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Abstract Hyperspectral image (HSI) data has a wide range of valuable spectral information for numerous tasks. HSI data encounters challenges such as small training samples, scarcity, and redundant information. Researchers have introduced various research works to address these challenges. Convolution Neural Network (CNN) has gained significant success in the field of HSI classification. CNN’s primary focus is to extract low-level features from HSI data, and it has a limited ability to detect long-range dependencies due to the confined filter size. In contrast, vision transformers exhibit great success in the HSI classification field due to the use of attention mechanisms to learn the long-range dependencies. As mentioned earlier, the primary issue with these models is that they require sufficient labeled training data. To address this challenge, we proposed a spectral-spatial feature extractor group attention transformer that consists of a multiscale feature extractor to extract low-level or shallow features. For high-level semantic feature extraction, we proposed a group attention mechanism. Our proposed model is evaluated using four publicly available HSI datasets, which are Indian Pines, Pavia University, Salinas, and the KSC dataset. Our proposed approach achieved the best classification results in terms of overall accuracy (OA), average accuracy (AA), and Kappa coefficient. As mentioned earlier, the proposed approach utilized only 5%, 1%, 1%, and 10% of the training samples from the publicly available four datasets.

Abstract Malignant transformation (MT) is commonly seen in IDH-mutant gliomas. There has been a growing research interest in revealing its underlying mechanisms and intervening prior to MT at the early stages of the transforming process. Here we established a unique pair of matched 3D cell models: 403L, derived from a low-grade glioma (LGG), and 403H, derived from a high-grade glioma (HGG), by utilizing IDH-mutant astrocytoma samples from the same patient when the tumor was diagnosed as WHO grade 2 (tumor mutational burden (TMB) of 3.96/Mb) and later as grade 4 (TMB of 70.07/Mb), respectively. Both cell models were authenticated to a patient’s sample retaining endogenous expression of IDH1 R132H. DNA methylation profiles of the parental tumors referred to LGG and HGG IDH-mutant glioma clusters. The immunopositivity of SOX2, NESTIN, GFAP, OLIG2, and beta 3-Tubulin suggested the multilineage potential of both models. 403H was more prompt to cell invasion and developed infiltrative HGG in vivo. The differentially expressed genes (DEGs) from the RNA sequencing analysis revealed the tumor invasion and aggressiveness related genes exclusively upregulated in the 403H model. Pathway analysis showcased an enrichment of genes associated with epithelial-mesenchymal transition (EMT) and Notch signaling pathways in 403H and 403L, respectively. Mass spectrometry-based targeted metabolomics and hyperpolarized (HP) 1-13C pyruvate in-cell NMR analyses demonstrated significant alterations in the TCA cycle and fatty acid metabolism. Citrate, glutamine, and 2-HG levels were significantly higher in 403H. To our knowledge, this is the first report describing the development of a matched pair of 3D patient-derived cell models representative of MT and temozolomide (TMZ)-induced hypermutator phenotype (HMP) in IDH-mutant glioma, providing insights into genetic and metabolic changes during MT/HMP. This novel in vitro model allows further investigation of the mechanisms of MT at the cellular level. Graphic Abstract

Abstract Chimeric antigen receptor (CAR) T-cells targeting Fibroblast Growth Factor Receptor 4 (FGFR4), a highly expressed surface tyrosine receptor in rhabdomyosarcoma (RMS), are already in the clinical phase of development, but tumour heterogeneity and suboptimal activation might hamper their potency. Here we report an optimization strategy of the co-stimulatory and targeting properties of a FGFR4 CAR. We replace the CD8 hinge and transmembrane domain and the 4-1BB co-stimulatory domain with those of CD28. The resulting CARs display enhanced anti-tumor activity in several RMS xenograft models except for an aggressive tumour cell line, RMS559. By searching for a direct target of the RMS core-regulatory transcription factor MYOD1, we identify another surface protein, CD276, as a potential target. Bicistronic CARs (BiCisCAR) targeting both FGFR4 and CD276, containing two distinct co-stimulatory domains, have superior prolonged persistent and invigorated anti-tumor activities compared to the optimized FGFR4-specific CAR and the other BiCisCAR with the same 4-1BB co-stimulatory domain. Our study thus lays down the proof-of-principle for a CAR T-cell therapy targeting both FGFR4 and CD276 in RMS.

A series of new benzohydrazide based thiourea derivatives were synthesized, characterized through different spectroscopic techniques like 1HNMR, 13CNMR and HREI-MS and screened against Bacillus pasteurii (B.P) and Jack bean (J.B) ureases enzymes. All derivatives showed good inhibitory potential ranging from 20.05 ± 0.03 to 39.34 ± 1.05 (against J.B Urease) and 23.54 ± 0.21 to 58.65 ± 0.41 (against B.P Urease) as compared to the standard thiourea (IC50 = 14.02 ± 0.25 and 18.01 ± 0.13 µM, respectively). It was observed that the two scaffold 1 (IC50 = 23.54 ± 0.21 and 20.05 ± 0.03 µM) and 2 (IC50 = 26.20 ± 0.32 and 21.33 ± 0.17 µM) among the series showed good inhibitory potential. The binding interaction of the most potent analogues with the active site of enzyme were examined through the molecular docking study.

Underwater Wireless Sensor Networks (UWSNs) are essential for a number of environmental and oceanographic monitoring applications. However, they face different and more complex challenges than terrestrial wireless sensor networks (TWSNs). The main challenges faced by UWSNs are limited include high propagation delays, poor bandwidth, low throughput, and high energy consumption. Replacing sensor batteries in such networks becomes extremely difficult as they are usually deployed in remote areas where limited human interaction is possible. The unbalanced and inefficient usage of energy by various network nodes poses another issue, as it may reduce the applicability and feasibility of the network. Therefore, proposing Energy-Efficient Routing Protocols (E-ER-Ps) is crucial to improve the performance and lifespan of these networks. Due to the challenges mentioned earlier, this research presents an extensive analysis of several different E-ER-Ps intended for UWSNs. We compare contemporary approaches that use machine learning (ML) with conventional protocols, as ML-based approaches have shown significant potential in resolving the intricate challenges faced by UWSNs. This paper aims to present a critical review of different E-ER-Ps from various prospects for UWSNs. To better comprehend the structure and uses of these protocols, we provide an innovative taxonomy for their classification. While ML-based protocols are evaluated for their flexibility, predictive power, and overall efficiency advancements, traditional protocols are evaluated based on their routing tactics and energy-efficiency improvements. A thorough comparative analysis highlights the advantages, disadvantages, and possible uses for different protocols. Furthermore, a critical analysis of ML’s function, incorporating intelligent and adaptive routing approaches, is presented, highlighting the technology’s potential to completely alter UWSN management. To formulate and implement E-ER-Ps for UWSNs, the article concludes by highlighting the present obstacles, including the need for real-time flexibility, resilience to environmental alters, and interaction with pre-existing network infrastructures. The development of ML-based approaches, hybrid approaches that combine conventional and ML-based methodologies, and the design of protocols that can adapt dynamically to the changing circumstances of underwater habitats are highlighted as future research objectives. This research provides the foundation for future advancements in this crucial field by presenting a comprehensive overview of the state-of-the-art UWSN E-ER-Ps.

