Unlocking the potential of oncology biomarkers: advancements in clinical theranostics.

INTRODUCTION: Cancer biomarkers have revolutionized the field of oncology by providing valuable insights into tumor changes and aiding in screening, diagnosis, prognosis, treatment prediction, and risk assessment. The emergence of "omic" technologies has enabled biomarkers to become reliable and accurate predictors of outcomes during cancer treatment. CONTENT: In this review, we highlight the clinical utility of biomarkers in cancer identification and motivate researchers to establish a personalized/precision approach in oncology. By extending a multidisciplinary technology-based approach, biomarkers offer an alternative to traditional techniques, fulfilling the goal of cancer therapeutics to find a needle in a haystack. SUMMARY AND OUTLOOK: We target different forms of cancer to establish a dynamic role of biomarkers in understanding the spectrum of malignancies and their biochemical and molecular characterization, emphasizing their prospective contribution to cancer screening. Biomarkers offer a promising avenue for the early detection of human cancers and the exploration of novel technologies to predict disease severity, facilitating maximum survival and minimum mortality rates. This review provides a comprehensive overview of the potential of biomarkers in oncology and highlights their prospects in advancing cancer diagnosis and treatment.

Long-Term Follow-Up of Abatacept, Post-Transplantation Cyclophosphamide, and Sirolimus-Based Haploidentical Transplantation in Younger Patients with Nonmalignant Diseases.

Haploidentical (haplo) hematopoietic cell transplantation (HCT) for nonmalignant disease (NMD) carries inherent challenges of both alloreactivity and graft failure. Building on promising results from pilot studies in which abatacept was combined with post-transplantation cyclophosphamide (PTCy) and sirolimus (AbaCyS) in younger NMD patients undergoing haplo-HCT, we present the long-term outcomes of this protocol. On the back of uniform disease-specific conditioning regimens containing antithymocyte globulin 4.5 mg/kg from day -9 to day -7, GVHD prophylaxis with AbaCyS consisted of abatacept administered on days 0, +5, +20, +35, and monthly until 180 days with PTCy and sirolimus. The patients were followed up with longitudinal assessment of immune reconstitution, growth, and reproductive development and quality of life (QoL) analyses. Among 40 patients (aplastic anemia, n = 24; hemoglobinopathies, n = 14; and primary immunodeficiencies, n = 2) with a median age of 10 years (range, 2 to 25 years), 95% achieved sustained engraftment. Post-transplantation hemophagocytic syndrome was detected in 3 patients, leading to graft failure in 2 cases. The incidence of acute graft-versus-host disease (GVHD) was 2.6%, and that of chronic GVHD (cGVHD) was 14.3%. Cytomegalovirus, adenovirus, and Epstein-Barr virus infections were observed in 45%, 5%, and 0% respectively. Rates of nonrelapse mortality, overall survival, event-free survival, and GVHD-free, event-free survival were 5%, 95%, 90%, and 82%, respectively, at a median follow-up of 4.6 years. Absence of cGVHD correlated with younger patient age and early sustained recovery of regulatory T cells and mature natural killer cells, which in turn was associated with improved QoL and lack of late infections. The AbaCyS protocol was associated with excellent long-term survival, with attenuation of both early and late alloreactivity in >80% of younger patients undergoing haplo-HCT for NMD. This study sheds light on predispositions to cGVHD and its impact on QoL, warranting further optimization of this approach.

LncRNA-mediated orchestrations of alternative splicing in the landscape of breast cancer.

