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Abstract Brainstem cerebral cavernous malformations (CCM) are clinically more aggressive compared to superficial CCMs. Due to their location, resection can be challenging, making stereotactic radiosurgery (SRS) an attractive alternative for symptomatic patient. Brainstem CCM patients (n = 170) were treated with Gamma Knife SRS at 11 radiosurgical centers. Hemorrhagic risk reduction, risk factors of post-SRS hemorrhage, and clinical outcomes were retrospectively analyzed. Most patients had a single (165/170 patients) brainstem CCMs treated; the majority of CCMs (165/181) presented with bleeding. Single-session SRS decreased the risk of repeat hemorrhage in patients with hemorrhagic brainstem CCM (HR: 0.17, p 13 Gy (HR = 2.57, p = 0.044). Adverse radiation effect (ARE) occurred in 9 patients (5.3%) and was symptomatic in four (2.4%). At a median follow-up of 3.4 years (Inter-quartile range: 5.4), 13 patients (8.0%) had a worsened clinical status, with the treated CCM being the cause in 5.6% (10) of the patients. Single-session SRS decreased the risk of repeat hemorrhage in patients with hemorrhagic brainstem CCM and conveyed this benefit with a low risk of advrse radiation effects (ARE) and worsening clinical status.

Abstract Sugarcane smut is the most damaging disease that is present almost across the globe, causing mild to severe yield losses depending upon the cultivar types, pathogen races and climatic conditions. Cultivation of smut-resistant cultivars is the most feasible and economical option to mitigate its damages. Previous investigations revealed that there is a scarcity of information on early detection and effective strategies to suppress etiological agents of smut disease due to the characteristics overlapping within species complexes. In this study, 104 sugarcane cultivars were screened by artificial inoculation with homogenate of all possible pathogen races of Sporisorium scitamineum during two consecutive growing seasons. The logistic smut growth pattern and the disease intrinsic rate were recorded by disease growth curve. Variable levels of disease incidence i.e., ranging from 0 to 54.10% were observed among these sugarcane cultivars. Besides, pathogen DNA in plant shoots of all the cultivars was successfully amplified by PCR method using smut-specific primers except 26 cultivars which showed an immune reaction in the field trial. Furthermore, the plant germination and tillering of susceptible sugarcane cultivars were greatly influenced by pathogen inoculation. In susceptible cultivars, S. scitamineum caused a significant reduction in setts germination, coupled with profuse tillering, resulting in fewer millable canes. Correlation analysis demonstrated that there was a positive relationship between reduction in setts germination and increase in the number of tillers. The present study would be helpful for the evaluation of smut resistance in a wide range of sugarcane germplasm, especially from the aspects of setts germination and tillers formation, and it also screened out several excellent germplasm for potential application in sugarcane breeding.

Abstract Unpredictable fatal outcome of COVID-19 is attributed to dysregulated inflammation. Impaired early adaptive immune response leads to late-stage inflammatory outcome. The purpose of this study was to develop biomarkers for early detection of host immune impairment at first diagnosis from leftover RNA samples, which may in turn identify high risk patients. Leftover RNA samples of COVID-19 patients at first diagnosis were stored. Following prospective follow-up, the samples were shorted and categorized into outcome groups. Impaired adaptive T cell response (severity score) and Impaired IL-10 response (undetectable IL-10 in the presence of high expression of a representative interferon response gene) were determined by RT-PCR based assay. We demonstrate that a T cell response based ‘severity score’ comprising rational combination of Ct values of a target genes’ signature can predict high risk noncomorbid potentially critical COVID-19 patients with a sensitivity of 91% (95% CI 58.7–99.8) and specificity of 92.6% (95% CI 75.7–99) (AUC:0.88). Although inclusion of comorbid patients reduced sensitivity to 77% (95% CI 54.6–92.2), the specificity was still 94% (95% CI 79.8–99.3) (AUC:0.82). The same for ‘impaired IL-10 response’ were little lower to predict high risk noncomorbid patients 64.2% (95% CI 35.1–87.2) and 82% (95% CI 65.5–93.2) respectively. Inclusion of comorbid patients drastically reduce sensitivity and specificity51.6% (95% CI 33.1–69.8) and 80.5% (95% CI 64.0–91.8) respectively. As best of our knowledge this is the first demonstration of a metric-based approach showing the ‘severity score’ as an indicator of early adoptive immune response, could be used as predictor of severe COVID-19 outcome at the time of first diagnosis using the same leftover swab RNA. The work flow could reduce expenditure and reporting time of the prognostic test for an earliest clinical decision ensuring possibility of early rational management.

