Miracle-dz/UniFAR-FTUs huggingface dataset:
Grapevine Responses to Heat Stress and Global Warming

The potential effects of the forthcoming climate change include the rising of the average annual temperature and the accumulation of extreme weather events, like frequent and severe heatwaves, a phenomenon known as global warming. Temperature is an important environmental factor affecting almost all aspects of growth and development in plants. The grapevine (Vitis spp.) is quite sensitive to extreme temperatures. Over the current century, temperatures are projected to continue rising with negative impacts on viticulture. These consequences range from short-term effects on wine quality to long-term issues such as the suitability of certain varieties and the sustainability of viticulture in traditional wine regions. Many viticultural zones, particularly in Mediterranean climate regions, may not be suitable for growing winegrapes in the near future unless we develop heat-stress-adapted genotypes or identify and exploit stress-tolerant germplasm. Grapevines, like other plants, have developed strategies to maintain homeostasis and cope with high-temperature stress. These mechanisms include physiological adaptations and activation of signaling pathways and gene regulatory networks governing heat stress response and acquisition of thermotolerance. Here, we review the major impacts of global warming on grape phenology and viticulture and focus on the physiological and molecular responses of the grapevine to heat stress.
Assessing Prognostic and Predictive Biomarkers of Regorafenib Response in Patients with Advanced Soft Tissue Sarcoma: REGOSARC Study

Simple Summary In a double-blind, placebo-controlled, randomized phase 2 trial, Regorafenib provided a clinical benefit to patients with advanced and anthracycline-pretreated soft tissue sarcoma. However, extensive mutational analysis of tumor genes could not identify predictive markers of regorafenib efficacy, including among genes involving in angiogenesis (FLT1, FLT2, FLT3, FLT4, KDR, TEK (TIE2), and VHL). The identification of the precise mechanism of action of multikinase inhibitor in sarcoma and the identification of responding patients requires further clinical studies. Abstract Regorafenib significantly prolonged progression-free survival (PFS) in pretreated patients with advanced non-adipocytic sarcoma (HR = 0.46; p < 0.001) in a placebo-controlled, randomized, phase-II trial (NCT01900743). Thus, here, we assessed the prevalence of 57 biomarkers and their prognostic and predictive values for PFS and overall survival (OS). We analyzed 134/182 patients included in this trial, treated with regorafenib (n = 71, 53%) or placebo (n = 63, 47%). Mutational analyses were performed via full coding sequence analysis for 10 genes, and mutation hotspot panel for 50 genes (four genes in common). H19 was studied with RNA in-situ hybridization. The prognostic and predictive biomarkers’ values were studied only for biomarkers found positive/mutated in at least 10 patients. Overall, 25 out of 57 studied biomarkers, including five out of seven genes involved in angiogenesis, were found mutated/positive in at least one patient, of which 23 biomarkers had low prevalence (fewer than eight out of 134 patients), contrasting with H19 (n = 24, 18%), and TP53 (n = 35, 26%). However, in multivariable models of PFS and OS, including treatment effects and interactions, no significant prognostic or predictive values of the tested biomarkers were observed. Though several promising biomarkers were found to be positive/mutated, none of them were identified as viable predictive and prognostic biomarkers.
Targeting the tumor microenvironment in cholangiocarcinoma: implications for therapy

ABSTRACT Introduction: Cholangiocarcinomas (CCAs) are biliary epithelial tumors with rising incidence over the past 3 decades. Early diagnosis of CCAs remains a significant challenge and the majority of patients present at an advanced stage. CCAs are heterogeneous tumors and currently available standard systemic therapy options are of limited effectiveness. Immune checkpoint inhibition (ICI) has transformed cancer therapy across a spectrum of malignancies. However, the response rate to ICI has been relatively disappointing in CCAs owing to its desmoplastic tumor microenvironment (TME). Areas covered: Tumor microenvironment of CCAs consists of innate and adaptive cells, stromal cells, and extracellular components (cytokines, chemokines, exosomes, etc.). This intricate microenvironment has multiple immunosuppressive elements that promote tumor cell survival and therapeutic resistance. Accordingly, there is a need for the development of effective therapeutic strategies that target the TME. Herein, we review the components of the CCA TME, and potential therapies targeting the CCA TME. Expert opinion: CCAs are desmoplastic tumors with a dense tumor microenvironment. An enhanced understanding of the various components of the CCA TME is essential in the effort to develop novel biomarkers for patient stratification as well as combination therapeutic strategies that target the tumor plus the TME.
Prediction of Cassava Starch Edible Film Properties by Chemometric Analysis of Infrared Spectra

