Unlocking Trehalose's versatility: A comprehensive Journey from biosynthesis to therapeutic applications.

For over forty years, a sugar of rare configuration known as trehalose (two molecules of glucose linked at their 1-carbons), has been recognised for more than just its roles as a storage compound. The ability of trehalose to protect an extensive range of biological materials, for instance cell lines, tissues, proteins and DNA, has sparked considerable interest in the biotechnology and pharmaceutical industries. Currently, trehalose is now being investigated as a promising therapeutic candidate for human use, as it has shown potential to reduce disease severity in various experimental models. Despite its diverse biological effects, the precise mechanism underlying this observation remain unclear. Therefore, this review delves into the significance of trehalose biosynthesis pathway in the development of novel drug, investigates the inhibitors of trehalose synthesis and evaluates the binding efficiency of T6P with TPS1. Additionally, it also emphasizes the knowledge about the protective effect of trehalose on modulation of autophagy, combating viral infections, addressing the conditions like cancer and neurodegenerative diseases based on the recent advancement. Furthermore, review also highlight the trehalose's emerging role as a surfactant in delivering monoclonal antibodies that will further broadening its potential application in biomedicines.

Comprehensive genetic diversity and genome-wide association studies revealed the genetic basis of avocado fruit quality traits.

Introduction: Avocado (Persea americana) is a highly nutritious fruit gaining worldwide popularity. However, its cultivation is currently reliant on a limited number of cultivars with restricted genetic diversity. This study aims to investigate the genetic diversity and population structure of avocado germplasm and identify genetic loci associated with key fruit quality traits that influence customer preference. Methods: A diversity panel of 110 avocado accessions was analyzed using 4,706 high-quality single nucleotide polymorphisms (SNPs). Genetic diversity and population structure were analyzed using pairwise FST, AMOVA, admixture analysis, and phylogenetic analysis. Genome-wide association studies (GWAS) were conducted targeting nine fruit quality traits using two models: General Linear Model (GLM) with Principal Component Analysis (PCA) and Mixed Linear Model (MLM) with PCA and kinship (PCA + K). Results: The analysis revealed three distinct populations corresponding to the three avocado ecotypes: Guatemalan, West Indian, and Mexican. Phylogenetic analysis indicated a closer relationship between the Guatemalan and West Indian races compared to the Mexican race in our Florida germplasm collection. GWAS led to identification of 12 markers within 11 genomic regions significantly associated with fruit quality traits such as fruit color, shape, taste, and skin texture. These markers explained between 14.84% to 43.96% of the phenotypic variance, with an average of 24.63%. Annotation of these genomic regions unveiled candidate genes potentially responsible for controlling these traits. Discussion: The findings enhance our understanding of genetic diversity and population structure in avocado germplasm. The identified genetic loci provide valuable insights into the genetic basis of fruit quality traits, aiding breeding programs in developing improved avocado cultivars. Marker-assisted selection can accelerate the development of new varieties, promoting a more diverse and resilient avocado market.

Phase-Engineered MoSe2/CeO2 Composites for Room-Temperature Gas Sensing with a Drastic Discrimination of NH3 and TEA Gases.

Detecting and distinguishing between hazardous gases with similar odors by using conventional sensor technology for safeguarding human health and ensuring food safety are significant challenges. Bulky, costly, and power-hungry devices, such as that used for gas chromatography-mass spectrometry (GC-MS), are widely employed for gas sensing. Using a single chemiresistive semiconductor or electric nose (e-nose) gas sensor to achieve this objective is difficult, mainly because of its selectivity issue. Thus, there is a need to develop new materials with tunable and versatile sensing characteristics. Phase engineering of two-dimensional materials to better utilize their physiochemical properties has attracted considerable attention. Here, we show that MoSe2 phase-transition/CeO2 composites can be effectively used to distinguish ammonia (NH3) and triethylamine (TEA) at room temperature. The phase transition of nanocomposite samples from semimetallic (1T) to semiconducting (2H) prepared at different synthesis temperatures is confirmed via X-ray photoelectron spectroscopy (XPS). A composite sensor in which the 2H phase of MoSe2 is predominant lacks discrimination capability and is less responsive to NH3 and TEA. An MoSe2/CeO2 composite sensor with a higher 1T phase content exhibits high selectivity for NH3, whereas one with a higher 2H phase content (2H > 1T) shows more selective behavior toward TEA. For example, for 50% relative humidity, the MoSe2/CeO2 sensor's signal changes from the baseline by 45% and 58% for 1 ppm of NH3 and TEA, respectively, indicating a low limit of detection (LOD) of 70 and 160 ppb, respectively. The composites' superior sensing characteristics are mainly attributed to their large specific surface area, their numerous active sites, presence of defects, and the n-n type heterojunction between MoSe2 and CeO2. The sensing mechanism is elucidated using Raman spectroscopy, XPS, and GC-MS results. Their phase-transition characteristics render MoSe2/CeO2 sensors promising for use in distributed, low-cost, and room-temperature sensor networks, and they offer new opportunities for the development of integrated advanced smart sensing technologies for environmental and healthcare.

