Miracle-dz/UniFAR-FTUs huggingface dataset:
Temperature-dependent gene regulatory divergence underlies local adaptation with gene flow in the Atlantic silverside

Gene regulatory divergence is thought to play an important role in adaptation, yet its extent and underlying mechanisms remain largely elusive under scenarios of local adaptation with gene flow. Local adaptation is widespread in marine species despite generally high connectivity and often associated with tightly-linked genomic architectures, such as chromosomal inversions. To investigate gene regulatory evolution under gene flow and the role of discrete genomic regions associated with local adaptation to a steep thermal gradient, we generated RNA-seq data from Atlantic silversides (Menidia menidia) from two locally adapted populations and their F1 hybrids, reared under two different temperatures. We found substantial divergence in gene expression and thermal plasticity, with up to 31% of genes being differentially expressed, and primarily trans-rather than cis-regulatory divergence between populations, despite ongoing gene flow. Substantially reduced thermal plasticity, temperature-dependent gene misexpression and the disruption of co-expression networks in hybrids point toward a role of regulatory incompatibilities in maintaining local adaptation, particularly under colder temperatures, which appear more challenging for this species. Adaptive chromosomal inversions seem to play an important role in gene regulatory divergence through the accumulation of regulatory incompatibilities but are not consistently enriched for divergently regulated genes. Together, these results highlight that gene regulation can diverge substantially among populations connected by strong gene flow in marine environments, partly due to the accumulation of temperature-dependent regulatory incompatibilities within inversions.
MEK inhibitor resistance in lung cancer cells associated with addiction to sustained ERK suppression

MEK inhibitors have yielded limited efficacy in KRAS-mutant lung adenocarcinoma (LUAD) patients due to drug resistance. We established trametinib-resistant KRAS-mutant LUAD cells and describe a state of “drug addiction” in a subset of resistant cases where cells are dependent on trametinib for survival. Dependence on ERK2 suppression underlies this phenomenon whereby trametinib removal hyperactivates ERK and results in ER stress and apoptosis. Amplification of KRASG12C occurs in drug-addicted cells and blocking mutant specific activity with AMG 510 rescues the lethality after trametinib withdrawal. Furthermore, increased KRASG12C expression is lethal to other KRAS mutant LUAD cells, consequential to ERK hyperactivation. Our study represents the first instance of this phenotype associated with KRAS amplification and demonstrates that acquired genetic changes that develop in the background of MAPK suppression can have unique consequence. We suggest that the presence of mutant KRAS amplification in patients may identify those that may benefit from a “drug holiday” to circumvent drug resistance. These findings demonstrate the toxic potential of hyperactive ERK signaling and highlight potential therapeutic opportunities in patients bearing KRAS mutations.
A novel computational approach to identify cancer cells in scRNA-seq data

Single-cell RNA-seq is an invaluable research tool that allows for the investigation of gene expression in heterogeneous cancer cell populations in ways that bulk RNA-seq cannot. However, normal (i.e., non tumor) cells in cancer samples have the potential to confound the downstream analysis of single-cell RNA-seq data. Several existing methods for identifying tumor cells use copy number variation inference. This work aims to extend existing approaches for identifying cancer cells in single-cell RNA-seq samples by incorporating putative driver alterations. We found that putative driver alterations can be detected in single-cell RNA-seq data and that a subset of cells in tumor samples are enriched in putative driver alterations as compared to normal cells. Furthermore, we show that the number of putative driver alterations and inferred copy number variation are not correlated in all samples. Taken together, our findings suggest that combining copy number variation inference with putative driver mutation load can augment the number of tumor cells that can be confidently included in downstream analyses of single-cell RNA-seq datasets.
Thyroid hormone and ALK5 inhibitor improve maturation of human pluripotent stem cell derived hepatocytes

