Transcriptional Factors Mediated Reprogramming to Pluripotency.

A unique kind of pluripotent cell, i.e., Induced pluripotent stem cells (iPSCs), now being targeted for iPSC synthesis, are produced by reprogramming animal and human differentiated cells (with no change in genetic makeup for the sake of high efficacy iPSCs formation). The conversion of specific cells to iPSCs has revolutionized stem cell research by making pluripotent cells more controllable for regenerative therapy. For the past 15 years, somatic cell reprogramming to pluripotency with force expression of specified factors has been a fascinating field of biomedical study. For that technological primary viewpoint reprogramming method, a cocktail of four transcription factors (TF) has required: Kruppel-like factor 4 (KLF4), four-octamer binding protein 34 (OCT3/4), MYC and SOX2 (together referred to as OSKM) and host cells. IPS cells have great potential for future tissue replacement treatments because of their ability to self-renew and specialize in all adult cell types, although factor-mediated reprogramming mechanisms are still poorly understood medically. This technique has dramatically improved performance and efficiency, making it more useful in drug discovery, disease remodeling, and regenerative medicine. Moreover, in these four TF cocktails, more than 30 reprogramming combinations were proposed, but for reprogramming effectiveness, only a few numbers have been demonstrated for the somatic cells of humans and mice. Stoichiometry, a combination of reprogramming agents and chromatin remodeling compounds, impacts kinetics, quality, and efficiency in stem cell research.

Metabolomic and transcriptomic analyses identify external conditions and key genes underlying high levels of toxic glycoalkaloids in tubers of stress-sensitive potato cultivars.

Introduction: High levels of toxic steroidal glycoalkaloids (SGAs) in potato tubers constitute a recognized food quality problem. Tuber SGA levels vary between potato cultivars and can increase after post-harvest stresses such as wounding and light exposure. A few cultivars, e.g., 'Magnum Bonum' and 'Lenape,' have been withdrawn from commercial sales due to excessive SGA levels during some cultivation years. However, these sudden SGA increases are diffucult to predict, and their causes are not understood. To identify external and genetic factors that underlie sudden SGA increases in certain potato cultivars, we have here in a 2-year study investigated 'Magnum Bonum' and five additional table potato cultivars for their SGA levels after wounding and light exposure. Results and methods: Results showed that 'Magnum Bonum' has an unusual strong SGA response to light exposure, but not to wounding, whereas 'Bintje' displayed an opposite regulation. Levels of calystegine alkaloids were not significantly altered by treatments, implicating independent metabolic regulation of SGA and calystegine levels also under conditions of high SGA accumulation. Metabolomic and transcriptomic analyses identified a small number of key genes whose expression correlated with SGA differences between cultivars. Overexpression of two key genes in transgenic low-SGA potato cultivars increased their leaf SGA levels significantly. Discussion: The results show that a strong response to light can underlie the SGA peaks that occasionally occur in certain potato cultivars and indicate that a between-cultivar variation in the expression of single SGA key genes can account for cultivar SGA differerences. We propose that current attempts to mitigate the SGA hazard will benefit from an increased consideration of cultivar-dependent SGA responses to post-harvest conditions, particularly light exposure. The identified key SGA genes can now be used as a molecular tool in this work.

Serum proteome profiles in patients treated with targeted temperature management after out-of-hospital cardiac arrest.

