Effect of salinity stress and surfactant treatment with zinc and boron on morpho-physiological and biochemical indices of fenugreek (Trigonella foenum-graecum).

Micronutrient application has a crucial role in mitigating salinity stress in crop plants. This study was carried out to investigate the effect of zinc (Zn) and boron (B) as foliar applications on fenugreek growth and physiology under salt stress (0 and 120 mM). After 35 days of salt treatments, three levels of zinc (0, 50, and 100 ppm) and two levels of boron (0 and 2 ppm) were applied as a foliar application. Salinity significantly reduced root length (72.7%) and shoot length (33.9%), plant height (36%), leaf area (37%), root fresh weight (48%) and shoot fresh weight (75%), root dry weight (80%) and shoot dry weight (67%), photosynthetic pigments (78%), number of branches (50%), and seeds per pod (56%). Fenugreek's growth and physiology were improved by foliar spray of zinc and boron, which increased the length of the shoot (6%) and root length (2%), fresh root weight (18%), and dry root weight (8%), and chlorophyll a (1%), chlorophyll b (25%), total soluble protein content (3%), shoot calcium (9%) and potassium (5%) contents by significantly decreasing sodium ion (11%) content. Moreover, 100 ppm of Zn and 2 ppm of B enhanced the growth and physiology of fenugreek by reducing the effect of salt stress. Overall, boron and zinc foliar spray is suggested for improvement in fenugreek growth under salinity stress.

Mitigation effect of alpha-tocopherol and thermo-priming in Brassica napus L. under induced mercuric chloride stress.

Soil pollution with heavy metals has grown to be a big hassle, leading to the loss in farming production particularly in developing countries like Pakistan, where no proper channel is present for irrigation and extraction of these toxic heavy metals. The present study aims to ameliorate the damages caused by heavy metal ions (Hg-Mercury) on rapeseed (Brassica napus L.) via a growth regulator (α-tocopherol 150 mg/L) and thermopriming technique at 4 °C and 50 °C to maintain plant agronomical and physiological characteristics. In pot experiments, we designed total of 11 treatments viz.( T0 (control), T1 (Hg4ppm), T2 (Hg8ppm), T3 (Hg4ppm + 4 °C), T4 (Hg4ppm + 4 °C + tocopherol (150 m/L)), T5 (Hg4ppm + 50 °C), T6 (Hg4ppm + 50 °C + tocopherol (150 mg/L)), T7 (Hg8ppm + 4 °C), T8 (Hg8ppm + 4 °C + tocopherol (150 mg/L)), T9 (Hg8ppm + 50 °C), T10 (Hg8ppm + 50 °C + tocopherol (150 mg/L) the results revealed that chlorophyll content at p < 0.05 with growth regulator and antioxidant enzymes such as catalase, peroxidase, and malondialdehyde enhanced up to the maximum level at T5 = Hg4ppm + 50 °C (50 °C thermopriming under 4 ppm mercuric chloride stress), suggesting that high temperature initiate the antioxidant system to reduce photosystem damage. However, protein, proline, superoxide dismutase at p < 0.05, and carotenoid, soluble sugar, and ascorbate peroxidase were increased non-significantly (p > 0.05) 50 °C thermopriming under 8 ppm high mercuric chloride stress (T9 = Hg8ppm + 50 °C) representing the tolerance of selected specie by synthesizing osmolytes to resist oxidation mechanism. Furthermore, reduction in % MC (moisture content) is easily improved with foliar application of α-tocopherol and 50 °C thermopriming and 4 ppm heavy metal stress at T6 = Hg4ppm + 50 °C + α-tocopherol (150 mg/L), with a remarkable increase in plant vigor and germination energy. It has resulted that the inhibitory effect of only lower concentration (4 ppm) of heavy metal stress was ameliorated by exogenous application of α-tocopherol and thermopriming technique by synthesizing high levels of proline and antioxidant activities in maintaining seedling growth and development on heavy metal contaminated soil.

MicroRNA-29-mediated cross-talk between metabolic organs in the pathogenesis of diabetes mellitus and its complications: A narrative review.

