Prediction of DNA methylation-based tumor types from histopathology in central nervous system tumors with deep learning.

Precision in the diagnosis of diverse central nervous system (CNS) tumor types is crucial for optimal treatment. DNA methylation profiles, which capture the methylation status of thousands of individual CpG sites, are state-of-the-art data-driven means to enhance diagnostic accuracy but are also time consuming and not widely available. Here, to address these limitations, we developed Deep lEarning from histoPathoLOgy and methYlation (DEPLOY), a deep learning model that classifies CNS tumors to ten major categories from histopathology. DEPLOY integrates three distinct components: the first classifies CNS tumors directly from slide images ('direct model'), the second initially generates predictions for DNA methylation beta values, which are subsequently used for tumor classification ('indirect model'), and the third classifies tumor types directly from routinely available patient demographics. First, we find that DEPLOY accurately predicts beta values from histopathology images. Second, using a ten-class model trained on an internal dataset of 1,796 patients, we predict the tumor categories in three independent external test datasets including 2,156 patients, achieving an overall accuracy of 95% and balanced accuracy of 91% on samples that are predicted with high confidence. These results showcase the potential future use of DEPLOY to assist pathologists in diagnosing CNS tumors within a clinically relevant short time frame.

Study of Correlated Motions to Detect the Conformational Transitions of the Intrinsically Disordered Sheep Prion Peptide.

Intrinsically disordered proteins (IDPs) are known for their random structural changes throughout their sequence based on the environment. The mechanism underlying these structural changes is difficult to explain. All biological processes are known to follow the direction through which they act. A study of the correlated motion can help to understand the direction of the change. Herein, we introduced the multivariate statistical analysis (MSA) technique to study the correlated motion of the peptide. The correlated motion of the sheep prion peptide was studied with the change in the temperature and solvent. These techniques helped to identify the contributing residual motions that helped to form the different secondary structures of the protein and also the triggering factors that drive these sorts of residual motions. The structural details match the experimentally reported data. It was found that the direction of the change of the secondary structure for this peptide shifted from the C-terminal to the N-terminal with an increase in the temperature. It was found that the involvement of the hydrophobic residues present at the C-terminal and the middle residues (residues 12-17) is responsible for forming a ß-sheet at the normal temperature. Hydration water was found to play an important role in this change. Insights gained from this study can be used to design strategies for desirable structural changes in the IDPs.

Molecular and clinicopathologic characteristics of CNS embryonal tumors with BRD4::LEUTX fusion.

Central nervous system (CNS) embryonal tumors are a heterogeneous group of high-grade malignancies, and the increasing clinical use of methylation profiling and next-generation sequencing has led to the identification of molecularly distinct subtypes. One proposed tumor type, CNS tumor with BRD4::LEUTX fusion, has been described. As only a few CNS tumors with BRD4::LEUTX fusions have been described, we herein characterize a cohort of 9 such cases (4 new, 5 previously published) to further describe their clinicopathologic and molecular features. We demonstrate that CNS embryonal tumor with BRD4::LEUTX fusion comprises a well-defined methylation class/cluster. We find that patients are young (4 years or younger), with large tumors at variable locations, and frequently with evidence of leptomeningeal/cerebrospinal fluid (CSF) dissemination. Histologically, tumors were highly cellular with high-grade embryonal features. Immunohistochemically, 5/5 cases showed synaptophysin and 4/5 showed OLIG2 expression, thus overlapping with CNS neuroblastoma, FOXR2-activated. DNA copy number profiles were generally flat; however, two tumors had chromosome 1q gains. No recurring genomic changes, besides the presence of the fusion, were found. The LEUTX portion of the fusion transcript was constant in all cases assessed, while the BRD4 portion varied but included a domain with proto-oncogenic activity in all cases. Two patients with clinical follow up available had tumors with excellent response to chemotherapy. Two of our patients were alive without evidence of recurrence or progression after gross total resection and chemotherapy at 16 and 33 months. One patient relapsed, and the last of our four patients died of disease one month after diagnosis. Overall, this case series provides additional evidence for this as a distinct tumor type defined by the presence of a specific fusion as well as a distinct DNA methylation signature. Studies on larger series are required to further characterize these tumors.

