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An open challenge in human genetics is to better understand the systems-level impact of genotype variation on developmental cognition. To characterize the genetic underpinnings of peri-adolescent cognition, we performed genotype–phenotype and systems analysis for binarized accuracy in nine cognitive tasks from the Philadelphia Neurodevelopmental Cohort (~2,200 individuals of European continental ancestry aged 8–21 years). We report a region of genome-wide significance within the 3′ end of the Fibulin-1 gene (P = 4.6 × 10−8), associated with accuracy in nonverbal reasoning, a heritable form of complex reasoning ability. Diffusion tensor imaging data from a subset of these participants identified a significant association of white matter fractional anisotropy with FBLN1 genotypes (P

The reach of nanotechnology has permeated into a range of disciplines and systematically revolutionized many manufacturing techniques. Today, nanoparticles are fabricated using varied approaches, each with its pros and cons. Of them, the green synthesis approach has been very effective in terms of overall economics and the stability of nanoparticles. The current study investigates the use of the leaf extract of Bridelia retusa for the synthesis of iron oxide nanoparticles. Typical of these nanoparticles, no specific peak was discernible on employing UV–visible spectroscopy. The size, morphological features, and crystallinity of the nanoparticles were determined by employing scanning electron microscopy and electron diffraction spectroscopy. Almost uniformly sized at 38.58 nm, the nanoparticles were spherical, constituting elemental iron at 11.5% and elemental oxygen at 59%. Their relative composition confirmed the nanoparticles to be iron oxide. X-ray diffraction studies showed the particles to be hexagonal and rhombohedral, estimating the crystallite size at 24.27 nm. BET analysis put the pore volume at 0.1198 cm3/g and pore diameter at 7.92 nm. The unique feature of the nanoparticles was that the specific surface area was 75.19 m2/g, which is more than 12 times higher than commercial α-Fe2O3. The participation of a variety of biochemicals in the leaf extract towards the reduction-cum-stabilization was confirmed using FTIR analysis. The Fenton-like catalytic activity of the nanoparticles was put to test by attempting to degrade crystal violet dye, which was completely achieved in 270 min. The kinetics of the degradation was also modelled in the study.

Zinc oxide nanoflowers (ZnONFs) were prepared by employing the pod extract of Peltophorum pterocarpum as a green resource and characterized by various methods. UV–vis spectrum displayed a peak at 361 nm which confirmed the formation of ZnO nanoparticles. The optical band gap was calculated as 3.43 eV. FE-SEM images exposed the flower-like morphology and EDX portrayed strong signals for Zn and O. XRD studies substantiated signature peaks for the wurtzite phase of ZnONFs and the lattice parameters matched well with the literature. Mesoporous nature was confirmed by BET analysis which yielded a high specific surface area of 19.61 m2/g. FTIR bands at 420.48 and 462.92 cm−1affirmed the Zn and O bonding vibrations. The photocatalytic potential of the ZnONFs was successfully examined for the removal of methylene blue dye under natural solar light. The experimental data were fitted to Langmuir–Hinshelwood’s first-order equation and the kinetic constant was calculated as 0.0114 min–1.

In the current work, the leaf extract of Bridelia retusa was used for the first time to synthesize zinc oxide nanoparticles (ZnONPs). A zinc nanoparticle-specific 364-nm peak was discerned via UV–Vis studies with a typical bandgap energy of 3.41 eV. FE-SEM micrographs revealed flower-shaped structure of the ZnONPs. EDS analysis corroborated the presence of zinc and oxygen. XRD spectrum established the wurtzite structure, sized at 11.06 nm. The mesoporous texture (4.89 nm) of the nanoparticles was deduced from BET analysis, proving a higher specific surface area than commercial ZnONPs. FTIR spectroscopy resulted in absorption bands typical for ZnONPs. Within a span of 165 min, under solar irradiation, the ZnONPs facilitated the photocatalytic degradation of Rhodamine B dye upto 94.74%. Exhibiting pseudo-first-order kinetics, the process had a degradation constant of 0.0109 min−1. It was concluded that numerous factors led to the high degradation efficiency. High values of bandgap energy and specific surface area, along with the mesoporous and crystalline nature of the ZnONPs led to the observed effect. The ZnONPs were also stabilized by the phytochemicals in the B. retusa leaves. The study is thus able to successfully demonstrate the huge potential in the field of environmental nanoremediation. The viability of using ZnONPs as solar photocatalysts for treating dye-laden industrial wastewater was thus attested.

