Cognitive Function in Early Onset Type 1 Diabetes in Children

OBJECTIVES

To assess cognitive function and factors affecting it in Indian children with early-onset type 1 diabetes (T1D) (less than 6 y).

METHODS

This cross-sectional, single-centre study recruited children diagnosed with T1D before 6 y of age and having a disease duration of at least 2 y, as cases. Controls were age- and sex-matched apparently healthy children or siblings. Children with birth asphyxia, intellectual disability, syndromic children, or pre-existing psychiatric illness were excluded. Enrolled children underwent cognitive assessment using Malin's Intelligence Scale for Indian Children (MISIC), and scores in various subtests were compared between cases and controls.

RESULTS

A total of 60 children were enrolled in each group. When compared to controls, cases had significantly lower scores on most subtests, verbal, performance and overall Intelligence Quotient (IQ- 100.62 ± 3.26 vs. 103.23 ± 1.22). HbA1c >9%, severe hypoglycemia and lesser duration since the last diabetic ketoacidosis (DKA) episode significantly correlated with lower neurocognitive scores.

CONCLUSIONS

Children with early onset T1D showed significant deficits in various cognitive domains and IQ. Poor glycemic control, higher glycemic variability and exposure to severe hypoglycemia are risk factors for poor cognitive outcomes in these children. Further longitudinal studies could potentially aid in a finer understanding of factors affecting cognitive functioning in T1D children in developing countries.

Abstract 6606: Biomarker discovery in non-small-cell lung cancer enabled by deep multi-omics profiling of proteins, metabolites, transcripts, and genes in blood

Lung cancer is the leading cause of cancer-related deaths in the United States, with estimates of 236,740 new cases and 118,830 deaths in 2022 secondary to the disease. Blood-based liquid biopsies hold promise to reduce morbidity and mortality from lung cancer by enabling early detection to downstage disease at diagnosis, theragnostic identification of patients most likely to be helped or harmed by therapy, monitoring of therapeutic efficacy, and detection of residual disease. PrognomiQ’s multi-omics platform comprehensively profiles proteins, metabolites, lipids, mRNA, and cfDNA in blood samples which can be used for the development of liquid biopsy tests with high sensitivity and specificity for lung cancer. We conducted a case-control study comprising 1031 subjects: 361 subjects with untreated non-small-cell lung cancer (NSCLC) and 670 matched controls which included 340 subjects with salient pulmonary and gastrointestinal co-morbidities. Blood samples from each subject were processed to provide 7 different `omics readouts. LCMS was used to detect and quantify proteins, metabolites, and lipids. In addition, cfDNA and mRNA were assayed using next-generation sequencing. cfDNA reads were analyzed to estimate fragment-lengths, copy-number variation, and CpG site methylation. All molecular data were normalized using standard methods specific to each assay. Univariate analyses of cases vs controls were performed to identify differentially abundant features on all available samples per assay. We detected 9,868 proteins, 605 lipids, 329 metabolites, and 109,070 mRNA transcripts. Of these, 3,098 proteins, 210 lipids, 57 metabolites, and 30,236 mRNA transcripts were significantly different (FWER < 0.05) in cases versus controls. Gene set enrichment analysis on statistically significant transcripts and proteins identified multiple gene-ontology terms associated with cancer including the Wnt signaling process and IgA immunoglobulin complex, respectively. From cfDNA data, we identified 234 non-contiguous genomic regions associated with the fragment-length disorder, 4,790 with copy-number variation, and 74 differentially methylated genomic regions spanning 184 CpG sites (FWER < 0.05). With the premise that deviations from copy number neutrality are more likely to indicate a tumor contribution, we then focused our examination on those differentially expressed proteins that overlap with differentially expressed mRNA transcripts as well as CNV genomic regions. We identified 52 protein coding genes including E-cadherin (associated with EMT) and related binding proteins such as RAB11B, CAPZB, EPS15, FLNB, MYH9, STK24 and YWHAE. Ongoing machine-learning-based classifier training to distinguish between cancer and non-cancer can serve as the basis for the development of high-sensitivity liquid-biopsy tests for lung cancer.

Citation Format: Jinlyung Choi, Ajinkya Kokate, Ehdieh Khaledian, Manway Liu, Preethi Prasad, John Blume, Jessica Chan, Rea Cuaresma, Kevin Dai, Manoj Khadka, Thidar Khin, Yuya Kodama, Joon-Yong Lee, Hoda Malekpour, Megan Mora, Nithya Mudaliar, Sara Nouri Golmaei, Madhuvanthi Ramaiah, Saividya Ramaswamy, Peter Spiro, Dijana Vitko, Kavya Swaminathan, James Yee, Brian Young, Chinmay Belthangady, Bruce Wilcox, Brian Koh, Philip Ma. Biomarker discovery in non-small-cell lung cancer enabled by deep multi-omics profiling of proteins, metabolites, transcripts, and genes in blood. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6606.