Alternative splicing (AS) is a fundamental post-transcriptional process in eukaryotes, enabling a single gene to generate diverse mRNA transcripts, thereby enhancing protein variability. This process involves the excision of introns and the joining of exons in pre-mRNA(s) to form mature mRNA. The resulting mature mRNAs exhibit various combinations of exons, contributing to functional diversity. Dysregulation of AS can substantially modulate protein functions, impacting the onset and progression of numerous diseases, including cancer. Non-coding RNAs (ncRNAs) are distinct from protein-coding RNAs and consist of short and long types. Long non-coding RNAs (lncRNAs) play an important role in regulating several cellular processes, particularly alternative splicing, according to new research. This review provides insight into the latest discoveries concerning how lncRNAs influence alternative splicing within the realm of breast cancer. Additionally, it explores potential therapeutic strategies focused on targeting lncRNAs.

Potential role of p53 deregulation in modulating immune responses in human malignancies: A paradigm to develop immunotherapy.

The crucial role played by the oncogenic expression of TP53, stemming from mutation or amyloid formation, in various human malignancies has been extensively studied over the past two decades. Interestingly, the potential role of TP53 as a crucial player in modulating immune responses has provided new insight into the field of cancer biology. The loss of p53's transcriptional functions and/or the acquisition of tumorigenic properties can efficiently modulate the recruitment and functions of myeloid and lymphoid cells, ultimately leading to the evasion of immune responses in human tumors. Consequently, the oncogenic nature of the tumor suppressor p53 can dynamically alter the function of immune cells, providing support for tumor progression and metastasis. This review comprehensively explores the dual role of p53 as both the guardian of the genome and an oncogenic driver, especially in the context of regulation of autophagy, apoptosis, the tumor microenvironment, immune cells, innate immunity, and adaptive immune responses. Additionally, the focus of this review centers on how p53 status in the immune response can be harnessed for the development of tailored therapeutic strategies and their potential application in immunotherapy against human malignancies.

AI-enhanced adsorption modeling: Challenges, applications, and bibliographic analysis.

Inorganic and organic contaminants, such as fertilisers, heavy metals, and dyes, are the primary causes of water pollution. The field of artificial intelligence (AI) has received significant interest due to its capacity to address challenges across various fields. The use of AI techniques in water treatment and desalination has recently shown useful for optimising processes and dealing with the challenges of water pollution and scarcity. The utilization of AI in the water treatment industry is anticipated to result in a reduction in operational expenditures through the lowering of procedure costs and the optimisation of chemical utilization. The predictive capabilities of artificial intelligence models have accurately assessed the efficacy of different adsorbents in removing contaminants from wastewater. This article provides an overview of the various AI techniques and how they can be used in the adsorption of contaminants during the water treatment process. The reviewed publications were analysed for their diversity in journal type, publication year, research methodology, and initial study context. Citation network analysis, an objective method, and tools like VOSviewer are used to find these groups. The primary issues that need to be addressed include the availability and selection of data, low reproducibility, and little proof of uses in real water treatment. The provision of challenges is essential to ensure the prospective success of AI associated with technologies. The brief overview holds importance to everyone involved in the field of water, encompassing scientists, engineers, students, and stakeholders.

Machine learning approaches for the treatment of textile wastewater using sugarcane bagasse (Saccharum officinarum) biochar.

Most dyes present in wastewater from the textile industry exhibit toxicity and are resistant to biodegradation. Hence, the imperative arises for the environmentally significant elimination of textile dye by utilising agricultural waste. The achievement of this objective can be facilitated through the utilisation of the adsorption mechanism, which entails the passive absorption of pollutants using biochar. In this study, we compare the efficacy of the response surface methodology (RSM), the artificial neural network (ANN), the k-nearest neighbour (kNN), and adaptive neuro-fuzzy inference system (ANFIS) in removing crystal violet (CV) from wastewater. The characterisation of biochar is carried out by scanning electron microscope (SEM) and Fourier transform infrared (FTIR). The impacts of the solution pH, adsorbent dosage, initial dye concentration, and temperature were investigated using a variety of models (RSM, ANN, kNN, and ANFIS). The statistical analysis of errors was conducted, resulting in a maximum removal effectiveness of 97.46% under optimised settings. These conditions included an adsorbent dose of 0.4 mg, a pH of 5, a CV concentration of 40.1 mg/L, and a temperature of 20 °C. The ANN, RSM, kNN, and ANFIS models all achieved R2 0.9685, 0.9618, 0.9421, and 0.8823, respectively. Even though all models showed accuracy in predicting the removal of CV dye, it was observed that the ANN model exhibited greater accuracy compared to the other models.