BACKGROUND: Definition of temporal serum proteome profiles after out-of-hospital cardiac arrest may identify biological processes associated with severe hypoxia-ischaemia and reperfusion. It may further explore intervention effects for new mechanistic insights, identify candidate prognostic protein biomarkers and potential therapeutic targets. This pilot study aimed to investigate serum proteome profiles from unconscious patients admitted to hospital after out-of-hospital cardiac arrest according to temperature treatment and neurological outcome. METHODS: Serum samples at 24, 48, and 72 h after cardiac arrest at three centres included in the Target Temperature Management after out-of-hospital cardiac arrest trial underwent data-independent acquisition mass spectrometry analysis (DIA-MS) to find changes in serum protein concentrations associated with neurological outcome at 6-month follow-up and targeted temperature management (TTM) at 33 °C as compared to 36 °C. Neurological outcome was defined according to Cerebral Performance Category (CPC) scale as "good" (CPC 1-2, good cerebral performance or moderate disability) or "poor" (CPC 3-5, severe disability, unresponsive wakefulness syndrome, or death). RESULTS: Of 78 included patients [mean age 66 ± 12 years, 62 (80.0%) male], 37 (47.4%) were randomised to TTM at 36 °C. Six-month outcome was poor in 47 (60.3%) patients. The DIA-MS analysis identified and quantified 403 unique human proteins. Differential protein abundance testing comparing poor to good outcome showed 19 elevated proteins in patients with poor outcome (log2-fold change (FC) range 0.28-1.17) and 16 reduced proteins (log2(FC) between - 0.22 and - 0.68), involved in inflammatory/immune responses and apoptotic signalling pathways for poor outcome and proteolysis for good outcome. Analysis according to level of TTM showed a significant protein abundance difference for six proteins [five elevated proteins in TTM 36 °C (log2(FC) between 0.33 and 0.88), one reduced protein (log2(FC) - 0.6)] mainly involved in inflammatory/immune responses only at 48 h after cardiac arrest. CONCLUSIONS: Serum proteome profiling revealed an increase in inflammatory/immune responses and apoptosis in patients with poor outcome. In patients with good outcome, an increase in proteolysis was observed, whereas TTM-level only had a modest effect on the proteome profiles. Further validation of the differentially abundant proteins in response to neurological outcome is necessary to validate novel biomarker candidates that may predict prognosis after cardiac arrest.

Identification of biomarkers for glycaemic deterioration in type 2 diabetes.

We identify biomarkers for disease progression in three type 2 diabetes cohorts encompassing 2,973 individuals across three molecular classes, metabolites, lipids and proteins. Homocitrulline, isoleucine and 2-aminoadipic acid, eight triacylglycerol species, and lowered sphingomyelin 42:2;2 levels are predictive of faster progression towards insulin requirement. Of ~1,300 proteins examined in two cohorts, levels of GDF15/MIC-1, IL-18Ra, CRELD1, NogoR, FAS, and ENPP7 are associated with faster progression, whilst SMAC/DIABLO, SPOCK1 and HEMK2 predict lower progression rates. In an external replication, proteins and lipids are associated with diabetes incidence and prevalence. NogoR/RTN4R injection improved glucose tolerance in high fat-fed male mice but impaired it in male db/db mice. High NogoR levels led to islet cell apoptosis, and IL-18R antagonised inflammatory IL-18 signalling towards nuclear factor kappa-B in vitro. This comprehensive, multi-disciplinary approach thus identifies biomarkers with potential prognostic utility, provides evidence for possible disease mechanisms, and identifies potential therapeutic avenues to slow diabetes progression.

Molecular mechanism of Ferula asafoetida for the treatment of asthma: Network pharmacology and molecular docking approach.

Asthma is a significant health-care burden that has great impact on the quality of life of patients and their families. The limited amount of previously reported data and complicated pathophysiology of asthma make it a difficult to treat and significant economic burden on public healthcare systems. Ferula asafoetida is an herbaceous, monoecious, perennial plant of the Umbelliferae family. In Asia, F. asafoetida is used to treat a range of diseases and disorders, including asthma. Several in vitro studies demonstrated the therapeutic efficacy of F. asafoetida against asthma. Nevertheless, the precise molecular mechanism is yet to be discovered. In the framework of current study, network pharmacology approach was used to identify the bioactive compounds of F. asafoetida in order to better understand its molecular mechanism for the treatment of asthma. In present work, we explored a compound-target-pathway network and discovered that assafoetidin, cynaroside, farnesiferol-B, farnesiferol-C, galbanic-acid, and luteolin significantly influenced the development of asthma by targeting MAPK3, AKT1 and TNF genes. Later, docking analysis revealed that active constituents of F. asafoetida bind stably with three target proteins and function as asthma repressor by regulating the expression of MAPK3, AKT1 and TNF genes. Thus, integration of network pharmacology with molecular docking revealed that F. asafoetida prevent asthma by modulating asthma-related signaling pathways. This study lays the basis for establishing the efficacy of multi-component, multi-target compound formulae, as well as investigating new therapeutic targets for asthma.

