Chemical and biological study of Premna resinosa (hochst) Schauer surface extract

In this investigation we report the isolation and characterization of labdane diterpenes of the surface extract of P. resinosa. and the evaluation of their antiproliferative effects

Cerebellar Pathology in an Inducible Mouse Model of Friedreich Ataxia

Friedreich ataxia (FRDA) is an autosomal recessive neurodegenerative disorder caused by deficiency of the mitochondrial protein frataxin. Lack of frataxin causes neuronal loss in various areas of the CNS and PNS. In particular, cerebellar neuropathology in FRDA patients includes loss of large principal neurons and synaptic terminals in the dentate nucleus (DN), and previous studies have demonstrated early synaptic deficits in the Knockin-Knockout mouse model of FRDA. However, the exact correlation of frataxin deficiency with cerebellar neuropathology remains unclear. Here we report that doxycycline-induced frataxin knockdown in a mouse model of FRDA (FRDAkd) leads to synaptic cerebellar degeneration that can be partially reversed by AAV8-mediated frataxin restoration. Loss of cerebellar Purkinje neurons and large DN principal neurons are observed in the FRDAkd mouse cerebellum. Levels of the climbing fiber-specific glutamatergic synaptic marker VGLUT2 decline starting at 4 weeks after dox induction, whereas levels of the parallel fiber-specific synaptic marker VGLUT1 are reduced by 18-weeks. These findings suggest initial selective degeneration of climbing fiber synapses followed by loss of parallel fiber synapses. The GABAergic synaptic marker GAD65 progressively declined during dox induction in FRDAkd mice, while GAD67 levels remained unaltered, suggesting specific roles for frataxin in maintaining cerebellar synaptic integrity and function during adulthood. Expression of frataxin following AAV8-mediated gene transfer partially restored VGLUT1/2 levels. Taken together, our findings show that frataxin knockdown leads to cerebellar degeneration in the FRDAkd mouse model, suggesting that frataxin helps maintain cerebellar structure and function

Leveraging technology-driven strategies to untangle omics big data: circumventing roadblocks in clinical facets of oral cancer

Oral cancer is one of the 19most rapidly progressing cancers associated with significant mortality, owing to its extreme degree of invasiveness and aggressive inclination. The early occurrences of this cancer can be clinically deceiving leading to a poor overall survival rate. The primary concerns from a clinical perspective include delayed diagnosis, rapid disease progression, resistance to various chemotherapeutic regimens, and aggressive metastasis, which collectively pose a substantial threat to prognosis. Conventional clinical practices observed since antiquity no longer offer the best possible options to circumvent these roadblocks. The world of current cancer research has been revolutionized with the advent of state-of-the-art technology-driven strategies that offer a ray of hope in confronting said challenges by highlighting the crucial underlying molecular mechanisms and drivers. In recent years, bioinformatics and Machine Learning (ML) techniques have enhanced the possibility of early detection, evaluation of prognosis, and individualization of therapy. This review elaborates on the application of the aforesaid techniques in unraveling potential hints from omics big data to address the complexities existing in various clinical facets of oral cancer. The first section demonstrates the utilization of omics data and ML to disentangle the impediments related to diagnosis. This includes the application of technology-based strategies to optimize early detection, classification, and staging via uncovering biomarkers and molecular signatures. Furthermore, breakthrough concepts such as salivaomics-driven non-invasive biomarker discovery and omics-complemented surgical interventions are articulated in detail. In the following part, the identification of novel disease-specific targets alongside potential therapeutic agents to confront oral cancer via omics-based methodologies is presented. Additionally, a special emphasis is placed on drug resistance, precision medicine, and drug repurposing. In the final section, we discuss the research approaches oriented toward unveiling the prognostic biomarkers and constructing prediction models to capture the metastatic potential of the tumors. Overall, we intend to provide a bird’s eye view of the various omics, bioinformatics, and ML approaches currently being used in oral cancer research through relevant case studies