Abstract Suspended sediment concentration prediction is critical for the design of reservoirs, dams, rivers ecosystems, various operations of aquatic resource structure, environmental safety, and water management. In this study, two different machine models, namely the cascade correlation neural network (CCNN) and feedforward neural network (FFNN) were applied to predict daily-suspended sediment concentration (SSC) at Simga and Jondhara stations in Sheonath basin, India. Daily-suspended sediment concentration and discharge data from 2010 to 2015 were collected and used to develop the model to predict suspended sediment concentration. The developed models were evaluated using statistical indices like Nash and Sutcliffe efficiency coefficient (NES), root mean square error (RMSE), Willmott’s index of agreement (WI), and Legates–McCabe’s index (LM), supplemented by a scatter plot, density plots, histograms and Taylor diagram for graphical representation. The developed model was evaluated and compared with CCNN and FFNN. Nine input combinations were explored using different lag-times for discharge (Qt-n) and suspended sediment concentration (St-n) as input variables, with the current suspended sediment concentration as the desired output, to develop CCNN and FFNN models. The CCNN4 model with 4 lagged inputs (St-1, St-2, St-3, St-4) outperformed the other developed models with the lowest RMSE = 95.02 mg/l and the highest NES = 0.0.662, WI = 0.890 and LM = 0.668 for the Jondhara Station while the same CCNN4 model secure as the best with the lowest RMSE = 53.71 mg/l and the highest NES = 0.785, WI = 0.936 and LM = 0.788 for the Simga Station. The result shows the CCNN model was better than the FFNN model for predicting daily-suspended sediment at both stations in the Sheonath basin, India. Overall, CCNN showed better forecasting potential for suspended sediment concentration compared to FFNN at both stations, demonstrating their applicability for hydrological forecasting with complex relationships.

Abstract Human microbiota mainly resides on the skin and in the gut. Human gut microbiota can produce a variety of short chain fatty acids (SCFAs) that affect many physiological functions and most importantly modulate brain functions through the bidirectional gut-brain axis. Similarly, skin microorganisms also have identical metabolites of SCFAs reported to be involved in maintaining skin homeostasis. However, it remains unclear whether these SCFAs produced by skin bacteria can affect brain cognitive functions. In this study, we hypothesize that the brain’s functional activities are associated with the skin bacterial population and examine the influence of local skin-bacterial growth on event-related potentials (ERPs) during an oddball task using EEG. Additionally, five machine learning (ML) methods were employed to discern the relationship between skin microbiota and cognitive functions. Twenty healthy subjects underwent three rounds of tests under different conditions—alcohol, glycerol, and water. Statistical tests confirmed a significant increase in bacterial population under water and glycerol conditions when compared to the alcohol condition. The metabolites of bacteria can turn phenol red from red–orange to yellow, confirming an increase in acidity. P3 amplitudes were significantly enhanced in response to only oddball stimulus at four channels (Fz, FCz, and Cz) and were observed after the removal of bacteria when compared with that under the water and glycerol manipulations. By using machine learning methods, we demonstrated that EEG features could be separated with a good accuracy (> 88%) after experimental manipulations. Our results suggest a relationship between skin microbiota and brain functions. We hope our findings motivate further study into the underlying mechanism. Ultimately, an understanding of the relationship between skin microbiota and brain functions can contribute to the treatment and intervention of diseases that link with this pathway.

Abstract In the present work, the Nickel oxide (rGO–NiO), Silver (rGO–Ag), Copper oxide (rGO–CuO) doped Graphene Oxide are reported for catalytic reactions. A comparative study for catalytic activities of these materials are performed with nitroaromatic compound 4-nitroaniline and the results are statistically studied by using univariate analysis of variance and Post Hoc Test through Statistical Package for Social Sciences and it is observed that CuO doped Graphene material is showing better catalytic activity in minimum time. So, further research has been focused on the catalytic acitivity of rGO–CuO only and it is found that it is efficient in reducing other nitro compounds also such as Picric acid and Nitrobenzene. Dye degradation of Methylene blue is also performed using CuO decorated Graphene material and significant changes were observed using UV spectroscopy. The characterization of rGO–CuO is done with Fourier-transform Infrared Spectroscopy, Powder X-ray Diffraction, Thermogravimetric Analysis, Scanning Electron Microscope and Transmission Electron Microscopy.