Abstract Temporal regulation of super-enhancer (SE) driven transcription factors (TFs) underlies normal developmental programs. Neuroblastoma (NB) arises from an inability of sympathoadrenal progenitors to exit a self-renewal program and terminally differentiate. To identify SEs driving TF regulators, we use all-trans retinoic acid (ATRA) to induce NB growth arrest and differentiation. Time-course H3K27ac ChIP-seq and RNA-seq reveal ATRA coordinated SE waves. SEs that decrease with ATRA link to stem cell development (MYCN, GATA3, SOX11). CRISPR-Cas9 and siRNA verify SOX11 dependency, in vitro and in vivo. Silencing the SOX11 SE using dCAS9-KRAB decreases SOX11 mRNA and inhibits cell growth. Other TFs activate in sequential waves at 2, 4 and 8 days of ATRA treatment that regulate neural development (GATA2 and SOX4). Silencing the gained SOX4 SE using dCAS9-KRAB decreases SOX4 expression and attenuates ATRA-induced differentiation genes. Our study identifies oncogenic lineage drivers of NB self-renewal and TFs critical for implementing a differentiation program.

Summary: Sarcomas are a diverse group of rare malignancies composed of multiple different clinical and molecular subtypes. Due to their rarity and heterogeneity, basic, translational, and clinical research in sarcoma has trailed behind that of other cancers. Outcomes for patients remain generally poor due to an incomplete understanding of disease biology and a lack of novel therapies. To address some of the limitations impeding preclinical sarcoma research, we have developed Sarcoma_CellMinerCDB, a publicly available interactive tool that merges publicly available sarcoma cell line data and newly generated omics data to create a comprehensive database of genomic, transcriptomic, methylomic, proteomic, metabolic, and pharmacologic data on 133 annotated sarcoma cell lines. The reproducibility, functionality, biological relevance, and therapeutic applications of Sarcoma_CellMinerCDB described herein are powerful tools to address and generate biological questions and test hypotheses for translational research. Sarcoma_CellMinerCDB (https://discover.nci.nih.gov/SarcomaCellMinerCDB) aims to contribute to advancing the preclinical study of sarcoma.

Abstract Fusion-positive rhabdomyosarcoma (FP-RMS) is an aggressive pediatric sarcoma driven primarily by the PAX3-FOXO1 fusion oncogene, for which therapies targeting PAX3-FOXO1 are lacking. Here, we screen 62,643 compounds using an engineered cell line that monitors PAX3-FOXO1 transcriptional activity identifying a hitherto uncharacterized compound, P3FI-63. RNA-seq, ATAC-seq, and docking analyses implicate histone lysine demethylases (KDMs) as its targets. Enzymatic assays confirm the inhibition of multiple KDMs with the highest selectivity for KDM3B. Structural similarity search of P3FI-63 identifies P3FI-90 with improved solubility and potency. Biophysical binding of P3FI-90 to KDM3B is demonstrated using NMR and SPR. P3FI-90 suppresses the growth of FP-RMS in vitro and in vivo through downregulating PAX3-FOXO1 activity, and combined knockdown of KDM3B and KDM1A phenocopies P3FI-90 effects. Thus, we report KDM inhibitors P3FI-63 and P3FI-90 with the highest specificity for KDM3B. Their potent suppression of PAX3-FOXO1 activity indicates a possible therapeutic approach for FP-RMS and other transcriptionally addicted cancers.

Abstract The significant natural energy sources for reducing the global usage of fossil fuels are renewable energy (RE) sources. Solar energy is a crucial and reliable RE source. Site selection for solar photovoltaic (PV) farms is a crucial issue in terms of spatial planning and RE policies. This study adopts a Geographic Information System (GIS)-based Multi-Influencing Factor (MIF) technique to enhance the precision of identifying and delineating optimal locations for solar PV farms. The choice of GIS and MIF is motivated by their ability to integrate diverse influencing factors, facilitating a holistic analysis of spatial data. The selected influencing factors include solar radiation, wind speed, Land Surface Temperature (LST), relative humidity, vegetation, elevation, land use, Euclidean distance from roads, and aspect. The optimal sites of solar PV power plant delineated revealed that ‘very low’ suitability of site covering 4.866% of the study area, ‘low’ suitability of site 13.190%, ‘moderate’ suitability of site 31.640%, ‘good’ suitability of site 32.347%, and ‘very good’ suitability of site for solar PV power plant encompassing 17.957% of the study area. The sensitivity analysis results show that the solar radiation, relative humidity, and elevation are the most effective on the accuracy of the prediction. The validation of the results shows the accuracy of solar PV power plant prediction using MIF technique in the study area was 81.80%. The integration of GIS and MIF not only enhances the accuracy of site suitability assessment but also provides a practical implementation strategy. This research offers valuable insights for renewable energy policymakers, urban planners, and other stakeholders seeking to identify and develop optimal locations for solar energy power farms in their respective regions.

This Power quality problem is a vital issue in current-day power system with the increased penetration of distributed generation (DG) systems which greatly affects the stability and reliability of the system. This study presents a comprehensive analysis of detection and classification strategies for monitoring power quality (PQ) disturbances. Specifically, the focus is on PQ disturbances caused as a result of load switching and variations in environmental factors, such as changes in solar irradiation and wind speed. Twelve different types of PQ disturbances under various operating scenarios are considered for the detection and classification study. Twelve different statistical features are extracted by passing the disturbances through robust H-infinity filter in order to minimize the data size and computational complexities. The statistical properties of PQ disturbances are initially categorized using the Fast Generalized Fuzzy-C means (FGFCM) clustering approach. Further, the disturbances are correctly classified by pattern classification approach like support vector machines (SVM) in order to distinctly classify them. The validity of the classification analysis is reinforced by the inclusion of experimental data gathered from a prototype wind energy system and photovoltaic (PV) system setup. Again, Genetic algorithm (GA) is used for extracting optimal features and Particle swarm optimization (PSO) is applied for optimising the heuristic parameters of the SVM in order to improvise the classification accuracy under normal, noisy as well as increased penetration of wind and photovoltaic (PV) systems.

This article addresses the optimality and stability issues of a Tidal power based hybrid power system (HPS). The Tidal system gets destabilized by the uncertain variation of tidal waves and wind input. Stability of the system is restored through the introduction of Unified Power Flow Controller (UPFC) controller. The controller is optimized through the process of configuration of Hyper Spherical Search (HSS) based algorithm. The evaluation of the effectiveness of the suggested controllers is conducted through comparison analyses in order to regulate the voltage profile of the interconnected power network under various loading scenarios. The efficacy of the suggested controllers is assessed by stability analysis utilizing Eigen and Nyquist plots. Further, it is quite evident that optimal tuning is possible in case of the controller where the parameters can create significant impact on the system performance. Consequently, a novel heuristic optimization technique, such as HSS Algorithm are suggested to find the best output of the proposed controller. Finally, by using real-data, the performance as well as robustness of the suggested controller have examined by utilizing a real-time digital simulation platform, specifically the OPAL-RT 5142.

