Deep learning framework for bovine iris segmentation.

Iris segmentation is an initial step for identifying the biometrics of animals when establishing a traceability system for livestock. In this study, we propose a deep learning framework for pixel-wise segmentation of bovine iris with a minimized use of annotation labels utilizing the BovineAAEyes80 public dataset. The proposed image segmentation framework encompasses data collection, data preparation, data augmentation selection, training of 15 deep neural network (DNN) models with varying encoder backbones and segmentation decoder DNNs, and evaluation of the models using multiple metrics and graphical segmentation results. This framework aims to provide comprehensive and in-depth information on each model's training and testing outcomes to optimize bovine iris segmentation performance. In the experiment, U-Net with a VGG16 backbone was identified as the optimal combination of encoder and decoder models for the dataset, achieving an accuracy and dice coefficient score of 99.50% and 98.35%, respectively. Notably, the selected model accurately segmented even corrupted images without proper annotation data. This study contributes to the advancement of iris segmentation and the establishment of a reliable DNN training framework.

Graphitic Carbon Nitride/Zinc Oxide-Based Z-Scheme and S-Scheme Heterojunction Photocatalysts for the Photodegradation of Organic Pollutants.

Graphitic carbon nitride (g-C3N4), a metal-free polymer semiconductor, has been recognized as an attractive photocatalytic material for environmental remediation because of its low band gap, high thermal and photostability, chemical inertness, non-toxicity, low cost, biocompatibility, and optical and electrical efficiency. However, g-C3N4 has been reported to suffer from many difficulties in photocatalytic applications, such as a low specific surface area, inadequate visible-light utilization, and a high charge recombination rate. To overcome these difficulties, the formation of g-C3N4 heterojunctions by coupling with metal oxides has triggered tremendous interest in recent years. In this regard, zinc oxide (ZnO) is being largely explored as a self-driven semiconductor photocatalyst to form heterojunctions with g-C3N4, as ZnO possesses unique and fascinating properties, including high quantum efficiency, high electron mobility, cost-effectiveness, environmental friendliness, and a simple synthetic procedure. The synergistic effect of its properties, such as adsorption and photogenerated charge separation, was found to enhance the photocatalytic activity of heterojunctions. Hence, this review aims to compile the strategies for fabricating g-C3N4/ZnO-based Z-scheme and S-scheme heterojunction photocatalytic systems with enhanced performance and overall stability for the photodegradation of organic pollutants. Furthermore, with reference to the reported system, the photocatalytic mechanism of g-C3N4/ZnO-based heterojunction photocatalysts and their charge-transfer pathways on the interface surface are highlighted.

Oxidative Stress and DNA Damage in Pagrus major by the Dinoflagellate Karenia mikimotoi.

Karenia mikimotoi is a common species of red tide dinoflagellate that causes the mass mortality of marine fauna in coastal waters of Republic of Korea. Despite continuous studies on the ecophysiology and toxicity of K. mikimotoi, the underlying molecular mechanisms remain poorly understood. Red sea bream, Pagrus major, is a high-value aquaculture fish species, and the coastal aquaculture industry of red sea bream has been increasingly affected by red tides. To investigate the potential oxidative effects of K. mikimotoi on P. major and the molecular mechanisms involved, we exposed the fish to varying concentrations of K. mikimotoi and evaluated its toxicity. Our results showed that exposure to K. mikimotoi led to an accumulation of reactive oxygen species (ROS) and oxidative DNA damage in the gill tissue of P. major. Furthermore, we found that K. mikimotoi induced the activation of antioxidant enzymes, such as superoxide dismutase, catalase, glutathione peroxidase, and glutathione reductase, in the gill tissue of P. major, with a significant increase in activity at concentrations above 5000 cells/mL. However, the activity of glutathione S-transferase did not significantly increase at the equivalent concentration. Our study confirms that oxidative stress and DNA damage is induced by acute exposure to K. mikimotoi, as it produces ROS and hypoxic conditions in P. major. In addition, it was confirmed that gill and blood samples can be used as biomarkers to detect the degree of oxidative stress in fish. These findings have important implications for the aquaculture of red sea bream, particularly in the face of red tide disasters.