Role of p53 transcription factor in determining the efficacy of telomerase inhibitors in cancer treatment.

AIM: Telomerase expression is unique to cancer cells, making it a promising target for therapy. However, a major drawback of telomerase inhibition is that it affects cancer cell proliferation only when telomeres shorten, creating a lag phase post-continuous drug treatment. Acute cytotoxicity of telomerase inhibitors is dependent on their ability to induce DNA damage. p53 senses DNA damage and is the primary effector required for sensitizing cells towards apoptosis. MAIN METHODS: Isogenic p53+/+ and p53-/- ovarian cancer cell lines were generated using the CRISPR/Cas9 system and the anti-cancer effect of telomerase inhibitors MST-312 and BIBR1532 were determined. Flow cytometry, real-time PCR, and western blot were performed to study cell cycle, apoptosis, and gene expression. KEY FINDINGS: We report that MST-312 exhibits p53-dependent cytotoxicity, while BIBR1532 exhibits p53-independent cytotoxicity. Colony-forming ability also confirms the p53-dependent effect of MST-312. Re-expression of p53 in p53-/- cells could rescue MST-312 sensitivity. In p53+/+ cells, MST-312 causes S phase arrest and activation of p53-dependent target genes like anti-apoptosis markers (Fas and Puma) and cell cycle markers (p21 and cyclinB). In p53-/- cells, MST-312 causes S/G2/M arrest. BIBR1532 induces S/G2/M phase cell cycle arrest irrespective of p53 status. This correlates with the expression of the DNA damage marker (γ-H2AX). Long-term continuous treatment with MST-312 or BIBR1532 results in p53-independent telomere shortening. SIGNIFICANCE: In summary, we demonstrate that acute anti-cancer effects of MST-312 are dependent on p53 expression. Hence, it is important to consider the p53 expression status in cancer cells when selecting and administering telomerase inhibitors.

Multifaceted role of mTOR (mammalian target of rapamycin) signaling pathway in human health and disease.

The mammalian target of rapamycin (mTOR) is a protein kinase that controls cellular metabolism, catabolism, immune responses, autophagy, survival, proliferation, and migration, to maintain cellular homeostasis. The mTOR signaling cascade consists of two distinct multi-subunit complexes named mTOR complex 1/2 (mTORC1/2). mTOR catalyzes the phosphorylation of several critical proteins like AKT, protein kinase C, insulin growth factor receptor (IGF-1R), 4E binding protein 1 (4E-BP1), ribosomal protein S6 kinase (S6K), transcription factor EB (TFEB), sterol-responsive element-binding proteins (SREBPs), Lipin-1, and Unc-51-like autophagy-activating kinases. mTOR signaling plays a central role in regulating translation, lipid synthesis, nucleotide synthesis, biogenesis of lysosomes, nutrient sensing, and growth factor signaling. The emerging pieces of evidence have revealed that the constitutive activation of the mTOR pathway due to mutations/amplification/deletion in either mTOR and its complexes (mTORC1 and mTORC2) or upstream targets is responsible for aging, neurological diseases, and human malignancies. Here, we provide the detailed structure of mTOR, its complexes, and the comprehensive role of upstream regulators, as well as downstream effectors of mTOR signaling cascades in the metabolism, biogenesis of biomolecules, immune responses, and autophagy. Additionally, we summarize the potential of long noncoding RNAs (lncRNAs) as an important modulator of mTOR signaling. Importantly, we have highlighted the potential of mTOR signaling in aging, neurological disorders, human cancers, cancer stem cells, and drug resistance. Here, we discuss the developments for the therapeutic targeting of mTOR signaling with improved anticancer efficacy for the benefit of cancer patients in clinics.

