Miracle-dz/UniFAR-FTUs huggingface dataset:
Validation of the X-ray microtomography in the assessment of duodenal morphometry and surface area in celiac disease

Background Duodenal histology remains the diagnostic reference standard in celiac disease. However, traditional methods have suboptimal sensitivity and reproducibility for early mucosal changes and research purposes. We validated a recently introduced micro-CT imaging method for an accurate digital evaluation of duodenal histomorphometry and mucosal surface areas. Methods Endoscopic biopsies from 58 individuals were utilized for the micro-CT imaging, selecting histological changes ranging from normal to severely damaged mucosa. The imaging protocol was optimized for practicability and resolution. The Bland–Altman method was applied to test intra- and interobserver variations in the blinded measurements. Results The 3D micro-CT reconstructions enabled easy and precise digital cutting with optimal orientation and computer-assisted measurement of the surface area. Intraobserver analysis of morphological measurements showed a mean difference of 0.011 with limits of agreement (LA) from -0.397 to 0.375 and a standard deviation (SD) of 0.197. The corresponding figures for interobserver analysis were 0.080, from -0.719 to 0.537 and 0.320, respectively. The intraclass correlation coefficients (ICC) for the intraobserver and interobserver variations were 0.981 and 0.954, respectively. Intraobserver surface area analysis yielded a mean difference of 0.010, LA from -0.764 to 0.785 and an SD of 0.395, and an interobserver analysis mean difference of 0.028, LA from -0.642 to 0.698 and SD of 0.342. The respective ICCs for the intra- and interobserver variations were 0.963 and 0.972. Conclusions Micro-CT showed excellent accuracy and reproducibility in the evaluation of mucosal morphometry and surface areas. The improved sensitivity for histological changes is a powerful tool for the diagnosis of celiac disease and for clinical and pharmacological studies.
Non-invasive type 2 diabetes risk scores do not identify diabetes when the cause is β-cell failure: The Africans in America study

Background Emerging data suggests that in sub-Saharan Africa β-cell-failure in the absence of obesity is a frequent cause of type 2 diabetes (diabetes). Traditional diabetes risk scores assume that obesity-linked insulin resistance is the primary cause of diabetes. Hence, it is unknown whether diabetes risk scores detect undiagnosed diabetes when the cause is β-cell-failure. Aims In 528 African-born Blacks living in the United States [age 38 ± 10 (Mean ± SE); 64% male; BMI 28 ± 5 kg/m2] we determined the: (1) prevalence of previously undiagnosed diabetes, (2) prevalence of diabetes due to β-cell-failure vs. insulin resistance; and (3) the ability of six diabetes risk scores [Cambridge, Finnish Diabetes Risk Score (FINDRISC), Kuwaiti, Omani, Rotterdam, and SUNSET] to detect previously undiagnosed diabetes due to either β-cell-failure or insulin resistance. Methods Diabetes was diagnosed by glucose criteria of the OGTT and/or HbA1c ≥ 6.5%. Insulin resistance was defined by the lowest quartile of the Matsuda index (≤ 2.04). Diabetes due to β-cell-failure required diagnosis of diabetes in the absence of insulin resistance. Demographics, body mass index (BMI), waist circumference, visceral adipose tissue (VAT), family medical history, smoking status, blood pressure, antihypertensive medication, and blood lipid profiles were obtained. Area under the Receiver Operator Characteristics Curve (AROC) estimated sensitivity and specificity of each continuous score. AROC criteria were: Outstanding: >0.90; Excellent: 0.80–0.89; Acceptable: 0.70–0.79; Poor: 0.50–0.69; and No Discrimination: 0.50. Results Prevalence of diabetes was 9% (46/528). Of the diabetes cases, β-cell-failure occurred in 43% (20/46) and insulin resistance in 57% (26/46). The β-cell-failure group had lower BMI (27 ± 4 vs. 31 ± 5 kg/m2 P < 0.001), lower waist circumference (91 ± 10 vs. 101 ± 10cm P < 0.001) and lower VAT (119 ± 65 vs. 183 ± 63 cm3, P < 0.001). Scores had indiscriminate or poor detection of diabetes due to β-cell-failure (FINDRISC AROC = 0.49 to Cambridge AROC = 0.62). Scores showed poor to excellent detection of diabetes due to insulin resistance, (Cambridge AROC = 0.69, to Kuwaiti AROC = 0.81). Conclusions At a prevalence of 43%, β-cell-failure accounted for nearly half of the cases of diabetes. All six diabetes risk scores failed to detect previously undiagnosed diabetes due to β-cell-failure while effectively identifying diabetes when the etiology was insulin resistance. Diabetes risk scores which correctly classify diabetes due to β-cell-failure are urgently needed.
Brain gene expression differences related to ethanol preference in the collaborative cross founder strains