Abstract Rhabdomyosarcomas (RMS) are pediatric mesenchymal-derived malignancies encompassing PAX3/7-FOXO1 Fusion Positive (FP)-RMS, and Fusion Negative (FN)-RMS with frequent RAS pathway mutations. RMS express the master myogenic transcription factor MYOD that, whilst essential for survival, cannot support differentiation. Here we discover SKP2, an oncogenic E3-ubiquitin ligase, as a critical pro-tumorigenic driver in FN-RMS. We show that SKP2 is overexpressed in RMS through the binding of MYOD to an intronic enhancer. SKP2 in FN-RMS promotes cell cycle progression and prevents differentiation by directly targeting p27Kip1 and p57Kip2, respectively. SKP2 depletion unlocks a partly MYOD-dependent myogenic transcriptional program and strongly affects stemness and tumorigenic features and prevents in vivo tumor growth. These effects are mirrored by the investigational NEDDylation inhibitor MLN4924. Results demonstrate a crucial crosstalk between transcriptional and post-translational mechanisms through the MYOD-SKP2 axis that contributes to tumorigenesis in FN-RMS. Finally, NEDDylation inhibition is identified as a potential therapeutic vulnerability in FN-RMS.

The electrochemical act of valve-regulated lead acid batteries can be enhanced by conductive materials like metal oxides. This work aims to examine the preparation and influence of zirconia on poly(vinyl alcohol) based gel valve-regulated lead acid battery. Characterizations like Fourier transform infrared spectroscopy, ionic conductivity, water retention study, cyclic voltammetry, electrochemical impedance spectroscopy and galvanostatic charge-discharge techniques were done. The optimized gel system exhibited a discharge capacity of 198.45 μAh cm−2 at the current density of 0.6 mA cm−2. The battery cell with an optimized gel matrix displayed a maximum discharge capacity of 22.5 μAh at a current of 20 μA. After 500 continuous cycles, the battery attained a discharge capacity retention of 91 %. The presence of zirconia will increase the electrochemical performance of gel valve-regulated lead acid batteries.

Abstract Rational design of chimeric antigen receptor T (CAR-T) cells based on the recognition of antigenic epitopes capable of evoking the most potent CAR activation is an important objective in optimizing immune therapy. In solid tumors, the B7-H3 transmembrane protein is an emerging target that harbours two distinct epitope motifs, IgC and IgV, in its ectodomain. Here, we generate dromedary camel nanobodies targeting B7-H3 and demonstrate that CAR-T cells, based on the nanobodies recognizing the IgC but not IgV domain, had potent antitumour activity against large tumors in female mice. These CAR-T cells are characterized by highly activated T cell signaling and significant tumor infiltration. Single-cell transcriptome RNA sequencing coupled with functional T-cell proteomics analysis uncovers the top-upregulated genes that might be critical for the persistence of polyfunctional CAR-T cells in mice. Our results highlight the importance of the specific target antigen epitope in governing optimal CAR-T activity and provide a nanobody-based B7-H3 CAR-T product for use in solid tumor therapy.

ABSTRACT: We report a comprehensive drug synergy study in acute myeloid leukemia (AML). In this work, we investigate a panel of cell lines spanning both MLL-rearranged and non-rearranged subtypes. The work comprises a resource for the community, with many synergistic drug combinations that could not have been predicted a priori, and open source code for automation and analyses. We base our definitions of drug synergy on the Chou-Talalay method, which is useful for visualizations of synergy experiments in isobolograms, and median-effects plots, among other representations. Our key findings include drug synergies affecting the chromatin state, specifically in the context of regulation of the modification state of histone H3 lysine-27. We report open source high throughput methodology such that multidimensional drug screening can be accomplished with equipment that is accessible to most laboratories. This study will enable preclinical investigation of new drug combinations in a lethal blood cancer, with data analysis and automation workflows freely available to the community.

Calotropis procera is a medicinal, traditional, and therapeutic plant in Pakistan. In this research study, the biological activities, for instance, anticancer, antileishmanial, antibacterial, antifungal, anti-inflammatory, and brine shrimp lethality assay and GC-MS are studied. MTT assay, antileishmanial bioassay, microplate Alamar Blue assay, agar tube dilution method, oxidative burst assay using chemiluminescence technique, B-hatching techniques, and triple quadrupole acquisition method MS parameters were the methods used for anticancer, antileishmanial, antibacterial, antifungal, anti-inflammatory, brine shrimp lethality assay, and gas chromatography-mass spectrometry. Whole plant methanol extract of Calotropis procera (WMECP) inhibited 69.1% of the growth of HeLa cell line with an IC50 value of 3.1 ± 0.4 and whole plant n-hexane fraction of Calotropis procera (WHFCP) and whole plant and aqueous fraction of Calotropis procera (WAFCP) inhibited the growth by 70.2% and 65.2% with IC50 values of 5.0 ± 0.3 and 17.1 ± 1.0. Whole plant methanol extract of Calotropis procera (WMECP) inhibited 70.1% of the growth of the PC3 cell line with an IC50 value of 5.1 ± 0.3 and whole plant n-hexane fraction of Calotropis procera (WHFCP) and whole plant aqueous fraction of Calotropis procera (WAFCP) inhibited 61.6% and 59.7% with IC50 values of 3.7 ± 0.5 and 16.4 ± 1.0. None of the extract and fractions of Calotropis procera showed anticancer activities against the 3T3 cell line. None of the extract and fractions of Calotropis procera showed antileishmanial, antibacterial, antifungal, and anti-inflammatory activities. Whole plant methanol extract of Calotropis procera (WMECP) exhibited lethality at the highest concentration while other fractions did not exhibit lethality. GC-MS studies revealed that the whole plant methanol extract of Calotropis procera (WMECP) consists of 11 compounds, whole plant n-hexane fraction of Calotropis procera (WHFCP) consists of 9 compounds, and whole plant aqueous fraction of Calotropis procera (WAFCP) consists of 7 compounds.

Naphthoquinones are secondary plant metabolites that are used to treat a variety of human ailments in traditional medicine. In light of this, the synthesis of derivatives of naphthoquinone has been investigated to include substances with potential biological processes. It has been claimed that adding chemical groups such as amines, amino acids, furan, pyran, pyrazole, triazole, and indole increases the pharmacological effects of naphthoquinones. Drugs based on 1,4 naphthoquinone ring-containing moieties have attracted a lot of interest lately because of their wide range of biological activity and possible therapeutic uses. This article offers a thorough overview of 1,4 naphthoquinone ring containing derivatives synthesizing methods and therapeutic uses. The creation of naphthoquinone scaffolds was accomplished using a variety of synthesis techniques, including both traditional chemical synthesis and contemporary green chemistry techniques. In addition, the pharmacological characteristics and therapeutic potential of medications based on 1,4 naphthoquinone ring-containing moieties are investigated in a number of disease states, including cancer, infectious illnesses, cardiovascular disorders, and neurological diseases.