The GTPase Activating Rap/RanGAP Domain-Like 1 Gene Is Associated with Chicken Reproductive Traits

BACKGROUND: Abundant evidence indicates that chicken reproduction is strictly regulated by the hypothalamic-pituitary-gonad (HPG) axis, and the genes included in the HPG axis have been studied extensively. However, the question remains as to whether any other genes outside of the HPG system are involved in regulating chicken reproduction. The present study was aimed to identify, on a genome-wide level, novel genes associated with chicken reproductive traits. METHODOLOGY/PRINCIPAL FINDING: Suppressive subtractive hybridization (SSH), genome-wide association study (GWAS), and gene-centric GWAS were used to identify novel genes underlying chicken reproduction. Single marker-trait association analysis with a large population and allelic frequency spectrum analysis were used to confirm the effects of candidate genes. Using two full-sib Ningdu Sanhuang (NDH) chickens, GARNL1 was identified as a candidate gene involved in chicken broodiness by SSH analysis. Its expression levels in the hypothalamus and pituitary were significantly higher in brooding chickens than in non-brooding chickens. GWAS analysis with a NDH two tail sample showed that 2802 SNPs were significantly associated with egg number at 300 d of age (EN300). Among the 2802 SNPs, 2 SNPs composed a block overlapping the GARNL1 gene. The gene-centric GWAS analysis with another two tail sample of NDH showed that GARNL1 was strongly associated with EN300 and age at first egg (AFE). Single marker-trait association analysis in 1301 female NDH chickens confirmed that variation in this gene was related to EN300 and AFE. The allelic frequency spectrum of the SNP rs15700989 among 5 different populations supported the above associations. Western blotting, RT-PCR, and qPCR were used to analyze alternative splicing of the GARNL1 gene. RT-PCR detected 5 transcripts and revealed that the transcript, which has a 141 bp insertion, was expressed in a tissue-specific manner. CONCLUSIONS/SIGNIFICANCE: Our findings demonstrate that the GARNL1 gene contributes to chicken reproductive traits

Volatile Compounds in Honey: A Review on Their Involvement in Aroma, Botanical Origin Determination and Potential Biomedical Activities

Volatile organic compounds (VOCs) in honey are obtained from diverse biosynthetic pathways and extracted by using various methods associated with varying degrees of selectivity and effectiveness. These compounds are grouped into chemical categories such as aldehyde, ketone, acid, alcohol, hydrocarbon, norisoprenoids, terpenes and benzene compounds and their derivatives, furan and pyran derivatives. They represent a fingerprint of a specific honey and therefore could be used to differentiate between monofloral honeys from different floral sources, thus providing valuable information concerning the honey’s botanical and geographical origin. However, only plant derived compounds and their metabolites (terpenes, norisoprenoids and benzene compounds and their derivatives) must be employed to discriminate among floral origins of honey. Notwithstanding, many authors have reported different floral markers for honey of the same floral origin, consequently sensory analysis, in conjunction with analysis of VOCs could help to clear this ambiguity. Furthermore, VOCs influence honey’s aroma described as sweet, citrus, floral, almond, rancid, etc. Clearly, the contribution of a volatile compound to honey aroma is determined by its odor activity value. Elucidation of the aroma compounds along with floral origins of a particular honey can help to standardize its quality and avoid fraudulent labeling of the product. Although only present in low concentrations, VOCS could contribute to biomedical activities of honey, especially the antioxidant effect due to their natural radical scavenging potential

Correlation between p38 mitogen-activated protein kinase and human telomerase reverse transcriptase in sarcomas