Abstract In the cutting-edge era of developing precision therapeutics, nanoparticles have emerged as a potent drug delivery system. Altering the size of poorly water-soluble drugs to nanoscale could confer change in their physical properties, including enhanced water solubility and bioavailability. Evodiamine (EVO), a natural indolequinone alkaloid extract from Evodia rutaecarpa, has shown several important pharmacological applications, anti-cancer being one of them. Protein-based nano-drug delivery systems have gained the interest of researchers due to their better biocompatibility, biodegradability, non-immunogenicity and non-toxicity. In the present study, EVO encapsulated BSA nanoparticles (ENPs) were synthesized and characterized, which were nanoscale-sized (~ 150 nm), monodispersed, spherical shaped, and showed high entrapment efficiency (~ 86%) and controlled drug release. The in-vitro anti-cancer activity of ENPs on human breast cancer cells was dose- and time-dependent. The apoptotic molecular mechanism investigated using FACS, qRT-PCR, and western blotting analysis, revealed increased expression of p53 and Bax and decreased expression of Bcl-2. Biological studies demonstrated comparatively more efficient and targeted delivery of ENPs than pure EVO. The comprehensive physiochemical characterization and in-vitro validation collectively pinpoint ENPs as a promising avenue for harnessing the therapeutic potential of the natural anti-cancer compound EVO. The findings indicate improved cytotoxicity, positioning ENPs as a propitious strategy for advancing breast cancer treatment.

Abstract Graphene is a 2D material with promising commercial applications due to its physicochemical properties. Producing high-quality graphene economically and at large scales is currently of great interest and demand. Here, the potential of producing high-quality graphene at a large scale via water-phase exfoliation methods is investigated. By altering exfoliation parameters, the production yield of graphene and flake size are evaluated. Pretreatment of the precursor graphite powder using acidic solutions of H2SO4 at different concentrations is found to increase further the yield and structural quality of the exfoliated graphene flakes. These findings are confirmed through various spectroscopy and surface characterization techniques. Controlling flake size, thickness, and yield are demonstrated via optimization of the sonication process, centrifuge time, and H2SO4 pretreatment.

Abstract We present an innovative approach to achieve all-optical modulation within an ITO-based vertically coupled ring resonator. This method leverages the material's enhanced nonlinear response in the near-infrared wavelengths, particularly within the epsilon-near-zero (ENZ) state. To enhance the interaction between light and the material while minimizing scattering losses, our approach employs an ITO-based vertically connected ring resonator. The vertical arrangement eliminates the need for etching fine gaps to separate the ring and bus waveguide. The novel waveguide design addresses the necessity of high sensitivity, non-linear effects and compact size opening the possibilities for all-optical signal processing. This unique resonator structure effectively facilitates the coupling of a high-intensity pump wavelength into the ITO-based micro-ring resonator. Consequently, this optical pumping induces electron heating within the ITO material, leading to a significant increase in its nonlinear optical properties. This, in turn, results in a noteworthy alteration of ITO's refractive index, specifically in the unity order, thereby modifying the complex effective index of the optical beam propagating at 1550 nm. Our experimental findings demonstrate an impressive extinction ratio of 18 dB for a 30 µm long device, which highlights the efficiency of our approach in achieving all-optical modulation through the optical pumping of an ITO-based vertically coupled ring resonator. The proposed all-optical modulator has outperformed as compared to conventional waveguide-based modulators in terms of extinction ratio and footprint. This novel technique holds immense potential for advancing high-speed data communication systems in the future. As the demand for advanced processing capabilities, such as artificial intelligence, continues to grow, all-optical modulation emerges as a groundbreaking technology poised to revolutionize the next generation of computing and communication systems.

Abstract During the early pre and postnatal life, host and environmental factors can impart a major influence on immune development, thus shaping lifelong disease resistance. Two major factors known to influence immune function and mortality in animals and people are early life stress and biological sex. How these two factors interact to shape long-term immune development and later life disease risk is poorly understood. Here we investigated how early weaning, a common early life stressor in pigs, and biological sex impacts long-term systemic inflammatory responses and hypothalamic–pituitary–adrenal axis (HPA axis) activation later in life. Ten-week-old female (F), intact-male (IM) and castrated-male (CM) pigs that were randomly assigned to early weaning (EW) and later weaning (LW) (at 15 or 28 days of age, respectively) were intramuscularly injected with either saline vehicle or lipopolysaccharide (LPS) to induce a systemic inflammatory response. Complete blood counts (CBC), proinflammatory cytokines, cortisol, testosterone, estradiol, and rectal temp were measured at 0 h, 2 h, and 4 h post-LPS challenge. At 4 h post-LPS, peritoneal fluid (PF) and white blood cells (WBC) were collected for differential analysis. LPS challenge significantly increased rectal temp and plasma cortisol level in all treatment groups. Together, the CBC results and immune cell counts in peritoneal cavity indicated that EW-F exhibited greater systemic immune response characterized by increased neutrophils to lymphocytes ratio (NLR) and enhanced neutrophil trafficking to the peritoneal cavity. Early weaning had an opposite effect on IM and CM pigs, which exhibited a suppressed LPS-induced neutrophil migration. Early weaning induced significantly greater cortisol responses only in IM pigs indicating a heightened HPA axis responses in EW-IM. how early weaning and biological sex affect immune and stress responses in pigs. Together, these results demonstrate that early weaning and biological sex and castration shape later life immune responses in pigs and provides insight into potential mechanisms driving sex differences in later life inflammatory disease risk and mortality.