Integrating artificial neural networks and response surface methodology for predictive modeling and mechanistic insights into the detoxification of hazardous MB and CV dyes using Saccharum officinarum L. biomass.

The presence of dye pollutants in industrial wastewater poses significant environmental and health risks, necessitating effective treatment methods. The optimal adsorption treatment of methylene blue (MB) and crystal violet (CV) dye-simulated wastewater utilising Saccharum officinarum L presents a key challenge in the selection of appropriate modelling approaches. While RSM and ANN models are frequently used, there is a noticeable knowledge gap when it comes to evaluating their relative strengths and weaknesses in this context. The study compared the predictive abilities of response surface methodology (RSM) and artificial neural network (ANN) for the adsorption treatment of MB and CV dye-simulated wastewater using Saccharum officinarum L. The process experimental variables were modelled and predicted using a three-layer artificial neural network trained using the Levenberg-Marquard backpropagation algorithm and 30 central composite designs (CCD). The adsorption study used a specific mechanism, which led to noteworthy maximum removals of 98.3% and 98.2% for dyes (MB and CV), respectively. The RSM model achieved an impressive R2 of 0.9417, while the ANN model achieved 0.9236 in MB. Adsorption is commonly used to remove colour from many different materials. Saccharum officinarum L., a byproduct of sugarcane processing, has shown potential as an efficient and ecological adsorbent in this environment. The purpose of this study is to evaluate sugarcane bagasse's potential as an adsorbent for the removal of dyes MB and CV from industrial wastewater, providing a long-term strategy for reducing dye pollution. Due to its beneficial economic and environmental characteristics, the Saccharum officinarum L. adsorbent has prompted research into sustainable resources with low pollutant indices.

In-silico design, pharmacophore-based screening, and molecular docking studies reveal that benzimidazole-1,2,3-triazole hybrids as novel EGFR inhibitors targeting lung cancer.

Lung cancer is a complex and heterogeneous disease, which has been associated with various molecular alterations, including the overexpression and mutations of the epidermal growth factor receptor (EGFR). In this study, designed a library of 1843 benzimidazole-1,2,3-triazole hybrids and carried out pharmacophore-based screening to identify potential EGFR inhibitors. The 164 compounds were further evaluated using molecular docking and molecular dynamics simulations to understand the binding interactions between the compounds and the receptor. In-si-lico ADME and toxicity studies were also conducted to assess the drug-likeness and safety of the identified compounds. The results of this study indicate that benzimidazole-1,2,3-triazole hybrids BENZI-0660, BENZI-0125, BENZI-0279, BENZI-0415, BENZI-0437, and BENZI-1110 exhibit dock scores of -9.7, -9.6, -9.6, -9.6, -9.6, -9.6 while referencing molecule -7.9 kcal/mol for EGFR (PDB ID: 4HJO), respectively. The molecular docking and molecular dynamics simulations revealed that the identified compounds formed stable interactions with the active site of EGFR, indicating their potential as inhibitors. The in-silico ADME and toxicity studies showed that the compounds had favorable drug-likeness properties and low toxicity, further supporting their potential as therapeutic agents. Finally, performed DFT studies on the best-selected ligands to gain further insights into their electronic properties. The findings of this study provide important insights into the potential of benzimidazole-1,2,3-triazole hybrids as promising EGFR inhibitors for the treatment of lung cancer. This research opens up a new avenue for the discovery and development of potent and selective EGFR inhibitors for the treatment of lung cancer.Communicated by Ramaswamy H. Sarma.

In-silico identification of small molecule benzofuran-1,2,3-triazole hybrids as potential inhibitors targeting EGFR in lung cancer via ligand-based pharmacophore modeling and molecular docking studies.