Abstract 6597: A multi-omics classifier achieves high sensitivity and specificity for pancreatic ductal adenocarcinoma in a case-control study of 146 subjects

Pancreatic ductal adenocarcinoma (PDAC) is currently the 3rd leading cause of cancer-related deaths in the US. Although the all-stage 5-year survival rate is ~10%, early-stage 5-year survival is markedly superior and in excess of 40%. Hence, early detection of PDAC via blood-based liquid biopsies holds promise to reduce morbidity and mortality. PrognomiQ’s multi-omics platform performs deep and unbiased molecular profiling of blood samples to detect proteins, metabolites, lipids, mRNA, miRNA, cfDNA fragmentation and copy-number, and CpG methylation. Here we report results from training and validation of a classifier on a subset of that multi-omic data with the potential to enable the development of high sensitivity and specificity tests for early detection of PDAC.We conducted a case-control study comprising 146 subjects across 16 clinical sites, including 63 pathology-confirmed, untreated PDAC cases (12 stage I, 8 stage II, 4 stage III, 36 stage IV, and 3 stage unknown) and 83 age- and gender- matched controls without any known cancer. For each subject, venous blood samples including plasma were collected. Unbiased LCMS was used to detect and quantify proteins, and targeted, multiplexed MRM-LCMS assays were used for both metabolites and lipids. After data processing, we detected 54,114 proteomic features, 898 lipids, and 373 metabolites. 445 proteomic features, 170 lipids, and 37 metabolites were found to be significantly different as determined by Bonferroni-corrected Wilcoxon tests with FWER < 0.05. For classification, the dataset was split into training (37 cases and 37 controls) and validation (26 cases and 46 controls) sets, with control for collection site and date, age, and gender. XGBoost models were constructed for each analyte class using ten repeats of 10-fold cross-validation. To improve specificity to PDAC, all proteomic features which mapped to GOBP terms associated with acute-phase response, inflammation, and immune response were excluded prior to training. The best-performing hyperparameters were used for a final model built on the full training set and then used for inference on the validation set. At 99% specificity, the proteomic classifier had sensitivities of 77%, 57%, and 88% for Stages 1-4, Stages 1-2, and Stages 3-4, respectively, estimated by bootstrap re-sampling of the validation results. Metabolomics had sensitivities of 81%, 71%, and 88%. Lipidomics had sensitivities of 65%, 71%, and 65%. A joint, multi-omic model was constructed by averaging the scaled probabilities of all models. This joint model improved performance at 99% specificity with sensitivities of 92%, 86%, and 94%, highlighting the synergy of multi-omics data, particularly phenotypically related omics such as those described here. Multi-omic classifiers such as these can serve as the foundation for blood-based liquid biopsies for the early detection of PDAC.

Citation Format: John Blume, Ghristine Bundalian, Jessica Chan, Connie Chao-Shern, Jinlyung Choi, Rea Cuaresma, Kevin Dai, Sara N. Golmaei, Jun Heok Jang, Manoj Khadka, Ehdieh Khaledian, Thidar Khin, Yuya Kodama, Ajinkya Kokate, Joon-Yong Lee, Manway Liu, Hoda Malekpour, Megan Mora, Nithya Mudaliar, Preethi Prasad, Madhuvanthi Ramaiah, Saividya Ramaswamy, Peter Spiro, Kavya Swaminathan, Dijana Vitko, James Yee, Brian Young, Susan Zhang, Chinmay Belthangady, Bruce Wilcox, Brian Koh, Philip Ma. A multi-omics classifier achieves high sensitivity and specificity for pancreatic ductal adenocarcinoma in a case-control study of 146 subjects [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6597.

Abstract A038: High-dimensional, multi-omics analyses of proteins, metabolites, transcripts, and genes enable biomarker discovery in early- and late-stage pancreatic cancer

Pancreatic cancer is the third leading cause of cancer-related deaths in the United States. Disease biomarkers quantified from blood-based assays may help reduce mortality by enabling early detection, treatment selection, or response and resistance assessment. PrognomiQ has developed a multi-omics assay and analysis platform that comprehensively profiles blood samples to detect proteins, metabolites, lipids, mRNA, miRNA, cfDNA fragments, and methylation at CpG sites. This platform can provide deep insights into the biology of pancreatic cancer and could enable the development of high sensitivity and specificity tests for the early detection of pancreatic cancer. We conducted a case-control study comprising 196 subjects: 92 with untreated pancreatic cancer and 104 matched controls without pancreatic cancer. For each subject, blood was collected in assay-specific tubes and processed to provide 7 different `omics readouts. cfDNA and mRNA were isolated from samples and assayed following standard NGS protocols. cfDNA fragments were processed to estimate fragment-length disorder and copy-number variation along with CpG site methylation. In addition, targeted and untargeted LCMS were used to detect and quantify proteins, metabolites, and lipids. After normalization, non-parametric univariate analyses of cases versus controls were performed to identify differentially abundant features on all available samples for each assay. Unsupervised learning was used to investigate the separation of subjects into groups based on disease status for the subset of 157 subjects for which complete data on all 7 readouts were available. We detected 2,812 proteins, 811 lipids, 373 metabolites, and 110,864 mRNA transcripts in all samples where data for each assay was available. Of these, 275 proteins, 232 lipids, 49 metabolites, and 3385 mRNA transcripts were significantly different (FWER < 0.05) in cases versus controls. From cfDNA data, we identified 35 non-contiguous genomic regions associated with fragment-length disorder, 557 with copy-number variation, and 5 with multiple, differentially methylated CpGs (FWER < 0.05) that aggregately span 307 protein-coding genes; of these, the overlap with the differentially expressed proteins included E-cadherin (tumor suppressor) and N-cadherin (involved in epithelial-to-mesenchymal transition). Statistically significant genes and proteins were found to be associated with processes including Wnt signaling, regulation of focal adhesion assembly, and actin cytoskeleton organization. Multi-omics, unsupervised learning showed separation of early- and late-stage cases and controls. High-dimensional bioinformatics analyses systematically decomposed each `omics data type into joint and orthogonal components associated with pancreatic cancer. Ongoing multivariate analyses, including supervised machine learning, will further elucidate the biology of pancreatic cancer development, and serve as the foundation for high-sensitivity blood tests for the early detection and monitoring of pancreatic cancer.