TLR10 (CD290) Is a Regulator of Immune Responses in Human Plasmacytoid Dendritic Cells.

TLRs are the most thoroughly studied group of pattern-recognition receptors that play a central role in innate immunity. Among them, TLR10 (CD290) remains the only TLR family member without a known ligand and clearly defined functions. One major impediment to studying TLR10 is its absence in mice. A recent study on TLR10 knock-in mice demonstrated its intrinsic inhibitory role in B cells, indicating that TLR10 is a potential drug target in autoimmune diseases. In this study, we interrogated the expression and function of TLR10 in human plasmacytoid dendritic cells (pDCs). We have seen that primary human pDCs, B cells, and monocytes constitutively express TLR10. Upon preincubation with an anti-TLR10 Ab, production of cytokines in pDCs was downregulated in response to stimulation with DNA and RNA viruses. Upon further investigation into the possible mechanism, we documented phosphorylation of STAT3 upon Ab-mediated engagement of TLR10. This leads to the induction of inhibitory molecule suppressor of cytokine signaling 3 (SOCS3) expression. We have also documented the inhibition of nuclear translocation of transcription factor IFN regulatory factor 7 (IRF7) in pDCs following TLR10 engagement. Our data provide the (to our knowledge) first evidence that TLR10 is constitutively expressed on the surface of human pDCs and works as a regulator of their innate response. Our findings indicate the potential of harnessing the function of pDCs by Ab-mediated targeting of TLR10 that may open a new therapeutic avenue for autoimmune disorders.

A Machine Learning Approach to Identify C Type Lectin Domain (CTLD) Containing Proteins.

Lectins are sugar interacting proteins which bind specific glycans reversibly and have ubiquitous presence in all forms of life. They have diverse biological functions such as cell signaling, molecular recognition, etc. C-type lectins (CTL) are a group of proteins from the lectin family which have been studied extensively in animals and are reported to be involved in immune functions, carcinogenesis, cell signaling, etc. The carbohydrate recognition domain (CRD) in CTL has a highly variable protein sequence and proteins carrying this domain are also referred to as C-type lectin domain containing proteins (CTLD). Because of this low sequence homology, identification of CTLD from hypothetical proteins in the sequenced genomes using homology based programs has limitations. Machine learning (ML) tools use characteristic features to identify homologous sequences and it has been used to develop a tool for identification of CTLD. Initially 500 sequences of well annotated CTLD and 500 sequences of non CTLD were used in developing the machine learning model. The classifier program Linear SVC from sci kit library of python was used and characteristic features in CTLD sequences like dipeptide and tripeptide composition were used as training attributes in various classifiers. A precision, recall and multiple correlation coefficient (MCC) value of 0.92, 0.91 and 0.82 respectively were obtained when tested on external test set. On fine tuning of the parameters like kernel, C value, gamma, degree and increasing number of non CTLD sequences there was improvement in precision, recall and MCC and the corresponding values were 0.99, 0.99 and 0.96. New CTLD have also been identified in the hypothetical segment of human genome using the trained model. The tool is available on our local server for interested users.

Less is more: Validating a single method for comprehensive rh-insulin analysis.