The growth of multi-omic tumour profile datasets along with knowledge of genome regulatory networks has created an unprecedented opportunity to advance precision oncology. Achieving this goal requires computational methods that can make sense of and combine heterogeneous data sources. Interpretability and integration of prior knowledge is of particular relevance for genomic models to minimize ungeneralizable models, promote rational treatment design, and make use of sparse genetic mutation data. While networks have long been used to capture genomic interactions at the levels of genes, proteins, and pathways, the use of networks in precision oncology is relatively new. In this chapter, I provide an introduction to network-based approaches used to integrate multi-modal data sources for patient stratification and patient classification. There is a particular emphasis on methods using patient similarity networks (PSNs) as part of the design. I separately discuss strategies for inferring driver mutations from individual patient mutation data. Finally, I discuss challenges and opportunities the field will need to overcome to achieve its full potential, with an outlook towards a clinic of the future.

In the present study, magnetite nanoparticles (Fe

High pressure injuries to the oral cavity and oropharynx, like water jets, are surgical emergencies. Such injuries are commonly reported while cleaning clogged pipes. This is a report of an adult male with water jet injury to larynx and hypopharynx. Based on the results of flexible laryngoscopy and contrast-enhanced CT, this case was managed with suspension microlaryngoscopy and extensive debridement of the necrosed tissue under general anesthesia. Following this, the patient recovered with minimal residual hoarseness which eventually resolvedover six months. Keywords: Water jet injuries, Oropharynx, Debridement, Hoarseness, Microlaryngoscopy.

Calcium hydroxide nanoadsorbent was prepared from waste bivalve clamshells and used for the adsorptive removal of Acid blue 113 (AB 113) dye. The morphology, elemental nature, functional groups, and thermal stability of the nanoadsorbent were characterized by various methods. The nanoadsorbent had a high monolayer adsorption capacity (153.53 mg/g) for AB 113 dye. Langmuir and Temkin isotherms better fitted (R

In this study, magnetite nanoparticles (MNPs) were synthesized using the seaweed - Ulva prolifera, an amply found marine source in the Western coastal regions of India. The surface and other properties of MNPs were characterized by many sophisticated methods. Spherical nanoclusters were observed in the FESEM image and iron and oxygen elements were seen in EDS results. XRD peaks were consistent with magnetite standards and MNPs had good crystallinity. FTIR portrayed the specific signals for MNPs and TGA profile ascertained the thermal stability. Magnetic saturation of 41.84 emu/g with negligible hysteresis loop substantiated the superparamagnetism. XPS pointed out the presence of Fe and O with oxidation states specific for MNPs, and the results were consistent with EDS. BET revealed a high specific surface area (144.98 m

Nanotechnology is considered the budding discipline in various fields of science and technology. In this review, the various synthesis methods of iron and iron oxide nanoparticles were summarised with more emphasis on green synthesis - a sustainable and eco-friendly method. The mechanism of green synthesis of these nanomaterials was reviewed in recent literature. The magnetic properties of these nanomaterials were briefed which makes them unique in the family of nanomaterials. An overview of various removal methods for the pollutants such as dye, heavy metals, and emerging contaminants using green synthesized iron and iron oxide nanoparticles is discussed. The mechanism of pollutant removal methods like Fenton-like degradation, photocatalytic degradation, and adsorption techniques was also detailed. The review is concluded with the challenges and possible future aspects of these nanomaterials for various environmental applications.

The leaf extract of Muntingia calabura is being first reported to be used for the synthesis superparamagnetic hematite nanoparticles by following the green-chemistry approach. Field Emission - Scanning Electron Microscopic image revealed the formation of irregular nano spheroids averaging at 48.57 nm in size and characteristic of Fe and O atoms, as revealed by Energy Dispersive X-Ray spectrum. X-ray diffraction analysis results proved the crystallinity of hematite diffraction planes with crystallite sizes averaging at 30.68 nm. The lattice parameter values stayed concordant with the literature. The superparamagnetic nature was attested by the high value of saturation magnetism (2.20 emu/g) with negligible coercivity and retentivity. Fourier Transform Infrared Spectroscopy results affirmed numerous moieties involved in the synthesis of hematite nanoparticles and the existence of signature Fe-O bands. Thermogravimetric analysis studies portrayed the thermal behavior nanoparticles with 28% weight loss and thermal stability was attained after 700 °C. X-ray photoelectron spectroscopy analysis confirmed the valence states of Fe and O in the hematite nanoparticles and ascertained the purity. The mesoscopic structure was revealed by Brunauer-Emmett-Teller studies with considerable surface area (112.50 m