The biological synthesis of metallic nanoparticles (MtNPs) has increased greatly in the last few decades. Nanoparticles (NPs) are synthesized via different approaches like chemical and physical methods. However various drawbacks such as higher cost, high energy requirement, and the use of toxic chemicals limit the use of these approaches. It is thus important to look for an alternative method for the development of MtNPs. One such method, which has gained the most attention in recent years, is the bio-fabrication of MtNPs using microorganism like bacteria, fungi, actinomycetes and viruses. Amongst the microorganism used for NPs synthesis, bacteria are the most preferred candidate due to their diversity and better growth control. In this context, the present article concerns with association of genus bacillus with metal and metal oxide NPs. The current review thoroughly summarizes the mechanisms involved in the synthesis of MtNPs and their biomedical applications. The review also explains the major drawbacks associated with the synthesis of NPs via bacillus spp as well as the future prospects.

This numerical study aims to determine the exergy analysis for a modified solar heat collector (SHC) having wavy delta winglets as turbulent promoters. These winglets disrupt the viscous layer to improve the heat transfer rate from the heat-absorbing surface to the fluid medium in the rectangular channel. The analysis considers following parameters: the relative longitudinal pitch (P/H), number of waves (φ), and flow angle of attack (α0) and flow Reynolds number range of 4000–18000. The maximum exergy efficiency of 29.18% is achieved with a longitudinal pitch of 5, an angle of attack of 60°, and a relative number of waves of 5. To evaluate the system's feasibility and sustainability, the study uses a Sustainability Index (SI), which reflects the system's Waste Energy Ratio (WER) and Improvement Potential (IP). This assessment helps identify opportunities for improvement in the thermal system.

Abstract Aims In people at risk of heart failure (HF) enrolled in the Heart ‘OMics’ in AGEing (HOMAGE) trial, spironolactone reduced circulating markers of collagen synthesis, natriuretic peptides, and blood pressure and improved cardiac structure and function. In the present report, we explored factors associated with dyskalaemia. Methods and results The HOMAGE trial was an open‐label study comparing spironolactone (up to 50 mg/day) versus standard care in people at risk for HF. After randomization, serum potassium was assessed at 1 and 9 months and was defined as low when ≤3.5 mmol/L (hypokalaemia) and high when ≥5.5 mmol/L (hyperkalaemia). Multivariable logistic regression models were constructed to identify clinical predictors of dyskalaemia. A total of 513 participants (median age 74 years, 75% men, median estimated glomerular filtration rate 71 mL/min/1.73 m2) had serum potassium available and were included in this analysis. At randomization, 88 had potassium 5.0 mmol/L. During follow‐up, on at least one occasion, a serum potassium 5.0 mmol/L was observed in 38 (8%) and >5.5 mmol/L in 5 (1.0%) participants. The median (percentile25−75) increase in serum potassium with spironolactone during the study was 0.23 (0.16; 0.29) mmol/L. Because of the low incidence of dyskalaemia, for regression analysis, hypokalaemia and hyperkalaemia thresholds were set at 5.0 mmol/L, respectively. The occurrence of a serum potassium > 5.0 mmol/L during follow‐up was positively associated with the presence of diabetes mellitus {odds ratio [OR]: 1.21 [95% confidence interval (CI) 2.14; 3.79]} and randomization to spironolactone (OR: 2.83 [95% CI 1.49; 5.37]). Conversely, the occurrence of a potassium concentration

Abstract Background The life history and predation rate of the ladybird beetle, Harmonia dimidiata Fabricius (Coleoptera: Coccinellidae) were compared at four different temperatures (16, 20, 24, and 28 °C). The beetles were fed on the bird cherry-oat aphid, Rhopalosiphum padi Linnaeus (Hemiptera: Aphididae) and investigated at 70 ± 10% RH with a photoperiod of 14:10 h (L:D). Results The reproductive rates (R 0) were 20.07, 51.37, 66.95, and 14.54 beetle offspring at 16, 20, 24, and 28 °C, respectively. Results indicated that temperature had good impacts on the feeding potential, development, survivorship and fecundity, especially at 24 and 28 C compared with the other tested temperatures. In addition, the jackknife and bootstrap techniques were employed to estimate the population parameters' means. The obtained means of R 0 and other population parameters, using the bootstrap technique fit a normal distribution. Meanwhile, the jackknife technique generated biologically meaningless zero values for R 0. Both finite and predation rates were incorporated into limited predation rates for comparison of predation potential. Conclusion Both of the growth and predation rates indicated that H. dimidiata is more effective biocontrol agent for R. padi at 24 and 28 °C than at 20, 16 °C.

This paper provides the capability with a control topology for low voltage distribution network to satisfy sudden peak load demand by designing a system. Develop the electric vehicle (EV) farm accumulated based on the charging system for voltage regulation at a distribution node for transmitting power to the grid from EVs by a control vehicle-to-grid operation. Also, this paper concerns with modelling of an EV system with dynamic interaction with grid integrated with major classifications from the state of charge (SOC). In EV farm, four various EV profiles were considered to understand the grid integration and supply the sudden peak load demand. The EV farm integration with the grid was observed by modelling an equivalent system in MATLAB/Simulink.

In the past few years, significant research efforts have been directed toward improving the electrochemical capabilities of supercapacitors by advancing electrode materials. The present work signifies the development of poly(lactic acid)/alloysite nano-clay as an electrode material for supercapacitors. Physico-chemical characterizations were analyzed by Fourier transform infrared spectroscopy, wide-angle X-ray diffraction, and a universal testing machine. Cyclic voltammetry, electrochemical impedance spectroscopy, and galvanostatic charge–discharge techniques were employed to evaluate electrochemical characteristics. The optimized poly(lactic acid)/halloysite nano-clay film revealed the highest specific capacitance of 205.5 F g−1 at 0.05 A g−1 current density and showed 14.6 Wh kg−1 energy density at 72 W kg−1 power density. Capacitance retention of 98.48% was achieved after 1000 cycles. The microsupercapacitor device presented a specific capacitance of 197.7 mF g−1 at a current density of 0.45 mA g−1 with 10.8 mWh kg−1 energy density at 549 mW kg−1 power density.

