Miracle-dz/UniFAR-FTUs huggingface dataset:
Mechanistic Modeling of Gene Regulation and Metabolism Identifies Potential Targets for Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the predominant form of liver cancer and has long been among the top three cancers that cause the most deaths worldwide. Therapeutic options for HCC are limited due to the pronounced tumor heterogeneity. Thus, there is a critical need to study HCC from a systems point of view to discover effective therapeutic targets, such as through the systematic study of disease perturbation in both regulation and metabolism using a unified model. Such integration makes sense for cancers as it links one of the dominant physiological features of cancers (growth, which is driven by metabolic networks) with the primary available omics data source, transcriptomics (which is systematically integrated with metabolism through the regulatory-metabolic network model). Here, we developed an integrated transcriptional regulatory-metabolic model for HCC molecular stratification and the prediction of potential therapeutic targets. To predict transcription factors (TFs) and target genes affecting tumorigenesis, we used two algorithms to reconstruct the genome-scale transcriptional regulatory networks for HCC and normal liver tissue. which were then integrated with corresponding constraint-based metabolic models. Five key TFs affecting cancer cell growth were identified. They included the regulator CREB3L3, which has been associated with poor prognosis. Comprehensive personalized metabolic analysis based on models generated from data of liver HCC in The Cancer Genome Atlas revealed 18 genes essential for tumorigenesis in all three subtypes of patients stratified based on the non-negative matrix factorization method and two other genes (ACADSB and CMPK1) that have been strongly correlated with lower overall survival subtype. Among these 20 genes, 11 are targeted by approved drugs for cancers or cancer-related diseases, and six other genes have corresponding drugs being evaluated experimentally or investigationally. The remaining three genes represent potential targets. We also validated the stratification and prognosis results by an independent dataset of HCC cohort samples (LIRI-JP) from the International Cancer Genome Consortium database. In addition, microRNAs targeting key TFs and genes were also involved in established cancer-related pathways. Taken together, the multi-scale regulatory-metabolic model provided a new approach to assess key mechanisms of HCC cell proliferation in the context of systems and suggested potential targets.
Thioredoxin Delays Photoreceptor Degeneration, Oxidative and Inflammation Alterations in Retinitis Pigmentosa

Retinitis pigmentosa (RP) is an inherited ocular disorder with no effective treatment. RP onset and progression trigger a cascade of retinal disorders that lead to the death of photoreceptors. After photoreceptors death, neuronal, glial and vascular remodeling can be observed in the retina. The purpose of this study was to study if thioredoxin (TRX) administration is able to decrease photoreceptor death in an animal model of RP (rd1 mouse), but also if it is able to modulate the retinal oxidative stress, glial and vascular changes that can be observed as the disease progresses. Wild type and rd1 mice received several doses of TRX. After treatment, animals were euthanized at postnatals days 11, 17, or 28. Glutathione (GSH) and other thiol compounds were determined by high performance liquid chromatography (HPLC). Glial fibrilary acidic protein (GFAP) and anti-ionized calcium binding adaptor molecule 1 (Iba1) were studied by immunohistochemistry. Vascular endothelial growth factor (VEGF) and hepatic growth factor (HGF) expression were determined by western blot. TRX administration significantly diminished cell death in rd1 mouse retinas and increased GSH retinal concentrations at postnatal day 11 (PN11). TRX was also able to reverse glial alterations at PN11 and PN17. No alterations were observed in retinal VEGF and HGF expression in rd1 mice. In conclusion, TRX treatment decreases photoreceptor death in the first stages of RP and this protective effect may be due in part to the GSH system activation and to a partially decrease in inflammation.
Intracellular Porphyromonas gingivalis Promotes the Proliferation of Colorectal Cancer Cells via the MAPK/ERK Signaling Pathway

