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Abstract This study aimed to classifying wheat genotypes using support vector machines (SVMs) improved with ensemble algorithms and optimization techniques. Utilizing data from 302 wheat genotypes and 14 morphological attributes to evaluate six SVM kernels: linear, radial basis function (RBF), sigmoid, and polynomial degrees 1–3. Various optimization methods, including grid search, random search, genetic algorithms, differential evolution, and particle swarm optimization, were used. The radial basis function kernel achieves the highest accuracy at 93.2%, and the weighted accuracy ensemble further improves it to 94.9%. This study shows the effectiveness of these methods in agricultural research and crop improvement. Notably, optimization-based SVM classification, particularly with particle swarm optimization, saw a significant 1.7% accuracy gain in the test set, reaching 94.9% accuracy. These findings underscore the efficacy of RBF kernels and optimization techniques in improving wheat genotype classification accuracy and highlight the potential of SVMs in agricultural research and crop improvement endeavors.

Abstract Multiple studies have demonstrated that cancer cells with microsatellite instability (MSI) are intolerant to loss of the Werner syndrome helicase (WRN), whereas microsatellite-stable (MSS) cancer cells are not. Therefore, WRN represents a promising new synthetic lethal target for developing drugs to treat cancers with MSI. Given the uncertainty of how effective inhibitors of WRN activity will prove in clinical trials, and the likelihood of tumours developing resistance to WRN inhibitors, alternative strategies for impeding WRN function are needed. Proteolysis-targeting chimeras (PROTACs) are heterobifunctional small molecules that target specific proteins for degradation. Here, we engineered the WRN locus so that the gene product is fused to a bromodomain (Bd)-tag, enabling conditional WRN degradation with the AGB-1 PROTAC specific for the Bd-tag. Our data revealed that WRN degradation is highly toxic in MSI but not MSS cell lines. In MSI cells, WRN degradation caused G2/M arrest, chromosome breakage and ATM kinase activation. We also describe a multi-colour cell-based platform for facile testing of selective toxicity in MSI versus MSS cell lines. Together, our data show that a degrader approach is a potentially powerful way of targeting WRN in MSI cancers and paves the way for the development of WRN-specific PROTAC compounds.

Abstract Oscillatory flow in confined spaces is central to understanding physiological flows and rational design of synthetic periodic-actuation based micromachines. Using theory and experiments on oscillating flows generated through a laser-induced cavitation bubble, we associate the dynamic bubble size (fluid velocity) and bubble lifetime to the laser energy supplied—a control parameter in experiments. Employing different channel cross-section shapes, sizes and lengths, we demonstrate the characteristic scales for velocity, time and energy to depend solely on the channel geometry. Contrary to the generally assumed absence of instability in low Reynolds number flows ( $$

Abstract This work experimentally addresses damage calibration of an unmanned aerial vehicle in operational condition. A wide range of damage level and types are simulated and controlled by an electric motor via pulse width modulation in this regard. The measurement is carried out via established protocols of using a piezo-patch on one of the 8 arms, utilising the vibration sensitivity and flexibility of the arms, demonstrating repeatability of such protocol. Subsequently, recurrence analysis on the voltage time series data is performed for detection of damage. Quantifiers of damage extent are then created for the full range of damage conditions, including the extreme case of complete loss of power. Experimental baseline condition for no damage condition is also established in this regard. Both diagonal-line and vertical-line based indicators from recurrence analysis are sensitive to the quantitative estimates of damage levels and a statistical test of significance analysis confirms that it is possible to automate distinguishing the levels of damage. The damage quantifiers proposed in this paper are useful for rapid monitoring of unmanned aerial vehicle operations of connection.

Abstract One of the most vital parameters to achieve sustainability in any field is encompassing the Occupational Health and Safety (OHS) of the workers. In mining industry where heavy earth moving machineries are largely employed, ergonomic hazards turn out to be significant OHS hazards causing Musculoskeletal Disorders (MSDs) in the operators. Nevertheless, the Indian mining industry lacks a comprehensive technique of OHS risk assessment, especially for ergonomic hazards that cause MSDs. This research appraises ergonomic hazards and develops Fuzzy Musculoskeletal-disorders Index (FMI) model to evaluate ergonomic-related MSDs. Work process and work tool ergonomic risk factors were identified through literature review and directives recommended by experts. Work posture was evaluated using RULA. The data-collecting approach was implemented using participatory ergonomic and design science principles. The FMI results show average MSDs score of 3.69, indicating high to extremely high risk. Surface plots show that combined work tool and work process was the most sensitive factors to MSDs risk compared to other two combinations. A two-sample t-test validated the FMI. The findings should help safety experts and managers develop effective OHS management plans and programmes for the sustainability of Indian mining industry.

