Uniform trehalose nanogels for glucagon stabilization.

Glucagon is a peptide hormone that acts via receptor-mediated signaling predominantly in the liver to raise glucose levels by hepatic glycogen breakdown or conversion of noncarbohydrate, 3 carbon precursors to glucose by gluconeogenesis. Glucagon is administered to reverse severe hypoglycemia, a clinical complication associated with type 1 diabetes. However, due to low stability and solubility at neutral pH, there are limitations in the current formulations of glucagon. Trehalose methacrylate-based nanoparticles were utilized as the stabilizing and solubilizing moiety in the system reported herein. Glucagon was site-selectively modified to contain a cysteine at amino acid number 24 to covalently attach to the methacrylate-based polymer containing pyridyl disulfide side chains. PEG2000 dithiol was employed as the crosslinker to form uniform nanoparticles. Glucagon nanogels were monitored in Dulbecco's phosphate-buffered saline (DPBS) pH 7.4 at various temperatures to determine its long-term stability in solution. Glucagon nanogels were stable up to at least 5 months by size uniformity when stored at -20 °C and 4 °C, up to 5 days at 25 °C, and less than 12 hours at 37 °C. When glucagon stability was studied by either HPLC or thioflavin T assays, the glucagon was intact for at least 5 months at -20 °C and 4 °C within the nanoparticles at -20 °C and 4 °C and up to 2 days at 25 °C. Additionally, the glucagon nanogels were studied for toxicity and efficacy using various assays in vitro. The findings indicate that the nanogels were nontoxic to fibroblast cells and nonhemolytic to red blood cells. The glucagon in the nanogels was as active as glucagon alone. These results demonstrate the utility of trehalose nanogels towards a glucagon formulation with improved stability and solubility in aqueous solutions, particularly useful for storage at cold temperatures.

A lipo-polymeric hybrid nanosystem with metal enhanced fluorescence for targeted imaging of metastatic breast cancer.

Cancer metastasis plays a major role in failure of therapeutic avenues against cancer. Owing to metastasis, nearly 70-80% of stage IV breast cancer patients lose their lives. Nanodrug delivery systems are playing a critical role in the therapy of metastatic cancer in the recent times. This paper reports the enhanced permeation and retention (EPR) based targeting of metastatic breast cancer using a novel nano lipo-polymeric system (PIR-Au NPs). The PIR-Au NPs demonstrated an increase in fluorescence by virtue of surface coating with gold, owing to the metal enhanced fluorescence phenomenon as reported in our earlier reports. Enhanced fluorescence of PIR-Au NPs was observed in murine mammary carcinoma cell line (4T1), as compared to free IR780 or IR780 loaded nanosystems (P-IR NPs), when incubated for same time at same concentrations, indicating its potential application for imaging and an enhanced bioavailability of IR780. Significant cell death was noted with photothermal mediated cytotoxicity in-vitro against breast cancer cells (MCF-7 and 4T1). An enhanced fluorescence was observed in the zebra fish embryos incubated with PIR-Au NPs. The enhanced permeation and retention (EPR) effect was seen with PIR-Au NPs in-vivo. A strong fluorescent signal was recorded in mice injected with PIR-Au NPs. The tumor tissue collected after 72 h, clearly showed a greater fluorescence as compared to other groups, indicating the plasmon enhanced fluorescence. We also demonstrated the EPR-based targeting of the PIR-Au NPs in-vivo by means of photothermal heat. This lipo-polymeric hybrid nanosystem could therefore be successfully applied for image-guided, passive-targeting to achieve maximum therapeutic benefits.

Identification of Kaempferol as Viral Entry Inhibitor and DL-Arginine as Viral Replication Inhibitor from Selected Plants of Indian Traditional Medicine against COVID-19: An in silico Guided in vitro Approach.

