Miracle-dz/UniFAR-FTUs huggingface dataset:
Cancer Connectors: Connexins, Gap Junctions, and Communication

Despite concerted clinical and research efforts, cancer is a leading cause of death worldwide. Surgery, radiation, and chemotherapy have remained the most common standard-of-care strategies against cancer for decades. However, the side effects of these therapies demonstrate the need to investigate adjuvant novel treatment modalities that minimize the harm caused to healthy cells and tissues. Normal and cancerous cells require communication amongst themselves and with their surroundings to proliferate and drive tumor growth. It is vital to understand how intercellular and external communication impacts tumor cell malignancy. To survive and grow, tumor cells, and their normal counterparts utilize cell junction molecules including gap junctions (GJs), tight junctions, and adherens junctions to provide contact points between neighboring cells and the extracellular matrix. GJs are specialized structures composed of a family of connexin proteins that allow the free diffusion of small molecules and ions directly from the cytoplasm of adjacent cells, without encountering the extracellular milieu, which enables rapid, and coordinated cellular responses to internal and external stimuli. Importantly, connexins perform three main cellular functions. They enable direct gap junction intercellular communication (GJIC) between cells, form hemichannels to allow cell communication with the extracellular environment, and serve as a site for protein-protein interactions to regulate signaling pathways. Connexins themselves have been found to promote tumor cell growth and invasiveness, contributing to the overall tumorigenicity and have emerged as attractive anti-tumor targets due to their functional diversity. However, connexins can also serve as tumor suppressors, and therefore, a complete understanding of the roles of the connexins and GJs in physiological and pathophysiological conditions is needed before connexin targeting strategies are applied. Here, we discuss how the three aspects of connexin function, namely GJIC, hemichannel formation, and connexin-protein interactions, function in normal cells, and contribute to tumor cell growth, proliferation, and death. Finally, we discuss the current state of anti-connexin therapies and speculate which role may be most amenable for the development of targeting strategies.
Robust Distributed Averaging in Networks

In this work, we consider two types of adversarial attacks on a network of nodes seeking to reach consensus. The first type involves an adversary that is capable of breaking a specific number of links at each time instant. In the second attack, the adversary is capable of corrupting the values of the nodes by adding a noise signal. In this latter case, we assume that the adversary is constrained by a power budget. We consider the optimization problem of the adversary and fully characterize its optimum strategy for each scenario.
A New Bifidobacteria Expression SysTem (BEST) to Produce and Deliver Interleukin-10 in Bifidobacterium bifidum

In the last years there has been a growing interest in the use of genetically modified bacteria to deliver molecules of therapeutic interest at mucosal surfaces. Due to the well-recognized probiotic properties of some strains, bifidobacteria represent excellent candidates for the development of live vehicles to produce and deliver heterologous proteins at mucosal surfaces. However, very few studies have considered this genus because of its complexity to be genetically manipulated. In this work, we report the development of a new Bifidobacteria Expression SysTem (BEST) allowing the production of heterologous proteins in Bifidobacterium bifidum. This system is based on: i) the broad host range plasmid pWV01, ii) a stress-inducible promoter, and iii) two different signal peptides (SPs) one issued from Lactococcus lactis (SPExp4) and issued from Bifidobacterium longum (SPBL1181). The functionality of BEST system was validated by cloning murine interleukin-10 (IL-10) and establishing the resulting plasmids (i.e., pBESTExp4:IL-10 and pBESTBL1181:IL-10) in the strain of B. bifidum BS42. We then demonstrated in vitro that recombinant B. bifidum BS42 harboring pBESTBL1181:IL-10 plasmid efficiently secreted IL-10 and that this secretion was significantly higher (sevenfold) than its counterpart B. bifidum BS42 harboring pBESTExp4:IL-10 plasmid. Finally, we validated in vivo that recombinant B. bifidum strains producing IL-10 using BEST system efficiently delivered this cytokine at mucosal surfaces and exhibit beneficial effects in a murine model of low-grade intestinal inflammation.
Stress as a Risk Factor for Substance Use Disorders: A Mini-Review of Molecular Mediators