Plasma proteome profiling of healthy individuals across the life span in a Sicilian cohort with long-lived individuals.

The study of healthy human aging is important for shedding light on the molecular mechanisms behind aging to promote well-being and to possibly predict and/or avoid the development of age-related disorders such as atherosclerosis and diabetes. Herein, we have employed an untargeted mass spectrometry-based approach to study age-related protein changes in a healthy Sicilian plasma cohort including long-lived individuals. This approach confirmed some of the previously known proteins correlated with age including fibulin-1, dystroglycan, and gamma-glutamyl hydrolase. Furthermore, our findings include novel proteins that correlate with age and/or with location and uric acid, which could represent a unique signature for healthy aging.

Regulation of micro-RNA, epigenetic factor by natural products for the treatment of cancers: Mechanistic insight and translational association.

From onset to progression, cancer is a ailment that might take years to grow. All common epithelial malignancies, have a long latency period, frequently 20 years or more, different gene may contain uncountable mutations if they are clinically detectable. MicroRNAs (miRNAs) are around 22nt non-coding RNAs that control gene expression sequence-specifically through translational inhibition or messenger degradation of RNA (mRNA). Epigenetic processes of miRNA control genetic variants through genomic DNA methylation, post-translation histone modification, rework of the chromatin, and microRNAs. The field of miRNAs has opened a new era in understanding small non-coding RNAs since discovering their fundamental mechanisms of action. MiRNAs have been found in viruses, plants, and animals through molecular cloning and bioinformatics approaches. Phytochemicals can invert the epigenetic aberrations, a leading cause of the cancers of various organs, and act as an inhibitor of these changes. The advantage of phytochemicals is that they only function on cells that cause cancer without affecting normal cells. Phytochemicals appear to play a significant character in modulating miRNA expression, which is linked to variations in oncogenes, tumor suppressors, and cancer-derived protein production, according to several studies. In addition to standard anti-oxidant or anti-inflammatory properties, the initial epigenetic changes associated with cancer prevention may be modulated by many polyphenols. In correlation with miRNA and epigenetic factors to treat cancer some of the phytochemicals, including polyphenols, curcumin, resveratrol, indole-3-carbinol are studied in this article.

Exploring the therapeutic potential of benzothiazine-pyrazole hybrid molecules against alpha-glucosidase: Pharmacological and molecular modelling based approach.

Diabetes mellitus (DM) is a metabolic disorder and a significant health problem all over the world. The current study elucidates the inhibitory potentials of the benzothiazine-pyrazole hybrid series against the α-Glucosidase enzyme. The molecular docking was employed to determine the binding affinity of synthetic compounds (ligands) with α-Glucosidase enzyme (receptor) active sites via the molecular operating environment (MOE). The molecular docking analysis revealed the best inhibitory interaction between certain synthetic compounds and the enzyme's active sites (α-Glucosidase). These compounds were further examined for drug-like properties, which necessarily validate the use of the compound as a drug. Then selected compounds were subjected to in vitro analysis to find the inhibitory potential with minimal dose. All compounds were docked into the active sites with the best binding pose and low rmsd values. The anti-diabetic analysis revealed that compound ST3 is more active against α-Glucosidase with IC50 values 5.8 µM as compared to acarbose which is 58.8 µM. The present study exhibited compound 2c has a high proficiency in lowering blood glucose levels compared to acarbose. This study strengthened the scope of designing/synthesizing these benzothiazine-pyrazole hybrid molecules as anti-diabetic drug molecules in the pharmaceutical industry.

The Insight of In Silico and In Vitro evaluation of Beta vulgaris phytochemicals against Alzheimer's disease targeting acetylcholinesterase.