A comparative study of epidemiological characteristics, treatment outcomes, and mortality among patients undergoing hemodialysis by health insurance types: data from the Korean Renal Data System.

Background: The prevalence of end-stage renal disease (ESRD) requiring dialysis has progressively increased. Therefore, to achieve financial stability by managing the increasing numbers of patients undergoing hemodialysis (HD), a fixed-payment system was introduced in 2001 for medical aid (MA) beneficiaries receiving HD in Korea. Methods: We identified patients in the Korean Renal Data System that received HD between 2001 and 2017 and stratified them into the following two groups: the National Health Insurance (NHI) and MA groups. Then, we compared the two groups that differed in demographic characteristics, the treatment process and outcomes, and mortality based on health insurance type. Results: Among 52,574 patients, the number of patients aged 65 years or older, hypertension was higher in the NHI group, but diabetes was higher in the MA group. Additionally, the MA group had more weekly dialysis sessions, and expensive drugs tended to be used less frequently. Regarding treatment outcomes, including laboratory test results, the MA group achieved significantly lower goals than the NHI group (p < 0.001). Furthermore, the mortality rate per 1,000 persons was 31 and 27 in the MA and NHI groups, respectively, and the mortality rate ratio was 1.2 (95% confidence interval [CI], 1.076-1.230). Moreover, the hazard ratio for mortality was 1.39 (95% CI, 1.30-1.49, p < 0.001) after adjusting for age, sex, causes of ESRD, and comorbidities. Conclusion: There were significant differences in the treatment and mortality indicators between the groups. Therefore, policy support should be strengthened to provide better medical services to MA beneficiaries undergoing HD.

Unveiling Neuroprotection and Regeneration Mechanisms in Optic Nerve Injury: Insight from Neural Progenitor Cell Therapy with Focus on Vps35 and Syntaxin12.

Axonal degeneration resulting from optic nerve damage can lead to the progressive death of retinal ganglion cells (RGCs), culminating in irreversible vision loss. We contrasted two methods for inducing optic nerve damage: optic nerve compression (ONCo) and optic nerve crush (ONCr). These were assessed for their respective merits in simulating traumatic optic neuropathies and neurodegeneration. We also administered neural progenitor cells (NPCs) into the subtenon space to validate their potential in mitigating optic nerve damage. Our findings indicate that both ONCo and ONCr successfully induced optic nerve damage, as shown by increases in ischemia and expression of genes linked to neuronal regeneration. Post NPC injection, recovery in the expression of neuronal regeneration-related genes was more pronounced in the ONCo model than in the ONCr model, while inflammation-related gene expression saw a better recovery in ONCr. In addition, the proteomic analysis of R28 cells in hypoxic conditions identified Vps35 and Syntaxin12 genes. Vps35 preserved the mitochondrial function in ONCo, while Syntaxin12 appeared to restrain inflammation via the Wnt/ß-catenin signaling pathway in ONCr. NPCs managed to restore damaged RGCs by elevating neuroprotection factors and controlling inflammation through mitochondrial homeostasis and Wnt/ß-catenin signaling in hypoxia-injured R28 cells and in both animal models. Our results suggest that ischemic injury and crush injury cause optic nerve damage via different mechanisms, which can be effectively simulated using ONCo and ONCr, respectively. Moreover, cell-based therapies such as NPCs may offer promising avenues for treating various optic neuropathies, including ischemic and crush injuries.

Deep Learning-Based Precision Analysis for Acrosome Reaction by Modification of Plasma Membrane in Boar Sperm.