Potential prognostic determinants for FET::CREB fusion-positive intracranial mesenchymal tumor.

Intracranial mesenchymal tumor (IMT), FET::CREB fusion-positive is a provisional tumor type in the 2021 WHO classification of central nervous system tumors with limited information available. Herein, we describe five new IMT cases from four females and one male with three harboring an EWSR1::CREM fusion and two featuring an EWSR1::ATF1 fusion. Uniform manifold approximation and projection of DNA methylation array data placed two cases to the methylation class "IMT, subclass B", one to "meningioma-benign" and one to "meningioma-intermediate". A literature review identified 74 cases of IMTs (current five cases included) with a median age of 23 years (range 4-79 years) and a slight female predominance (female/male ratio = 1.55). Among the confirmed fusions, 25 (33.8%) featured an EWSR1::ATF1 fusion, 24 (32.4%) EWSR1::CREB1, 23 (31.1%) EWSR1::CREM, one (1.4%) FUS::CREM, and one (1.4%) EWSR1::CREB3L3. Among 66 patients with follow-up information available (median: 17 months; range: 1-158 months), 26 (39.4%) experienced progression/recurrences (median 10.5 months; range 0-120 months). Ultimately, three patients died of disease, all of whom underwent a subtotal resection for an EWSR1::ATF1 fusion-positive tumor. Outcome analysis revealed subtotal resection as an independent factor associated with a significantly shorter progression free survival (PFS; median: 12 months) compared with gross total resection (median: 60 months; p < 0.001). A younger age (< 14 years) was associated with a shorter PFS (median: 9 months) compared with an older age (median: 49 months; p < 0.05). Infratentorial location was associated with a shorter overall survival compared with supratentorial (p < 0.05). In addition, the EWSR1::ATF1 fusion appeared to be associated with a shorter overall survival compared with the other fusions (p < 0.05). In conclusion, IMT is a locally aggressive tumor with a high recurrence rate. Potential risk factors include subtotal resection, younger age, infratentorial location, and possibly EWSR1::ATF1 fusion. Larger case series are needed to better define prognostic determinants in these tumors.

Power-line interference and baseline wander elimination in ECG using VMD and EWT.

Electrocardiogram (ECG) is a critical biomedical signal and plays an imperative role in diagnosing cardiovascular disorders. During ECG data acquisition in clinical environment, noise is frequently present. Various noises such as powerline interference (PLI) and baseline wandering (BLW) distort the ECG signal which may lead to incorrect interpretation. Consequently, substantial emphasis has been dedicated to ECG denoising for reliable diagnosis and analysis. In this study, a novel hybrid ECG denoising method based on variational mode decomposition (VMD) and the empirical wavelet transform (EWT) is presented. For effective denoising using the VMD and EWT approach, the noisy ECG signal is decomposed within narrow-band variational mode functions (VMFs). The aim is to remove noise from these narrow-band VMFs. In current approach, the centre frequency of each VMF was computed and utilized to design an adaptive wavelet filter bank using EWT. This leads to effective removal of noise components from the signal. The proposed approach was applied to ECG signals obtained from the MIT-BIH Arrhythmia database. To evaluate the denoising performance, noise sources from the MIT-BIH Noise Stress Test Database (NSTDB) are used for simulation. The assessment of denoising performance in based on two key metrics: the percentage-root-mean-square difference (PRD) and the signal-to-noise ratio (SNR). The findings of the simulation experiment demonstrate that the suggested method has lower percentage root mean square difference and higher signal-to-noise ratio as compared to existing state of the art denoising methods. An average output SNR of 24.03 was achieved, along with a 5% reduction in PRD.

Exploring the Barriers in the Aggregation of a Hexadecameric Human Prion Peptide through the Markov State Model.