Diabetes mellitus (DM) is a heterogeneous group of disorders characterized by hyperglycemia. Microribonucleic acids (microRNAs) are noncoding RNA molecules synthesized in the nucleus, modified, and exported to the extracellular environment to bind to their complementary target sequences. It regulates protein synthesis in the targeted cells by inhibiting translation or triggering the degradation of the target messenger. MicroRNA-29 is one of noncoding RNA that can be secreted by adipose tissue, hepatocytes, islet cells, and brain cells. The expression level of the microRNA-29 family in several metabolic organs is regulated by body weight, blood concentrations of inflammatory mediators, serum glucose levels, and smoking habits. Several experimental studies have demonstrated the effect of microRNA-29 on the expression of target genes involved in glucose metabolism, insulin synthesis and secretion, islet cell survival, and proliferation. These findings shed new light on the role of microRNA-29 in the pathogenesis of diabetes and its complications, which plays a vital role in developing appropriate therapies. Different molecular pathways have been proposed to explain how microRNA-29 promotes the development of diabetes and its complications. However, to the best of our knowledge, no published review article has summarized the molecular mechanism of microRNA-29-mediated initiation of DM and its complications. Therefore, this narrative review aims to summarize the role of microRNA-29-mediated cross-talk between metabolic organs in the pathogenesis of diabetes and its complications.

Programmed cell death pathways as targets for developing antifilarial drugs: Lessons from the recent findings.

More than half a century has passed since the introduction of the National Filariasis Control Program; however, as of 2023, lymphatic filariasis (LF) still prevails globally, particularly in the tropical and subtropical regions, posing a substantial challenge to the objective of worldwide elimination. LF is affecting human beings and its economically important livestock leading to a crucial contributor to morbidities and disabilities. The current scenario has been blowing up alarms of attention to develop potent therapeutics and strategies having efficiency against the adult stage of filarial nematodes. In this context, the exploration of a suitable drug target that ensures lethality to macro and microfilariae is now our first goal to achieve. Apoptosis has been the potential target across all three stages of filarial nematodes viz. oocytes, microfilariae (mf) and adults resulting in filarial death after receiving the signal from the reactive oxygen species (ROS) and executed through intrinsic and extrinsic pathways. Hence, it is considered a leading target for developing antifilarial drugs. Herein, we have shown the efficacy of several natural and synthetic compounds/nanoformulations in triggering the apoptotic death of filarial parasites with little or no toxicity to the host body system.

Genome-wide identification of CCO gene family in cucumber (Cucumis sativus) and its comparative analysis with A. thaliana.

Carotenoid cleavage oxygenase (CCO) is an enzyme capable of converting carotenoids into volatile, aromatic compounds and it plays an important role in the production of two significant plant hormones, i.e., abscisic acid (ABA) and strigolactone (SL). The cucumber plant genome has not been mined for genomewide identification of the CCO gene family. In the present study, we conducted a comprehensive genome-wide analysis to identify and thoroughly examine the CCO gene family within the genomic sequence of Cucumis sativus L. A Total of 10 CCO genes were identified and mostly localized in the cytoplasm and chloroplast. The CCO gene is divided into seven subfamilies i.e. 3 NCED, 3 CCD, and 1 CCD-like (CCDL) subfamily according to phylogenetic analysis. Cis-regulatory elements (CREs) analysis revealed the elements associated with growth and development as well as reactions to phytohormonal, biotic, and abiotic stress conditions. CCOs were involved in a variety of physiological and metabolic processes, according to Gene Ontology annotation. Additionally, 10 CCO genes were regulated by 84 miRNA. The CsCCO genes had substantial purifying selection acting upon them, according to the synteny block. In addition, RNAseq analysis indicated that CsCCO genes were expressed in response to phloem transportation and treatment of chitosan oligosaccharides. CsCCD7 and CsNCED2 showed the highest gene expression in response to the exogenous application of chitosan oligosaccharides to improve cold stress in cucumbers. We also found that these genes CsCCD4a and CsCCDL-a showed the highest expression in different plant organs with respect to phloem content. The cucumber CCO gene family was the subject of the first genome-wide report in this study, which may help us better understand cucumber CCO proteins and lay the groundwork for the gene family's future cloning and functional investigations.

Salivary microbiome in kidney diseases: A narrative review.