B. vulgaris extracts possess antioxidant, anti-inflammatory along with its role in improving memory disorders. Subsequently, in vitro and in silico studies of its purified phytochemicals may expand complementary and alternative Alzheimer's therapeutic option. Super activation of acetylcholinesterase enzyme is associated explicitly with Alzheimer's disease (AD) ultimately resulting in senile dementia. Hence, acetylcholinesterase enzyme inhibition is employed as a promising approach for AD treatment. Many FDA approved drugs are unable to cure the disease progression completely. The Present study was devised to explore the potential bioactive phytochemicals of B. vulgaris as alternative therapeutic agents against AD by conducting in vitro and in silico studies. To achieve this, chemical structures of phytochemicals were recruited from PubChem. Further, these compounds were analyzed for their binding affinities towards acetylcholinesterase (AChE) enzyme. Pharmacophoric ligand-based models showed major characteristics like, HBA, HBD, hydrophobicity, aromaticity and positively ionizable surface morphology for receptor binding. Virtual screening identified three hit compounds including betanin, myricetin and folic acid with least binding score compared to the reference drug, donepezil (-17 kcal/mol). Further, in vitro studies for anti-acetylcholinesterase activity of betanin and glycine betaine were performed. Dose response analysis showed 1.271 µM and 1.203 µM 50% inhibitory concentration (IC50) values for betanin and glycine betaine compounds respectively. Our findings indicate that phytoconstituents of B. vulgaris can be implicated as an alternative therapeutic drug candidate for cognitive disorders like Alzheimer's disease.

Hypoxia induces radioresistance, epithelial­mesenchymal transition, cancer stem cell­like phenotype and changes in genes possessing multiple biological functions in head and neck squamous cell carcinoma.

Hypoxia has been linked with increased resistance to treatment in various solid tumors, including head and neck squamous cell carcinoma (HNSCC). The aim of the present study was to identify genes involved in hypoxia­mediated responses to radiotherapy in HNSCC. A total of three HNSCC cell lines with an epithelial phenotype were selected for this study and cultured under normoxic (21% O2) or hypoxic (1% O2) conditions. The sensitivity of the HNSCC cells to radiotherapy was assessed by a crystal violet assay. Western blotting (for protein expression), cDNA microarrays and reverse transcription­quantitative PCR (for gene expression) were also applied. Small interfering RNA silencing was used to knock down target genes. The results revealed that hypoxia negatively affected the response of HNSCC cells to radiotherapy. Of note, increased levels of N­cadherin, vimentin and fibronectin, as well as stem cell­associated transcription factors, were observed under hypoxia. The microarray analysis revealed a number of hypoxia­regulated genes that were involved in multiple biological functions. However, downregulation of hypoxia­regulated genes did not affect sensitivity to radiotherapy of the investigated cell lines. Taken together, the present findings indicated several important pathways and genes that were involved in hypoxia and radiotherapy resistance. It is hypothesized that panels of reported hypoxia­regulated genes may be useful for the prediction of radiotherapy responses in patients with HNSCC.

Weakened resilience of benthic microbial communities in the face of climate change.

Increased ocean temperature associated with climate change is especially intensified in coastal areas and its influence on microbial communities and biogeochemical cycling is poorly understood. In this study, we sampled a Baltic Sea bay that has undergone 50 years of warmer temperatures similar to RCP5-8.5 predictions due to cooling water release from a nuclear power plant. The system demonstrated reduced oxygen concentrations, decreased anaerobic electron acceptors, and higher rates of sulfate reduction. Chemical analyses, 16S rRNA gene amplicons, and RNA transcripts all supported sediment anaerobic reactions occurring closer to the sediment-water interface. This resulted in higher microbial diversities and raised sulfate reduction and methanogenesis transcripts, also supporting increased production of toxic sulfide and the greenhouse gas methane closer to the sediment surface, with possible release to oxygen deficient waters. RNA transcripts supported prolonged periods of cyanobacterial bloom that may result in increased climate change related coastal anoxia. Finally, while metatranscriptomics suggested increased energy production in the heated bay, a large number of stress transcripts indicated the communities had not adapted to the increased temperature and had weakened resilience. The results point to a potential feedback loop, whereby increased temperatures may amplify negative effects at the base of coastal biochemical cycling.