Abstract Urinary bladder dysfunction can be caused by environmental, genetic, and developmental insults. Depending upon insult severity, the bladder may lose its ability to maintain volumetric capacity and intravesical pressure resulting in renal deterioration. Bladder augmentation enterocystoplasty (BAE) is utilized to increase bladder capacity to preserve renal function using autologous bowel tissue as a “patch.” To avoid the clinical complications associated with this procedure, we have engineered composite grafts comprised of autologous bone marrow mesenchymal stem cells (MSCs) co-seeded with CD34+ hematopoietic stem/progenitor cells (HSPCs) onto a pliable synthetic scaffold [poly(1,8-octamethylene-citrate-co-octanol)(POCO)] or a biological scaffold (SIS; small intestinal submucosa) to regenerate bladder tissue in our baboon bladder augmentation model. We set out to determine the global protein expression profile of bladder tissue that has undergone regeneration with the aforementioned stem cell seeded scaffolds along with baboons that underwent BAE. Data demonstrate that POCO and SIS grafted animals share high protein homogeneity between native and regenerated tissues while BAE animals displayed heterogeneous protein expression between the tissues following long-term engraftment. We posit that stem cell-seeded scaffolds can recapitulate tissue that is nearly indistinguishable from native tissue at the protein level and may be used in lieu of procedures such as BAE.

Abstract In the era of social media, the use of emojis and code-mixed language has become essential in online communication. However, selecting the appropriate emoji that matches a particular sentiment or emotion in the code-mixed text can be difficult. This paper presents a novel task of predicting multiple emojis in English-Hindi code-mixed sentences and proposes a new dataset called SENTIMOJI, which extends the SemEval 2020 Task 9 SentiMix dataset. Our approach is based on exploiting the relationship between emotion, sentiment, and emojis to build an end-to-end framework. We replace the self-attention sublayers in the transformer encoder with simple linear transformations and use the RMS-layer norm instead of the normal layer norm. Moreover, we employ Gated Linear Unit and Fully Connected layers to predict emojis and identify the emotion and sentiment of a tweet. Our experimental results on the SENTIMOJI dataset demonstrate that the proposed multi-task framework outperforms the single-task framework. We also show that emojis are strongly linked to sentiment and emotion and that identifying sentiment and emotion can aid in accurately predicting the most suitable emoji. Our work contributes to the field of natural language processing and can help in the development of more effective tools for sentiment analysis and emotion recognition in code-mixed languages. The codes and data will be available at https://www.iitp.ac.in/~ai-nlp-ml/resources.html#SENTIMOJI to facilitate research.

Abstract 5q-spinal muscular atrophy (SMA) is a neuromuscular disorder (NMD) that has become one of the first 5% treatable rare diseases. The efficacy of new SMA therapies is creating a dynamic SMA patient landscape, where disease progression and scoliosis development play a central role, however, remain difficult to anticipate. New approaches to anticipate disease progression and associated sequelae will be needed to continuously provide these patients the best standard of care. Here we developed an interpretable machine learning (ML) model that can function as an assistive tool in the anticipation of SMA-associated scoliosis based on disease progression markers. We collected longitudinal data from 86 genetically confirmed SMA patients. We selected six features routinely assessed over time to train a random forest classifier. The model achieved a mean accuracy of 0.77 (SD 0.2) and an average ROC AUC of 0.85 (SD 0.17). For class 1 ‘scoliosis’ the average precision was 0.84 (SD 0.11), recall 0.89 (SD 0.22), F1-score of 0.85 (SD 0.17), respectively. Our trained model could predict scoliosis using selected disease progression markers and was consistent with the radiological measurements. During post validation, the model could predict scoliosis in patients who were unseen during training. We also demonstrate that rare disease data sets can be wrangled to build predictive ML models. Interpretable ML models can function as assistive tools in a changing disease landscape and have the potential to democratize expertise that is otherwise clustered at specialized centers.

