A primer on the use of machine learning to distil knowledge from data in biological psychiatry.

Applications of machine learning in the biomedical sciences are growing rapidly. This growth has been spurred by diverse cross-institutional and interdisciplinary collaborations, public availability of large datasets, an increase in the accessibility of analytic routines, and the availability of powerful computing resources. With this increased access and exposure to machine learning comes a responsibility for education and a deeper understanding of its bases and bounds, borne equally by data scientists seeking to ply their analytic wares in medical research and by biomedical scientists seeking to harness such methods to glean knowledge from data. This article provides an accessible and critical review of machine learning for a biomedically informed audience, as well as its applications in psychiatry. The review covers definitions and expositions of commonly used machine learning methods, and historical trends of their use in psychiatry. We also provide a set of standards, namely Guidelines for REporting Machine Learning Investigations in Neuropsychiatry (GREMLIN), for designing and reporting studies that use machine learning as a primary data-analysis approach. Lastly, we propose the establishment of the Machine Learning in Psychiatry (MLPsych) Consortium, enumerate its objectives, and identify areas of opportunity for future applications of machine learning in biological psychiatry. This review serves as a cautiously optimistic primer on machine learning for those on the precipice as they prepare to dive into the field, either as methodological practitioners or well-informed consumers.

A comprehensive exploration of the druggable conformational space of protein kinases using AI-predicted structures.

Protein kinase function and interactions with drugs are controlled in part by the movement of the DFG and ɑC-Helix motifs that are related to the catalytic activity of the kinase. Small molecule ligands elicit therapeutic effects with distinct selectivity profiles and residence times that often depend on the active or inactive kinase conformation(s) they bind. Modern AI-based structural modeling methods have the potential to expand upon the limited availability of experimentally determined kinase structures in inactive states. Here, we first explored the conformational space of kinases in the PDB and models generated by AlphaFold2 (AF2) and ESMFold, two prominent AI-based protein structure prediction methods. Our investigation of AF2's ability to explore the conformational diversity of the kinome at various multiple sequence alignment (MSA) depths showed a bias within the predicted structures of kinases in DFG-in conformations, particularly those controlled by the DFG motif, based on their overabundance in the PDB. We demonstrate that predicting kinase structures using AF2 at lower MSA depths explored these alternative conformations more extensively, including identifying previously unobserved conformations for 398 kinases. Ligand enrichment analyses for 23 kinases showed that, on average, docked models distinguished between active molecules and decoys better than random (average AUC (avgAUC) of 64.58), but select models perform well (e.g., avgAUCs for PTK2 and JAK2 were 79.28 and 80.16, respectively). Further analysis explained the ligand enrichment discrepancy between low- and high-performing kinase models as binding site occlusions that would preclude docking. The overall results of our analyses suggested that, although AF2 explored previously uncharted regions of the kinase conformational space and select models exhibited enrichment scores suitable for rational drug discovery, rigorous refinement of AF2 models is likely still necessary for drug discovery campaigns.

Combination of EZH2 and ATM inhibition in BAP1-deficient mesothelioma.

BACKGROUND: More than half of mesothelioma tumours show alterations in the tumour suppressor gene BAP1. BAP1-deficient mesothelioma is shown to be sensitive to EZH2 inhibition in preclinical settings but only showed modest efficacy in clinical trial. Adding a second inhibitor could potentially elevate EZH2i treatment efficacy while preventing acquired resistance at the same time. METHODS: A focused drug synergy screen consisting of 20 drugs was performed by combining EZH2 inhibition with a panel of anti-cancer compounds in mesothelioma cell lines. The compounds used are under preclinical investigation or already used in the clinic. The synergistic potential of the combinations was assessed by using the Bliss model. To validate our findings, in vivo xenograft experiments were performed. RESULTS: Combining EZH2i with ATMi was found to have synergistic potential against BAP1-deficient mesothelioma in our drug screen, which was validated in clonogenicity assays. Tumour growth inhibition potential was significantly increased in BAP1-deficient xenografts. In addition, we observe lower ATM levels upon depletion of BAP1 and hypothesise that this might be mediated by E2F1. CONCLUSIONS: We demonstrated the efficacy of the combination of ATM and EZH2 inhibition against BAP1-deficient mesothelioma in preclinical models, indicating the potential of this combination as a novel treatment modality using BAP1 as a biomarker.

