Miracle-dz/UniFAR-FTUs huggingface dataset:
ITPR1 Mutation Contributes to Hemifacial Microsomia Spectrum

Hemifacial microsomia (HM) is a craniofacial congenital defect involving the first and second branchial arch, mainly characterized by ocular, ear, maxilla-zygoma complex, mandible, and facial nerve malformation. HM follows autosomal dominant inheritance. Whole-exome sequencing of a family revealed a missense mutation in a highly conserved domain of ITPR1. ITPR1 is a calcium ion channel. By studying ITPR1’s expression pattern, we found that ITPR1 participated in craniofacial development, especially the organs that corresponded to the phenotype of HM. In zebrafish, itpr1b, which is homologous to human ITPR1, is closely related to craniofacial bone formation. The knocking down of itpr1b in zebrafish could lead to a remarkable decrease in craniofacial skeleton formation. qRT-PCR suggested that knockdown of itpr1b could increase the expression of plcb4 while decreasing the mRNA level of Dlx5/6. Our findings highlighted ITPR1’s role in craniofacial formation for the first time and suggested that ITPR1 mutation contributes to human HM.
Simultaneous adsorption of aniline and Cu2+ from aqueous solution using activated carbon/chitosan composite

AbstractA multifunction adsorbent, activated carbon (AC)/chitosan composite, was synthesized by incorporating AC into chitosan based on the ratio of AC to chitosan being 1/1. The simultaneous adsorption of aniline and Cu2+ from aqueous solution onto AC/chitosan composite was investigated by a batch procedure. These results showed that an adsorbent dosage of 0.3 g was appropriate, and a contact time of 210 min was convenient for reaching adsorption equilibriums for aniline and Cu2+. The simultaneous adsorption of aniline and Cu2+ was realized in a wide pH range. The adsorption process obeyed the pseudo-second-order kinetic model. The adsorption behaviors of aniline and Cu2+ followed Freundlich and Langmuir, respectively. No obvious competitive adsorption existed between Cu2+ and aniline.
All Roads Lead to Cytosol: Trypanosoma cruzi Multi-Strategic Approach to Invasion

T. cruzi has a complex life cycle involving four developmental stages namely, epimastigotes, metacyclic trypomastigotes, amastigotes and bloodstream trypomastigotes. Although trypomastigotes are the infective forms, extracellular amastigotes have also shown the ability to invade host cells. Both stages can invade a broad spectrum of host tissues, in fact, almost any nucleated cell can be the target of infection. To add complexity, the parasite presents high genetic variability with differential characteristics such as infectivity. In this review, we address the several strategies T. cruzi has developed to subvert the host cell signaling machinery in order to gain access to the host cell cytoplasm. Special attention is made to the numerous parasite/host protein interactions and to the set of signaling cascades activated during the formation of a parasite-containing vesicle, the parasitophorous vacuole, from which the parasite escapes to the cytosol, where differentiation and replication take place.
Characterization of Tumor Microenvironment in Lung Adenocarcinoma Identifies Immune Signatures to Predict Clinical Outcomes and Therapeutic Responses