BACKGROUND: Indian traditional medicinal plants are known for their great potential in combating viral diseases. Previously, we reported a systematic review approach of seven plausible traditional Indian medicinal plants against SARS-CoV-2. METHODS: Molecular docking was conducted with Biovia Discovery Studio. Three binding domains for spike glycoprotein (PDB IDs: 6LZG, 6M17, 6M0J) and one binding domain of RdRp (PDB ID: 7BTF) were used. Among 100 phytoconstituents listed from seven plants by the IMPPAT database used for virtual screening, the best six compounds were again filtered using Swiss ADME prediction and Lipinski's rule. Additionally, a pseudovirion assay was performed to study the interaction of SARS-CoV-2 S1-protein with the ACE 2 receptor to further confirm the effect. RESULTS: Chebulagic acid (52.06 Kcal/mol) and kaempferol (48.84 Kcal/mol) showed increased interaction energy compared to umifenovir (33.68 Kcal/mol) for the 6LZG binding domain of spike glycoprotein. Epicatechin gallate (36.95 Kcal/mol) and arachidic acid (26.09 Kcal/mol) showed equally comparable interaction energy compared to umifenovir (38.20 Kcal/mol) for the 6M17 binding domain of spike glycoprotein. Trihydroxychalcone (35.23 Kcal/mol) and kaempferol (36.96 Kcal/mol) showed equally comparable interaction energy with umifenovir (36.60 Kcal/mol) for 6M0J binding domain of spike glycoprotein. Upon analyzing the phytoconstituents against RdRp binding domain, DL-arginine (41.78 Kcal/mol) showed comparable results with the positive control remdesivir (47.61 Kcal/mol). ADME analysis performed using Swiss ADME revealed that kaempferol and DL arginine showed drug-like properties with appropriate pharmacokinetic parameters. Further in vitro analysis of kaempferol by pseudovirion assay confirmed an acceptable decrease of the lentiviral particles in transfected HEK293T-hACE2 cells. CONCLUSION: The study highlights that kaempferol and DL-arginine could be the significant molecules to exhibit potent action against SARS-CoV-2 and its variants.

Chitosan IR806 dye-based polyelectrolyte complex nanoparticles with mitoxantrone combination for effective chemo-photothermal therapy of metastatic triple-negative breast cancer.

Chemo-photothermal therapy is one of the emerging therapies for treating triple-negative breast cancer. In this study, we have used ionotropic gelation method to fabricate chitosan and IR806 dye-based polyelectrolyte complex (CIR-PEx) nanoparticles. These nano-complexes were in size range of 125 ± 20 nm. The complexation of IR 806 dye with chitosan improved photostability, photothermal transduction, and showed excellent biocompatibility. Cancer cells treated with CIR-PEx NPs enhanced intracellular uptake within 5 h of incubation and also displayed mitochondrial localization. With the combination of CIR-PEx NPs and a chemotherapeutic agent (i.e., mitoxantrone, MTX), a significant decline in cancer cell viability was observed in both 2D and 3D cell culture models. The chemo-photothermal effect of CIR-PEx NPs + MTX augmented apoptosis in cancer cells when irradiated with NIR light. Furthermore, when tested in the 4 T1-tumor model, the chemo-photothermal therapy showed a drastic decline in tumor volume and inhibited metastatic lung nodules. The localized hyperthermia caused by photothermal therapy reduced the primary tumor burden, and the chemotherapeutic activity of mitoxantrone further complemented by inhibiting the spread of cancer cells. The proposed chemo-photothermal therapy combination could be a promising strategy for treating triple-negative metastatic breast cancer.

Distribution and characterization of plastic debris pollution along the Poompuhar Beach, Tamil Nadu, Southern India.

The present study was carried out to determine the characteristics, distribution, and abundance of plastic debris in 25 sediment samples collected from the Poompuhar beach, southeast coast of India. The result reveals that the mean plastic debris abundance was 42 ± 27 particles/m2 dry weight (dw) (1 SD, n = 25) with higher concentrations in the river mouth. The dominant shapes in the study area were fragment (70.7%), followed by fiber (20.7%), and pellet-shaped (8.6%). The dominant colors of the plastic debris were: white-colored (47%) followed by blue (28%) and green (14%). The study further reveals that the dominant polymer type was polyethylene (PE, 63.4%), followed by nylon (PA, 16.9), polyvinyl chloride (PVC, 15.5%), polypropylene (PP, 3.1%), and polystyrene (PS, 1.1%). In the study area, the main source of plastic debris was from land-based fishing and tourism activities, and rainwater runoff from the Cauvery River.