The objective of this current study is to establish a single method for potency and related proteins analysis of human insulin formulations using reverse-phase high performance liquid (RP-HPLC) chromatography technique which was validated and verified for the potency analysis in insulin formulations. Chromatographic separation was achieved using an octadecylsilane (C-18) stationary phase and a mobile phase composed of 55% (v/v) buffer (0.2 M sodium sulfate in water, {pH 2.3}) and 45% (v/v) acetonitrile. Detection was performed by UV detector at 214 nm with a flow rate of 1 ml/min and an injection volume of 20 µL, at 40°C. Currently there are separate methods available in Indian Pharmacopoeia for analysis of Potency and Related proteins in human insulin. We have validated a single method where quantitation of potency and related proteins can be performed in the same run. The method validation exhibited linearity over the concentration range of 0.08-4.5 mg/ml (r2=0.999) with limit of detection of 0.094 mg/ml The accuracy of the method was 99-102.8%. Thus, it is proposed that both potency and related proteins in insulin formulations can be precisely evaluated using a single run thus saving the time and cost for quality analysis of insulin preparations both at manufacturing and regulatory laboratories which in turn will increase the market availability of such standard quality insulin preparations for public health use.

Porous SnO2 nanosheets for room temperature ammonia sensing in extreme humidity.

Gas sensors based on tin dioxide (SnO2) for the detection of ammonia (NH3) have become commercially available for environmental monitoring due to their reactive qualities when exposed to different gaseous pollutants. Nevertheless, their implementation in the medical field has been hindered by certain inherent drawbacks, such as needing to operate at high temperatures, lack of selectivity, unreliable operation under high-humidity conditions, and a lower detection limit. To counter these issues, this study created 2D nanosheets of SnO2 through an optimized solvothermal method. It was found that tuning the precursor solution's pH to either neutral or 14 led to aggregated or distributed, uniform-size nanosheets with a higher crystallinity, respectively. Remarkably, the SnO2 nanosheet sensor (SNS-14) displayed a much lower response to water molecules and specific reactivity to ammonia even when subjected to reducing and oxidizing agents at 25 °C due to the micropores and chemisorbed oxygen on the nanosheets. Furthermore, the SNS-14 was seen to have the highest sensitivity to ammonia at 100 ppm, with rapid response (8 s) and recovery times (55 s) even at a high relative humidity of 70%. Its theoretical detection limit was recorded to be 64 ppt, better than any of the earlier SnO2-based chemiresistive sensors. Its exceptional sensing abilities were credited to its optimal crystallinity, specific surface area, defects, chemisorbed oxygen, and porous structure. NH3-TPD measurements and computational simulations were employed to understand the ammonia interaction with atomistic details on the SnO2 nanosheet surface. A real time breath sensing experiment was simulated to test the efficacy of the sensor. Reaching this advancement is an achievement in bypassing past boundaries of SnO2-centered sensors, making it feasible to detect ammonia with enhanced precision, discrimination, dependability, and velocity for probable usages in medical diagnostics and ecological surveillance.

Paradigms and Success Stories of Natural Products in Drug Discovery Against Neurodegenerative Disorders (NDDs).

Neurodegenerative disorders (NDDs) are multifaceted complex disorders that have put a great health and economic burden around the globe nowadays. The multi-factorial nature of NDDs has presented a great challenge in drug discovery and continuous efforts are in progress in search of suitable therapeutic candidates. Nature has a great wealth of active principles in its lap that has cured the human population since ancient times. Natural products have revealed several benefits over conventional synthetic medications and scientists have shifted their vision towards exploring the therapeutic potentials of natural products in the past few years. The structural mimicking of natural compounds to endogenous ligands has presented them as a potential therapeutic candidate to prevent the development of NDDs. In the presented review, authors have summarized demographical facts about various NDDs including Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD) and various types of sclerosis in the brain. The significant findings of new active principles of natural origin along with their therapeutic potentials on NDDs have been included. Also, a description of clinical trials and patents on natural products has been enlisted in this compilation. Although natural products have shown promising success in drug discovery against NDDs, still their use is associated with several ethical issues which need to be solved in the upcoming time.

Functionalized Multiwalled Carbon Nanotubes for Highly Stable Room Temperature and Humidity-Tolerant Triethylamine Sensing.