Background and Objective Increasing evidence has elucidated the clinicopathological significance of individual TME component in predicting outcomes and immunotherapeutic efficacy in lung adenocarcinoma (LUAD). Therefore, we aimed to investigate whether comprehensive TME-based signatures could predict patient survival and therapeutic responses in LUAD, and to assess the associations among TME signatures, single nucleotide variations and clinicopathological characteristics. Methods In this study, we comprehensively estimated the TME infiltration patterns of 493 LUAD patients and systematically correlated the TME phenotypes with genomic characteristics and clinicopathological features of LUADs using two proposed computational algorithms. A TMEscore was then developed based on the TME signature genes, and its prognostic value was validated in different datasets. Bioinformatics analysis was used to evaluate the efficacy of the TMEscore in predicting responses to immunotherapy and chemotherapy. Results Three TME subtypes were identified with no prognostic significance exhibited. Among them, naïve B cells accounted for the majority in TMEcluster1, while M2 TAMs and M0 TAMs took the largest proportion in TMEcluster2 and TMEcluster3, respectively. A total of 3395 DEGs among the three TME clusters were determined, among which 217 TME signature genes were identified. Interestingly, these signature genes were mainly involved in T cell activation, lymphocyte proliferation and mononuclear cell proliferation. With somatic variations and tumor mutation burden (TMB) of the LUAD samples characterized, a genomic landscape of the LUADs was thereby established to visualize the relationships among the TMEscore, mutation spectra and clinicopathological profiles. In addition, the TMEscore was identified as not only a prognosticator for long-term survival in different datasets, but also a predictive biomarker for the responses to immune checkpoint blockade (ICB) and chemotherapeutic agents. Furthermore, the TMEscore exhibited greater accuracy than other conventional biomarkers including TMB and microsatellite instability in predicting immunotherapeutic response (p < 0.001). Conclusion In conclusion, our present study depicted a comprehensive landscape of the TME signatures in LUADs. Meanwhile, the TMEscore was proved to be a promising predictor of patient survival and therapeutic responses in LUADs, which might be helpful to the future administration of personalized adjuvant therapy.
l-Borneol Exerted the Neuroprotective Effect by Promoting Angiogenesis Coupled With Neurogenesis via Ang1-VEGF-BDNF Pathway

At present, Stroke is still one of the leading causes of population death worldwide and leads to disability. Traditional Chinese medicine plays an important role in the prevention or treatment of stroke. l-borneol, a traditional Chinese medicine, has been used in China to treat stroke for thousands of years. However, its mechanism of action is unclear. After cerebral ischemia, promoting angiogenesis after cerebral ischemia and providing nutrition for the infarct area is an important strategy to improve the damage in the ischemic area, but it is also essential to promote neurogenesis and replenish new neurons. Here, our research shows that l-borneol can significantly improve the neurological deficits of pMCAO model rats, reduce cerebral infarction, and improve the pathological damage of cerebral ischemia. and significantly increase serum level of Ang-1 and VEGF, and significantly decrease level of ACE and Tie2 to promote angiogenesis. PCR and WB showed the same results. Immunohistochemistry also showed that l-borneol can increase the number of CD34 positive cells, further verifying that l-borneol can play a neuroprotective effect by promoting angiogenesis after cerebral ischemia injury. In addition, l-borneol can significantly promote the expression level of VEGF, BDNF and inhibit the expression levels of TGF-β1 and MMP9 to promote neurogenesis. The above suggests that l-borneol can promote angiogenesis coupled neurogenesis by regulating Ang1-VEGF-BDNF to play a neuroprotective effect. Molecular docking also shows that l-borneol has a very high binding rate with the above target, which further confirmed the target of l-borneol to improve cerebral ischemic injury. These results provide strong evidence for the treatment of cerebral ischemia with l-borneol and provide reference for future research.
Identification of ABA-Mediated Genetic and Metabolic Responses to Soil Flooding in Tomato (Solanum lycopersicum L. Mill)