With the passage of time, scale gradually forms inside the oil pipeline. The produced scale, which has a high density, strongly attenuates photons, which lowers the measurement accuracy of three-phase flow meters based on gamma radiation. It is worth mentioning that the need for multiphase flow metering arises when it is necessary or desirable to meter well stream(s) upstream of inlet separation and/or commingling. In this investigation, a novel technique based on artificial intelligence is presented to overcome the issue mentioned earlier. Initially, a detection system was comprised of two NaI detectors and a dual-energy gamma source (241 Am and 133 Ba radioisotopes) using Monte Carlo N particle (MCNP) code. A stratified flow regime with varying volume percentages of oil, water, and gas was modeled inside a pipe that included a scale layer with varying thicknesses. Two detectors record the attenuated photons that could travel through the pipe. Four characteristics with the names of the amplitude of the first and second dominant signal frequencies were extracted from the received signals by both detectors. The aforementioned obtained characteristics were used to train two Radial Basis Function (RBF) neural networks to forecast the volumetric percentages of each component. The RMSE value of the gas and oil prediction neural networks are equal to 0.27 and 0.29, respectively. By measuring two phases of fluids in the pipe, the volume of the third phase can be calculated by subtracting the volume of two phases from the total volume of the pipe. Extraction and introduction of suitable characteristics to determine the volume percentages, reducing the computational burden of the detection system, considering the scale value thickness the pipe, and increasing the accuracy in determining the volume percentages of oil pipes are some of the advantages of the current research, which has increased the usability of the proposed system as a reliable measuring system in the oil and petrochemical industry.

Background: Till date, no data has been published about the use of intravenous (IV) thrombolysis in acute ischemic stroke (AIS) from Kashmir valley. Objective: The objective of the study is to assess and determine the pattern of use of IV thrombolysis for AIS in Kashmir, including its efficacy and the difficulties faced in providing this modality of treatment. Materials and Methods: This was a prospective cross-sectional observational study conducted from July 2016 to July 2018. All those patients who were admitted with a diagnosis of stroke and gave informed consent were included in this study. Results: A total of 2023 patients of stroke presented to our emergency department during the study period. Out of them, 1085 (53.6%) cases were found to have hemorrhagic stroke and 938 (46.3%) patients were having ischemic stroke. 9.2% patients of ischemic stroke presented within the window period of thrombolysis, but only 34 (3.6%) patients received IV alteplase. The mean onset to door time in those who received thrombolysis was 103.5 ± 51.17 min. Door-to-needle time (DNT) of ≤60 min was achieved in only 14 (41.2%) cases, whereas mean DNT was 82.7 ± 49.17. There was a statistically significant improvement in the National Institutes of Health Stroke Scale in those who received thrombolysis as compared to those who did not receive it. Conclusion: Hemorrhagic stroke occurs in majority of stroke patients (53.6%) in our community. 3.6% of ischemic stroke patients were thrombolyzed. Thrombolytic therapy presented positive outcomes in comparison to nonthrombolyzed patients which, however, was not statistically significant.

Abstract Background Copy number variants (CNVs) are the gain or loss of DNA segments in the genome. Studies have shown that CNVs are linked to various disorders, including autism, intellectual disability, and schizophrenia. Consequently, the interest in studying a possible association of CNVs to specific disease traits is growing. However, due to the specific multi-dimensional characteristics of the CNVs, methods for testing the association between CNVs and the disease-related traits are still underdeveloped. We propose a novel multi-dimensional CNV kernel association test (MCKAT) in this paper. We aim to find significant associations between CNVs and disease-related traits using kernel-based methods. Results We address the multi-dimensionality in CNV characteristics. We first design a single pair CNV kernel, which contains three sub-kernels to summarize the similarity between two CNVs considering all CNV characteristics. Then, aggregate single pair CNV kernel to the whole chromosome CNV kernel, which summarizes the similarity between CNVs in two or more chromosomes. Finally, the association between the CNVs and disease-related traits is evaluated by comparing the similarity in the trait with kernel-based similarity using a score test in a random effect model. We apply MCKAT on genome-wide CNV datasets to examine the association between CNVs and disease-related traits, which demonstrates the potential usefulness the proposed method has for the CNV association tests. We compare the performance of MCKAT with CKAT, a uni-dimensional kernel method. Based on the results, MCKAT indicates stronger evidence, smaller p-value, in detecting significant associations between CNVs and disease-related traits in both rare and common CNV datasets. Conclusion A multi-dimensional copy number variant kernel association test can detect statistically significant associated CNV regions with any disease-related trait. MCKAT can provide biologists with CNV hot spots at the cytogenetic band level that CNVs on them may have a significant association with disease-related traits. Using MCKAT, biologists can narrow their investigation from the whole genome, including many genes and CNVs, to more specific cytogenetic bands that MCKAT identifies. Furthermore, MCKAT can help biologists detect significantly associated CNVs with disease-related traits across a patient group instead of examining each subject’s CNVs case by case.

Abstract Nanotechnology is a vast field of science with the most vibrant and conspicuous applications. The green synthesis approach is cost-effective, eco-friendly, and produces the most stable metal-based nanoparticles without the use of toxic chemicals. This study presents the green synthesis of iron nanoparticles (FeNPs). For biosynthesis of FeNPs, Phoenix dactylifera extract was used as a reducing agent and iron sulfate heptahydrate (FeSO4·7H2O) was used as a substrate. FeNPs were characterized by different techniques including UV–Visible spectroscopy, Fourier transform infrared spectroscopy (FTIR), and nano zeta-sizer analysis. The antimicrobial activity of FeNPs synthesized by using an aqueous extract of Phoenix dactylifera was evaluated against Escherichia coli, Bacillus subtilis, Micrococcus leutus, and Klebsiella pneumoniae. A notable color change from yellow to black confirmed the synthesis of FeNPs. The sharp peak at 450 nm UV–Visible spectroscopy confirmed the synthesis of FeNPs. FTIR showed the presence of O–H and C=C stretching due to the presence of phenol and alkene functional groups. The average size of FeNPs was 6092 d.nm. The results of antimicrobial activity showed that FeNPs exhibit different potential against different bacterial strains with a maximum 25 ± 0.360 zone of inhibition against Escherichia coli. Thus, green synthesized FeNPs could be used as potential antimicrobial agents.

Rhabdomyosarcoma (RMS) is a pediatric malignancy of skeletal muscle lineage with an aggressive subtype caused by translocations involving PAX3- /PAX7-FOXO1 chimeric transcription factors. Here the authors show that the BRG1-containing BAF complex is overexpressed and acts largely independently of the PAX3-FOXO1 chimera on chromatin to result in a myogenic differentiation blockade in this malignancy.

An innovative technique for implementing the maximum power point tracking (MPPT) system for the Photo-Voltaic (PV) panel is proposed in this paper. The system comprises of a Neural Network Estimator (NNE), followed by a conversion coefficient and a calculation stage of the optimal duty cycle. The proposed NNE technique, implemented in MATLAB/Simulink, calculates the ratio of open circuit voltage corresponding to each solar radiation for various value of temperature to the corresponding standard open circuit voltage. A regularization coefficient is determined, which estimates the voltage corresponding to the maximum power directly from the open circuit voltage for each solar radiation. Finally, from the input/output equation of boost converter, the optimal duty cycle is evaluated. Simulation results have been used to assess the system performance for various situations obtained by using an existing photovoltaic model and real weather data, and relevant comparisons are also done to substantiate the performance advantages of the method. The Simulation results demonstrate that the optimization of the P&O MPPT control with a NN algorithm provides better results and performance in terms of accuracy and complexity. The results support the effectiveness and performance of using NNE-based MPPT controller approach. It is demonstrated that this controller can achieve almost 99% of the real PVP maximum power.

