M4X3 MXenes: Application in Energy Storage Devices.

MXene has garnered widespread recognition in the scientific community due to its remarkable properties, including excellent thermal stability, high conductivity, good hydrophilicity and dispersibility, easy processability, tunable surface properties, and admirable flexibility. MXenes have been categorized into different families based on the number of M and X layers in Mn+1Xn, such as M2X, M3X2, M4X3, and, recently, M5X4. Among these families, M2X and M3X2, particularly Ti3C2, have been greatly explored while limited studies have been given to M5X4 MXene synthesis. Meanwhile, studies on the M4X3 MXene family have developed recently, hence, demanding a compilation of evaluated studies. Herein, this review provides a systematic overview of the latest advancements in M4X3 MXenes, focusing on their properties and applications in energy storage devices. The objective of this review is to provide guidance to researchers on fostering M4X3 MXene-based nanomaterials, not only for energy storage devices but also for broader applications.

Design and Fabrication of a Biomimetic Smart Material for Electrochemical Detection of Carbendazim Pesticides in Real Samples with Enhanced Selectivity.

Agricultural products are vitally important for sustaining life on earth and their production has notably grown over the years worldwide in general and in Brazil particularly. Elevating agricultural practices consequently leads to a proportionate increase in the usage of pesticides that are crucially important for enhanced crop yield and protection. These compounds have been employed excessively in alarming concentrations, causing the contamination of soil, water, and air. Additionally, they pose serious threats to human health. The current study introduces an innovative tool for producing appropriate materials coupled with an electrochemical sensor designed to measure carbendazim levels. The sensor is developed using a molecularly imprinted polymer (MIP) mounted on a glassy carbon electrode. This electrode is equipped with multi-walled carbon nanotubes (MWCNTs) for improved performance. The combined system demonstrates promising potential for accurately quantifying carbendazim. The morphological characteristics of the synthesized materials were investigated using field emission scanning electron microscopy (FESEM) and the Fourier-transform infrared (FTIR) technique. The analytical curve was drawn using the electrochemical method in the range of 2 to 20 ppm while for HPLC 2-12 ppm; the results are presented as the maximum adsorption capacity of the MIP (82.4%) when compared with NIP (41%) using the HPLC method. The analysis conducted using differential pulse voltammetry (DPV) yielded a limit of detection (LOD) of 1.0 ppm and a repeatability of 5.08% (n = 10). The results obtained from the analysis of selectivity demonstrated that the proposed electrochemical sensor is remarkably efficient for the quantitative assessment of carbendazim, even in the presence of another interferent. The sensor was successfully tested for river water samples for carbendazim detection, and recovery rates ranging from 94 to 101% were obtained for HPLC and 94 to 104% for the electrochemical method. The results obtained show that the proposed electrochemical technique is viable for the application and quantitative determination of carbendazim in any medium.

Eryngial: An α,ß-unsaturated Fatty Aldehyde as the Major Phytotoxin in Spiny Coriander (Eryngium foetidum L.) Essential Oil.

Weed species many times possess allelochemicals as a part of their survival strategy. These metabolites can be potential targets in search of natural phytotoxins. This study aims to evaluate the phytotoxic ability of fatty aldehyde-rich essential oil from spiny coriander (Eryngium foetidum) leaves, also known as fitweed or spiritweed and to further identify the active phytotoxins. This oil dose-dependently inhibited the wheatgrass coleoptile and radicle growth in multiple bioassays with half maximal inhibitory concentration (IC50) 30.6-56.7 µg/mL, while exhibiting a less pronounced effect on the germination (IC50 181.8 µg/mL). The phytotoxicity assessment of two oil constituents identified eryngial (trans-2-dodecenal), exclusively major fatty aldehydic constituent as the potent growth inhibitor with IC50 in the range 20.8-36.2 µg/mL during an early phase of wheatgrass emergence. Eryngial-inspired screening of eleven saturated fatty aldehydes and alcohols did not find a significantly higher phytotoxic potency. In an open vessel, eryngial as the supplementation in agar medium, dose-dependently inhibited the growth of pre-germinated seeds of one monocot (bermudagrass) and one dicot (green amaranth) weed species with IC50 in the range 23.8-65.4 µg/mL. The current study identified eryngial, an α,ß-unsaturated fatty aldehyde of coriander origin to be a promising phytotoxic candidate for weed control.