Soil flooding is a compound abiotic stress that alters soil properties and limits atmospheric gas diffusion (O2 and CO2) to the roots. The involvement of abscisic acid (ABA) in the regulation of soil flooding-specific genetic and metabolic responses has been scarcely studied despite its key importance as regulator in other abiotic stress conditions. To attain this objective, wild type and ABA-deficient tomatoes were subjected to short-term (24 h) soil waterlogging. After this period, gas exchange parameters were reduced in the wild type but not in ABA-deficient plants that always had higher E and gs. Transcript and metabolite alterations were more intense in waterlogged tissues, with genotype-specific variations. Waterlogging reduced the ABA levels in the roots while inducing PYR/PYL/RCAR ABA receptors and ABA-dependent transcription factor transcripts, of which induction was less pronounced in the ABA-deficient genotype. Ethylene/O2-dependent genetic responses (ERFVIIs, plant anoxia survival responses, and genes involved in the N-degron pathway) were induced in hypoxic tissues independently of the genotype. Interestingly, genes encoding a nitrate reductase and a phytoglobin involved in NO biosynthesis and scavenging and ERFVII stability were induced in waterlogged tissues, but to a lower extent in ABA-deficient tomato. At the metabolic level, flooding-induced accumulation of Ala was enhanced in ABA-deficient lines following a differential accumulation of Glu and Asp in both hypoxic and aerated tissues, supporting their involvement as sources of oxalacetate to feed the tricarboxylic acid cycle in waterlogged tissues and constituting a potential advantage upon long periods of soil waterlogging. The promoter analysis of upregulated genes indicated that the production of oxalacetate from Asp via Asp oxidase, energy processes such as acetyl-CoA, ATP, and starch biosynthesis, and the lignification process were likely subjected to ABA regulation. Taken together, these data indicate that ABA depletion in waterlogged tissues acts as a positive signal, inducing several specific genetic and metabolic responses to soil flooding.
How SARS-CoV-2 and Comparable Pathogens Can Be Defeated in a Single Day: Description and Mathematical Model of the Carrier Separation Plan (CSP)

A simple, common-sense, three-component procedure—the Carrier Separation Plan (CSP)—can immediately halt the transmission of SARS-CoV-2 or a comparable pathogen, allow the safe reopening of an entire economy without the need for social distancing, and quickly eradicate the pathogen from the population (assuming the pathogen can be killed by the immune systems of the carriers). The three components are (a) nearly simultaneous self-testing for the pathogen by an entire population, followed rapidly by (b) nearly simultaneous self-isolation of carriers, and (c) secondary screening at entrances to facilities where people congregate. After a period of preparation lasting roughly 5–10 weeks, these steps could and probably should be taken in a single day. The power of this methodology has already been demonstrated in varying degrees with groups ranging in size from 1,000 to 11 million. Although this plan might seem daunting, its costs are minimal compared to the losses we have incurred by relying on half measures, and the US and other countries have the technological, logistical, and industrial capacities to implement this plan in a matter of weeks. With proper messaging during the weeks leading up to the testing, compliance in such a program is likely to be high given the potential benefits, and because participation is voluntary and testing is noninvasive, the legal and ethical issues associated with such a program are minimal – trivial, in fact, compared to those associated with imposing a months-long lockdown on an entire population. A SIRD/CSP model suggests that the single-day testing and separation procedure will substantially lower the number of infections, even if compliance with the procedure is modest. Modeling also suggests that when long-term secondary screening is added to the 1-day procedure, over time, the pathogen is eradicated from the population. This can occur even when compliance with secondary screening is itself relatively low.
Development of a Machine Learning Model for Optimal Applicator Selection in High-Dose-Rate Cervical Brachytherapy

Purpose To develop and validate a preliminary machine learning (ML) model aiding in the selection of intracavitary (IC) versus hybrid interstitial (IS) applicators for high-dose-rate (HDR) cervical brachytherapy. Methods From a dataset of 233 treatments using IC or IS applicators, a set of geometric features of the structure set were extracted, including the volumes of OARs (bladder, rectum, sigmoid colon) and HR-CTV, proximity of OARs to the HR-CTV, mean and maximum lateral and vertical HR-CTV extent, and offset of the HR-CTV centre-of-mass from the applicator tandem axis. Feature selection using an ANOVA F-test and mutual information removed uninformative features from this set. Twelve classification algorithms were trained and tested over 100 iterations to determine the highest performing individual models through nested 5-fold cross-validation. Three models with the highest accuracy were combined using soft voting to form the final model. This model was trained and tested over 1,000 iterations, during which the relative importance of each feature in the applicator selection process was determined. Results Feature selection indicated that the mean and maximum lateral and vertical extent, volume, and axis offset of the HR-CTV were the most informative features and were thus provided to the ML models. Relative feature importances indicated that the HR-CTV volume and mean lateral extent were most important for applicator selection. From the comparison of the individual classification algorithms, it was found that the highest performing algorithms were tree-based ensemble methods – AdaBoost Classifier (ABC), Gradient Boosting Classifier (GBC), and Random Forest Classifier (RFC). The accuracy of the individual models was compared to the voting model for 100 iterations (ABC = 91.6 ± 3.1%, GBC = 90.4 ± 4.1%, RFC = 89.5 ± 4.0%, Voting Model = 92.2 ± 1.8%) and the voting model was found to have superior accuracy. Over the final 1,000 evaluation iterations, the final voting model demonstrated a high predictive accuracy (91.5 ± 0.9%) and F1 Score (90.6 ± 1.1%). Conclusion The presented model demonstrates high discriminative performance, highlighting the potential for utilization in informing applicator selection prospectively following further clinical validation.
The Genetic Germline Background of Single and Multiple Primary Melanomas