Iontophoresis mediated localized delivery of liposomal gold nanoparticles for photothermal and photodynamic therapy of acne.

Acne is one of the common dermatological skin inflammatory conditions. The current therapeutic modalities for the treatment of acne include the administration of antibiotics and anti-inflammatory agents. The rising instance of antibiotic resistance in acne strains has led to the exploration of alternative therapeutic modalities. In the current study, we have employed a liposomal gold nanoparticle entrapping curcumin (Au Lipos Cur NPs) for dual light-mediated therapy for the treatment of acne. These nanoparticles exerted a positive zeta potential that enabled their localized follicular delivery by iontophoresis. The localized deposition of Au Lipos NPs leads to photothermal transduction causing destruction of sebaceous glands. Furthermore, when the nanoparticles were assessed in vitro by sequential irradiation with NIR and blue light, it resulted in significant inhibition of bacterial growth. Thus the dual light-mediated therapy by Au Lipos Cur NPs can form a potential therapeutic modality for the efficient treatment of recurrent acne.

MutT Homolog1 has multifaceted role in glioma and is under the apparent orchestration by Hypoxia Inducible factor1 alpha.

AIMS: The study focused on the expression and role of a recent potential cancer therapeutic target protein, MutT Homolog1 (MTH1). MTH1 gets activated in an increased reactive oxygen species (ROS) environment and removes the oxidized nucleotides from the cell. The study aimed to check the role of MTH1 in DNA damage and apoptosis, migration and angiogenesis and also to examine its regulation in glioma. MAIN METHODS: The experiments were carried out in human glioma tissue samples and brain tissues of epilepsy patients (non-tumor control). We used two human glioblastomas cell lines, U87MG and U251MG cells. In order to study the role of MTH1 in glioma and to analyze the relation of MTH1 with Hif1α, we have used MTH1 siRNA and Hif1α siRNA respectively. KEY FINDINGS: We found an increased expression of MTH1 in glioma tissues compared to the non-tumor brain tissues. Correlation analysis revealed that those samples showing reduced expression of MTH1 also had high levels of DNA damage and apoptotic markers, while diminished expression of angiogenesis regulators and levels of migration. MTH1 knockdown in vitro by siRNA in tumor cell lines corroborates the above observation. This justifies the emergence of MTH1 inhibitors as potential first-in-class drugs. Mechanistically, our observations suggest that Hif1α may modulate MTH1 expression. SIGNIFICANCE: We found elevated MTH1 expression in glioma irrespective of their grades, while its inhibition affects multiple tumor progression pathways, and that targeting Hif1α could simulate the same.

NIR-dye based mucoadhesive nanosystem for photothermal therapy in breast cancer cells.

Breast cancer is one of the leading causes of mortality in women, worldwide. The average survival rate of patients suffering from advanced breast cancer is about 27% for five years. Photothermal therapy employing biodegradable nanoparticle are extensively researched for enhanced anticancer therapy in breast cancer treatment. In the current study, we report a chitosan based mucoadherant and biodegradable niosome nanoparticle entrapping near infrared (NIR) dye (IR 806) for the treatment of breast cancer. Niosome entrapping IR 806 (NioIR) showed encapsulation efficacy of about 56 ± 2%. The prepared nanoparticles (NioIR) were further coated with chitosan (NioIR-C) to impart mucoadhesive property to the nanosystem. NioIR-C showed minimal degradation following NIR laser irradiation, thus enhancing its photothermal stability. They also exhibited efficient photothermal transduction, when compared with IR 806 dye. NioIR-C were biocompatible when treated with normal cell lines (NIH 3T3 and L929) and showed cytotoxicity towards breast cancer cell lines (MCF-7 and MDA-MB 231). When triggered with NIR laser, NioIR-C showed photothermal cell death (approximately 93%). The presence of chitosan coating on NioIR led to mucoadherence potential that further enhances the therapeutic effect on breast cancer cells when compared with IR 806 dye and NioIR. Thus NioIR-C can be a promising nanosystem for effective treatment of breast cancer using photothermal therapy.

To be Wild or Mutant: Role of Isocitrate Dehydrogenase 1 (IDH1) and 2-Hydroxy Glutarate (2-HG) in Gliomagenesis and Treatment Outcome in Glioma.