USP44 overexpression drives a MYC-like gene expression program in neuroblastoma through epigenetic reprogramming.

Neuroblastoma is an embryonic cancer that contributes disproportionately to death in young children. Sequencing data have uncovered few recurrently mutated genes in this cancer, although epigenetic pathways have been implicated in disease pathogenesis. We used an expression-based computational screen that examined the impact of deubiquitinating enzymes on patient survival to identify potential new targets. We identified the histone H2B deubiquitinating enzyme USP44 as the enzyme with the greatest impact on survival in patients with neuroblastoma. High levels of USP44 significantly correlate with metastatic disease, unfavorable histology, advanced patient age, and MYCN-amplification. The subset of patients with tumors expressing high levels of USP44 had a significantly worse survival, including those with tumors lacking MYCN amplification. We showed experimentally that USP44 regulates neuroblastoma cell proliferation, migration, invasion, and neuronal development. Depletion of the histone H2B ubiquitin ligase subunit RNF20 resulted in similar findings, strongly implicating this histone mark as the target of USP44 activity in this disease. Integration of transcriptome and epigenome in analyses demonstrates a distinct set of genes that is regulated by USP44, including those in Hallmark MYC target genes in both murine embryonic fibroblasts and the SH-SY5Y neuroblastoma cell line. We conclude that USP44 is a novel epigenetic regulator that promotes aggressive features and may be a novel target in neuroblastoma. Implications: This study identifies a new genetic marker of aggressive neuroblastoma and identifies the mechanisms by which its overactivity contributes to pathophysiology in this disease.

Study on PTFE superhydrophobic coating modified by IC@dMSNs and its enhanced antibacterial effect.

INTRODUCTION: Vascular catheter-related infections and thrombosis are common and may lead to serious complications after catheterization. Reducing the incidence of such infections has become a significant challenge. OBJECTIVES: This study aims to develop a super hydrophobic nanocomposite drug-loaded vascular catheter that can effectively resist bacterial infections and blood coagulation. METHODS: In this study, a SiO2 nanocoated PTFE (Polytetrafluoroethylene) catheter (PTFE-SiO2) was prepared and further optimized to prepare a SiO2 nanocoated PTFE catheter loaded with imipenem/cilastatin sodium (PTFE-IC@dMSNs). The catheters were characterized for performance, cell compatibility, anticoagulant performance, in vitro and in vivo antibacterial effect and biological safety. RESULTS: PTFE-IC@dMSNs catheter has efficient drug loading performance and drug release rate and has good cell compatibility and anticoagulant effect in vitro. Compared with the PTFE-SiO2 catheter, the inhibition ring of the PTFE-IC@dMSNs catheter against Escherichia coli increased from 3.98 mm2 to 4.56 mm2, and the antibacterial rate increased from about 50.8 % to 56.9 %, with a significant difference (p < 0.05). The antibacterial zone against Staphylococcus aureus increased from 8.63 mm2 to 11.74 mm2, and the antibacterial rate increased from approximately 83.5 % to 89.3 %, showing a significant difference (p < 0.05). PTFE-IC@dMSNs catheter also has good biocompatibility in vivo. Furthermore, the PTFE-IC@dMSNs catheter can reduce the adhesion of blood cells and have excellent anticoagulant properties, and even maintain these properties even with the addition of imipenem/cilastatin sodium. CONCLUSION: Compared with PTFE, PTFE-SiO2 and PTFE-IC@dMSNs catheters have good characterization performance, cell compatibility, and anticoagulant properties. PTFE SiO2 and PTFE-IC@dMSNs catheters have good antibacterial performance and tissue safety against E. coli and S. aureus. Relatively, PTFE-SiO2 and PTFE-IC@dMSNs catheter has better antibacterial properties and histocompatibility and has potential application prospects in anti-bacterial catheter development and anticoagulation.

