Miracle-dz/UniFAR-FTUs huggingface dataset:
Phenotypic plasticity and partial EMT underlie local invasion and distant metastasis in colon cancer

Phenotypic plasticity represents the most relevant hallmark of the metastasizing carcinoma cell as it bestows it with the capacity of altering its own cellular identity when exposed to different environments along the invasion-metastasis cascade. However, the study of the mechanisms underlying phenotypic plasticity is hindered by the rarity of these events within primary lesions and by the lack of experimental study models. Here, we identified a subpopulation of colon cancer cells endowed with phenotypic plasticity: CD44hi/EpCAMlo cells are highly motile, invasive, chemoresistant, and metastatic both in vitro and in vivo. Bulk and single-cell RNAseq analysis indicated that they encompass a broad spectrum of degrees of EMT activation, together with stem/progenitor-like feature, enhanced Wnt/β-catenin signaling, and a high correlation with the CMS4 subtype, accounting for ∼25% of colon cancer cases with poor prognosis. Enhanced Wnt and the downstream upregulation of EMT transcription factors such as ZEB1 represent key events in eliciting phenotypic plasticity to cancer cells along the invasive front of primary colon carcinomas. Of note, different combinations of distinct sets of epithelial and mesenchymal genes define alternative transcriptional trajectories through which state transitions arise. Hybrid E/M stages are predicted to represent the origin of these differentiation routes through biologically-distinct cellular states and as such to underlie the phenotypic plasticity of colon cancer cells.
Development and validation of a clinical risk score to predict the risk of SARS-CoV-2 infection from administrative data: A population-based cohort study from Italy

Background The novel coronavirus (SARS-CoV-2) pandemic spread rapidly worldwide increasing exponentially in Italy. To date, there is lack of studies describing clinical characteristics of the population most at risk of infection. Hence, we aimed to identify clinical predictors of SARS-CoV-2 infection risk and to develop and validate a score predicting SARS-CoV-2 infection risk comparing it with unspecific surrogates. Methods Retrospective case/control study using administrative health-related database was carried out in Southern Italy (Campania region) among beneficiaries of Regional Health Service aged over than 30 years. For each subject with Covid-19 confirmed diagnosis (case), up to five controls were randomly matched for gender, age and municipality of residence. Odds ratios and 90% confidence intervals for associations between candidate predictors and risk of infection were estimated by means of conditional logistic regression. SARS-CoV-2 Infection Score (SIS), was developed by generating a total aggregate score obtained from assignment of a weight at each selected covariate using coefficients estimated from the model. Finally, the score was categorized by assigning increasing values from 1 to 4. SIS was validated by comparison with specific and unspecific predictors of SARS-CoV-2 infection. Results Subjects suffering from diabetes, anaemias, Parkinson’s disease, mental disorders, cardiovascular and inflammatory bowel and kidney diseases showed increased risk of SARS-CoV-2 infection. Similar estimates were recorded for men and women and younger and older than 65 years. Fifteen conditions significantly contributed to the SIS. As SIS value increases, risk progressively increases, being odds of SARS-CoV-2 infection among people with the highest SIS value (SIS=4), 1.74 times higher than those unaffected by any SIS contributing conditions (SIS=1). Conclusion This study identified conditions and diseases making individuals more vulnerable to SARS-CoV-2 infection. Our results are a decision-maker support tool for identifying population most at risk allowing adoption of preventive measures to minimize a potential new relapse damage.
Designing milk fat to improve healthfulness and functional properties of dairy products: from feeding strategies to a genetic approach

Abstract The present review, in the first part, deals with the most effective feeding strategies applied to dairy ruminants in order to enhance the healthfulness of milk fat. The largest changes in milk fatty acid (FA) composition have been obtained either by changing the amounts and the nature of forages in the diets of ruminants, particularly pasture, or by adding plant or marine oils to the diet. Alpine and legume based pastures are associated with high levels of conjugated linoleic acid (CLA), omega-3 FA and with low levels of saturated FA, but further studies are needed with the aim to better explain the effect of some plant species on milk FA composition. Linseed, soybeans safflower and sunflower are the most effective sources of unsaturated plant lipids used to enhance CLA and unsaturated FA content in milk fat. Among animal sources, marine oil is more effective than plant oils for enhancing CLA, vaccenic acid (VA) and omega-3 FA in milk fat, especially when fish oil is fed in combination with oil supplements rich in linoleic acid. In the second part of the review the potential contribute of genetic improvement to modifying milk FA composition is discussed. Recent studies have suggested that the genetic improvement of the nutritional quality of milk based on FA profile may be possible. At this aim, genetic parameters of milk FA composition have been estimated in Dutch, US and Italian Holstein populations and in a Belgian multiple breed population of dairy cows. In dairy sheep and goat there is still a lack of knowledge about genetic parameters and correlations of milk FA. The develop of specific selection indexes aimed to improve the nutritional properties of milk could be supported by the new insight about potential candidate genes able to affect a significant quote of the milk FA variability. Increasing evidences indicate the Stearoyl-CoA Desaturase (SCD) and Diacylglycerol acyltransferase (DGAT-1) genes as possible sources of FA variation in milk. Evidences from quantitative and molecular studies suggest a potential future animal selection, but some question about the kind of selection mechanism and the economic incentive for the improvement should be preliminarily answered.
Exploring the Impact of Random Telegraph Noise-Induced Accuracy Loss on Resistive RAM-Based Deep Neural Network

