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Fulltext Neuropharmacological evaluation on four traditional herbs used as nervine tonic and commonly available as Shankhpushpi in India

Sethiya NK, Nahata A, Singh PK, Mishra SH

J Ayurveda Integr Med, 2018 03 09;10(1):25-31.
PMID: 29530454 DOI: 10.1016/j.jaim.2017.08.012

BACKGROUND: Shankhpushpi is an Ayurvedic drug, widely used for its actions on the central nervous system, especially to improve intellect and boost memory. Four botanicals viz. Canscora decussata Schult. (CD), Clitorea ternatea Linn. (CT), Convolvulus pluricaulis Choisy. (CP) and Evolvulus alsinoides Linn. (EA) are considered as sources of Shankhpushpi by Indian practitioners on the basis of their morphological descriptions given in ancient texts.
OBJECTIVE: The present study was undertaken to evaluate the neuropharmacological effect of four herbs commonly identified as source of Shankhpushpi.
MATERIALS AND METHODS: Methanol extracts of all four varieties were tested and evaluated in vitro and in vivo for their neuropharmacological effects. Experiments such as protection against β-amyloid induced neurotoxicity on brain cell line (Neuro 2A), antioxidant potential, AchE (acetylcholinesterase enzyme) inhibition, and 5-LOX (lipoxygenase) enzyme inhibition were conducted for in vitro evaluation. For in vivo evaluation, scopolamine (0.3 mg/kg i.p.) induced memory retrieval using pole climbing apparatus and Morris water maze were performed in rat models.
RESULTS: It was found that protective effects of EA and CD against β-amyloid induced neurotoxicity in Neuro 2A cells were significantly higher than CT and CP. EA proved to be superior than other varieties on the basis of antioxidant activity, AchE inhibitory and LOX inhibitory activities. The preventive activity of EA on scopolamine induced memory retrieval in pole climbing and Morris water maze task in rats was found to be higher than that of CD, CT and CP.
CONCLUSION: EA has remarkable neuropharmacological effect as compared to other three varieties of Shankhpushpi. This effect may be attributed due to the presence of steroids (stigmasterol and betulinic acid), coumarins (scopoletin) and flavonoids (β-carotene and chlorogenic acid). Hence it can be used as a promising lead in development and management of neuronal disorders including Alzheimer's disease.
Fulltext ET-NET: an ensemble of transfer learning models for prediction of COVID-19 infection through chest CT-scan images

Kundu R, Singh PK, Ferrara M, Ahmadian A, Sarkar R

Multimed Tools Appl, 2022;81(1):31-50.
PMID: 34483709 DOI: 10.1007/s11042-021-11319-8

The COVID-19 virus has caused a worldwide pandemic, affecting numerous individuals and accounting for more than a million deaths. The countries of the world had to declare complete lockdown when the coronavirus led to community spread. Although the real-time Polymerase Chain Reaction (RT-PCR) test is the gold-standard test for COVID-19 screening, it is not satisfactorily accurate and sensitive. On the other hand, Computer Tomography (CT) scan images are much more sensitive and can be suitable for COVID-19 detection. To this end, in this paper, we develop a fully automated method for fast COVID-19 screening by using chest CT-scan images employing Deep Learning techniques. For this supervised image classification problem, a bootstrap aggregating or Bagging ensemble of three transfer learning models, namely, Inception v3, ResNet34 and DenseNet201, has been used to boost the performance of the individual models. The proposed framework, called ET-NET, has been evaluated on a publicly available dataset, achieving 97.81 ± 0.53 % accuracy, 97.77 ± 0.58 % precision, 97.81 ± 0.52 % sensitivity and 97.77 ± 0.57 % specificity on 5-fold cross-validation outperforming the state-of-the-art method on the same dataset by 1.56%. The relevant codes for the proposed approach are accessible in: https://github.com/Rohit-Kundu/ET-NET_Covid-Detection.
Fulltext Comparison of efficacy and tolerability of pharmacological treatment for the overactive bladder in women: A network meta-analysis