Single-cell analysis of myeloid cells in HPV+ tonsillar cancer.

The incidence of human papillomavirus-positive (HPV+) tonsillar cancer has been sharply rising during the last decades. Myeloid cells represent an appropriate therapeutic target due to their proximity to virus-infected tumor cells, and their ability to orchestrate antigen-specific immunity, within the tonsil. However, the interrelationship of steady-state and inflammatory myeloid cell subsets, and their impact on patient survival remains unexplored. Here, we used single-cell RNA-sequencing to map the myeloid compartment in HPV+ tonsillar cancer. We observed an expansion of the myeloid compartment in HPV+ tonsillar cancer, accompanied by interferon-induced cellular responses both in dendritic cells (DCs) and monocyte-macrophages. Our analysis unveiled the existence of four DC lineages, two macrophage polarization processes, and their sequential maturation profiles. Within the DC lineages, we described a balance shift in the frequency of progenitor and mature cDC favoring the cDC1 lineage in detriment of cDC2s. Furthermore, we observed that all DC lineages apart from DC5s matured into a common activated DC transcriptional program involving upregulation of interferon-inducible genes. In turn, the monocyte-macrophage lineage was subjected to early monocyte polarization events, which give rise to either interferon-activated or CXCL-producing macrophages, the latter enriched in advanced tumor stages. We validated the existence of most of the single-cell RNA-seq clusters using 26-plex flow cytometry, and described a positive impact of cDC1 and interferon-activated DCs and macrophages on patient survival using gene signature scoring. The current study contributes to the understanding of myeloid ontogeny and dynamics in HPV-driven tonsillar cancer, and highlights myeloid biomarkers that can be used to assess patient prognosis.

Synthesis and α-glucosidase inhibition studies of norfloxacin-acetanilide hybrids.

α-Glucosidase inhibitors occupy a prominent position among the various treatments of type-2 diabetes mellitus (DM2). In this study, a series of new norfloxacin-acetanilide hybrid molecules were synthesized and screened for α-glucosidase inhibition activity. The synthetic methodology involves the synthesis of a series of α-bromoacetanilides by condensing bromoacetyl bromide with various substituted anilines. These α-bromoacetanilides were coupled with norfloxacin in DMF to get the titled hybrids. The structure elucidation of synthesized compounds were characterized by 1H NMR, 13C NMR and LC-MS. Finally, the compounds were screened for their α-glucosidase inhibition activity using acarbose as a reference drug (IC50 =58 µM). Among the tested compounds, 3i and 3j displayed potent α-glucosidase inhibition activity with IC50 values of 7.81±0.038 and 5.55±0.012 µM respectively. In-addition, 3m, 3f and 3k were demonstrated moderate alpha-glucosidase inhibition activities with IC50 values of 52.905±0.041, 23.79± 0.087 and 23.06±0.026 µM respectively. The structure-activity relationship was established with the help of molecular docking by using Molecular Operating Environment software (MOE 2014).

Identifying key genes and screening therapeutic agents associated with diabetes mellitus and HCV-related hepatocellular carcinoma by bioinformatics analysis.