Abstract Quinoa (Chenopodium quinoa Willd.), an Andean crop, is a facultative halophyte food crop recognized globally for its high nutritional value and plasticity to adapt to harsh conditions. We conducted a genome-wide association study on a diverse set of quinoa germplasm accessions. These accessions were evaluated for the following agronomic and biochemical traits: days to 50% flowering (DTF), plant height (PH), panicle length (PL), stem diameter (SD), seed yield (SY), grain diameter (GD), and thousand-grain weight (TGW). These accessions underwent genotyping-by-sequencing using the DNBSeq-G400R platform. Among all evaluated traits, TGW represented maximum broad-sense heritability. Our study revealed average SNP density of ≈ 3.11 SNPs/10 kb for the whole genome, with the lowest and highest on chromosomes Cq1B and Cq9A, respectively. Principal component analysis clustered the quinoa population in three main clusters, one clearly representing lowland Chilean accessions, whereas the other two groups corresponded to germplasm from the highlands of Peru and Bolivia. In our germplasm set, we estimated linkage disequilibrium decay to be ≈ 118.5 kb. Marker-trait analyses revealed major and consistent effect associations for DTF on chromosomes 3A, 4B, 5B, 6A, 7A, 7B and 8B, with phenotypic variance explained (PVE) as high as 19.15%. Nine associations across eight chromosomes were also found for saponin content with 20% PVE by qSPN5A.1. More QTLs were identified for PL and TGW on multiple chromosomal locations. We identified putative candidate genes in the genomic regions associated with DTF and saponin content. The consistent and major-effect genomic associations can be used in fast-tracking quinoa breeding for wider adaptation across marginal environments.

Abstract The survival of leukemic cells is significantly influenced by the bone marrow microenvironment, where stromal cells play a crucial role. While there has been substantial progress in understanding the mechanisms and pathways involved in this crosstalk, limited data exist regarding the impact of leukemic cells on bone marrow stromal cells and their potential role in drug resistance. In this study, we identify that leukemic cells prime bone marrow stromal cells towards osteoblast lineage and promote drug resistance. This biased differentiation of stroma is accompanied by dysregulation of the canonical Wnt signaling pathway. Inhibition of Wnt signaling in stroma reversed the drug resistance in leukemic cells, which was further validated in leukemic mice models. This study evaluates the critical role of leukemic cells in establishing a drug-resistant niche by influencing the bone marrow stromal cells. Additionally, it highlights the potential of targeting Wnt signaling in the stroma by repurposing an anthelmintic drug to overcome the microenvironment-mediated drug resistance.

Abstract Scaling up the synthesis of fluorescent silica nanoparticles to meet the current demand in diverse applications involves technological limitations. The present study relates to the hydrothermal synthesis of water-soluble, crystalline, blue-emitting amine-functionalized silica nanoparticles from coal fly ash sustainably and economically. This study used tertiary amine (trimethylamine) to prepare amine-functionalized fluorescent silica nanoparticles, enhancing fluorescence quantum yield and nitrogen content for nanofertilizer application. The TEM and FESEM studies show that the silica nanoparticles have a spherical morphology with an average diameter of 4.0 nm. The x-ray photoelectron and Fourier transform infrared spectroscopy studies reveal the presence of the amine group at the surface of silica nanoparticles. The silica nanoparticles exhibit blue fluorescence with an emission maximum of 454 nm at 370 nm excitation and show excitation-dependent emission properties in the aqueous medium. With the perfect spectral overlap between silica nanoparticle emission (donor) and chlorophyll absorption (acceptor), fluorescent silica nanoparticles enhance plant photosynthesis rate by resonance energy transfer. This process accelerates the photosynthesis rate to improve the individual plant’s quality and growth. These findings suggested that the fly ash-derived functionalized silica nanoparticles could be employed as nanofertilizers and novel delivery agents.