Nalliah S, Wg P, Masten Singh PK, Naidu P, Lim V, Ahamed AA

Aust Fam Physician, 2017 Mar;46(3):139-144.
PMID: 28260277

BACKGROUND: Overactive bladder syndrome (OAB) is a common medical condition that causes significant distress and impact on the quality of life in women. Muscarinic receptor antagonists remain the mainstay of therapy, but they are limited by their efficacy and adverse effects. The objective of the article was to compare the clinical efficacy and tolerability of medications used to treat OAB in women through network meta-analysis.

METHODS: Data from eligible studies of commonly prescribed pharmacological agents in the treatment of OAB in women were entered into Net-MetaXL after a literature search using two online databases (PubMed and Cochrane). Studies between 31 July 2000 and 31 July 2015 were included in this study.

RESULTS: Five quantitative studies were eligible for analysis. The most efficacious drug to treat OAB in women appears to be solifenacin 10 mg once daily (OD), followed by oxybutynin 3 mg three times a day. However, solifenacin 10 mg OD caused more adverse effects that the other treatments.

DISCUSSION: Our results are similar to those of another systematic review. When considering efficacy, tolerability and cost, solifenacin 5 mg once daily is the drug of choice as it is more efficacious, albeit with more adverse effects, than other treatments. If solifenacin is unsuitable, oxybutynin 3 mg TDS is recommended.
Evaluation of ethnopharmacologically selected Vitex negundo L. for In vitro antimalarial activity and secondary metabolite profiling

Dwivedi MK, Shukla R, Sharma NK, Manhas A, Srivastava K, Kumar N, et al.

J Ethnopharmacol, 2021 Jul 15;275:114076.
PMID: 33789139 DOI: 10.1016/j.jep.2021.114076

ETHANOPHARMACOLOGICAL RELEVANCE: Limited drugs, rise in drug resistance against frontline anti-malarial drugs, non-availability of efficacious vaccines and high cost of drug development hinders malaria intervention programs. Search for safe, effective and affordable plant based anti-malarial agents, thus becomes crucial and vital in the current scenario. The Vitex negundo L. is medicinal plant possessing a variety of pharmaceutically important compounds. The plant is used traditionally worldwide for the treatment of malaria including India and Malaysia by the indigenous tribes. In vitro studies have reported the anti-malarial use of the plant in traditional medicinal systems.
AIM OF THE STUDY: The aim of the current study is to evaluate the traditionally used medicinal plants for in vitro anti-malarial activity against human malaria parasite Plasmodium falciparum and profiling secondary metabolite using spectroscopic and chromatographic methods. Chemical profiling of active secondary metabolites in the extracts was undertaken using LC-MS.
MATERIALS AND METHODS: Based on the ethno-botanical data V. negundo L. was selected for in vitro anti-malarial activity against P. falciparum chloroquine-sensitive (3D7) and multidrug resistant (K1) strains using SYBR Green-I based fluorescence assay. Cytotoxicity of extracts was evaluated in VERO cell line using the MTT assay. Haemolysis assay was performed using human red blood cells. Secondary metabolites profiling was undertaken using chromatographic and spectroscopic analysis. Liquid chromatography analysis was performed using a C18, 150 X 2.1, 2.6 μm column with gradient mobile phase Solvent A: 95% (H2O: ACN), Solvent B: Acetonitrile, Solvent C: Methanol, Solvent D: 5 mM NH4 in 95:5 (H2O: ACN) at a constant flow rate of 0.250 ml/min. The LC-MS spectra were acquired in both positive and negative ion modes with electrospray ionization (ESI) source.
RESULTS: The anti-malarial active extract of V. negundo L. leaf exhibited potent anti-malarial activity with IC50 values of 7.21 μg/ml and 7.43 μg/ml against 3D7 and K1 strains, respectively with no evidence of significant cytotoxicity against mammalian cell line (VERO) and no toxicity as observed in haemolysis assay. The HPLC-LC-MS analysis of the extract led to identification of 73 compounds. We report for the first time the presence of Sabinene hydrate acetate, 5-Hydroxyoxindole, 2(3,4-dimethoxyphenyl)-6, 7-dimethoxychromen-4-one, Cyclotetracosa-1, 13-diene and 5, 7-Dimethoxyflavanone in the anti-malarial active extract of V. negundo L. leaf. Agnuside, Behenic acid and Globulol are some of the novel compounds with no reports of anti-malarial activity so far and require further evaluation in pure form for the development of potent anti-malarial compounds.
CONCLUSIONS: The result report and scientifically validate the traditional use of V. negundo L. for the treatment of malaria providing new avenues for anti-malarial drug development. Several novel and unknown compounds were identified that need to be further characterized for anti-malarial potential.
Fulltext Retraction Note: GraphCovidNet: A graph neural network based model for detecting COVID-19 from CT scans and X-rays of chest