A machine learning based framework for IoT devices identification using web traffic.

Identification of the Internet of Things (IoT) devices has become an essential part of network management to secure the privacy of smart homes and offices. With its wide adoption in the current era, IoT has facilitated the modern age in many ways. However, such proliferation also has associated privacy and data security risks. In the case of smart homes and smart offices, unknown IoT devices increase vulnerabilities and chances of data theft. It is essential to identify the connected devices for secure communication. It is very difficult to maintain the list of rules when the number of connected devices increases and human involvement is necessary to check whether any intruder device has approached the network. Therefore, it is required to automate device identification using machine learning methods. In this article, we propose an accuracy boosting model (ABM) using machine learning models of random forest and extreme gradient boosting. Featuring engineering techniques are employed along with cross-validation to accurately identify IoT devices such as lights, smoke detectors, thermostat, motion sensors, baby monitors, socket, TV, security cameras, and watches. The proposed ensemble model utilizes random forest (RF) and extreme gradient boosting (XGB) as base learners with adaptive boosting. The proposed ensemble model is tested with extensive experiments involving the IoT Device Identification dataset from a public repository. Experimental results indicate a higher accuracy of 91%, precision of 93%, recall of 93%, and F1 score of 93%.

Integrated AI-driven optimization of Fenton process for the treatment of antibiotic sulfamethoxazole: Insights into mechanistic approach.

Antibiotics, as a class of environmental pollutants, pose a significant challenge due to their persistent nature and resistance to easy degradation. This study delves into modeling and optimizing conventional Fenton degradation of antibiotic sulfamethoxazole (SMX) and total organic carbon (TOC) under varying levels of H2O2, Fe2+ concentration, pH, and temperature using statistical and artificial intelligence techniques including Multiple Regression Analysis (MRA), Support Vector Regression (SVR) and Artificial Neural Network (ANN). In statistical metrics, the ANN model demonstrated superior predictive accuracy compared to its counterparts, with lowest RMSE values of 0.986 and 1.173 for SMX and TOC removal, respectively. Sensitivity showcased H2O2/Fe2+ ratio, time and pH as pivotal for SMX degradation, while in simultaneous SMX and TOC reduction, fine tuning the time, pH, and temperature was essential. Leveraging a Hybrid Genetic Algorithm-Desirability Optimization approach, the trained ANN model revealed an optimal desirability of 0.941 out of 1000 solutions which yielded a 91.18% SMX degradation and 87.90% TOC removal under following specific conditions: treatment time of 48.5 min, Fe2+: 7.05 mg L-1, H2O2: 128.82 mg L-1, pH: 5.1, initial SMX: 97.6 mg L-1, and a temperature: 29.8 °C. LC/MS analysis reveals multiple intermediates with higher m/z (242, 270 and 288) and lower m/z (98, 108, 156 and 173) values identified, however no aliphatic hydrocarbon was isolated, because of the low mineralization performance of Fenton process. Furthermore, some inorganic fragments like NH4+ and NO3- were also determined in solution. This comprehensive research enriches AI modeling for intricate Fenton-based contaminant degradation, advancing sustainable antibiotic removal strategies.

Recent advances in the fluorimetric and colorimetric detection of cobalt ions.