Triethylamine (TEA) poses a significant threat to our health and is extremely difficult to detect at the parts-per-billion (ppb) level at room temperature. Carbon nanotubes (CNTs) are versatile materials used in chemiresistive vapor sensing. However, achieving high sensitivity and selectivity with a low detection limit remains a challenge for pristine CNTs, hindering their widespread commercial application. To address these issues, we propose functionalized multiwalled CNTs (MWCNTs) with carboxylic acid (COOH)-based sensing channels for ultrasensitive TEA detection under ambient conditions. Advanced structural analyses confirmed the necessary modification of MWCNTs after functionalization. The sensor exhibited excellent sensitivity to TEA in air, with a superior noise-free signal (10 ppb), an extremely low limit of detection (LOD ≈ 0.8 ppb), excellent repeatability, and long-term stability under ambient conditions. Moreover, the response values became more stable, demonstrating excellent humidity resistance (40-80% RH). Notably, the functionalized MWCNT sensor exhibited improved response and recovery kinetics (200 and 400 s) to 10 ppm of TEA compared to the pristine MWCNT sensor (400 and 1300 s), and the selectivity coefficient for TEA gas was improved by approximately three times against various interferants, including ammonia, formaldehyde, nitrogen dioxide, and carbon monoxide. The remarkable improvements in TEA detection were mainly associated with the large specific surface area, abundant active sites, adsorbed oxygen, and other defects. The sensing mechanism was thoroughly explained by using Raman spectroscopy, X-ray photoelectron spectroscopy (XPS), and gas chromatography-mass spectrometry (GC-MS). This study provides a new platform for CNT-based chemiresistive sensors with high selectivity, low detection limits, and enhanced precision with universal potential for applications in food safety and environmental monitoring.

Microplastics in environment: a comprehension on sources, analytical detection, health concerns, and remediation.

Contamination of ecosystems by microplastics (MPs) has been reported intensively worldwide in the recent decade. A trend of reports indicated their presence in the atmosphere; food items and soil ecosystems are rising continuously. Literature evidenced that MPs are abundant in seawater, beach sand, drinking water, agricultural soils, wastewater treatment plant (WWTP) effluent, and the atmosphere. The greater abundance of MPs in the environment has led to their invasion of seafood, human-consumed food items such as table salts, beverages, takeout food containers, and disposable cups, marine biological lives, and creating serious health hazards in humans. Moreover, the absence of guidelines and specifications for controlling MPs in the environment makes the situation alarming, and the human toxicity data of MPs is scarce. Thereby, the toxicity assessment of MPs in humans is of greater concern. This review compiles the updated information on the potential sources of MPs in different components of the environment (viz. soil, water, and air), their analysis methods, effects on human health, and remediation methods.

The increase in cell death rates in caloric restricted cells of the yeast helicase mutant rrm3 is Sir complex dependent.

Calorie restriction (CR), which is a reduction in calorie intake without malnutrition, usually extends lifespan and improves tissue integrity. This report focuses on the relationship between nuclear genomic instability and dietary-restriction and its effect on cell survival. We demonstrate that the cell survival rates of the genomic instability yeast mutant rrm3 change under metabolic restricted conditions. Rrm3 is a DNA helicase, chromosomal replication slows (and potentially stalls) in its absence with increased rates at over 1400 natural pause sites including sites within ribosomal DNA and tRNA genes. Whereas rrm3 mutant cells have lower cell death rates compared to wild type (WT) in growth medium containing normal glucose levels (i.e., 2%), under CR growth conditions cell death rates increase in the rrm3 mutant to levels, which are higher than WT. The silent-information-regulatory (Sir) protein complex and mitochondrial oxidative stress are required for the increase in cell death rates in the rrm3 mutant when cells are transferred from growth medium containing 2% glucose to CR-medium. The Rad53 checkpoint protein is highly phosphorylated in the rrm3 mutant in response to genomic instability in growth medium containing 2% glucose. Under CR, Rad53 phosphorylation is largely reduced in the rrm3 mutant in a Sir-complex dependent manner. Since CR is an adjuvant treatment during chemotherapy, which may target genomic instability in cancer cells, our studies may gain further insight into how these therapy strategies can be improved.

Genetic analysis of iron, zinc and grain yield in wheat-Aegilops derivatives using multi-locus GWAS.