Molecular and clinical research based on isocitrate dehydrogenase (IDH) mutations is much sought after in glioma research since a decade of its discovery in 2008. IDH enzyme normally catalyzes isocitrate to α-keto-glutarate (α-KG), but once the gene is mutated it produces an 'oncometabolite', 2-hydroxyglutarate (2-HG). 2-HG is proposed to inhibit α-KG-dependent dioxygenases and also blocks cellular differentiation. Here, we discuss the role of the IDH1 mutation in gliomagenesis. The review also focuses on the effect of 2-HG on glioma epigenetics, the cellular signaling involved in IDH1 mutant glioma cells and the therapeutic response seen in mutant IDH1(mIDH1) harboring glioma patients in comparison to the patients with wild-type IDH1. The review encompasses the debatable impacts of the mutation on immune microenvironment a propos of various mIDH1 inhibitors in practice or in trials. Recent studies revealing the relation of IDH mutation with the immune microenvironment and inflammatory status in untreated versus treated glioblastoma patients are highlighted with respect to prospective therapeutic targets. Also at the molecular level, the association of mIDH1/2-HG with the intracellular components such as mitochondria and other neighboring cells is discussed.

A Real-Time Health 4.0 Framework with Novel Feature Extraction and Classification for Brain-Controlled IoT-Enabled Environments.

In this letter, we propose two novel methods for four-class motor imagery (MI) classification using electroencephalography (EEG). Also, we developed a real-time health 4.0 (H4.0) architecture for brain-controlled internet of things (IoT) enabled environments (BCE), which uses the classified MI task to assist disabled persons in controlling IoT-enabled environments such as lighting and heating, ventilation, and air-conditioning (HVAC). The first method for classification involves a simple and low-complex classification framework using a combination of regularized Riemannian mean (RRM) and linear SVM. Although this method performs better compared to state-of-the-art techniques, it still suffers from a nonnegligible misclassification rate. Hence, to overcome this, the second method offers a persistent decision engine (PDE) for the MI classification, which improves classification accuracy (CA) significantly. The proposed methods are validated using an in-house recorded four-class MI data set (data set I, collected over 14 subjects), and a four-class MI data set 2a of BCI competition IV (data set II, collected over 9 subjects). The proposed RRM architecture obtained average CAs of 74.30% and 67.60% when validated using datasets I and II, respectively. When analyzed along with the proposed PDE classification framework, an average CA of 92.25% on 12 subjects of data set I and 82.54% on 7 subjects of data set II is obtained. The results show that the PDE algorithm is more reliable for the classification of four-class MI and is also feasible for BCE applications. The proposed low-complex BCE architecture is implemented in real time using Raspberry Pi 3 Model B+ along with the Virgo EEG data acquisition system. The hardware implementation results show that the proposed system architecture is well suited for body-wearable devices in the scenario of Health 4.0. We strongly feel that this study can aid in driving the future scope of BCE research.

The "nano to micro" transition of hydrophobic curcumin crystals leading to in situ adjuvant depots for Au-liposome nanoparticle mediated enhanced photothermal therapy.

Photothermal therapy (PTT) is emerging as a promising treatment for skin cancer. Plasmon-resonant gold-coated liposome nanoparticles (Au Lipos NPs) specifically absorb Near Infra-Red (NIR) light resulting in localized hyperthermia (PTT). In the current study, curcumin (a hydrophobic anticancer agent) was entrapped in Au Lipos NPs as nanocrystals to act as an adjuvant for the PTT of melanoma. NIR light irradiation on Au Lipos Cur NPs triggered the release of curcumin nanocrystals which coalesce to form curcumin microcrystals (CMCs). An in situ"nano to micro" transition in the crystal state of curcumin was observed. This in situ transition leads to the formation of CMCs. These CMCs exhibited sustained release of curcumin for a prolonged duration (>10 days). The localized availability of curcumin aids in enhancing PTT by inhibiting the growth and mobility of cancer cells that escape PTT. In the in vitro modified scratch assay, the Au Lipos Cur NP + Laser group showed >1.5 fold enhanced therapeutic coverage when compared with the Au Lipos NP + Laser group. In vivo PTT studies performed in a B16 tumor model using Au Lipos Cur NPs showed a significant reduction of the tumor volume along with the localized release of curcumin in the tumor environment. It was observed that the localized release of curcumin enables an immediate adjuvant effect resulting in the enhancement of PTT.