The extant literature supports the role of stress in enhancing the susceptibility of drug abuse progressing to a substance use disorder diagnosis. However, the molecular mediators by which stress enhances the progression from cocaine abuse to cocaine use disorder via the mesolimbic pathway remain elusive. In this mini-review article, we highlight three mechanisms by which glucocorticoids (GCs) and the dopaminergic system interact. First, GCs upregulate tyrosine hydroxylase (TH), the rate-limiting enzyme in dopamine (DA) synthesis. Second, GCs downregulate monoamine-oxidase (MAO), an enzyme responsible for DA removal. Lastly, GCs are hypothesized to decrease DA reuptake, subsequently increasing synaptic DA. Based on these interactions, we review preclinical literature highlighting how stress modulates the mesolimbic pathway, including the ventral tegmental area (VTA) and nucleus accumbens (NAcs), to alter cocaine abuse-related effects. Taken together, stress enhances cocaine’s abuse-related effects at multiple points along the VTA mesolimbic projection, and uniquely in the NAcs through a positive feedback type mechanism. Furthermore, we highlight future directions to elucidate the interaction between the prefrontal cortex (PFC) and key intermediaries including ΔFosB, cAMP response element binding protein (CREB) and cyclin-dependent kinase 5 (CDK5) to highlight possible mechanisms that underlie stress-induced acceleration of the progression to a cocaine use disorder diagnosis.
Highly Heterogeneous Excitatory Connections Require Less Amount of Noise to Sustain Firing Activities in Cortical Networks

Cortical networks both in vivo and in vitro sustain asynchronous irregular firings with extremely low frequency. To realize such self-sustained activity in neural network models, balance between excitatory and inhibitory activities is known to be one of the keys. In addition, recent theoretical studies have revealed that another feature commonly observed in cortical networks, i.e., sparse but strong connections and dense weak connections, plays an essential role. The previous studies, however, have not thoroughly considered the cooperative dynamics between a network of such heterogeneous synaptic connections and intrinsic noise. The noise stimuli, representing inherent nature of the neuronal activities, e.g., variability of presynaptic discharges, should be also of significant importance for sustaining the irregular firings in cortical networks. Here, we numerically demonstrate that highly heterogeneous distribution, typically a lognormal type, of excitatory-to-excitatory connections, reduces the amount of noise required to sustain the network firing activities. In the sense that noise consumes an energy resource, the heterogeneous network receiving less amount of noise stimuli is considered to realize an efficient dynamics in cortex. A noise-driven network of bi-modally distributed synapses further shows that many weak and a few very strong synapses are the key feature of the synaptic heterogeneity, supporting the network firing activity.
Pathogenomics of Virulence Traits of Plesiomonas shigelloides That Were Deemed Inconclusive by Traditional Experimental Approaches

One of the major challenges of modern medicine includes the failure of conventional protocols to characterize the pathogenicity of emerging pathogens. This is particularly apparent in the case of Plesiomonas shigelloides. Although a number of infections have been linked to this microorganism, experimental evidence of its virulence factors (VFs), obtained by traditional approaches, is somewhat inconclusive. Hence, it remains unclear whether P. shigelloides is a true or opportunistic one. In the current study, four publicly available whole-genome sequences of P. shigelloides (GN7, NCTC10360, 302-73, and LS1) were profiled using bioinformatics platforms to determine the putative candidate VFs to characterize the bacterial pathogenicity. Overall, 134 unique open reading frames (ORFs) were identified that were homologous or orthologous to virulence genes identified in other pathogens. Of these, 52.24% (70/134) were jointly shared by the strains. The numbers of strain-specific virulence traits were 4 in LS1; 7 in NCTC10360; 10 in 302-73; and 15 in GN7. The pathogenicity islands (PAIs) common to all the strains accounted for 24.07% ORFs. The numbers of PAIs exclusive to each strain were 8 in 302-73; 11 in NCTC10360; 14 in GN7; and 18 in LS1. A PAI encoding Vibrio cholerae ToxR-activated gene d protein was specific to 302-73, GN7, and NCTC10360 strains. Out of 33 antibiotic multi-resistance genes identified, 16 (48.48%) genes were intrinsic to all strains. Further, 17 (22.08%) of 77 antibiotic resistance islands were found in all the strains. Out of 23 identified distinct insertion sequences, 13 were only harbored by strain LS1. The number of intact prophages identified in the strains was 1 in GN7; 2 in 302-73; and 2 in NCTC10360. Further, 1 CRISPR element was identified in LS1; 2 in NCTC10360; and 8 in 302-73. Fifteen (78.95%) of 19 secretion systems and secretion effector variants were identified in all the strains. In conclusion, certain P. shigelloides strains might possess VFs associated with gastroenteritis and extraintestinal infections. However, the role of host factors in the onset of infections should not be undermined.
Contraction Dynamics of Rod Microtissues of Gingiva-Derived and Periodontal Ligament-Derived Cells