Immune checkpoint blockade (ICB) benefits only a small subset of patients with small cell lung cancer (SCLC) and the mechanisms driving benefit are poorly understood. Here, the authors show that elevated Notch signaling predicts clinical benefit in ICB in relapsed SCLC.

Chimeric antigen receptor (CAR) T cell therapies targeting single antigens have performed poorly in clinical trials for solid tumors due to heterogenous expression of tumor-associated antigens (TAAs), limited T cell persistence, and T cell exhaustion. Here, we aimed to identify optimal CARs against glypican 2 (GPC2) or CD276 (B7-H3), which were highly but heterogeneously expressed in neuroblastoma (NB), a lethal extracranial solid tumor of childhood. First, we examined CAR T cell expansion in the presence of targets by digital droplet PCR. Next, using pooled competitive optimization of CAR by cellular indexing of transcriptomes and epitopes by sequencing (CITE-Seq), termed P-COCC, we simultaneously analyzed protein and transcriptome expression of CAR T cells to identify high-activity CARs. Finally, we performed cytotoxicity assays to identify the most effective CAR against each target and combined the CARs into a bicistronic “OR” CAR (BiCisCAR). BiCisCAR T cells effectively eliminated tumor cells expressing GPC2 or CD276. Furthermore, the BiCisCAR T cells demonstrated prolonged persistence and resistance to exhaustion when compared with CARs targeting a single antigen. This study illustrated that targeting multiple TAAs with BiCisCAR may overcome heterogenous expression of target antigens in solid tumors and identified a potent, clinically relevant CAR against NB. Moreover, our multimodal approach integrating competitive expansion, P-COCC, and cytotoxicity assays is an effective strategy to identify potent CARs among a pool of candidates.

Coal-fired power plants have been used to meet the energy requirements in countries where coal reserves are abundant and are the key source of NOx emissions. Owing to the serious environmental and health concerns associated with NOx emissions, much work has been carried out to reduce NOx emissions. Sophisticated artificial intelligence (AI) techniques have been employed during the past few decades, such as least-squares support vector machine (LSSVM), artificial neural networks (ANN), long short-term memory (LSTM), and gated recurrent unit (GRU), to develop the NOx prediction model. Several studies have investigated deep neural networks (DNN) models for accurate NOx emission prediction. However, there is a need to investigate a DNN-based NOx prediction model that is accurate and computationally inexpensive. Recently, a new AI technique, convolutional neural network (CNN), has been introduced and proven superior for image class prediction accuracy. According to the best of the author’s knowledge, not much work has been done on the utilization of CNN on NOx emissions from coal-fired power plants. Therefore, this study investigated the prediction performance and computational time of one-dimensional CNN (1D-CNN) on NOx emissions data from a 500 MW coal-fired power plant. The variations of hyperparameters of LSTM, GRU, and 1D-CNN were investigated, and the performance metrics such as RMSE and computational time were recorded to obtain optimal hyperparameters. The obtained optimal values of hyperparameters of LSTM, GRU, and 1D-CNN were then employed for models’ development, and consequently, the models were tested on test data. The 1D-CNN NOx emission model improved the training efficiency in terms of RMSE by 70.6% and 60.1% compared to LSTM and GRU, respectively. Furthermore, the testing efficiency for 1D-CNN improved by 10.2% and 15.7% compared to LSTM and GRU, respectively. Moreover, 1D-CNN (26 s) reduced the training time by 83.8% and 50% compared to LSTM (160 s) and GRU (52 s), respectively. Results reveal that 1D-CNN is more accurate, more stable, and computationally inexpensive compared to LSTM and GRU on NOx emission data from the 500 MW power plant.

Over time, the accumulation of scale within the transmission pipeline results in a decrease in the internal diameter of the pipe, leading to a decline in efficiency and energy waste. The employment of a gamma ray attenuation system that is non-invasive has been found to be a highly precise diagnostic technique for identifying volumetric percentages across various states. The most appropriate setup for simulating a volume percentage detection system through Monte Carlo N particle (MCNP) simulations involves a system consisting of two NaI detectors and dual-energy gamma sources, namely 241Am and 133Ba radioisotopes. A three-phase flow consisting of oil, water, and gas exhibits symmetrical homogenous flow characteristics across varying volume percentages as it traverses through scaled pipes of varying thicknesses. It is worth mentioning that there is an axial symmetry of flow inside the pipe that creates a homogenous flow pattern. In this study, the experiment involved the emission of gamma rays from one end of a pipe, with photons being absorbed by two detectors located at the other end. The resulting data included three distinct features, namely the counts under the photopeaks of 241Am and 133Ba from the first detector as well as the total count from the second detector. Through the implementation of a two-output MLP neural network utilising the aforementioned inputs, it is possible to accurately forecast the volumetric percentages with an RMSE of under 1.22, regardless of the thickness of the scale. The minimal error value ensures the efficacy of the proposed technique and the practicality of its implementation in the domains of petroleum and petrochemicals.

Aneurysmal fibrous histiocytoma (AFH) is a rare variant of cutaneous fibrous histiocytoma, with low malignant potential and infrequent metastatic progression. We present the case of a 19-year-old female with a large AFH of the neck metastatic to soft tissue and treated with radiation therapy and molecularly targeted therapy. To our knowledge, this is the first report describing either radiation therapy and palliation or the use of targeted therapy in this uncommon malignancy and can provide insight into future therapeutic strategies.

Rhabdomyosarcomas are tumours blocked in myogenic differentiation, which despite the expression of master muscle regulatory factors, including MYOD, are unable to differentiate. Here, the authors show that SNAI2 is upregulated by MYOD through super enhancers, binds to MYOD target enhancers, and arrests differentiation.

Embryonal rhabdomyosarcoma (ERMS) is a childhood cancer with impaired myogenic differentiation despite the presence of myogenic transcription factors. Here, the authors show that CASZ1 directly regulates these myogenic factors and the loss of CASZ1 is due to RAS-MEK signaling in ERMS.

Four-dimensional continuous chaotic models with Caputo fractional derivative are presented. Fixed point theory is used to investigate the existence and uniqueness of complex systems. The dynamical properties are studied, including the Lyapunov exponent, phase portrait, and time series analysis. The hyperchaotic nature of each system is revealed by the positive exponents. The numerical method is introduced to describe the influence of the order of the Caputo fractional derivative. The phase portraits are presented to investigate the behavior and effect of some key parameters and fractional orders on model dynamics. The systems approach fixed point attractors for fractional-order and increase the visibility of the attractor by decreasing fractional order. This means that a change in fractional order has a significant impact on the dynamics of the models. When the order of the derivative is equal to one, both systems oscillate frequently. However, as the fractional order is reduced, the system oscillations decrease as compared to the integer-order, and the system moves towards its fixed point, reveals the hidden attractors inherent in the system, and enabling it to develop to a stable state more efficiently.