The analysis of AR is widely used to detect loss of acrosome in sperm, but the subjective decisions of experts affect the accuracy of the examination. Therefore, we develop an ARCS for objectivity and consistency of analysis using convolutional neural networks (CNNs) trained with various magnification images. Our models were trained on 215 microscopic images at 400× and 438 images at 1000× magnification using the ResNet 50 and Inception-ResNet v2 architectures. These models distinctly recognized micro-changes in the PM of AR sperms. Moreover, the Inception-ResNet v2-based ARCS achieved a mean average precision of over 97%. Our system's calculation of the AR ratio on the test dataset produced results similar to the work of the three experts and could do so more quickly. Our model streamlines sperm detection and AR status determination using a CNN-based approach, replacing laborious tasks and expert assessments. The ARCS offers consistent AR sperm detection, reduced human error, and decreased working time. In conclusion, our study suggests the feasibility and benefits of using a sperm diagnosis artificial intelligence assistance system in routine practice scenarios.

Comparison of cancer subtype identification methods combined with feature selection methods in omics data analysis.

BACKGROUND: Cancer subtype identification is important for the early diagnosis of cancer and the provision of adequate treatment. Prior to identifying the subtype of cancer in a patient, feature selection is also crucial for reducing the dimensionality of the data by detecting genes that contain important information about the cancer subtype. Numerous cancer subtyping methods have been developed, and their performance has been compared. However, combinations of feature selection and subtype identification methods have rarely been considered. This study aimed to identify the best combination of variable selection and subtype identification methods in single omics data analysis. RESULTS: Combinations of six filter-based methods and six unsupervised subtype identification methods were investigated using The Cancer Genome Atlas (TCGA) datasets for four cancers. The number of features selected varied, and several evaluation metrics were used. Although no single combination was found to have a distinctively good performance, Consensus Clustering (CC) and Neighborhood-Based Multi-omics Clustering (NEMO) used with variance-based feature selection had a tendency to show lower p-values, and nonnegative matrix factorization (NMF) stably showed good performance in many cases unless the Dip test was used for feature selection. In terms of accuracy, the combination of NMF and similarity network fusion (SNF) with Monte Carlo Feature Selection (MCFS) and Minimum-Redundancy Maximum Relevance (mRMR) showed good overall performance. NMF always showed among the worst performances without feature selection in all datasets, but performed much better when used with various feature selection methods. iClusterBayes (ICB) had decent performance when used without feature selection. CONCLUSIONS: Rather than a single method clearly emerging as optimal, the best methodology was different depending on the data used, the number of features selected, and the evaluation method. A guideline for choosing the best combination method under various situations is provided.

Transcriptomic Changes Induced by Low and High Concentrations of Heavy Metal Exposure in Ulva pertusa.

The impact of sewage and wastewater pollution on marine ecosystems is of increasing concern due to the rapid accumulation of heavy metals in seaweeds inhabiting near-shore environments. Seaweeds can be severely damaged by heavy metals throughout their life cycles. Although the physiological and ecological effects of heavy metal exposure have been studied, there is limited research on their molecular responses. Ulva pertusa is a prevalent seaweed species in South Korea and is ecologically significant in coastal ecosystems. We utilized high-throughput RNA sequencing to analyze changes in the transcriptome profiles of U. pertusa under low concentrations of heavy metals (MPS) and high concentrations of copper (MPS-Cu) and cadmium (MPS-Cd). Differential gene expression analysis revealed that 53 (control vs. MPS), 27 (MPS vs. MPS-Cd), and 725 (MPS vs. MPS-Cu) genes were expressed differentially. Differentially expressed genes identified in our study included those with protective roles against oxidative stress and those involved in metal transport to the vacuole. Furthermore, exposure to heavy metal stress had a negative impact on the photosynthetic apparatus structural proteins of U. pertusa, resulting in photosynthetic inhibition. Moreover, exposure to high concentrations of copper resulted in the activation of carbon-related metabolism. These findings contribute to our understanding of the molecular mechanisms underlying heavy metal toxicity in U. pertusa.

MXene-Embedded Electrospun Polymeric Nanofibers for Biomedical Applications: Recent Advances.

