Miracle-dz/UniFAR-FTUs huggingface dataset:
The Association of Fat-Mass-and Obesity-Associated Gene Polymorphism (rs9939609) With Colorectal Cancer: A Case-Control Study

Background and Aim The association between the rs9939609 polymorphism of fat mass and obesity-associated gene (FTO) and risk of colorectal cancer is controversial. This study aims to evaluate the relationship between FTO rs9939609 polymorphism and colorectal cancer (CRC) in Iranian people. Methods A case-control study was conducted on 125 patients with CRC and 250 healthy subjects in Tehran, Iran. Demographic data and blood samples were collected from all participants. Genotyping of rs9939609 polymorphism was performed by the tetra-primer amplification refractory mutation system-polymerase chain reaction (T-ARMS-PCR) method. Results The occurrence of AA genotype of FTO rs9939609 polymorphism in the colorectal cancer patients was significantly higher compared to that of healthy subjects (16.4 vs. 2.9%, respectively, P=0.02). The association between the frequency of risk allele of the FTO polymorphism and CRC (B=1.67, P=0.042) remained significant after adjustment for age. Further adjustment for gender (model 2) and marital status (model 3) did not change this result (B=1.67, P= 0.042 and B=1.67, P=0.043, respectively). The results remained significant after additional adjustment for ethnicity (B=1.57, P= 0.047). Conclusion We found a positive association between the A allele of the rs9939609 polymorphism and CRC. Future studies are required to identify the underlying mechanisms.
Towards Deciphering the Fetal Foundation of Normal Cognition and Cognitive Symptoms From Sulcation of the Cortex

Growing evidence supports that prenatal processes play an important role for cognitive ability in normal and clinical conditions. In this context, several neuroimaging studies searched for features in postnatal life that could serve as a proxy for earlier developmental events. A very interesting candidate is the sulcal, or sulco-gyral, patterns, macroscopic features of the cortex anatomy related to the fold topology—e.g., continuous vs. interrupted/broken fold, present vs. absent fold-or their spatial organization. Indeed, as opposed to quantitative features of the cortical sheet (e.g., thickness, surface area or curvature) taking decades to reach the levels measured in adult, the qualitative sulcal patterns are mainly determined before birth and stable across the lifespan. The sulcal patterns therefore offer a window on the fetal constraints on specific brain areas on cognitive abilities and clinical symptoms that manifest later in life. After a global review of the cerebral cortex sulcation, its mechanisms, its ontogenesis along with methodological issues on how to measure the sulcal patterns, we present a selection of studies illustrating that analysis of the sulcal patterns can provide information on prenatal dispositions to cognition (with a focus on cognitive control and academic abilities) and cognitive symptoms (with a focus on schizophrenia and bipolar disorders). Finally, perspectives of sulcal studies are discussed.
Inattention and Uncertainty in the Predictive Brain

Negative effects of inattention on task performance can be seen in many contexts of society and human behavior, such as traffic, work, and sports. In traffic, inattention is one of the most frequently cited causal factors in accidents. In order to identify inattention and mitigate its negative effects, there is a need for quantifying attentional demands of dynamic tasks, with a credible basis in cognitive modeling and neuroscience. Recent developments in cognitive science have led to theories of cognition suggesting that brains are an advanced prediction engine. The function of this prediction engine is to support perception and action by continuously matching incoming sensory input with top-down predictions of the input, generated by hierarchical models of the statistical regularities and causal relationships in the world. Based on the capacity of this predictive processing framework to explain various mental phenomena and neural data, we suggest it also provides a plausible theoretical and neural basis for modeling attentional demand and attentional capacity “in the wild” in terms of uncertainty and prediction error. We outline a predictive processing approach to the study of attentional demand and inattention in driving, based on neurologically-inspired theories of uncertainty processing and experimental research combining brain imaging, visual occlusion and computational modeling. A proper understanding of uncertainty processing would enable comparison of driver's uncertainty to a normative level of appropriate uncertainty, and thereby improve definition and detection of inattentive driving. This is the necessary first step toward applications such as attention monitoring systems for conventional and semi-automated driving.
Genetic Variations and Differential DNA Methylation to Face Contrasted Climates in Small Ruminants: An Analysis on Traditionally-Managed Sheep and Goats