For the first time, zinc oxide nanoparticles (ZnONPs) were synthesized using the aqueous extract of Peltophorum pterocarpum leaves by the reduction of zinc acetate. The phenolic compounds present in the leaf extract reduced zinc acetate to ZnONPs. The synthesis process was visually monitored and a strong absorption peak observed at 365 nm in UV–vis spectrum confirmed the formation of ZnONPs. The band gap energy was estimated as 3.39 eV. FE-SEM image revealed discrete flower-shaped ZnONPs and characteristic peaks for zinc and oxygen were observed in EDS spectrum. Hexagonal wurtzite structure was confirmed in XRD spectrum and the crystallite size was calculated as 11.64 nm. In addition, the lattice parameter values were consistent with the standard values for ZnONPs. BET analysis affirmed the mesoporous structure (pore diameter = 10.77 nm) with a relatively high surface area (13.56 m2/g). The thermal stability of the ZnONPs was evidenced from a TGA curve in which only 12% weight loss was observed. The specific functional groups responsible for reduction and capping of ZnONPs were denoted in FTIR spectrum. A sharp band at 425 cm–1 indicated the zinc-oxygen stretching. The photocatalytic potential of ZnONPs was evidenced by the degradation of methylene blue (MB) dye under sunlight irradiation. It was possible to degrade 95% of the dye within 120 min. Therefore, the synthesized ZnONPs can be used as photocatalysts for the degradation of dyes from wastewater.

Magnetic activated charcoal/Fe

The present work reports the study on the green synthesis of hydroxyapatite (HAP) nanoadsorbents using Peltophorum pterocarpum pod extract. HAP nanoadsorbents were characterized by using FESEM, EDS, TEM, XRD, FTIR, XPS, and BET analyses. The results highlighted the high purity, needle-like aggregations, and crystalline nature of the prepared HAP nanoadsorbents. The surface area was determined as 40.04 m

Introduction: Our goal is to develop interpretable, prognostic models for Group 3/4 medulloblastoma (G3/4 MB) and PFA ependymomas (PFA-EP) using brain tumor DNA methylomes. Our models use prior knowledge of genome regulation and may identify cellular processes that help develop molecular therapies. We previously developed a classifier algorithm, netDx, which uses similarity networks to integrate heterogeneous patient data and predict outcome1. netDx demonstrates excellent performance and allows measures to be grouped into biologically meaningful features (e.g. grouping genes into pathway features). Ependymoma Methods: We predicted survival in PFA-EP using 569 methylomes2 (Illumina 450K). Using netDx, we evaluated a model that grouped CpG-level methylation into sets reflecting 25 cell types from the developing human cerebellum, 3 chromatin states, EZH2 binding sites, and brain super enhancers (80:20 train/test split, feature selection >=8/10; 10 splits). This model was compared to a baseline lacking prior knowledge. Preliminary Results: Organizing methylomes by prior knowledge significantly improves prognostic prediction (Table 1, p < 5x10-3, one-sided WMW). Features that predict prognosis are consistent with known dysregulation in PFA-EP2 (Table 1). G3/4 MB Methods: We predicted binarized survival using 285 methylomes3 (Illumina 450K), using identical methods as above. Preliminary results: Tumor methylomes carry predictive signal for survival prediction (Table 1), consistent with previous findings. We are currently evaluating the effect of including prior knowledge. Interim Conclusion: Prior knowledge can improve survival prediction in PFA-EP and identifies features reflecting tumor biology. We are interested in extending interpretable modeling to other tumours.1. Pai et al. (2019) Mol Sys Biol. 15. 2. Pajtler et al. (2018) Acta Neuropathol. 136. 3. Northcott et al. (2017) Nature 547. Table 1. Average model performance and top features. Dataset Predictor design AUPR (mean+/- SD, 10 train/test splits) Predictive features PFA-EP; 252 good/317 poor survivors2 DNAm, no prior knowledge 64.2 +/- 2.3 n/a * Covariates: CXOrf67 mutation status, sex DNAm, prior knowledge* 67.5 +/- 3.5(p < 5x10-3; one-sided WMW test compared to baseline model) CXOrf67mut, methylation in: {H3K9me3 sites; marker genes for ependymal cells of choroid plexus; marker genes for multiple interneuron classes} G3/4 MB: 146 good/139 poor survivors3 DNAm, no prior knowledge 0.61 +/- 6.3 n/a ** Covariates: age, sex DNAm, prior knowledge** In progress Citation Format: Indy Ng, Alexander Fricke, Shraddha Pai. Predicting prognosis in PFA ependymoma and group 3/4 medulloblastoma methylomes using interpretable epigenetic models [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2505.