Many research has been conducted since the microbiota's discovery that have focused on the role it plays in health and disease. Microbiota can be divided into categories like intestinal, oral, respiratory, and skin microbiota based on the specific localized areas. To maintain homeostasis and control immunological response, the microbial populations live in symbiosis with the host. On the other hand, dysbiosis of the microbiota can cause diseases including kidney diseases and the deregulation of body functioning. We discuss the current understanding of how various kidney diseases are caused by the salivary microbiome (SM) in this overview. First, we review the studies on the salivary microbiota in diverse clinical situations. The importance of the SM in diabetic kidney disease, chronic kidney disease, membranous nephropathy, and IgA nephropathy is next highlighted. We conclude that the characteristics of the SM of patients with various kidney diseases have revealed the potential of salivary microbial markers as noninvasive tool for the detection of various kidney diseases.

Integrative artificial intelligence models for Australian coastal sediment lead prediction: An investigation of in-situ measurements and meteorological parameters effects.

Heavy metals (HMs) such as Lead (Pb) have played a vital role in increasing the sediments of the Australian bay's ecosystem. Several meteorological parameters (i.e., minimum, maximum and average temperature (Tmin, Tmax and TavgoC), rainfall (Rn mm) and their interactions with the other batch HMs, are hypothesized to have high impact for the decision-making strategies to minimize the impacts of Pb. Three feature selection (FS) algorithms namely the Boruta method, genetic algorithm (GA) and extreme gradient boosting (XGBoost) were investigated to select the highly important predictors for Pb concentration in the coastal bay sediments of Australia. These FS algorithms were statistically evaluated using principal component analysis (PCA) Biplot along with the correlation metrics describing the statistical characteristics that exist in the input and output parameter space of the models. To ensure a high accuracy attained by the applied predictive artificial intelligence (AI) models i.e., XGBoost, support vector machine (SVM) and random forest (RF), an auto-hyper-parameter tuning process using a Grid-search approach was also implemented. Cu, Ni, Ce, and Fe were selected by all the three applied FS algorithms whereas the Tavg and Rn inputs remained the essential parameters identified by GA and Boruta. The order of the FS outcome was XGBoost > GA > Boruta based on the applied statistical examination and the PCA Biplot results and the order of applied AI predictive models was XGBoost-SVM > GA-SVM > Boruta-SVM, where the SVM model remained at the top performance among the other statistical metrics. Based on the Taylor diagram for model evaluation, the RF model was reflected only marginally different so overall, the proposed integrative AI model provided an evidence a robust and reliable predictive technique used for coastal sediment Pb prediction.

Screening the elite chemotypes of Gloriosa superba L. in India for the production of anticancer colchicine: simultaneous microwave-assisted extraction and HPTLC studies.

BACKGROUND: Gloriosa superba L. (Colchicaceae) is a high-value medicinal plant indigenous to Africa and Southeast Asia. Its therapeutic benefits are well-established in traditional medicines including Ayurveda. It is well known for its natural bioactive compound colchicine which exhibits a wide range of pharmacological activities i.e. rheumatism, gout and was also introduced into clinical practices. The increasing demand as well as its illegal harvesting has brought this valuable plant under threatened category. METHODS: The present investigation describes a microwave assisted extraction (MAE) strategy coupled with a densitometric-high performance thin layer chromatographic (HPTLC) methodology for the analysis of colchicine from 32 different populations of G. superba. A Box-Behnken statistical design (3 level factor) has been employed to optimize MAE, in which power of microwave, time of irradiation, aqueous ethanol and pH were used as independent variables whereas colchicine was used as the dependent variables. Chromatography was carried out on Silica gel 60 F254 TLC plates with toluene: methanol, 85:15 (v/v) being used as solvent system. Densitometric measurement was performed at λ=254 nm following post-derivatization (10% methanolic sulphuric acid). RESULTS: Optimal conditions for extraction to obtain the maximum colchicine yield was found to be 7.51 mg g- 1 which was very close to be predicted response 7.48 mg g- 1 by maintaining microwave power (460 W), irradiation time (6.4 min), aqueous ethanol-30, pH -3. Colchicine content ranged between 2.12-7.58 mg g- 1 among 32 G. superba populations in which only three chemotypes viz. GS- 1, GS- 3, and GS- 2 collected from West Bengal and Sikkim, respectively exhibited maximum yield of colchicine. CONCLUSION: Therefore, this newly developed optimized MAE coupled with HPTLC densitometry methodology not only quantifies colchicine in order to identify elite chemotypes of G. superba, but it also encourages in selecting high yielding populations of the plants for industrial use and economic boost for the farmers. This validated, simple and reproducible HPTLC protocol is being used for the first time to estimate colchicine from natural populations of G. superba obtained from 32 different geographical regions of India.