Abstract A major environmental problem on a global scale is the contamination of water by dyes, particularly from industrial effluents. Consequently, wastewater treatment from various industrial wastes is crucial to restoring environmental quality. Dye is an important class of organic pollutants that are considered harmful to both people and aquatic habitats. The textile industry has become more interested in agricultural-based adsorbents, particularly in adsorption. The biosorption of Methylene blue (MB) dye from aqueous solutions by the wheat straw (T. aestivum) biomass was evaluated in this study. The biosorption process parameters were optimized using the response surface methodology (RSM) approach with a face-centred central composite design (FCCCD). Using a 10 mg/L concentration MB dye, 1.5 mg of biomass, an initial pH of 6, and a contact time of 60 min at 25 °C, the maximum MB dye removal percentages (96%) were obtained. Artificial neural network (ANN) modelling techniques are also employed to stimulate and validate the process, and their efficacy and ability to predict the reaction (removal efficiency) were assessed. The existence of functional groups, which are important binding sites involved in the process of MB biosorption, was demonstrated using Fourier Transform Infrared Spectroscopy (FTIR) spectra. Moreover, a scan electron microscope (SEM) revealed that fresh, shiny particles had been absorbed on the surface of the T. aestivum following the biosorption procedure. The bio-removal of MB from wastewater effluents has been demonstrated to be possible using T. aestivum biomass as a biosorbent. It is also a promising biosorbent that is economical, environmentally friendly, biodegradable, and cost-effective.

Abstract PCOS is a prevalent endocrine disorder among women of reproductive age, characterized by hormonal imbalances and metabolic disturbances. This study explores the correlation between gut microbial β-glucuronidase and β-glucosidase and PCOS, focusing on their association with hormone levels and other clinical parameters. In this case-control study, fecal samples were collected from women of reproductive age, both with and without PCOS. The analysis of gut β-glucuronidase and β-glucosidase enzymes was conducted with the other clinical parameters, including body mass index, hormone levels, and hirsutism. These factors were then subjected to correlation analysis. PCOS women showed significantly higher levels of β-glucuronidase activity with a statistically significant P-value (0.05 ± 0.1 vs. 0.04 ± 0.1; P = 0.006) as well as β-glucosidase activity (0.13 ± 0.08 vs. 0.09 ± 0.05; P = 0.06) compared to the controls. This study also revealed intriguing connections between the selected enzymes and hormone levels, particularly testosterone and estradiol. Gut microbial enzymes β-glucuronidase and β-glucosidase may be used as biomarkers for early detection and monitoring of PCOS in women with metabolic challenges. It could lead to improved diagnostic tools and treatment options.

Abstract One of the greatest challenges for widespread utilization of solar energy is the low conversion efficiency, motivating the needs of developing more innovative approaches to improve the design of solar energy conversion equipment. Solar cell is the fundamental component of a photovoltaic (PV) system. Solar cell’s precise modelling and estimation of its parameters are of paramount importance for the simulation, design, and control of PV system to achieve optimal performances. It is nontrivial to estimate the unknown parameters of solar cell due to the nonlinearity and multimodality of search space. Conventional optimization methods tend to suffer from numerous drawbacks such as a tendency to be trapped in some local optima when solving this challenging problem. This paper aims to investigate the performance of eight state-of-the-art metaheuristic algorithms (MAs) to solve the solar cell parameter estimation problem on four case studies constituting of four different types of PV systems: R.T.C. France solar cell, LSM20 PV module, Solarex MSX-60 PV module, and SS2018P PV module. These four cell/modules are built using different technologies. The simulation results clearly indicate that the Coot-Bird Optimization technique obtains the minimum RMSE values of 1.0264E-05 and 1.8694E−03 for the R.T.C. France solar cell and the LSM20 PV module, respectively, while the wild horse optimizer outperforms in the case of the Solarex MSX-60 and SS2018 PV modules and gives the lowest value of RMSE as 2.6961E−03 and 4.7571E−05, respectively. Furthermore, the performances of all eight selected MAs are assessed by employing two non-parametric tests known as Friedman ranking and Wilcoxon rank-sum test. A full description is also provided, enabling the readers to understand the capability of each selected MA in improving the solar cell modelling that can enhance its energy conversion efficiency. Referring to the results obtained, some thoughts and suggestions for further improvements are provided in the conclusion section.

Abstract In studying resilience in temporal human networks, relying solely on global network measures would be inadequate; latent sub-structural network mechanisms need to be examined to determine the extent of impact and recovery of these networks during perturbations, such as urban flooding. In this study, we utilize high-resolution aggregated location-based data to construct temporal human mobility networks in Houston in the context of the 2017 Hurricane Harvey. We examine motif distribution, motif persistence, temporal stability, and motif attributes to reveal latent sub-structural mechanisms related to the resilience of human mobility networks during disaster-induced perturbations. The results show that urban flood impacts persist in human mobility networks at the sub-structure level for several weeks. The impact extent and recovery duration are heterogeneous across different network types. Also, while perturbation impacts persist at the sub-structure level, global topological network properties indicate that the network has recovered. The findings highlight the importance of examining the microstructures and their dynamic processes and attributes in understanding the resilience of temporal human mobility networks (and other temporal networks). The findings can also provide disaster managers, public officials, and transportation planners with insights to better evaluate impacts and monitor recovery in affected communities.

Abstract Medicinal plants possess range of phytochemicals accountable for their diverse biological activities. Presently, such compounds have been isolated from medicinal plants, characterized and evaluated for their pharmacological potential. In the present study, the efforts have been made to isolate the compound(s) from Grewia tiliaefolia Vahl., plant known for its ameliorative effect on brain related diseases such as anxiety, depression, cognitive disorders and Parkinson’s disease. Plant extract was subjected to isolation of compound(s) using column chromatography and isolated compound was characterized by NMR FTIR and LCMS. The isolated compound was novel with the IUPAC name of the compound is propyl 3-hydroxy-10,13-dimethyl-6,7,8,9,10,11,12,13,14,15,16,17-dodecahydro-3H-cyclopenta[a]phenanthrene-17-carboxylate, designated as A-1 and has not been reported before. A-1 was further evaluated for its antioxidant potential using in vitro antioxidant assays (2,2-diphenyl-1-picryl-hydrazyl-hydrate, DPPH assay and reducing power assay, RPA). Also, Acetylcholinesterase (AChE) inhibitory potential of A-1 and extract was analysed. Results showed that A-1 exhibited significantly higher antioxidant activity in both DPPH and RPA assay as compared to plant extract. In case of AChE inhibitory activity again, A-1 has shown significantly higher activity as compared to plant extract. In silico study was conducted to predict its action on proteins playing crucial role in neurological and neurodegenerative disorders such as gamma amino butyric acid (GABA) receptor and glutamate α amino-3-hydroxyl-5-methyl-4-isoxazolepropionic acid (Glu AMPA) receptor in epilepsy and AChE enzyme in Alzheimer’s diseases. The compound has shown interaction in following order: AChE > GABA receptor > Glu AMPA receptor. Further, molecular dynamic simulations and ADME studies of A-1 and AChE enzyme revealed that A-1 yielded good results in all parameters and hence can relieve Alzheimer’s like symptoms.

Abstract For effective soil remediation, it is vital to apply environmentally friendly and cost-effective technologies following the notion of green sustainable development. In the context of recycling waste and preserving nutrients in the soil, biochar production and utilization have become widespread. There is an urgent need to develop high-efficiency biochar-based sorbents for pollution removal from soil. This research examined the efficacy of soil remediation using biochar made from three distinct sources: wood, and agricultural residues (sunflower and rice husks). The generated biochars were characterized by SEM/SCEM, XRF, XRD, FTIR, BET Specific Surface Area, and elemental compositions. The presence of hydroxyl and phenolic functional groups and esters in wood, sunflower and rice husk biochar were noted. The total volume of pores was in the following descending order: rice husk > wood > sunflower husk. However, wood biochar had more thermally stable, heterogeneous, irregular-shaped pores than other samples. Adsorption of soil-heavy metals into biochars differed depending on the type of adsorbent, according to data derived from distribution coefficients, sorption degree, Freundlich, and Langmuir adsorption models. The input of biochars to Calcaric Fluvic Arenosol increased its adsorption ability under contamination by Cu(II), Zn(II), and Pb(II) in the following order: wood > rice husk > sunflower husk. The addition of sunflower husk, wood, and rice husk biochar to the soil led to an increase in the removal efficiency of metals in all cases (more than 77%). The increase in the percentage adsorption of Cu and Pb was 9–19%, of Zn was 11–21%. The present results indicated that all biochars functioned well as an absorbent for removing heavy metals from soils. The tailor-made surface chemistry properties and the high sorption efficiency of the biochar from sunflower and rice husks could potentially be used for soil remediation.