Aqueous two-phase system (ATPS) is long seen as a technique that promotes higher purity and yield in a single step. It is witnessing increased acceptance as a preferred choice for combined goals of concentration, separation and purification of a target product, be it industrially valuable or environmentally contaminating. Purification of biomolecules like enzymes, proteins, nucleic acids, viruses, etc. has been the forte of ATPS. Currently, the technique is used for concentrating the toxic fractions from diverse industrial let offs, from food, dairy, beverage, pharmaceuticals, agriculture, dyeing, tannery and metal-processing industries. Apart from being simple, efficient, rapid, flexible, economical, and biocompatible, the selectivity, purity and yield are on par and sometimes higher than the traditional downstream steps. From an industrial angle too, problems related to scale-up of ATPS are being actively addressed. Many novel approaches are being added by way of varying ATPS components to increase the yield and purity. Another case in point is the inclusion of optimization techniques for zeroing in on the precise setting of the operating parameters. With increasing impetus to the approach, we attempt to draw attention from academia and industries, alike, that are developing novel tweaks to the currently existing practices in ATPS. This review aims to assess and evaluate the different types of ATPS that have been used for the recovery of valuables and contaminants from industrial waste discharges.

Clinical research and practice in the 21(st) century is poised to be transformed by analysis of computable electronic medical records and population-level genome-scale patient profiles. Genomic data captures genetic and environmental state, providing information about heterogeneity in disease and treatment outcome, but genomic-based clinical risk scores are limited. Achieving the goal of routine precision medicine that takes advantage of this rich genomics data will require computational methods that support heterogeneous data, have excellent predictive performance, and ideally, provide biologically-interpretable results. Traditional machine-learning approaches excel at performance, but often have limited interpretability. Patient similarity networks are an emerging paradigm for precision medicine, in which patients are clustered or classified based on their similarities in various features, including genomic profiles. This strategy is analogous to standard medical diagnosis, has excellent performance, is interpretable, and can preserve patient privacy. We review new methods based on patient similarity networks, including Similarity Network Fusion for patient clustering and netDx for patient classification. While these methods are already useful, much work is required to improve their scalability for contemporary genetic cohorts, optimize parameters, and incorporate a wide range of genomics and clinical data. The coming five years will provide an opportunity to assess the utility of network-based algorithms for precision medicine.

Magnetic activated charcoal/Fe2O3 nanocomposite (AC/Fe2O3NC) was fabricated using Spondias dulcis leaf extract by a facile method and used for the adsorptive removal of 2,4-Dichlorophenoxyacetic acid (2,4-D) from aqueous solutions for the first time. The nanocomposite was characterized by methods such as FE-SEM, EDS, XRD, FTIR, TGA, VSM, and BET to identify and confirm the surface morphology, elemental composition, crystalline nature, functional groups, thermal stability, magnetic behavior, and surface area respectively. Box-Behnken Design (BBD) – an optimization method, which belongs to the Response surface methodology (RSM) and a modeling tool – Artificial Neural Network (ANN) were employed to design, optimize and predict the relationship between the input parameters (pH, initial concentration of 2,4-D, time and agitation speed) versus the output parameter (adsorption efficiency of 2,4-D). Adsorption efficiency of 98.12% was obtained at optimum conditions (pH: 2.05, initial concentration: 32 ppm, contact time: 100 min, agitation speed: 130 rpm, temperature: 30 °C, and dosage: 0.2 g/L). The predictive ability of the ANN was superior (R2 = 0.99) than the quadratic model, given by the RSM (R2 = 0.93). The equilibrium data were best-fitted to Langmuir isotherm (R2 = 0.9944) and the kinetics obeyed pseudo-second-order model (R2 = 0.9993) satisfactorily. Thermodynamic studies revealed the spontaneity and exothermic nature of adsorption. The maximum adsorption capacity, qm was found to be 255.10 mg/g, substantially larger than the reported values for 2,4-D adsorption by other magnetic nanoadsorbents. Therefore, this nanoadsorbent may be utilized as an excellent alternative for the elimination of 2,4-D from the waterbodies.