The way in which living organisms mobilize a combination of long-term adaptive mechanisms and short-term phenotypic plasticity to face environmental variations is still largely unknown. In the context of climate change, understanding the genetic and epigenetic bases for adaptation and plasticity is a major stake for preserving genomic resources and the resilience capacity of livestock populations. We characterized both epigenetic and genetic variations by contrasting 22 sheep and 21 goats from both sides of a climate gradient, focusing on free-ranging populations from Morocco. We produced for each individual Whole-Genome Sequence at 12X coverage and MeDIP-Seq data, to identify regions under selection and those differentially methylated. For both species, the analysis of genetic differences (FST) along the genome between animals from localities with high vs. low temperature annual variations detected candidate genes under selection in relation to environmental perception (5 genes), immunity (4 genes), reproduction (8 genes) and production (11 genes). Moreover, we found for each species one differentially methylated gene, namely AGPTA4 in goat and SLIT3 in sheep, which were both related, among other functions, to milk production and muscle development. In both sheep and goats, the comparison between genomic regions impacted by genetic and epigenetic variations suggests that climatic variations impacted similar biological pathways but different genes.
Genistein Inhibits the Pathogenesis of Aeromonas hydrophila by Disrupting Quorum Sensing Mediated Biofilm Formation and Aerolysin Production

Aeromonas hydrophila is an opportunistic pathogen that is responsible for a variety of infectious diseases both in human and animals, particularly aquatic animals. Moreover, the pathogen has become a foodborne pathogen by transmitting from seafood to human. The abuse of antibiotics in aquaculture results in the emergence of antibiotic resistance and treatment failure. Therefore, novel approaches are urgently needed for managing resistant A. hydrophila associated infections. Aerolysin, an essential virulence factor of pathogenic A. hydrophila strain, has been identified as target developing novel drugs against pathogenesis of A. hydrophila. In the present study, genistein, without anti-A. hydrophila activity, was identified that could decrease the production of aerolysin and biofilm formation at a dose-dependent manner. Transcription of aerolysin encoding gene aerA and quorum sensing related genes ahyI and ahyR was significantly down-regulated when co-cultured with genistein. Cell viability studies demonstrated that genistein could significantly improve aerolysin mediated A549 cell injury. Furthermore, genistein could provide a remarkable protection to channel catfish infected with A. hydrophila. These findings indicate that targeting quorum sensing and virulence can be a useful approach developing drugs against A. hydrophila infections in aquaculture. Moreover, genistein can be chosen as a promising candidate in developing drugs against A. hydrophila.
Evaluation of the Short-Term Music Therapy on Brain Functions of Preterm Infants Using Functional Near-Infrared Spectroscopy

Music contains substantial contents that humans can perceive and thus has the capability to evoke positive emotions. Even though neonatal intensive care units (NICUs) can provide preterm infants a developmental environment, they still cannot fully simulate the environment in the womb. The reduced maternal care would increase stress levels in premature infants. Fortunately, music intervention has been proved that it can improve the NICU environment, such as stabilize the heart rate and the respiratory rate, reduce the incidence of apnea, and improve feeding. However, the effects of music therapy on the brain development of preterm infants need to be further investigated. In this paper, we evaluated the influence of short-term music therapy on the brain functions of preterm infants measured by functional near-infrared spectroscopy (fNIRS). We began by investigating how premature babies perceive structural information of music by calculating the correlations between music features and fNIRS signals. Then, the influences of short-term music therapy on brain functions were evaluated by comparing the resting-state functional connectivity before and after the short-term music therapy. The results show that distinct brain regions are responsible for processing corresponding musical features, indicating that preterm infants have the capability to process the complex musical content. However, the results of network analysis show that short-term music intervention is insufficient to cause the changes in cerebral functional connectivity. Therefore, long-term music therapy may be required to achieve the deserved effects on brain functional connectivity.
Interruption of Endolysosomal Trafficking After Focal Brain Ischemia

A typical neuron consists of a soma, a single axon with numerous nerve terminals, and multiple dendritic trunks with numerous branches. Each of the 100 billion neurons in the brain has on average 7,000 synaptic connections to other neurons. The neuronal endolysosomal compartments for the degradation of axonal and dendritic waste are located in the soma region. That means that all autophagosomal and endosomal cargos from 7,000 synaptic connections must be transported to the soma region for degradation. For that reason, neuronal endolysosomal degradation is an extraordinarily demanding and dynamic event, and thus is highly susceptible to many pathological conditions. Dysfunction in the endolysosomal trafficking pathways occurs in virtually all neurodegenerative diseases. Most lysosomal storage disorders (LSDs) with defects in the endolysosomal system preferentially affect the central nervous system (CNS). Recently, significant progress has been made in understanding the role that the endolysosomal trafficking pathways play after brain ischemia. Brain ischemia damages the membrane fusion machinery co-operated by N-ethylmaleimide sensitive factor (NSF), soluble NSF attachment protein (SNAP), and soluble NSF attachment protein receptors (SNAREs), thus interrupting the membrane-to-membrane fusion between the late endosome and terminal lysosome. This interruption obstructs all incoming traffic. Consequently, both the size and number of endolysosomal structures, autophagosomes, early endosomes, and intra-neuronal protein aggregates are increased extensively in post-ischemic neurons. This cascade of events eventually damages the endolysosomal structures to release hydrolases leading to ischemic brain injury. Gene knockout and selective inhibition of key endolysosomal cathepsins protects the brain from ischemic injury. This review aims to provide an update of the current knowledge, future research directions, and the clinical implications regarding the critical role of the neuronal endolysosomal trafficking pathways in ischemic brain injury.
Enriched Environment Attenuates Pyroptosis to Improve Functional Recovery After Cerebral Ischemia/Reperfusion Injury

Enriched environment (EE) is a complex containing social, cognitive, and motor stimuli. Exposure to EE can promote functional recovery after ischemia/reperfusion (I/R) injury. However, the underlying mechanisms remained unclear. Pyroptosis has recently been identified and demonstrated a significant role in ischemic stroke. The purpose of this study was to explore the effect of EE on neuronal pyroptosis after cerebral I/R injury. In the current study, middle cerebral artery occlusion/reperfusion (MCAO/R) was applied to establish the cerebral I/R injury model. Behavior tests including the modified Neurological Severity Scores (mNSS) and the Morris Water Maze (MWM) were performed. The infarct volume was evaluated by Nissl staining. To evaluate the levels of pyroptosis-related proteins, the levels of GSDMD-N and nod-like receptor protein 1/3 (NLRP1/3) inflammasome-related proteins were examined. The mRNA levels of IL-1β and IL-18 were detected by Quantitative Real-Time PCR (qPCR). The secretion levels of IL-1β and IL-18 were analyzed by ELISA. Also, the expression of p65 and p-p65 were detected. The results showed that EE treatment improved functional recovery, reduced infarct volume, attenuated neuronal pyroptosis after cerebral I/R injury. EE treatment also suppressed the activities of NLRP1/NLRP3 inflammasomes. These may be affected by inhabiting the NF-κB p65 signaling pathway. Our findings suggested that neuronal pyroptosis was probably the neuroprotective mechanism that EE treatment rescued neurological deficits after I/R injury.
Enzymatic Fibre Modification During Production of Dissolving Wood Pulp for Regenerated Cellulosic Materials

The production of regenerated cellulosic fibres, such as viscose, modal and lyocell, is based mainly on the use of dissolving wood pulp as raw material. Enzymatic processes are an excellent alternative to conventional chemical routes in the production of dissolving pulp, in terms of energy efficiency, reagent consumption and pulp yield. The two main characteristics of a dissolving pulp are the cellulose purity and the molecular weight, both of which can be controlled with the aid of enzymes. A purification process for paper-grade kraft pulp has been proposed, based on the use of xylanases in combination with hot and cold caustic extraction, without the conventional pre-hydrolysis step before kraft pulping. This enzyme aided purification allowed the production of a dissolving pulp that met the specifications for the manufacture of viscose, < 3% xylan, > 92% ISO brightness and 70% Fock’s reactivity. Endoglucanases (EGs) can efficiently reduce the average molecular weight of the cellulose while simultaneously increasing the pulp reactivity for viscose production. It is shown in this study that lytic polysaccharide monooxygenases act synergistically with EGs in the modification of bleached dissolving pulp.
Biomarkers in Bladder Cancer Surveillance

Aim: This is a narrative review with an aim to summarise and describe urinary biomarkers in the surveillance of non-muscle-invasive bladder cancer (NMIBC). It provides a summary of FDA-approved protein biomarkers along with emerging ones which utilise genetic, epigenetic and exosomal markers. We discuss the current limitations of the available assays. Background: Current guidelines advice a combination of cystoscopy, imaging,and urine cytology in diagnosis and surveillance. Although cytology has a high specificity, it is limited by low sensitivity particularly in low grade tumours. There are six FDA-approved urinary assays for diagnosis and surveillance of bladder cancer. They have shown to improve sensitivity and specificity to be used alongside cytology and cystoscopy but have a lower specificity in comparison to cytology and false positives often occur in benign conditions. Recent developments in laboratory techniques has allowed for use of markers which are RNA-, DNA-based as well as extracellular vesicles in the past decade. Methods: Using the PubMed/Medline search engines as well as Google Scholar, we performed an online search using the terms “bladder cancer,” “non-muscle invasive bladder cancer,” and “urine biomarkers” with filter for articles in English published up to May 2021. Systematic reviews and original data of clinical trials or observational studies which contributed to the development of the biomarkers were collated. Results: Biomarkers identified were divided into FDA-approved molecular biomarkers, protein biomarkers and gene-related biomarker with a table summarising the findings of each marker with the most relevant studies. The studies conducted were mainly retrospective. Due to the early stages of development, only a few prospective studies have been done for more recently developed biomarkers and limited meta-analyses are available.Therefore a detailed evaluation of these markers are still required to decide on their clinical use. Conclusion: Advancements of analytical methods in BC has driven the research towards non-invasive liquid-based biomarkers in adjunct to urine cytology. Further large prospective studies are required to determine its feasibility in a clinical setting as they are not effective when used in isolation as they have their limitation. With the ongoing pandemic, other than reduction in costs and increased accuracy, the need for biomarkers to cope with delay in cystoscopies in diagnosis and surveillance is crucial. Thus clinical trials with direct comparison is required to improve patient care.
The Role of Short-Chain Fatty Acids of Gut Microbiota Origin in Hypertension

Hypertension is a significant risk factor for cardiovascular and cerebrovascular diseases, and its development involves multiple mechanisms. Gut microbiota has been reported to be closely linked to hypertension. Short-chain fatty acids (SCFAs)—the metabolites of gut microbiota—participate in hypertension development through various pathways, including specific receptors, immune system, autonomic nervous system, metabolic regulation and gene transcription. This article reviews the possible mechanisms of SCFAs in regulating blood pressure and the prospects of SCFAs as a target to prevent and treat hypertension.
Hemodynamic and Morphological Parameters of Ruptured Mirror Posterior Communicating Artery Aneurysms