Hepatocytes derived from human pluripotent stem cells (PSCs) hold great promise for modeling human liver disease, in vitro hepatotoxicity testing, and future cellular therapy. However, current protocols generate hepatocyte-like cells (HLCs) that resemble fetal hepatocytes, and thus do not accurately recapitulate the molecular identity and functions of the adult liver. To address this, we compared the transcriptomes of human fetal and adult liver to PSC-derived HLCs during progressive stages of in vitro differentiation. This revealed that during the final stages of in vitro differentiation the hepatic transcription factors HNF4A and CEBPA were sub-optimally expressed. Computational analyses predicted that ALK5i II (TGF-β receptor inhibitor) and thyroid hormone (T3) would be able to rectify this and improve HLC maturation. We next show that application of these molecules during hepatocyte differentiation indeed increases CEBPA and HNF4A mRNA and protein expression, and that these HLCs show enhanced albumin secretion, a 25-fold increase in CYP3A4 activity, and 10 to 100-fold increased expression of mature hepatic markers. We demonstrate that this improved maturation is effective across different cell lines and HLC differentiation protocols, and exemplifies that our approach provides a tractable template for identifying and targeting additional factors that that will fully mature human liver cells from human pluripotent stem cells.
All-trans retinoic acid enhances the anti-tumour effects of fimaporfin-based photodynamic therapy

The vitamin A metabolite all-trans retinoic acid (ATRA; tretinoin) has anticancer potential. However, lack of clinical success has prevented its approval for solid tumours. Herein, we propose combining short-term low-dose ATRA preconditioning with fimaporfin-based photodynamic therapy (ATRA+PDT) for the improved treatment of solid cancers. Compared to monotherapies, ATRA+PDT induced synergistic cytotoxic responses including promotion of apoptosis in colon and breast carcinoma cell lines. Neither enhanced activity of alkaline phosphatase (ALP) nor increased expression of CD133 was detected after ATRA treatment indicating that ATRA+PDT cause cell death independent of differentiation. In the human colorectal adenocarcinoma cell line HT-29, the effect of ATRA+PDT on gene expression was evaluated by RNA sequencing (RNA-seq). We identified 1129 differentially expressed genes (DEGs) after ATRA+PDT compared to PDT. Ingenuity Pathway Analysis (IPA) predicted the unfolded protein response (UPR), interferon (IFN) signaling and retinoic acid-mediated apoptosis signaling as strongly activated canonical pathways after ATRA+PDT compared to PDT. A validation of the RNA-sec data by RT-qPCR revealed that ATRA+PDT elevated mRNA expression of early growth response 1 (EGR1) and strongly the stress-induced activating transcription factor 3 (ATF3), of which was confirmed on the protein level. In addition, ATRA+PDT abolished mRNA expression of regenerating islet-derived protein 4 (REG4). During the first 20 days post-ATRA+PDT, we obtained significant anti-tumour responses in HT-29 xenografts, including complete responses in 2/5 mice. In conclusion, ATRA+PDT represent a novel combination therapy for solid tumours that should be further tested in immunocompetent preclinical models.
High-resolution quantitative and functional MRI indicate lower myelination of thin and thick stripes in human secondary visual cortex

The characterization of cortical myelination is essential for the study of structure-function relationships in the human brain. However, knowledge about cortical myelination is largely based on post mortem histology, which generally renders direct comparison to function impossible. The repeating pattern of pale-thin-pale-thick stripes of cytochrome oxidase (CO) activity in the primate secondary visual cortex (V2) is a prominent columnar system, in which histology also indicates different myelination of thin/thick versus pale stripes. We used quantitative magnetic resonance imaging (qMRI) in conjunction with functional magnetic resonance imaging (fMRI) at ultra-high field strength (7 T) to localize and study myelination of stripes in four human participants at sub-millimeter resolution in vivo. Thin and thick stripes were functionally localized by exploiting their sensitivity to color and binocular disparity, respectively. Resulting functional activation maps showed robust stripe patterns in V2 which enabled further comparison of quantitative relaxation parameters between stripe types. Thereby, we found lower longitudinal relaxation rates (R1) of thin and thick stripes compared to surrounding gray matter in the order of 1–2%, indicating higher myelination of pale stripes. No consistent differences were found for effective transverse relaxation rates . The study demonstrates the feasibility to investigate structure-function relationships in living humans within one cortical area at the level of columnar systems using qMRI.
Exploration of AI-Oriented Power System Dynamic Simulations