Microwave Doping of Sulfur and Iron in ß12 Borophene.

Borophene, a 2D material exhibiting unique crystallographic phases like the anisotropic atomic lattices of ß12 and X3 phases, has attracted considerable attention due to its intriguing Dirac nature and metallic attributes. Despite surpassing graphene in electronic mobility, borophene's potential in energy storage and catalysis remains untapped due to its inherent electrochemical and catalytic limitations. Elemental doping emerges as a promising strategy to introduce charge carriers, enabling localized electrochemical and catalytic functionalities. However, effective doping of borophene has been a complex and underexplored challenge. Here, an innovative, one-pot microwave-assisted doping method, tailored for the ß12 phase of borophene is introduced. By subjecting dispersed ß12 borophene in dimethylformamide to controlled microwave exposure with sulfur powder and FeCl3 as doping precursors, S- and Fe doping in borophene can be controlled. Employing advanced techniques including high-resolution transmission electron microscopy, Raman spectroscopy, and X-ray photoelectron spectroscopy, confirm successful sulfur and iron dopant incorporation onto ß12 borophene is confirmed, achieving doping levels of up to 11 % and 13 %, respectively. Remarkably, S- and Fe-doped borophene exhibit exceptional supercapacitive behavior, with specific capacitances of 202 and 120 F g-1 , respectively, at a moderate current density of 0.25 A g-1 .

Deciphering the transcriptional network of the dendritic cell lineage.

Although much progress has been made in the understanding of the ontogeny and function of dendritic cells (DCs), the transcriptional regulation of the lineage commitment and functional specialization of DCs in vivo remains poorly understood. We made a comprehensive comparative analysis of CD8(+), CD103(+), CD11b(+) and plasmacytoid DC subsets, as well as macrophage DC precursors and common DC precursors, across the entire immune system. Here we characterized candidate transcriptional activators involved in the commitment of myeloid progenitor cells to the DC lineage and predicted regulators of DC functional diversity in tissues. We identified a molecular signature that distinguished tissue DCs from macrophages. We also identified a transcriptional program expressed specifically during the steady-state migration of tissue DCs to the draining lymph nodes that may control tolerance to self tissue antigens.

Coherent multi-band MIMO radar: robustness analysis to SSMF-based RF signal delivery.

A numerical evaluation is conducted to assess the impact of distributing radio frequency (RF) signals through optical fiber links on the performance of a coherent multi-band multiple-input multiple-output (MIMO) radar system. The analysis focuses on scenarios where the antennas are widely separated in comparison to the employed signal wavelengths. The development of a model to quantify the phase noise (PN) induced on each RF band due to the signal transmission through optical fiber links between the centralized base station and each radar peripheral is described. Monte Carlo simulation results are collected to estimate the key performance indicators (KPIs) for varying standard single-mode fiber (SSMF) length and different PN contributions. The main contributors to the PN are revealed to be chromatic dispersion (CD), double Rayleigh scattering (DRS), and mechanical vibrations. In a shipborne scenario, a significant performance degradation occurs only when the length of the fiber links reaches approximately 20 km. Further, the PN impact has also been studied in a shipborne scenario to analyze the robustness of the system for worse phase noise level assumptions. The results reveal excellent robustness of the proposed centralized acquisition and processing approach in the presence of both very long fiber links and economically employed RF oscillators.

Multi-omic integration reveals alterations in nasal mucosal biology that mediate air pollutant effects on allergic rhinitis.