Lung cancer is one of the most common and deadly types of cancer worldwide, and the epidermal growth factor receptor (EGFR) has emerged as a promising therapeutic target for the treatment of this disease. In this study, we designed a library of 1840 benzofuran-1,2,3-triazole hybrids and conducted pharmacophore-based screening to identify potential EGFR inhibitors. The 20 identified compounds were further evaluated using molecular docking and molecular dynamics simulations to understand their binding interactions with the EGFR receptor. In-silico ADME and toxicity studies were also performed to assess their drug-likeness and safety profiles. The results of this study showed the benzofuran-1,2,3-triazole hybrids BENZ-0454, BENZ-0143, BENZ-1292, BENZ-0335, BENZ-0332, and BENZ-1070 dock score of - 10.2, - 10, - 9.9, - 9.8, - 9.7, - 9.6, while reference molecule - 7.9 kcal/mol for EGFR (PDB ID: 4HJO) respectively. The molecular docking and molecular dynamics simulations revealed that the identified compounds formed stable interactions with the active site of the receptor, indicating their potential as inhibitors. The in-silico ADME and toxicity studies suggested that the compounds had good pharmacokinetic and safety profiles, further supporting their potential as therapeutic agents. Finally, performed DFT studies on the best-selected ligands to gain further insights into their electronic properties. The findings of this study provide important insights into the potential of benzofuran-1,2,3-triazole hybrids as promising EGFR inhibitors for the treatment of lung cancer. Overall, this study provides a valuable starting point for the development of novel EGFR inhibitors with improved efficacy and safety profiles. Supplementary Information: The online version contains supplementary material available at 10.1007/s40203-023-00157-1.

The emerging regulatory roles of non-coding RNAs associated with glucose metabolism in breast cancer.

Altered energy metabolism is one of the hallmarks of tumorigenesis and essential for fulfilling the high demand for metabolic energy in a tumor through accelerating glycolysis and reprogramming the glycolysis metabolism through the Warburg effect. The dysregulated glucose metabolic pathways are coordinated not only by proteins coding genes but also by non-coding RNAs (ncRNAs) during the initiation and cancer progression. The ncRNAs are responsible for regulating numerous cellular processes under developmental and pathological conditions. Recent studies have shown that various ncRNAs such as microRNAs, circular RNAs, and long noncoding RNAs are extensively involved in rewriting glucose metabolism in human cancers. In this review, we demonstrated the role of ncRNAs in the progression of breast cancer with a focus on outlining the aberrant expression of glucose metabolic pathways. Moreover, we have discussed the existing and probable future applications of ncRNAs to regulate energy pathways along with their importance in the prognosis, diagnosis, and future therapeutics for human breast carcinoma.

Introducing machine learning model to response surface methodology for biosorption of methylene blue dye using Triticum aestivum biomass.

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.

Design and Synthesis of Thiazole Scaffold-Based Small Molecules as Anticancer Agents Targeting the Human Lactate Dehydrogenase A Enzyme.

A new series of thiazole central scaffold-based small molecules of hLDHA inhibitors were designed using an in silico approach. Molecular docking analysis of designed molecules with hLDHA (PDB ID: 1I10) demonstrates that Ala 29, Val 30, Arg 98, Gln 99, Gly 96, and Thr 94 possessed strong interaction with the compounds. Compounds 8a, 8b, and 8d showed good binding affinity (-8.1 to -8.8 kcal/mol), whereas an additional interaction of NO2 at the ortho position in compounds 8c with Gln 99 through hydrogen bonding enhanced the affinity to -9.8 kcal/mol. Selected high-scored compounds were synthesized and screened for hLDHA inhibitory activities and in vitro anticancer activity in six cancer cell lines. Biochemical enzyme inhibition assays showed the highest hLDHA inhibitory activity observed with compounds 8b, 8c, and 8l. Compounds 8b, 8c, 8j, 8l, and 8m depicted significant anticancer activities, exhibiting IC50 values in the range of 1.65-8.60 µM in HeLa and SiHa cervical cancer cell lines. Compounds 8j and 8m exhibited notable anticancer activity with IC50 values of 7.90 and 5.15 µM, respectively, in liver cancer cells (HepG2). Interestingly, compounds 8j and 8m did not induce noticeable toxicity in the human embryonic kidney cells (HEK293). Insilico absorption, distribution, metabolism, and excretion profiling demonstrates that the compounds possess drug-likeness, and results may pave the way for the development of novel thiazole-based biologically active small molecules for therapeutics.