Saha P, Mukherjee D, Singh PK, Ahmadian A, Ferrara M, Sarkar R

Sci Rep, 2021 11 30;11(1):23451.
PMID: 34848779 DOI: 10.1038/s41598-021-02469-8
Fulltext MRFGRO: a hybrid meta-heuristic feature selection method for screening COVID-19 using deep features

Dey A, Chattopadhyay S, Singh PK, Ahmadian A, Ferrara M, Senu N, et al.

Sci Rep, 2021 Dec 15;11(1):24065.
PMID: 34911977 DOI: 10.1038/s41598-021-02731-z

COVID-19 is a respiratory disease that causes infection in both lungs and the upper respiratory tract. The World Health Organization (WHO) has declared it a global pandemic because of its rapid spread across the globe. The most common way for COVID-19 diagnosis is real-time reverse transcription-polymerase chain reaction (RT-PCR) which takes a significant amount of time to get the result. Computer based medical image analysis is more beneficial for the diagnosis of such disease as it can give better results in less time. Computed Tomography (CT) scans are used to monitor lung diseases including COVID-19. In this work, a hybrid model for COVID-19 detection has developed which has two key stages. In the first stage, we have fine-tuned the parameters of the pre-trained convolutional neural networks (CNNs) to extract some features from the COVID-19 affected lungs. As pre-trained CNNs, we have used two standard CNNs namely, GoogleNet and ResNet18. Then, we have proposed a hybrid meta-heuristic feature selection (FS) algorithm, named as Manta Ray Foraging based Golden Ratio Optimizer (MRFGRO) to select the most significant feature subset. The proposed model is implemented over three publicly available datasets, namely, COVID-CT dataset, SARS-COV-2 dataset, and MOSMED dataset, and attains state-of-the-art classification accuracies of 99.15%, 99.42% and 95.57% respectively. Obtained results confirm that the proposed approach is quite efficient when compared to the local texture descriptors used for COVID-19 detection from chest CT-scan images.
Fulltext Fuzzy rank-based fusion of CNN models using Gompertz function for screening COVID-19 CT-scans