Introduction: PARP inhibition may enhance antitumor responses in BAP1-associated mesothelioma by inducing synthetic lethality. Methods: A single-center, nonrandomized, phase 2 trial was conducted, in which patients with refractory mesothelioma were given olaparib 300 mg twice daily in a 21-day cycle until disease progression or intolerable toxicity. The primary objective was to determine the objective response rate on the basis of somatic or germline mutation status of DNA repair genes. The secondary objectives were to assess safety and tolerability and to determine progression-free survival (PFS) and overall survival (OS). Whole-exome sequencing was performed on blood and tumor. Results: A total of 23 previously treated patients with pleural and peritoneal mesothelioma were enrolled and treated (germline BAP1, n = 4; germline MRE11A, n = 1; somatic BAP1, n = 8 mutations). There was one (4%) partial response, 18 (78%) with stable disease at 6 weeks, and four (17%) with progressive disease. The median overall PFS and OS were 3.6 months (95% confidence interval [CI]: 2.7–4.2 mo) and 8.7 months (95% CI: 4.7 mo–not estimable), respectively. The median PFS of germline BAP1 mutants (n = 4) was 2.3 months (95% CI: 1.3–3.6 mo) versus 4.1 months (95% CI: 2.7–5.5 mo) for wild-type (n = 19; p = 0.019). The median OS was 4.6 months (95% CI: 3.1–4.9 mo) for germline BAP1 mutation versus 9.6 months (95% CI: 5.5 mo–not estimable) in no germline mutation (p = 0.0040). Olaparib was safe with no new safety concerns. Conclusions: Olaparib has limited activity in previously treated mesothelioma including patients with BAP1 mutations. Germline BAP1 mutations were associated with decreased PFS and OS.

The present study aims at understanding the effects of fuel preheating on engine characteristics of waste animal fat-oil (WAF-O) biodiesel in a single-cylinder CI engine, with the preheating technique proposed as an effective means for enhancing the fuel properties. To understand the effects of the preheated fuel, the WAF-O biodiesel was preheated at 60, 80, 100 and 120 °C and tested along with neat diesel and unheated WAF-O biodiesel. For this purpose, biodiesel was produced from different animal wastes by means of KOH-assisted ethanol-based transesterification, reporting its maximum yield as 96.37 ± 1.8%, with significant distribution of unsaturated oleic acid, saturated palmitic acid and stearic acid. Upon evaluating its fuel characteristics as per ASTM D6751 standards, a rise in preheating temperature by 1 °C reduced the density and kinematic viscosity of WAF-O biodiesel by 0.383 kg/m3 and 0.025 mm2/s, respectively, and was explained by the weakening of intermolecular forces between its fatty acid ester molecules. Preheated samples reported superior combustion characteristics by exhibiting increased in-cylinder pressure (2.24%, on average) and heat release rates in addition to their shortened ignition delay (1–4 °CA). Furthermore, preheating of WAF-O biodiesel reduced its specific fuel consumption and increased its brake thermal efficiency by 7.86% (on average) and 9.23% (on average), respectively. However, higher preheating temperatures (>120 °C) resulted in increased fuel consumption owing to its varied flow characteristics. In addition to the changes in combustion characteristics, preheating WAF-O bio-diesel also resulted in reduced carbon monoxide, nitrous oxide and hydrocarbon emission by 13.88%, 7.21% and 26.94%, respectively, and increased carbon dioxide emission by 7.58%. Summing up, the enhancements in overall engine characteristics of preheated samples were accounted for by their improvised fuel injection characteristics due to their reduced density and viscosity, which ensured for their effective combustion.

Summary: Targeting solid tumors must overcome several major obstacles, in particular, the identification of elusive tumor-specific antigens. Here, we devise a strategy to help identify tumor-specific epitopes. Glypican 2 (GPC2) is overexpressed in neuroblastoma. Using RNA sequencing (RNA-seq) analysis, we show that exon 3 and exons 7–10 of GPC2 are expressed in cancer but are minimally expressed in normal tissues. Accordingly, we discover a monoclonal antibody (CT3) that binds exons 3 and 10 and visualize the complex structure of CT3 and GPC2 by electron microscopy. The potential of this approach is exemplified by designing CT3-derived chimeric antigen receptor (CAR) T cells that regress neuroblastoma in mice. Genomic sequencing of T cells recovered from mice reveals the CAR integration sites that may contribute to CAR T cell proliferation and persistence. These studies demonstrate how RNA-seq data can be exploited to help identify tumor-associated exons that can be targeted by CAR T cell therapies.

Abstract Cellulose-based polymers have been successfully used in many areas of petroleum engineering especially in enhanced oil recovery drilling fluid, fracturing and cementing. This paper presents the application of cellulose-based polymer in oil well cementing. These polymers work as multifunctional additive in cement slurry that reduce the quantity of additives and lessen the operational cost of cementing operation. The viscosity of cellulose polymers such as hydroxyethyl cellulose (HEC), carboxymethylcellulose (CMC) and hydroxypropyl methylcellulose (HPMC) has been determined at various temperatures to evaluate the thermal degradation. Moreover, polymers are incorporated in cement slurry to evaluate the properties and affect in cement slurry at 90 °C. The API properties like rheology, free water separation, fluid loss and compressive strength of slurries with and without polymer have been determined at 90 °C. The experimental results showed that the viscosity of HPMC polymer was enhanced at 90 °C than other cellulose-based polymers. The comparative and experimental analyses showed that the implementation of cellulose-based polymers improves the API properties of cement slurry at 90 °C. The increased viscosity of these polymers showed high rheology that was adjusted by adding dispersant which optimizes the rheology of slurry. Further, improved API properties, i.e., zero free water separation, none sedimentation, less than 50 ml/30 min fluid loss and high compressive strength, were obtained through HEC, CMC and HPMC polymer. It is concluded that cellulose-based polymers are efficient and effective in cement slurry that work as multifunctional additive and improve API properties and cement durability. The cellulose-based polymers work as multifunctional additive that reduces the quantity of other additives in cement slurry and ultimately reduces the operational cost of cementing operation. The comparative analysis of this study opens the window for petroleum industry for proper selection of cellulose-based polymer in designing of cement slurry.

Core regulatory transcription factors are usually regulated by cell-type specific super enhancers (SEs). Here, the authors screen for chemical probes able to distinguish between SE-driven and promoter-driven transcription and find that histone deacetylases are selectively required for core regulatory transcription.