Citation Format: Ehdieh Khaledian, Preethi Prasad, John Blume, Ghristine Bundalian, Connie Chao-Shern, Jinlyung Choi, Rea Cuaresma, Jared Deyarmin, Jun Heok Jang, Manoj Khadka, Thidar Khin, Yuya Kodama, Ajinkya Kokate, Joon-Yong Lee, Manway Liu, Nithya Mudaliar, Madhuvanthi Ramaiah, Saividya Ramaswamy, Peter Spiro, Kavya Swaminathan, Preston Williams, Mi Yang, James Yee, Brian Young, Robert Zawada, Susan Zhang, Chinmay Belthangady, Bruce Wilcox, Philip Ma. High-dimensional, multi-omics analyses of proteins, metabolites, transcripts, and genes enable biomarker discovery in early- and late-stage pancreatic cancer [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer; 2022 Sep 13-16; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2022;82(22 Suppl):Abstract nr A038.

Immunoregulatory effects of RGMb in gut inflammation

Graft-versus-host disease (GvHD) is a major complication after allogeneic hematopoietic cell transplantation (HCT). Current strategies to prevent GvHD with immunosuppressive drugs carry significant morbidity and may affect the graft-versus-tumor (GVT) effect. Inflammatory bowel disease (IBD) is an intestinal inflammatory condition that affects more than 2 million people in the United States. Current strategies to prevent colitis with immunosuppressive drugs carry significant morbidity. Recently, Repulsive Guidance Molecule b (RGMb) has been identified as part of a signaling hub with neogenin and BMP receptors in mice and humans. In addition, RGMb binds BMP-2/4 in mice and humans as well as PD-L2 in mice. RGMb is expressed in the gut epithelium and by antigen presenting cells, and we found significantly increased expression in mouse small intestine after total body irradiation HCT conditioning. We hypothesized that RGMb may play a role in GvHD and IBD pathogenesis by contributing to mucosal inflammation. Using major-mismatched HCT mouse models, treatment with an anti-RGMb monoclonal antibody (mAb) that blocks the interaction with BMP-2/4 and neogenin prevented GvHD and improved survival compared to isotype control (75% versus 30% survival at 60 days after transplantation). The GVT effect was retained in tumor models. Using an inflammatory bowel disease dextran sulfate sodium model, treatment with anti-RGMb blocking monoclonal antibody but not isotype control prevented colitis and improved survival compared to control (73% versus 33% at 21 days after treatment) restoring gut homeostasis. Anti-RGMb mAb (9D1) treatment decreased IFN-γ and significantly increased IL-5 and IL-10 in the gut of the treated mice compared to the isotype control treated mice.

NK cells are associated with immunometabolic response to a single exercise exertion in heart failure patients

Background

Increased systemic inflammation and metabolic dysfunction are observed in heart failure with reduced ejection fraction (HFrEF). On the other hand, cardiorespiratory exercise testing (CPET) exerts a physical challenge and initiates the activation of the immune system, including acute release of natural killer (NK) cells into the circulation, and several metabolic pathways.

Aim

To characterize the inflammatory and metabolic alterations of HFrEF patients in response to an acute exercise challenge, and after 2 hours of recovery.

Methods

Participants with HFrEF (n=16), age and sex matched controls (CON, n=13) were investigated at baseline, immediately after and 2 hours after CPET. Clinical and physiological parameters, leukocyte profile, plasma cytokines and metabolites were assessed along with inflammatory and metabolic parameters at all three time points. NK cell counts and morphological/activation parameters in different contexts were examined. Further, the time-dependent coordination of NK cell numbers post-exercise with tryptophan metabolism and plasma triglycerides were assessed. NK cells were isolated from blood of healthy donors for ex vivo proof-of-principle experiments, including phenotype polarization and NK cell specific tryptophan metabolism.