For resistive RAM (RRAM)-based deep neural network (DNN), random telegraph noise (RTN) causes accuracy loss during inference. In this article, we systematically investigated the impact of RTN on the complex DNNs with different data sets. By using eight mainstream DNNs and four data sets, we explored the origin that caused the RTN-induced accuracy loss. Based on the understanding, for the first time, we proposed a new method to estimate the accuracy loss. The method was verified with other ten DNN/data set combinations that were not used for establishing the method. Finally, we discussed its potential adoption for the cooptimization of the DNN architecture and the RRAM technology, paving ways to RTN-induced accuracy loss mitigation for future neuromorphic hardware systems.
Daphnia defense strategies in fishless lakes and ponds: one size does not fit all

Body size and neck spine development in Daphnia greatly influence this animal’s vulnerability to predation by the size-selective invertebrate planktivore Chaoborus. We develop a stage-classified matrix population model for Daphnia that investigates the interaction and evolution of these two traits in situations (fishless lakes and ponds) where Chaoborus predation constitutes the major source of mortality. This model produces fitness landscapes for these traits in ten distinct Daphnia environments that are characterized by Chaoborus size (medium-sized Chaoborus americanus or large Chaoborus trivittatus), Chaoborus density (0–1.0 L –1 ) and food level (high or low). Larger Daphnia phenotypes are favored in both high and low food environments that contain C. americanus, and also in a high food situation with C. trivittatus. The environments with C. trivittatus and low food availability, however, select for very small, as well as very large, Daphnia phenotypes (small phenotypes are favored more at high Chaoborus densities), but not those that are intermediate in size. The development of neck spines is advantageous in all situations with Chaoborus, but high food environments that contain C. americanus favor their elimination following juvenile development, while the other model environments favor their retention (to various degrees) after maturity. These model predictions describe alternative antipredator strategies, two of which correspond closely with phenotypic patterns exhibited by two species of Daphnia (Daphnia pulex and Daphnia minnehaha) that commonly coexist with Chaoborus in fishless lakes and ponds.
Atrioventricular heart valves of indigenous cattle (Bos indicus): the morphology and morphometry.

Gerec ve Yontem: Calismada sigirlardan alinan kirk atrioventricular kalp kapakcigi kullanildi. Valva tricuspidalis ve valva bicuspidalis, temin edilen kalplerin el ve makas yardimi ile dikkatlice acilmasi ve ventrikuler miyokardiyum’un uzaklastirilmasi ile toplandi. Toplanan kapakciklar pamuga sarilarak kapakciklarin normal yapisi korunmaya calisildi ve daha sonra %10 formol solusyonu icerisinde muhafaza edildi.
Partial prion cross-seeding between fungal and mammalian amyloid signaling motifs