Optimization of salicylic acid and chitosan treatment for bitter secoiridoid and xanthone glycosides production in shoot cultures of Swertia paniculata using response surface methodology and artificial neural network.

BACKGROUND: In this study, response surface methodology (RSM) and artificial neural network (ANN) was used to construct the predicted models of linear, quadratic and interactive effects of two independent variables viz. salicylic acid (SA) and chitosan (CS) for the production of amarogentin (I), swertiamarin (II) and mangiferin (III) from shoot cultures of Swertia paniculata Wall. These compounds are the major therapeutic metabolites in the Swertia plant, which have significant role and demand in the pharmaceutical industries. RESULTS: Present study highlighted that different concentrations of SA and CS elicitors substantially influenced the % yield of (I), (II) and (III) compounds in the shoot culture established on modified ½ MS medium (supplemented with 2.22 mM each of BA and KN and 2.54 mM NAA). In RSM, different response variables with linear, quadratic and 2 way interaction model were computed with five-factor-three level full factorial CCD. In ANN modelling, 13 runs of CCD matrix was divided into 3 subsets, with approximate 8:1:1 ratios to train, validate and test. The optimal enhancement of (I) (0.435%), (II) (4.987%) and (III) (4.357%) production was achieved in 14 days treatment in shoot cultures of S. paniculata elicited by 9 mM and 12 mg L- 1 concentrations (SA) and (CS). CONCLUSIONS: In optimization study, (I) show 0.170-0.435%; (II) display 1.020-4.987% and (III) upto 2.550-4.357% disparity with varied range of SA (1-20 mM) and CS (1-20 mg L- 1). Overall, optimization of elicitors to promote secoiridoid and xanthone glycoside production with ANN modeling (r2 = 100%) offered more significant results as compared to RSM (r2 = 99.8%).

The newly emerged COVID-19 disease: a systemic review.

Coronaviruses are large family-RNA viruses that belong to the order Nidovirales, family Coronaviridae, subfamily Coronavirinae. The novel COVID-19 infection, caused by a beta coronavirus called SARS-CoV-2, is a new outbreak that has been emerged in Wuhan, China in December 2019. The most common symptoms of COVID-19 are fever, cough, and dyspnea. As per the March 12, 2020, WHO report, more than 125,048 confirmed COVID-19 cases and over 4613 deaths have been identified in more than 117 countries. It is now regarded as a pandemic that seriously spread and attack the world. The primary means of transmission is person to person through droplets that occurred during coughing or sneezing, through personal contact (shaking hands), or by touching contaminated objects. So far, there is no effective therapy and vaccine available against this novel virus and therefore, only supportive care is used as the mainstay of management of patients with COVID-19. The mortality rate of COVID-19 is considerable. This work aimed to provide insight on the newly emerged COVID-19, in the hope to gain a better understanding on the general overview, epidemiology, transmission, clinical features, diagnosis, treatment, and clinical outcomes as well as the prevention and control of COVID-19.

An Immunoinformatic-Based In Silico Identification on the Creation of a Multiepitope-Based Vaccination Against the Nipah Virus.