Porphyromonas gingivalis (P. gingivalis) is a keystone pathogen in periodontitis. However, several clinical studies have revealed an enrichment of P. gingivalis in the stool samples and colorectal mucosa of colorectal cancer patients. Thus, the goal of this study was to determine whether P. gingivalis can promote colorectal cancer progression in vitro. We established an acute infection model (24 h, multiplicity of infection =100) of P. gingivalis invasion of colorectal cancer cells to study the alterations induced by P. gingivalis in the proliferation and cell cycle of colorectal cancer cells. We observed that P. gingivalis can adhere and invade host cells a few hours after infection. Once invaded, P. gingivalis significantly promoted colorectal cancer cell proliferation, and the percentage of S phase cells was increased in the cell cycle assay. However, KDP136, a gingipain-deficient mutant of P. gingivalis 33277, showed a decreased ability to promote colorectal cancer cell proliferation, indicating that gingipain is associated with colorectal cancer cell proliferation. Furthermore, we extracted RNA from colorectal cancer cells for high-throughput sequencing analysis and reconfirmed the results by quantitative polymerase chain reaction and western blot analyses. The results suggested that the MAPK/ERK signaling pathway is significantly activated by P. gingivalis, while these changes were not observed for KDP136. In conclusion, P. gingivalis can invade cells and promote the proliferation of colorectal cancer cells by activating the MAPK/ERK signaling pathway. Gingipain is an essential virulence factor in this interaction.
Association Analysis of Neuronal Nitric Oxide Synthase 1 Gene Polymorphism With Psychopathological Symptoms in Chronic Ketamine Users

Objective: We previously found that chronic ketamine usages were associated with various psychotic and cognitive symptoms mimicking schizophrenia. The blockade of the NMDA receptor and subsequent nitric oxide synthase 1 (NOS1) dysfunction were found to be closely correlated with schizophrenia including NOS1 gene polymorphisms. We examined the allelic variants of the gene coding neuronal nitric oxide synthase 1 (NOS1) in chronic ketamine users in the Chinese population and analyzed the association between NOS1 gene polymorphism and psychopathological symptoms in chronic ketamine users. The association between the NOS1 polymorphism and ketamine use characteristics was also examined. Methods: One hundred ninety seven male chronic ketamine users and 82 controls were recruited. Four common SNPs of the NOS1 gene, rs6490121, rs41279104, rs3782206, and rs3782219, were examined by real-time PCR with the TaqMan® assay system. Psychopathological symptoms were assessed using the Positive and Negative Syndrome Scale (PANSS), Beck Depression Inventory (BDI), and the Beck Anxiety Inventory (BAI). Results: The genotype distribution of rs6490121 and rs41279104 in chronic ketamine users was significantly different from that in the control (p = 0.0001 and p = 0.002). The G allele frequency of rs6490121 in ketamine users was higher than that in the control (p = 2.23 * 10−6, OR = 3.07, 95% CI = 1.93–4.90). The T allele frequency of rs41279104 in chronic ketamine users was higher than that in the control (p = 0.01, OR = 1.76, 95% CI = 1.14–2.72). The BAI score was significantly different among the three genotypic groups of rs6490121 (F = 6.21, p = 0.002) in ketamine users; subjects of genotype AG and GG had a lower score than subjects of genotype AA. The score of the negative symptom subscale of PANSS was significantly different among the three genotypic groups of rs41279104 (F = 5.39, p = 0.005); in ketamine users, subjects of genotype CT and TT had a higher score than subjects of genotype CC. There was no difference in drug use characteristics in different genotypes of the four NOS1 gene polymorphisms tested in ketamine users (p > 0.05).
The Role of Context in Language Development for Children With Autism Spectrum Disorder

Parent and preschool teacher ratings of the 10 noun categories of MacArthur-Bates Communication Development Inventory (CDI) were used to study expressive language in 2–4-year-old children with autism spectrum disorder (ASD) (N = 58) across the home and preschool context. There was no significant difference in the total number of words the children said in the two contexts, but the children said significantly more words in the noun categories “Furniture and rooms” and “People” at home. Only one third of the words the children said were said both at home and in the preschool, while the other two thirds were said only at home or only in preschool. This suggests that what words the children use across contexts differ substantially and that their vocabulary is larger than it seems when measured only in one context. This novel study highlights the importance of assessing the language in children with ASD in multiple contexts in order to better measure their vocabulary and to design appropriate language interventions.
Influence of Autocorrelated Rhythmic Auditory Stimulations on Parkinson’s Disease Gait Variability: Comparison With Other Auditory Rhythm Variabilities and Perspectives