Tissue engineering strategies using microtissues as “building blocks” have high potential in regenerative medicine. Cognition of contraction dynamics involved in the in vitro self-assembly of these microtissues can be conceived as the bedrock of an effective periodontal tissue regenerative therapy. Our study was directed at evaluating the shrinkage in the rod-shaped structure of a directed self-assembly of human gingiva-derived cells (GC) and periodontal ligament-derived cells (PDLC) and developing insights into the potential mechanisms responsible for the shrinkage. GC and PDLC were seeded in non-adherent agarose molds to form rod microtissues. Cells used for the experiments were characterized using fluorescence-activated cell sorting (FACS). To assess the viability, resazurin-based cytotoxicity assays, trypan blue dye exclusion assay, MTT and live/dead staining, and histological evaluation of rods based on hematoxylin and eosin staining were performed. Rod contraction was evaluated and measured at 0, 2, 6, and 24 h and compared to L-929 cells. The role of transforming growth factor (TGF)-β signaling, phosphoinositide 3-kinase (PI3K)/AKT, and mitogen activated protein kinase (MAPK) signaling was analyzed. Our results show that the rod microtissues were vital after 24 h. A reduction in the length of rods was seen in the 24 h period. While the recombinant TGF-β slightly reduced contraction, inhibition of TGF-β signaling did not interfere with the contraction of the rods. Interestingly, inhibition of phosphoinositide 3-kinase by LY294002 significantly delayed contraction in GC and PDLC rods. Overall, GC and PDLC have the ability to form rod microtissues which contract over time. Thus, approaches for application of these structures as “building blocks” for periodontal tissue regeneration should consider that rods have the capacity to contract substantially. Further investigation will be needed to unravel the mechanisms behind the dynamics of contraction.
Deletion of Glucocorticoid Receptors in Forebrain GABAergic Neurons Alters Acute Stress Responding and Passive Avoidance Behavior in Female Mice

The glucocorticoid receptor (GR) is critically involved in regulation of stress responses [inhibition of the hypothalamic-pituitary-adrenal (HPA) axis], emotional behavior and cognition via interactions with forebrain corticolimbic circuity. Work to date has largely focused on GR actions in forebrain excitatory neurons; however, recent studies suggest a potential role mediated by interneurons. Here, we targeted GR deletion in forebrain GABAergic neurons, including the cortical interneurons, using a Dlx5/6-Cre driver line to test the role of forebrain interneuronal GR in HPA axis regulation and behavior. Our data indicate that GR deletion in GABAergic neurons causes elevated corticosterone stress responsiveness and decreased cross-over latencies in a passive avoidance task in females, but not males. Dlx5/6-Cre driven gene deletion caused loss of GR in interneurons in the prefrontal cortex (PFC) and hippocampus, but also in select diencephalic GABAergic neurons (including the reticular thalamic nucleus and dorsomedial hypothalamus). Our data suggest that GR signaling in interneurons is differentially important in females, which may have implications for GR-directed therapies for stress-related affective disease states.
On board regeneration of uplink signals affected by cross polarization interference and multipath propagation using a blind adaptive multichannel estimator

We propose a method to compensate channel distortions due to multipath and cochannel interference when multichannel transmission is employed in the uplink of an mobile satellite communication system. The signal processing architecture is numerically robust and attractive because vector operations are avoided by efficient orthogonal transformations. Since the algorithm is high order statistics based, it can restore signals also in particularly severe distorsion conditions, when a traditional Kalman multichannel filter perfectly trained obtains poor performance.
Novel Insights Into Bacterial Dimethylsulfoniopropionate Catabolism in the East China Sea

