3-cyclohexanedione phenyliodonium ylide or 5,5-dimethyl-1,3-cyclohexanedione phenyliodonium ylide in the presence of alkyl halides yields the corresponding 3-alkoxy-2-halocyclohex-2-enones via a 1,4 alkyl group migration shown to be concerted and intramolecular. In the case of (S)-alpha-phenethyl chloride, the rearrangement proceeds with essentially 88.6% retention of configuration. Theoretical calculations at the B3LYP/6-31G level reveal an activation energy of 5.4 kcal/mol for the process. A Claisen-like rearrangement occurs in the case where allylic halides, such as dimethylallyl or methallyl chorides, are used. The mechanistic pathway proposed for these processes involves addition of the halogen atom of the alkyl or allyl halide to the rhodium carbenoid from the iodonium ylide to yield a halonium intermediate that undergoes halogen to oxygen group migration. Aryl halides, such as chloro-, bromo-, iodo-, and fluorobenzene, behave differently under the same reaction conditions, yielding the product of electrophilic aromatic substitution, namely, the 2-(4-halophenyl) 1,3-cyclohexanedione.

Performance of an IS6110-based PCR assay and the COBAS AMPLICOR MTB PCR system for detection of Mycobacterium tuberculosis complex DNA in human lymph node samples.

We compared the performance of two PCR assays, an IS6110-based in-house protocol and the COBAS AMPLICOR MTB PCR (COBAS MTB) system, for the detection of Mycobacterium tuberculosis complex in 43 human lymph node samples from 40 patients. For the in-house PCR and the COBAS MTB assays, respectively, sensitivities were 87.5% versus 45.5% (P < 0.05), specificities were 100.0% versus 91.3% (P > 0.05), and inhibition rates were 4.8% versus 19.5% (P < 0.05). For the COBAS MTB system, additional N-acetyl-L-cysteine-NaOH pretreatment of the samples changed neither the inhibition rate nor the sensitivity significantly.