 Abstract —With the rapid development of Artificial Intelligence (AI), it is foreseeable that the accuracy and efficiency of future power system dynamic analysis will be greatly improved by the integration of dynamic simulators and AI. To explore the interaction mechanism of power system dynamic simulations and AI, a general design of an AI-oriented power system dynamic simulator is proposed, which consists of a high-performance simulator with neural network supportability and flexible external and internal application programming interfaces (APIs). With the support of APIs, simulation-assisted AI and AI-assisted simulation form a comprehensive interaction mechanism between power system dynamic simulations and AI. A prototype of this design is implemented and made public based on a highly efficient electromechanical simulator. Tests of this prototype are carried out under four scenarios including sample generation, AI-based stability prediction, data-driven dynamic component modeling, and AI-aided stability control, which prove the validity, flexibility, and efficiency of the design and implementation of the AI-oriented simulator.
Permuton-induced Chinese Restaurant Process

This paper proposes the permuton-induced Chinese restaurant process (PCRP), a stochastic process on rectangular partitioning of a matrix. This distribution is suitable for use as a prior distribution in Bayesian nonparametric relational model to ﬁnd hidden clusters in matrices and network data. Our main contribution is to introduce the notion of permutons into the well-known Chinese restaurant process (CRP) for sequence partitioning: a permuton is a probability measure on [0 , 1] × [0 , 1] and can be regarded as a geometric interpretation of the scaling limit of permutations. Speciﬁcally, we extend the model that the table order of CRPs has a random geometric arrangement on [0 , 1] × [0 , 1] drawn from the permuton. By analogy with the relationship between the stick-breaking process (SBP) and CRP for the inﬁnite mixture model of a sequence, this model can be regarded as a multi-dimensional extension of CRP paired with the block-breaking process (BBP), which has been recently proposed as a multi-dimensional extension of SBP. While BBP always has an inﬁnite number of redundant intermediate variables, PCRP can be composed of varying size intermediate variables in a data-driven manner depending on the size and quality of the observation data. Experiments show that PCRP can improve the prediction performance in relational data analysis by reducing the local optima and slow mixing problems compared with the conventional BNP models because the local transitions of PCRP in Markov chain Monte Carlo inference are more ﬂexible than the previous models.
Ace Your Self-Study: A Mobile Application to Support Self-Regulated Learning

Without guidance, students typically overestimate their understanding and memory of learning materials, which can have detrimental effects on the learning process. However, most students do not receive guidance or instruction about how to study. Moreover, students are largely unaware of strategies to self-regulate their learning and study effectively. Research has shown that prompting both cognitive and metacognitive strategies is effective to support self-regulated learning (SRL). Therefore we developed a mobile application, the Ace your self-study app, to prompt both cognitive and metacognitive strategies to support learning processes. In this article a theoretical background, description of the app’s features and design choices are presented. Also, data from the application in presented to give provide an idea of how the app has been used.
GTPase-Dependent Mechanointegration of Shear-Mediated Cell Contractility Through Dynamic Binding of FLNa and FilGAP