Results

Cardiovascular risk profiles as well as leukocyte, cytokine and metabolic parameters at baseline were similar in CON and HFrEF. Immediately after CPET, lactate, and NK T cell blood counts were significantly increased in both groups. In HFrEF but not CON, platelet aggregates with NK cells, CD8+ cytotoxic T cells and “classical” CD14++CD16-monocytes, phosphatidylcholines and triglycerides were increased. After 2h of recovery, almost all altered parameters returned to baseline in CON. In contrast, blood counts and morphological markers of inflammatory effector cell types, including CD8+ T cells and neutrophils remained elevated in HFrEF. NK cells remained elevated after the recovery period and correlated with levels of various triglyceride species in the HFrEF patients. Tryptophan levels in plasma were reduced by acute exercise and the kynurenine to tryptophan ratio was increased and correlated with increase in NK and NK-T cell counts, as well as IL-12 plasma levels. Treatment with IL-12 led to increased synthesis of kynurenine from tryptophan, expression of indoleamine 2,3-dioxygenase and abundance of regulatory CD56bri NK cell phenotypes ex vivo. Secretome of untreated NK cells impaired cellular respiration, increased glycolysis/oxidation ratio in skeletal muscle cells, and increased the release of triglycerides from hepatocarcinoma cells.

Conclusion

CPET induced a complex acute immunometabolic response, whose restitution to baseline levels differed between HFrEF and healthy controls. Exercise-induced changes in NK cell metabolism and phenotype shift might modulate cellular respiration in myocytes and release of triglycerides by hepatocytes in HFrEF and in CON.

Funding Acknowledgement

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): DZHK (German Centre for Cardiovascular Research)

Individualization of exosuit assistance based on measured muscle dynamics during versatile walking

Variability in human walking depends on individual physiology, environment, and walking task. Consequently, in the field of wearable robotics, there is a clear need for customizing assistance to the user and task. Here, we developed a muscle-based assistance (MBA) strategy wherein exosuit assistance was derived from direct measurements of individuals’ muscle dynamics during specific tasks. We recorded individuals’ soleus muscle dynamics using ultrasonographic imaging during multiple walking speeds and inclines. From these prerecorded images, we estimated the force produced by the soleus through inefficient concentric contraction and designed the exosuit assistance profile to be proportional to that estimated force. We evaluated this approach with a bilateral ankle exosuit at each measured walking task. Compared with not wearing a device, the MBA ankle exosuit significantly reduced metabolic demand by an average of 15.9, 9.7, and 8.9% for level walking at 1.25, 1.5, and 1.75 meters second−1, respectively, and 7.8% at 1.25 meters second−1 at 5.71° incline while applying lower assistance levels than in existing literature. In an additional study (n = 2), we showed for multiple walking tasks that the MBA profile outperforms other bioinspired strategies and the average profile from a previous optimization study. Last, we show the feasibility of online assistance generation in a mobile version for overground outdoor walking. This muscle-based approach enables relatively rapid (~10 seconds) generation of individualized low-force assistance profiles that provide metabolic benefit. This approach may help support the adoption of wearable robotics in real-world, dynamic locomotor tasks by enabling comfortable, tailored, and adaptive assistance.

Protein aggregation and the evolution of stress resistance in clinical yeast

Protein aggregation, particularly in its prion-like form, has long been thought to be detrimental. However, recent studies have identified multiple instances where protein aggregation is important for normal physiological functions. Combining mass spectrometry and cell biological approaches, we developed a strategy for the identification of protein aggregates in cell lysates. We used this approach to characterize prion-based traits in pathogenic strains of the yeast Saccharomyces cerevisiae isolated from immunocompromised human patients. The proteins that we found, including the metabolic enzyme Cdc19, the translation elongation factor Yef3 and the fibrillarin homologue Nop1, are known to assemble under certain physiological conditions. Yet, such assemblies have not been reported to be stable or heritable. Our data suggest that some proteins which aggregate in response to stress have the capacity to acquire diverse assembled states, certain ones of which can be propagated across generations in a form of protein-based epigenetics. This article is part of the theme issue 'How does epigenetics influence the course of evolution?'

TagGraph reveals vast protein modification landscapes from large tandem mass spectrometry datasets

Although mass spectrometry is well suited to identifying thousands of potential protein post-translational modifications (PTMs), it has historically been biased towards just a few. To measure the entire set of PTMs across diverse proteomes, software must overcome the dual challenges of covering enormous search spaces and distinguishing correct from incorrect spectrum interpretations. Here, we describe TagGraph, a computational tool that overcomes both challenges with an unrestricted string-based search method that is as much as 350-fold faster than existing approaches, and a probabilistic validation model that we optimized for PTM assignments. We applied TagGraph to a published human proteomic dataset of 25 million mass spectra and tripled confident spectrum identifications compared to its original analysis. We identified thousands of modification types on almost 1 million sites in the proteome. We show alternative contexts for highly abundant yet understudied PTMs such as proline hydroxylation, and its unexpected association with cancer mutations. By enabling broad characterization of PTMs, TagGraph informs as to how their functions and regulation intersect.