OBJECTIVE: Incidence of both Type 2 diabetes mellitus (T2DM) and hepatocellular carcinoma (HCC) are rapidly increasing worldwide. One of the leading causes of HCC is hepatitis C virus (HCV), which is a resource of blood-borne viral infection. HCV increases the risk for HCC probably by promoting fibrosis and cirrhosis. Association among T2DM and HCV related HCC remains significant, indicating that such association is clinically reliable and robust. Lawson was the first who uncovered HCC in person suffered from T2DM. Until now, genetic association between HCV related HCC and T2DM is poorly known. Current work was designed to figure out the molecular mechanisms of both diseases by identifying the hub genes and therapeutic drugs using integrated bioinformatics analysis. METHODS: Four microarray datasets were downloaded from GEO database and analyzed using R in order to obtain different expressed genes (DEGs). Protein-protein interaction (PPI) networks was constructed using STRING tool and visualized by Cytoscape. Moreover, hub genes were identified on the basis of their degree of connectivity. Finally, Networkanalyst and DGIdb were used for the identification of transcription factors (TFs) and selection of candidate drugs, respectively. RESULTS: A total of 53 DEGs were identified, of which 41 were upregulated genes and 12 were downregulated genes. PPI network obtained from STRING were subjected to Cytoscape plugin cytoHubba, and top 10 genes (AURKA, JUN, AR, MELK, NCOA2, CENPF, NCAPG, PCK1, RAD51AP1, and GTSE1) were chosen as the target hub genes based on the highest degree of connectivity. Furthermore, 47 drugs of AURKA, JUN, AR, MELK, and NCOA2 were found having therapeutic potential to treat HCV-HCC in patients with T2DM. CONCLUSION: This study updates the information and yield a new perspective in context of understanding the pathogenesis and development of HCV related HCC in affected persons with T2DM. In vivo and in vitro investigation of hub genes and pathway interaction is essential to delineate the specific roles of the novel hub genes, which may help to reveal the genetic association between HCV-HCC and T2DM. In future, hub genes along with their candidate drugs might be capable of improving the personalized detection and therapies for both diseases.

Distinct Molecular Signatures of Clinical Clusters in People With Type 2 Diabetes: An IMI-RHAPSODY Study.

Type 2 diabetes is a multifactorial disease with multiple underlying aetiologies. To address this heterogeneity, investigators of a previous study clustered people with diabetes according to five diabetes subtypes. The aim of the current study is to investigate the etiology of these clusters by comparing their molecular signatures. In three independent cohorts, in total 15,940 individuals were clustered based on five clinical characteristics. In a subset, genetic (N = 12,828), metabolomic (N = 2,945), lipidomic (N = 2,593), and proteomic (N = 1,170) data were obtained in plasma. For each data type, each cluster was compared with the other four clusters as the reference. The insulin-resistant cluster showed the most distinct molecular signature, with higher branched-chain amino acid, diacylglycerol, and triacylglycerol levels and aberrant protein levels in plasma were enriched for proteins in the intracellular PI3K/Akt pathway. The obese cluster showed higher levels of cytokines. The mild diabetes cluster with high HDL showed the most beneficial molecular profile with effects opposite of those seen in the insulin-resistant cluster. This study shows that clustering people with type 2 diabetes can identify underlying molecular mechanisms related to pancreatic islets, liver, and adipose tissue metabolism. This provides novel biological insights into the diverse aetiological processes that would not be evident when type 2 diabetes is viewed as a homogeneous disease.

Replication and cross-validation of type 2 diabetes subtypes based on clinical variables: an IMI-RHAPSODY study.