Cellular mechanotransduction is a common mechanism by which cells convert mechanical cues (or stimuli) from their environment into biochemical and cellular responses. In the case of shearing forces, such as when individual cells encounter interstitial shear stress and blood shear stress, mechanotransduction involves mechanical stretching and spatial reconfiguration of Filamin A (FLNa) binding sites and subsequent release of FilGAP molecules normally bound to FLNa. However, the connection and importance of downstream molecular effectors and cellular metrics involved in response to shear stress are not understood. Here we reveal mechano-sensitive GTPase-mediated changes in cell contractility. By varying expression of FilGAP, and expression of FLNa, we show that microfluidic shear stress results in cell contractile changes only when FilGAP and FLNa dynamically bind and dissociate. By using FRET sensors that quantify the Rho or Rac charge state, we demonstrate that only cells with dynamic FLNa and FilGAP convert shear stress into GTPase activity, and the resulting downstream contractile changes. Finally, we show that manipulation of Rho and Rac through pharmacological means rescues the contractile activity, in the absence of intact FLNa-FilGAP mechanosensing. This research clarifies a precise mechanomolecular pathway used for cellular force sensing and may play critical roles in human health challenges from cancer metastasis to cardiovascular disease.
Echocardiographic Evaluation of Initial Ambrisentan Plus Phosphodiesterase Type 5 Inhibitor on Right Ventricular Pulmonary Artery Coupling in Severe Pulmonary Arterial Hypertension Patients

Introduction ambrisentan and phosphodiesterase type 5 inhibitor (PDE5i) have been approved for treating patients with pulmonary arterial hypertension (PAH). Echocardiographic right ventricular pulmonary artery coupling (RVPAC) has been shown to be a valid non-invasive and alternative measurement method to assess the predicted outcomes in PAH patients. The aim of this study was to study the effect and clinical correlates of initial ambrisentan plus PDE5i combination therapy on RVPAC in patients with severe PAH. Method and Results We retrospectively studied and analyzed comprehensive clinical data, hemodynamics, and echocardiography in 27 patients with severe PAH before and after 6 months of initial combination therapy. Compared with the baseline, significant improvements in RVPAC ratios were observed, including RVFAC/PASP (0.31 ± 0.10 vs. 0.44 ± 0.15%/mmHg, p < 0.001), TAPSE/PASP (0.15 ± 0.05 vs. 0.21 ± 0.06 mm/mmHg, p = 0.001), S’/PASP (0.10 ± 0.03 vs. 0.14 ± 0.05 cm/s∙mmHg, p = 0.001), and RVSV/RVESV (0.79 ± 0.22 vs. 1.02 ± 0.20, p < 0.001). Functional status indices [World Health Organization functional classifications (WHO-FC) and 6 min walk distance (6MWD) and N-terminal pro B-type natriuretic peptide (NT-proBNP) levels] showed significant improvements. Right heart catheterization (RHC) evaluations for hemodynamic measurements between baseline and the 6–12 month follow-up were sPAP (96 ± 22 vs. 86 ± 24 mmHg, p = 0.002), mPAP (64 ± 18 vs. 56 ± 17 mmHg, p < 0.001) and TPVR (17.3 ± 6.7 vs. 12.1 ± 5.4 WU, p = 0.001). Simultaneously, significant associations between RVPAC ratios and NT-proBNP levels and WHO-FC and 6MWD were observed. Conclusion Ambrisentan plus PDE-5i combination therapy resulted in a significant improvement in RVPAC in severe PAH. Importantly, RVPAC parameters correlated with known prognostic markers of PAH.
Anticoagulant SERPINs: Endogenous Regulators of Hemostasis and Thrombosis

Appropriate activation of coagulation requires a balance between procoagulant and anticoagulant proteins in blood. Loss in this balance leads to hemorrhage and thrombosis. A number of endogenous anticoagulant proteins, such as antithrombin and heparin cofactor II, are members of the serine protease inhibitor (SERPIN) family. These SERPIN anticoagulants function by forming irreversible inhibitory complexes with target coagulation proteases. Mutations in SERPIN family members, such as antithrombin, can cause hereditary thrombophilias. In addition, low plasma levels of SERPINs have been associated with an increased risk of thrombosis. Here, we review the biological activities of the different anticoagulant SERPINs. We further consider the clinical consequences of SERPIN deficiencies and insights gained from preclinical disease models. Finally, we discuss the potential utility of engineered SERPINs as novel therapies for the treatment of thrombotic pathologies.
Using Experience Sampling Methodology Data to Characterize the Substance Use of Youth With or At-Risk of Psychosis