Kundu R, Basak H, Singh PK, Ahmadian A, Ferrara M, Sarkar R

Sci Rep, 2021 Jul 08;11(1):14133.
PMID: 34238992 DOI: 10.1038/s41598-021-93658-y

COVID-19 has crippled the world's healthcare systems, setting back the economy and taking the lives of several people. Although potential vaccines are being tested and supplied around the world, it will take a long time to reach every human being, more so with new variants of the virus emerging, enforcing a lockdown-like situation on parts of the world. Thus, there is a dire need for early and accurate detection of COVID-19 to prevent the spread of the disease, even more. The current gold-standard RT-PCR test is only 71% sensitive and is a laborious test to perform, leading to the incapability of conducting the population-wide screening. To this end, in this paper, we propose an automated COVID-19 detection system that uses CT-scan images of the lungs for classifying the same into COVID and Non-COVID cases. The proposed method applies an ensemble strategy that generates fuzzy ranks of the base classification models using the Gompertz function and fuses the decision scores of the base models adaptively to make the final predictions on the test cases. Three transfer learning-based convolutional neural network models are used, namely VGG-11, Wide ResNet-50-2, and Inception v3, to generate the decision scores to be fused by the proposed ensemble model. The framework has been evaluated on two publicly available chest CT scan datasets achieving state-of-the-art performance, justifying the reliability of the model. The relevant source codes related to the present work is available in: GitHub.
Fulltext GraphCovidNet: A graph neural network based model for detecting COVID-19 from CT scans and X-rays of chest

Saha P, Mukherjee D, Singh PK, Ahmadian A, Ferrara M, Sarkar R

Sci Rep, 2021 04 15;11(1):8304.
PMID: 33859222 DOI: 10.1038/s41598-021-87523-1

COVID-19, a viral infection originated from Wuhan, China has spread across the world and it has currently affected over 115 million people. Although vaccination process has already started, reaching sufficient availability will take time. Considering the impact of this widespread disease, many research attempts have been made by the computer scientists to screen the COVID-19 from Chest X-Rays (CXRs) or Computed Tomography (CT) scans. To this end, we have proposed GraphCovidNet, a Graph Isomorphic Network (GIN) based model which is used to detect COVID-19 from CT-scans and CXRs of the affected patients. Our proposed model only accepts input data in the form of graph as we follow a GIN based architecture. Initially, pre-processing is performed to convert an image data into an undirected graph to consider only the edges instead of the whole image. Our proposed GraphCovidNet model is evaluated on four standard datasets: SARS-COV-2 Ct-Scan dataset, COVID-CT dataset, combination of covid-chestxray-dataset, Chest X-Ray Images (Pneumonia) dataset and CMSC-678-ML-Project dataset. The model shows an impressive accuracy of 99% for all the datasets and its prediction capability becomes 100% accurate for the binary classification problem of detecting COVID-19 scans. Source code of this work can be found at GitHub-link .
Fulltext Halocarbon emissions by selected tropical seaweeds: species-specific and compound-specific responses under changing pH

Mithoo-Singh PK, Keng FS, Phang SM, Leedham Elvidge EC, Sturges WT, Malin G, et al.

PeerJ, 2017;5:e2918.
PMID: 28149690 DOI: 10.7717/peerj.2918

Five tropical seaweeds, Kappaphycus alvarezii (Doty) Doty ex P.C. Silva, Padina australis Hauck, Sargassum binderi Sonder ex J. Agardh (syn. S. aquifolium (Turner) C. Agardh), Sargassum siliquosum J. Agardh and Turbinaria conoides (J. Agardh) Kützing, were incubated in seawater of pH 8.0, 7.8 (ambient), 7.6, 7.4 and 7.2, to study the effects of changing seawater pH on halocarbon emissions. Eight halocarbon species known to be emitted by seaweeds were investigated: bromoform (CHBr3), dibro-momethane (CH2Br2), iodomethane (CH3I), diiodomethane (CH2I2), bromoiodomethane (CH2BrI), bromochlorometh-ane (CH2BrCl), bromodichloromethane (CHBrCl2), and dibro-mochloromethane (CHBr2Cl). These very short-lived halocarbon gases are believed to contribute to stratospheric halogen concentrations if released in the tropics. It was observed that the seaweeds emit all eight halocarbons assayed, with the exception of K. alvarezii and S. binderi for CH2I2 and CH3I respectively, which were not measurable at the achievable limit of detection. The effect of pH on halocarbon emission by the seaweeds was shown to be species-specific and compound specific. The highest percentage changes in emissions for the halocarbons of interest were observed at the lower pH levels of 7.2 and 7.4 especially in Padina australis and Sargassum spp., showing that lower seawater pH causes elevated emissions of some halocarbon compounds. In general the seaweed least affected by pH change in terms of types of halocarbon emission, was P. australis. The commercially farmed seaweed K. alvarezii was very sensitive to pH change as shown by the high increases in most of the compounds in all pH levels relative to ambient. In terms of percentage decrease in maximum quantum yield of photosynthesis (Fv∕Fm) prior to and after incubation, there were no significant correlations with the various pH levels tested for all seaweeds. The correlation between percentage decrease in the maximum quantum yield of photosynthesis (Fv∕Fm) and halocarbon emission rates, was significant only for CH2BrCl emission by P. australis (r = 0.47; p ≤ 0.04), implying that photosynthesis may not be closely linked to halocarbon emissions by the seaweeds studied. Bromine was the largest contributor to the total mass of halogen emitted for all the seaweeds at all pH. The highest total amount of bromine emitted by K. alvarezii (an average of 98% of total mass of halogens) and the increase in the total amount of chlorine with decreasing seawater pH fuels concern for the expanding seaweed farming activities in the ASEAN region.
Fulltext Stable and Efficient Dye-Sensitized Solar Cells and Supercapacitors Developed Using Ionic-Liquid-Doped Biopolymer Electrolytes