Abstract Cassava starch has been shown to make transparent and colorless flexible films without any previous chemical treatment. The functional properties of edible films are influenced by starch properties, including chain conformation, molecular bonding, crystallinity, and water content. Fourier‐transform infrared (FTIR) spectroscopy in combination with attenuated total reflectance (ATR) has been applied for the elucidation of the structure and conformation of carbohydrates. This technique associated with chemometric data processing could indicate the relationship between the structural parameters and the functional properties of cassava starch–based edible films. Successful prediction of the functional properties values of the starch–based films was achieved by partial least squares regression data. The results showed that presence of the hydroxyl group on carbon 6 of the cyclic part of glucose is directly correlated with the functional properties of cassava starch films. This paper was by special invi.
Protein subcellular localization based on deep image features and criterion learning strategy

The spatial distribution of proteome at subcellular levels provides clues for protein functions, thus is important to human biology and medicine. Imaging-based methods are one of the most important approaches for predicting protein subcellular location. Although deep neural networks have shown impressive performance in a number of imaging tasks, its application to protein subcellular localization has not been sufficiently explored. In this study, we developed a deep imaging-based approach to localize the proteins at subcellular levels. Based on deep image features extracted from convolutional neural networks (CNNs), both single-label and multi-label locations can be accurately predicted. Particularly, the multi-label prediction is quite a challenging task. Here we developed a criterion learning strategy to exploit the label-attribute relevancy and label-label relevancy. A criterion that was used to determine the final label set was automatically obtained during the learning procedure. We concluded an optimal CNN architecture that could give the best results. Besides, experiments show that compared with the hand-crafted features, the deep features present more accurate prediction with less features. The implementation for the proposed method is available at https://github.com/RanSuLab/ProteinSubcellularLocation.
Bactericidal antibodies against hypervirulent Neisseria meningitidis C field strains following MenC-CRM or MenACWY-CRM priming and MenACWY-CRM booster in children

ABSTRACT An increase in invasive meningococcal disease (IMD) incidence was observed in Tuscany in 2015/2016, mainly due to hypervirulent clonal complex (cc) 11 strains. In a post-hoc analysis, we assessed bactericidal activity of antibodies in sera from children primed with MenACWY-CRM or MenC-CRM conjugate vaccines and receiving a MenACWY-CRM booster dose against 5 meningococcal C (MenC) strains isolated from IMD cases. Sera collected from 90 infants/toddlers who participated in a phase III, open-label study (NCT00667602) and its extension (NCT01345721) were tested by serum bactericidal activity assay with human complement (hSBA). Children were primed with either MenACWY-CRM at 6–8 and 12 months of age (group 2_MenACWY; N = 30), MenACWY-CRM (group 1_MenACWY; N = 30), or MenC-CRM at 12 months of age (group 1_MenC; N = 30); all received MenACWY-CRM booster dose at 22–45 months of age. Four tested strains (FI001–FI004) were C:P1.5–1,10-8:F3-6:ST-11 (cc11) and 1 (FI005) was C:P1.7–4,14-6:F3-9:ST-1031 (cc334). Overall, immune responses tended to be higher against Fl002–FI004 than Fl001 and Fl005. Geometric mean titers were high in group 2_MenACWY (range: 94.8 [FI005]–588.1 [FI004]) and very high post-boosting with MenACWY-CRM in all groups (176.9 [FI005]–3911.0 [FI004]). Seroresponse rates tended to be higher in group 1_MenC (33.3% [FI005]–93.3% [FI004]) than in group 1_MenACWY (16.7% [FI005]–73.3% [FI004]). Irrespective of strains tested or the identity/number of priming doses, ≥96.7% of children had hSBA titers ≥1:8 post-MenACWY-CRM booster dose. MenACWY-CRM and MenC-CRM elicited bactericidal antibodies and immunological memory against hypervirulent cc11 and cc334 MenC strains responsible for IMD outbreaks.
EED is Required for Male and Female Primordial Germ Cell Differentiation in the Embryonic Gonad