Immuno-proteomic interrogation of antigen presentation during Dengue and Zika infections reveals novel targets for the design of broad acting T-cell vaccines

The recent outbreak of Zika virus (ZIKV) infection across the Americas has raised dire concerns about its potential long-term health effects including its negative impact on neuronal, psychological and motor development in affected individuals. Emerging evidence pointing to Alzheimer’s-like damage to the adult brain further highlights the urgent need for efficacious prophylactic measures. Zika-affected regions are often endemic to the related Dengue virus (DENV). Antibodies against the two viruses are crossreactive and cause antibody-mediated enhancement (ADE) of infection. This confounds the design of traditional vaccines that elicit humoral antibody-mediated responses. T cell vaccines mediated by cytotoxic CD8+ T cells that recognize conserved viral epitopes presented on the major histocompatibility complex (MHC-I) of infected cells are unencumbered by ADE and can supplement or substitute traditional vaccines. In order to identify robust T cell vaccine candidates, we first used an immunoproteomic approach and isolated over 100 novel DENV and ZIKA epitopes presented by infected B lymphocytes in vitro. These viral peptides were not predicted to be epitopes by computational programs typically used for epitope discovery, which discard >95% of all predictions. Focussing on epitopes derived from polyprotein regions strictly conserved between the two viruses, we validated the presentation of these epitopes in primary dendritic cells and assayed their ability to stimulate robust T cell responses in ex vivo ELISpot assays. Together these discoveries let us assay the immunogenic potentials of an unprecedented range of DENV and ZIKV antigens which have the potential to serve as broad acting and effective Zika vaccine candidates.

Antigen presentation profiling reveals T-cell recognition of lymphoma immunoglobulin neoantigens

Presentation of novel antigenic peptides (neoantigens) that distinguish malignant from normal cells by major histocompatibility complexes (MHC) can serve as potent substrates for specific anti-tumor immune responses. We sought to identify mantle cell lymphoma (MCL) neoantigens by taking an integrated genomic and proteomic strategy that interrogates antigen peptides presented by MHC-class I and class II. Peptides bound to MHC were purified via immunoprecipitation followed by identification using mass spectrometry. Mass spectra were searched against patient-specific proteome databases generated by whole exome sequencing and targeted immunoglobulin gene sequencing. This approach was applied to systematically characterize over 36,000 immunopeptides from 17 patients’ tumor specimens. Interestingly, 52 neoantigenic peptides were derived from the lymphoma immunoglobulin (Ig) heavy or light chain variable regions. Although we identified MHC presentation of private germline polymorphic alleles, no mutated peptides were recovered from non-Ig somatically mutated genes. Furthermore, somatic mutations within the immunoglobulin variable region were almost exclusively presented by MHC-II. T-cells specific for Ig-derived neoantigens were found in two patients. Following ex vivo activation and expansion, the T-cells were remarkably able to mediate killing of autologous lymphoma cells. These results demonstrate that combining MHC isolation, peptide identification and exome sequencing is an effective platform to uncover tumor neoantigens. Application of this strategy to MCL implicates immunoglobulin neoantigens as targets for lymphoma immunotherapy.

Crystal structures of two new carbazole derivatives: 12-(4-nitrophenyl)-7-phenylsulfonyl-7H-benzofuro[2,3-b]carbazole and 2-methyl-4-(4-nitrophenyl)-9-phenylsulfonyl-9H-thieno[2,3-b]carbazole

The title compounds are carbazole derivatives, with a benzo­furan ring system in (I) and a methyl­thio­phene ring in (II) fused with the respective carbazole moiety. In the crystals of both compounds, mol­ecules are linked via C—H⋯O hydrogen bonds, forming sheets lying parallel to (10).

The title compounds, C₃₀H₁₈N₂O₅S, (I), and C₂₇H₁₈N₂O₄S₂, (II), are carbazole derivatives with a phenyl­sulfonyl group and a nitro­phenyl group attached to the carbazole moiety in identical positions in both mol­ecules. A benzo­furan ring system in (I) and a methyl­thio­phene ring in (II) are fused with the respective carbazole moieties on the same sides. The mean plane of the carbazole ring system makes a dihedral angle of 3.17 (7)° with the benzo­furan ring system in (I) and a dihedral angle of 3.39 (11)° with the methyl­thio­phene ring in (II), implying that both fused units are essentially planar. The mean planes of the carbazole ring systems in both the compounds are almost orthogonal to the respective nitro-substituted phenyl rings, making dihedral angles of 75.64 (10) and 77.63 (12)° in compounds (I) and (II), respectively. In (I), the phenyl­sulfonyl ring system is positionally disordered with a refined occupancy ratio of 0.63 (2):0.37 (2). In both compounds, the mol­ecular structures are stabilized by intra­molecular C—H⋯O hydrogen bonds, generating S(6) ring motifs with the sulfone group O atoms. In the crystal of compound (I), mol­ecules are linked by pairs of C—H⋯O hydrogen bonds, which generate R₂²(18) inversion dimers, and inter­connected by C(14) chains running along the c-axis direction, whereas in compound (II), the C—H⋯O hydrogen bonds generate R₄³(37) ring motifs. In the crystals of both compounds, C—H⋯O hydrogen-bonded sheets are formed lying parallel to (10-1). In addition, C—H⋯π and offset π–π inter­actions [inter­centroid distance = 3.7158 (14) Å in (I) and 3.9040 (15) Å in (II)] are also present in the crystals of both compounds.

Sudden cardiac death in South India: Incidence, risk factors and pathology

BACKGROUND

Sudden cardiac death (SCD) is a major cause of mortality secondary to coronary artery disease (CAD) in the industrialized societies. Although South Asians have a high prevalence of CAD, the frequency and underlying pathology of SCD among this population are unknown.

METHODS

Medical records of consecutive patients presenting with unexplained sudden death (USD) in a tertiary care center were reviewed. Patients with trauma, violent deaths, positive toxicology and non-cardiac pathology were excluded to determine sudden cardiac death (SCD). Cardiac pathological findings were analyzed by autopsy. SCD rate was estimated based on census and government vital statistics for the years studied.