BACKGROUND: Allergic rhinitis is a common inflammatory condition of the nasal mucosa that imposes a considerable health burden. Air pollution has been observed to increase the risk of developing allergic rhinitis. We addressed the hypotheses that early life exposure to air toxics is associated with developing allergic rhinitis, and that these effects are mediated by DNA methylation and gene expression in the nasal mucosa. METHODS: In a case-control cohort of 505 participants, we geocoded participants' early life exposure to air toxics using data from the US Environmental Protection Agency, assessed physician diagnosis of allergic rhinitis by questionnaire, and collected nasal brushings for whole-genome DNA methylation and transcriptome profiling. We then performed a series of analyses including differential expression, Mendelian randomization, and causal mediation analyses to characterize relationships between early life air toxics, nasal DNA methylation, nasal gene expression, and allergic rhinitis. RESULTS: Among the 505 participants, 275 had allergic rhinitis. The mean age of the participants was 16.4 years (standard deviation = 9.5 years). Early life exposure to air toxics such as acrylic acid, phosphine, antimony compounds, and benzyl chloride was associated with developing allergic rhinitis. These air toxics exerted their effects by altering the nasal DNA methylation and nasal gene expression levels of genes involved in respiratory ciliary function, mast cell activation, pro-inflammatory TGF-ß1 signaling, and the regulation of myeloid immune cell function. CONCLUSIONS: Our results expand the range of air pollutants implicated in allergic rhinitis and shed light on their underlying biological mechanisms in nasal mucosa.

Efficient Control of Electron Localization and Probability Modulation with Synthesized Two-Color Intense Laser Pulses.

A coupled electron-nuclear dynamical study at attosecond time scale is performed on the HD+ and H2+ molecular ions under the influence of synthesized intense two-color electric fields. We have employed ω - 2ω and also, ω - 3ω two-color fields in the infrared/mid-infrared regime to study the different fragmentation processes originating from the interference of n - (n + i) (i = 1, 2) photon absorption pathways. The branching ratios corresponding to different photofragments are controlled by tuning the relative phase as well as intensity of the two-color pulses, while the effect of the initial nuclear wave function is also studied by taking an individual vibrational eigenstate or a coherent superposition of several eigenstates of HD+ and H2+. By comprehensive analysis, the efficacy of the two different types of synthesized two-color pulses (ω - 2ω and ω - 3ω) are analyzed with respect to one-color intense pulses in terms of controlling the probability modulation and electron localization asymmetry and compared with previous theoretical calculations and experimental findings. Through the detailed investigation, we have addressed which one is the major controlling knob to have better electron localization as well as probability modulation.

Remediation of pharmacophoric laboratory waste by using biodegradable carbon nanoparticles of bacterial biofilm origin.

Research laboratories generate a broad range of hazardous pharmacophoric chemical contaminants, from drugs to dyes used during various experimental procedures. In the recent past, biological methods have demonstrated great potential in the remediation of such contaminants. However, the presence of pharmacophoric chemicals containing antibiotics, xenobiotics, and heavy metals suppresses the growth and survivability of used microbial agents, thus decreasing the overall efficiency of biological remediation processes. Bacterial biofilm is a natural arrangement to counter some of these inhibitions but its use in a systemic manner, portable devices, and pollutant remediation plants post serious challenges. This could be countered by synthesizing a biodegradable carbon nanoparticle from bacterial biofilm. In this study, extracellular polymeric substance-based carbon nanoparticles (Bio-EPS-CNPs) were synthesized from bacterial biofilm derived from Bacillus subtilis NCIB 3610, as a model bacterial system. The produced Bio-EPS-CNPs were investigated for physiochemical properties by dynamic light scattering, optical, Fourier-transformed infrared, and Raman spectroscopy techniques, whereas X-ray diffraction study, scanning electron microscopy, and transmission electron microscopy were used to investigate structural and morphological features. The Bio-EPS-CNPs exhibited negative surface charge with spherical morphology having a uniform size of sub-100 nm. The maximum remediation of some laboratory-produced pharmacophoric chemicals was achieved through a five-round scavenging process and confirmed by UV/Vis spectroscopic analysis with respect to the used pharmacophore. This bioinspired remediation of used pharmacophoric chemicals was achieved through the mechanism of surface adsorption via hydrogen bonding and electrostatic interactions, as revealed by different characterizations. Further experiments were performed to investigate the effects of pH, temperature, stirring, and the protocol of scavenging to establish Bio-EPS-CNP as a possible alternative to be used in research laboratories for efficient removal of pharmacophoric chemicals by incorporating it in a portable, filter-based device.