Efficacious stem cell-based therapies for traumatic brain injury (TBI) depend on successful delivery, migration, and engraftment of stem cells to induce neuroprotection. L-myc expressing human neural stem cells (LMNSC008) demonstrate an inherent tropism to injury sites after intranasal (IN) administration. We hypothesize that IN delivered LMNSC008 cells migrate to primary and secondary injury sites and modulate biomarkers associated with neuroprotection and tissue regeneration. To test this hypothesis, immunocompetent adult female rats received either controlled cortical impact injury or sham surgery. LMNSC008 cells or a vehicle were administered IN on postoperative days 7, 9, 11, 13, 15, and 17. The distribution and migration of eGFP-expressing LMNSC008 cells were quantified over 1 mm-thick optically cleared (CLARITY) coronal brain sections from TBI and SHAM controls. NSC migration was observed along white matter tracts projecting toward the hippocampus and regions of TBI. ELISA and Nanostring assays revealed a shift in tissue gene expression in LMNSC008 treated rats relative to controls. LMNSC008 treatment reduced expression of genes and pathways involved in inflammatory response, microglial function, and various cytokines and receptors. Our proof-of-concept studies, although preliminary, support the rationale of using intranasal delivery of LMNSC008 cells for functional studies in preclinical models of TBI and provide support for potential translatability in TBI patients.

Abstract Even though many varieties have been recommended across agro-climate zones of Himachal Pradesh, yet the information on stability is lacking in this State. Hence, the present investigation was carried out to identify high yielding stable genotypes among various pre-adapted landraces. The material consists of 20 chilli landraces including check i.e. DKC-8. The experiment was laid out in a RCBD. The data were recorded and analyzed to work out mean performances and the inferences were drawn for parameters of variability, correlation coefficients, path coefficients and stability analysis. As per mean performances, CS7 and CS9 were earliest in flowering, CS13 is earliest in days to ripe maturity, CS10 had highest plant height and CS9 had highest average fruit weight and ripe fruit yield plant−1. High PCV and GCV were recorded for ripe fruit yield plant−1. Heritability and genetic advance were recorded maximum for plant height in summer seasons and were recorded maximum for number of ripe fruits plant−1 in winter season. Correlation coefficients showed that number of ripe fruits plant−1 and average ripe fruit weight were positively and significantly correlated with ripe fruit yield plant−1. Path coefficient analysis in summer and winter seasons showed that average ripe fruit weight had the highest positive direct effect on ripe fruit yield plant−1. The pooled data over environments were analyzed to estimate the interaction effects between genotypes × environment. The mean sum of squares due to genotypes, environments and genotypes × environment interaction were significant for all the characteristics. CS1, CS3, CS6, CS10, CS13, CS15 were adapted to all environments, CS7 and CS9 were specifically adapted to favourable environment and CS2 was specifically adapted to unfavorable environment for 50% flowering, landraces CS1, CS2 and CS3were well adapted to all environments for ripe maturity whereas landraces CS6, CS10 and CS19 were well adapted to all environment for number of ripe fruit and ripe fruit yield.

Abstract Efficacious stem cell-based therapies for traumatic brain injury (TBI) depend on successful delivery, migration, and engraftment of stem cells to induce neuroprotection. L-myc expressing human neural stem cells (LMNSC008) demonstrate an inherent tropism to injury sites after intranasal (IN) administration. We hypothesize that IN delivered LMNSC008 cells migrate to primary and secondary injury sites and modulate biomarkers associated with neuroprotection and tissue regeneration. To test this hypothesis, immunocompetent adult female rats received either controlled cortical impact injury or sham surgery. LMNSC008 cells or a vehicle were administered IN on postoperative days 7, 9, 11, 13, 15, and 17. The distribution and migration of eGFP-expressing LMNSC008 cells were quantified over 1 mm-thick optically cleared (CLARITY) coronal brain sections from TBI and SHAM controls. NSC migration was observed along white matter tracts projecting toward the hippocampus and regions of TBI. ELISA and Nanostring assays revealed a shift in tissue gene expression in LMNSC008 treated rats relative to controls. LMNSC008 treatment reduced expression of genes and pathways involved in inflammatory response, microglial function, and various cytokines and receptors. Our proof-of-concept studies, although preliminary, support the rationale of using intranasal delivery of LMNSC008 cells for functional studies in preclinical models of TBI and provide support for potential translatability in TBI patients.