Abstract Molybdenum disulfide (MoS2) has been combined so far with other photodetecting semiconductors as an enhancing agent owing to its optical and electronic properties. Existing approaches demonstrated MoS2-incorporated photodetector devices using complex and costly fabrication processes. Here, we report on simplified one-step on the chemical vapor deposition (CVD) based synthesis of a unique microfiber/microflower MoS2-based heterostructure formed by capturing MoO2 intermediate material during the CVD process. This particular morphology engenders a material chemical and electronic interplay exalting the heterostructure absorption up to ~ 98% over a large spectral range between 200 and 1500 nm. An arsenal of characterization methods were used to elucidate the properties of these novel heterostructures including Raman spectroscopy, X-ray diffraction, X-ray photoelectron spectrometry, high-resolution transmission and scanning electron microscopies, and Kelvin probe force microscopy. Our findings revealed that the MoS2 and the MoO2 crystallize in the hexagonal and monoclinic lattices, respectively. The integration of the MoS2/MoO2 heterostructures into functional photodetectors revealed a strong photoresponse under both standard sun illumination AM1.5G and blue light excitation at 450 nm. Responsivity and detectivity values as high as 0.75 mA W−1 and 1.45 × 107 Jones, respectively, were obtained with the lowest light intensity of 20 mW cm−2 at only 1 V bias. These results demonstrate the high performances achieved by the unique MoS2/MoO2 heterostructure for broadband light harvesting and pave the way for their adoption in photodetection applications.

Abstract The primary objective of this investigation was to determine the hub genes of hepatocellular carcinoma (HCC) through an in silico approach. In the current context of the increased incidence of liver cancers, this approach could be a useful prognostic biomarker and HCC prevention target. This study aimed to examine hub genes for immune cell infiltration and their good prognostic characteristics for HCC research. Human genes selected from databases (Gene Cards and DisGeNET) were used to identify the HCC markers. Further, classification of the hub genes from communicating genes was performed using data derived from the targets' protein–protein interaction (PPI) platform. The expression as well as survival studies of all these selected genes were validated by utilizing databases such as GEPIA2, HPA, and immune cell infiltration. Based on the studies, five hub genes (TP53, ESR1, AKT1, CASP3, and JUN) were identified, which have been linked to HCC. They may be an important prognostic biomarker and preventative target of HCC. In silico analysis revealed that out of five hub genes, the TP53 and ESR1 hub genes potentially act as key targets for HCC prevention and treatment.

Abstract Friction stir welding is a novel technique for joining ferrous and non-ferrous materials in a solid state. The groove fill techniques are most popular and generally used by researchers to dope reinforcement in the FSWed zone to improve the properties of joints. The main drawback of this technique is that a few amounts of reinforcement material come out from the groove during the fabrication of the joint. In the present work, the adhesive-assisted reinforcement technique was used to overcome this problem for the fabrication of particulates reinforced friction stirred weld joint. In the present work, the aluminum alloy plate edges were coated with a thin layer of TiB2. The coated and non-coated edge plates were joined using friction stir welding at the rotational speed of 1400 and 2240 rpm, and welding speed of 32 mm/min using a taper threaded pin tool. The tensile strength of coated edge plate welded joints was found highest in comparison to non-coated joints which was 39.74% superior. The percentage elongation of coated edge joint was observed about 1.5 times lower than the non-coated edge plate joint. The flexure strength of TiB2 reinforced coated edge joint was found about 1.5 times higher. However, the impact strength of coated edge plate was found nearly three times lower than the uncoated edge joints. The TiB2 coated edge joints reveal 22.75% higher hardness than the non-coated edge plate joints welded at the rotational speed of 2240.