The collaborative cross (CC) founder strains include five classical inbred laboratory strains [129S1/SvlmJ (S129), A/J (AJ), C57BL/6J (B6), NOD/ShiLtJ (NOD), and NZO/HILtJ (NZO)] and three wild-derived strains [CAST/EiJ (CAST), PWK/PhJ (PWK), and WSB/EiJ (WSB)]. These strains encompass 89% of the genetic diversity available in Mus musculus and ∼10–20 times more genetic diversity than found in Homo sapiens. For more than 60 years the B6 strain has been widely used as a genetic model for high ethanol preference and consumption. However, another of the CC founder strains, PWK, has been identified as a high ethanol preference/high consumption strain. The current study determined how the transcriptomes of the B6 and PWK strains differed from the 6 low preference CC strains across 3 nodes of the brain addiction circuit. RNA-Seq data were collected from the central nucleus of the amygdala (CeA), the nucleus accumbens core (NAcc) and the prelimbic cortex (PrL). Differential expression (DE) analysis was performed in each of these brain regions for all 28 possible pairwise comparisons of the CC founder strains. Unique genes for each strain were identified by selecting for genes that differed significantly [false discovery rate (FDR) < 0.05] from all other strains in the same direction. B6 was identified as the most distinct classical inbred laboratory strain, having the highest number of total differently expressed genes (DEGs) and DEGs with high log fold change, and unique genes compared to other CC strains. Less than 50 unique DEGs were identified in common between B6 and PWK within all three brain regions, indicating the strains potentially represent two distinct genetic signatures for risk for high ethanol-preference. 338 DEGs were found to be commonly different between B6, PWK and the average expression of the remaining CC strains within all three regions. The commonly different up-expressed genes were significantly enriched (FDR < 0.001) among genes associated with neuroimmune function. These data compliment findings showing that neuroimmune signaling is key to understanding alcohol use disorder (AUD) and support use of these 8 strains and the highly heterogeneous mouse populations derived from them to identify alcohol-related brain mechanisms and treatment targets.
Mitochondrial membrane models built from native lipid extracts: Interfacial and transport properties

The mitochondrion is an essential organelle enclosed by two membranes whose functionalities depend on their very specific protein and lipid compositions. Proteins from the outer mitochondrial membrane (OMM) are specialized in mitochondrial dynamics and mitophagy, whereas proteins of the inner mitochondrial membrane (IMM) have dedicated functions in cellular respiration and apoptosis. As for lipids, the OMM is enriched in glycerophosphatidyl choline but cardiolipin is exclusively found within the IMM. Though the lipid topology and distribution of the OMM and IMM are known since more than four decades, little is known about the interfacial and dynamic properties of the IMM and OMM lipid extracts. Here we build monolayers, supported bilayers and giant unilamellar vesicles (GUVs) of native OMM and IMM lipids extracts from porcine heart. Additionally, we perform a comparative analysis on the interfacial, phase immiscibility and mechanical properties of both types of extract. Our results show that IMM lipids form more expanded and softer membranes than OMM lipids, allowing a better understanding of the physicochemical and biophysical properties of mitochondrial membranes.
Building trusting relationships to support implementation: A proposed theoretical model

This paper presents a theory of change that articulates (a) proposed strategies for building trust among implementation stakeholders and (b) the theoretical linkages between trusting relationships and implementation outcomes. The theory of change describes how trusting relationships cultivate increases in motivation, capability, and opportunity for supporting implementation among implementation stakeholders, with implications for commitment and resilience for sustained implementation, and ultimately, positive implementation outcomes. Recommendations related to the measurement of key constructs in the theory of change are provided. The paper highlights how the development of a testable causal model on trusting relationships and implementation outcomes can provide a bridge between implementation research and implementation practice.
The native stem holoparasitic Cuscuta japonica suppresses the invasive plant Ambrosia trifida and related mechanisms in different light conditions in northeast China

Increasing evidence from low-latitude ranges has demonstrated that native parasitic plants are promising biocontrol agents for some major invasive weeds. However, related mechanisms and the effect of environments on the control effect of the parasite are still unclear. In addition, few related studies have been conducted in high latitude (>40°), where the exotic plant richness is the highest in the globe, but natural enemies are relatively scarce. During field surveys, a Cuscuta species was found on the cosmopolitan invasive weed Ambrosia trifida L. in Shenyang, northeast China. Here, we first studied the impacts of the parasite on the invader at three sites with different light regimes and related mechanisms, then the haustorial connections between the parasite and the invader using anatomy and measurement of carbon (C) and nitrogen (N) stable isotope compositions (δ13C, δ15N), and finally identified the parasite using two molecular marks. The parasite was identified as C. japonica Choisy. This native holoparasitic vine posed serious C rather than N limitation to the invader, explaining its greatly inhibitory effects on the invader. Its negative effects were stronger on reproductive relative to vegetative growth, and at high relative to low light habitats, which indicated that the higher the vigor of the host is, the higher the impact of the parasite pose. The parasite could establish haustorial connections with phloem, xylem, and pith of the invader and thus obtain resources from both leaves and roots, which was confirmed by difference of δ13C and δ15N between the two species. The parasite had significantly higher leaf C concentrations and δ13C than its invasive host, being a strong C sink of the parasitic association. Our results indicate that C. japonica may be a promising biological control agent for the noxious invader in China.
A novel germline HAVCR2 (TIM-3) compound heterozygous mutation is related to hemophagocytic lymphohistiocytic syndrome in EBV-positive peripheral T-cell lymphoma (NOS) with down-regulated TIM-3 signaling

Recently, it have been reported that Hepatitis A Virus-Cellular Receptor 2(HAVCR2,encoding T-cell immunoglobulin and Mucin-Containing Protein 3[TIM3]) mutations are associated with severe hemophagocytic syndrome(HLH) in subcutaneous panniculitis-like T-cell lymphoma(SPTCL),and there are also frequent mutations in sporadic SPTCL, suggesting the individuals harboring HAVCR2(TIM-3) germline mutations are highly susceptible to familial or sporadic SPTCL. Here, we identify a novel germline compound heterozygous mutation of TIM-3 gene,c.245A>G (p.Tyr82Cys) and c.265C>T(p.Arg89Cys) variations in a single familial case with EBV-positive peripheral T-cell lymphoma(NOS),accompanied HLH;we also detected Tyr82Cys germline mutation in TIM-3 gene in one sporadic patient with cutaneous T cell lymphoma. We screened the distributive frequencies for TIM-3 mutations in healthy controls(n=87), B-(n=79) or T-cell lymphoma(n=25) not SPTCL, and the results showed that the mutation was found in two out of 25 patients with T-cell lymphoma but was not detected in 79 patients with B-cell lymphoma nor in a group of 87 controls. The mRNA expression of TIM-3 on primary cells and transfected HEK293 cells reduced significantly, indicating Tyr82Cys and Arg89Cys mutations is a loss-of function mutations on TIM-3,resulting in a weakened TIM-3 signaling. Our results suggest Tyr82Cys TIM-3 germline mutations are not only limited in SPTCL, and also occurred in other types of T-cell lymphoma, especially complicated HLH. TIM-3 mutations may be an predisposing factor for T-cell lymphoma and molecular marker for auxiliary diagnosis in T cell lymphoma,especially complicated with HLH.
Fibroblast growth factor receptor signaling in cardiomyocytes is protective in the acute phase following ischemia-reperfusion injury

