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The portable X-ray fluorescence (pXRF) spectrometry has been very useful for the characterization of different earth materials, and its application for foliar analysis is really promising. The performance of pXRF for foliar analysis depends on several factors such as concentration of the elements, fluorescence yield which is influenced by atomic number, spectral interference, and water content. Mn is one of the elements that present a prominent fluorescence peak. In this sense, it was hypothesized that pXRF can directly determine the Mn concentration on foliar samples, even when used on intact leaves (fresh or dry) being a useful tool for agronomic and environmental purposes. Thus, the objective was to assess the performance of a pXRF to determine Mn concentration in two different foliar datasets from Brazil/South America and Mali/Africa. In the Brazilian dataset, leaves from eight crops (common bean, castor plant, coffee, eucalyptus, guava tree, maize, mango, and soybean) were scanned via pXRF at the following conditions: intact and fresh leaves, intact and dry leaves, and powdered samples). In the Malian dataset, powdered samples from cotton and maize were analyzed via pXRF. For comparison, Mn concentration was also determined after nitro-perchloric digestion followed by quantification via inductively coupled plasma optical emission spectroscopy (ICP-OES). After descriptive statistics, linear regressions were performed for all sample preparation conditions in both datasets, using Mn concentrations obtained through pXRF and the acid digestion method. The data quality level of all linear regressions was considered quantitative with high R (0.93 to 0.98) and R² (0.87 to 0.96) values. The direct analysis of Mn via pXRF on intact and fresh leaves yielded R of 0.93, R² of 0.87, and a low relative standard deviation (< 10%). The manufactured pXRF calibration used in this work allowed an accurate direct Mn determination in plant leaves. Considering the importance of Mn as a plant micronutrient and its potential toxicity depending on soil redox conditions, the fast, in situ, non-destructive, and eco-friendly determination via pXRF has a tremendous agronomic and environmental application worldwide.

Surface-enhanced Raman spectroscopy (SERS) is a highly sensitive analytical technique that captures vibrational spectra of analytes adsorbed to rough coin metal surfaces with remarkable signal intensities. However, its wider application is limited by challenges in substrate range, quantification, and the disposable nature of SERS substrates partly due to irreversible analyte adsorption-commonly referred to as the 'memory effect'. Overcoming these limitations and achieving real-time analysis in flow-through systems remains a key challenge for the advancement of SERS. This study presents a SERS flow cell incorporating an Ag-based SERS substrate and a Pt counter-electrode, enabling the investigation of how electrochemical methods can address existing challenges. Our approach demonstrates that signal intensities can be both enhanced and spectroelectrochemically modified. Additionally, the combination of constant solvent flow and electrochemical potentials enhances the longevity of the SERS substrate, facilitating multianalyte measurements while mitigating the memory effect. Key parameters have been systematically studied, including SERS substrate materials (silver and copper), solvents, buffers, supporting electrolytes, and electrochemical protocols. We achieved consistent and reproducible electrochemical tuning of SERS signals by using halogen-free electrolytes in polar solvents commonly used in techniques like HPLC. The versatility of the system was validated through the analysis of several model compounds and the sequential detection of multiple analytes. We also successfully applied the system to detect and characterise contaminants and pharmaceuticals, highlighting its potential for a wide range of analytical applications.

Cancer remains the leading cause of death worldwide, with the Globocan 2022 study reporting an estimated 9.7 million cancer deaths. Without the selectivity built for tumour cells, chemotherapeutic agents could be toxic to non-cancerous cells. Administration of such non-selective cytotoxic compounds causes severe side effects and could lead to death. Improved cancer treatments are required to overcome the limitations of the current cancer treatment. The potential of thiazolidinedione derivatives as anticancer drugs has recently drawn attention, despite their primary use as insulin sensitizers in the treatment of type 2 diabetes. The ability of thiazolidinedione derivatives to alter important molecular pathways implicated in carcinogenesis, such as cell proliferation, apoptosis, angiogenesis, Raf kinase, EGFR and HER-2 kinases, HDAC, COX-2 enzyme and metastasis, is highlighted in this review, which examines the growing relevance of these compounds in cancer treatment. Thiazolidinediones have anti-inflammatory, antioxidant, and antiproliferative properties in a variety of cancer types, including breast, colon, and prostate cancers, via activating the peroxisome proliferator-activated gamma receptor (PPARγ). In addition to examining the safety profile and difficulties in clinical translation, the paper looks at preclinical and clinical research that points to these medicines potential to improve the effectiveness of immunotherapy and chemotherapy. This review highlights the encouraging therapeutic possibilities and structure-activity relationship insight of TZDs for their anticancer activity and highlights the molecular level facets of the 'glitazone' pharmacophore for its anticancer activity.