Glioma is the most common primary malignant brain tumor with a poor prognosis. Immune checkpoint inhibitors have been of great interest in investigation of glioma treatments. Here, we report single-cell transcriptomic analyses of two tumor areas from an oligodendroglioma taken from a patient who had multiple tumor recurrences, following several chemotherapies and radiation treatments. The patient subsequently received nivolumab and was considered have disease progression based on conventional diagnostic imaging after two cycles of treatment. He underwent a debulking surgical resection and pathological diagnosis was recurrent disease. During the surgery, tumor tissues were also collected from the enhancing and non-enhancing areas for a scRNAseq analysis to investigate the tumor microenvironment of these radiographically divergent areas. The scRNAseq analysis reveals a plethora of immune cells, suggesting that the increased mass observed on MRI may be partially a result of immune cell infiltration. The patient continued to receive immunotherapy after a short course of palliative radiation and remained free of disease progression for at least 12 months after the last surgery, suggesting a sustained response to immunotherapy. The scRNAseq analysis indicated that the radiological progression was in large part due to immune cell infiltrate and continued immunotherapy led to a positive clinical outcome in a patient who would have otherwise been admitted to hospice care with halting of immunotherapy. Our study demonstrates the potential of scRNAseq analyses in understanding the tumor microenvironment, which may assist the clinical decision-making process for challenging glioma cases following immunotherapy.

Recently, the investor overreaction catches the attention of the academicians and practitioners. The topic comes under the limelight of academicians and policymakers. This study, therefore, addresses investor overreaction and its relationship with the global financial crisis for the period of 2004–15. The study used stratified random sampling technique; equal allocation method of Krejcie and Morgan. By adopting the methodology of Debondt and Thaler, the study finds that there is highly significant overreaction (distinct reversal) in the stock market in the global-financial crisis period, which may attribute to the aggressive behavior of individual investors in the market. Overreaction has also been shown in the line graph shaded area which opposes the efficient market hypothesis and verifies the presence of a weak form of efficiency. Econometric tests are applied for robustness check that confirms weak form of efficiency in the PSX. The study has implications for both the investors and policymakers. This study is quintessential for those investors who have the aptitude to look introspectively and to evaluate their behavioral biases. Further, investors would learn to transmute behaviors and to build portfolios which will help them to stick to their long-term investment strategies and hence achieve their investment goals.

The NuRD complex subunit CHD4 is essential for fusion-positive rhabdomyosarcoma (FP-RMS) survival, but the mechanisms underlying this dependency are not understood. Here, a NuRD-specific CRISPR screen demonstrates that FP-RMS is particularly sensitive to CHD4 amongst the NuRD members. Mechanistically, NuRD complex containing CHD4 localizes to super-enhancers where CHD4 generates a chromatin architecture permissive for the binding of the tumor driver and fusion protein PAX3-FOXO1, allowing downstream transcription of its oncogenic program. Moreover, CHD4 depletion removes HDAC2 from the chromatin, leading to an increase and spread of histone acetylation, and prevents the positioning of RNA Polymerase 2 at promoters impeding transcription initiation. Strikingly, analysis of genome-wide cancer dependency databases identifies CHD4 as a general cancer vulnerability. Our findings describe CHD4, a classically defined repressor, as positive regulator of transcription and super-enhancer accessibility as well as establish this remodeler as an unexpected broad tumor susceptibility and promising drug target for cancer therapy.

Immunotherapeutic strategies targeting B-cell acute lymphoblastic leukemia (B-ALL) effectively induce remission; however, disease recurrence remains a challenge. Due to the potential for antigen loss, antigen diminution, lineage switch or development of a secondary or treatment-related malignancy, the phenotype and manifestation of subsequent leukemia may be elusive. We report on two patients with multiply relapsed/refractory B-ALL who, following chimeric antigen receptor T-cell therapy, developed myeloid malignancies. In the first case, a myeloid sarcoma developed in a patient with a history of myelodysplastic syndrome. In the second case, two distinct events occurred. The first event represented a donor-derived myelodysplastic syndrome with monosomy 7 in a patient with a prior hematopoietic stem cell transplantation. This patient went on to present with lineage switch of her original B-ALL to ambiguous lineage T/myeloid acute leukemia. With the rapidly evolving field of novel immunotherapeutic strategies, evaluation of relapse and/or subsequent neoplasms is becoming increasingly more complex. By virtue of these uniquely complex cases, we provide a framework for the evaluation of relapse or evolution of a subsequent malignancy following antigen-targeted immunotherapy.

Zakat is one of the main pillars of Islam. On one hand, it purifies the income of the wealthy people, on the other hand, it helps the needy people hence the social value of Islam and brotherhood is promoted. The niṣāb of few things are very clear as mentioned in aḥādīth in quit unambiguous manner just like nisāb of gold, silver, and livestock, etc. However in a situation when a person’s wealth is a mixture of a different kind of Amwāl-e-zakat and none of them reach to the limit of nisāb, especially in the case of gold, silver, and modern-day paper currency, in this case, whether gold, silver or paper shall be combined for the obligation of zakat or not? Imam Malik, Imam Abū Yūsuf and Imam Muhammad are of the view that the merger shall be based on its quantity/parts((ضم بالاجزاء. On the other hand, according to Imam Abū Ḥanifa, the merger shall be based on the price of gold and silver and the person should be considered nisāb holder if the price of the combined assets reaches the price of nisāb of silver. The above principle shall also be applied for Uzḥiyyah as well. Currently, due to the huge difference in the price of silver and gold, if we take the merger of different assets based on price, people who are not even secure from financial worries become nisāb holder and they have to pay zakat as well as Uzḥiyyah. In this paper, Zakat and its conditions are briefly defined, the issue of the combination of various niṣābs is elaborated, and the modern-day problems in light of the impact of the price of silver on the combination of niṣābs are discussed along with the recommendations.

This study examines the impact of corporate governance compliance and global financial crisis on stock liquidity of Pakistani listed non-financial firms. By using a sample of 170 firms for the period of 2007 to 2016, and employing fixed effect regression model, the study finds a positive relationship between stock liquidity and corporate governance compliance, stating that more complied firms with the given code of corporate governance have better stock liquidity. The relationship of the global financial crisis with stock liquidity is negative and statistically significant, which means that stock liquidity of Pakistani listed firms is affected negatively during the global financial crisis. Conclusively, findings of the study signify the role of corporate governance compliance and financial crisis in determining stock liquidity of Pakistani listed firms, which have implications for investment and policymaking in Pakistan.

Summary: Core regulatory transcription factors (CR TFs) establish enhancers with logical ordering during embryogenesis and development. Here we report that in fusion-positive rhabdomyosarcoma, a cancer of the muscle lineage, the chief oncogene PAX3-FOXO1 is driven by a translocated FOXO1 super enhancer (SE) restricted to a late stage of myogenesis. Using chromatin conformation capture techniques, we demonstrate that the extensive FOXO1 cis-regulatory domain interacts with PAX3. Furthermore, RNA sequencing and chromatin immunoprecipitation sequencing data in tumors bearing rare PAX translocations implicate enhancer miswiring across all fusion-positive tumors. HiChIP of H3K27ac showed connectivity between the FOXO1 SE, additional intra-domain enhancers, and the PAX3 promoter. We show that PAX3-FOXO1 transcription is diminished when this network of enhancers is ablated by CRISPR. Our data reveal a hijacked enhancer network that disrupts the stepwise CR TF logic of normal skeletal muscle development (PAX3 to MYOD to MYOG), replacing it with an “infinite loop” enhancer logic that locks rhabdomyosarcoma in an undifferentiated stage.