Primordial germ cells (PGCs) are the source of the entire germ line in adult animals. During PGC development in mammals, major epigenetic remodeling occurs characterized by an almost complete loss of DNA methylation from genomic DNA accompanied by a global increase in H3K27me3. Through the use of a conditional knockout in mouse PGCs (mPGCs), we show that H3K27me3 is essential for regulating the expression of germ cell differentiation genes and preventing precocious sex-specific differentiation in response to signals from the gonadal niche. Although H3K27me3 affects both male and female mPGC development during the gonadal stages of germline reprogramming in the embryo, the female germline is more sensitive to loss of H3K27me3. Taken together, the differentiation of mPGCs requires the coordinated activity of H3K27me3, DNA methylation and hydroxymethylation as well as the ubiquitination of H2AK119ub1 to regulate timing of PGC differentiation into oocytes and prospermatogonia.
Validation of the Chinese Version of the Body Image Concern Inventory

The Body Image Concern Inventory (BICI) was developed to assess dysmorphic appearance concern and has been found to be a reliable and valid instrument in Western societies. To examine the psychometric properties of a new Chinese BICI, the BICI was administered to 1,231 Chinese young adults (Study 1) and 47 female patients with eating disorders and 56 matched controls (ED; Study 2). In study 1, Cronbach’s alpha of . 92 and test-retest reliability of . 73 over a 6-month interval was observed for the total scale. Confirmatory factor analysis supported a 3-factor model for the BICI: avoidant behaviors (AB), safety behaviors against perceived flaws (SB), and negative appearance evaluation (NE). In study 2, ED patients scored significantly higher on the BICI total and three subscale scores than controls. In addition, AB best differentiated ED patients and matched controls (Cohen’s d = 1.52); SB best differentiated between the non-clinical female and male groups (Cohen’s d = 0.75); NE was most closely associated with level of negative affect and subjective well-being (inverse relationship) in both clinical and non-clinical groups. In conclusion, the Chinese BICI is a reliable and valid tool for evaluating dysmorphic appearance concern among Chinese speakers.
Prospective Associations Between Fixed-Term Contract Positions and Mental Illness Rates in Denmark’s General Workforce: Protocol for a Cohort Study

Background In 2018, 14% of employees in the European Union had fixed-term contracts. Fixed-term contract positions are often less secure than permanent contract positions. Perceived job insecurity has been associated with increased rates of mental ill health. However, the association between fixed-term contract positions and mental ill health is uncertain. A recent review concluded that the quality of most existing studies is low and that the results of the few studies with high quality are contradictory. Objective This study aims to estimate the incidence rate ratios (RRs) of psychotropic drug use and psychiatric hospital treatment. These ratios will be considered, first, in relation to the contrast fixed-term versus permanent contract and, second, to fixed-term contract versus unemployment. Methods Interview data with baseline information on employment status from the Danish Labor Force Surveys in the years 2001-2013 will be linked to data from national registers. Participants will be followed up for up to 5 years after the interview. Poisson regression will be used to estimate incidence RRs for psychiatric hospital treatment for mood, anxiety, or stress-related disorders and redeemed prescriptions for psychotropic drugs, as a function of employment status at baseline. The following contrasts will be considered: full-time temporary employment versus full-time permanent employment and temporary employment (regardless of weekly working hours) versus unemployment. The analyses will be controlled for a series of possible confounders. People who have received sickness benefits, have received social security cash benefits, have redeemed a prescription for psychotropic drugs, or have received psychiatric hospital treatment for a mental disorder sometime during a 1-year period preceding baseline will be excluded from the study. The study will include approximately 134,000 participants (13,000 unemployed, 106,000 with permanent contracts, and 15,000 with fixed-term contracts). We expect to find approximately 16,400 incident cases of redeemed prescriptions of psychotropic drugs and 2150 incident cases of psychiatric hospital treatment for mood, anxiety, or stress-related disorders. Results We expect the analyses to be completed by the end of 2021 and the results to be published in mid-2022. Conclusions The statistical power of the study will be large enough to test the hypothesis of a prospective association between fixed-term contract positions and mental illness in the general workforce of Denmark. International Registered Report Identifier (IRRID) DERR1-10.2196/24392
Inclusion of Effect Size Measures and Clinical Relevance in Research Papers.