In filamentous fungi, NLR-based signalosomes activate downstream membrane-targeting cell-death inducing proteins by a mechanism of amyloid templating. In the species Podospora anserina, two such signalosomes, NWD2/HET-S and FNT1/HELLF have been described. An analogous system, involving a distinct amyloid signaling motif termed PP was also identified in the genome of the species Chaetomium globosum and studied using heterologous expression in Podospora anserina. The PP-motif bears resemblance to the RHIM and RHIM-like motifs controlling necroptosis in mammals and innate immunity in flies. We identified here, a third NLR signalosome in Podospora anserina comprising a PP-motif and organized as a two-gene cluster encoding a NLR and a HELL-domain cell-death execution protein termed HELLP. We show that the PP-motif region of HELLP forms a prion we term [π] and that [π] prions trigger the cell-death inducing activity of full length HELLP. We detect no prion cross-seeding between HET-S, HELLF and HELLP amyloid motifs. In addition, we find that akin to PP-motifs, RHIM motifs from human RIP1 and RIP3 kinases are able to form prions in Podospora, and that [π] and [Rhim] prions partially cross-seed. Our study shows that Podospora anserina displays three independent cell-death inducing amyloid signalosomes. Based on the described functional similarity between RHIM and PP, it appears likely that these amyloid motifs constitute evolutionary related cell-death signaling modules. Importance Amyloids are β-sheet-rich protein polymers that can be pathological or display a variety of biological roles. In filamentous fungi, specific immune receptors activate programmed cell-death execution proteins through a process of amyloid templating akin to prion propagation. Among these fungal amyloid signaling sequences, the PP-motif stands out because it shows similarity to RHIM, an amyloid sequence controlling necroptotic cell-death in mammals. We characterized an amyloid signaling system comprising a PP-motif in the model species Podospora anserina thus bringing to three the number of independent amyloid signaling cell death pathways described in that species. We then show that human RHIM motifs not only propagate as prions in P. anserina but also partially cross-seed with fungal PP-prions. These results indicate that in addition to show sequence similarity, PP and RHIM-motif are at least partially functionally related, supporting a model of long-term evolutionary conservation of amyloid signaling mechanisms from fungi to mammals.
Epigenomic characterization of latent HIV infection identifies latency regulating transcription factors

Transcriptional silencing of HIV generates a reservoir of latently infected cells, but the mechanisms that lead to this outcome are not well understood. We characterized a primary cell model of HIV latency, and observed that latency is a stable, heritable viral state that is rapidly reestablished after stimulation. Using Assay of Transposon-Accessible Chromatin sequencing (ATACseq) we found that latently infected cells exhibit reduced proviral accessibility, elevated activity of Forkead and Kruppel-like factor transcription factors (TFs), and reduced activity of AP-1, RUNX and GATA TFs. Latency reversing agents caused distinct patterns of chromatin reopening across the provirus. Furthermore, depletion of a chromatin domain insulator, CTCF inhibited HIV latency, identifying this factor as playing a key role in the initiation or enforcement of latency. These data indicate that HIV latency develops preferentially in cells with a distinct pattern of TF activity that promotes a closed proviral structure and inhibits viral gene expression.
Bariatric surgery normalizes circulating glucocorticoid levels and lowers glucocorticoid action tissue-selectively in mice

Background Glucocorticoids produced by the adrenal cortex are essential for the maintenance of metabolic homeostasis. Glucocorticoid activation is catalyzed by 11β-hydroxysteroid dehydrogenase 1 (11β-HSD1) and signalling is achieved through the glucocorticoid receptor (GR), a ligand-dependent transcription factor. Excess glucocorticoids are associated with insulin resistance and hyperglycaemia. A small number of studies have investigated the effects of bariatric surgery, a gastrointestinal procedure known to improve insulin sensitivity, on glucocorticoid metabolism, but the hypothesised mechanism is assumed to be via weight loss. Aim To investigate the effect of bariatric surgery on glucocorticoid metabolism in lean and obese mice. Methods Lean mice and HFD mice underwent Vertical Sleeve Gastrectomy (VSG) or sham surgery. Glucose and insulin tolerance tests were performed at four and ten weeks post operatively and circulating corticosterone was measured. Liver and adipose tissues were harvested from fed mice and 11β-HSD1 and GR levels were measured by quantitative RT-PCR or Western (immuno-) blotting, respectively. Results VSG did not cause excess weight loss in lean mice when compared to sham operated mice. However, both lean and HFD VSG mice displayed significantly improved glucose clearance and insulin sensitivity. Remarkably, VSG restores physiological corticosterone production in HFD mice and reduces11β-HSD1 levels at four and ten weeks post-surgery. Additionally, lean mice displayed significantly lowered mRNA levels of 11β-HSD1 in subcutaneous adipose tissue and GR in liver. Conclusions Bariatric surgery improves insulin sensitivity and reduces glucocorticoid activation at tissular level, under physiological and pathophysiological (obesity) conditions, irrespective of weight loss. The reduction of glucocorticoid exposure may represent an additional contribution to the health benefits of bariatric surgery. These findings point towards a physiologically relevant gut-adrenal axis.
NanoReviser: An Error-Correction Tool for Nanopore Sequencing Based on a Deep Learning Algorithm