Abstract Selective vascular access to the brain is desirable in metabolic tracer, pharmacological and other studies aimed to characterize neural properties in isolation from somatic influences from chest, abdomen or limbs. However, current methods for artificial control of cerebral circulation can abolish pulsatility-dependent vascular signaling or neural network phenomena such as the electrocorticogram even while preserving individual neuronal activity. Thus, we set out to mechanically render cerebral hemodynamics fully regulable to replicate or modify native pig brain perfusion. To this end, blood flow to the head was surgically separated from the systemic circulation and full extracorporeal pulsatile circulatory control (EPCC) was delivered via a modified aorta or brachiocephalic artery. This control relied on a computerized algorithm that maintained, for several hours, blood pressure, flow and pulsatility at near-native values individually measured before EPCC. Continuous electrocorticography and brain depth electrode recordings were used to evaluate brain activity relative to the standard offered by awake human electrocorticography. Under EPCC, this activity remained unaltered or minimally perturbed compared to the native circulation state, as did cerebral oxygenation, pressure, temperature and microscopic structure. Thus, our approach enables the study of neural activity and its circulatory manipulation in independence of most of the rest of the organism.

Abstract Across the three domains of life, circadian clock is known to regulate vital physiological processes, like, growth, development, defence etc. by anticipating environmental cues. In this work, we report an integrated network theoretic methodology comprising of random walk with restart and graphlet degree vectors to characterize genome wide core circadian clock and clock associated raw candidate proteins in a plant for which protein interaction information is available. As a case study, we have implemented this framework in Ocimum tenuiflorum (Tulsi); one of the most valuable medicinal plants that has been utilized since ancient times in the management of a large number of diseases. For that, 24 core clock (CC) proteins were mined in 56 template plant genomes to build their hidden Markov models (HMMs). These HMMs were then used to identify 24 core clock proteins in O. tenuiflorum. The local topology of the interologous Tulsi protein interaction network was explored to predict the CC associated raw candidate proteins. Statistical and biological significance of the raw candidates was determined using permutation and enrichment tests. A total of 66 putative CC associated proteins were identified and their functional annotation was performed.

Abstract Lung cancer is the leading cause of cancer-related mortality in the United States. Investigating epidemiological and clinical parameters can contribute to an improved understanding of disease development and management. In this cross-sectional, case–control study, we used the All of Us database to compare healthcare access, family history, smoking-related behaviors, and psychiatric comorbidities in light smoking controls, matched smoking controls, and primary and secondary lung cancer patients. We found a decreased odds of primary lung cancer patients versus matched smoking controls reporting inability to afford follow-up or specialist care. Additionally, we found a significantly increased odds of secondary lung cancer patients having comorbid anxiety and insomnia when compared to matched smoking controls. Our study provides a profile of the psychiatric disease burden in lung cancer patients and reports key epidemiological factors in patients with primary and secondary lung cancer. By using two controls, we were able to separate smoking behavior from lung cancer and identify factors that were mediated by heavy smoking alone or by both smoking and lung cancer.

Abstract Heat stress is one of the major challenges in wheat cultivation because it coincides with the flowering period and limits the crop productivity. This study was conducted for evaluation of 50 wheat genotypes to identify the heat stress tolerant genotypes for improvement of stress tolerance. All genotypes were cultivated for two consecutive years (2018–2020) under normal and late sown conditions. The results of the study revealed that the combined analysis of variance indicated significant variations among genotypes for all the studied stress indices. The reduction in mean grain yield of all genotypes under stress condition as compared to non-stress condition, indicating that the heat stress significantly affect the grain yield. The correlation analysis showed that the negative correlation of tolerance index and stress susceptibility percentage index with the grain yield of genotypes under heat stress condition (Ys) and a highly positive correlation of stress tolerance index, mean productivity, geometric mean, harmonic mean and mean relative performance with grain yield (Yp and Ys) under both conditions, helped accurately to identify the desirable genotypes. From the results obtained from principal component, biplot and cluster analysis, it was reported that HD 2967, WH 1249, HI 1617, WH 1202, WH 1021 and WH 1142 are suitable and good yielding genotypes under both conditions. Thus, above genotypes can be used for cultivation at high temperature or as genetic resources for introducing genetic variations in wheat genotypes to improve stress tolerance.