The zoonotic viruses pose significant threats to public health. Nipah virus (NiV) is an emerging virus transmitted from bats to humans. The NiV causes severe encephalitis and acute respiratory distress syndrome, leading to high mortality rates, with fatality rates ranging from 40% to 75%. The first emergence of the disease was found in Malaysia in 1998-1999 and later in Bangladesh, Cambodia, Timor-Leste, Indonesia, Singapore, Papua New Guinea, Vietnam, Thailand, India, and other South and Southeast Asian nations. Currently, no specific vaccines or antiviral drugs are available. The potential advantages of epitope-based vaccines include their ability to elicit specific immune responses while minimizing potential side effects. The epitopes have been identified from the conserved region of viral proteins obtained from the UniProt database. The selection of conserved epitopes involves analyzing the genetic sequences of various viral strains. The present study identified two B cell epitopes, seven cytotoxic T lymphocyte (CTL) epitopes, and seven helper T lymphocyte (HTL) epitope interactions from the NiV proteomic inventory. The antigenic and physiological properties of retrieved protein were analyzed using online servers ToxinPred, VaxiJen v2.0, and AllerTOP. The final vaccine candidate has a total combined coverage range of 80.53%. The tertiary structure of the constructed vaccine was optimized, and its stability was confirmed with the help of molecular simulation. Molecular docking was performed to check the binding affinity and binding energy of the constructed vaccine with TLR-3 and TLR-5. Codon optimization was performed in the constructed vaccine within the Escherichia coli K12 strain, to eliminate the danger of codon bias. However, these findings must require further validation to assess their effectiveness and safety. The development of vaccines and therapeutic approaches for virus infection is an ongoing area of research, and it may take time before effective interventions are available for clinical use.

Tissue-specific variations of piperine in ten populations of Piper longum L.: bioactivities and toxicological profile.

P. longum L., one of the most significant species of the genus Piperaceae, is most frequently employed in Indian-Ayurvedic and other traditional medicinal-systems for treating a variety of illnesses. The alkaloid piperine, is the key phytoconstituent of the plant, primarily responsible for its' pharmacological-impacts. The aim of the study is to analyse the intra-specific variation in piperine content among different chemotypes (PL1 to PL 30) and identify high piperine yielding chemotype (elite-chemotype) collected from 10 different geographical regions of West Bengal by validated HPTLC chromatography method. The study also focused on the pharmacological-screening to better understand the antioxidant activity of the methanol extracts of P. longum by DPPH and ABTS radical-scavenging activity and genotoxic activity by Allium cepa root tip assay. It was found that the P. longum fruit chemotypes contain high amount piperine (highest 16.362 mg/g in chemotype PL9) than the stem and leaf chemotypes. Both DPPH and ABTS antioxidant assays revealed that P. longum showed moderate radical-scavenging activity and the highest activity was found in PL9 (fruit) chemotype with IC50 values of 124.2 ± 0.97 and 104 ± 0.78 µg/ml respectively. The A. cepa root tip assay showed no such significant genotoxic-effect and change in mitotic-index. The quick, reproducible, and validated HPTLC approach offers a useful tool for determining quantitative variations of piperine among P. longum chemotypes from different geographical-regions and also according to the different tissues and choose elite genotypes with high piperine production for continued propagation and commercialization for the pharmaceutical sector. Additionally, the plant's in-vitro antioxidant property and lack of genotoxicity directly supports its' widespread and long history of use as a medicinal and culinary plant.

Harnessing fluorescent carbon quantum dots from natural resource for advancing sweat latent fingerprint recognition with machine learning algorithms for enhanced human identification.

Nowadays, it is fascinating to engineer waste biomass into functional valuable nanomaterials. We investigate the production of hetero-atom doped carbon quantum dots (N-S@MCDs) to address the adaptability constraint in green precursors concerning the contents of the green precursors i.e., Tagetes erecta (marigold extract). The successful formation of N-S@MCDs as described has been validated by distinct analytical characterizations. As synthesized N-S@MCDs successfully incorporated on corn-starch powder, providing a nano-carbogenic fingerprint powder composition (N-S@MCDs/corn-starch phosphors). N-S@MCDs imparts astounding color-tunability which enables highly fluorescent fingerprint pattern developed on different non-porous surfaces along with immediate visual enhancement under UV-light, revealing a bright sharp fingerprint, along with long-time preservation of developed fingerprints. The creation and comparison of latent fingerprints (LFPs) are two key research in the recognition and detection of LFPs, respectively. In this work, developed fingerprints are regulated with an artificial intelligence program. The optimum sample has a very high degree of similarity with the standard control, as shown by the program's good matching score (86.94%) for the optimal sample. Hence, our results far outperform the benchmark attained using the conventional method, making the N-S@MCDs/corn-starch phosphors and the digital processing program suitable for use in real-world scenarios.

Systemic Analysis of Glyphosate Impact on Environment and Human Health.