Metal nanoparticles have lately been considered as a very promising material in a host of applications such as medicine, catalysis, energy, electronics and environmental remediation. Their green synthesis is currently driving the trend owing to operational convenience and product stability. The approach is simple, rapid, ecofriendly and compatible with the biologically-derived molecules. The present study describes the silver nanoparticle synthesis using the whole nut extract of Arachis hypogaea (peanut). Upon using UV–visible spectroscopy to confirm the actual realization of the nanoparticles, a characteristic peak was detected at 435 nm. The nanoparticles were then analyzed using scanning electron microscopy (for morphological imaging and size confirmation), energy-dispersive X-ray spectroscopy (for element-wise composition) and X-ray diffraction (for verifying crystallinity). Investigation using FT-IR spectroscopy confirmed the presence of phytochemicals that would be responsible for the reduction (mono-to zero-valent silver). Dynamic light scattering revealed the particle size profiling in the preparation and confirmed the particles were mono-disperse. It also provided a zeta potential of −34.6 mV, implying that the silver nanoparticles were stable. The work concluded with the catalysis based application of the synthesized nanoparticles towards environmental remediation, in the presence of NaBH4. The degradation of the two commercial fabric dyes, acid red 88 and acid blue 113 was achieved in the experimental study.

Dye removal from wastewater is of prominence due to its hostile effects on human health and the environment. The complex structure of the dye molecule is responsible for its difficulty in removal. Adsorption is found to be a promising technique to eliminate dye wastes due to its high removal capacity at low concentration. Among different adsorbents used, hydroxyapatite is a biocompatible adsorbent that is relatively efficient in both anionic and cationic dye removal. Recently, modification of hydroxyapatite by doping with other materials to increase its removal efficiency has gained much attention. This review summarizes compilation of recent literature on the removal of anionic and cationic dye by different hydroxyapatite nanocomposites, comparison of adsorption capacities of different hydroxyapatite nanocomposites, the possible adsorption mechanism of removal of dyes, the general isotherm, and kinetic and thermodynamic studies explaining the type of adsorption and the characteristics, advantages, and limitations of adsorbents.

An open challenge in human genetics is to better understand the link between genotype variation and the various molecular, cellular, anatomical and physiological systems that it can affect. To address this challenge, we performed genotype-phenotype-systems analysis for accuracy in nine cognitive tasks from the Philadelphia Neurodevelopmental Cohort (3,319 individuals aged 8-21 years). We report a region of genome-wide significance within the 3’ end of the FBLN1 gene (p=4.6×10−8), associated with nonverbal reasoning, a heritable form of complex reasoning ability. Integration of published brain-specific ‘omic maps reveals that FBLN1 shows greatest expression in the fetal brain, is a marker of neural progenitor cells, is differentially expressed in schizophrenia and increases genetic risk for bipolar disorder. These findings suggest that nonverbal reasoning and FBLN1 variation warrant further investigation in studies of neurodevelopmental disorders and psychosis. Using genotype-pathway analysis, we identify pathways related to development and to autonomic nervous system dysfunction associated with working memory accuracy. Top-ranking pathway genes include those genetically associated with multiple diseases with working memory deficits, such as schizophrenia and Parkinson’s disease, and that are also markers for specific brain cell types. Our findings identify novel molecular players involved in specific cognitive tasks and link variants to genes, pathways, cell types, diseases and drugs. This work advances the “molecules-to-behaviour” view of cognition, and provides a framework for using systems-level organization of data for other biomedical domains.