Acute pancreatitis is characterized by generalized intestinal barrier dysfunction in early stage.

BACKGROUND AND AIMS: The role of intestinal-barrier in acute pancreatitis(AP) is poorly understood. We aimed to assess structural and functional changes in the intestinal-barrier in patients with early AP (time from onset<2 weeks) and the effect of enteral nutrition on them. METHODS: In this prospective observational study, patients with early AP not on enteral nutrition were compared with controls for baseline intestinal-permeability(lactulose: mannitol ratio(L:M)), endotoxinemia(serum IgM/IgG anti-endotoxin antibodies), bacterial-translocation(serum bacterial 16S rRNA) and duodenal epithelial tight-junction structure by immunohistochemistry(IHC) for tight-junction proteins(claudin-2,-3,-4, zonula occludens-1(ZO1), junctional adhesion molecule(JAM) and occludin) and electron microscopy. These parameters were reassessed after 2 weeks enteral feeding in a AP patients subset. RESULTS: 96 patients with AP(age: 38.0 ± 14.5 years; etiology: biliary[46.8%]/alcohol[39.6%]; severe:53.2%, mortality:11.4%) and 40 matched controls were recruited. Patients with AP had higher baseline intestinal permeability(median L:M 0.176(IQR 0.073-0.376) vs 0.049(0.024-0.075) in controls; p < 0.001) and more frequent bacteraemia(positive bacterial 16S rRNA in 24/48 AP vs 0/21 controls; p < 0.001) with trend towards higher serum endotoxinemia(median IgG anti-endotoxin 78(51.2-171.6) GMU/ml vs 51.2(26.16-79.2) in controls; p = 0.061). Claudin-2, claudin-3, ZO1 were downregulated in both duodenal crypts and villi while claudin-4 and JAM were downregulated in duodenal villi and crypts respectively. 22 AP patients reassessed after initiation of enteral nutrition showed trend towards improving intestinal permeability, serum endotoxinemia and bacteraemia, with significant improvement in claudin-2,-3 in duodenal villi. CONCLUSION: Patients with AP have significant disturbances in intestinal barrier structure and function in first 2 weeks from onset that persist despite institution of enteral nutrition.

Strong Laser Field-Driven Coupled Electron-Nuclear Dynamics: Quantum vs Classical Description.

We have performed a coupled electron-nuclear dynamics study of H2+ molecular ions under the influence of an intense few-cycle 4.5 fs laser pulse with an intensity of 4 × 1014 W/cm2 and a central wavelength of 750 nm. Both quantum and classical dynamical methods are employed in the exact similar initial conditions with the aim of head-to-head comparison of two methodologies. A competition between ionization and dissociation channel is explained under the framework of quantum and classical dynamics. The origin of the electron localization phenomena is elucidated by observing the molecular and electronic wave packet evolution pattern. By probing with different carrier envelope phase (CEP) values of the ultrashort pulse, the possibility of electron localization on either of the two nuclei is investigated. The effects of initial vibrational states on final dissociation and ionization probabilities for several CEP values are studied in detail. Finally, asymmetries in the dissociation probabilities are calculated and mutually compared for both quantum and classical dynamical methodologies, whereas Franck-Condon averaging over the initial vibrational states is carried out in order to mimic the existing experimental conditions.

Bioactive molecules from fungal endophytes and their applications in pharmaceutical industries: challenges and future scope.