RESULTS

During a two year period, 223 patients (mean age 55 + 10 yrs, 78.9% male, body mass index 26 + 4, 60% smokers, 39% known CAD, 46% hypertension, 43% diabetes) presented to hospital with USD. SCD was attributed to myocardial infarction (MI) in 87% of cases; 69% were acute (96% anterior MI); 76% were small/moderate infarct and 9.9% of the cohort had normal hearts. Based on official municipal vital statistics, the SCD rate in those >35 yrs of age was estimated as 39.7/100,000 with male/female ratio of 4.6.

CONCLUSIONS

SCD in this south Indian city occurred predominantly in men of relatively young age and was most frequently associated with small or moderate-sized acute MI. Improved health care access, preventive measures and enhanced emergency management may reduce SCD from acute MI in this locale.

Genetic dissection of Flaviviridae host factors through genome-scale CRISPR screens

The Flaviviridae are a family of viruses that cause severe human diseases. For example, dengue virus (DENV) is a rapidly emerging pathogen causing an estimated 100 million symptomatic infections annually worldwide. No approved antivirals are available to date and clinical trials with a tetravalent dengue vaccine showed disappointingly low protection rates. Hepatitis C virus (HCV) also remains a major medical problem, with 160 million chronically infected patients worldwide and only expensive treatments available. Despite distinct differences in their pathogenesis and modes of transmission, the two viruses share common replication strategies. A detailed understanding of the host functions that determine viral infection is lacking. Here we use a pooled CRISPR genetic screening strategy to comprehensively dissect host factors required for these two highly important Flaviviridae members. For DENV, we identified endoplasmic-reticulum (ER)-associated multi-protein complexes involved in signal sequence recognition, N-linked glycosylation and ER-associated degradation. DENV replication was nearly completely abrogated in cells deficient in the oligosaccharyltransferase (OST) complex. Mechanistic studies pinpointed viral RNA replication and not entry or translation as the crucial step requiring the OST complex. Moreover, we show that viral non-structural proteins bind to the OST complex. The identified ER-associated protein complexes were also important for infection by other mosquito-borne flaviviruses including Zika virus, an emerging pathogen causing severe birth defects. By contrast, the most significant genes identified in the HCV screen were distinct and included viral receptors, RNA-binding proteins and enzymes involved in metabolism. We found an unexpected link between intracellular flavin adenine dinucleotide (FAD) levels and HCV replication. This study shows notable divergence in host-depenency factors between DENV and HCV, and illuminates new host targets for antiviral therapy.

Immuno-proteomic interrogation of antigen presentation during Dengue infection reveals novel and HLA haplotype-specific MHC-I antigens

Dengue (DEN) virus infection is a leading cause of hospitalization and death in the developing world and broadly effective vaccines and therapies remain elusive. Identifying infection-specific peptide antigens would open new avenues for developing T cell based interventions. Past efforts towards mapping viral antigens used computational predictions that only partially reflect actual antigens presented by the major histocompatibility complex (MHC). To identify DEN-specific antigens without relying on error prone predictions, we developed an immuno-proteomics approach for interrogating antigen presentation in DEN infected B-lymphocytes. This approach enabled three fundamental findings; First, we identified 86 viral MHC-I antigens (59 novel), and mapped them to presentation hotspots in the DEN genome. Second, we discovered post-translationally modified viral and host antigens and antigens derived from alternate reading frames. Predicting these antigens using computational methods alone would be infeasible. Third, we found antigens responsible for HLA-haplotype dependent immune responses against DEN infection: we genetically engineered B-lymphocytes to express HLA alleles associated with either strong or weak DEN-immune responses and identified corresponding allele specific antigens. Together these discoveries let us assay the immunogenic potentials of an unprecedented range of DEN-specific antigens. Ex-vivo assays including ELISPOT and HLA tetramer staining supported our identification of immunogenic antigens in DEN-specific CD8+ T cells. These antigens have potential as both diagnostic tools to characterize DEN-specific T cell immunity, and serve as candidates for designing effective DEN vaccines.

Crystal structures and conformational analyses of three pyranochromene derivatives

