Journal of Biosciences最新文献

Seed and seedling traits govern plant fitness and persistence and are influenced by the interaction between the plant and its environment. Changing climatic and edaphic conditions will drastically affect early fitness-related traits and can alter the demography and species distribution range. It is widely documented that trait variation among populations may increase resilience of tree communities and reduce the risk of extinction under future climates. In the present study, variation in seed and seedling traits were documented from seven populations of Santalum album representing the natural distribution range of the species in the Indian subcontinent. Significant intra-specific variation was documented in seed and seedling traits, indicating high adaptive potential of the species. Further, the measured traits were correlated with climatic variables. No significant correlation was predicted for seed-related traits, while seedling-related traits like shoot and root weight, photochemical reflectance index, relative water content, and root–shoot ratio correlated with different climatic parameters. Variance partitioning revealed predominant combined effect of environment and genotype on seed traits except seed weight, which was governed by genotypic effect. The dominance of genotypic effect was documented for all seed leachate parameters, while seedling-related traits were predominantly affected by the environment. Conservation of sandalwood genetic resources will benefit from the insights gained from the variability recorded in these fitness-related traits, which are likely to affect the adaptive potential of the species.

Rare diseases form the bulk of the financial expenditure of any developing or developed economy. Among the various rare diseases, paediatric neuromuscular disorders form a major portion, with a worldwide survey estimating a prevalence of 1 in 3500 individuals. In a lower middle-income country (LMIC) like India, malnutrition still accounts for most of the under-5 mortality. However, the economic burden of rare paediatric neuromuscular disorders cannot be underestimated. The treating physician should have a basic understanding of how to approach a child presenting with weakness and how to utilise the available tests which are affordable in an LMIC setting. History and examination still form the core, and with new diagnostic methods like next-generation sequencing, more and more rare disorders are getting diagnosed. It is important for the treating physician to know about basic supportive care, recent advancements, and available treatment options for these conditions. With exciting new treatment options being available for these disorders, the perception of these diseases as being not treatable is gradually changing. This review aims to be of guidance to clinicians from an LMIC setting like India and to empower them to manage such rare paediatric neuromuscular disorders.

Screening strategies for cancer, the second largest cause of deaths, exist, but are invasive, cumbersome, and expensive. Many cancers lack viable screening modalities all together. Circulating tumor cell clusters (CTCCs) are seen during early stages of cancer and are larger than normal blood cells. Discrimination of such differential sizes by real-time ultrasound scanning of a blood vessel offers an attractive universal screening tool for cancer. Yeast colonies were grown to different sizes mimicking CTCCs and normal blood cells, using sugar and starch to incubate and sodium fluoride to arrest growth after specified times. They were circulated using syringes and an infusion pump through a wall-less ultrasound phantom, made using agar (mimicking human soft tissue), and Doppler ultrasound was performed, with screenshots taken. Key characteristics of particles of interest were identified. Ultrasound data were processed and used to train a convolutional neural network (CNN). Six models with binary classification were tested. Doppler signals of CTCC surrogates could be visually distinguished from normal cells and normal saline, proving the principle of ultrasound size discrimination of CTCCs. The most accurate machine learning model yielded 98.35% accuracy in the prediction of CTCCs, exceeding human evaluation accuracy. Thus, machine learning could help automate and improve detection of cancer by screening for CTCCs.

Compartmental models that dynamically divide the host population into categories such as susceptible, infected, and immune constitute the mainstream of epidemiological modelling. Effectively, such models treat infection and immunity as binary variables. We constructed an individual-based stochastic model that considers immunity as a continuous variable and incorporates factors that bring about small changes in immunity. The small immunity effects (SIE) comprise cross-immunity by other infections, small increments in immunity by subclinical exposures, and slow decay in the absence of repeated exposure. The model makes qualitatively different epidemiological predictions, including repeated waves without the need for new variants, dwarf peaks (peak and decline of a wave much before reaching herd immunity threshold), symmetry in upward and downward slopes of a wave, endemic state, new surges after variable and unpredictable gaps, and new surges after vaccinating majority of the population. In effect, the SIE model raises alternative possible causes of universally observed dwarf and symmetric peaks and repeated surges, observed particularly well during the COVID-19 pandemic. We also suggest testable predictions to differentiate between the alternative causes for repeated waves. The model further shows complex interactions of different interventions that can be synergistic as well as antagonistic. It also suggests that interventions that are beneficial in the short run could also be hazardous in the long run.

The cation diffusion facilitator (CDF) family of zinc transporters plays a crucial role in zinc homeostasis in eukaryotes, including fungi. Here, we investigated the cell functions and genetic interactions of CDF zinc transporters zrc-1 and msc-2 in Neurospora crassa. The Δzrc-1 mutant could not grow in a high-zinc environment, indicating that the zinc transporter protein ZRC-1 was essential for growth in high-zinc conditions. However, the deletion of msc-2 did not show any severe phenotypic defects. Furthermore, we studied the genetic interactions of the zinc transporters using the CDF double mutants. Previously, zrg-17 was reported to be critical, where the Δzrg-17 mutant showed defects in both vegetative development and asexual sporulation. Interestingly, the Δmsc-2;Δzrg-17 double mutant showed phenotypes similar to the wild type, and restored the phenotypic defects of the Δzrg-17 mutation. However, the Δzrc-1;Δmsc-2 and Δzrc-1;Δzrg-17 double mutants continue to display phenotypic defects like their parental single mutants. The double mutant Δzrc-1;Δzrg-17 showed severe vegetative growth defects, including slow growth, short aerial hyphae, narrowed septation, and defective asexual sporulation. In addition, aerial hyphae development of the Δzrc-1;Δmsc-2 and Δzrc-1;Δzrg-17 double mutants were reduced under endoplasmic reticulum stress. Thus, this study revealed the cell functions and genetic interactions of zrc-1, msc-2, and zrg-17 for vegetative development and tolerance to stress conditions in N. crassa.