Cobalt is an essential metal to maintain several functions in the human body and is present in functional materials for numerous applications. Thus, to monitor these functions, it is necessary to develop suitable probes for the detection of cobalt. Presently, researchers are focused on designing different chemosensors for the qualitative and quantitative detection of the metal ions. Among the numerous methods devised for the identification of cobalt ions, colorimetric and fluorimetric techniques are considered the best choice due to their user-friendly nature, sensitivity, accuracy, linearity and robustness. In these techniques, the interaction of the analyte with the chemosensor leads to structural changes in the molecule, causing the emission and excitation intensities (bathochromic, hyperchromic, hypochromic, and hypsochromic) to change with a change in the concentration of the analyte. In this review, the recent advancements in the fluorimetric and colorimetric detection of cobalt ions are systematically summarized, and it is concluded that the development of chemosensors having distinctive colour changes when interacting with cobalt ions has been targeted for on-site detection. The chemosensors are grouped in various categories and their comparison and the discussion of computational studies will enable readers to have a quick overview and help in designing effective and efficient probes for the detection of cobalt in the field of chemo-sensing.

A Review of Rechargeable Zinc-Air Batteries: Recent Progress and Future Perspectives.

Zinc-air batteries (ZABs) are gaining attention as an ideal option for various applications requiring high-capacity batteries, such as portable electronics, electric vehicles, and renewable energy storage. ZABs offer advantages such as low environmental impact, enhanced safety compared to Li-ion batteries, and cost-effectiveness due to the abundance of zinc. However, early research faced challenges due to parasitic reactions at the zinc anode and slow oxygen redox kinetics. Recent advancements in restructuring the anode, utilizing alternative electrolytes, and developing bifunctional oxygen catalysts have significantly improved ZABs. Scientists have achieved battery reversibility over thousands of cycles, introduced new electrolytes, and achieved energy efficiency records surpassing 70%. Despite these achievements, there are challenges related to lower power density, shorter lifespan, and air electrode corrosion leading to performance degradation. This review paper discusses different battery configurations, and reaction mechanisms for electrically and mechanically rechargeable ZABs, and proposes remedies to enhance overall battery performance. The paper also explores recent advancements, applications, and the future prospects of electrically/mechanically rechargeable ZABs.

Formulation of Hierarchical Nanowire-Structured CoNiO2 and MoS2/CoNiO2 Hybrid Composite Electrodes for Supercapacitor Applications.

Hierarchical porous nanowire-like MoS2/CoNiO2 nanohybrids were synthesized via the hydrothermal process. CoNiO2 nanowires were selected due to the edge site, high surface/volume ratio, and superior electrochemical characteristics as the porous backbone for decoration of layered MoS2 nanoflakes to construct innovative structure hierarchical three-dimensional (3D) porous NWs MoS2/CoNiO2 hybrids with excellent charge accumulation and efficient ion transport capabilities. Physicochemical analyses were conducted on the developed hybrid composite, revealing conclusive evidence that the CoNiO2 nanowires have been securely anchored onto the surface of the MoS2 nanoflake array. The electrochemical results strongly proved the benefit of the hierarchical 3D porous MoS2/CoNiO2 hybrid structure for the charge storage kinetics. The synergistic characteristics arising from the MoS2/CoNiO2 composite yielded a notably high specific capacitance of 1340 F/g at a current density of 0.5 A/g. Furthermore, the material exhibited sustained cycling stability, retaining 95.6% of its initial capacitance after 10 000 long cycles. The asymmetric device comprising porous MoS2/CoNiO2//activated carbon encompassed outstanding energy density (93.02 Wh/kg at 0.85 kW/kg) and cycling stability (94.1% capacitance retention after 10 000 cycles). Additionally, the successful illumination of light-emitting diodes underscores the significant potential of the synthesized MoS2/CoNiO2 (2D/1D) hybrid for practical high-energy storage applications.

N2 reduction to NH3 on surfaces of Co-Al18P18, Ni-Al21N21, Fe-B24N24, Mn-B27P27, Ti-C60 and Cu-Si72 catalysts.