The title compounds, C27H20O6, (I) [systematic name: methyl 7-oxo-14-phenyl-1H,7H,14H-pyrano[3,2-c:5,4-c']dichromene-14a(6bH)-carboxyl-ate], C24H22O5, (II) [systematic name: methyl 1-oxo-6-phenyl-2,3,4,12b-tetra-hydro-1H,6H-chromeno[3,4-c]chromene-6a(7H)-carboxyl-ate], and C25H23N3O4, (III) [systematic name: 6-(4-ethyl-phen-yl)-2,4-dimethyl-1,3-dioxo-2,3,4,12b-tetra-hydro-1H,6H-chromeno[4',3':4,5]pyrano[2,3-d]pyrimidine-6a(7H)-carbo-nitrile], are pyran-ochromene derivatives. The central pyran rings (B) of compounds (I) and (III) adopt half-chair conformations, whereas that of compound (II) adopts a sofa conformation. The pyran rings (A) of the chromene ring systems of compounds (II) and (III) adopt half-chair conformations, while that of compound (I) adopts a sofa conformation. The mean plane of the central pyran rings (B) make dihedral angles of 70.02 (6), 61.52 (6) and 69.12 (7)°, respectively, with the mean planes of the chromene moieties (C+A) of compounds (I), (II) and (III). The bicyclic coumarin ring system (C+A+B+E) in compound (I) is almost planar (r.m.s. deviation = 0.042 Å). The carbo-nitrile side chain in compound (III) is very nearly linear, with the C-C N angle being 176.6 (2)°. The cyclo-hexene ring (E), fused with the central pyran ring (B) in compound (II) adopts a sofa conformation. In the mol-ecular structures of compounds (II) and (III), there are C-H⋯O short contacts, which generate S(7) ring motifs. In the crystal structures of the title compounds, mol-ecules are linked by C-H⋯O hydrogen bonds, which generate mol-ecular sheets parallel to the ab plane, with R 4 (3)(28) loops in (I), inversion dimers with R 2 (2)(10) loops in (II) and chains along [010] with R 2 (2)(12) ring motifs in (III). In the crystal structures of (I) and (III), there are also C-H⋯π inter-actions present, leading to the formation of a three-dimensional framework in (II) and to sheets parallel to (101) in (III).

Relapsing Guillain-Barre syndrome in pregnancy and postpartum

Guillain-Barre syndrome (GBS) rarely complicates pregnancy, but can be associated with high maternal and perinatal morbidity if not properly identified and treated. A high index of suspicion, supportive measures, access to intensive care unit and intravenous immunoglobulin (IVIG) therapy are cornerstones of management in GBS complicating pregnancy. Neurologists and Obstetricians should be aware of the risks of relapsing GBS in the immediate postpartum period. Surgery and anesthesia may be triggers for relapse in association with an overall increase in pro-inflammatory cytokines in the postpartum period. We report a unique case of GBS complicating pregnancy in the third trimester followed by a relapse in the postpartum period. She made a good recovery with supportive measures and a repeat course of IVIG during the relapse.

Substituent effects on the binding of natural product anthocyanidin inhibitors to influenza neuraminidase with mass spectrometry

The binding of three closely related anthocyanins within the 430-cavity of influenza neuraminidase is studied using a combination of mass spectrometry and molecular docking. Despite their similar structures, which differ only in the number and position of the hydroxyl substituents on the phenyl group attached to the chromenylium ring, subtle differences in their binding characteristics are revealed by mass spectrometry and molecular docking that are in accord with their inhibitory properties by neuraminidase inhibition assays. The cyanidin and delphinidin, with the greatest number of hydroxyl groups, bind more strongly and are better inhibitors than pelargonidin that contains a lone hydroxyl group at the 4' position. The study demonstrates, for the first time, the sensitivity of the mass spectrometry based approach for investigating the molecular basis and relative affinity of antiviral inhibitors, with subtly different structures, to their target protein. It has broader application for the screening of other protein interactions more generally with reasonable high-throughput.

Pesticides and human diabetes: a link worth exploring?

It is no exaggeration to claim that the 'diabetes epidemic' has become a 'runaway train' causing huge health and economic consequences, especially in the developing nations. Traditionally, the risk factors for diabetes have largely focused on genetics and lifestyle. Great emphasis is placed on lifestyle measures and finding novel pharmacological treatment options to combat diabetes, but there is increasing evidence linking environmental pollutants, especially pesticides, to the development of insulin resistance and Type 2 diabetes. Pesticide use has increased dramatically worldwide and the effects of pesticides on glucose metabolism are too significant for a possible diabetogenic link to be dismissed. The aim of this review article was to assess the links between pesticides and human diabetes with the goal of stimulating further research in this area.

Feasibility studies for production of 89Sr in the Fast Breeder Test Reactor (FBTR)

89Sr, a pure beta emitter with half life of 50.53 d is used as its chloride solution for palliative care of bone metastases. This paper describes the feasibility studies that have been conducted at FBTR, IGCAR for production of this radionuclide using the 89Y(n, p)89Sr reaction. Yttria pellets were irradiated in a special subassembly at the core centre for a total of 73 d in two steps of 35 d and 38 d with a time gap of 38 d. The irradiated yttria target was dissolved in nitric acid and the bulk Y was separated by solvent extraction using the TBP-HNO3 complex. The 89Sr fraction was purified using the cation exchange resin DOWEX 50W×8 (100-200 mesh size) from the other radioactive impurities seen. The eluted 89Sr fraction was assayed using a GM counting system. The 89Sr activity produced in 1 g of yttria pellet was found to be 19 mCi.

Methyl (2Z)-2-bromomethyl-3-(3-chlorophenyl)prop-2-enoate

There are two independent mol­ecules (A and B) in the asymmetric unit of the title compound C₁₁H₁₀BrClO₂, which represents the Z isomer. The methyl­acrylate moieties are essentially planar, within 0.084 (2) and 0.027 (5) Å in mol­ecules A and B, respectively. The benzene ring makes dihedral angles of 13.17 (7) and 27.89 (9)° with the methyl­acrylate moiety in mol­ecules A and B, respectively. The methyl­bromide moiety is almost orthogonal to the benzene ring, making dihedral angles of 81.46 (16)° in mol­ecule A and 79.61 (16)° in mol­ecule B. The methyl­acrylate moiety exhibits an extended trans conformation in both mol­ecules. In the crystal, pairs of C—H⋯O hydrogen bonds result in the formation of quasi-centrosymmetric R₂²(14) AB dimers.