Konwar S, Singh D, Strzałkowski K, Masri MNB, Yahya MZA, Diantoro M, et al.

Molecules, 2023 Jun 29;28(13).
PMID: 37446761 DOI: 10.3390/molecules28135099

An ionic liquid (IL) 1-ethyl, 2-methyl imidazolium thiocyanate incorporated biopolymer system is reported in this communication for applications in dual energy devices, i.e., electric double-layer capacitors (EDLCs) and dye-sensitized solar cells (DSSCs). The solution caste method has been used to synthesize ionic-liquid-incorporated biopolymer electrolyte films. The IL mixed biopolymer electrolytes achieve high ionic conductivity up to the order of 10-3 S/cm with good thermal stability above 250 °C. Electrical, structural, and optical studies of these IL-doped biopolymer electrolyte films are presented in detail. The performance of EDLCs was evaluated using low-frequency electrochemical impedance spectroscopy, cyclic voltammetry, and constant current charge-discharge, while that of DSSCs was assessed using J-V characteristics. The EDLC cells exhibited a high specific capacitance of 200 F/gram, while DSSCs delivered 1.53% efficiency under sun conditions.
Fulltext The Impact of Polymer Electrolyte Properties on Lithium-Ion Batteries

Badi N, Theodore AM, Alghamdi SA, Al-Aoh HA, Lakhouit A, Singh PK, et al.

Polymers (Basel), 2022 Jul 30;14(15).
PMID: 35956616 DOI: 10.3390/polym14153101

In recent decades, the enhancement of the properties of electrolytes and electrodes resulted in the development of efficient electrochemical energy storage devices. We herein reported the impact of the different polymer electrolytes in terms of physicochemical, thermal, electrical, and mechanical properties of lithium-ion batteries (LIBs). Since LIBs use many groups of electrolytes, such as liquid electrolytes, quasi-solid electrolytes, and solid electrolytes, the efficiency of the full device relies on the type of electrolyte used. A good electrolyte is the one that, when used in Li-ion batteries, exhibits high Li+ diffusion between electrodes, the lowest resistance during cycling at the interfaces, a high capacity of retention, a very good cycle-life, high thermal stability, high specific capacitance, and high energy density. The impact of various polymer electrolytes and their components has been reported in this work, which helps to understand their effect on battery performance. Although, single-electrolyte material cannot be sufficient to fulfill the requirements of a good LIB. This review is aimed to lead toward an appropriate choice of polymer electrolyte for LIBs.
Fulltext Phylodynamic profile of HIV-1 subtype B, CRF01_AE and the recently emerging CRF51_01B among men who have sex with men (MSM) in Singapore

Ng KT, Ng KY, Khong WX, Chew KK, Singh PK, Yap JK, et al.