Abstract Computational tools provide a unique opportunity to study and design optimal materials by enhancing our ability to comprehend the connections between their atomistic structure and functional properties. However, designing materials with tailored functionalities is complicated due to the necessity to integrate various computational-chemistry software (not necessarily compatible with one another), the heterogeneous nature of the generated data, and the need to explore vast chemical and parameter spaces. The latter is especially important to avoid bias in scattered data points-based models and derive statistical trends only accessible by systematic datasets. Here, we introduce a robust high-throughput multi-scale computational infrastructure coined MISPR (Materials Informatics for Structure–Property Relationships) that seamlessly integrates classical molecular dynamics (MD) simulations with density functional theory (DFT). By enabling high-performance data analytics and coupling between different methods and scales, MISPR addresses critical challenges arising from the needs of automated workflow management and data provenance recording. The major features of MISPR include automated DFT and MD simulations, error handling, derivation of molecular and ensemble properties, and creation of output databases that organize results from individual calculations to enable reproducibility and transparency. In this work, we describe fully automated DFT workflows implemented in MISPR to compute various properties such as nuclear magnetic resonance chemical shift, binding energy, bond dissociation energy, and redox potential with support for multiple methods such as electron transfer and proton-coupled electron transfer reactions. The infrastructure also enables the characterization of large-scale ensemble properties by providing MD workflows that calculate a wide range of structural and dynamical properties in liquid solutions. MISPR employs the methodologies of materials informatics to facilitate understanding and prediction of phenomenological structure–property relationships, which are crucial to designing novel optimal materials for numerous scientific applications and engineering technologies.

Abstract The iron impregnated fungal bio-filter (IIFB) discs of luffa sponge containing Phanerochaete chrysosporium mycelia have been used for the removal of As(III) from water. Two different forms of same biomass viz. free fungal biomass (FFB) and modified free fungal biomass (chemically modified and iron impregnated; CFB and IIFB) have been simultaneously investigated to compare the performance of immobilization, chemo-tailoring and iron impregnation for remediation of As(III). IIFB showed highest uptake capacity and percentage removal of As(III), 1.32 mg/g and 92.4% respectively among FFB, CFB and IIFB. Further, the application of RSM and ANN-GA based mathematical model showed a substantial increase in removal i.e. 99.2% of As(III) was filtered out from water at optimised conditions i.e. biomass dose 0.72 g/L, pH 7.31, temperature 42 °C, and initial As(III) concentration 1.1 mg/L. Isotherm, kinetic and thermodynamic studies proved that the process followed monolayer sorption pattern in spontaneous and endothermic way through pseudo-second order kinetic pathway. Continuous mode of As(III) removal in IIFB packed bed bioreactor, revealed increased removal of As(III) from 76.40 to 88.23% with increased column height from 5 to 25 cm whereas the removal decreased from 88.23 to 69.45% while increasing flow rate from 1.66 to 8.30 mL/min. Moreover, the IIFB discs was regenerated by using 10% NaOH as eluting agent and evaluated for As(III) removal for four sorption–desorption cycles, showing slight decrease of their efficiency by 1–2%. SEM–EDX, pHzpc, and FTIR analysis, revealed the involvement of hydroxyl and amino surface groups following a non-electrostatic legend exchange sorption mechanism during removal of As(III).

POU5F1 is a transcription factor and master regulator of cell pluripotency with indispensable roles in early embryo development and cell lineage specification. The role of embryonic POU5F1 in blastocyst formation and cell lineage specification differs between mammalian species but remains completely unknown in cattle. The CRISPR/Cas9 system was utilized for targeted disruption of the POU5F1 gene by direct injection into zygotes. Disruption of the bovine POU5F1 locus prevented blastocyst formation and was associated with embryonic arrest at the morula stage. POU5F1 knockout morulas developed at a similar rate as control embryos and presented a similar number of blastomeres by day 5 of development. Initiation of SOX2 expression by day 5 of development was not affected by lack of POU5F1. On the other hand, CDX2 expression was aberrant in embryos lacking POU5F1. Notably, the phenotype observed in bovine POU5F1 knockout embryos reveals conserved functions associated with loss of human embryonic POU5F1 that differ from Pou5f1- null mice. The similarity observed in transcriptional regulation of early embryo development between cattle and humans combined with highly efficient gene editing techniques make the bovine a valuable model for human embryo biology with expanded applications in agriculture and assisted reproductive technologies.

