Miracle-dz/UniFAR-FTUs huggingface dataset:
Role of GPER1 in the Mechanism of EGFR-TKIs Resistance in Lung Adenocarcinoma

Epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitors (TKIs) have a good clinical efficacy in lung adenocarcinoma harboring activating-mutation EGFR. Such EGFR mutations are more frequently observed in women and non-smokers. EGFR mutations are frequently reported to correlate with estrogen receptor (ER) α and/or β-expressions in lung adenocarcinoma. However, the role of GPER1, a novel G-protein-coupled estrogen receptor, in the estrogen signaling pathway and the association between its expression and EGFR mutation in lung adenocarcinoma are less well understood. Here, we aimed to examine ERα, Erβ, and GPER1 expressions, and to analyze their roles in the mechanism of EGFR-TKIs resistance in lung adenocarcinoma. We report an enhanced cytoplasmic expression of GPER1 in tissue samples. The nuclear GPER1 positively correlated with ER expression while the nuclear and also cytoplasmic expressing GPER1 negatively correlated with ER expression. Further, TKI resistance results in higher cytoplasmic GPER1 expression and decreased ER and nuclear GPER1 expression with evidence for GPER1 translocation to cell surface during the resistance. GPER1 itself is capable of regulating ER expression with concomitant regulation of MAPK signaling, and co-inhibition of GPER1 and ERs attenuates ERK1/2 and Akt phosphorylation. The results were also verified in vivo in mice where GPER1 silencing slowed tumor progression which was further potentiated by gefitinib.
Sinusoidal Optic Flow Perturbations Reduce Transient but Not Continuous Postural Stability: A Virtual Reality-Based Study

Optic flow perturbations induced by virtual reality (VR) are increasingly used in the rehabilitation of postural control and gait. Here, VR offers the possibility to decouple the visual from the somatosensory and vestibular system. By this means, it enables training under conflicting sensorimotor stimulation that creates additional demands on sensory reweighting and balance control. Even though current VR-interventions still lack a well-defined standardized metric to generate optic flow perturbations that can challenge balance in a repeatable manner, continuous oscillations of the VR are typically used as a rehabilitation tool. We therefore investigated if continuous sensory conflicts induced by optic flow perturbations can challenge the postural system sustainably. Eighteen young adults (m = 8, f = 10, age = 24.1 ± 2.0 yrs) were recruited for the study. The VR was provided using a state-of-the-art head-mounted display including the virtual replica of the real environment. After familiarization in quiet stance without and with VR, bipedal balance was perturbed by sinusoidal rotations of the visual scenery in the sagittal plane with an amplitude of 8° and a frequency of 0.2 Hz. Postural stability was quantified by mean center of mass speed derived from 3D-kinematics. A rmANOVA found increased postural instability only during the first perturbation cycle, i.e., the first 5 s. Succeeding the first perturbation cycle, visual afferents were downregulated to reduce the destabilizing influence of the sensory conflicts. In essence, only the transient beginning of sinusoidal oscillation alters balance compared to quiet standing. Therefore, continuous sinusoidal optic flow perturbations appear to be not suitable for balance training as they cannot trigger persisting sensory conflicts and hence challenge the postural system sustainably. Our study provides rationale for using unexpected and discrete optic flow perturbation paradigms to induce sustainable sensory conflicts.
Efficacy of a Combined Acceptance and Commitment Intervention to Improve Psychological Flexibility and Associated Symptoms in Cancer Patients: Study Protocol for a Randomized Controlled Trial

Psychological flexibility is a key concept of acceptation and commitment therapy (ACT). This factor has been linked with psychological wellbeing and associated factors, such as quality of life, in cancer patients. These and other positive results of acceptation and commitment therapy in cancer patients found in previous research could be enhanced by using mhealth tools. A three-arm randomized superiority clinical trial, with a pre-post-follow-up repeated measures intergroup design with a 1:1:1 allocation ratio is proposed. A hundred and twenty cancer patients will be randomly assigned to one of the following interventions: (1) face-to-face ACT + mobile application (app), (2) face-to-face ACT, and (3) Waitlist control group. The primary expected outcome is to observe significant improvements in psychological flexibility acceptance and action questionnaire- II (AAQ-II) in the face-to-face ACT + app group, after comparing baseline and post-treatment scores, and the scores will remain stable in the two assessment points, 3 and 6 months after the intervention. Secondary expected outcomes are significant increasing scores in quality of life (EORTC QLQ C-30) and post-traumatic-growth (PTGI-SF), and significant decreasing scores in anxiety and depression (HADS), insomnia (ISI) and fatigue (BFI) at the same assessment points. Also, it is expected that the scores of this group will be higher than the scores of the face-to-face ACT group and the waitlist control group. This study aims to assess the efficacy of a combined intervention (face-to face ACT + app) for psychological flexibility and associated symptoms in cancer patients. The results of this protocol may help to consider the use of acceptation and commitment therapy and mhealth applications in cancer settings as a valid therapeutic choice. Clinical Trial Registration [www.ClinicalTrials. gov], identifier [NCT05126823].
Extreme Precipitation in the Eastern Canadian Arctic and Greenland: An Evaluation of Atmospheric Reanalyses

Extreme precipitation events are becoming more common in the Arctic as the climate warms, but characterizing these events is notoriously challenging. Atmospheric reanalyses have become popular tools for climate studies in data-sparse regions such as the Arctic. While modern reanalyses have been shown to perform reasonably well at reproducing Arctic climate, their ability to represent extreme precipitation events has not been investigated in depth. In this study, three of the most recent reanalyses, ERA-5, MERRA-2, and CFSR, are compared to surface precipitation observations in the Eastern Canadian Arctic and Greenland from 1980 to 2016 to assess how well they represent the most intense observed events. Overall, the reanalyses struggled to match observed accumulations from individual events (−0.11 ≤ r ≤ 0.47) but matched the observed seasonality of precipitation extremes. The region with the strongest match between observations and reanalyses was Southwest Greenland. Performance varies by event, and the best match between reanalyses and station observations may have a spatial/temporal offset (up to one grid cell or 1 day). The three products saw similar performance in general; however, ERA-5 tends to see slightly higher correlations and lower biases than MERRA-2 or CFSR. Considering the limitations of in situ observations, these results suggest that the reanalyses are capable of representing aggregate extreme precipitation (e.g., seasonal or annual time scales), but struggle to consistently match the timing and location of specific observed events.
Identification of Novel Immune Ferropotosis-Related Genes Associated With Clinical and Prognostic Features in Gastric Cancer

Background Gastric cancer (GC) is the fifth commonest cancer and the third commonest reason of death causing by cancer worldwide. Currently, tumor immunology and ferropotosis develop rapidly that has made gastric cancer be treated in new directions. So, finding the potential targets and prognostic biomarkers for immunotherapy combined with ferropotosis is urgent. Methods By mining TCGA, immune-related genes, ferropotosis-related genes and immune-ferropotosis-related differentially expressed genes (IFR-DEGs) were identified. The independent prognostic value of IFR-DEGs was determined by differential expression analysis, prognostic analysis, and univariate and lasso regression analysis. Then, based on the prognostic risk model, the correlation between IFR-DEGs and immune scores, immune checkpoints were evaluated. Besides, we predicted the response of high and low risk groups to drugs. Results A 15-gene prognostic feature was constructed. The high-risk group had a poorer prognosis than the low-risk group. High-risk group had higher level of Treg immune cell infiltration compared with that in the low-risk group, and the tumor purity, immune checkpoint PD-1 and CTLA4, and immunity in the high-risk group were higher than those in the low-risk group. These results indicate that immune ferropotosis-related genes migh be potential predictors of STAD’s response to ICI immunotherapy biomarkers. In addition, the response of small molecule drugs such as Nilotini, Sunitinib, Imatinib, etc. for high and low risk groups was predicted. Conclusion IFRSig can be regarded as an independent prognostic feature and may estimate OS and clinical treatment response in patients with STAD. IFRSig also has important correlation with immune microenvironment. A new understanding of the immune-ferropotosis-related genes during the occurrence and development of STAD is provided in this study.
The Impacts of the CEO's Network Effect on Digitalization and Agile Leadership in China

: Digitalization as a business enabler has speeded and scaled innovation in many firms. As the corporate leader, the CEO is there to set the stage for a learning process that facilitates strategic agility and enhances network effects to create value. This study uses innovation efficiency as the proxy of digitalization to examine the contribution of the CEO networks to firm-level innovation efficiency in Chinese listed firms. We apply a frontier analysis approach (e.g., DEA and SFA) and measure innovation efficiency based on the scale ratio of innovation output (i.e., patent counts) and input (R&D investment and R&D personnel). First, we find that innovation is more efficient when CEO has more outside directorships by considering 13,516 firm-year observations in Chinese listed high-tech firms between 2007 and 2017. Second, a significant and positive relationship exists between a well-connected CEO and innovation efficiency when the newly appointed CEO has larger networks than the predecessor. Third, it is found out that the positive correlation between a well-connected CEO and innovation efficiency will become non-significant when the number of outside directorships is above the yearly median level. This empirical study provides evidence for the network effects of a CEO for improving innovation efficiency. The findings emphasize the contingent value of the CEO's external social capital on agility, especially the multiple directorships in a transitional economy.
Data Quality Influences the Predicted Distribution and Habitat of Four Southern-Hemisphere Albatross Species

Few studies have assessed the influence of data quality on the predicted probability of occurrence and preferred habitat of marine predators. We compared results from four species distribution models (SDMs) for four southern-hemisphere albatross species, Buller’s (Thalassarche bulleri), Campbell (T. impavida), grey-headed (T. chrysostoma), and white-capped (T. steadi), based on datasets of differing quality, ranging from no location data to twice-daily locations of individual birds collected by geolocation devices. Two relative environmental suitability (RES) models were fit using minimum and maximum preferred and absolute values for each environmental variable based on (1) monthly 50% kernel density contours and background environmental data, and (2) primary literature or expert opinion. Additionally, two boosted regression tree (BRT) models were fit using (1) opportunistic sightings data, and (2) geolocation data from bird-borne electronic tags. Using model-specific threshold values, habitat was quantified for each species and model. Model variables included distance from land, bathymetry, sea surface temperature, and chlorophyll-a concentration. Results from both RES models and the BRT model fit with opportunistic sightings were compared to those from the BRT model fit using geolocation data to assess the influence of data quality on predicted occupancy and habitat. For all species, BRT models outperformed RES models. BRT models offer a predictive advantage over RES models by being able to identify relevant variables, incorporate environmental interactions, and provide spatially explicit estimates of model uncertainty. RES models resulted in larger, less refined areas of predicted habitat for all species. Our study highlights the importance of data quality in predicting the distribution and habitat of albatrosses and emphasises the need to consider the pros and cons associated with different levels of data quality when using SDMs to inform management decisions. Furthermore, we examine the overlap in preferred habitat predicted by each SDM with fishing effort. We discuss the influence of data quality on predicting the wide-scale distributions of pelagic seabirds and how these impacts could result in different protection measures.
Mapping Microbial Abundance and Prevalence to Changing Oxygen Concentration in Deep-Sea Sediments Using Machine Learning and Differential Abundance

Oxygen constitutes one of the strongest factors explaining microbial taxonomic variability in deep-sea sediments. However, deep-sea microbiome studies often lack the spatial resolution to study the oxygen gradient and transition zone beyond the oxic-anoxic dichotomy, thus leaving important questions regarding the microbial response to changing conditions unanswered. Here, we use machine learning and differential abundance analysis on 184 samples from 11 sediment cores retrieved along the Arctic Mid-Ocean Ridge to study how changing oxygen concentrations (1) are predicted by the relative abundance of higher taxa and (2) influence the distribution of individual Operational Taxonomic Units. We find that some of the most abundant classes of microorganisms can be used to classify samples according to oxygen concentration. At the level of Operational Taxonomic Units, however, representatives of common classes are not differentially abundant from high-oxic to low-oxic conditions. This weakened response to changing oxygen concentration suggests that the abundance and prevalence of highly abundant OTUs may be better explained by other variables than oxygen. Our results suggest that a relatively homogeneous microbiome is recruited to the benthos, and that the microbiome then becomes more heterogeneous as oxygen drops below 25 μM. Our analytical approach takes into account the oft-ignored compositional nature of relative abundance data, and provides a framework for extracting biologically meaningful associations from datasets spanning multiple sedimentary cores.
Reconstruction of the Evolutionary Origin, Phylodynamics, and Phylogeography of the Porcine Circovirus Type 3

Porcine circovirus type 3 (PCV3) is a newly identified virus associated with porcine dermatitis and nephropathy syndrome (PDNS) and multisystemic inflammatory responses in pigs. Recent studies suggests that PCV3 originated from bat circoviruses; however, the origin time, mode of spread, and geographic distribution of PCV3 remain unclear. In this study, the evolutionary origin, phylodynamics, and phylogeography of PCV3 were reconstructed based on the available complete genome sequences. PCV3 showed a closer relationship with bird circovirus than with bat circovirus, but their common ancestor was bat circovirus, indicating that birds may be intermediate hosts for the spread of circoviruses in pigs. Using the BEAST and phylogenetic analyses, three different clades of PCV3 (PCV3a, PCV3b, and PCV3c) were identified, with PCV3a being the most prevalent PCV3 clade. Further studies indicated that the earliest origin of PCV3 can be traced back to 1907.53–1923.44, with a substitution rate of 3.104 × 10–4 to 6.8524 × 10–4 substitution/site/year. A phylogeographic analysis highlighted Malaysia as the earliest location of the original PCV3, which migrated to Asia, America, and Europe. Overall, this study provides novel insights into the evolutionary origin, spread mode, and geographic distribution of PCV3, which will facilitate the prevention and control of PCV3 epidemics in the future.
Title: Multi-Omics and Immune Landscape of Proliferative LncRNA Signatures: Implications for Risk Stratification and Immunotherapy in Hepatocellular Carcinoma

Background: Long noncoding RNAs (lncRNAs) are significantly implicated in tumor proliferation. Nevertheless, proliferation-derived lncRNAs and their latent clinical significance remain largely unrevealed in hepatocellular carcinoma (HCC). Methods: This research enrolled 658 HCC patients from five independent cohorts. We retrieved 50 Hallmark gene sets from the MSigDB portal. Consensus clustering was applied to identify heterogeneous proliferative subtypes, and the nearest template prediction (NTP) was utilized to validate the subtypes. We introduced an integrative framework (termed “ProLnc”) to identify proliferation-derived lncRNAs. Moreover, a proliferation-related signature was developed and verified in four independent cohorts. Results: In 50 Hallmarks, seven proliferation pathways were significantly upregulated and correlated with a worse prognosis. Subsequently, we deciphered two heterogeneous proliferative subtypes in TCGA-LIHC. Subtype 2 displayed enhanced proliferative activities and a worse prognosis, whereas subtype 1 was associated with hyperproliferative HCC and a favorable prognosis. The NTP further verified the robustness and reproducibility of two subtypes in four cohorts derived from different platforms. Combining the differentially expressed lncRNAs from two subtypes with proliferative lncRNA modulators from our ProLnc pipeline, we determined 230 proliferation-associated lncRNAs. Based on the bootstrapping channel and the verification of multiple cohorts, we further identified ten lncRNAs that stably correlated with prognosis. Subsequently, we developed and validated a proliferative lncRNA signature (ProLncS) that could independently and accurately assess the overall survival (OS) and relapse-free survival (RFS) of HCC patients in the four cohorts. Patients with high ProLncS score displayed significantly genomic alterations (e.g., TP53 mutation, 8p23-8p24 copy number variation) and higher abundances of immune cells and immune checkpoint molecules, which suggested immunotherapy was more suitable for patients with high ProLncS score. Conclusion: Our work provided new insights into the heterogeneity of tumor proliferation, and ProLncS could be a prospective tool for tailoring the clinical decision and management of HCC.
Robust Neuro-Fuzzy Control of N-Link Robot Manipulators: Discrete-Time Case

This paper deals with the design of robust and model-free controller for an n-link robot manipulator in discrete-time domain. At the first step, a robust and model-based discrete-time sliding mode controller (DSMC) is developed. Afterwards, a discrete-time neuro-fuzzy sliding mode controller (DNFSMC) is proposed to remove the drawbacks of DSMC. In this technique, a neural network (NN) parallel with fuzzy blocks is utilized to approximate the equivalent and switching terms of DSMC. NN weights are updated adaptively with back-propagation algorithm by using the fuzzy system output. Simulation results are illustrated to compare performances of DSMC and DNFSMC in the control of a three-link SCARA robot. Moreover, the sampling time effects on DNFSMC are discussed.
Slow Shallow Energy States as the Origin of Hysteresis in Perovskite Solar Cells

Organic-inorganic metal halide perovskites have attracted a considerable interest in the photovoltaic scientific community demonstrating a rapid and unprecedented increase in conversion efficiency in the last decade. Besides the stunning progress in performance, the understanding of the physical mechanisms and limitations that govern perovskite solar cells are far to be completely unravelled. In this work, we study the origin of their hysteretic behaviour from the standpoint of fundamental semiconductor physics by means of technology computer aided design electrical simulations. Our findings identify that the density of shallow interface defects at the interfaces between perovskite and transport layers plays a key role in hysteresis phenomena. Then, by comparing the defect distributions in both spatial and energetic domains for different bias conditions and using fundamental semiconductor equations, we can identify the driving force of hysteresis in terms of slow recombination processes and charge distributions.
Impact of the COVID-19 Pandemic on China's Stock Market Volatility, During and After the Outbreak: Evidence From an ARDL Approach

Purpose In this study, we empirically investigate the impact of the COVID-19 pandemic on China's stock price volatility during and after its initial outbreak, using time-series daily data covering the period from July to October, 2020 and 2021, respectively. Design/Methodology/Approach In the estimation, the ARDL bounds test approach was employed to examine the existence of co-integration and the relationship of long-run and short-run between the new infection rates and stock price volatility, as stable and unstable variables are mixed. The inner-day and inter-day volatility, based on the Shanghai (securities) composite index, are estimated in separate empirical models. In addition, the Inter-bank overnight lending rate (IBOLR) is controlled in order to consider the effect of liquidity and investment cost. Findings and Implications We find that in the initial year (2020) of the epidemic, the new infection rate is negatively correlated to stock prices in the short-term, whereas no significant evidence existed in the long-term, regardless of model specifications. However, after the epidemic's outbreak (2021), the result depicts that new infections increased stock prices in the long-term, and depressed its inner-day volatility in the short-term, which is inconsistent with most investigations. This phenomenon may be due to the fact that investors were more concerned about the withdrawal of monetary easing and fiscal stimulus, which were introduced to fight against the epidemic's impact on economy, than the epidemic itself. This study complements the limitations of most existing studies, which just focus on the period of the epidemic's outbreak, and provides insight into macroeconomic policy making in the era of the post COVID-19 epidemic such as the structural and ordered exit of the stimulating policies, intervention in IBOLR and balance social and economic sustainability.