Parkinson’s Disease patients suffer from gait impairments such as reduced gait speed, shortened step length, and deterioration of the temporal organization of stride duration variability (i.e., breakdown in Long-Range Autocorrelations). The aim of this study was to compare the effects on Parkinson’s Disease patients’ gait of three Rhythmic Auditory Stimulations (RAS), each structured with a different rhythm variability (isochronous, random, and autocorrelated). Nine Parkinson’s Disease patients performed four walking conditions of 10–15 min each: Control Condition (CC), Isochronous RAS (IRAS), Random RAS (RRAS), and Autocorrelated RAS (ARAS). Accelerometers were used to assess gait speed, cadence, step length, temporal organization (i.e., Long-Range Autocorrelations computation), and magnitude (i.e., coefficient of variation) of stride duration variability on 512 gait cycles. Long-Range Autocorrelations were assessed using the evenly spaced averaged Detrended Fluctuation Analysis (α-DFA exponent). Spatiotemporal gait parameters and coefficient of variation were not modified by the RAS. Long-Range Autocorrelations were present in all patients during CC and ARAS although all RAS conditions altered them. The α-DFA exponents were significantly lower during IRAS and RRAS than during CC, exhibiting anti-correlations during IRAS in seven patients. α-DFA during ARAS was the closest to the α-DFA during CC and within normative data of healthy subjects. In conclusion, Isochronous RAS modify patients’ Long-Range Autocorrelations and the use of Autocorrelated RAS allows to maintain an acceptable level of Long-Range Autocorrelations for Parkinson’s Disease patients’ gait.
CD103 Deficiency Promotes Autism (ASD) and Attention-Deficit Hyperactivity Disorder (ADHD) Behavioral Spectra and Reduces Age-Related Cognitive Decline

The incidence of autism spectrum disorders (ASD) and attention deficit hyperactivity disorder (ADHD), which frequently co-occur, are both rising. The causes of ASD and ADHD remain elusive, even as both appear to involve perturbation of the gut-brain-immune axis. CD103 is an integrin and E-cadherin receptor most prominently expressed on CD8 T cells that reside in gut, brain, and other tissues. CD103 deficiency is well-known to impair gut immunity and resident T cell function, but it's impact on neurodevelopmental disorders has not been examined. We show here that CD8 T cells influence neural progenitor cell function, and that CD103 modulates this impact both directly and potentially by controlling CD8 levels in brain. CD103 knockout (CD103KO) mice exhibited a variety of behavioral abnormalities, including superior cognitive performance coupled with repetitive behavior, aversion to novelty and social impairment in females, with hyperactivity with delayed learning in males. Brain protein markers in female and male CD103KOs coincided with known aspects of ASD and ADHD in humans, respectively. Surprisingly, CD103 deficiency also decreased age-related cognitive decline in both sexes, albeit by distinct means. Together, our findings reveal a novel role for CD103 in brain developmental function, and identify it as a unique factor linking ASD and ADHD etiology. Our data also introduce a new animal model of combined ASD and ADHD with associated cognitive benefits, and reveal potential therapeutic targets for these disorders and age-related cognitive decline.
Artificial Intelligence: A Clarification of Misconceptions, Myths and Desired Status

The field artificial intelligence (AI) was founded over 65 years ago. Starting with great hopes and ambitious goals the field progressed through various stages of popularity and has recently undergone a revival through the introduction of deep neural networks. Some problems of AI are that, so far, neither the “intelligence” nor the goals of AI are formally defined causing confusion when comparing AI to other fields. In this paper, we present a perspective on the desired and current status of AI in relation to machine learning and statistics and clarify common misconceptions and myths. Our discussion is intended to lift the veil of vagueness surrounding AI to reveal its true countenance.
Reproducing Five Motor Behaviors in a Salamander Robot With Virtual Muscles and a Distributed CPG Controller Regulated by Drive Signals and Proprioceptive Feedback