PLoS One, 2013;8(12):e80884.
PMID: 24312505 DOI: 10.1371/journal.pone.0080884

HIV-1 subtype B and CRF01_AE are the predominant infecting subtypes among men who have sex with men (MSM) in Singapore. The genetic history, population dynamics and pattern of transmission networks of these genotypes remain largely unknown. We delineated the phylodynamic profiles of HIV-1 subtype B, CRF01_AE and the recently characterized CRF51_01B strains circulating among the MSM population in Singapore. A total of 105 (49.5%) newly-diagnosed treatment-naïve MSM were recruited between February 2008 and August 2009. Phylogenetic reconstructions of the protease gene (HXB2: 2239 - 2629), gp120 (HXB2: 6942 - 7577) and gp41 (HXB2: 7803 - 8276) of the env gene uncovered five monophyletic transmission networks (two each within subtype B and CRF01_AE and one within CRF51_01B lineages) of different sizes (involving 3 - 23 MSM subjects, supported by posterior probability measure of 1.0). Bayesian coalescent analysis estimated that the emergence and dissemination of multiple sub-epidemic networks occurred between 1995 and 2005, driven largely by subtype B and later followed by CRF01_AE. Exponential increase in effective population size for both subtype B and CRF01_AE occurred between 2002 to 2007 and 2005 to 2007, respectively. Genealogical estimates suggested that the novel CRF51_01B lineages were probably generated through series of recombination events involving CRF01_AE and multiple subtype B ancestors. Our study provides the first insight on the phylodynamic profiles of HIV-1 subtype B, CRF01_AE and CRF51_01B viral strains circulating among MSM in Singapore.
Targeting the mitochondria in chronic respiratory diseases

Chellappan DK, Paudel KR, Tan NW, Cheong KS, Khoo SSQ, Seow SM, et al.

Mitochondrion, 2022 Nov;67:15-37.
PMID: 36176212 DOI: 10.1016/j.mito.2022.09.003

Mitochondria are one of the basic essential components for eukaryotic life survival. It is also the source of respiratory ATP. Recently published studies have demonstrated that mitochondria may have more roles to play aside from energy production. There is an increasing body of evidence which suggest that mitochondrial activities involved in normal and pathological states contribute to significant impact to the lung airway morphology and epithelial function in respiratory diseases such as asthma, COPD, and lung cancer. This review summarizes the pathophysiological pathways involved in asthma, COPD, lung cancer and highlights potential treatment strategies that target the malfunctioning mitochondria in such ailments. Mitochondria are responsive to environmental stimuli such as infection, tobacco smoke, and inflammation, which are essential in the pathogenesis of respiratory diseases. They may affect mitochondrial shape, protein production and ultimately cause dysfunction. The impairment of mitochondrial function has downstream impact on the cytosolic components, calcium control, response towards oxidative stress, regulation of genes and proteins and metabolic activities. Several novel compounds and alternative medicines that target mitochondria in asthma and chronic lung diseases have been discussed here. Moreover, mitochondrial enzymes or proteins that may serve as excellent therapeutic targets in COPD are also covered. The role of mitochondria in respiratory diseases is gaining much attention and mitochondria-based treatment strategies and personalized medicine targeting the mitochondria may materialize in the near future. Nevertheless, more in-depth studies are urgently needed to validate the advantages and efficacy of drugs that affect mitochondria in pathological states.
Targeting eosinophils in respiratory diseases: Biological axis, emerging therapeutics and treatment modalities

Lee LY, Hew GSY, Mehta M, Shukla SD, Satija S, Khurana N, et al.