BACKGROUND: Wheat is a major staple crop and helps to reduce worldwide micronutrient deficiency. Investigating the genetics that control the concentrations of iron (Fe) and zinc (Zn) in wheat is crucial. Hence, we undertook a comprehensive study aimed at elucidating the genomic regions linked to the contents of Fe and Zn in the grain. METHODS AND RESULTS: We performed the multi-locus genome-wide association (ML-GWAS) using a panel of 161 wheat-Aegilops substitution and addition lines to dissect the genomic regions controlling grain iron (GFeC), and grain zinc (GZnC) contents. The wheat panel was genotyped using 10,825 high-quality SNPs and phenotyped in three different environments (E1-E3) during 2017-2019. A total of 111 marker-trait associations (MTAs) (at p-value < 0.001) were detected that belong to all three sub-genomes of wheat. The highest number of MTAs were identified for GFeC (58), followed by GZnC (44) and yield (9). Further, six stable MTAs were identified for these three traits and also two pleiotropic MTAs were identified for GFeC and GZnC. A total of 1291 putative candidate genes (CGs) were also identified for all three traits. These CGs encode a diverse set of proteins, including heavy metal-associated (HMA), bZIP family protein, AP2/ERF, and protein previously associated with GFeC, GZnC, and grain yield. CONCLUSIONS: The significant MTAs and CGs pinpointed in this current study are poised to play a pivotal role in enhancing both the nutritional quality and yield of wheat, utilizing marker-assisted selection (MAS) techniques.

Infection and inflammation stimulate expansion of a CD74+ Paneth cell subset to regulate disease progression.

Paneth cells (PCs), a specialized secretory cell type in the small intestine, are increasingly recognized as having an essential role in host responses to microbiome and environmental stresses. Whether and how commensal and pathogenic microbes modify PC composition to modulate inflammation remain unclear. Using newly developed PC-reporter mice under conventional and gnotobiotic conditions, we determined PC transcriptomic heterogeneity in response to commensal and invasive microbes at single cell level. Infection expands the pool of CD74+ PCs, whose number correlates with auto or allogeneic inflammatory disease progressions in mice. Similar correlation was found in human inflammatory disease tissues. Infection-stimulated cytokines increase production of reactive oxygen species (ROS) and expression of a PC-specific mucosal pentraxin (Mptx2) in activated PCs. A PC-specific ablation of MyD88 reduced CD74+ PC population, thus ameliorating pathogen-induced systemic disease. A similar phenotype was also observed in mice lacking Mptx2. Thus, infection stimulates expansion of a PC subset that influences disease progression.

A Compiled Update on Nutrition, Phytochemicals, Processing Effects, Analytical Testing and Health Effects of Chenopodium album: A Non-Conventional Edible Plant (NCEP).

Bathua (Chenopodium album) is a rich source of extensive-ranging nutrients, including bio-active carbohydrates, flavonoids and phenolics, minerals, and vitamins that translate to countless health benefits such as anticancer, antidiabetic, anti-inflammatory, antimicrobial, and antioxidant activity. Ascaridole, an important phytoconstituent present in aerial parts of the plant, contributes to its anthelmintic property. Even with vast historical use and significant health benefits, its renown has not spread, and utilization has significantly decreased in recent decades. Gradually, the plant has become known under the name of Non-conventional edible plant (NCEP). This compilation is prepared to bring out the plant under the spotlight for further research by foregrounding previous studies on the plant. Scientific research databases, including PubMed, Google Scholar, Scopus, SpringerLink, ScienceDirect, and Wiley Online, were used to fetch data on C. album. This review offers over up-to-date knowledge on nutritious values, phytochemical composition, volatile compounds, as well as health benefits of C. album. The ethnobotanical and ethnomedicinal uses of the plant in India and other parts of the world are deliberately discussed. Scrutinizing the reported literature on C. album reveals its powerful nutrient composition advantageous in the development of food products. The impact of various cooking and processing methods on the nutritional profile and bioavailability are discussed. The future perspectives with regards to the potential for food and nutraceutical products are critically addressed. This review proves the necessity of breakthrough research to investigate the pharmacology and safety of phytochemicals and nutraceutical development studies on the C. album.

Agricultural and Socioeconomic Factors Associated with Farmer Household Dietary Diversity in India: A Comparative Study of Visakhapatnam and Sonipat.