Objective: Morphological and hemodynamic parameters might predict rupture of intracranial aneurysms (IAs). A practical model for the study is patients with ruptured mirror IAs in which one is ruptured and the other is unruptured. Although there have been analyses of the morphology and hemodynamics of ruptured mirror posterior communicating artery aneurysms (PComAAs), the sample sizes in these studies were small and only considered hemodynamics or morphological characters. Therefore, this study aimed to investigate the morphological and hemodynamic parameters associated with ruptured mirror PComAAs. Methods: We considered 72 patients with ruptured mirror PComAAs using computational fluid dynamics (CFDs). Ruptured mirror PComAAs were divided into ruptured and unruptured groups. Fourteen morphological and eight hemodynamic parameters were calculated and compared. Significant parameters were analyzed by the multivariate logistic regression to identify independent risk factors. Receiver operating characteristic (ROC) analysis was performed, and the area under the ROC curve (AUC) was calculated for all independent risk factors to determine the predictability and identify the optimal threshold. Results: Four hemodynamic and three morphological parameters were significantly different between ruptured and unruptured groups: normalized wall shear stress (NWSS), mean WSS, low wall shear WSS area (LSA%), size, aspect ratio (AR), size ratio (SR), and inflow angle (IA). Multivariate logistic regression analysis showed that AR, SR, NWSS, mean WSS, and LSA% were all independent factors significantly associated with PComAAs rupture. The ROC analysis for independent risk factors indicated that AR (0.751), NWSS (0.755), mean WSS (0.69), and LSA (0.778) had merely acceptable AUC values. Only SR (0.803) had a high acceptable AUC value. The threshold value of SR was 1.96. Conclusions: SR (>1.96) was the most significant parameter associated with IA rupture, whereas AR, NWSS, mean WSS, and LSA independently characterized the status of IA rupture.
Q-Learning-Based SCMA for Efficient Random Access in mMTC Networks With Short Packets

In massive machine-type communications (mMTC) networks, the ever-growing number of MTC devices and the limited radio resources have caused a severe problem of random access channel (RACH) congestion. To mitigate this issue, several potential multiple access (MA) mechanisms including sparse code MA (SCMA) have been proposed. Besides, the short-packet transmission feature of MTC devices requires the design of new transmission and congestion avoidance techniques as the existing techniques based on the assumption of infinite data-packet length may not be suitable for mMTC networks. Therefore, it is important to find novel solutions to address RACH congestion in mMTC networks while considering SCMA and short-packet communications (SPC). In this paper, we propose an SCMA-based random access (RA) method, in which Q-learning is utilized to dynamically allocate the SCMA codebooks and time-slot groups to MTC devices with the aim of minimizing the RACH congestion in SPC-based mMTC networks. To clarify the benefits of our proposed method, we compare its performance with those of the conventional RA methods with/without Q-learning in terms of RA efficiency and evaluate its convergence. Our simulation results show that the proposed method outperforms the existing methods in overloaded systems, i.e., the number of devices is higher than the number of available RA slots. Moreover, we illustrate the sum rate comparison between SPC and long-packet communications (LPC) when applying the proposed method to achieve more insights on SPC.
Cluster-Based Routing Approach in Hierarchical Wireless Sensor Networks toward Energy Efficiency using Genetic Algorithm

Energy efficiency is one of the important factors when exploiting Wireless Sensor Networks, especially for increasing lifespan and performance. In the network nowadays, the number of sensor nodes can reach hundreds or thousands and can be arranged in complex hierarchical architecture. Besides, the current sensor nodes have a small size, limited battery source but are operated in vast areas. The clustered-based method has been an effective and potentially extensible means of boosting the management and operation of such large-scale networks and minimizing the overall energy consumption. In this paper, the issue of arranging and routing the nodes in the sensor network in a hierarchical manner is investigated, in which each lowest level sensor nodes are grouped in a cluster with a common cluster head, then the cluster-head plays an intermediate role transmit the information back and forth between the sensor nodes and the base station. In this way, the route to exchange information can not only be optimized with respect to the distance but also for energy spent on the communication. In order to do so, this paper proposed a novel method based on a Genetic Algorithm to establish a routing protocol to achieve energy optimization. The results demonstrate that this approach can decrease the energy consumption according to the optimized routing through clustering and increase the performance superior to the other clustering schemes.