Genetic variations in the lipoprotein lipase (LPL) gene including the HindIII polymorphism (rs320) have been reported to modify fat metabolism, adiposity, and body weight. However, little attention has been given to the African population. The present study aimed to investigate the relationship between the rs320 gene polymorphism and a number of metabolic and anthropometric parameters in a sample of the Nigerian population. We recruited 236 participants for the study. The participants were required to sign informed consent forms after which information related to their calorie intake and utilization as well as anthropometric measurements were recorded. Plasma metabolic parameters were subsequently determined using an autoanalyzer. Genotyping for HindIII polymorphism was performed using the PCR-RFLP method. The frequencies (n) of T and G alleles were 0.841 (397) and 0.158 (75), while the frequencies (n) of TT, TG, and GG were 0.691(163), 0.301(71), and 0.01(2), respectively. The population was not in Hardy-Weinberg equilibrium (χ² = 3.717, df = 1, p = 0.841). The anthropometric parameters, the fasting blood glucose, and low-density lipoprotein cholesterol showed no association with the alleles, while plasma high-density lipoprotein cholesterol and total cholesterol were significantly higher among the G allele carriers. However, triglyceride and total protein were significantly higher among the non-G allele carriers. The LPL HindIII gene polymorphism is associated with changes in plasma lipid profile in a sample of the Nigerian population.

Cancer remains one of the leading causes of death worldwide, with the rising incidence of breast cancer being a significant public health concern. Poly (ADP-ribose) polymerase-1 (PARP-1) has emerged as a promising therapeutic target for breast cancer treatment due to its crucial role in DNA repair. This study aimed to discover novel, targeted, and non-toxic PARP-1 inhibitors using an integrated approach that combines machine learning-based screening, molecular docking simulations, and quantum mechanical calculations. We trained a widely used machine learning models, Random Forest, using bioactivity data from known PARP-1 inhibitors. After evaluating the performance, it was used to screen an FDA-approved drug library, successfully identifying Atazanavir, Brexpiprazole, Raltegravir, and Nisoldipine as potential PARP-1 inhibitors. These compounds were further validated through molecular docking and all-atom molecular dynamics simulations, highlighting their potential for breast cancer therapy. The binding free energies indicated that Atazanavir at - 41.86 kJ/mol and Brexpiprazole at - 45.44 kJ/mol exhibited superior binding affinity compared to the control drug at - 30.42 kJ/mol, highlighting their promise as candidates for breast cancer therapy. Subsequent optimized geometries and electron density mappings of the two molecular structures revealed a Gibbs free energy of - 2334.610 Ha for the first molecule and - 1682.278316 Ha for the second, confirming enhanced stability compared to the standard drug. This study not only highlights the efficacy of machine learning in drug discovery but also underscores the importance of quantum mechanics in validating molecular stability, setting a robust foundation for future pharmacological explorations. Additionally, this approach could revolutionize the drug repurposing process by significantly reducing the time and cost associated with traditional drug development methods. Our results establish a promising basis for subsequent research aimed at optimizing these PARP-1 inhibitors for clinical use, potentially offering more effective treatment options for breast cancer patients.

The Niger River is critical in providing water for the socio-economic activities and development of Bamako city. However, predicting future water supply and demand is challenging. Therefore, an approach capable of analysing water availability is necessary. This study aims to use the Water Evaluation And Planning (WEAP) software to forecast water availability, treatment scenarios, and the reuse of treated wastewater by 2030. Evaluating the future pollution of the river in Bamako, the simulated flow, Dissolved Oxygen (DO), and Biochemical Oxygen Demand (BOD) along the Niger River from 2017 to 2030 were compared with 2016 values. Notwithstanding the elevated water demand resulting from the accelerated urbanisation and industrialisation, the entire length of the Niger River in Bamako would be contaminated. Even though the water tends to improve downstream, a BOD concentration of 9.83 mg/l will exceed the requirement of 5 mg/l set by the European Commission's recommendation for surface water quality. The high BOD downstream indicates the river's weakening capacity for self-purification and points to a 0% water demand coverage by 2030. Contrary to irrigation needs, the river cannot be used for domestic purposes due to pollution. Establishing wastewater treatment systems will improve the reuse of treated wastewater and reduce pollution levels in the Niger River by 86%.