Diverse locomotor behaviors emerge from the interactions between the spinal central pattern generator (CPG), descending brain signals and sensory feedback. Salamander motor behaviors include swimming, struggling, forward underwater stepping, and forward and backward terrestrial stepping. Electromyographic and kinematic recordings of the trunk show that each of these five behaviors is characterized by specific patterns of muscle activation and body curvature. Electrophysiological recordings in isolated spinal cords show even more diverse patterns of activity. Using numerical modeling and robotics, we explored the mechanisms through which descending brain signals and proprioceptive feedback could take advantage of the flexibility of the spinal CPG to generate different motor patterns. Adapting a previous CPG model based on abstract oscillators, we propose a model that reproduces the features of spinal cord recordings: the diversity of motor patterns, the correlation between phase lags and cycle frequencies, and the spontaneous switches between slow and fast rhythms. The five salamander behaviors were reproduced by connecting the CPG model to a mechanical simulation of the salamander with virtual muscles and local proprioceptive feedback. The main results were validated on a robot. A distributed controller was used to obtain the fast control loops necessary for implementing the virtual muscles. The distributed control is demonstrated in an experiment where the robot splits into multiple functional parts. The five salamander behaviors were emulated by regulating the CPG with two descending drives. Reproducing the kinematics of backward stepping and struggling however required stronger muscle contractions. The passive oscillations observed in the salamander's tail during forward underwater stepping could be reproduced using a third descending drive of zero to the tail oscillators. This reduced the drag on the body in our hydrodynamic simulation. We explored the effect of local proprioceptive feedback during swimming and forward terrestrial stepping. We found that feedback could replace or reduce the need for different drives in both cases. It also reduced the variability of intersegmental phase lags toward values appropriate for locomotion. Our work suggests that different motor behaviors do not require different CPG circuits: a single circuit can produce various behaviors when modulated by descending drive and sensory feedback.
Alpha2-Antiplasmin: The Devil You Don't Know in Cerebrovascular and Cardiovascular Disease

Alpha2-antiplasmin (α2AP), the fast-reacting, serine protease inhibitor (serpin) of plasmin, was originally thought to play a key role in protection against uncontrolled, plasmin-mediated proteolysis of coagulation factors and other molecules. However, studies of humans and mice with genetic deficiency of α2AP have expanded our understanding of this serpin, particularly in disease states. Epidemiology studies have shown an association between high α2AP levels and increased risk or poor outcome in cardiovascular diseases. Mechanistic studies in disease models indicate that α2AP stops the body's own fibrinolytic system from dissolving pathologic thrombi that cause venous thrombosis, pulmonary embolism, arterial thrombosis, and ischemic stroke. In addition, α2AP fosters the development of microvascular thrombosis and enhances matrix metalloproteinase-9 expression. Through these mechanisms and others, α2AP contributes to brain injury, hemorrhage and swelling in experimental ischemic stroke. Recent studies also show that α2AP is required for the development of stasis thrombosis by inhibiting the early activation of effective fibrinolysis. In this review, we will discuss the key role played by α2AP in controlling thrombosis and fibrinolysis and, we will consider its potential value as a therapeutic target in cardiovascular diseases and ischemic stroke.
A Pilot Study for Forgiveness Intervention in Adolescents With High Trait Anger: Enhancing Empathy and Harmony