Investigating the Biochemical Responses in Wheat Cultivars Exposed to Thermal Power Plant Emission.

The current study aimed to assess how high concentrations of ozone (O3) and suspended particulate matter (SPM) alter biochemical properties of high yielding wheat cultivars (i.e., HD3086 and HD2967) grown under 10 km radius in 8 villages, located around Thermal Power Plant (TPP), Auraiya, Uttar Pradesh, India. Significant foliar damage was brought on by O3 and SPM exposure in both wheat cultivars and noted for consecutive 2 years as per emission patterns, air movement and biochemical defense capabilities. The detected air pollutants at the chosen experimental site ranged from 34 to 46 ppb O3 and 139-189 µg/m3 SPM. Range of biochemical parameter for both cultivars are as pH 6.6-7.1, relative water content (RWC) 44-62%, chlorophyll 0.23-0.35 mg/g, ascorbic acid (AA) 54-68 mg/g and air pollution tolerance index (APTI) 47-72. It has been observed that SPM deposition had a meaningful impact (P-value = 0.05) on the chlorophyll, pH, RWC and APTI.

Long non-coding RNAs: Fundamental regulators and emerging targets of cancer stem cells.

Cancer is one of the leading causes of death worldwide, primarily due to the dearth of efficient therapies that result in long-lasting remission. This is especially true in cases of metastatic cancer where drug resistance causes the disease to recur after treatment. One of the factors contributing to drug resistance, metastasis, and aggressiveness of the cancer is cancer stem cells (CSCs) or tumor-initiating cells. As a result, CSCs have emerged as a potential target for drug development. In the present review, we have examined and highlighted the lncRNAs with their regulatory functions specific to CSCs. Moreover, we have discussed the difficulties and various methods involved in identifying lncRNAs that can play a particular role in regulating and maintaining CSCs. Interestingly, this review only focuses on those lncRNAs with strong functional evidence for CSC specificity and the mechanistic role that allows them to be CSC regulators and be the focus of CSC-specific drug development.

Neo-vascularization-based therapeutic perspectives in advanced ovarian cancer.

The process of angiogenesis is well described for its potential role in the development of normal ovaries, and physiological functions as well as in the initiation, progression, and metastasis of ovarian cancer (OC). In advanced stages of OC, cancer cells spread outside the ovary to the pelvic, abdomen, lung, or multiple secondary sites. This seriously limits the efficacy of therapeutic options contributing to fatal clinical outcomes. Notably, a variety of angiogenic effectors are produced by the tumor cells to initiate angiogenic processes leading to the development of new blood vessels, which provide essential resources for tumor survival, dissemination, and dormant micro-metastasis of tumor cells. Multiple proangiogenic effectors and their signaling axis have been discovered and functionally characterized for potential clinical utility in OC. In this review, we have provided the current updates on classical and emerging proangiogenic effectors, their signaling axis, and the immune microenvironment contributing to the pathogenesis of OC. Moreover, we have comprehensively reviewed and discussed the significance of the preclinical strategies, drug repurposing, and clinical trials targeting the angiogenic processes that hold promising perspectives for the better management of patients with OC.

Use of artificial intelligence for optimizing biosorption of textile wastewater using agricultural waste.