With a growing global population, agricultural scientists are focusing on crop production management and the creation of new strategies for a higher agricultural output. However, the growth of undesirable plants besides the primary crop poses a significant challenge in agriculture, necessitating the massive application of herbicides to eradicate this problem. Several synthetic herbicides are widely utilized, with glyphosate emerging as a potential molecule for solving this emerging issue; however, it has several environmental and health consequences. Several weed species have evolved resistance to this herbicide, therefore lowering agricultural yield. The persistence of glyphosate residue in the environment, such as in water and soil systems, is due to the misuse of glyphosate in agricultural regions, which causes its percolation into groundwater via the vertical soil profile. As a result, it endangers many nontarget organisms existing in the natural environment, which comprises both soil and water. The current Review aims to provide a systemic analysis of glyphosate, its various effects on the environment, its subsequent impact on human health and animals, which will lead us toward a better understanding of the issues about herbicide usage and aid in managing it wisely, as in the near the future glyphosate market is aiming for a positive forecast until 2035.

Computational Frontiers in Aptamer-Based Nanomedicine for Precision Therapeutics: A Comprehensive Review.

In the rapidly evolving landscape of nanomedicine, aptamers have emerged as powerful molecular tools, demonstrating immense potential in targeted therapeutics, diagnostics, and drug delivery systems. This paper explores the computational features of aptamers in nanomedicine, highlighting their advantages over antibodies, including selectivity, low immunogenicity, and a simple production process. A comprehensive overview of the aptamer development process, specifically the Systematic Evolution of Ligands by Exponential Enrichment (SELEX) process, sheds light on the intricate methodologies behind aptamer selection. The historical evolution of aptamers and their diverse applications in nanomedicine are discussed, emphasizing their pivotal role in targeted drug delivery, precision medicine and therapeutics. Furthermore, we explore the integration of artificial intelligence (AI), machine learning (ML), Internet of Things (IoT), Internet of Medical Things (IoMT), and nanotechnology in aptameric development, illustrating how these cutting-edge technologies are revolutionizing the selection and optimization of aptamers for tailored biomedical applications. This paper also discusses challenges in computational methods for advancing aptamers, including reliable prediction models, extensive data analysis, and multiomics data incorporation. It also addresses ethical concerns and restrictions related to AI and IoT use in aptamer research. The paper examines progress in computer simulations for nanomedicine. By elucidating the importance of aptamers, understanding their superiority over antibodies, and exploring the historical context and challenges, this review serves as a valuable resource for researchers and practitioners aiming to harness the full potential of aptamers in the rapidly evolving field of nanomedicine.

Synthesis and characterization of iron oxide nanoparticles from Lawsonia inermis and its effect on the biodegradation of crude oil hydrocarbon.

Crude oil hydrocarbons are considered major environmental pollutants and pose a significant threat to the environment and humans due to having severe carcinogenic and mutagenic effects. Bioremediation is one of the practical and promising technology that can be applied to treat the hydrocarbon-polluted environment. In this present study, rhamnolipid biosurfactant (BS) produced by Pseudomonas aeruginosa PP4 and green synthesized iron nanoparticles (G-FeNPs) from Lawsonia inermis was used to evaluate the biodegradation efficiency (BE) of crude oil. The surface analysis of G-FeNPs was carried out by using FESEM and HRTEM to confirm the size and shape. Further, the average size of the G-FeNPs was observed around 10 nm by HRTEM analysis. The XRD and Raman spectra strongly confirm the presence of iron nanoparticles with their respective peaks. The BE (%) of mixed degradation system-V (PP4+BS+G-FeNPs) was obtained about 82%. FTIR spectrum confirms the presence of major functional constituents (C=O, -CH3, C-O, and OH) in the residual oil content. Overall, this study illustrates that integrated nano-based bioremediation could be an efficient approach for hydrocarbon-polluted environments. This study is the first attempt to evaluate the G-FeNPs with rhamnolipid biosurfactant on the biodegradation of crude oil.

Oestrogen receptor positive breast cancer and its embedded mechanism: breast cancer resistance to conventional drugs and related therapies, a review.