Objectives Psychotic-spectrum disorders emerge during adolescence and early adulthood, which corresponds with the peak period for substance use initiation. Clinical and epidemiological data provide support that substance use is associated with psychotic symptom onset and severity. Experience-sampling methodology (ESM) data may provide additional insight into dynamic associations between substance use and psychotic symptoms. This is one of the first efforts to characterize substance use frequency and dynamic associations with psychotic symptoms and negative affect from ESM data in both clinical high risk (CHR) and early psychosis (EP) individuals. Methods Using ESM, 33 individuals, including 17 with CHR and 16 EP (age range: 15–24), provided information on substance use, negative affect, and psychotic symptoms 6 times a day across a 21-day data collection window. Psychotic symptoms and negative affect included multi-item variables rated on a seven-point Likert Scale. Participants reported recent substance use for 4 drug classes (nicotine, cannabis, depressants, stimulants) via a yes/no item. Descriptive information included data on substance use frequency, and momentary negative affect and psychotic symptoms. Exploratory analyses included multi-level and person-level dynamic structural equation models, which assessed contemporaneous and lagged associations between substance use and symptoms. Results Twenty-seven individuals (82%) reported recurrent substance use including stimulants (n = 12, 46%), nicotine (n = 9, 27%), cannabis (n = 6, 18%), and depressants (n = 4, 12%). Individuals with any recurrent substance use indicated usage at 47.7% of answered prompts; stimulants at 23.6%; nicotine at 74.2%; cannabis at 39.1%; and depressants at 20.1%. A multi-level dynamic structural equation model reflected that substance use (any class) was associated with lagged negative affect (β = −0.02, CI: −0.06, < -0.00) but no significant contemporaneous or lagged associations between substance use and psychotic symptoms. Person-level models suggest potentially meaningful inter-individual variability. Conclusions CHR and EP individuals use a range of substances that may both reflect and influence other experiences in daily life experiences. Data reflected moderate to high rates of recurrent substance use with more consistent use within nicotine and cannabis classes. ESM data have the potential to increase our understanding of the dynamic relationships between substance use and symptoms and to inform treatment for individuals in early course psychosis.
Head-Mounted Display-Based Virtual Reality and Physiological Computing for Stroke Rehabilitation: A Systematic Review

Virtual reality (VR)-mediated rehabilitation is emerging as a useful tool for stroke survivors to recover motor function. Recent studies are showing that VR coupled with physiological computing (i.e., real-time measurement and analysis of different behavioral and psychophysiological signals) and feedback can lead to 1) more engaged and motivated patients, 2) reproducible treatments that can be performed at the comfort of the patient’s home, and 3) development of new proxies of intervention outcomes and success. While such systems have shown great potential for stroke rehabilitation, an extensive review of the literature is still lacking. Here, we aim to fill this gap and conduct a systematic review of the twelve studies that passed the inclusion criteria. A detailed analysis of the papers was conducted along with a quality assessment/risk of bias evaluation of each study. It was found that the quality of the majority of the studies ranked as either good or fair. Study outcomes also showed that VR-based rehabilitation protocols coupled with physiological computing can enhance patient adherence, improve motivation, overall experience, and ultimately, rehabilitation effectiveness and faster recovery times. Limitations of the examined studies are discussed, such as small sample sizes and unbalanced male/female participant ratios, which could limit the generalizability of the obtained findings. Finally, some recommendations for future studies are given.
Pancreatic Organoids for Regenerative Medicine and Cancer Research

In recent years, the development of ex vivo organoid cultures has gained substantial attention as a model to study regenerative medicine and diseases in several tissues. Diabetes and pancreatic ductal adenocarcinoma (PDAC) are the two major devastating diseases affecting the pancreas. Suitable models for regenerative medicine in diabetes and to accurately study PDAC biology and treatment response are essential in the pancreatic field. Pancreatic organoids can be generated from healthy pancreas or pancreatic tumors and constitute an important translational bridge between in vitro and in vivo models. Here, we review the rapidly emerging field of pancreatic organoids and summarize the current applications of the technology to tissue regeneration, disease modelling, and drug screening.