Life Sci, 2021 Feb 15;267:118973.
PMID: 33400932 DOI: 10.1016/j.lfs.2020.118973

Eosinophils are bi-lobed, multi-functional innate immune cells with diverse cell surface receptors that regulate local immune and inflammatory responses. Several inflammatory and infectious diseases are triggered with their build up in the blood and tissues. The mobilization of eosinophils into the lungs is regulated by a cascade of processes guided by Th2 cytokine generating T-cells. Recruitment of eosinophils essentially leads to a characteristic immune response followed by airway hyperresponsiveness and remodeling, which are hallmarks of chronic respiratory diseases. By analysing the dynamic interactions of eosinophils with their extracellular environment, which also involve signaling molecules and tissues, various therapies have been invented and developed to target respiratory diseases. Having entered clinical testing, several eosinophil targeting therapeutic agents have shown much promise and have further bridged the gap between theory and practice. Moreover, researchers now have a clearer understanding of the roles and mechanisms of eosinophils. These factors have successfully assisted molecular biologists to block specific pathways in the growth, migration and activation of eosinophils. The primary purpose of this review is to provide an overview of the eosinophil biology with a special emphasis on potential pharmacotherapeutic targets. The review also summarizes promising eosinophil-targeting agents, along with their mechanisms and rationale for use, including those in developmental pipeline, in clinical trials, or approved for other respiratory disorders.
Protein and peptide delivery to lungs by using advanced targeted drug delivery

Chellappan DK, Prasher P, Saravanan V, Vern Yee VS, Wen Chi WC, Wong JW, et al.

Chem Biol Interact, 2022 Jan 05;351:109706.
PMID: 34662570 DOI: 10.1016/j.cbi.2021.109706

The challenges and difficulties associated with conventional drug delivery systems have led to the emergence of novel, advanced targeted drug delivery systems. Therapeutic drug delivery of proteins and peptides to the lungs is complicated owing to the large size and polar characteristics of the latter. Nevertheless, the pulmonary route has attracted great interest today among formulation scientists, as it has evolved into one of the important targeted drug delivery platforms for the delivery of peptides, and related compounds effectively to the lungs, primarily for the management and treatment of chronic lung diseases. In this review, we have discussed and summarized the current scenario and recent developments in targeted delivery of proteins and peptide-based drugs to the lungs. Moreover, we have also highlighted the advantages of pulmonary drug delivery over conventional drug delivery approaches for peptide-based drugs, in terms of efficacy, retention time and other important pharmacokinetic parameters. The review also highlights the future perspectives and the impact of targeted drug delivery on peptide-based drugs in the coming decade.
Fulltext Assessment of variation in immunosuppressive pathway genes reveals TGFBR2 to be associated with risk of clear cell ovarian cancer

Hampras SS, Sucheston-Campbell LE, Cannioto R, Chang-Claude J, Modugno F, Dörk T, et al.

Oncotarget, 2016 10 25;7(43):69097-69110.
PMID: 27533245 DOI: 10.18632/oncotarget.10215

BACKGROUND: Regulatory T (Treg) cells, a subset of CD4+ T lymphocytes, are mediators of immunosuppression in cancer, and, thus, variants in genes encoding Treg cell immune molecules could be associated with ovarian cancer.
METHODS: In a population of 15,596 epithelial ovarian cancer (EOC) cases and 23,236 controls, we measured genetic associations of 1,351 SNPs in Treg cell pathway genes with odds of ovarian cancer and tested pathway and gene-level associations, overall and by histotype, for the 25 genes, using the admixture likelihood (AML) method. The most significant single SNP associations were tested for correlation with expression levels in 44 ovarian cancer patients.
RESULTS: The most significant global associations for all genes in the pathway were seen in endometrioid ( p = 0.082) and clear cell ( p = 0.083), with the most significant gene level association seen with TGFBR2 ( p = 0.001) and clear cell EOC. Gene associations with histotypes at p < 0.05 included: IL12 ( p = 0.005 and p = 0.008, serous and high-grade serous, respectively), IL8RA ( p = 0.035, endometrioid and mucinous), LGALS1 ( p = 0.03, mucinous), STAT5B ( p = 0.022, clear cell), TGFBR1 ( p = 0.021 endometrioid) and TGFBR2 ( p = 0.017 and p = 0.025, endometrioid and mucinous, respectively).
CONCLUSIONS: Common inherited gene variation in Treg cell pathways shows some evidence of germline genetic contribution to odds of EOC that varies by histologic subtype and may be associated with mRNA expression of immune-complex receptor in EOC patients.
Fulltext Estimating global injuries morbidity and mortality: methods and data used in the Global Burden of Disease 2017 study

James SL, Castle CD, Dingels ZV, Fox JT, Hamilton EB, Liu Z, et al.