<p>Abstract</p> <p>Background</p> <p>One of the major components of telomerase is the human telomerase reverse transcriptase (hTERT) as the catalytic protein. hTERT mRNA expression are reported to be associated with prognosis and tumor progression in several sarcomas. However, there is no clear understanding of the mechanisms of hTERT in human sarcomas. Recent studies have suggested that signals transmitted through p38 mitogen-activated protein kinase (MAPK) can increase or decrease hTERT transcription in human cells. The purpose of this study was to analyse the correlation between p38 MAPK and hTERT in sarcoma samples.</p> <p>Methods</p> <p>We investigated 36 soft tissue malignant fibrous histiocytomas (MFH), 24 liposarcomas (LS) and 9 bone MFH samples for hTERT and p38 MAPK expression. Quantitative detection of hTERT and p38 MAPK was performed by RT-PCR.</p> <p>Results</p> <p>There was a significant positive correlation between the values of hTERT and p38 MAPK in all samples (r = 0.445, p = 0.0001), soft tissue MFH (r = 0.352, p = 0.0352), LS (r = 0.704, p = 0.0001) and bone MFH samples (r = 0.802, p = 0.0093). Patients who had a higher than average expression of p38 MAPK had a significantly worse prognosis than other patients (p = 0.0036).</p> <p>Conclusions</p> <p>p38 MAPK may play a role in up-regulation of hTERT, and therefore, p38 MAPK may be a useful marker in the assessment of hTERT and patients' prognosis in sarcomas.</p

Absence of Aquaporin-4 in Skeletal Muscle Alters Proteins Involved in Bioenergetic Pathways and Calcium Handling

Aquaporin-4 (AQP4) is a water channel expressed at the sarcolemma of fast-twitch skeletal muscle fibers, whose expression is altered in several forms of muscular dystrophies. However, little is known concerning the physiological role of AQP4 in skeletal muscle and its functional and structural interaction with skeletal muscle proteome. Using AQP4-null mice, we analyzed the effect of the absence of AQP4 on the morphology and protein composition of sarcolemma as well as on the whole skeletal muscle proteome. Immunofluorescence analysis showed that the absence of AQP4 did not perturb the expression and cellular localization of the dystrophin-glycoprotein complex proteins, aside from those belonging to the extracellular matrix, and no alteration was found in sarcolemma integrity by dye extravasation assay. With the use of a 2DE-approach (BN/SDS-PAGE), protein maps revealed that in quadriceps, out of 300 Coomassie-blue detected and matched spots, 19 proteins exhibited changed expression in AQP4−/− compared to WT mice. In particular, comparison of the protein profiles revealed 12 up- and 7 down-regulated protein spots in AQP4−/− muscle. Protein identification by MS revealed that the perturbed expression pattern belongs to proteins involved in energy metabolism (i.e. GAPDH, creatine kinase), as well as in Ca2+ handling (i.e. parvalbumin, SERCA1). Western blot analysis, performed on some significantly changed proteins, validated the 2D results. Together these findings suggest AQP4 as a novel determinant in the regulation of skeletal muscle metabolism and better define the role of this water channel in skeletal muscle physiology

The Tissue-Specific Rep8/UBXD6 Tethers p97 to the Endoplasmic Reticulum Membrane for Degradation of Misfolded Proteins

The protein known as p97 or VCP in mammals and Cdc48 in yeast is a versatile ATPase complex involved in several biological functions including membrane fusion, protein folding, and activation of membrane-bound transcription factors. In addition, p97 plays a central role in degradation of misfolded secretory proteins via the ER-associated degradation pathway. This functional diversity of p97 depends on its association with various cofactors, and to further our understanding of p97 function it is important that these cofactors are identified and analyzed. Here, we isolate and characterize the human protein named Rep8 or Ubxd6 as a new cofactor of p97. Mouse Rep8 is highly tissue-specific and abundant in gonads. In testes, Rep8 is expressed in post-meiotic round spermatids, whereas in ovaries Rep8 is expressed in granulosa cells. Rep8 associates directly with p97 via its UBX domain. We show that Rep8 is a transmembrane protein that localizes to the ER membrane with its UBX domain facing the cytoplasm. Knock-down of Rep8 expression in human cells leads to a decreased association of p97 with the ER membrane and concomitantly a retarded degradation of misfolded ER-derived proteasome substrates. Thus, Rep8 tethers p97 to the ER membrane for efficient ER-associated degradation

SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease