Total Synthesis of Vibrio Cholerae O43 Tetrasaccharide Repeating Unit.

Vibrio cholerae is a pathogen responsible for the deadly pandemic - cholera. The glycans present on the surface of various strains of V. cholerae are considered as potential vaccine candidates. The tetrasaccharide repeating unit (RU) of V. cholerae O43 is decorated with less-explored rare deoxy amino sugars like d-quinosamine and d-viosamine, along with a rare amino acid, N-acetyl-l-allothreonine. Herein, we report a detailed account of the total synthesis of V. cholerae O43 tetrasaccharide RU. In our earlier attempt, while a one-pot assembly of trisaccharide was successful, the final coupling with a fully functionalized d-viosamine donor was low yielding. The successful route involved employing the Fmoc-protected d-viosamine building block as a donor and a late-stage amide bond formation of the tetrasaccharide.

Screening for obstructive sleep apnea in patients with cancer - a machine learning approach.

Background: Obstructive sleep apnea (OSA) is a highly prevalent sleep disorder associated with daytime sleepiness, fatigue, and increased all-cause mortality risk in patients with cancer. Existing screening tools for OSA do not account for the interaction of cancer-related features that may increase OSA risk. Study Design and Methods: This is a retrospective study of patients with cancer at a single tertiary cancer institution who underwent a home sleep apnea test (HSAT) to evaluate for OSA. Unsupervised machine learning (ML) was used to reduce the dimensions and extract significant features associated with OSA. ML classifiers were applied to principal components and model hyperparameters were optimized using k-fold cross-validation. Training models for OSA were subsequently tested and compared with the STOP-Bang questionnaire on a prospective unseen test set of patients who underwent an HSAT. Results: From a training dataset of 249 patients, kernel principal component analysis (PCA) extracted eight components through dimension reduction to explain the maximum variance with OSA at 98%. Predictors of OSA were smoking, asthma, chronic kidney disease, STOP-Bang score, race, diabetes, radiation to head/neck/thorax (RT-HNT), type of cancer, and cancer metastases. Of the ML models, PCA + RF had the highest sensitivity (96.8%), specificity (92.3%), negative predictive value (92%), F1 score (0.93), and ROC-AUC score (0.88). The PCA + RF screening algorithm also performed better than the STOP-Bang questionnaire alone when tested on a prospective unseen test set. Conclusions: The PCA + RF ML model had the highest accuracy in screening for OSA in patients with cancer. History of RT-HNT, cancer metastases, and type of cancer were identified as cancer-related risk factors for OSA.

Thioglycosides Act as Metabolic Inhibitors of Bacterial Glycan Biosynthesis.

Glycans that coat the surface of bacteria are compelling antibiotic targets because they contain distinct monosaccharides that are linked to pathogenesis and are absent in human cells. Disrupting glycan biosynthesis presents a path to inhibiting the ability of a bacterium to infect the host. We previously demonstrated that O-glycosides act as metabolic inhibitors and disrupt bacterial glycan biosynthesis. Inspired by a recent study which showed that thioglycosides (S-glycosides) are 10 times more effective than O-glycosides at inhibiting glycan biosynthesis in mammalian cells, we crafted a panel of S-glycosides based on rare bacterial monosaccharides. The novel thioglycosides altered glycan biosynthesis and fitness in pathogenic bacteria but had no notable effect on glycosylation or growth in beneficial bacteria or mammalian cells. In contrast to findings in mammalian cells, S-glycosides and O-glycosides exhibited comparable potency in bacteria. However, S-glycosides exhibited enhanced selectivity relative to O-glycosides. These novel metabolic inhibitors will allow selective perturbation of the bacterial glycocalyx for functional studies and set the stage to expand our antibiotic arsenal.

Total Synthesis of a Structurally Complex Tetrasaccharide Repeating Unit of Vibrio cholerae O43.

Herein we report the first total synthesis of a densely functionalized tetrasaccharide repeating unit of Vibrio cholerae O43, which contains rare deoxy amino sugars d-quinovosamine and d-viosamine attached with the rare amino acid N-acetyl-l-allothreonine. Synthesis of orthogonally protected rare sugars and unnatural amino acid building blocks, stereoselective construction of three consecutive 1,2-cis glycosidic linkages, amide coupling, and the presence of five nitrogen atoms dispersed over four sugar units as well as the carboxylic acid functionality make the total synthesis a formidable task.

Total Synthesis of the Repeating Units of Proteus penneri 26 and Proteus vulgaris TG155 via a Common Disaccharide.