Medicinal plants are an important source of bioactive compounds and have been used to isolate various bioactive compounds having industrial applications. The demand for plants derived bioactive molecules is increasing gradually. However, the extensive use of these plants to extract bioactive molecules has threatened many plant species. Moreover, extracting bioactive molecules from these plants is laborious, costly, and time-consuming. So, some alternative sources and strategies are urgently needed to produce these bioactive molecules similar to that of plant origin. However, the interest in new bioactive molecules has recently shifted from plants to endophytic fungi because many fungi produce bioactive molecules similar to their host plant. Endophytic fungi live in mutualistic association within the healthy plant tissue without causing disease symptoms to the host plant. These fungi are a treasure house of novel bioactive molecules having broad pharmaceutical, industrial, and agricultural applications. The rapid increase in publications in this domain over the last three decades proves that natural product biologists and chemists are paying great attention to the natural bioactive products from endophytic fungi. Though endophytes are source of novel bioactive molecules but there is need of advanced technologies like clustered regularly interspaced short palindromic repeats and CRISPR-associated protein 9 (CRISPR-Cas9) and epigenetic modifiers to enhance the production of compounds having industrial applications. This review provides an overview of the various industrial applications of bioactive molecules produced by endophytic fungi and the rationale behind selecting specific plants for fungal endophyte isolation. Overall, this study presents the current state of knowledge and highlights the potential of endophytic fungi for developing alternative therapies for drug-resistant infections.

Isolated pulmonary hemorrhage after electric shock: a rare phenomenon.

Any type of contact with electricity of low or high voltage can cause injury to the human body, with a variable effect on the body. Low-voltage injury is quite common worldwide, but there is very little information present in the available literature. The degree of organ damage depends on many factors, which include the duration of electric current exposure, current type, and nature of the affected tissue. The most common presentations are muscle injury, hyperkalemia, pulmonary edema, and rarely isolated diffuse pulmonary hemorrhage. We present a case of bilateral pulmonary hemorrhage due to electric shock with no visible signs of damage to the chest wall when exposed to a 220 V shock. The diagnosis was confirmed by fresh hemoptysis, chest imaging that showed bilateral perihilar ground glass opacities, and bronchoscopy findings. Given a life-threatening condition, a timely diagnosis is required, as massive hemoptysis can occlude the airways, leading to hypoxia and mortality.

Combined inhibition of EZH2 and ATM is synthetic lethal in BRCA1-deficient breast cancer.

BACKGROUND: The majority of BRCA1-mutant breast cancers are characterized by a triple-negative phenotype and a basal-like molecular subtype, associated with aggressive clinical behavior. Current treatment options are limited, highlighting the need for the development of novel targeted therapies for this tumor subtype. METHODS: Our group previously showed that EZH2 is functionally relevant in BRCA1-deficient breast tumors and blocking EZH2 enzymatic activity could be a potent treatment strategy. To validate the role of EZH2 as a therapeutic target and to identify new synergistic drug combinations, we performed a high-throughput drug combination screen in various cell lines derived from BRCA1-deficient and -proficient mouse mammary tumors. RESULTS: We identified the combined inhibition of EZH2 and the proximal DNA damage response kinase ATM as a novel synthetic lethality-based therapy for the treatment of BRCA1-deficient breast tumors. We show that the combined treatment with the EZH2 inhibitor GSK126 and the ATM inhibitor AZD1390 led to reduced colony formation, increased genotoxic stress, and apoptosis-mediated cell death in BRCA1-deficient mammary tumor cells in vitro. These findings were corroborated by in vivo experiments showing that simultaneous inhibition of EZH2 and ATM significantly increased anti-tumor activity in mice bearing BRCA1-deficient mammary tumors. CONCLUSION: Taken together, we identified a synthetic lethal interaction between EZH2 and ATM and propose this synergistic interaction as a novel molecular combination for the treatment of BRCA1-mutant breast cancer.

Dissociative ionization of the H2 molecule under a strong elliptically polarized laser field: carrier-envelope phase and orientation effect.