CONTEXT: The abilities of Co-Al18P18, Ni-Al21N21, Fe-B24N24, Mn-B27P27, Ti-C60 and Cu-Si72 as catalysts for N2-RR to create the NH3 are investigated by theoretical levels. The ∆Eadoption and ∆Eformation of Co-Al18P18, Ni-Al21N21, Fe-B24N24, Mn-B27P27, Ti-C60 and Cu-Si72 are investigated. The ∆Eadsorption of N2-RR intermediates and ΔGreaction of reaction steps of N2-RR on Co-Al18P18, Ni-Al21N21, Fe-B24N24, Mn-B27P27, Ti-C60 and Cu-Si72 are examined. In acceptable mechanisms, the *NN → *NNH step is potential limiting step and *NN → *NNH step in enzymatic mechanism is endothermic reaction. The ∆Greaction of *NHNH2 → *NH2NH2 step on Co-Al18P18, Ni-Al21N21, Fe-B24N24, Mn-B27P27, Ti-C60 and Cu-Si72 are -0.904, -0.928, -0.860, -0.882, -0.817 and -0.838 eV, respectively. The Co-Al18P18 and Ni-Al21N21 have the highest ∆Greaction values for reaction steps of N2-RR. Finally, it can be concluded that the Co-Al18P18, Ni-Al21N21, Fe-B24N24 and Mn-B27P2 have acceptable potential for N2-RR by acceptable pathways. METHODS: The structures of Co-Al18P18, Ni-Al21N21, Fe-B24N24, Mn-B27P27, Ti-C60 and Cu-Si72 and N2-RR intermediates are optimized by PW91PW91/6-311+G (2d, 2p) and M06-2X/cc-pVQZ as theoretical levels in GAMESS software. The convergence for force set displacement of Co-Al18P18, Ni-Al21N21, Fe-B24N24, Mn-B27P27, Ti-C60 and Cu-Si72 and N2-RR intermediates are 1.5 × 105 Hartree/Bohr and 6.0 × 10-5 Angstrom. The Opt = Tight and MaxStep = 30 are considered to optimize Co-Al18P18, Ni-Al21N21, Fe-B24N24, Mn-B27P27, Ti-C60 and Cu-Si72 and N2-RR intermediates. The frequencies of Co-Al18P18, Ni-Al21N21, Fe-B24N24, Mn-B27P27, Ti-C60 and Cu-Si72 and N2-RR intermediates are calculated.

Functionalization of Shorea faguetiana biochar using Fe2O3 nanoparticles and MXene for rapid removal of methyl blue and lead from both single and binary systems.

The synthesis of polymeric magnetic composites is a promising strategy for the rapid and efficient treatment of wastewater. Lead and methyl blue are extremely hazardous to living organisms. The sorption of Pb2+ and the dye methyl blue (MB) by biochar is an ecologically sustainable method to remediate this type of water pollution. We functionalized Shorea faguetiana biochar with Fe2O3 and MXene, resulting in Fe2O3/BC/MXene composites with an efficient, rapid, and selective adsorption performance. Based on X-ray photoelectron and Fourier transform infrared spectrometry, we found that the Fe2O3/BC/MXene composites had an increased number of surface functional groups (F-, C[double bond, length as m-dash]O, CN, NH, and OH-) compared with the original biochar. The batch sorption findings showed that the maximum sorption capacities for Pb2+ and MB at 293 K were 882.76 and 758.03 mg g-1, respectively. The sorption phenomena obeyed a pseudo-second-order (R2 = 1) model and the Langmuir isotherm. There was no competition between MB and Pb2+ in binary solutions, indicating that MB and Pb2+ did not influence each other as a result of their different adsorption mechanisms (electrostatic interaction for Pb2+ and hydrogen bonding for MB). This illustrates monolayer sorption on the Fe2O3/BC/MXene composite governed by chemical adsorption. Thermodynamic investigations indicated that the sorption process was spontaneous and exothermic at 293-313 K, suggesting that it is feasible for practical applications. Fe2O3/BC/MXene can selectively adsorb Pb2+ ions and MB from wastewater containing multiple interfering metal ions. The sorption capacities were still high after five reusability experiments. This work provides a novel Fe2O3/BC/MXene composite for the rapid and efficient removal of Pb2+ and MB.

