Journal of Biosciences最新文献

Immunotherapy is a promising and safer alternative to conventional cancer therapies. It involves adaptive T-cell therapy, cancer vaccines, monoclonal antibodies, immune checkpoint blockade (ICB), and chimeric antigen receptor (CAR) based therapies. However, most of these modalities encounter restrictions in solid tumours owing to a dense, highly hypoxic and immune-suppressive microenvironment as well as the heterogeneity of tumour antigens. The elevated intra-tumoural pressure and mutational rates within fastgrowing solid tumours present challenges in efficient drug targeting and delivery. The tumour microenvironment is a dynamic niche infiltrated by a variety of immune cells, most of which are macrophages. Since they form a part of the innate immune system, targeting macrophages has become a plausible immunotherapeutic approach. In this review, we discuss several versatile approaches (both at pre-clinical and clinical stages) such as the direct killing of tumour-associated macrophages, reprogramming pro-tumour macrophages to anti-tumour phenotypes, inhibition of macrophage recruitment into the tumour microenvironment, novel CAR macrophages, and genetically engineered macrophages that have been devised thus far. These strategies comprise a strong and adaptable macrophage-toolkit in the ongoing fight against cancer and by understanding their significance, we may unlock the full potential of these immune cells in cancer therapy.

One of the integral part of the network analysis is finding groups of nodes that exhibit similar properties. Community detection techniques are a popular choice to find such groups or communities within a network and it relies on graph-based methods to achieve this goal. Finding communities in biological networks such as gene co-expression networks are particularly important to find groups of genes where we can focus on further downstream analysis and find valuable insights regarding concerned diseases. Here, we present an effective community detection method called community detection using centrality-based approach (CDCA), designed using the graph centrality approach. The method has been tested using four benchmark bulk RNA-seq datasets for schizophrenia and bipolar disorder, and the performance has been proved superior in comparison to several other counterparts. The quality of communities are determined using intrinsic graph properties such as modularity and homogeneity. The biological significance of resultant communities is decided using the pathway enrichment analysis.

Atherosclerosis is a common cardiovascular disease in which the arteries are thickened due to buildup of plaque. This study aims to identify programmed cell death (PCD)-related biomarkers and explore the crucial regulatory mechanisms of atherosclerosis. Gene expression profiles of atherosclerosis and control groups from GSE20129 and GSE23746 were obtained. Necroptosis was elevated in atherosclerosis. Weighted gene coexpression network analysis (WGCNA) was conducted in GSE23746 and GSE56045 to identify PCD-related modules and to perform enrichment analysis. Two necroptosis-related genes (IRF9 and STAT1) were identified and considered as biomarkers. Enrichment analysis showed that these gene modules were mainly related to immune response regulation. In addition, single-cell RNA sequencing data from GSE159677 were obtained and the characteristic cell types of atherosclerosis were identified. A total of 11 immune cell types were identified through UMAP dimension reduction. Most immune cells were mainly enriched in plaque samples, and STAT1 and IRF9 were primarily expressed in T-cells and macrophages. Moreover, the roles of IRF9 and STAT1 were assessed and found to be significantly upregulated in atherosclerosis, which was associated with increased risk of atherosclerosis. This study provides a molecular feature of atherosclerosis, offering an important basis for further research on its pathological mechanisms and the search for new therapeutic targets.

The migration and dispersal of organisms is fascinating from many perspectives and, in the case of crop plants, intersects with the movement of human beings. As they explore new areas, agricultural peoples carry seeds of crops, which move and may establish ('diffuse') where they go. In order to understand the movement of the crop across regions, we need to understand the pattern and rate of diffusion of the crop, as well as that of the people involved, both those who carried it and those who adopted it. What determines whether a particular crop will establish in a new region with a different climate and other environmental factors (e.g., precipitation), likely necessitating genetic change through natural or artificial selection (e.g., Rendo´n-Anaya et al. 2017)? The extent to which the rate of diffusion is determined by evolutionary and environmental processes, on the one hand, and human migratory processes, on the other, is a complex question that has not been resolved even for as intensively studied a crop as maize (Stoneking et al. 2023).

Increasing soil and underground water salinization with decreasing availability of fresh water has become a potential threat to sustainable crop production in arid and semi-arid areas globally. Introduction and evaluation of salt-tolerant halophytic crops is one of the sustainable ways to preserve productivity in saline ecosystems. This study was aimed to screen quinoa germplasms under high-sodium adsorption ratio (SAR) saline stress. Thirteen quinoa germplasms were evaluated under four levels [best available water (BAW), 8, 16, and 24 dSm^-1] of high-SAR saline water irrigation. The evaluation was carried out based on growth, yield, and ionic content parameters along with statistical tools such as multivariate analysis, salt tolerance indices, and correlation. The results showed that the salinity levels of 16 and 24 dSm^-1 resulted in increase of chlorophyll content relative to BAWand 8 dSm^-1. The germplasm CSQ2 recorded the highest proline content (163.7 mg g^-1 FW) at 24 dSm^-1. Increasing levels of salinity reduced relative water content in plant leaves, and the germplasm CSQ2 showed minimal reduction of 4% at 24 dSm^-1. Na⁺ and K⁺ contents in the plants increased with increasing salinity levels, while the K⁺/Na⁺ ratio decreased. The grain yield of quinoa germplasms ranged between 3.5 and 14.1 g plant^-1. The germplasm EC507740 recorded the highest grain yield (7.0 g plant^-1) followed by CSQ1 and CSQ2 at a maximum stress of 24 dSm^-1. Principal component analysis (PCA) and correlation elucidated that Na⁺ content in plants was negatively correlated with all the studied traits except SPAD, proline content, and K⁺ content. The different salt tolerance indices indicated that the germplasms EC507740, CSQ1, CSQ2, EC507738, and IC411825 were more stable at high-SAR salinity, while PCA showed the germplasms EC507740 and CSQ2 as the most salt-tolerant germplasms.