Abstract Fuel influx and metabolism replenish carbon lost during normal neural activity. Ketogenic diets studied in epilepsy, dementia and other disorders do not sustain such replenishment because their ketone body derivatives contain four carbon atoms and are thus devoid of this anaplerotic or net carbon donor capacity. Yet, in these diseases carbon depletion is often inferred from cerebral fluorodeoxyglucose-positron emission tomography. Further, ketogenic diets may prove incompletely therapeutic. These deficiencies provide the motivation for complementation with anaplerotic fuel. However, there are few anaplerotic precursors consumable in clinically sufficient quantities besides those that supply glucose. Five-carbon ketones, stemming from metabolism of the food supplement triheptanoin, are anaplerotic. Triheptanoin can favorably affect Glucose transporter type 1 deficiency (G1D), a carbon-deficiency encephalopathy. However, the triheptanoin constituent heptanoate can compete with ketogenic diet-derived octanoate for metabolism in animals. It can also fuel neoglucogenesis, thus preempting ketosis. These uncertainties can be further accentuated by individual variability in ketogenesis. Therefore, human investigation is essential. Consequently, we examined the compatibility of triheptanoin at maximum tolerable dose with the ketogenic diet in 10 G1D individuals using clinical and electroencephalographic analyses, glycemia, and four- and five-carbon ketosis. 4 of 8 of subjects with pre-triheptanoin beta-hydroxybutyrate levels greater than 2 mM demonstrated a significant reduction in ketosis after triheptanoin. Changes in this and the other measures allowed us to deem the two treatments compatible in the same number of individuals, or 50% of persons in significant beta-hydroxybutyrate ketosis. These results inform the development of individualized anaplerotic modifications to the ketogenic diet. ClinicalTrials.gov registration NCT03301532, first registration: 04/10/2017.

Abstract Differences in social attention are well-documented in autistic individuals, representing one of the earliest signs of autism. Spontaneous blink rate has been used to index attentional engagement, with lower blink rates reflecting increased engagement. We evaluated novel methods using computer vision analysis (CVA) for automatically quantifying patterns of attentional engagement in young autistic children, based on facial orientation and blink rate, which were captured via mobile devices. Participants were 474 children (17–36 months old), 43 of whom were diagnosed with autism. Movies containing social or nonsocial content were presented via an iPad app, and simultaneously, the device’s camera recorded the children’s behavior while they watched the movies. CVA was used to extract the duration of time the child oriented towards the screen and their blink rate as indices of attentional engagement. Overall, autistic children spent less time facing the screen and had a higher mean blink rate compared to neurotypical children. Neurotypical children faced the screen more often and blinked at a lower rate during the social movies compared to the nonsocial movies. In contrast, autistic children faced the screen less often during social movies than during nonsocial movies and showed no differential blink rate to social versus nonsocial movies.

Abstract The international postal network is one of the most widely used methods for correspondence throughout the world. Most postal traffic across the globe consists of legitimate interpersonal, business-consumer, and business-business communications. However, the global postal system is also utilized for criminal activity. In particular, it is often utilized to ship and distribute contraband, including illegal psychoactive drugs such as fentanyl and heroin, to consumers. Existing technological solutions are capable of identifying synthetic opioids and other illegal drugs within packages, but are accompanied by several disadvantages that make them unsuitable for large-scale authentication of international mail traffic. This paper presents a novel method for non-invasive authentication of mail packages that overcomes these challenges. The approach uses nuclear quadrupole resonance (NQR) spectroscopy to detect and quantify the presence of known active pharmaceutical ingredients (APIs) within the package. It has been experimentally demonstrated using a bench top prototype. Test results from a variety of package types demonstrate the effectiveness of the proposed authentication approach.