A coupled electron-nuclear dynamical study is performed to investigate the sub-cycle dissociation and ionization of the H2 molecule in a strong 750 nm 4.5 fs elliptically polarized laser pulse. A quasi-classical method is employed in which additional momentum-dependent potentials are added to the molecular Hamiltonian to account for the non-classical effects. The effect of molecular orientation with respect to the laser polarization plane on the probabilities of different dynamical channels and proton energy spectra has been examined. We demonstrate the 2D-control of proton anisotropy by manipulating the carrier-envelope phase of the pulse. We demonstrate that the quasi-classical method can capture the carrier-envelope phase effects in the dissociative ionization of the H2 molecule. Our results indicate that the classical models provide an efficient approach to study the mechanistic insights of strong-field molecular dynamics.

MetaClean: a machine learning-based classifier for reduced false positive peak detection in untargeted LC-MS metabolomics data.

INTRODUCTION: Despite the availability of several pre-processing software, poor peak integration remains a prevalent problem in untargeted metabolomics data generated using liquid chromatography high-resolution mass spectrometry (LC-MS). As a result, the output of these pre-processing software may retain incorrectly calculated metabolite abundances that can perpetuate in downstream analyses. OBJECTIVES: To address this problem, we propose a computational methodology that combines machine learning and peak quality metrics to filter out low quality peaks. METHODS: Specifically, we comprehensively and systematically compared the performance of 24 different classifiers generated by combining eight classification algorithms and three sets of peak quality metrics on the task of distinguishing reliably integrated peaks from poorly integrated ones. These classifiers were compared to using a residual standard deviation (RSD) cut-off in pooled quality-control (QC) samples, which aims to remove peaks with analytical error. RESULTS: The best performing classifier was found to be a combination of the AdaBoost algorithm and a set of 11 peak quality metrics previously explored in untargeted metabolomics and proteomics studies. As a complementary approach, applying our framework to peaks retained after filtering by 30% RSD across pooled QC samples was able to further distinguish poorly integrated peaks that were not removed from filtering alone. An R implementation of these classifiers and the overall computational approach is available as the MetaClean package at https://CRAN.R-project.org/package=MetaClean . CONCLUSION: Our work represents an important step forward in developing an automated tool for filtering out unreliable peak integrations in untargeted LC-MS metabolomics data.

Controlling the Ultrafast Dynamics of HD+ by the Carrier-Envelope Phases of an Ultrashort Laser Pulse: A Quasi-Classical Dynamics Study.

A theoretical study on the coupled electron-nuclear dynamics of HD+ molecular ions under ultrashort, intense laser pulses is performed by employing a well-established quasi-classical model. The influence of the laser carrier-envelope phase on various channel (H + D+, D + H+, and H+ + D+) probabilities is investigated at different laser field intensities. The carrier-envelope phase is found to govern the dissociation (H + D+ and D + H+) and Coulomb explosion (H+ + D+) channel probabilities. The kinetic energy release distributions of the fragments are also found to be sensitive to the carrier-envelope phase of the laser pulse. Our results are in agreement with the previously reported quantum dynamics studies and experiments.

Assessing computational predictions of the phenotypic effect of cystathionine-beta-synthase variants.

Accurate prediction of the impact of genomic variation on phenotype is a major goal of computational biology and an important contributor to personalized medicine. Computational predictions can lead to a better understanding of the mechanisms underlying genetic diseases, including cancer, but their adoption requires thorough and unbiased assessment. Cystathionine-beta-synthase (CBS) is an enzyme that catalyzes the first step of the transsulfuration pathway, from homocysteine to cystathionine, and in which variations are associated with human hyperhomocysteinemia and homocystinuria. We have created a computational challenge under the CAGI framework to evaluate how well different methods can predict the phenotypic effect(s) of CBS single amino acid substitutions using a blinded experimental data set. CAGI participants were asked to predict yeast growth based on the identity of the mutations. The performance of the methods was evaluated using several metrics. The CBS challenge highlighted the difficulty of predicting the phenotype of an ex vivo system in a model organism when classification models were trained on human disease data. We also discuss the variations in difficulty of prediction for known benign and deleterious variants, as well as identify methodological and experimental constraints with lessons to be learned for future challenges.