The prefibrillar aggregation kinetics of prion peptides are still an enigma. In this perspective, we employ atomistic molecular dynamics (MD) simulations of the shortest human prion peptide (HPP) (127GYMLGS132) at various temperatures and peptide concentrations and apply the Markov state model to determine the various intermediates and lag phases. Our results reveal that the natural mechanism of prion peptide self-assembly in the aqueous phase is impeded by two significant kinetic barriers with oligomer sizes of 6-9 and 12-13 peptides, respectively. The first one is the aggregation of unstructured lower-order oligomers, and the second is fibril nucleation, which impedes the further growth of prion aggregates. Among these two activation barriers, the second one is found to be dominant irrespective of the increase in temperature and peptide concentration. These lag phases are captured in all three different force-field parameters, namely, GROMOS-54a7, AMBER-99SB-ILDN, and CHARMMS 36m, at different concentrations. The GROMOS-54a7 and AMBER-99SB-ILDN force fields showed a comparatively higher percentage of ß-sheet formation in the metastable aggregate that evolved during the aggregation process. In contrast, the CHARMM-36m force field showed mostly coil or turn conformations. The addition of a novel catecholamine derivative (naphthoquinone dopamine (NQDA)) arrests the aggregation process between the lag phases by increasing the activation barrier for the Lag1 and Lag2 phases in all of the force fields, which further validates the existence of these lag phases. The preferential binding of NQDA with the peptides increases the hydration of peptides and eventually disrupts the organized morphology of prefibrillar aggregates. It reduces the dimer dissociation energy by -24.34 kJ/mol.

Phytochemicals and bioactive compounds effective against acute myeloid leukemia: A systematic review.

This systematic review identified various bioactive compounds which have the potential to serve as novel drugs or leads against acute myeloid leukemia. Acute myeloid leukemia (AML) is a heterogeneous hematopoietic malignancy that arises from the dysregulation of cell differentiation, proliferation, and cell death. The risk factors associated with the onset of AML include long-term exposure to radiation and chemicals such as benzene, smoking, genetic disorders, blood disorders, advancement in age, and others. Although novel strategies to manage AML, including a refinement of the conventional chemotherapy regimens, hypomethylating agents, and molecular targeted drugs, have been developed in recent years, resistance and relapse remain the main clinical problems. In this study, three databases, PubMed/MEDLINE, ScienceDirect, and Google Scholar, were systematically searched to identify various bioactive compounds with antileukemic properties. A total of 518 articles were identified, out of which 59 were viewed as eligible for the current report. From the data extracted, over 60 bioactive compounds were identified and divided into five major groups: flavonoids, alkaloids, organosulfur compounds, terpenes, and terpenoids, and other known and emerging bioactive compounds. The mechanism of actions of the analyzed individual bioactive molecules differs remarkably and includes disrupting chromatin structure, upregulating the synthesis of certain DNA repair proteins, inducing cell cycle arrest and apoptosis, and inhibiting/regulating Hsp90 activities, DNA methyltransferase 1, and histone deacetylase 1.

Growth Reaction of Gold Nanorods in the Presence of Mutated Peptides and Amine-Modified Single-Stranded Nucleic Acids.

Conformation of biomolecules like DNA, peptides and amino acids play vital role during nanoparticle growth. Herein, we have experimentally explored the effect of different noncovalent interaction between a 5'-amine modified DNA sequence (NH2 -C6 H12 -5'-ACATCAGT-3', PMR) and arginine during the seed-mediated growth reaction of gold nanorods (GNRs). Amino acid-mediated growth reaction of GNRs results in a snowflake-like gold nanoarchitecture. However, in case of Arg, prior incubation of GNRs with PMR selectively produces sea urchin-like gold suprastructures, via strong hydrogen bonding and cation-π interaction between PMR and Arg. This distinctive structure formation strategy has been extended to study the structural modulation caused by two structurally close α-helical RRR (Ac-(AAAAR)3 A-NH2 ) peptide and the lysine mutated KKR (Ac-AAAAKAAAAKAAAARA-NH2 ) peptide with partial helix at the amino terminus. Simulation studies confirm that a greater number of hydrogen bonding and cation-π interaction between the Arg residues and PMR resulted in the gold sea urchin structure for RRR peptide against KKR peptide.