Inj Prev, 2020 Oct;26(Supp 1):i125-i153.
PMID: 32839249 DOI: 10.1136/injuryprev-2019-043531

BACKGROUND: While there is a long history of measuring death and disability from injuries, modern research methods must account for the wide spectrum of disability that can occur in an injury, and must provide estimates with sufficient demographic, geographical and temporal detail to be useful for policy makers. The Global Burden of Disease (GBD) 2017 study used methods to provide highly detailed estimates of global injury burden that meet these criteria.
METHODS: In this study, we report and discuss the methods used in GBD 2017 for injury morbidity and mortality burden estimation. In summary, these methods included estimating cause-specific mortality for every cause of injury, and then estimating incidence for every cause of injury. Non-fatal disability for each cause is then calculated based on the probabilities of suffering from different types of bodily injury experienced.
RESULTS: GBD 2017 produced morbidity and mortality estimates for 38 causes of injury. Estimates were produced in terms of incidence, prevalence, years lived with disability, cause-specific mortality, years of life lost and disability-adjusted life-years for a 28-year period for 22 age groups, 195 countries and both sexes.
CONCLUSIONS: GBD 2017 demonstrated a complex and sophisticated series of analytical steps using the largest known database of morbidity and mortality data on injuries. GBD 2017 results should be used to help inform injury prevention policy making and resource allocation. We also identify important avenues for improving injury burden estimation in the future.
Fulltext Global injury morbidity and mortality from 1990 to 2017: results from the Global Burden of Disease Study 2017

James SL, Castle CD, Dingels ZV, Fox JT, Hamilton EB, Liu Z, et al.

Inj Prev, 2020 10;26(Supp 1):i96-i114.
PMID: 32332142 DOI: 10.1136/injuryprev-2019-043494

BACKGROUND: Past research in population health trends has shown that injuries form a substantial burden of population health loss. Regular updates to injury burden assessments are critical. We report Global Burden of Disease (GBD) 2017 Study estimates on morbidity and mortality for all injuries.
METHODS: We reviewed results for injuries from the GBD 2017 study. GBD 2017 measured injury-specific mortality and years of life lost (YLLs) using the Cause of Death Ensemble model. To measure non-fatal injuries, GBD 2017 modelled injury-specific incidence and converted this to prevalence and years lived with disability (YLDs). YLLs and YLDs were summed to calculate disability-adjusted life years (DALYs).
FINDINGS: In 1990, there were 4 260 493 (4 085 700 to 4 396 138) injury deaths, which increased to 4 484 722 (4 332 010 to 4 585 554) deaths in 2017, while age-standardised mortality decreased from 1079 (1073 to 1086) to 738 (730 to 745) per 100 000. In 1990, there were 354 064 302 (95% uncertainty interval: 338 174 876 to 371 610 802) new cases of injury globally, which increased to 520 710 288 (493 430 247 to 547 988 635) new cases in 2017. During this time, age-standardised incidence decreased non-significantly from 6824 (6534 to 7147) to 6763 (6412 to 7118) per 100 000. Between 1990 and 2017, age-standardised DALYs decreased from 4947 (4655 to 5233) per 100 000 to 3267 (3058 to 3505).
INTERPRETATION: Injuries are an important cause of health loss globally, though mortality has declined between 1990 and 2017. Future research in injury burden should focus on prevention in high-burden populations, improving data collection and ensuring access to medical care.

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