BACKGROUND There are multiple issues that arise when researchers focus on and only report "statistical significance" of study findings. An important element that is often not included in reports is a discussion of clinical relevance. OBJECTIVES The authors address issues related to significance, the use of effect sizes, confidence or credible intervals, and the inclusion of clinical relevance in reports of research findings. METHODS Measures of magnitude, precision, and relevance such as effect sizes, confidence intervals (CIs), and clinically relevant effects are described in detail. Additionally, recommendations for reporting and evaluating effect sizes and CIs are included. Example scenarios are presented to illustrate the interplay of statistical significance and clinical relevance. RESULTS There are several issues that may arise when significance is the focus of clinical research reporting. One issue is the lack of attention to nonsignificant findings in published works even though findings demonstrate clinical relevance. Another issue is that significance is interpreted as clinical relevance. As well, clinically relevant results from small sample studies are often not considered for publication, and, thus, findings might not be available for meta-analysis. DISCUSSION Findings in research reports should address effect sizes and clinical relevance and significance. Failure to publish clinically relevant effects and CIs may preclude the inclusion of clinically relevant studies in systematic reviews and meta-analyses thereby limiting the advancement of evidence-based practice. Several accessible resources for researchers to generate, report, and evaluate measures of magnitude, precision, and relevance are included in this article.
SPInDel Analysis of the Non-Coding Regions of cpDNA as a More Useful Tool for the Identification of Rye (Poaceae: Secale) Species

Secale is a small but very diverse genus from the tribe Triticeae (family Poaceae), which includes annual, perennial, self-pollinating and open-pollinating, cultivated, weedy and wild species of various phenotypes. Despite its high economic importance, classification of this genus, comprising 3–8 species, is inconsistent. This has resulted in significantly reduced progress in the breeding of rye which could be enriched with functional traits derived from wild rye species. Our previous research has suggested the utility of non-coding sequences of chloroplast and mitochondrial DNA in studies on closely related species of the genus Secale. Here we applied the SPInDel (Species Identification by Insertions/Deletions) approach, which targets hypervariable genomic regions containing multiple insertions/deletions (indels) and exhibiting extensive length variability. We analysed a total of 140 and 210 non-coding sequences from cpDNA and mtDNA, respectively. The resulting data highlight regions which may represent useful molecular markers with respect to closely related species of the genus Secale, however, we found the chloroplast genome to be more informative. These molecular markers include non-coding regions of chloroplast DNA: atpB-rbcL and trnT-trnL and non-coding regions of mitochondrial DNA: nad1B-nad1C and rrn5/rrn18. Our results demonstrate the utility of the SPInDel concept for the characterisation of Secale species.
Transcriptional readout of neuronal activity via an engineered Ca2+-activated protease