Abstract The Novel Coronavirus which emerged in India on January/30/2020 has become a catastrophe to the country on the basis of health and economy. Due to rapid variations in the transmission of COVID-19, an accurate prediction to determine the long term effects is infeasible. This paper has introduced a nonlinear mathematical model to interpret the transmission dynamics of COVID-19 infection along with providing vaccination in the precedence. To minimize the level of infection and treatment burden, the optimal control strategies are carried out by using the Pontryagin’s Maximum Principle. The data validation has been done by correlating the estimated number of infectives with the real data of India for the month of March/2021. Corresponding to the model, the basic reproduction number $${\mathcal {R}}_0$$ R 0 is introduced to understand the transmission dynamics of COVID-19. To justify the significance of parameters we determined the sensitivity analysis of $${\mathcal {R}}_0$$ R 0 using the parameters value. In the numerical simulations, we concluded that reducing $${\mathcal {R}}_0$$ R 0 below unity is not sufficient enough to eradicate the COVID-19 disease and thus, it is required to increase the vaccination rate and its efficacy by motivating individuals to take precautionary measures.

Abstract Tuberculosis is one the oldest known affliction of mankind caused by the pathogen Mycobacterium tuberculosis. Till date, there is no absolute single treatment available to deal with the pathogen, which has acquired a great potential to develop drug resistance rapidly. BCG is the only anti-tuberculosis vaccine available till date which displays limited global efficacy due to genetic variation and concurrent pathogen infections. Extracellular vesicles or exosomes vesicle (EVs) lie at the frontier cellular talk between pathogen and the host, and therefore play a significant role in establishing pathogenesis. In the present study, an in-silico approach has been adopted to construct a multi-epitope vaccine from selected immunogenic EVs proteins to elicit a cellular as well as a humoral immune response. Our designed vaccine has wide population coverage and can effectively compensate for the genetic variation among different populations. For maximum efficacy and minimum adverse effects possibilities the antigenic, non-allergenic and non-toxic B-cell, HTL and CTL epitopes from experimentally proven EVs proteins were selected for the vaccine construct. TLR4 agonist RpfE served as an adjuvant for the vaccine construct. The vaccine construct structure was modelled, refined and docked on TLR4 immune receptor. The designed vaccine construct displayed safe usage and exhibits a high probability to elicit the critical immune regulators, like B cells, T-cells and memory cells as displayed by the in-silico immunization assays. Therefore, it can be further corroborated using in vitro and in vivo assays to fulfil the global need for a more efficacious anti-tuberculosis vaccine.

Abstract Irradiation induced damage in materials is highly detrimental and is a critical issue in several vital science and technology fields, e.g., the nuclear and space industries. While the effect of dimensionality (nano/bulk) of materials on its radiation damage tolerance has been receiving tremendous interest, studies have only concentrated on low energy (nuclear energy loss (Sn) dominant) and high energy (electronic energy loss (Se) dominant) irradiations independently (wherein, interestingly, the effect is opposite). In-fact, research on radiation damage in general has almost entirely focused only on independent irradiations with low and/or high energy particles till date, and investigations under simultaneous impingement of energetic particles (which also correspond to the actual irradiation conditions during real-world applications) are very scarce. The present work elucidates, taking cubic zirconia as a model system, the effect of grain size (26 nm vs 80 nm) on the radiation tolerance against simultaneous irradiation with low energy (900 keV I) and high energy (27 meV Fe) particles/ions; and, in particular, introduces the enhancement in the radiation damage tolerance upon downsizing from bulk to nano dimension. This result is interpreted within the framework of the thermal-spike model after considering (1) the fact that there is essentially no spatial and time overlap between the damage events of the two ‘simultaneous’ irradiations, and (2) the influence of grain size on radiation damage against individual Sn and Se. The present work besides providing the first fundamental insights into how the grain size/grain boundary density inherently mediates the radiation response of a material to simultaneous Sn and Se deposition, also (1) paves the way for potential application of nano-crystalline materials in the nuclear industry (where simultaneous irradiations with low and high energy particles correspond to the actual irradiation conditions), and (2) lays the groundwork for understanding the material behaviour under other simultaneous (viz. Sn and Sn, Se and Se) irradiations.

Abstract Patients infected with SARS-CoV-2 may deteriorate rapidly and therefore continuous monitoring is necessary. We conducted an observational study involving patients with mild COVID-19 to explore the potentials of wearable biosensors and machine learning-based analysis of physiology parameters to detect clinical deterioration. Thirty-four patients (median age: 32 years; male: 52.9%) with mild COVID-19 from Queen Mary Hospital were recruited. The mean National Early Warning Score 2 (NEWS2) were 0.59 ± 0.7. 1231 manual measurement of physiology parameters were performed during hospital stay (median 15 days). Physiology parameters obtained from wearable biosensors correlated well with manual measurement including pulse rate (r = 0.96, p