Illicit fentanyl and fentanyl analogs are a growing concern in the United States as opioid related deaths rise. Given that fentanyl analogs are readily obtained by modifying the structure of fentanyl, illicit fentanyl analogs appearing on the black market often contain similar structures, making analogue differentiation and identification difficult. Thus, obtaining both precursor and product ion data during analysis is becoming increasingly valuable in fentanyl analog characterization. In this paper, we provide GC column retention time, precursor, and product ion mass spectrum data for 74 fentanyl analogs that were analyzed using atmospheric pressure chemical ionization-gas chromatography-mass spectrometry (APCI-GC-MS) utilizing a triple quadrupole mass analyzer. During analysis, precursor ions underwent collision induced dissociation (CID) by increasing the collision energy (10, 20, 30, 40, and 50 V) throughout a single run. Data reveal that APCI readily produces product ions of the piperidine and N-alkyl chain but rarely provides data on the acyl group. Furthermore, fentanyl analogs with greater substitution at the N-alkyl chain demonstrate a greater preference for dissociation at the N-αC and αC-βC bond, while greater substitution at the amide group leads to fragmentation at the N-C4 bond.

Recently, the present authors proposed a three-dimensional computational model for the transit of suspended cancer cells through a microchannel (Wang et al. in Biomech Model Mechanobiol 22: 1129-1143, 2023). The cell model takes into account the three major subcellular components: A viscoelastic membrane that represents the lipid bilayer supported by the underlying cell cortex, a viscous cytoplasm, and a nucleus modelled as a smaller microcapsule. The cell deformation and its interaction with the surrounding fluid were solved by an immersed boundary-lattice Boltzmann method. The computational model accurately recovered the transient flow-induced deformation of the human leukaemia HL-60 cells in a constricted channel. However, as a general modelling framework, its applicability to other cell types in different flow geometries remains unknown, due to the lack of quantitative experimental data. In this study, we conduct experiments of the transit of human prostate cancer (PC-3) and leukaemia (K-562) cells, which represent solid and liquid tumour cell lines, respectively, through two distinct microchannel geometries, each dominated by shear and extension flow. We find that the two cell lines have qualitatively similar flow-induced dynamics. Comparisons between experiments and numerical simulations suggest that our model can accurately predict the transient cell deformation in both geometries, and that it can serve as a general modelling framework for the dynamics of suspended cancer cells in microchannels.

This research reports heavy metal pollution in riverine sediments from River Kabul, Pakistan, which could endanger human health and ecology via the food web. The results revealed a substantial special variation in the average contents (mg/kg) of chromium (Cr), manganese (Mn), cobalt (Co), nickel (Ni), copper (Cu), zinc (Zn), cadmium (Cd), mercury (Hg), lead (Pb), iron (Fe), and aluminum (Al) in riverine sediments, in the order of Fe (20,234.51) > Al (17,550.86) > Mn (375.45) > Zn (149.08) > Ni (89.11) > Cr (83.36) > Pb (45.29) > Cu (19.86) > Cd (7.48) > Co (6.28) > Hg (0.81). Among the heavy metals, Cd exhibited the highest degree of pollution along the river, followed by Hg > Ni > Zn > Pb > Al > Cr > Mn > Fe > Cu > Co. The overall contamination factor (CF) values for the sum of heavy metals were highest at monitoring site S-9, followed by S-8 > S-10 > S-6 > S-5 > S-7 > S-1 > S-4 > S-12 > S-3 > S-2 > S-1 with pollution load index (PLI) > 1, whereas the geo-accumulation index (Igeo) values of Cd and Hg fluctuated between Levels 3, 4, and 6, suggesting moderate to extreme pollution in the river. The correlation statistics determined the fate and distribution of heavy metals by establishing significant positive correlations between the specific metals of bounded sediments. The cluster analysis separates the correlated metals into Groups A and B, and Groups 1 and 2. While the principal component analysis evaluates the qualitative behavior of clustering by discerning industrial, agrochemicals, mining, and domestic wastewater discharges, leakages of lubricants along with multiple geogenic inputs, erosion of mafic and ultramafic rocks, and minimal atmospheric deposition are all potential sources of Cr, Mn, Co, Ni, Cu, Zn, Cd, Hg, Pb, Fe, and Al contamination. In terms of risk, the contaminations of Mn, Co, Cu, Zn, and Pb in riverine sediments were 85, 100, 100, 17, and 11%, respectively, representing a rare biological influence because their value is less than their corresponding threshold effect concentrations (TECs), whereas the levels of Mn, Ni, Cd, and Hg were above their probable effect concentrations (PECs) of 100, 100, 81, and 52%, respectively, representing prominent adverse biological influence. Based on consensus-based TECs and PECs, the contamination levels of Cr, Mn, Zn, Cd, Hg, and Pb were 100, 85, 83, 19, 48, and 90%, respectively, indicating occasionally exhibited adverse biological effects on the riverine population. Besides, the overall potential ecological risk index (PERI) of Cd and Hg, in particular, exhibited the maximum pollution level ( $E_{\text{r}}^{\text{i}}$ ≥ 320), suggesting a very high potential ecological risk in the drainage that requires special attention from pollution control authorities.