In the current study, the green synthesis of zinc oxide nanoparticles (ZnONPs) using the leaf extract of Cyanometra ramiflora and zinc acetate precursor is presented. The phyto-components of the extract aided the reduction and the formation of nanoparticles. The purified ZnONPs were characterized by UV–Vis spectroscopy, SEM, EDS, XRD, BET, and FTIR techniques. A sharp absorption maximum at 360 nm in the UV–Vis data affirmed the formation of ZnONPs. SEM image revealed the nanoflower morphology and EDS showed strong signals for zinc and oxygen elements. XRD spectrum confirmed the hexagonal wurtzite crystalline structure of size 13.33 nm. A significant large surface area of 16.27 m2/g with mesopores, was affirmed using BET analysis. FTIR substantiated the existence of the characteristic zinc and oxygen bonding vibrations at 557 cm−1, 511 cm−1 and 433 cm−1. The photocatalytic activity of the ZnONPs was examined using the pollutant dye, Rhodamine B. A remarkable degradation efficiency of 98% within 200 min was achieved under sunlight irradiation and a degradation constant of 0.017 min−1 was obtained. Therefore, ZnONPs synthesized using a cheap and abundant source – the leaf extract of C.ramiflora possibly will play a promising part in the degradation of toxic dyes present in the wastewater.

Patient classification has widespread biomedical and clinical applications, including diagnosis, prognosis and treatment response prediction. A clinically useful prediction algorithm should be accurate, generalizable, be able to integrate diverse data types, and handle sparse data. A clinical predictor based on genomic data needs to be easily interpretable to drive hypothesis-driven research into new treatments. We describe netDx, a novel supervised patient classification framework based on patient similarity networks. netDx meets the above criteria and particularly excels at data integration and model interpretability. As a machine learning method, netDx demonstrates consistently excellent performance in a cancer survival benchmark across four cancer types by integrating up to six genomic and clinical data types. In these tests, netDx has significantly higher average performance than most other machine-learning approaches across most cancer types and its best model outperforms all other methods for two cancer types. In comparison to traditional machine learning-based patient classifiers, netDx results are more interpretable, visualizing the decision boundary in the context of patient similarity space. When patient similarity is defined by pathway-level gene expression, netDx identifies biological pathways important for outcome prediction, as demonstrated in diverse data sets of breast cancer and asthma. Thus, netDx can serve both as a patient classifier and as a tool for discovery of biological features characteristic of disease. We provide a software complete implementation of netDx along with sample files and automation workflows in R.

The present work has attempted to use broken rice as an economical substrate for the solid-state fermentation (SSF) mediated by Monascus sanguineus NFCCI 2453 for red pigment production. UV–Vis spectral and FTIR analyses were employed for the confirmation of the red pigment production. Response surface methodology (RSM) was used to optimize four significant parameters (extraction time, ethanol concentration, liquid-to-solid ratio and agitation speed) for extracting red pigment from the fermented biomass. Results from ANOVA proved the developed model to be significant as the R2 value (0.9602) demonstrated that the experimental values matched well with the results, as predicted. The maximum red pigment yield of 143.3 ODU/gds was obtained with the optimal setting of the process parameters. The model was found to be accurate (99.3%) using validation experimental data. The study serves as a prelude for exploiting M. sanguineus for the efficient production of red pigment using a low-cost substrate.

In the current study, Thunbergia grandiflora (Bengal clock vine) leaf extract has been used as green-resource to prepare Fe3O4 nanoparticles. SEM image showed agglomerated spherical (25 nm) particles, and EDS ascertained the existence of elemental iron (between 6 – 7 k eV) and oxygen (at 0.5 keV). XRD and XPS designated signature peaks for Fe3O4. BET studies revealed a high specific surface area of 114.42 m2/g with mesoporous structure. FTIR showed the distinct band for iron-oxide at 542 cm−1. A very low coercivity (1.5812 Oe) and retentivity (2.216 memu/g) indicated the paramagnetic properties of Fe3O4 nanoparticles. Batch adsorption of Acid blue 113 considering several factors conceded 95% removal within 3.5 h of contact time at pH 2 with the adsorbent dosage of 1 g/L, the concentration of 25 mg/L, 150 rpm, and the temperature of 303 K. The pseudo-second-order equation was best suited for the adsorption data indicating chemisorption. Freundlich isotherm model indicated a good fit for the equilibrium data. Thermodynamic parameters indicated exothermicity and spontaneity of the adsorption process. The maximum sorption capacity gained under an optimized environment was 138.89 mg/g. Hence, this study convincingly recognized the feasibility of the green synthesized Fe3O4 adsorbent for efficient Acid blue 113 dye removal with a suggestively greater sorption capacity.