Recently MXenes has gained immense attention as a new and exciting class of two-dimensional material. Due to their unique layered microstructure, the presence of various functional groups at the surface, earth abundance, and attractive electrical, optical, and thermal properties, MXenes are considered promising candidates for various applications such as energy, environmental, and biomedical. The ease of dispersibility and metallic conductivity of MXene render them promising candidates for use as fillers in polymer nanocomposites. MXene-polymer nanocomposites simultaneously benefit from the attractive properties of MXenes and the flexibility and facile processability of polymers. However, the potentiality of MXene to modify the electrospun nanofibers has been less studied. Understanding the interactions between polymeric nanofibers and MXenes is important to widen their role in biomedical applications. This review explores diverse methods of MXene synthesis, discusses our current knowledge of the various biological characteristics of MXene, and the synthesis of MXene incorporated polymeric nanofibers and their utilization in biomedical applications. The information discussed in this review serves to guide the future development and application of MXene-polymer nanofibers in biomedical fields.

Nanoarchitectonics of Three-Dimensional Carbon Nanofiber-Supported Hollow Copper Sulfide Spheres for Asymmetric Supercapacitor Applications.

Three-dimensional carbon nanofiber (3D-CNF)-supported hollow copper sulfide (HCuS) spheres were synthesized by the facile hydrothermal method. The morphology of the as-synthesized HCuS@3D-CNF composite clearly revealed that the 3D-CNFs act as a basement for HCuS spheres. The electrochemical performance of as-synthesized HCuS@3D-CNFs was evaluated by cyclic voltammetry (CV) tests, gravimetric charge-discharge (GCD) tests, and Nyquist plots. The obtained results revealed that the HCuS@3D-CNFs exhibited greater areal capacitance (4.6 F/cm2) compared to bare HCuS (0.64 F/cm2) at a current density of 2 mA/cm2. Furthermore, HCuS@3D-CNFs retained excellent cyclic stability of 83.2% after 5000 cycles. The assembled asymmetric device (HCuS@3D-CNFs//BAC) exhibits an energy density of 0.15 mWh/cm2 with a working potential window of 1.5 V in KOH electrolyte. The obtained results demonstrate that HZnS@3D-CNF nanoarchitectonics is a potential electrode material for supercapacitor applications.

CFP1 governs uterine epigenetic landscapes to intervene in progesterone responses for uterine physiology and suppression of endometriosis.

Progesterone (P4) is required for the preparation of the endometrium for a successful pregnancy. P4 resistance is a leading cause of the pathogenesis of endometrial disorders like endometriosis, often leading to infertility; however, the underlying epigenetic cause remains unclear. Here we demonstrate that CFP1, a regulator of H3K4me3, is required for maintaining epigenetic landscapes of P4-progesterone receptor (PGR) signaling networks in the mouse uterus. Cfp1f/f;Pgr-Cre (Cfp1d/d) mice showed impaired P4 responses, leading to complete failure of embryo implantation. mRNA and chromatin immunoprecipitation sequencing analyses showed that CFP1 regulates uterine mRNA profiles not only in H3K4me3-dependent but also in H3K4me3-independent manners. CFP1 directly regulates important P4 response genes, including Gata2, Sox17, and Ihh, which activate smoothened signaling pathway in the uterus. In a mouse model of endometriosis, Cfp1d/d ectopic lesions showed P4 resistance, which was rescued by a smoothened agonist. In human endometriosis, CFP1 was significantly downregulated, and expression levels between CFP1 and these P4 targets are positively related regardless of PGR levels. In brief, our study provides that CFP1 intervenes in the P4-epigenome-transcriptome networks for uterine receptivity for embryo implantation and the pathogenesis of endometriosis.

Novel Materials in Perovskite Solar Cells: Efficiency, Stability, and Future Perspectives.

Solar energy is regarded as the finest clean and green energy generation method to replace fossil fuel-based energy and repair environmental harm. The more expensive manufacturing processes and procedures required to extract the silicon utilized in silicon solar cells may limit their production and general use. To overcome the barriers of silicon, a new energy-harvesting solar cell called perovskite has been gaining widespread attention around the world. The perovskites are scalable, flexible, cost-efficient, environmentally benign, and easy to fabricate. Through this review, readers may obtain an idea about the different generations of solar cells and their comparative advantages and disadvantages, working mechanisms, energy alignment of the various materials, and stability achieved by applying variable temperature, passivation, and deposition methods. Furthermore, it also provides information on novel materials such as carbonaceous, polymeric, and nanomaterials that have been employed in perovskite solar in terms of the different ratios of doping and composite and their optical, electrical, plasmonic, morphological, and crystallinity properties in terms of comparative solar parameters. In addition, information on current trends and future commercialization possibilities of perovskite solar have been briefly discussed based on reported data by other researchers.

Electrospun Nanofibers for Dura Mater Regeneration: A Mini Review on Current Progress.

Dural defects are a common problem in neurosurgical procedures and should be repaired to avoid complications such as cerebrospinal fluid leakage, brain swelling, epilepsy, intracranial infection, and so on. Various types of dural substitutes have been prepared and used for the treatment of dural defects. In recent years, electrospun nanofibers have been applied for various biomedical applications, including dural regeneration, due to their interesting properties such as a large surface area to volume ratio, porosity, superior mechanical properties, ease of surface modification, and, most importantly, similarity with the extracellular matrix (ECM). Despite continuous efforts, the development of suitable dura mater substrates has had limited success. This review summarizes the investigation and development of electrospun nanofibers with particular emphasis on dura mater regeneration. The objective of this mini-review article is to give readers a quick overview of the recent advances in electrospinning for dura mater repair.

Suppression of triple-negative breast cancer aggressiveness by LGALS3BP via inhibition of the TNF-α-TAK1-MMP9 axis.

Transforming growth factor-ß-activated kinase 1 (TAK1), which is highly expressed and aberrantly activated in triple-negative breast cancer (TNBC), plays a pivotal role in metastasis and progression. This makes it a potential therapeutic target for TNBC. Previously, we reported lectin galactoside-binding soluble 3 binding protein (LGALS3BP) as a negative regulator of TAK1 signaling in the inflammatory response and inflammation-associated cancer progression. However, the role of LGALS3BP and its molecular interaction with TAK1 in TNBC remain unclear. This study aimed to investigate the function and underlying mechanism of action of LGALS3BP in TNBC progression and determine the therapeutic potential of nanoparticle-mediated delivery of LGALS3BP in TNBC. We found that LGALS3BP overexpression suppressed the overall aggressive phenotype of TNBC cells in vitro and in vivo. LGALS3BP inhibited TNF-α-mediated gene expression of matrix metalloproteinase 9 (MMP9), which encodes a protein crucial for lung metastasis in TNBC patients. Mechanistically, LGALS3BP suppressed TNF-α-mediated activation of TAK1, a key kinase linking TNF-α stimulation and MMP9 expression in TNBC. Nanoparticle-mediated delivery enabled tumor-specific targeting and inhibited TAK1 phosphorylation and MMP9 expression in tumor tissues, suppressing primary tumor growth and lung metastasis in vivo. Our findings reveal a novel role of LGALS3BP in TNBC progression and demonstrate the therapeutic potential of nanoparticle-mediated delivery of LGALS3BP in TNBC.

The use of virtual reality in screening for preclinical Alzheimer's disease: A scoping review protocol.

INTRODUCTION: Preclinical Alzheimer's disease (AD) represents the earliest phase of AD, often years before the onset of mild cognitive impairment (MCI). There is a pressing focus on identifying individuals in the preclinical AD phase to alter the trajectory or impact of the disease potentially. Increasingly, Virtual Reality (VR) technology is being used to support a diagnosis of AD. While VR technology has been applied to the assessment of MCI and AD, studies about how best to utilize VR as a screening tool for preclinical AD are limited and discordant. The objectives of this review are to synthesize the evidence pertaining to the use of VR as a screening tool for preclinical AD as well as to identify factors that need to be considered when utilizing VR to screen for preclinical AD. METHODS AND ANALYSIS: The methodological framework proposed by Arksey and O'Malley (2005) will be introduced to guide the conduction of the scoping review, and Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews (PRISMA-ScR) (2018) will be used to organize and structure the review. PubMed, Web of Science, Scopus, ScienceDirect and Google Scholar will be used to search for literature. Obtained studies will be screened for eligibility based on predefined exclusion criteria. A narrative synthesis of eligible studies will be performed, after tabulating the extracted data from existing literature, to answer the research questions. ETHICS AND DISSEMINATION: Ethical approval is not required for this scoping review. Findings will be disseminated through conference presentations, publication in a peer-reviewed journal, and discussions among professional networks in the research domain combining neuroscience and information and communications technology (ICT). REGISTRATION DETAILS: This protocol has been registered on Open Science Framework (OSF). Relevant materials and potential following updates are available at https://osf.io/aqmyu.

Liposome-mediated small RNA delivery to convert the macrophage polarity: A novel therapeutic approach to treat inflammatory uterine disease.

Macrophages are present in all tissues for maintaining tissue homeostasis, and macrophage polarization plays a vital role in alleviating inflammation. Therefore, specific delivery of polarization modulators to macrophages in situ is critical for treating inflammatory diseases. We demonstrate that a size-controlled miRNA-encapsulated macrophage-targeting liposomes (miR/MT-Lip) specifically targets macrophages to promote M1-to-M2 polarization conversion, alleviating inflammation without cytotoxicity. miR/MT-Lip, approximately 1.2 µm, showed excellent internalization through phagocytosis and/or macropinocytosis in macrophages. miR-10a/MT-Lip, but not scramble miR-Fluorescein amidite (FAM)/MT-Lip as control, effectively converted the polarization of lipopolysaccharide (LPS)-induced M1 macrophages to M2 in vitro. When miR-10a/MT-Lip was intravenously delivered to mice insulted with LPS for inflammation, the proportion of M2 macrophages was significantly increased without disturbing the population of other immune cells. Furthermore, scramble miR-FAM/MT-Lip was mainly detected in macrophages, but not other immune cells. When our miR/MT-Lip was administered to mice with Asherman's syndrome that suffer from infertility because of sterile uterine inflammation, macrophage-specific targeting of miR-10a/MT-Lip facilitated M1-to-M2 conversion for angiogenesis in the impaired uterus, resulting in restoration of healthy uterine conditions. The results indicate that our MT-Lip encapsulating small RNAs has excellent potential to treat various inflammatory disorders by fine-tuning macrophage polarization in vivo without any side effects.

The Role of Extracellular Vesicles in Optic Nerve Injury: Neuroprotection and Mitochondrial Homeostasis.

Stem cell therapies hold great promise as alternative treatments for incurable optic nerve disorders. Although mesenchymal stem cells exhibit various tissue regeneration and recovery capabilities that may serve as valuable therapies, the clinical applications remain limited. Thus, we investigated the utility of extracellular vesicles (EVs) from human placenta-derived mesenchymal stem cells (hPSCs) in this context. Hypoxically preconditioned hPSCs (HPPSCs) were prepared via short-term incubation under 2.2% O2 and 5.5% CO2. The EVs were then isolated. R28 cells (retinal precursor cells) were exposed to CoCl2 and treated with EVs for 24 h. Cell proliferation and regeneration were measured using a BrdU assay and immunoblotting; ATP quantification revealed the extent of the mitochondrial function. The proteome was determined via liquid chromatography-tandem mass spectroscopy. Differentially expressed proteins (DEPs) were detected and their interactions identified. HPPSC_EVs functions were explored using animal models of optic nerve compression. HPPSC_EVs restored cell proliferation and mitochondrial quality control in R28 cells damaged by CoCl2. We identified DEPs (p < 0.05) that aided recovery. The mitochondrial DEPs included LONP1; PARK7; VDAC1, 2, and 3; HSPD1; and HSPA9. EVs regulated the levels of mitophagic proteins in R28 cells injured by hypoxia; the protein levels did not increase in LONP1 knockdown cells. LONP1 is a key mediator of the mitophagy that restores mitochondrial function after hypoxia-induced optic nerve injury.

Fly Ash-Incorporated Polystyrene Nanofiber Membrane as a Fire-Retardant Material: Valorization of Discarded Materials.

Reusing or recycling waste into new useful materials is essential for environmental protection. Herein, we used discarded polystyrene (PS) and fly-ash (FA) particles and a fabricated fly-ash incorporated polystyrene fiber (FA/PS fiber) composite. The electrospinning process produced continuous PS fibers with a good distribution of FA particles. The prepared nanofibers were characterized by state-of-the-art techniques. The performances of the composite nanofibers were tested for fire-retardant applications. We observed that the incorporation of FA particles into the PS fibers led to an improvement in the performance of the composite as compared to the pristine PS fibers. This study showed an important strategy in using waste materials to produce functional nanofibers through an economical procedure. We believe that the strategy presented in this paper can be extended to other waste materials for obtaining nanofiber membranes for various environmental applications.

Advancements in MXene-Polymer Nanocomposites in Energy Storage and Biomedical Applications.

MXenes are 2D ceramic materials, especially carbides, nitrides, and carbonitrides derived from their parent 'MAX' phases by the etching out of 'A' and are famous due to their conducting, hydrophilic, biocompatible, and tunable properties. However, they are hardly stable in the outer environment, have low biodegradability, and have difficulty in drug release, etc., which are overcome by MXene/Polymer nanocomposites. The MXenes terminations on MXene transferred to the polymer after composite formation makes it more functional. With this, there is an increment in photothermal conversion efficiency for cancer therapy, higher antibacterial activity, biosensors, selectivity, bone regeneration, etc. The hydrophilic surfaces become conducting in the metallic range after the composite formation. MXenes can effectively be mixed with other materials like ceramics, metals, and polymers in the form of nanocomposites to get improved properties suitable for advanced applications. In this paper, we review different properties like electrical and mechanical, including capacitances, dielectric losses, etc., of nanocomposites more than those like Ti3C2Tx/polymer, Ti3C2/UHMWPE, MXene/PVA-KOH, Ti3C2Tx/PVA, etc. along with their applications mainly in energy storing and biomedical fields. Further, we have tried to enlist the MXene-based nanocomposites and compare them with conducting polymers and other nanocomposites. The performance under the NIR absorption seems more effective. The MXene-based nanocomposites are more significant in most cases than other nanocomposites for the antimicrobial agent, anticancer activity, drug delivery, bio-imaging, biosensors, micro-supercapacitors, etc. The limitations of the nanocomposites, along with possible solutions, are mentioned.

Identification of the associations between genes and quantitative traits using entropy-based kernel density estimation.

Genetic associations have been quantified using a number of statistical measures. Entropy-based mutual information may be one of the more direct ways of estimating the association, in the sense that it does not depend on the parametrization. For this purpose, both the entropy and conditional entropy of the phenotype distribution should be obtained. Quantitative traits, however, do not usually allow an exact evaluation of entropy. The estimation of entropy needs a probability density function, which can be approximated by kernel density estimation. We have investigated the proper sequence of procedures for combining the kernel density estimation and entropy estimation with a probability density function in order to calculate mutual information. Genotypes and their interactions were constructed to set the conditions for conditional entropy. Extensive simulation data created using three types of generating functions were analyzed using two different kernels as well as two types of multifactor dimensionality reduction and another probability density approximation method called m-spacing. The statistical power in terms of correct detection rates was compared. Using kernels was found to be most useful when the trait distributions were more complex than simple normal or gamma distributions. A full-scale genomic dataset was explored to identify associations using the 2-h oral glucose tolerance test results and γ-glutamyl transpeptidase levels as phenotypes. Clearly distinguishable single-nucleotide polymorphisms (SNPs) and interacting SNP pairs associated with these phenotypes were found and listed with empirical p-values.