Background: Melanoma has a complex molecular background and multiple genes are involved in its development and progression. The advent of next generation sequencing platforms has enabled the evaluation of multiple genes at a time, thus unraveling new insights into the genetics of melanoma. We investigated a set of germline mutations able to discriminate the development of multiple primary melanomas (MPM) vs. single site primary melanomas (SPM) using a targeted next generation sequencing panel. Materials and Methods: A total of 39 patients, 20 with SPM and 19 with MPM, were enrolled in our study. Next generation analysis was carried out using a custom targeted sequencing panel that included 32 genes known to have a role in several carcinogenic pathways, such as those involved in DNA repair, pigmentation, regulation of kinases, cell cycle control and senescence. Results: We found a significant correlation between PIK3CA:p.I391M and MPMs, compared to SPMs, p = 0.031 and a trend for the association between CYP1B1: p.N453S and SPMs, compared to MPMs (p = 0.096). We also found that both subgroups shared a spectrum of 9 alterations in 8 genes (CYP1B1: p.N453S, BAP1: p.C39fs, PIK3CA: p.I391M, CDKAL1: c.1226_1227TG, POLE: p.V1161fs, OCA2: p.R419Q, OCA2: p.R305W, MC1R: p.V60L, MGMT: p.L115F), which suggested that these genes may play a role in melanoma development. Conclusions: In conclusion, despite the small cohort of patients, we found that germline mutations, such as those of PIK3CAand CYP1B1, might contribute to the differential development of SPM and MPM.
Assessment of Malnutrition and Intestinal Parasitoses in the Context of Crisis-Hit Venezuela: A Policy Case Study

Venezuela is in the midst of a humanitarian crisis with a dangerous cocktail of hyperinflation, violence, minimal local food production, and policies that impact the nutrition for millions of Venezuelans. Independent data suggests that most Venezuelans are food insecure, with alarming rates of acute and chronic malnutrition, especially among children. A re-emergence of poverty-related intestinal parasitoses and anemia has aggravated their health. With little to no response from public authorities, Venezuela is now the lowest-ranked country in the world in deworming coverage. Modest independent and private epidemiological studies suggest prevalence rates as high as 60% in some regions. This article reviews public health policies regarding malnutrition and intestinal parasitoses and aims to provide a rational approach based on international recommendations for countries in crisis.
The Effect of Dopaminergic Replacement Therapy on Creative Thinking and Insight Problem-Solving in Parkinson's Disease Patients

Parkinson's disease (PD) patients receiving dopaminergic treatment may experience bursts of creativity. Although this phenomenon is sometimes recognized among patients and their clinicians, the association between dopamine replacement therapy (DRT) in PD patients and creativity remains underexplored. It is unclear, for instance, whether DRT affects creativity through convergent or divergent thinking, idea generation, or a general lack of inhibition. It is also unclear whether DRT only augments pre-existing creative attributes or generates creativity de novo. Here, we tested a group of PD patients when “on” and “off” dopaminergic treatment on a series of tests of creative problem-solving (Alternative Uses Task, Compound Remote Associates, Rebus Puzzles), and related their performance to a group of matched healthy controls as well as to their pre-PD creative skills and measures of inhibition/impulsivity. Results did not provide strong evidence that DRT improved creative thinking in PD patients. Rather, PD patients “on” medication showed less flexibility in divergent thinking, generated fewer ideas via insight, and showed worse performance in convergent thinking overall (by making more errors) than healthy controls. Pre-PD creative skills predicted enhanced flexibility and fluency in divergent thinking when PD patients were “on” medication. However, results on convergent thinking were mixed. Finally, PD patients who exhibited deficits in a measure of inhibitory control showed weaker convergent thinking while “on” medication, supporting previous evidence on the importance of inhibitory control in creative problem-solving. Altogether, results do not support the hypothesis that DRT promotes creative thinking in PD. We speculate that bursts of artistic production in PD are perhaps conflated with creativity due to lay conceptions of creativity (i.e., an art-bias).
Pentobarbital Anesthesia Suppresses the Glucose Response to Acute Intermittent Hypoxia in Rat