Using primary data from 479 farmer households, this study examined the associations between agricultural and socioeconomic factors and farmer household dietary diversity in Visakhapatnam and Sonipat. Cropping intensity was positively associated with farmers' household dietary diversity score (HDDS), suggesting that higher cropping intensity may expand the gross cropped area and improve food security among subsistence farmers. Distance to food markets was also significantly associated with farmer HDDS, which suggests that market integration with rural households can improve farmer HDDS in Visakhapatnam. In Sonipat, wealth index had a positive association with farmer HDDS, targeting the income pathway by improving farmer HDDS in this region. Considering the relative contribution of these factors, distance to food markets, cropping intensity, and crop diversity were the three most important factors affecting farmer HDDS in Visakhapatnam, whereas wealth index, cropping intensity, and distance to food markets emerged as the top three important factors contributing to farmer HDDS in Sonipat. Our study concludes that the associations between agricultural and socioeconomic factors and farmer HDDS are complex but context- and location-specific; therefore, considering the site- and context-specific circumstances, different connections to HDDS in India can be found to better support policy priorities on the ground.

An Automated Segmentation of Leukocytes Using Modified Watershed Algorithm on Peripheral Blood Smear Images.

Leukemia can be detected by an abnormal rise in the number of immature lymphocytes and by a decrease in the number of other blood cells. To diagnose leukemia, image processing techniques are utilized to examine microscopic peripheral blood smear (PBS) images automatically and swiftly. To the best of our knowledge, the initial step in subsequent processing is a robust segmentation technique for identifying leukocytes from their surroundings. The paper presents the segmentation of leukocytes in which three color spaces are considered in this study for image enhancement. The proposed algorithm uses a marker-based watershed algorithm and peak local maxima. The algorithm was used on three different datasets with various color tones, image resolutions, and magnifications. The average precision for all three-color spaces was the same, i.e. 94% but the Structural Similarity Index Metric (SSIM) and recall of HSV were better than other two. The results of this study will aid experts in narrowing down their options for segmenting leukemia. Based on the comparison, it was concluded that when the colour space correction technique is used, the accuracy of the proposed methodology improves.

Cognitive remediation and schizophrenia: Effects on brain complexity.

The objective of this study is to investigate nonlinear neural dynamics of chronic patients with schizophrenia following 3 months of cognitive remediation and to find correlations with neuropsychological measures of cognition. Twenty nine patients were randomized to Cognitive Training (CT) and Treatment as Usual (TAU) group. The system complexity is estimated by Correlation Dimension (D2) and Largest Lyapunov Exponent (LLE) from the reconstructed attractor of the underlying system. Significant increase in dimensional complexity (D2) over time is observed in prefrontal and medial frontal-central regions in eyes open and arithmetic condition; and posterior parietal-occipital region under eyes closed after 3 months. Dynamical complexity (LLE) significantly decreased over time in medial left central region under eyes closed and eyes open condition; prefrontal region in eyes open and lateral right temporal region in arithmetic condition. Interaction is significant for medial left central region with TAU group exhibiting greater decrease in LLE compared to CT group. The CT group showed significant correlation of increased D2 with focused attention. In this study it is found that patients with schizophrenia exhibit higher dimensional and lower dynamical complexity over time indicating improvement in neurodynamics of underlying physiological system.

Bcl-x short-isoform is essential for maintaining homeostasis of multiple tissues.

BCL-2-like protein 1 (BCL2L1) is a key component of cell survival and death mechanisms. Its dysregulation and altered ratio of splicing variants associate with pathologies. However, isoform-specific loss-of-function analysis of BCL2L1 remains unexplored. Here we show the functional impact of genetically inhibiting Bcl-x short-isoform (Bcl-xS) in vivo. Bcl-xS is expressed in most tissues with predominant expression in the spleen and blood cells in mice. Bcl-xS knockout (KO) mice show no overt abnormality until 3 months of age. Thereafter, KO mice develop cardiac hypertrophy with contractile dysfunction and splenomegaly by 6 months. Cardiac fibrosis significantly increases in KO, but the frequency of apoptosis is indistinguishable despite cardiomyopathy. The Akt/mTOR and JNK/cJun signaling are upregulated in male KO heart, and the JNK/cJun is activated with increased Bax expression in KO spleen. These results suggest that Bcl-xS may be dispensable for development but is essential for maintaining the homeostasis of multiple organs.