Nanopore sequencing is regarded as one of the most promising third-generation sequencing (TGS) technologies. Since 2014, Oxford Nanopore Technologies (ONT) has developed a series of devices based on nanopore sequencing to produce very long reads, with an expected impact on genomics. However, the nanopore sequencing reads are susceptible to a fairly high error rate owing to the difficulty in identifying the DNA bases from the complex electrical signals. Although several basecalling tools have been developed for nanopore sequencing over the past years, it is still challenging to correct the sequences after applying the basecalling procedure. In this study, we developed an open-source DNA basecalling reviser, NanoReviser, based on a deep learning algorithm to correct the basecalling errors introduced by current basecallers provided by default. In our module, we re-segmented the raw electrical signals based on the basecalled sequences provided by the default basecallers. By employing convolution neural networks (CNNs) and bidirectional long short-term memory (Bi-LSTM) networks, we took advantage of the information from the raw electrical signals and the basecalled sequences from the basecallers. Our results showed NanoReviser, as a post-basecalling reviser, significantly improving the basecalling quality. After being trained on standard ONT sequencing reads from public E. coli and human NA12878 datasets, NanoReviser reduced the sequencing error rate by over 5% for both the E. coli dataset and the human dataset. The performance of NanoReviser was found to be better than those of all current basecalling tools. Furthermore, we analyzed the modified bases of the E. coli dataset and added the methylation information to train our module. With the methylation annotation, NanoReviser reduced the error rate by 7% for the E. coli dataset and specifically reduced the error rate by over 10% for the regions of the sequence rich in methylated bases. To the best of our knowledge, NanoReviser is the first post-processing tool after basecalling to accurately correct the nanopore sequences without the time-consuming procedure of building the consensus sequence. The NanoReviser package is freely available at https://github.com/pkubioinformatics/NanoReviser.
Impact of drain water on water quality and eutrophication status of Lake Burullus, Egypt, a southern Mediterranean lagoon

The ecological and biological status of Lake Burullus was examined in 2006 to determine its water quality and eutrophication status in response to the quality and quantity of drain water entering it. The lake suffers from excessive nutrient concentrations. Chlorophyll a showed wide variations over the sampling period with maximum levels (85–122 mg m−3) in the western part in response to the nutrient-rich water inputs from the surrounding farmlands. Nutrients were at maximum levels in the southern and western parts of the lake, which were affected by wastewater discharged into the lake through the drains system. A dense (up to c. 8 × 103 cells ml−1) and more diverse phytoplankton community (about 160 taxa) was found, with a four- to eight-fold increase in species abundance compared to that over the past two decades. Low Secchi transparency (0.15–0.50 m) and high total suspended matter were recorded when phytoplankton was abundant. According to the trophic state index, Lake Burullus could be classified as hypereutrophic with bad to very bad environmental conditions. A degree of nitrogen (N) limitation was recorded, possibly favouring N-fixing cyanobacteria, amongst which toxic species can exist. Lake restoration is recommended through drastic reduction of the external N and phosphorus loads by regulating effluents from fish farms and domestic and industrial sources.
Production of the Short Chain Fatty Acid, Acetic Acid/Acetate from Ethanol Metabolism Activates NMDAR

Short chain fatty acid (SCFA) regulation of neuronal function remains an interesting but poorly understood area of research. The SCFA, acetic acid, the main component of vinegar and the major metabolite of ethanol has been directly linked to altering neuronal function. However, the underlying mechanisms as it relates to alcohol consumption and SCFA regulation of neuronal function have yet to be elucidated. Here we show that local metabolism of ethanol to acetic acid/acetate in the central nucleus of amygdala (CeA) activates glutamatergicN-methyl-D-aspartate receptors (NMDAR)in vivocausing a sympathoexcitatory response. External acetate and intracellular loading of acetic acid in CeA neurons increased neuronal excitability through activation of NMDAR. Furthermore, cultured neurons exposed to acetate showed increased cytosolic calcium which response was abolished by NMDAR antagonist and decreased pH. These findings suggest that acetic acid/acetate is an underestimated bioactive metabolite of ethanol that mediates some effects via an NMDAR-dependent mechanism in the brain. The link between the SCFA, acetic acid/acetate on increased neuronal excitability at least partially through NMDAR may provide a novel avenue for understanding alcohol, metabolic, cardiovascular and neurodegenerative disorders related to alterations in SCFA concentrations in the brain.
The Trans-Ancestral Genomic Architecture of Glycaemic Traits

Glycaemic traits are used to diagnose and monitor type 2 diabetes, and cardiometabolic health. To date, most genetic studies of glycaemic traits have focused on individuals of European ancestry. Here, we aggregated genome-wide association studies in up to 281,416 individuals without diabetes (30% non-European ancestry) with fasting glucose, 2h-glucose post-challenge, glycated haemoglobin, and fasting insulin data. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P<5x10-8), 80% with no significant evidence of between-ancestry heterogeneity. Analyses restricted to European ancestry individuals with equivalent sample size would have led to 24 fewer new loci. Compared to single-ancestry, equivalent sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase understanding of diabetes pathophysiology by use of trans-ancestry studies for improved power and resolution.