Deletion of insulin receptor in the proximal tubule and fasting augment albumin excretion.

The contribution of proximal tubules (PT) to albumin uptake is now well recognized, however, its regulation is understudied area. There are reports suggesting that insulin resistance is associated with the development of albuminuria in nondiabetic individuals. We have previously reported reduced insulin receptor (IR) expression in renal-tubular-epithelial cells, including PT in various models of insulin resistance. However, the effect of a physiological fall in insulin levels and the role for IR in PT in tubular albumin uptake is not clear. To address these gaps in our understanding, we estimated urine excretion and renal uptake of albumin in fasted and fed C57Bl/6 mice injected with fluorescein isothiocyanate (FITC)-albumin (5 µg/mL/kg body weight, intraperitoneal, n = 6 per group). In addition, we compared spot urine analysis from 33 clinically healthy humans after overnight fasting (when insulin levels are lower than in the fed state) and then at 2 hours after 75 g oral glucose challenge (postprandial). Fasted mice had attenuated renal uptake of FITC-albumin and higher excretion in urine, relative to fed mice ( P = 0.04). Moreover, a significant drop in urine albumin-to-creatinine ratio (ACR) and urine albumin concentration (UAC) was observed in the postprandial state in these subjects ( P = 0.001 and P = 0.017, for ACR and UAC, respectively). The drop was negatively associated with postprandial blood glucose levels (ρ = -0.36, P = 0.03 for ΔUAC and ρ = -0.34, P = 0.05 for ΔACR). To test the role of IR in PT, we analyzed 24-hour urine albumin excretion in male mice with targeted deletion of IR from PT (insulin receptor knockout [IRKO]) and their wild-type (WT) littermates ( n = 7 per group). IRKO mice had significantly higher 24-hour urine albumin excretion relative to WT. Moreover, kidneys from KO mice revealed reduced expression of megalin and cubulin proteins in the PT relative to the WT. We also demonstrated insulin (100 nM) induced albumin internalization in human proximal tubule cells (hPT) and this effect of insulin was attenuated in hydroxy-2-naphthalenylmethylphosphonic acid (100 µM), a tyrosine kinase inhibitor, pretreated hPT. Our findings revealed albumin excretion was attenuated by glucose administration to fasting individuals implying a regulatory role for insulin in PT albumin reabsorption. Thus albuminuria associated with insulin resistance/diabetes may relate not only to glomerular dysfunction but also to impairment in insulin-mediated reabsorption.

Nanotechnology-based recent approaches for sensing and remediation of pesticides.

Pesticides are meant to control and destroy the pests and weeds. They are classified into different categories on the basis their origin and type of pest they target. Chemical pesticides such as insecticides, herbicides and fungicides are commonly used in agricultural fields. However, the excessive use of these agrochemicals have adverse effects on environment such as reduced population of insect pollinators, threat to endangered species and habitat of birds. Upon consumption; chemical pesticides also cause various health issues such as skin, eye and nervous system related problems and cancer upon prolonged exposure. Various techniques in the past have been developed on the basis of surface adsorption, membrane filtration and biological degradation to reduce the content of pesticides. However, slow response, less specificity and sensitivity are some of the drawbacks of such techniques. In recent times, Nanotechnology has emerged as a helping tool for the sensing and remediation of pesticides. This review focuses on the use of this technology for the detection, degradation and removal of pesticides. Nanomaterials have been classified into nanoparticles, nanotubes and nanocomposites that are commonly used for detection, degradation and removal of pesticides. The review also focuses on the chemistry behind the sensing and remediation of pesticides using nanomaterials. Different types of nanoparticles, viz. metal nanoparticles, bimetallic nanoparticles and metal oxide nanoparticles; nanotubes such as carbon nanotubes and halloysite nanotubes have been used for the detection, degradation and removal of pesticides. Further, various enzyme-based biosensors for detection of pesticides have also been summarized.