The compatible solute dimethylsulfoniopropionate (DMSP), made by many marine organisms, is one of Earth's most abundant organosulfur molecules. Many marine bacteria import DMSP and can degrade it as a source of carbon and/or sulfur via DMSP cleavage or DMSP demethylation pathways, which can generate the climate active gases dimethyl sulfide (DMS) or methanthiol (MeSH), respectively. Here we used culture-dependent and -independent methods to study bacteria catabolizing DMSP in the East China Sea (ECS). Of bacterial isolates, 42.11% showed DMSP-dependent DMS (Ddd+) activity, and 12.28% produced detectable levels of MeSH. Interestingly, although most Ddd+ isolates were Alphaproteobacteria (mainly Roseobacters), many gram-positive Actinobacteria were also shown to cleave DMSP producing DMS. The mechanism by which these Actinobacteria cleave DMSP is unknown, since no known functional ddd genes have been identified in genome sequences of Ddd+ Microbacterium and Agrococcus isolates or in any other sequenced Actinobacteria genomes. Gene probes to the DMSP demethylation gene dmdA and the DMSP lyase gene dddP demonstrated that these DMSP-degrading genes are abundant and widely distributed in ECS seawaters. dmdA was present in relatively high proportions in both surface (19.53% ± 6.70%) and bottom seawater bacteria (16.00% ± 8.73%). In contrast, dddP abundance positively correlated with chlorophyll a, and gradually decreased with the distance from land, which implies that the bacterial DMSP lyase gene dddP might be from bacterial groups that closely associate with phytoplankton. Bacterial community analysis showed positive correlations between Rhodobacteraceae abundance and concentrations of DMS and DMSP, further confirming the link between this abundant bacterial class and the environmental DMSP cycling.
The combination and prospects of neural networks, fuzzy logic and genetic algorithms

Today, there's a synergy beginning to form among neural nets (NNs), fuzzy logic (FL) and genetic algorithms (GAs). This paper reviews developments in this respect. Many designs of knowledge-based and associated learning systems using the combination of NNs and FL abilities have been presented. Some methods for the integration of GAs with fuzzy systems are described. Afterwards, work on hybrid systems of GAs and NNs is discussed. Finally, some advantages obtained through the fusion of the FL, NNs and GAs are emphasized, and possible ways of combining the three are developed.
Retinal Morphometric Markers of Crystallized and Fluid Intelligence Among Adults With Overweight and Obesity

Objective: To investigate the relationship between retinal morphometric measures and intellectual abilities among adults with overweight and obesity. Methods: Adults between 25 and 45 years (N = 55, 38 females) with overweight or obesity (BMI ≥ 25.0 kg/m2) underwent an optical coherence tomography (OCT) scan to assess retinal nerve fiber layer (RNFL) volume, ganglion cell layer (GCL) volume, macular volume, and central foveal thickness. Dual-Energy X-ray absorptiometry was used to assess whole-body adiposity (% Fat). The Kaufman Brief Intelligence Test-2 was used to assess general intelligence (IQ), fluid, and crystallized intelligence. Hierarchical linear regression analyses were performed to examine relationships between adiposity and intelligence measures following adjustment of relevant demographic characteristics and degree of adiposity (i.e., % Fat). Results: Although initial bivariate correlations indicated that % Fat was inversely related to fluid intelligence, this relationship was mitigated by inclusion of other demographic factors, including age, sex, and education level. Regression analyses for primary outcomes revealed that RNFL was positively related to IQ and fluid intelligence. However, only GCL was positively related to crystallized intelligence. Conclusion: This work provides novel data linking specific retinal morphometric measures – assessed using OCT – to intellectual abilities among adults with overweight and obesity. Clinical Trial Registration: www.clinicaltrials. gov, identifier NCT02740439.
Bacteroides fragilis Prevents Clostridium difficile Infection in a Mouse Model by Restoring Gut Barrier and Microbiome Regulation