A Novel Feature Extraction Framework for Four Class Motor Imagery Classification using Log Determinant Regularized Riemannian Manifold.

Brain-Computer Interface (BCI) systems allow the person in communicating with the external world using Electroencephalography (EEG). Motor Imagery (MI) based BCI systems play a vital role in interacting with the external environment. In this paper, we propose a novel robust feature extraction and classification framework for four class MI classification to improve the classification accuracy. The proposed architecture is developed using log-determinant (log-det) based Regularized Riemannian mean (LDRRM) and linear SVM. The robustness of features extracted from the four class MI data is improved to the outliers and noise by using the proposed LDRRM framework. We evaluated the performance of the proposed LDRRM classification framework on publicly available four class MI dataset 2a of BCI competition IV. The performance results show that the proposed LDRRM classification architecture obtained a mean classification accuracy of 69.12%, also achieved 1.54% higher classification accuracy when compared with the existing studies.

Compact and Programmable Ultrasound Front-End Processing Module for Research Activities.

Ultrasound signal processing involves diversified requirements in terms of processing, power, hardware etc. Ultrasound signal processing is continuously evolving area, and hence researchers who need to evaluate the novel algorithms in real time need to have the complete hardware setup. Commercially available ultrasound scanners are based on Application Specific Integrated Circuit (ASIC) and hence it does not have any provision to test the novel algorithms. In this paper, we propose a compact and programmable module, equipped with required hardware support for implementing complete front-end processing. The board is supported with an external interface that can be connected to other computing platforms like Field-Programmable Gate Arrays (FPGA's), and Digital Signal Processors (DSP's), etc, for implementing the mid-end and back-end algorithms. Provision is provided for acquiring the raw RF data, which will be beneficial for developing computer-aided diagnostics, and also to develop signal processing algorithms in offline. The proposed front-end hardware module will be very beneficial for rapid testing of the novel ultrasound signal processing algorithms.

Customized nutrition intervention and personalized counseling helps achieve nutrition targets in perioperative liver transplant patients.