Expanded analysis of high-grade astrocytoma with piloid features identifies an epigenetically and clinically distinct subtype associated with neurofibromatosis type 1.

High-grade astrocytoma with piloid features (HGAP) is a recently recognized glioma type whose classification is dependent on its global epigenetic signature. HGAP is characterized by alterations in the mitogen-activated protein kinase (MAPK) pathway, often co-occurring with CDKN2A/B homozygous deletion and/or ATRX mutation. Experience with HGAP is limited and to better understand this tumor type, we evaluated an expanded cohort of patients (n = 144) with these tumors, as defined by DNA methylation array testing, with a subset additionally evaluated by next-generation sequencing (NGS). Among evaluable cases, we confirmed the high prevalence CDKN2A/B homozygous deletion, and/or ATRX mutations/loss in this tumor type, along with a subset showing NF1 alterations. Five of 93 (5.4%) cases sequenced harbored TP53 mutations and RNA fusion analysis identified a single tumor containing an NTRK2 gene fusion, neither of which have been previously reported in HGAP. Clustering analysis revealed the presence of three distinct HGAP subtypes (or groups = g) based on whole-genome DNA methylation patterns, which we provisionally designated as gNF1 (n = 18), g1 (n = 72), and g2 (n = 54) (median ages 43.5 years, 47 years, and 32 years, respectively). Subtype gNF1 is notable for enrichment with patients with Neurofibromatosis Type 1 (33.3%, p = 0.0008), confinement to the posterior fossa, hypermethylation in the NF1 enhancer region, a trend towards decreased progression-free survival (p = 0.0579), RNA processing pathway dysregulation, and elevated non-neoplastic glia and neuron cell content (p < 0.0001 and p < 0.0001, respectively). Overall, our expanded cohort broadens the genetic, epigenetic, and clinical phenotype of HGAP and provides evidence for distinct epigenetic subtypes in this tumor type.

Understanding the role of water on temperature-dependent structural modifications of SARS CoV-2 main protease binding sites.

Thermally stable and labile proteases are found in microorganisms. Protease mediates the cleavage of polyproteins in the virus replication and transcription process. 6 µs MD simulations were performed for monomer/dimer SARS CoV-2 main protease system in both SPC/E and mTIP3P water model to analyse the temperature-dependent behaviour of the protein. It is found that maximum conformational changes are observed at 348 K which is near the melting temperature. Network distribution of evolved conformations shows an increase in the number of communities with the rise in the temperature. The global conformation of the protein was found to be intact whereas a local conformational space evolved due to thermal fluctuations. The global conformational change in the free energy ΔΔG value for the monomer and the dimer between 278 K and 383 K is found to be 2.51 and 2.10 kJ/mol respectively. A detailed analysis was carried out on the effect of water on the temperature-dependent structural modifications of four binding pockets of SARS CoV-2 main protease namely, catalytic dyad, substrate-binding site, dimerization site and allosteric site. It is found that the water structure around the binding sites is altered with temperature. The water around the dimer sites is more ordered than the monomer sites regardless of the rise in temperature due to structural rigidity. The energy expense of binding the small molecules at substrate binding is less compared to the allosteric site. The water-water hydrogen bond lifetime is found to be more near the cavity of His41. Also, it is observed that mTIP3P water molecules have a similar effect to that of SPC/E water molecules on the main protease.

Exploring the multiple conformational states of RNA genome through interhelical dynamics and network analysis.

The structural variation of RNA is often very transient and can be easily missed in experiments. Molecular dynamics simulation studies along with network analysis can be an effective tool to identify prominent conformations of such dynamic biomolecular systems. Here we describe a method to effectively sample different RNA conformations at six different temperatures based on the changes in the interhelical orientations. This method gives the information about prominent states of the RNA as well as the probability of the existence of different conformations and their interconnections during the process of evolution. In the case of the SARS-CoV-2 genome, the change of prominent structures was found to be faster at 333 K as compared to higher temperatures due to the formation of the non-native base pairs. ΔΔG calculated between 288 K and 363 K are found to be 10.31 kcal/mol (88 nt) considering the contribution from the multiple states of the RNA which agrees well with the experimentally reported denaturation energy for E. coli α mRNA pseudoknot (∼16 kcal/mol, 112 nt) determined by calorimetry/UV hyperchromicity and human telomerase RNA telomerase (4.5-6.6 kcal/mol, 54 nt) determined by FRET analysis.

Influence of Ion Specificity and Concentration on the Conformational Transition of Intrinsically Disordered Sheep Prion Peptide.

The structural sensitivity of the intrinsically disordered proteins with the ions has been observed experimentally; however, it is still unclear how the presence of different metal ions affects structural stability. We performed an atomistic molecular dynamics simulation of sheep prion peptide (142-167) in presence of different monovalent, divalent ions at various concentrations to find out the effect of the size, charge, and ionic concentration on the structure of the peptide. It is found that Li+ ions have a higher survival probability compared to Na+ , K+, and Mg2+ affecting the solvation structure of the protein leading to the alpha-helix structure. At high concentration, due to the increase in the ion-solvent and counter-ion interactions, the effect of the ions is screened on the surface of the protein and hence no ion specificity is observed. This study demonstrates how ions can be used to regulate the protein structure and function that can help in designing drugs.

Effect of nitrogen and zinc nanofertilizer with the organic farming practices on cereal and oil seed crops.

Sustainable and precision agriculture practices are essential to meet the global food demand with minimal impact on soil, air and water. In the present study, nanofertilizers of nitrogen and zinc was used with the organic farming practice under field condition for the cereal i.e. wheat, pearl millet, and oil seed crops i.e. mustard, sesame. The field trial was compared with chemical fertilizer based agricultural settings. A total of 160 field demonstrations were conducted at two locations: Khaliyawas (28.19° N, 76.76° E) and Khatawali (28.22° N, 76.76° E) of Haryana, India with a total area of 1225 acre and randomized block design. It was found that an average yield was recorded 5.35% higher in wheat, 24.24% higher yield in sesame, 4.2% higher in pearl millet and 8.4% higher yield in mustard by applying nanofertilizers of nitrogen and zinc along with the organic farming practice. The increased yield corroborated with the development parameters of plants such as wheat tillers, ear head length of pearl millet, capsule number per plant in sesame and siliquae number per plant in mustard. The trial observation suggests that the fields with applied organic manure, bio-fertilizer and nanofertilizers in combination resulted in higher yield and better plant growth performances when compared to the fields under conventional chemical fertilizer practice. The results suggest that the intervention of nanotechnology along with organic farming practice can help in minimizing the mass volume requirement of conventional chemical fertilizer while improving crop production.

Immune cell deconvolution of bulk DNA methylation data reveals an association with methylation class, key somatic alterations, and cell state in glial/glioneuronal tumors.