Significance Molecular reporters that “remember” the activity history of a cell and give a corresponding signal that can be read out by imaging, sequencing, or other modalities are valuable tools for the study of neural networks. Here, we develop a reporter that drives stable expression of any transgene (such as a fluorescent protein) in response to cellular calcium activity during a user-defined time window. As calcium is a universal proxy for neural activity, our reporter provides a stable “snapshot” of neural activity which can be used for subsequent imaging, analysis, or manipulation of behavior-associated neural networks. A core feature of our reporter is an engineered calcium-activated protease, which cuts a protein sequence to reveal a transcription factor when cellular calcium levels rise. Molecular integrators, in contrast to real-time indicators, convert transient cellular events into stable signals that can be exploited for imaging, selection, molecular characterization, or cellular manipulation. Many integrators, however, are designed as complex multicomponent circuits that have limited robustness, especially at high, low, or nonstoichiometric protein expression levels. Here, we report a simplified design of the calcium and light dual integrator FLARE. Single-chain FLARE (scFLARE) is a single polypeptide chain that incorporates a transcription factor, a LOV domain–caged protease cleavage site, and a calcium-activated TEV protease that we designed through structure-guided mutagenesis and screening. We show that scFLARE has greater dynamic range and robustness than first-generation FLARE and can be used in culture as well as in vivo to record patterns of neuronal activation with 10-min temporal resolution.
Dynamic Modeling of Weld Bead Geometry Features in Thick Plate GMAW Based on Machine Vision and Learning

Weld bead geometry features (WBGFs) such as the bead width, height, area, and center of gravity are the common factors for weighing welding quality control. The effective modeling of these WBGFs contributes to implementing timely decision making of welding process parameters to improve welding quality and enhance automatic levels. In this work, a dynamic modeling method of WBGFs is presented based on machine vision and learning in multipass gas metal arc welding (GMAW) with typical joints. A laser vision sensing system is used to detect weld seam profiles (WSPs) during the GMAW process. A novel WSP extraction method is proposed using scale-invariant feature transform and machine learning. The feature points of the extracted WSP, namely the boundary points of the weld beads, are identified with slope mutation detection and number supervision. In order to stabilize the modeling process, a fault detection and diagnosis method is implemented with cubic exponential smoothing, and the diagnostic accuracy is within 1.50 pixels. A linear interpolation method is presented to implement sub pixel discrimination of the weld bead before modeling WBGFs. With the effective feature points and the extracted WSP, a scheme of modeling the area, center of gravity, and all-position width and height of the weld bead is presented. Experimental results show that the proposed method in this work adapts to the variable features of the weld beads in thick plate GMAW with T-joints and butt/lap joints. This work can provide more evidence to control the weld formation in a thick plate GMAW in real time.
Railway Infrastructure Classification and Instability Identification Using Sentinel-1 SAR and Laser Scanning Data

Satellite radar interferometry (InSAR) techniques have been successfully applied for structural health monitoring of line-infrastructure such as railway. Limited by meter-level spatial resolution of Sentinel-1 satellite radar (SAR) imagery and meter-level geolocation precision, it is still challenging to (1) categorize radar scatterers (e.g., persistent scatterers (PS)) and associate radar scatterers with actual objects along railways, and (2) identify unstable railway segments using InSAR Line of Sight (LOS) deformation time series from a single viewing geometry. In response to this, (1) we assess and improve the 3-D geolocation quality of Sentinel-1 derived PS using a 2-step method for PS 3-D geolocation improvement aided by laser scanning data; after geolocation improvement, we step-wisely classify railway infrastructure into rails, embankments and surroundings; (2) we recognize unstable rail segments by utilizing the (localized) differential settlement of rails in the normal direction (near vertical) which is yielded from the LOS deformation decomposition. We tested and evaluated the methods using 170 Sentinel-1a/b ascending data acquired between January 2017 and December 2019, over the Betuwe freight train track, in the Netherlands. The results show that 98% PS were associated with real objects with a significance level of 25%, the PS settlement measurements were generally in line with the in-situ track survey Rail Infrastructure aLignment Acquisition (RILA) measurements, and the standard deviations of the PS settlement measurements varied slightly with an average value of 6.16 mm.