BACKGROUND AND AIM: Nutritional therapy is an integral part of care in all phases of liver transplantation (LTx). However, there are several factors that make it a challenge to manage malnutrition in these patients including, but not limited to, loss of appetite, dietary restrictions and dietary habits. Dietary habits are guided by personal choice, social, cultural and regional background with diversity ranging from veganism to vegetarianism with the latter predominant in Indian population. Therefore, it is difficult to improve nutritional intake of patients with standard dietary recommendations. We evaluated the effects of implementing personalized dietary counseling and a customized nutrition plan on its ability to enhance oral intake and, thereby improve nutritional status of patients with end stage liver disease (ESLD) being evaluated for LTx. We compared the outcomes with a matched group of patients who were prescribed standard dietary recommendations from a historic database. Primary outcome was measured by number of patients achieving ≥75% of recommended energy and protein requirements during hospitalization for LTx. Secondary outcomes included mean energy and protein intake, hours of ventilation, length of stay in Intensive Care Unit (ICU) and hospital, mortality and readmission rate in the acute phase (3months) after LTx. METHODS: This was a prospective observational study, performed at a single LTx centre. All patients >18years who enrolled for LTx and consented for the study were included. The study was conducted after obtaining institutional ethics committee approval. A protocol based nutrition planning was implemented from April'14. According to this protocol, all patients being evaluated for LTx underwent a detailed nutritional assessment by a qualified Clinical Dietitian (CD) and regularly followed up with until LTx. Nutritional intervention, including a customized nutrition care plan and personalized dietary counseling, was provided based on the severity of malnutrition. To evaluate the efficacy of this protocol, we compared the nutritional adequacy (calorie and protein intake) of 65 consecutive patients who underwent LTx between August'14-October'15 (group 1) with a historic database of 65 patients who underwent LTx between January'13 and April'14 (group 2). Patients' demographics, disease severity score, baseline markers of nutritional status (subjective global assessment (SGA), and body mass index (BMI)), were recorded. First, assessment of individual patient's oral energy and protein intake was determined by the daily calorie count during hospitalization. Then the nutritional intervention (oral nutrition supplement (ONS)/enteral nutrition (EN)/parenteral nutrition (PN)) plan was customized according to their spontaneous oral intake. As part of the protocol, health related quality of life was also assessed using short form 8 (SF-8) in group 1. Statistical analyses using Pearson's correlation, Chi-Square test were applied with SPSS version 20.0. RESULTS: The mean age of group 1 and 2 were 52.6 ± 9.8, 51.9 ± 10.5 (range 25-70years) with BMI of 26.8 ± 6.0, 26.5 ± 5.4 respectively. According to SGA, there was significant improvement in the nutritional status of group 1 patients compared to group 2 on admission for LTx. It was indicated that 88% of group 1 individuals in comparison to 98% in group 2 were malnourished. The calorie intake of group 1 (1740.2 ± 254.8) was significantly higher than group 2 (1568.5 ± 321.6) (p = 0.005). The marked improvement in protein intake in group 1 (63.1 ± 12.1) when compared with group 2 (53.1 ± 13.4) was statistically significant (p = 0.008). A subset analysis showed that non-vegetarians (consuming meat and dairy products) between the groups showed that group 1 had a significantly higher calorie (p = 0.004) and protein (p = 0.0001) intake compared to individuals in group 2. Following implementation of study's protocol, the goal of achieving ≥75% of the prescribed calories (p = 0.013) and protein (p = 0.0001) was significantly higher in group 1. CONCLUSION: When compared to the standard prescription, an individualized protocol to diagnose, stratify the severity of malnutrition early, and follow up by customized nutrition planning for patients helped to achieve nutritional targets more effectively. Inspite of patients' diversity in nutritional habits and reluctance to accept change, it is clear that a qualified and dedicated transplant nutrition team can successfully implement perioperative nutrition protocol to achieve better nutritional targets.

Deep scattering convolution network based features for ultrasonic fatty liver tissue characterization.

Accumulation of excess fat in the liver tissue is the leading cause for dysfunction of liver, which can lead to the diseases from fibrosis to end stage cirrhosis. Hence, early detection of fatty liver becomes crucial in avoiding the liver from permanent failure. Depending on the concentration of fat in the tissue, the liver is classified as Normal, Grade 1, Grade 2 and Grade 3 respectively. The texture of liver tissue in ultrasound image is so specific to the concentration of fat, hence classifying the fatty liver is formulated as a texture discrimination problem. In this paper, we present an automated algorithm for grading the tissue of a fatty liver based on the features obtained from the invariant scattering convolution network (ISCN). ISCN, which involves cascade of modulus complex wavelet transforms and averaging operations results in scattering coefficients (SC), these coefficients will give stable invariant representations and also maps the texture of fatty liver image to a discriminative manifold giving good features for classification. SC are of high dimension and hence a compact representation feature is obtained by summing all the SC coefficients. Summed SC features along with cubic SVM classifier gave an accuracy of 96.6% in automatically categorizing the fatty content present in the tissue of a liver.

Smartphone based automatic organ validation in ultrasound video.

Telesonography involves transmission of ultrasound video from remote areas to the doctors for getting diagnosis. Due to the lack of trained sonographers in remote areas, the ultrasound videos scanned by these untrained persons do not contain the proper information that is required by a physician. As compared to standard methods for video transmission, mHealth driven systems need to be developed for transmitting valid medical videos. To overcome this problem, we are proposing an organ validation algorithm to evaluate the ultrasound video based on the content present. This will guide the semi skilled person to acquire the representative data from patient. Advancement in smartphone technology allows us to perform high medical image processing on smartphone. In this paper we have developed an Application (APP) for a smartphone which can automatically detect the valid frames (which consist of clear organ visibility) in an ultrasound video and ignores the invalid frames (which consist of no-organ visibility), and produces a compressed sized video. This is done by extracting the GIST features from the Region of Interest (ROI) of the frame and then classifying the frame using SVM classifier with quadratic kernel. The developed application resulted with the accuracy of 94.93% in classifying valid and invalid images.