Clostridium difficile is currently the leading cause of nosocomial infection. Antibiotics remain the first-line therapy for C. difficile-associated diseases (CDAD), despite the risks of resistance promotion and further gut microbiota perturbation. Notably, the abundance of Bacteroides fragilis was reported to be significantly decreased in CDAD patients. This study aimed to clarify the prophylactic effects of B. fragilis strain ZY-312 in a mouse model of C. difficile infection (CDI). The CDI mouse model was successfully created using C. difficile strain VPI 10463 spores, as confirmed by lethal diarrhea (12.5% survival rate), serious gut barrier disruption, and microbiota disruption. CDI model mice prophylactically treated with B. fragilis exhibited significantly higher survival rates (100% in low dosage group, 87.5% in high dosage group) and improved clinical manifestations. Histopathological analysis of colon and cecum tissue samples revealed an intact gut barrier with strong ZO-1 and Muc-2 expression. The bacterial diversity and relative abundance of gut microbiota were significantly improved. Interestingly, the relative abundance of Akkermansia muciniphila was positively correlated with B. fragilis treatment. In vitro experiments showed that B. fragilis inhibited C. difficile adherence, and attenuated the decrease in CDI-induced transepithelial electrical resistance, ZO-1 and MUC-2 loss, and apoptosis, suggesting that B. fragilis protected against CDI possibly by resisting pathogen colonization and improving gut barrier integrity and functions. In summary, B. fragilis exerted protective effects on a CDI mouse model by modulating gut microbiota and alleviating barrier destruction, thereby relieving epithelial stress and pathogenic colitis triggered by C. difficile. This study provides an alternative preventative measure for CDI and lays the foundations for further investigations of the relationships among opportunistic pathogens, commensal microbiota, and the gut barrier.
In vitro and in vivo Inhibitory Activity of NADPH Against the AmpC BER Class C β-Lactamase

β-Lactamase-mediated resistance to β-lactam antibiotics has been significantly threatening the efficacy of these clinically important antibacterial drugs. Although some β-lactamase inhibitors are prescribed in combination with β-lactam antibiotics to overcome this resistance, the emergence of enzymes resistant to current inhibitors necessitates the development of novel β-lactamase inhibitors. In this study, we evaluated the inhibitory effect of dinucleotides on an extended-spectrum class C β-lactamase, AmpC BER. Of the dinucleotides tested, NADPH, a cellular metabolite, decreased the nitrocefin-hydrolyzing activity of the enzyme with a Ki value of 103 μM in a non-covalent competitive manner. In addition, the dissociation constant (KD) between AmpC BER and NADPH was measured to be 40 μM. According to our in vitro susceptibility study based on growth curves, NADPH restored the antibacterial activity of ceftazidime against a ceftazidime-resistant Escherichia coli BER strain producing AmpC BER. Remarkably, a single dose of combinatory treatment with NADPH and ceftazidime conferred marked therapeutic efficacy (100% survival rate) in a mouse model infected by the E. coli BER strain although NADPH or ceftazidime alone failed to prevent the lethal bacterial infection. These results may offer the potential of the dinucleotide scaffold for the development of novel β-lactamase inhibitors.
Measuring knowledge: investigative research into the quantification of performance within a contextual multi-source PED fusion process

Most intelligence analysts currently use Information Products (IP) from multiple sources with very different characteristics to perform a variety of intelligence tasks. In order to maximize the analysts’ efficacy (and ultimately provide intelligent automation), it is important to understand how and what each IP within the set of IPs contributes to the accuracy and validity of the analytic result. This paper describes initial research toward the development of a scale, analogous to the National Imagery Interpretability Scale (NIIRS), which will measure the knowledge contribution of each of the multi-source IPs, as well as measuring the extent to which the IP set as a whole meets the enduser’s intelligence need – which is actionable knowledge. This scale, the Knowledge-NIIRS (KnIIRS), when completed, will support the measurement of the quality and quantity of information gained through multi-source IP fusion and enables the development of smart (automated) tools for analysts using the next generation of PED workstations. The results of this initial study indicate that analysts are capable of making judgments that reflect the “value” of fused information, and that the judgments they make vary along at least two dimensions. Furthermore, there are substantial and significant differences among analysts in how they make these judgments that must be considered for further scale development. We suggest that the KnIIRS objectives and its derived understandings offer important and critical insights to enable automation that will achieve the goal to deliver actionable knowledge.