It is recognized that the tumor microenvironment (TME) plays a critical role in the biology of cancer. To better understand the role of immune cell components in CNS tumors, we applied a deconvolution approach to bulk DNA methylation array data in a large set of newly profiled samples (n = 741) as well as samples from external data sources (n = 3311) of methylation-defined glial and glioneuronal tumors. Using the cell-type proportion data as input, we used dimensionality reduction to visualize sample-wise patterns that emerge from the cell type proportion estimations. In IDH-wildtype glioblastomas (n = 2,072), we identified distinct tumor clusters based on immune cell proportion and demonstrated an association with oncogenic alterations such as EGFR amplification and CDKN2A/B homozygous deletion. We also investigated the immune cluster-specific distribution of four malignant cellular states (AC-like, OPC-like, MES-like and NPC-like) in the IDH-wildtype cohort. We identified two major immune-based subgroups of IDH-mutant gliomas, which largely aligned with 1p/19q co-deletion status. Non-codeleted gliomas showed distinct proportions of a key genomic aberration (CDKN2A/B loss) among immune cell-based groups. We also observed significant positive correlations between monocyte proportion and expression of PD-L1 and PD-L2 (R = 0.54 and 0.68, respectively). Overall, the findings highlight specific roles of the TME in biology and classification of CNS tumors, where specific immune cell admixtures correlate with tumor types and genomic alterations.

Temperature-Dependent Conformational Evolution of SARS CoV-2 RNA Genome Using Network Analysis.

Understanding the dynamics of the SARS CoV-2 RNA genome and its dependence on temperature is necessary to fight the current COVID-19 crisis. Computationally, the handling of large data is a major challenge in the elucidation of the structures of RNA. This work presents network analysis as an important tool to see the conformational evolution and the most dominant structures of the RNA genome at six different temperatures. It effectively distinguished different communities of RNA having structural variation. It is found that at higher temperatures (348 K and above), 80% of the RNA structure is destroyed in both the SPC/E and mTIP3P water models. The thermal denaturation free energy change ΔΔG value calculated for the long-lived structure at higher temperatures of 348 and 363 K ranges from 2.58 to 2.78 kcal/mol for the SPC/E water model, which agrees well with the experimentally reported thermal denaturation free energy range of 2.874 kcal/mol of SARS CoV-NP at normal pH. At higher temperatures, the stability of RNA conformation is found to be due to the existence of non-native base pairs in the SPC/E water model.

ECG denoising and feature extraction techniques - a review.

The electrocardiogram (ECG) is a non-invasive approach for the recording of bioelectric signals generated by the heart which is used for the examination of the electro physical state, the function of the heart, and many cardiac diseases. However, various artefacts and measurement noise usually hinder providing accurate feature extraction such as power line interference, baseline wander, electromyographic noise (EMG) and electrode motion artefact. Therefore, for better analysis and interpretation ECG signals must be noise-free. Most recent and efficient techniques for ECG denoising and feature extraction techniques have been reviewed in this paper, as feature extraction and denoising of ECG are remarkably helpful in cardiology. This paper presents the review of contemporary signal processing techniques such as discrete wavelet transform (DWT), Empirical mode decomposition (EMD), Variational mode decomposition (VMD) and Empirical wavelet transform (EWT) for ECG signal denoising and feature extraction.

Mechanistic understanding of the pollutant removal and transformation processes in the constructed wetland system.

Constructed wetland systems (CWs) are biologically and physically engineered systems to mimic the natural wetlands which can potentially treat the wastewater from the various point and nonpoint sources of pollution. The present study aims to review the various mechanisms involved in the different types of CWs for wastewater treatment and to elucidate their role in the effective functioning of the CWs. Several physical, chemical, and biological processes substantially influence the pollutant removal efficiency of CWs. Plants species Phragmites australis, Typha latifolia, and Typha angustifolia are most widely used in CWs. The rate of nitrogen (N) removal is significantly affected by emergent vegetation cover and type of CWs. Hybrid CWs (HCWS) removal efficiency for nutrients, metals, pesticides, and other pollutants is higher than a single constructed wetland. The contaminant removal efficiency of the vertical subsurface flow constructed wetlands (VSSFCW) commonly used for the treatment of domestic and municipal wastewater ranges between 31% and 99%. Biochar/zeolite addition as substrate material further enhances the wastewater treatment of CWs. Innovative components (substrate materials, plant species) and factors (design parameters, climatic conditions) sustaining the long-term sink of the pollutants, such as nutrients and heavy metals in the CWs should be further investigated in the future. PRACTITIONER POINTS: Constructed wetland systems (CWs) are efficient natural treatment system for on-site contaminants removal from wastewater. Denitrification, nitrification, microbial and plant uptake, sedimentation and adsorption are crucial pollutant removal mechanisms. Phragmites australis, Typha latifolia, and Typha angustifolia are widely used emergent plants in constructed wetlands. Hydraulic retention time (HRT), water flow regimes, substrate, plant, and microbial biomass substantially affect CWs treatment performance.