Enhancement of the photocatalytic activity of rGO/NiO/Ag nanocomposite for degradation of methylene blue dye.

The current study focuses on boosting the photocatalytic ability of reduced graphene oxide (rGO) by decorating the rGO nano-sheets with nickel oxide (NiOx) and silver (Ag) nanomaterials. The developed ternary nanomaterials were investigated using FTIR, XRD, FESEM, TEM, Raman, and UV-vis to evaluate the photo-degradation process. The rGO/NiOx/Ag ternary system showed promising photocatalytic dye degradation under simulated sunlight irradiance. The addition of NiOx and Ag nanomaterials widened the catalytic activity spectrum from the visible region to the UV-region. Besides, these materials hindered the electron-hole recombination, boosting the catalytic activity. The reusability results also clearly showed that the synthesized ternary nanomaterials have good reproducibility and stability for photocatalytic degradation of industrial wastewater.

Synergistic effect of a bamboo-like Bi2S3 covered Sm2O3 nanocomposite (Bi2S3-Sm2O3) for enhanced alkaline OER.

The availability of hydrogen energy from water splitting through the electrocatalytic route is strongly dependent on the efficiency, durability, and cost of the electrocatalysts. Herein, a novel Bi2S3-covered Sm2O3 (Bi2S3-Sm2O3) nanocomposite electrocatalyst was developed by a hydrothermal route for the oxygen evolution reaction (OER). The electrochemical properties were studied in 1.00 mol KOH solution after coating the target material on the stainless-steel substrate (SS). Physical analysis via XRD, FTIR, IV, TEM/EDX, and XPS revealed that the Bi2S3-Sm2O3 composite possesses metallic surface states, thereby displaying unconventional electron dynamics and purity of phases. The Bi2S3-Sm2O3 composite shows outstanding OER activity with a low overpotential of 197 mV and a Tafel slope of 74 mV dec-1 at a 10 mA cm-2 current density as compared to pure Bi2S3 and Sm2O3. Meanwhile, the composite catalyst retains high stability even after 100 h of the chronoamperometry test. Thus, this work unveils a new avenue for the speedy flow of electrons, which is attributed to the synergetic effect between Bi2S3 and Sm2O3, as well as enriched interfacial defects, which exhibit greater oxygen adsorption capability with improved electronic assemblies in the active interfacial region. In addition, the introduced porous structure in core-shell Bi2S3-Sm2O3 provides extraordinary electrical properties. Thus, this article offers a realistic framework for electrochemical energy generation.

Integrating DFT and machine learning for the design and optimization of sodium alginate-based hydrogel adsorbents: Efficient removal of pollutants from wastewater.

This study presents a novel approach to design and optimize a sodium alginate-based hydrogel (SAH) for efficient adsorption of the model water pollutant methylene blue (MB) dye. Utilizing density functional theory (DFT) calculations, sodium alginate-g-poly (acrylamide-co-itaconic acid) was identified with the lowest adsorption energy (Eads) for MB dye among 14 different clusters. SAHs were prepared using selected monomers and sodium alginate combinations through graft co-polymerization, and swelling studies were conducted to optimize grafting conditions. Advanced characterization techniques, including FTIR, XRD, XPS, SEM, EDS, and TGA, were employed, and the process was optimized using statistical and machine learning tools. Screening tests demonstrated that Eads serves as an effective predicting indicator for adsorption capacity (qe) and MB removal efficiency (RRMB,%), with reasonable agreement between Eads and both responses under given conditions. Process modeling and optimization revealed that 5 mg of selected SAH achieves a maximum qe of 3244 mg g-1 at 84.4% RRMB under pH 8.05, 98.8 min, and MB concentration of 383.3 mg L-1, as identified by the desirability function approach. Moreover, SAH effectively eliminated various contaminants from aqueous solutions, including sulfasalazine (SFZ) and dibenzothiophene (DBT). MB adsorption onto selected SAH was exothermic, spontaneous, and followed the pseudo-first-order and Langmuir-Freundlich isotherm models. The remarkable ability of SAH to adsorb MB is attributed to its well-designed structure predicted through DFT and optimal operational conditions achieved by AI-based parametric optimization. By integrating DFT-based computations and machine-learning tools, this study contributes to the efficient design of adsorbent materials and optimization of adsorption processes, also showcasing the potential of SAH as an efficient adsorbent for the abatement of aqueous pollution.