Rare muscular disorders (RMDs) are disorders that affect a small percentage of the population. The disorders which are attributed to genetic mutations often manifest in the form of progressive weakness and atrophy of skeletal and heart muscles. RMDs includes disorders such as Duchenne muscular dystrophy (DMD), GNE myopathy, spinal muscular atrophy (SMA), limb girdle muscular dystrophy, and so on. Due to the infrequent occurrence of these disorders, development of therapeutic approaches elicits less attention compared with other more prevalent diseases. However, in recent times, improved understanding of pathogenesis has led to greater advances in developing therapeutic options to treat such diseases. Exon skipping, gene augmentation, and gene editing have taken the spotlight in drug development for rare neuromuscular disorders. The recent innovation in targeting and repairing mutations with the advent of CRISPR technology has in fact opened new possibilities in the development of gene therapy approaches for these disorders. Although these treatments show satisfactory therapeutic effects, the susceptibility to degradation, instability, and toxicity limits their application. So, an appropriate delivery vector is required for the delivery of these cargoes. Viral vectors are considered potential delivery systems for gene therapy; however, the associated concurrent immunogenic response and other limitations have paved the way for the applications of other non-viral systems like lipids, polymers, cellpenetrating peptides (CPPs), and other organic and inorganic materials. This review will focus on non-viral vectors for the delivery of therapeutic cargoes in order to treat muscular dystrophies.

Spinal muscular atrophy (SMA) is a neuromuscular, rare genetic disorder caused due to loss-of-function mutations in the survival motor neuron-1 (SMN1) gene, leading to deficiency of the SMN protein. The severity of the disease phenotype is inversely proportional to the copy number of another gene, SMN2, that differs from SMN1 by a few nucleotides. The current diagnostic methods for SMA include symptom-based diagnosis, biochemical methods like detection of serum creatine kinase, and molecular detection of disease-causing mutations using polymerase chain reaction (PCR), multiplex ligation-dependent probe amplification (MLPA), and exome or next-generation sequencing (NGS). Along with detection of the disease-causing mutation in the SMN1 gene, it is crucial to identify the copy number of the SMN2 gene, which is a disease modifier. Therapeutic options like gene therapy, antisense therapy, and small molecules are available for SMA, but, the costs are prohibitively high. This review discusses the prevalence, diagnosis, available therapeutic options for SMA, and their clinical trials in the Indian context, and highlights the need for measures to make indigenous diagnostic and therapeutic interventions.

In recent years, several experimental evidences suggest that amino acid repeats are closely linked to many disease conditions, as they have a significant role in evolution of disordered regions of the polypeptide segments. Even though many algorithms and databases were developed for such analysis, each algorithm has some caveats, like limitation on the number of amino acids within the repeat patterns and number of query protein sequences. To this end, in the present work, a new method called the internal sequence repeats across multiple protein sequences (ISRMPS) is proposed for the first time to identify identical repeats across multiple protein sequences. It also identifies distantly located repeat patterns in various protein sequences. Our method can be applied to study evolutionary relationships, epitope mapping, CRISPR-Cas sequencing methods, and other comparative analytical assessments of protein sequences.

Disease cross-transmission between wild and domestic ungulates can negatively impact livelihoods and wildlife conservation. In Pin valley, migratory sheep and goats share pastures seasonally with the resident Asiatic ibex (Capra sibirica), leading to potential disease cross-transmission. Focussing on gastro-intestinal nematodes (GINs) as determinants of health in ungulates, we hypothesized that infection on pastures would increase over summer from contamination by migrating livestock. Consequently, interventions in livestock that are well-timed should reduce infection pressure for ibex. Using a parasite life-cycle model, that predicts infective larval availability, we investigated GIN transmission dynamics and evaluated potential interventions. Migratory livestock were predicted to contribute most infective larvae onto shared pastures due to higher density and parasite levels, driving infections in both livestock and ibex. The model predicted a c.30-day antiparasitic intervention towards the end of the livestock's time in Pin would be most effective at reducing GINs in both hosts. Albeit with the caveats of not being able to provide evidence of interspecific parasite transmission due to the inability to identify parasite species, this case demonstrates the usefulness of our predictive model for investigating parasite transmission in landscapes where domestic and wild ungulates share pastures. Additionally, it suggests management options for further investigation.

The objective of this study was to characterize the effects of barley powdery mildew infection on wheat via the evolution and dynamics of chloroplasts and oxidative processes based on in vivo measurements of ultra-weak photon emission, parallel measurement of chlorophyll and ascorbic acid content, and molecular identification of the pathogen. The results showed the temporal dynamics of the evolution of ultra-weak photon emission signals that were evidently different for healthy and powdery mildew-infested wheat leaves. In the dark, the ceasing of delayed fluorescence signal made it possible to visualize the ultra-weak luminescence signal as well. Both delayed fluorescence and ultra-weak luminescence signals were characteristic of stress symptoms induced by powdery mildew that was further strengthened by the changes of chlorophyll and ascorbic acid content as typical stress analytical parameters. The presented data and parameterization enabled the identification of stress induction due to powdery mildew infestation in wheat, which should be investigated in detail in the future for fine-tuning our measurements, even by using other species and increasing the length of the measurement in order to increase its specificity. The changes in R² values are suitable for monitoring the changes of plant stress response. The measurement of fluorescence and luminescence leads to a greater comprehension of the underlying photon emission-related processes, both in general and in the case of powdery mildew infestation.