Bioactive Compounds Effective Against Type 2 Diabetes Mellitus: A Systematic Review.

BACKGROUND: Type 2 diabetes (adult onset diabetes) is the most common type of diabetes, accounting for around 90% of all diabetes cases with insulin resistance and insulin secretion defect. The key goal of anti-diabetic therapy is to increase the development of insulin, immunity and/or decrease the amount of blood glucose. While many synthetic compounds have been produced as antidiabetic agents, due to their side effects and limited effectiveness, their usefulness has been hindered. METHODS: This systematic review investigated the bioactive compounds reported to possess activities against type 2 diabetes. Three (3) databases, PubMed, ScienceDirect and Google Scholar were searched for research articles published between January 2010 and October 2020. A total of 6464 articles were identified out of which 84 articles were identified to be elligible for the study. RESULT AND DISCUSSION: From the data extracted, it was found that quercetin, Kaempferol, Rosmarinic acid, Cyanidin, Rutin, Catechin, Luteolin and Ellagic acid were the most cited bioactive compounds which all falls within the class of polyphenolic compounds. The major sources of these bioactive compounds includes citrus fruits, grapes, onions, berries, cherries, broccoli, honey, apples, green tea, Ginkgo biloba, St. John's wort, green beans, cucumber, spinach, tea, Rosmarinus officinalis, Aloe vera, Moringa oleifera, tomatoes, potatoes, oregano, lemon balm, thyme, peppermint, Ocimum basilicum, red cabbage, pears, olive oil and walnut.

Ecological health and water quality of village ponds in the subtropics limiting their use for water supply and groundwater recharge.

Ponds are a typical feature of many villages in the subtropics, and have been widely used as important sources of water for agriculture, aquaculture and groundwater recharge, as well as enhancing village resilience to floods and drought. Currently many village ponds are in a very poor state and in dire need of rejuvenation. This paper assesses the current water quality status and ecological health of twelve sub-tropical village ponds, situated in western Uttar Pradesh, India. This assessment is used to evaluate their wastewater treatment needs in relation to potential village uses of the water. Physico-chemical (Secchi depth, Total phosphorus and Total nitrogen) and biological (Phytoplankton chlorophyll-a) indicators highlight hypertrophic conditions in all the ponds. The study indicates that the status of village ponds requires significant investments in wastewater treatment to restore their use for many purposes, including aquaculture, although some may still be acceptable for irrigation purposes, as long as pathogenic bacteria are not abundant. We propose increased implementation of decentralised systems for wastewater treatment, such as septic tanks and constructed wetlands, to reduce the organic and nutrient loads entering village ponds and allow their use for a wider range of purposes.

A new approach for identification of heartbeats in multimodal physiological signals.

In this paper, a technique is proposed for detection of heartbeats in multimodal data. Recording of multiple physiological signals from the same subject is common practice nowadays. Multiple physiological signals are generally available but are processed separately without taking into consideration information from other relevant signals. The heartbeats are generally detected from R peaks in electrocardiogram (ECG) signal, however, if ECG is noisy, other signals reflecting the cardiac activity may be used for identifying heartbeats. This paper describes a new method for detection of heartbeats using ECG and arterial blood pressure (ABP) signals. The physiological data are segmented into various fragments and signal quality is determined using the judgment of noise level. If the ECG data fragment is noisy, heartbeats are computed from the ABP fragment. The evaluation was performed on training data set of computing in cardiology challenge 2014. The proposed methodology has resulted in better detection accuracy as compared to the unimodal methods.