Most of the dyes are toxic and non-biodegradable in textile industry wastewaters. Therefore, removal of textile dye using agriculture waste becomes crucial for the environment. This can be accomplished by the biosorption process which is the passive uptake of pollutants by agricultural waste. In this study, Response Surface Methodology (RSM), Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) were used to obtain optimum conditions for Methylene Blue (MB) removal using sugarcane bagasse and peanut hulls as low-cost agricultural waste. The experimental design was carried out to study the effect of temperature, pH, biosorbent amount and dye concentration. The maximum MB dye removal considering the effect of total dissolved solids from aqueous solutions of 74.49% and 67.99% by sugarcane bagasse and peanut hulls, respectively. The models specify that they could predict biosorption with high accuracy having R2-value above 0.9. Statistical studies for RSM, ANFIS and ANN models were compared. Further, the models were optimized for maximum dye removal was at 1.21 g of biosorbent, pH 5.24, 31.24 mg/L MB concentration, 22.29°C of dye solution using sugarcane bagasse and at 1.37 g of biosorbent, pH 5.77, 36.7 mg/L MB concentration, 26.8°C of dye solution using peanut hulls. Additionally, Fourier Transform Infra-Red (FTIR) spectral analysis was also carried out to confirm the biosorption.

Targeting Virus-Induced Reprogrammed Cell Metabolism via Glycolytic Inhibitors: An Effective Therapeutic Approach Against SARS-CoV-2.

Reprogrammed cell metabolism has been observed in a wide range of virally infected cells. Viruses do not have their metabolism; they rely on the cellular metabolism of the host to ensure the energy and macromolecules requirement for replication. Like other viruses, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) does not own its metabolism, but virus infected cells adopt aberrant cell metabolism. Infected viral use the energy and macromolecules to make their own copies; to do so, they need to increase the rate of metabolism to ensure the requirement of macromolecules. In contrast, the cellular metabolism of noninfected cells is more plastic than infected cells. Therefore, it is essential to examine the virus infection in the context of metabolic alterations of host cells. A novel therapeutic approach is urgently required to treat highly infectious COVID-19 disease and its pathogenesis. Interference of glucose metabolism might be a promising strategy to determine COVID-19 treatment options. Based on the recent research, this mini-review aims to understand the impact of reprogrammed cell metabolism in COVID-19 pathogenesis and explores the potential of targeting metabolic pathways with small molecules as a new strategy for the development of a novel drug to treat COVID-19 disease. This type of research line provides new hope in the development of antiviral drugs by targeting hijacked cell metabolism in case of viral diseases and also in COVID-19.

A practical evaluation on integrated role of biochar and nanomaterials in soil remediation processes.

Soil decontamination and restoration continue to be a key environmental concern around the globe. The degradation of soil resources due to the presence of potentially toxic elements (PTEs) has a substantial influence on agricultural production, food security, and human well-being, and as a result, urgent action is required. PTEs pollution is not a threat to the agroecosystems but also a serious concern to human health; thereby, it needs to be addressed timely and effectively. Hence, the development of improved and cost-effective procedures to remove PTEs from polluted soils is imperative. With this context in mind, current review is designed to distinctly envisage the PTEs removal potential by the single and binary applications of biochar (BC) and nanomaterials (NMs).2 Recently, BC, a product of high-temperature biomass pyrolysis with high specific surface area, porosity, and distinctive physical and chemical properties has become one of the most used and economic adsorbent materials. Also, biochar's application has generated interest in a variety of fields and environments as a modern approach against the era of urbanization, industrialization, and climate change. Likewise, several NMs including metals and their oxides, carbon materials, zeolites, and bimetallic-based NMs have been documented as having the potential to remediate PTEs-polluted environments. However, both techniques have their own set of advantages and disadvantages, therefore combining them can be a more effective strategy to address the growing concern over the rapid accumulation and release of PTEs into the environment.