This study aims to develop fatty acid metabolism-related molecular subtypes and construct a fatty acid metabolism-related novel model for bladder cancer (BCa) by bioinformatic profiling. Genome RNA-seq expression data of BCa samples from the TCGA database and GEO database were downloaded. We then conducted consensus clustering analysis to identify fatty acid metabolism-related molecular subtypes for BCa. Univariate and multivariate Cox regression analysis were performed to identify a novel prognostic fatty acid metabolism-related prognostic model for BCa. Finally, we identified a total of three fatty acid metabolism-related molecular subtypes for BCa. These three molecular subtypes have significantly different clinical characteristics, PD-L1 expression levels, and tumor microenvironments. Also, we developed a novel fatty acid metabolism-related prognostic model. Patients with low-risk score have significantly preferable overall survival compared with those with high-risk score in the training, testing, and validating cohorts. The area under the ROC curve (AUC) for overall survival prediction was 0.746, 0.681, and 0.680 in the training, testing and validating cohorts, respectively. This model was mainly suitable for male, older, high-grade, cluster 2–3, any TCGA stage, any N-stage, and any T-stage patients. Besides, we selected FASN as a hub gene for BCa and further qRT-PCR validation was successfully conducted. In conclusion, we developed and successfully validated a novel fatty acid metabolism-related prognostic model for predicting outcome for BCa patients.

Accumulated evidence implicates lipid peroxidation as a key mechanism contributing to the pathogenesis of lupus nephritis (LN). Ferroptosis is a specialized form of cell death induced by loss or deficient activity of the glutathione peroxidase 4 (GPX4) and decreased clearance of polyunsaturated fatty acid hydroperoxides. STING production may lead to the occurrence of intracellular lipid peroxidation, ultimately triggering ferroptosis, but it has not been clarified whether STING can aggravate LN via ferroptosis. The adjacent normal kidney tissues from renal cell carcinoma and biopsied kidney tissue samples from LN patients were used for research, and the expression of STING protein in kidney tissue was detected by immunohistochemistry and RT-qPCR. MRL/lpr mice, a model of LN, were used to detect STING expression in kidney tissue. STING expression in the kidney tissue of MRL/lpr mice was knocked down by sh-STING-AAV, and then levels of 4-HNE, MDA, ROS, iron ion, blood urea nitrogen and serum creatinine, IL-6, IL-1β, and TNF-α, and the protein expression of STING, TBK1, NF-κB, GPX4, ACSL4, and SLC7A11 were subsequently examined. STING was elevated in the kidney tissue of LN patients and MRL/lpr mice. Compared with the MRL/lpr group, liproxstatin-1 or ferrostatin-1 treatment alleviated ferroptosis-related indicators 4-HNE, MDA, ROS, iron ion release, and GPX4 and SLC7A1 expression, whereas the treatment enhanced ACSL4 expression. STING interference observably decreased 4-HNE, ROS, MDA, iron ion, STING, and ACSL4 levels, and increased GPX4 and SLC7A11 expression in MRL/lpr mice kidney tissues. Besides, inhibition of STING reduced kidney tissue damage and inflammatory cell infiltration in MRL/lpr mice, and levels of serum creatinine, blood urea nitrogen, serum anti-double-stranded DNA antibody, inflammatory factors IL-6, IL-1β, and TNF-α, as well as phosphorylation of NF-κB were all significantly decreased in MRL/lpr mice. TBK1 overexpression reversed the impact of STING inhibition on ferroptosis and inflammatory response. STING contributed to ferroptosis and inflammatory response by activating the TBK1/NF-κB pathway, suggesting that STING may be a potent therapeutic target in LN.

Bees have been excellent model systems to study social learning - the ability of animals to change their behaviour based on observations of other individuals. Researchers have investigated several aspects of social learning in bees, including how it can lead to cultural traditions. A recent study also argues that bees have the capacity to socially learn behaviours that they could not innovate on their own. To understand these findings better, I review what we know about the mechanisms underlying social learning in bees and use these findings to compare social learning and culture in bees and humans. The findings suggest that the seemingly complex social behaviours of bees could arise from simple mechanisms underlying learning in general. I highlight the importance of investigating cognitive mechanisms and how they might differ across animals.

Seed and seedling traits govern plant fitness and persistence and are influenced by the interaction between the plant and its environment. Changing climatic and edaphic conditions will drastically affect early fitnessrelated traits and can alter the demography and species distribution range. It is widely documented that trait variation among populations may increase resilience of tree communities and reduce the risk of extinction under future climates. In the present study, variation in seed and seedling traits were documented from seven populations of Santalum album representing the natural distribution range of the species in the Indian subcontinent. Significant intra-specific variation was documented in seed and seedling traits, indicating high adaptive potential of the species. Further, the measured traits were correlated with climatic variables. No significant correlation was predicted for seed-related traits, while seedling-related traits like shoot and root weight, photochemical reflectance index, relative water content, and root-shoot ratio correlated with different climatic parameters. Variance partitioning revealed predominant combined effect of environment and genotype on seed traits except seed weight, which was governed by genotypic effect. The dominance of genotypic effect was documented for all seed leachate parameters, while seedling-related traits were predominantly affected by the environment. Conservation of sandalwood genetic resources will benefit from the insights gained from the variability recorded in these fitness-related traits, which are likely to affect the adaptive potential of the species.