Metal oxide-embedded carbon-based materials for polymer solar cells and X-ray detectors.

This study examines the effects of hybrid nanoparticles made of NiO@rGO (reduced graphene oxide) and NiO@CNT (carbon nanotubes) on PCDTBT and PCBM active layers in glass/ITO/HTL/active-layer/LiF/Al structured bulk heterojunction (BHJ) polymer solar cells (PSCs) and X-ray photodetectors. These hybrid nanoparticles were used to create BHJ solar cells and photodetectors, and microscopic research was conducted to determine how they affect the structure of the devices. The findings show that compared to conventional matrices, the active layers with NiO@rGO and NiO@CNT incorporation have increased the charge carrier capacities and exciton dissociation properties. In order to assess their impact on the characteristics of charge transport, various weight ratios of these hybrid nanoparticles dispersed in polymer junctions are being investigated. Notably, compared to the pure PCDTBT:PCBM active layer (power conversion efficiency (PCE) = 4.35%), the NiO@CNT device has the highest PCE = 6.42% which, among the tested configurations, demonstrates its superior performance in converting sunlight into electricity. Among the tested X-ray detector materials, "NiO@CNT" achieves the best performance with a sensitivity of 1.92 mA Gy-1 cm-2. Through improved interfacial behaviors and effective charge transport, this work highlights the potential of these cutting-edge hybrid nanoparticles to enhance the performance of organic electronic devices.

Nanomaterials-Based Field-Effect Transistor for Protein Sensing: New Advances.

It is crucial for early stage medical diagnostics to identify disease biomarkers at ultralow concentrations. A wide range of analytes can be identified using low-dimensional materials to build highly sensitive, targeted, label-free, field-effect transistor (FET) biosensors. Two-dimensional (2D) materials are preferable for high-performance biosensing because of their dramatic change in resistivity upon analyte adsorption or biomarker detection, tunable electronic properties, high surface activities, adequate stability, and layer-dependent semiconducting properties. We give a succinct overview of interesting applications for protein sensing with various architectural styles, such as 2D transition metal dichalcogenides (TMDs)-based FETs that include carbon nanotubes (CNTs), graphene (Gr), reduced graphene oxide (rGr), 2D transition-metal carbides (MXene), and Gr/MXene heterostructures. Because it might enable individuals to perform better, this review will be an important contribution to the field of medical science. These achievements demonstrate point-of-care diagnostics' abilities to detect biomarkers at ultrahigh performance levels. A summary of the present opportunities and challenges appears in the conclusion.

Supermolecule Polymer Derived Porous Carbon Nitride Microspheres with Controllable Energy Band Structure for Photocatalytic Hydrogen Evolution Reaction.