Mesoporous magnetite nanoparticles (Fe3O4NPs) were synthesized by using the leaf extract of Mussaenda erythrophylla (ME) by a cheap and simple method – green synthesis. The synthesized Fe3O4NPs@ME were characterized by various techniques. A strong absorption spectrum without any specific peak in the UV–vis image designated the formation of iron-containing nanoparticles. XRD image confirmed the presence of only magnetite and the purity was ascertained by the absence of other forms of iron-containing nanoparticles. The average crystallite size was calculated as 18.58 nm and the lattice parameter was 8.38 A which was close to the magnetite standards. FE-SEM image portrayed spherical aggregates and EDS showed signature peaks for Fe and O elements. XPS image showed the presence of peaks for oxygen, ferrous, and ferric ions which are consistent with magnetite along with carbon on the surface. Mesoporous structure (5.78 nm) was affirmed by BET results which showed a higher surface area (174.15 m2/g) than the commercial one. The FTIR bands obtained at 454.25 and 667.39 cm−1 corresponded to the distinctive Fe–O linkage, substantiating the formation of magnetite. The stability of the magnetite at very high temperature was validated by TGA results which showed a 15% total reduction in weight. The magnetite showed superparamagnetism with a low saturation magnetization value (5.14 emu/g) which confirmed the existence of non-magnetic surface layers arising from the phytomolecules residing in the leaf extract of M. erythrophylla. Hence, the pure, crystalline, and mesoporous Fe3O4NPs@ME with large surface area obtained by the above-mentioned facile procedure will surely make an impact in many areas such as catalysis, adsorption, and biomedical engineering.

The need for biomaterials is in ever-increasing demand for a plethora of applications nowadays. Hydroxyapatite (HAP) is a primary constituent of bones and teeth in vertebrates. HAP and organic/inorganic-coated-HAP composites are fabricated to mimic the natural properties and also endow it with special characteristics like high porosity, surface area, crystallinity, stability, mechanical properties and biocompatibility. These special features make them ideal biomaterial candidates to be employed in diverse biomedical applications such as surgical implants, bone grafts, drug delivery agents and environmental remediation to remove toxic dyes and heavy metals from wastewater. HAP and HAP-containing composites are synthesized by wet, dry and high temperature methods from phosphate and calcium precursors as well as from low-cost natural biowastes. The biowastes include vertebrate bones, egg shells and marine-shells whose usage is not only economical but also aids sustainability and provides value addition. The properties of the fabricated end-product depend on the type of the precursor used and the synthesis protocols employed. The review provides an insight into the various syn�thesis methods of HAP and HAP-containing composites. It also reviews the most recent developments in the environmental and biomedical applications.

In the current study, the synthesis of hydroxyapatite (HAP) and its composite by various techniques, are abridged highlighting the eco-friendly technique – a green synthesis that involves the use of eco-friendly solvents like water and precursor substitution by waste resources. Magnetic HAP plays a major role in the HAP composites because of the ease of recovery and reuse. This study also emphasizes the prowess of the adsorption technique for the removal of various pollutants such as heavy metals, dyes, and emerging pollutants. A detailed adsorption mechanism is explained to understand the possible reactions taking place between the adsorbent and the adsorbate. Recent literature regarding the adsorption of various environmental pollutants by HAP and its composites are reported to support the efficiency of the adsorption process.

Microporous α-Fe2O3 nanoparticles were synthesized by employing the extract of Spondias dulcis leaves by green-synthesis technique for the first time. The nanoparticles were characterized by many techniques. A continual absorption band without any peak in UV-vis spectrum and a strong signal for iron and oxygen atoms in EDS confirmed the formation of iron-oxide nanoparticles. Rod-like structures with few aggregations due to magnetic interactions were witnessed in FE-SEM image. Specific peaks belonging to α-Fe2O3 nanoparticles were observed in XRD spectrum, and they were very pure and crystalline with a mean particle diameter of 11.38 nm. XPS analysis confirmed oxidation state of Fe and O and portrayed the presence of α-Fe2O3. A relatively higher surface area (190.84 m2/g) than reported green-synthesized α-Fe2O3 nanoparticles has been obtained by BET analysis, and the pores were microscopic (0.465 nm) in nature. Signature bands for Fe-O (1136 cm−1) and organic moieties stretching vibrations were confirmed by FTIR spectrum. The point of zero charge was determined as 7.97 which is concordant with the published value for α-Fe2O3. The thermal stability was ascertained by TGA which showed 28% weight loss. The synthesized α-Fe2O3 were superparamagnetic with a very high saturation magnetization value of 34.46 emu/g. Besides, a probable mechanism for the synthesis of microporous α-Fe2O3 has been proposed. Therefore, the highly pure, crystalline, and microporous α-Fe2O3 with high surface area, synthesized by this green synthesis method could play a significant role in various fields.