Abstract We report the first experimental observations of a single-mode Kelvin-Helmholtz instability in a flowing dusty plasma in which the flow is compressible in nature. The experiments are performed in an inverted $$\Pi$$ Π -shaped dusty plasma experimental device in a DC glow discharge Argon plasma environment. A gas pulse valve is installed in the experimental chamber to initiate directional motion to a particular dust layer. The shear generated at the interface of the moving and stationary layers leads to the excitation of the Kelvin-Helmholtz instability giving rise to a vortex structure at the interface. The growth rate of the instability is seen to decrease with an increase in the gas flow velocity in the valve and the concomitant increase in the compressibility of the dust flow. The shear velocity is further increased by making the stationary layer to flow in an opposite direction. The magnitude of the vorticity is seen to become stronger while the vortex becomes smaller with such an increase of the shear velocity. A molecular dynamics simulation provides good theoretical support to the experimental findings.

Abstract A ternary nanohybrid CuO/Mn3O4/CeO2 was developed in the present work using a co-precipitation-assisted hydrothermal method. The designed photocatalyst's structural, morphology, elemental composition, electronic states of elements, and optical properties were studied using corresponding analytical techniques. Results from PXRD, TEM/HRTEM, XPS, EDAX, and PL showed that the desired nanostructure had formed. Using Tauc's energy band gap plot, it was determined that the nanostructures band gap was ~ 2.44 eV, which showed the band margins of the various moieties, CeO2, Mn3O4, and CuO, had modified. Thus, improved redox conditions led to a substantial decrease in the recombination rate of electron–hole pairs, which was further explained by a PL study in that charge separation plays a key role. Under exposure to visible light irradiation for 60 min, it was revealed that the photocatalyst achieved 98.98% of photodegradation efficiency for malachite green (MG) dye. The process of photodegradation proceeded according to a pseudo-first-order reaction kinetic model with an excellent rate of reaction of 0.07295 min−1 with R2 = 0.99144. The impacts of different reaction variables, inorganic salts, and water matrices were investigated. This research seeks to create a ternary nanohybrid photocatalyst with high photostability, visible spectrum activity, and reusability up to four cycles.

There is a lack of well validated prognostic biomarkers in osteosarcoma, a rare, recalcitrant disease for which treatment standards have not changed in over 20 years. We performed microRNA sequencing in 74 frozen osteosarcoma biopsy samples, constituting the largest single center translationally analyzed osteosarcoma cohort to date, and we separately analyzed a multi-omic dataset from a large NCI supported national cooperative group cohort. We validated the prognostic value of candidate microRNA signatures and contextualized them in relevant transcriptomic and epigenomic networks. Our results reveal the existence of molecularly defined phenotypes associated with outcome independent of clinicopathologic features. Through machine learning based integrative pharmacogenomic analysis, the microRNA biomarkers identify novel therapeutics for stratified application in osteosarcoma. The previously unrecognized osteosarcoma subtypes with distinct clinical courses and response to therapy could be translatable for discerning patients appropriate for more intensified, less intensified, or alternate therapeutic regimens.

In this study, we used shotgun metagenomic sequencing to characterise the microbial metabolic potential for lignocellulose transformation in the gut of two colonies of Argentine higher termite species with different feeding habits, Cortaritermes fulviceps and Nasutitermes aquilinus. Our goal was to assess the microbial community compositions and metabolic capacity, and to identify genes involved in lignocellulose degradation. Individuals from both termite species contained the same five dominant bacterial phyla (Spirochaetes, Firmicutes, Proteobacteria, Fibrobacteres and Bacteroidetes) although with different relative abundances. However, detected functional capacity varied, with C. fulviceps (a grass-wood-feeder) gut microbiome samples containing more genes related to amino acid metabolism, whereas N. aquilinus (a wood-feeder) gut microbiome samples were enriched in genes involved in carbohydrate metabolism and cellulose degradation. The C. fulviceps gut microbiome was enriched specifically in genes coding for debranching- and oligosaccharide-degrading enzymes. These findings suggest an association between the primary food source and the predicted categories of the enzymes present in the gut microbiomes of each species. To further investigate the termite microbiomes as sources of biotechnologically relevant glycosyl hydrolases, a putative GH10 endo-β-1,4-xylanase, Xyl10E, was cloned and expressed in Escherichia coli. Functional analysis of the recombinant metagenome-derived enzyme showed high specificity towards beechwood xylan (288.1 IU/mg), with the optimum activity at 50 °C and a pH-activity range from 5 to 10. These characteristics suggest that Xy110E may be a promising candidate for further development in lignocellulose deconstruction applications.