AIMS/HYPOTHESIS: Five clusters based on clinical characteristics have been suggested as diabetes subtypes: one autoimmune and four subtypes of type 2 diabetes. In the current study we replicate and cross-validate these type 2 diabetes clusters in three large cohorts using variables readily measured in the clinic. METHODS: In three independent cohorts, in total 15,940 individuals were clustered based on age, BMI, HbA1c, random or fasting C-peptide, and HDL-cholesterol. Clusters were cross-validated against the original clusters based on HOMA measures. In addition, between cohorts, clusters were cross-validated by re-assigning people based on each cohort's cluster centres. Finally, we compared the time to insulin requirement for each cluster. RESULTS: Five distinct type 2 diabetes clusters were identified and mapped back to the original four All New Diabetics in Scania (ANDIS) clusters. Using C-peptide and HDL-cholesterol instead of HOMA2-B and HOMA2-IR, three of the clusters mapped with high sensitivity (80.6-90.7%) to the previously identified severe insulin-deficient diabetes (SIDD), severe insulin-resistant diabetes (SIRD) and mild obesity-related diabetes (MOD) clusters. The previously described ANDIS mild age-related diabetes (MARD) cluster could be mapped to the two milder groups in our study: one characterised by high HDL-cholesterol (mild diabetes with high HDL-cholesterol [MDH] cluster), and the other not having any extreme characteristic (mild diabetes [MD]). When these two milder groups were combined, they mapped well to the previously labelled MARD cluster (sensitivity 79.1%). In the cross-validation between cohorts, particularly the SIDD and MDH clusters cross-validated well, with sensitivities ranging from 73.3% to 97.1%. SIRD and MD showed a lower sensitivity, ranging from 36.1% to 92.3%, where individuals shifted from SIRD to MD and vice versa. People belonging to the SIDD cluster showed the fastest progression towards insulin requirement, while the MDH cluster showed the slowest progression. CONCLUSIONS/INTERPRETATION: Clusters based on C-peptide instead of HOMA2 measures resemble those based on HOMA2 measures, especially for SIDD, SIRD and MOD. By adding HDL-cholesterol, the MARD cluster based upon HOMA2 measures resulted in the current clustering into two clusters, with one cluster having high HDL levels. Cross-validation between cohorts showed generally a good resemblance between cohorts. Together, our results show that the clustering based on clinical variables readily measured in the clinic (age, HbA1c, HDL-cholesterol, BMI and C-peptide) results in informative clusters that are representative of the original ANDIS clusters and stable across cohorts. Adding HDL-cholesterol to the clustering resulted in the identification of a cluster with very slow glycaemic deterioration.

Development and Comparative Analysis of Electrochemically Etched Tungsten Tips for Quartz Tuning Fork Sensor.

Quartz Tuning Fork (QTF) based sensors are used for Scanning Probe Microscopes (SPM), in particular for near-field scanning optical microscopy. Highly sharp Tungsten (W) tips with larger cone angles and less tip diameter are critical for SPM instead of platinum and iridium (Pt/Ir) tips due to their high-quality factor, conductivity, mechanical stability, durability and production at low cost. Tungsten is chosen for its ease of electrochemical etching, yielding high-aspect ratio, sharp tips with tens of nanometer end diameters, while using simple etching circuits and basic electrolyte chemistry. Moreover, the resolution of the SPM images is observed to be associated with the cone angle of the SPM tip, therefore Atomic-Resolution Imaging is obtained with greater cone angles. Here, the goal is to chemically etch W to the smallest possible tip apex diameters. Tips with greater cone angles are produced by the custom etching procedures, which have proved superior in producing high quality tips. Though various methods are developed for the electrochemical etching of W wire, with a range of applications from scanning tunneling microscopy (SPM) to electron sources of scanning electron microscopes, but the basic chemical etching methods need to be optimized for reproducibility, controlling cone angle and tip sharpness that causes problems for the end users. In this research work, comprehensive experiments are carried out for the production of tips from 0.4 mm tungsten wire by three different electrochemical etching techniques, that is, Alternating Current (AC) etching, Meniscus etching and Direct Current (DC) etching. Consequently, sharp and high cone angle tips are obtained with required properties where the results of the W etching are analyzed, with optical microscope, and then with field emission scanning electron microscopy (FE-SEM). Similarly, effects of varying applied voltages and concentration of NaOH solution with comparison among the produced tips are investigated by measuring their cone angle and tip diameter. Moreover, oxidation and impurities, that is, removal of contamination and etching parameters are also studied in this research work. A method has been tested to minimize the oxidation on the surface and the tips were characterized with scanning electron microscope (SEM).

Lipidomics of human adipose tissue reveals diversity between body areas.