Fibroblast growth factor receptors (FGFRs) are expressed in multiple cell types in the adult heart. Previous studies have shown a cardioprotective effect of some FGF ligands in cardiac ischemia-reperfusion (I/R) injury and a protective role for endothelial FGFRs in post-ischemic vascular remodeling. To determine the direct role FGFR signaling in cardiomyocytes in acute cardiac I/R injury, we inactivated Fgfr1 and Fgfr2 (CM-DCKO) or activated FGFR1 (CM-caFGFR1) in cardiomyocytes in adult mice prior to I/R injury. In the absence of injury, inactivation of Fgfr1 and Fgfr2 in adult cardiomyocytes had no effect on cardiac morphometry or function. When subjected to I/R injury, compared to controls, CM-DCKO mice had significantly increased myocyte death 1 day after reperfusion, and increased infarct size, cardiac dysfunction, and myocyte hypertrophy 7 days after reperfusion. No genotype-dependent effect was observed on post-ischemic cardiomyocyte cross-sectional area and vessel density in areas remote to the infarct. By contrast, transient activation of FGFR1 signaling in cardiomyocytes just prior to the onset of ischemia did not affect outcomes after cardiac I/R injury at 1 day and 7 days after reperfusion. These data demonstrate that endogenous cell-autonomous cardiomyocyte FGFR signaling supports the survival of cardiomyocytes in the acute phase following cardiac I/R injury and that this cardioprotection results in continued improved outcomes during cardiac remodeling. Combined with the established protective role of some FGF ligands and endothelial FGFR signaling in I/R injury, this study supports the development of therapeutic strategies that promote cardiomyocyte FGF signaling after I/R injury.
Investigating hydrate formation and flow properties in water-oil flow systems in the presence of wax

The coexistence of wax and hydrates will pose intractable challenges to the safety of offshore oil and gas production and transportation, especially for deep sea or ultra-deep sea reservoirs. Understanding the effect of wax crystals on hydrate formation, flow properties, and plugging risks of flow systems is imperative to the flow assurance industry. Experiments using systems composed of natural gas, water-in-oil emulsion with different wax contents, and AA (anti-agglomerant) were conducted in a high-pressure flow loop. For wax-containing systems, wax precipitates out during the induction period of hydrate formation. The induction time of hydrate formation decreased with the increasing wax content under the experimental conditions in this work. It was also found that the induction time for both wax-free and wax-containing systems increased with the increasing flow rate. The hydrate growth rate and the cumulative gas consumption were significantly reduced due to the existence of wax. Although the hydrate volume fraction of wax-containing systems was much smaller than that of wax-free systems, a stable slurry flow state could not be reached for wax-containing systems, the pressure drop of which gradually increased with the decreasing flow rates. The coexistence of wax and hydrates results in the deterioration of transportability and higher plugging risks. Based on the Darcy–Weisbach hydraulic formula, a dimensionless parameter was defined to characterize the plugging risk of flow systems with the coexistence of wax and hydrates. Additionally, regions with different levels of plugging risks could be evaluated and divided.
MRI radiomics-based machine learning model integrated with clinic-radiological features for preoperative differentiation of sinonasal inverted papilloma and malignant sinonasal tumors

Objective To explore the best MRI radiomics-based machine learning model for differentiation of sinonasal inverted papilloma (SNIP) and malignant sinonasal tumor (MST), and investigate whether the combination of radiomics features and clinic–radiological features can produce a superior diagnostic performance. Methods The database of 247 patients with SNIP (n=106) or MST (n=141) were analyzed. Dataset from scanner A were randomly divided into training set (n=135) and test set 1 (n=58) in a ratio of 7:3, and dataset from scanner B and C were used as an additional independent test set 2 (n=54). Fourteen clinic-radiological features were analyzed by using univariate analysis, and those with significant differences were applied to construct clinical model. Based on the radiomics features extracted from single sequence (T2WI or CE-T1WI) and combined sequence, four commonly used classifiers (logistic regression (LR), support vector machine (SVM), decision tree (DT) and k-nearest neighbor (KNN)) were employed to constitute twelve different machine learning models, and the best-performing one was confirmed as the optimal radiomics model. Furthermore, a combined model incorporated best radiomics feature subsets and clinic-radiological features was developed. The diagnostic performances of these models were assessed by the area under the receiver operating characteristic (ROC) curve (AUC) and the calibration curves. Results Five clinic-radiological features (age, convoluted cerebriform pattern sign, heterogeneity, adjacent bone involvement and infiltration of surrounding tissue) were considered to be significantly different between the tumor groups (P < 0.05). Among the twelve machine learning models, the T2WI-SVM model exhibited optimal predictive efficacy for classification tasks on the two test sets, with the AUC of 0.878 and 0.914, respectively. For three types of diagnostic models, the combined model achieved highest AUC of 0.912 (95%CI: 0.807-0.970) and 0.927 (95%CI: 0.823-0.980) for differentiation of SNIP and MST in test 1 and test 2 sets, which performed prominently better than clinical model (P=0.011, 0.005), but not significantly different from the optimal radiomics model (P=0.100, 0.452). Conclusion The machine learning model based on T2WI sequence and SVM classifier achieved best performance in differentiation of SNIP and MST, and the combination of radiomics features and clinic-radiological features significantly improved the diagnostic capability of the model.
The chemokine receptor CXCR4 regulates satellite cell activation, early expansion, and self-renewal, in response to skeletal muscle injury