Herein, we report the first total synthesis of the trisaccharide and tetrasaccharide repeating units of P. penneri 26 and P. vulgaris TG155, respectively, having a common disaccharide unit, 3-α-l-QuipNAc-(1 → 3)-α-d-GlcpNAc-(1 →. Striking features of the targets are the presence of rare sugar units, l-quinovosamine and l-rhamnosamine, all joined through α-glycosidic linkages. Major challenges in the formation of 1,2-cis glycosidic linkages in the case of d-glucosamine, l-quinovosamine, and d-galactosamine have been addressed.

Dual inhibition of IDO1/TDO2 enhances anti-tumor immunity in platinum-resistant non-small cell lung cancer.

BACKGROUND: The impact of non-small cell lung cancer (NSCLC) metabolism on the immune microenvironment is not well understood within platinum resistance. We have identified crucial metabolic differences between cisplatin-resistant (CR) and cisplatin-sensitive (CS) NSCLC cells with elevated indoleamine 2,3-dioxygenase-1 (IDO1) activity in CR, recognized by increased kynurenine (KYN) production. METHODS: Co-culture, syngeneic, and humanize mice models were utilized. C57BL/6 mice were inoculated with either Lewis lung carcinoma mouse cells (LLC) or their platinum-resistant counterpart (LLC-CR) cells. Humanized mice were inoculated with either A (human CS cells) or ALC (human CR cells). Mice were treated with either IDO1 inhibitor or TDO2 (tryptophan 2,3-dioxygenase-2) inhibitor at 200 mg/kg P.O. once a day for 15 days; or with a new-in-class, IDO1/TDO2 dual inhibitor AT-0174 at 170 mg/kg P.O. once a day for 15 days with and without anti-PD1 antibody (10 mg/kg, every 3 days). Immune profiles and KYN and tryptophan (TRP) production were evaluated. RESULTS: CR tumors exhibited a more highly immunosuppressive environment that debilitated robust anti-tumor immune responses. IDO1-mediated KYN production from CR cells suppressed NKG2D on immune effector natural killer (NK) and CD8+ T cells and enhanced immunosuppressive populations of regulatory T cells (Tregs) and myeloid-derived suppressor cells (MDSCs). Importantly, while selective IDO1 inhibition attenuated CR tumor growth, it concomitantly upregulated the TDO2 enzyme. To overcome the compensatory induction of TDO2 activity, we employed the IDO1/TDO2 dual inhibitor, AT-0174. Dual inhibition of IDO1/TDO2 in CR mice suppressed tumor growth to a greater degree than IDO1 inhibition alone. Significant enhancement in NKG2D frequency on NK and CD8+ T cells and a reduction in Tregs and MDSCs were observed following AT-1074 treatment. PD-L1 (programmed death-ligand-1) expression was increased in CR cells; therefore, we assessed dual inhibition + PD1 (programmed cell death protein-1) blocking and report profound anti-tumor growth and improved immunity in CR tumors which in turn extended overall survival in mice. CONCLUSION: Our study reports the presence of platinum-resistant lung tumors that utilize both IDO1/TDO2 enzymes for survival, and to escape immune surveillance as a consequence of KYN metabolites. We also report early in vivo data in support of the potential therapeutic efficacy of the dual IDO1/TDO2 inhibitor AT-0174 as a part of immuno-therapeutic treatment that disrupts tumor metabolism and enhances anti-tumor immunity.

Energy-Efficient Respiratory Anomaly Detection in Premature Newborn Infants.

Precise monitoring of respiratory rate in premature newborn infants is essential to initiating medical interventions as required. Wired technologies can be invasive and obtrusive to the patients. We propose a deep-learning-enabled wearable monitoring system for premature newborn infants, where respiratory cessation is predicted using signals that are collected wirelessly from a non-invasive wearable Bellypatch put on the infant's body. We propose a five-stage design pipeline involving data collection and labeling, feature scaling, deep learning model selection with hyperparameter tuning, model training and validation, and model testing and deployment. The model used is a 1-D convolutional neural network (1DCNN) architecture with one convolution layer, one pooling layer, and three fully-connected layers, achieving 97.15% classification accuracy. To address the energy limitations of wearable processing, several quantization techniques are explored, and their performance and energy consumption are analyzed for the respiratory classification task. Results demonstrate a reduction of energy footprints and model storage overhead with a considerable degradation of the classification accuracy, meaning that quantization and other model compression techniques are not the best solution for respiratory classification problem on wearable devices. To improve accuracy while reducing the energy consumption, we propose a novel spiking neural network (SNN)-based respiratory classification solution, which can be implemented on event-driven neuromorphic hardware platforms. To this end, we propose an approach to convert the analog operations of our baseline trained 1DCNN to their spiking equivalent. We perform a design-space exploration using the parameters of the converted SNN to generate inference solutions having different accuracy and energy footprints. We select a solution that achieves an accuracy of 93.33% with 18× lower energy compared to the baseline 1DCNN model. Additionally, the proposed SNN solution achieves similar accuracy as the quantized model with a 4× lower energy.