BACKGROUND AND AIMS: Adipose tissue plays a pivotal role in storing excess fat and its composition reflects the history of person's lifestyle and metabolic health. Broad profiling of lipids with mass spectrometry has potential for uncovering new knowledge on the pathology of obesity, metabolic syndrome, diabetes and other related conditions. Here, we developed a lipidomic method for analyzing human subcutaneous adipose biopsies. We applied the method to four body areas to understand the differences in lipid composition between these areas. MATERIALS AND METHODS: Adipose tissue biopsies from 10 participants were analyzed using ultra-high-performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry. The sample preparation optimization included the optimization of the lipid extraction, the sample amount and the sample dilution factor to detect lipids in an appropriate concentration range. Lipidomic analyses were performed for adipose tissue collected from the abdomen, breast, thigh and lower back. Differences in lipid levels between tissues were visualized with heatmaps. RESULTS: Lipidomic analysis on human adipose biopsies lead to the identification of 186lipids in 2 mg of sample. Technical variation of the lipid-class specific internal standards were below 5%, thus indicating acceptable repeatability. Triacylglycerols were highly represented in the adipose tissue samples, and lipids from 13 lipid classes were identified. Long polyunsaturated triacylglycerols in higher levels in thigh (q<0.05), when compared with the abdomen, breast and lower back, indicating that the lipidome was area-specific. CONCLUSION: The method presented here is suitable for the analysis of lipid profiles in 2 mg of adipose tissue. The amount of fat across the body is important for health but we argue that also the distribution and the particular profile of the lipidome may be relevant for metabolic outcomes. We suggest that the method presented in this paper could be useful for detecting such aberrations.

Designing of a next generation multiepitope based vaccine (MEV) against SARS-COV-2: Immunoinformatics and in silico approaches

Coronavirus disease 2019 (COVID-19) associated pneumonia caused by severe acute respiratory coronavirus 2 (SARS-COV-2) was first reported in Wuhan, China in December 2019. Till date, no vaccine or completely effective drug is available to cure COVID-19. Therefore, an effective vaccine against SARS-COV-2 is crucially needed. This study was conducted to design an effective multiepitope based vaccine (MEV) against SARS-COV-2. Seven antigenic proteins were taken as targets and different epitopes (B-cell, T-cell and IFN-{gamma} inducing) were predicted. Highly antigenic and overlapping epitopes were shortlisted. Selected epitopes indicated significant interactions with the HLA-binding alleles and 99.29% coverage of the worlds population. Finally, 505 amino acids long MEV was designed by connecting sixteen MHC class I and eleven MHC class II epitopes with suitable linkers and adjuvant. Linkers and adjuvant were added to enhance the immunogenicity response of the MEV. The antigenicity, allergenicity, physiochemical properties and structural details of MEV were analyzed in order to ensure safety and immunogenicity. MEV construct was non-allergenic, antigenic, stable and flexible. Molecular docking followed by molecular dynamics (MD) simulation analysis, demonstrated a stable and strong binding affinity of MEV with human pathogenic toll-like receptors (TLR), TLR3 and TLR8. Codon optimization and in silico cloning of MEV ensured increased expression in the Escherichia coli K-12 system. Designed MEV in present study could be a potential candidate for further vaccine production process against COVID-19. However, to ensure its safety and immunogenic profile, the proposed MEV needs to be experimentally validated.

Lipidomic profiles, lipid trajectories and clinical biomarkers in female elite endurance athletes.

We assessed whether blood lipid metabolites and their changes associate with various cardiometabolic, endocrine, bone- and energy-related comorbidities of Relative Energy Deficiency in Sport (RED-S) in female elite endurance athletes. Thirty-eight Scandinavian female elite athletes underwent a day-long exercise test. Five blood samples were obtained during the day - at fasting state and before and after two standardized exercise tests. Clinical biomarkers were assessed at fasting state, while untargeted lipidomics was undertaken using all blood samples. Linear and logistic regression was used to assess associations between lipidomic features and clinical biomarkers. Overrepresentations of findings with P < 0.05 from these association tests were assessed using Fisher's exact tests. Self-organizing maps and a trajectory clustering algorithm were utilized to identify informative clusters in the population. Twenty associations PFDR < 0.05 were detected between lipidomic features and clinical biomarkers. Notably, cortisol demonstrated an overrepresentation of associations with P < 0.05 compared to other traits (PFisher = 1.9×10-14). Mean lipid trajectories were created for 201 named features for the cohort and subsequently by stratifying participants by their energy availability and menstrual dysfunction status. This exploratory analysis of lipid trajectories indicates that participants with menstrual dysfunction might have decreased adaptive response to exercise interventions.