Impaired neuronal processes, including dopamine imbalance, are central to the pathogenesis of major psychosis, but the molecular origins are unclear. Here we perform a multi-omics study of neurons isolated from the prefrontal cortex in schizophrenia and bipolar disorder (n = 55 cases and 27 controls). DNA methylation, transcriptomic, and genetic-epigenetic interactions in major psychosis converged on pathways of neurodevelopment, synaptic activity, and immune functions. We observe prominent hypomethylation of an enhancer within the insulin-like growth factor 2 (IGF2) gene in major psychosis neurons. Chromatin conformation analysis revealed that this enhancer targets the nearby tyrosine hydroxylase (TH) gene responsible for dopamine synthesis. In patients, we find hypomethylation of the IGF2 enhancer is associated with increased TH protein levels. In mice, Igf2 enhancer deletion disrupts the levels of TH protein and striatal dopamine, and induces transcriptional and proteomic abnormalities affecting neuronal structure and signaling. Our data suggests that epigenetic activation of the enhancer at IGF2 may enhance dopamine synthesis associated with major psychosis., Dopamine dysregulation is centrally linked to major psychosis. Here, the authors characterise the hypomethylation of an enhancer within the insulin-like growth factor 2 gene in neurons of patients with major psychosis and provide evidence that this enhancer targets the tyrosine hydroxylase gene, responsible for dopamine synthesis.

Dopamine dysregulation is central to the pathogenesis of diseases with major psychosis, but its molecular origins are unclear. In an epigenome-wide investigation in neurons, individuals with schizophrenia and bipolar disorder showed reduced DNA modifications at an enhancer in IGF2, which disrupted the regulation of the dopamine synthesis enzyme tyrosine hydroxylase and striatal dopamine levels in transgenic mice. Epigenetic control of this enhancer may be an important molecular determinant of psychosis.

A key challenge in the application of whole-genome sequencing (WGS) for clinical diagnostic and research is the high-throughput prioritization of functional variants in the non-coding genome. This challenge is compounded by context-specific genetic modulation of gene expression, and variant-gene mapping depends on the tissues and organ systems affected in a given disease; for instance, a disease affecting the gastrointestinal system would use maps specific to genome regulation in gut-related tissues. While there are large-scale atlases of genome regulation, such as GTEx and NIH Roadmap Epigenomics, the clinical genetics community lacks publicly-available stand-alone software for high-throughput annotation of custom variant data with user-defined tissue-specific epigenetic maps and clinical genetic databases, to prioritize variants for a specific biomedical application. In this work, we provide a simple software pipeline, called SNPnotes, which takes as input variant calls for a patient and prioritizes those using information on clinical relevance from ClinVar, tissue-specific gene regulation from GTEx and disease associations from the NHGRI-EBI GWAS catalogue. This pipeline was developed as part of SVAI Research's "Undiagnosed-1" event for collaborative patient diagnosis. We applied this pipeline to WGS-based variant calls for an individual with a history of gastrointestinal symptoms, using 12 gut-specific eQTL maps and GWAS associations for metabolic diseases, for variant-gene mapping. Out of 6,248,584 SNPs, the pipeline identified 151 high-priority variants, overlapping 129 genes. These top SNPs all have known clinical pathogenicity, modulate gene expression in gut tissues and have genetic associations with metabolic disorders, and serve as starting points for hypotheses about mechanisms driving clinical symptoms. Simple software changes can be made to customize the pipeline for other tissue-specific applications. Future extensions could integrate maps of tissue-specific regulatory elements, higher-order chromatin loops, and mutations affecting splice variants.