Traditional medication and alternative therapies have long been used to treat breast cancer. One of the main problems with current treatments is that there is an increase in drug resistance in the cancer cells owing to genetic differences such as mutational changes, epigenetic changes and miRNA (microRNA) alterations such as miR-1246, miR-298, miR-27b and miR-33a, along with epigenetic modifications, such as Histone3 acetylation and CCCTC-Binding Factor (CTCF) hypermethylation for drug resistance in breast cancer cell lines. Certain forms of conventional drug resistance have been linked to genetic changes in genes such as ABCB1, AKT, S100A8/A9, TAGLN2 and NPM. This review aims to explore the current approaches to counter breast cancer, the action mechanism, along with novel therapeutic methods endowing potential drug resistance. The investigation of novel therapeutic approaches sheds light on the phenomenon of drug resistance including genetic variations that impact distinct forms of oestrogen receptor (ER) cancer, genetic changes, epigenetics-reported resistance and their identification in patients. Long-term effective therapy for breast cancer includes selective oestrogen receptor modulators, selective oestrogen receptor degraders and genetic variations, such as mutations in nuclear genes, epigenetic modifications and miRNA alterations in target proteins. Novel research addressing combinational therapies including maytansine, photodynamic therapy, guajadiol, talazoparib, COX2 inhibitors and miRNA 1246 inhibitors have been developed to improve patient survival rates.

Integrated Electrochemical Oxidation and Biodegradation for Remediation of a Neonicotinoid Insecticide Pollutant.

A novel integrated electrochemical oxidation (EO) and bacterial degradation (BD) technique was employed for the remediation of the chloropyridinyl and chlorothiazolyl classes of neonicotinoid (NEO) insecticides in the environment. Imidacloprid (IM), clothianidin (CL), acetamiprid (AC), and thiamethoxam (TH) were chosen as the target NEOs. Pseudomonas oleovorans SA2, identified through 16S rRNA gene analysis, exhibited the potential for BD. In EO, for the selected NEOs, the total percentage of chemical oxygen demand (COD) was noted in a range of 58-69%, respectively. Subsequently, in the biodegradation of EO-treated NEOs (BEO) phase, a higher percentage (80%) of total organic carbon removal was achieved. The optimum concentration of NEOs was found to be 200 ppm (62%) for EO, while for BEO, the COD efficiency was increased up to 79%. Fourier-transform infrared spectroscopy confirms that the heterocyclic group and aromatic ring were degraded in the EO and further utilized by SA2. Gas chromatography-mass spectroscopy indicated up to 96% degradation of IM and other NEOs in BD (BEO) compared to that of EO (73%). New intermediate molecules such as silanediamine, 1,1-dimethyl-n,n'-diphenyl produced during the EO process served as carbon sources for bacterial growth and further mineralized. As a result, BEO enhanced the removal of NEOs with a higher efficiency of COD and a lower consumption of energy. The removal efficiency of the NEOs by the integrated approach was achieved in the order of AC > CL > IM > TH. This synergistic EO and BD approach holds promise for the efficient detoxification of NEOs from polluted environments.

Application of photoelectrochemical oxidation of wastewater used in the cooling tower water and its influence on microbial corrosion.

Background: Cooling towers are specialized heat exchanger devices in which air and water interact closely to cool the water's temperature. However, the cooling water contains organic nutrients that can cause microbial corrosion (MC) on the metal surfaces of the tower. This research explores the combined wastewater treatment approach using electrochemical-oxidation (EO), photo-oxidation (PO), and photoelectrochemical oxidation (PEO) to contain pollutants and prevent MC. Methods: The study employed electro-oxidation, a process involving direct current (DC) power supply, to degrade wastewater. MC studies were conducted using weight loss assessments, scanning electron microscopy (SEM), and x-ray diffraction (XRD). Results: After wastewater is subjected to electro-oxidation for 4 h, a notable decrease in pollutants was observed, with degradation efficiencies of 71, 75, and 96%, respectively. In the wastewater treated by PEO, microbial growth is restricted as the chemical oxygen demand decreases. Discussion: A metagenomics study revealed that bacteria present in the cooling tower water consists of 12% of Nitrospira genus and 22% of Fusobacterium genus. Conclusively, PEO serves as an effective method for treating wastewater, inhibiting microbial growth, degrading pollutants, and protecting metal from biocorrosion.