Forgiveness interventions benefit victims’ mental health, reduce levels of anger, and promote forgiveness. However, forgiveness interventions are rarely used to improve the offender’s anger and mental health, especially in specific situations such as juvenile correctional facilities. The offender is often also a victim, and reducing the offender’s excessive anger may prevent or decrease the likelihood of future interpersonal violence. This study examined the effects of forgiveness interventions on anger, forgiveness, empathy, and harmony of juvenile delinquents with high levels of trait anger. Eighteen adolescents with trait anger in a juvenile correctional facility volunteered to participate in group counseling. A pretest–posttest method of quasi-experimental design was used, with 8 participants in the intervention group and 10 in the control group; the intervention group received forgiveness group counseling, and the control group did not. The results revealed that the intervention group had significantly higher scores for forgiveness, empathy, and harmony than the control group, although no significant differences in the scores of state and trait anger were found. The forgiveness intervention had significantly improved the levels of forgiveness toward specific perpetrators of childhood victimization for the juvenile delinquents with high levels of trait anger, raising their levels of empathy and harmony; there was no significant increase in trait anger. The findings indicated that forgiveness intervention provides an effective way to improve the positive mental strength of adolescents with high levels of trait anger.
Soil Salinity Drives the Distribution Patterns and Ecological Functions of Fungi in Saline-Alkali Land in the Yellow River Delta, China

High soil salinity is the main factor that limits soil microbial activity in the Yellow River Delta (YRD); however, its effects on fungal community and ecological function are unknown. Here, we comparatively investigated the diversity and structures of soil fungal communities targeting the internally transcribed fungal spacer gene using Illumina MiSeq sequencing methods under a salt gradient with five levels, namely, Low: low-salinity soil, Medium: medium-salinity soil, High: high-salinity soil, Extreme: extreme-salinity soil, and a non-salted site as the control (Non-saline). The results show that bulk density (BD) values significantly increased (p < 0.05), while significantly lower values of soil total carbon (TC), total nitrogen (TN), and fungal Shannon and Chao indexes were observed as the salinization gradient increased (p < 0.05). The relatively high levels of the families Nectriaceae and Cladosporiaceae distinguished two of the clusters, indicating two enterotypes of low (Non-saline and Low) and high (Medium, High, and Extreme) salinity soils, respectively. The family Nectriaceae was most abundant in the networks, and the positive correlations were more pronounced than negative correlations; however, Cladosporiaceae was the family most negatively correlated with others based on the network analysis. At the ecological function level, plant saprotrophs and litter saprotroph were significantly less abundant in extremely saline soil than non-saline soil. The change in soil properties (TC, TN, and BD) caused by soil salinization [salt and electrical conductivity (EC)] regulated the diversity of soil fungal communities, and ecological function, as indicated by Pearson correlation analyses. We suggest further investigation into the ecological functions of soil microorganisms in the extremely saline-alkaline soils of the YRD.
Image Patch-Based Net Water Uptake and Radiomics Models Predict Malignant Cerebral Edema After Ischemic Stroke

Malignant cerebral edema (MCE) after an ischemic stroke results in a poor outcome or death. Early prediction of MCE helps to identify subjects that could benefit from a surgical decompressive craniectomy. Net water uptake (NWU) in an ischemic lesion is a predictor of MCE; however, CT perfusion and lesion segmentation are required. This paper proposes a new Image Patch-based Net Water Uptake (IP-NWU) procedure that only uses non-enhanced admission CT and does not need lesion segmentation. IP-NWU is calculated by comparing the density of ischemic and contralateral normal patches selected from the middle cerebral artery (MCA) area using standard reference images. We also compared IP-NWU with the Segmented Region-based NWU (SR-NWU) procedure in which segmented ischemic regions from follow-up CT images are overlaid onto admission images. Furthermore, IP-NWU and its combination with imaging features are used to construct predictive models of MCE with a radiomics approach. In total, 116 patients with an MCA infarction (39 with MCE and 77 without MCE) were included in the study. IP-NWU was significantly higher for patients with MCE than those without MCE (p < 0.05). IP-NWU can predict MCE with an AUC of 0.86. There was no significant difference between IP-NWU and SR-NWU, nor between their predictive efficacy for MCE. The inter-reader and interoperation agreement of IP-NWU was exceptional according to the Intraclass Correlation Coefficient (ICC) analysis (inter-reader: ICC = 0.92; interoperation: ICC = 0.95). By combining IP-NWU with imaging features through a random forest classifier, the radiomics model achieved the highest AUC (0.96). In summary, IP-NWU and radiomics models that combine IP-NWU with imaging features can precisely predict MCE using only admission non-enhanced CT images scanned within 24 h from onset.