Binding of a natural anthocyanin inhibitor to influenza neuraminidase by mass spectrometry

The binding of a natural anthocyanin to influenza neuraminidase has been studied employing mass spectrometry and molecular docking. Derived from a black elderberry extract, cyanidin-3-sambubiocide has been found to be a potent inhibitor of sialidase activity. This study reveals the molecular basis for its activity for the first time. The anthocyanin is shown by parallel experimental and computational approaches to bind in the so-called 430-cavity in the vicinity of neuraminidase residues 356-364 and 395-432. Since this antiviral compound binds remote from Asp 151 and Glu 119, two residues known to regulate neuraminidase resistance, it provides the potential for the development of a new class of antivirals against the influenza virus without this susceptibility.

Mass trees: a new phylogenetic approach and algorithm to chart evolutionary history with mass spectrometry

A new phylogenetics approach and algorithm with which to chart the evolutionary history of organisms is presented. It utilizes mass spectral data produced from the proteolytic digestion of proteins, rather than partial or complete gene or translated gene sequences. The concept and validity of the approach is demonstrated herein using both theoretical and experimental mass data, together with the translated gene sequences of the hemagglutinin protein of the influenza virus. A comparison of the mass trees with conventional sequenced-based phylogenetic trees, using two separate tree comparison algorithms, reveals a high degree of similarity and congruence among the trees. Given that the mass map data can be generated more rapidly than gene sequences, even when next generation parallel sequencing is employed, mass trees offer new opportunities and advantages for phylogenetic analysis.

Methyl (2Z)-2-bromomethyl-3-(2,4-dichlorophenyl)prop-2-enoate

In the title compound C₁₁H₉BrCl₂O₂, which represents the Z isomer, the methyl­acrylate moiety is essentially planar within 0.039 (2) Å and has an extended trans configuration. The benzene ring makes a dihedral angle of 28.3 (1)° with the mean plane of the methyl­acrylate moiety. The crystal packing is characterized by C—H⋯O hydrogen bonding and halogen–halogen inter­actions [Cl⋯Cl = 3.486 (3) Å], resulting in the formation of R₂²(11) ring motifs and connecting the mol­ecules into chains propagating along the b axis.

(2S,5S,6R)-5-(4-Methyl-phen-yl)-3-phenyl-4,8-dioxa-3-aza-tricyclo-[7.4.0.0]trideca-1(13),9,11-triene-6-carbonitrile

In the title compound, C(24)H(20)N(2)O(2), the six-membered pyran ring adopts a half-chair conformation with one C atom deviating from the mean plane of the remaining ring atoms by 0.654 (6) Å. The five-membered isoxazole ring adopts an N-envelope conformation with the N atom displaced by 0.742 (5) Å from the mean plane formed by the remaining ring atoms. The carbonitrile side chain is almost linear, with a C-C-N angle of 178.6 (5)°. The crystal packing is stabilized by inter-molecular C-H⋯N inter-actions, through bifurcated acceptor hydrogen bonds formed between the carbonitrile N atom and two alternate C atoms in the unsubstituted benzene ring. The mol-ecular structure and crystal packing are further stabilized by intra-molecular and inter-molecular C-H⋯π inter-actions.

Methylrac-(2R,11S,12R)-12-(2-chlorophenyl)-22-oxo-9,13,21-trioxapentacyclo[12.8.0.02,11.03,8.015,20]docosa-1(14),3,5,7,15(20),16,18-heptaene-11-carboxylate

In the title compound C₂₇H₁₉ClO₆, the coumarin ring system is not exactly planar, with a dihedral angle of 4.12 (7)° between its benzene and lactone rings. The cis-fused pyran rings adopt half-chair conformations. The carbometh­oxy and chloro­phenyl groups are in a trans configuration. The crystal packing is stabilized by inter­molecular C—H⋯O interactions, which produce a centrosymmetric R₂²(14) dimer and two centrosymmetric R₂²(18) dimers connecting the mol­ecules in a two-dimensional fashion.

Diagnosis in diabetes: does it matter?

The diagnosis of diabetes subtypes in a busy clinic is usually based on the age at onset, phenotype and biochemical diagnostic criteria. Not surprisingly, the focus is predominantly on diagnosing type 1 and type 2 diabetes. More challenging for the physician is to think of monogenic diabetes, which results from gene mutations that reduce beta cell function. Often misdiagnosed as type 1 or type 2 diabetes, maturity-onset diabetes of the young (MODY) is the most common form of monogenic diabetes, accounting for 1-2% of all diabetes cases. A diagnosis of monogenic diabetes has important implications in treatment, the prediction of disease progression and screening of family members. We highlight two cases of monogenic diabetes, where the diagnosis had significant implications in all the above parameters. This is followed by a discussion on the glucokinase and hepatocyte nuclear factor-1 alpha MODY, which together constitute the most frequent cause of MODY syndromes in all populations.