A key feature of sleep disordered breathing syndromes, such as obstructive sleep apnea is intermittent hypoxia. Intermittent hypoxia is well accepted to drive the sympathoexcitation that is frequently associated with hypertension and diabetes, with measurable effects after just 1 h. The aim of this study was to directly measure the glucose response to 1 h of acute intermittent hypoxia in pentobarbital anesthetized rats, compared to conscious rats. However, we found that while a glucose response is measurable in conscious rats exposed to intermittent hypoxia, it is suppressed in anesthetized rats. Intermittent hypoxia for 1, 2, or 8 h increased blood glucose by 0.7 ± 0.1 mmol/L in conscious rats but had no effect in anesthetized rats (−0.1 ± 0.2 mmol/L). These results were independent of the frequency of the hypoxia challenges, fasting state, vagotomy, or paralytic agents. A supraphysiological challenge of 3 min of hypoxia was able to induce a glycemic response indicating that the reflex response is not abolished under pentobarbital anesthesia. We conclude that pentobarbital anesthesia is unsuitable for investigations into glycemic response pathways in response to intermittent hypoxia in rats.
Variability analysis of resistive ternary content addressable memories

Resistive ternary content addressable memories (Re‐TCAMs) are considered a potential platform for in‐memory associative processing. Re‐TCAM permits the store and process of the data in the same physical area, allowing in‐memory computing. Given the unique properties of the non‐volatile memristive device, Re‐TCAM is capable of low search energy, large‐scale storage, and massively parallel processing. However, like any other semiconductor, memristor as a nanodevice suffers from fabrication process imperfections that provoke a significant variance in their high (RH) and low (RL) resistance states. These variations might lead to the malfunction of the Re‐TCAM array and affect its performance and reliability. This paper proposes a simplified mathematical formulation of the memristor state variability for 2T2M bit‐cell‐based Re‐TCAM array. We present a comprehensive statistical design, considering different circuit parameters and variance effects, such as tolerance of memristance variation, the memristor ratio ( α=RH/RL ), transistor technology, and memory width. The impact of these parameters on the performance is formulated as the probability of error is extensively studied, and a closed‐form expression for the optimal threshold voltage is derived. The utility of the presented investigation is illustrated using a design example with real device parameters.
Interpretable Variational Graph Autoencoder with Noninformative Prior

Variational graph autoencoder, which can encode structural information and attribute information in the graph into low-dimensional representations, has become a powerful method for studying graph-structured data. However, most existing methods based on variational (graph) autoencoder assume that the prior of latent variables obeys the standard normal distribution which encourages all nodes to gather around 0. That leads to the inability to fully utilize the latent space. Therefore, it becomes a challenge on how to choose a suitable prior without incorporating additional expert knowledge. Given this, we propose a novel noninformative prior-based interpretable variational graph autoencoder (NPIVGAE). Specifically, we exploit the noninformative prior as the prior distribution of latent variables. This prior enables the posterior distribution parameters to be almost learned from the sample data. Furthermore, we regard each dimension of a latent variable as the probability that the node belongs to each block, thereby improving the interpretability of the model. The correlation within and between blocks is described by a block–block correlation matrix. We compare our model with state-of-the-art methods on three real datasets, verifying its effectiveness and superiority.