Porous graphitic carbon nitride microsphere with large specific surface area and controllable energy band structure is synthesized via a simple method with the supermolecule polymer of melamine-cyanuric acid (MCA) as the intermediates. The energy band structure and morphology of carbon nitride are closely correlative to the calcination time. And the CN-20 catalyst fabricated by calcination for 20 h exhibit superior photocatalytic activity of hydrogen evolution reaction (HER) under visible-light (λ ≥ 420 nm) irradiation. The photocatalytic and photoelectrochemical test results indicate that Pt is the optimum cocatalyst candidate compared with Pd, Ru, and Ag. Meanwhile, the time-dependent process of the intermediate pyrolysis to carbon nitride and the internal mechanism of photogenerated charge transfer between semiconductors and cocatalyst is investigated and supplemented by theoretical calculations. This work provides a novel and energy band structure controllable manufacture strategy for porous carbon nitride semiconductor with satisfying visible-light photocatalytic reduction performance.

Preparation, optimization and evaluation of Osthole transdermal therapeutic system.

In the current study, the solubility and permeability of Osthole-loaded microemulsion were enhanced, which increased bioavailability. In addition, Carbomer 940 was added for prolonged drug delivery. The microemulsion was prepared after the screening of Kukui oil, Labrasol (surfactant), and transcutol-P (co-surfactant). Pseudoternary phase diagrams were employed to find the microemulsion region. Box Behnken Design (BBD) was employed for optimizing microemulsions. Variables were related and compared using mathematical equations and response surface plots (RSP). MEBG was then compared with control gel on the basis of stability studies, drug permeation, skin irritation studies, and anti-inflammatory studies. Microemulsion preparations depicted a pH of 5.27 - 5.80, a conductivity of 139 - 185 µS/cm, a poly-dispersity index of 0.116 - 0.388, a refractive index of 1.330 - 1.427, an average droplet size of 64 - 89 nm, homogeneity, spherical shape, viscosity 52 - 185 cP. Predicted values of Optimized microemulsions showed more reasonable agreement than experimental values. The microemulsion was stable and non-irritating on Rabbit skin. MEBG showed a significant difference from control gel for percent edema inhibition from the standard. The permeation enhancing capability of MEBG using a suitable viscosity fabricates it promising carrier for transdermal delivery of Osthole.

Assessment and Exposure Analysis of Trace Metals in Different Age Groups of the Male Population in Southern Punjab, Pakistan.

In developing countries, like Pakistan, the pursuit of urbanization and economic development disrupts the delicate ecosystem, resulting in additional biogeochemical emissions of heavy metals into the human habitat and posing significant health risks. The levels of these trace elements in humans remain unknown in areas at higher risk of pollution in Pakistan. In this investigation, selected trace metals including Copper (Cu), Chromium (Cr), Lead (Pb) Cadmium (Cd), Cobalt (Co), Nickel (Ni), and Arsenic (As) were examined in human hair, urine, and nail samples of different age groups from three major cities (Muzaffargarh, Multan, and Vehari) in Punjab province, Pakistan. The results revealed that the mean concentrations (ppm) of Cr (1.1) and Cu (9.1) in hair was highest in Muzaffargarh. In urine samples, the mean concentrations (µg/L) of Co (93), As (79), Cu (69), Cr (56), Ni (49), Cd (45), and Pb (35) were highest in the Multan region, while As (34) and Cr (26) were highest in Vehari. The mean concentrations (ppm) of Ni (9.2), Cr (5.6), and Pb (2.8), in nail samples were highest in Vehari; however, Multan had the highest Cu (28) concentration (ppm). In urine samples, the concentrations of all the studied metals were within permissible limits except for As (34 µg/L) and Cr (26 µg/L) in Vehari. However, in nail samples, the concentrations of Ni in Multan (8.1 ppm), Muzaffargarh (9 ppm), Vehari (9.2 ppm), and Cd (3.69 ppm) in Muzaffargarh exceeded permissible limits. Overall, the concentrations of metals in urine, nail, and hair samples were higher in adults (39-45 age group). Cr, Cu, and Ni revealed significantly higher concentrations of metals in hair and water in Multan, whereas As in water was significantly (p < 0.001) correlated with urinary As in Multan, indicating that the exposure source was region-specific.