Acute skeletal muscle injury is followed by satellite cell activation, proliferation, and differentiation to replace damaged fibers with newly regenerated muscle fibers, processes that involve satellite cell interactions with various niche signals. Here we show that satellite cell specific deletion of the chemokine receptor CXCR4, followed by suppression of recombination escapers, leads to defects in regeneration and satellite cell pool repopulation in both the transplantation and in situ injury contexts. Mechanistically, we show that endothelial cells and FAPs express the gene for the ligand, SDF1α, and that CXCR4 is principally required for proper activation and for transit through the first cell division, and to a lesser extent the later cell divisions. In the absence of CXCR4, gene expression in quiescent satellite cells is not severely disrupted, but in activated satellite cells a subset of genes normally induced by activation fail to upregulate normally. These data demonstrate that CXCR4 signaling is essential to normal early activation, proliferation, and self-renewal of satellite cells.
Mild cold stress specifically disturbs clustering movement of DFCs and sequential organ left-right patterning in zebrafish

In poikilothermic animals, the distinct acclimatization ability of different organs has been previously addressed, while the tissue-specific role of cold stress in early development is largely unknown. In this study, we discovered that despite its role in delaying embryonic development, mild cold stress (22°C) does not disturb multiple-organ progenitor specification, but does give rise to organ left-right (LR) patterning defects. Regarding the mechanism, the data showed that mild cold stress downregulated the expression of cell-adhesion genes cdh1 and cdh2 during gastrulation, especially in dorsal forerunner cells (DFCs), which partially disturbed the clustering movement of DFCs, Kupffer’s vesicle (KV) morphogenesis, and ciliogenesis. As a result, the defects of KV/cilia disrupted asymmetric nodal signaling and subsequent heart and liver LR patterning. In conclusion, our data novelly identified that, in early development, DFCs are more sensitive to mild cold stress, and mild cold stress repressed the expression of cell adhesion-related gene cdh1 and cdh2. This role partially disturbed the clustering movement of DFCs, which resulted in defective KV/cilia development and sequential organ LR patterning defects.
Fault diagnosis of transformer using artificial intelligence: A review

Transformer is one of the important components of the power system, capable of transmitting and distributing the electricity generated by renewable energy sources. Dissolved Gas Analysis (DGA) is one of the effective techniques to diagnose early faults in oil-immersed transformers. It correlates the concentration and ratio of dissolved gases with transformer faults. Researchers have proposed many methods for fault diagnosis, such as double ratio method, Rogers method, Duval triangle method, etc., but all of them have some problems. Based on the strong data mining capability and good robustness of AI techniques, many researchers introduced AI techniques to mine the features of DGA data. According to the characteristics and scale of DGA data, researchers select appropriate AI techniques or make appropriate improvements to AI techniques to improve diagnostic performance. This paper presents a systematic review of the literature on the application of artificial intelligence techniques for DGA-based diagnosis and for solving intractable problems in early transformer fault diagnosis, which include neural networks, clustering, support vector machines, etc. In addition to reviewing the applications of these intelligent techniques, the diagnostic thinking proposed in this literature, such as the introduction of temporal parameters for comprehensive analysis of DGA data and the extraction of optimal features for DGA data, is also reviewed. Finally, this paper summarizes and prospects the artificial intelligence techniques applied by researchers in transformer fault diagnosis.