Synthesis of L-Hexoses: An Update.

Over the years, carbohydrates have increasingly become an important class of compounds contributing significantly to the target specific drug discovery and vaccine development. Several oligosaccharides contain L-hexoses that are biologically relevant as therapeutic and diagnostic tools. Since, L-hexoses and deoxy L-hexoses are not readily available in large amount and pure form, attention is drawn towards development of cost effective and high yielding synthetic routes for their procurement. In this review we give an update on the recent developments in strategies for synthesis of L-hexoses and deoxy L-hexoses.

Nanoemulsions for targeting the neurodegenerative diseases: Alzheimer's, Parkinson's and Prion's.

Neurodegenerative diseases need the drugs to be delivered right inside the brain to maximizing the therapeutic effects. This can be achieved by use of novel targeted delivery systems such as nanoemulsions. Nanoemulsions (NE) are nano-sized emulsions that are manufactured for enhancing the delivery of drugs to the targeted site and minimize adverse effects and toxic reactions. Looking into the advanced pharmaceutical applications of NE, the present review gives an insight to the understanding of the application of NE in NDs like AD, PD and Prion's disease. The review also touches upon the pathophysiology of these ND diseases to have a clear understanding of the molecular aspects of the disease. Finally, the review sets a standpoint of nanoemulsion's significance in the treatment therapy of ND besides the drawbacks associated with the current drug therapy in NDs.

Metabolic inhibitors of bacterial glycan biosynthesis.

The bacterial cell wall is a quintessential drug target due to its critical role in colonization of the host, pathogen survival, and immune evasion. The dense cell wall glycocalyx contains distinctive monosaccharides that are absent from human cells, and proper assembly of monosaccharides into higher-order glycans is critical for bacterial fitness and pathogenesis. However, the systematic study and inhibition of bacterial glycosylation enzymes remains challenging. Bacteria produce glycans containing rare deoxy amino sugars refractory to traditional glycan analysis, complicating the study of bacterial glycans and the creation of glycosylation inhibitors. To ease the study of bacterial glycan function in the absence of detailed structural or enzyme information, we crafted metabolic inhibitors based on rare bacterial monosaccharide scaffolds. Metabolic inhibitors were assessed for their ability to interfere with glycan biosynthesis and fitness in pathogenic and symbiotic bacterial species. Three metabolic inhibitors led to dramatic structural and functional defects in Helicobacter pylori. Strikingly, these inhibitors acted in a bacteria-selective manner. These metabolic inhibitors will provide a platform for systematic study of bacterial glycosylation enzymes not currently possible with existing tools. Moreover, their selectivity will provide a pathway for the development of novel, narrow-spectrum antibiotics to treat infectious disease. Our inhibition approach is general and will expedite the identification of bacterial glycan biosynthesis inhibitors in a range of systems, expanding the glycochemistry toolkit.

Does nature of livelihood regulate the urban community's vulnerability to climate change? Guwahati city, a case study from North East India.

There is dearth of studies on climate change based vulnerabilities of the urban people. It has been a matter of widespread debate whether nature of livelihood has any role to play in regulating the vulnerabilities of an individual. To find an answer, in a first ever attempt, this study tested three different approaches viz. Livelihood Vulnerability Index (LVI), LVI IPCC (Intergovernmental Panel on Climate Change) models and Climate Vulnerability Index (CVI) to estimate climate change vulnerability of urban communities from various livelihoods in Guwahati city, Assam, India. Guwahati is considered to be the gateway to the seven North Eastern states of India and therefore strategically very important for this region. A structured survey was conducted involving 200 stakeholders from various livelihood sectors viz. construction workers, perishable item sellers, farmers, taxi/auto driver/rickshaw puller/coolie, tea stall/fast food seller, gas cylinder deliverymen, street vendors/salespersons, traffic police/police, doctors and boatmen. Data was systematically aggregated and examined using the above-mentioned composite indices. The differential vulnerabilities were compared and results suggested that the farmers were the most vulnerable community by virtue of their high sensitivity towards health, economic losses, exacerbated by their poor adaptive capacity toward unpredictable climatic variations. Doctors were the least vulnerable owing to their higher levels of awareness and adaptive capacity. These results reiterated the importance of awareness and access to resources in regulating vulnerability. The vulnerability scores also revealed that LVI and Model II (M II) of LVI IPCC approaches were the two most suitable indices and could be used for comparative vulnerability analysis. These pragmatic approaches can be used to assess the community vulnerabilities and could stimulate robust Climate Smart Urban Planning (CSUP).