Kovacs Effect Studied Using The Distinguishable Particles Lattice Model Of Glass

Kovacs effect is a characteristic feature of glassy relaxation. It consists in a non-monotonic evolution of the volume (or enthalpy) of a glass after a succession of two abrupt temperatures changes. The second change is performed when the instantaneous value of the volume coincides with the equilibrium one at the final temperature. While this protocol might be expected to yield equilibrium dynamics right after the second temperature change, the volume instead rises and reaches a maximum, the so-called Kovacs hump, before dropping again to the final equilibrium value. Kovacs effect constitutes one of the hallmarks of aging in glasses. In this paper we reproduce all features of the Kovacs hump by means of the Distinguishable Particles Lattice Model (DPLM) which is a particle model of structural glasses.Comment: 4 pages, 2 figure

Expression of c-Kit, Flk-1, and Flk-2 Receptors in Benign and Malignant Tumors of Follicular Epithelial Origin

BackgroundVascular endothelial growth factor (VEGF) is a key regulator of physiologic as well as pathologic angiogenesis. The response of VEGF to endothelial cell mitogenesis and survival, as well as angiogenesis and microvascular permeability, is mainly mediated through its receptor-2, VEGFR2 (kinase domain receptor or fetal liver kinase-1, KDR or Flk-1). This study aimed to detect the expression of VEGFR2 in various forms of thyroid tumors. In addition, the expression of Flk-2 (receptor for Flt-3) and c-Kit (receptor for steel locus factor), which shows strong similarity to Flk-1, was also examined in thyroid tumors.MethodsRT-PCR analyses of c-Kit and immunohistochemical staining of c-Kit, Flk-1, and Flk-2 were performed in archived samples of 18 papillary thyroid carcinoma (PTC), 9 follicular thyroid carcinoma (FTC), 12 follicular adenoma (FA), and 7 nodular goiter (NG) samples. The data were correlated to clinicopathologic features.ResultsBy RT-PCR analyses, c-Kit expression was detected in 22% (4/18) of PTC, 22% (2/9) of FTC, 25% (3/12) of FA, and 57% (4/7) of NG samples. However, positive immunostaining signals of c-Kit were only observed in 17% (3/18) of PTC samples, and not in the others. Similarly, Flk-1 expression was only detected by immunohistochemistry in 67% (12/18) of PTC and 43% (3/7) of NG samples, and not in the others. Interestingly, the expression of Flk-2 was found in 89% (16/18) of PTC, 89% (8/9) of FTC, 75% (9/12) of FA, and 29% (2/7) of NG samples. An inverse relationship of thyroid cancer size with Flk-2 expression was found.ConclusionFlk-2 expression was detected in various forms of thyroid tumors and increased Flk-2 expression was correlated with thyroid tumors with increased transforming activity, suggesting that Flk-2 is involved in pathogenic development of thyroid malignancy. Similarly, Flk-1 expression was also found in some thyroid tumors, while the expression of c-Kit-mediated pathways may not play a major role in thyroid tumorigenesis

Fragile glasses associated with a dramatic drop of entropy under supercooling

We perform kinetic Monte Carlo simulations of a distinguishable-particle lattice model of structural glasses with random particle interactions. By varying the interaction distribution and the average particle hopping energy barrier, we obtain an extraordinary wide range of kinetic fragility. A stretching exponent, characterizing structural relaxation, is found to decrease with the kinetic fragility in agreement with experiments. The most fragile glasses are those exhibiting low hopping barriers and, more importantly, dramatic drops of entropies upon cooling towards the glass transition temperatures. The entropy drops reduce possible kinetic pathways and lead to dramatic slowdowns in the dynamics. In addition, the kinetic fragility is shown to correlate with a thermodynamic fragility

Prior Cancer Is Associated with Lower Atherosclerotic Cardiovascular Disease Risk at First Acute Myocardial Infarction

BACKGROUND: Patients with cancer are at increased risk of acute myocardial infarction (AMI). It is unclear if the Atherosclerotic Cardiovascular Disease (ASCVD) risk score at incident AMI is reflective of this higher risk in patients with prior cancer than those without. METHODS: We linked nationwide AMI and cancer registries from 2008 to 2019. A total of 18,200 eligible patients with ASCVD risk score calculated at incident AMI were identified (1086 prior cancer; 17,114 no cancer). RESULTS: At incident AMI, age-standardized mean ASCVD risk was lower in the prior cancer group (18.6%) than no cancer group (20.9%) (p < 0.001). Prior to incident AMI, smoking, hypertension, hyperlipidemia and diabetes mellitus were better controlled in the prior cancer group. However post-AMI, prior cancer was associated with lower guideline-directed medical therapy usage and higher all-cause mortality (adjusted hazard ratio 1.85, 95% confidence interval 1.66-2.07). CONCLUSIONS: AMI occurred despite better control of cardiovascular risk factors and lower age-standardized estimated mean 10-year ASCVD risk among patients with prior cancer than no cancer. Prior cancer was associated with lower guideline-directed medical therapy post-AMI and higher mortality

Automatic Diagnosis of Late-Life Depression by 3D Convolutional Neural Networks and Cross-Sample Entropy Analysis From Resting-State fMRI

Resting-state fMRI has been widely used in investigating the pathophysiology of late-life depression (LLD). Unlike the conventional linear approach, cross-sample entropy (CSE) analysis shows the nonlinear property in fMRI signals between brain regions. Moreover, recent advances in deep learning, such as convolutional neural networks (CNNs), provide a timely application for understanding LLD. Accurate and prompt diagnosis is essential in LLD; hence, this study aimed to combine CNN and CSE analysis to discriminate LLD patients and non-depressed comparison older adults based on brain resting-state fMRI signals. Seventy-seven older adults, including 49 patients and 28 comparison older adults, were included for fMRI scans. Three-dimensional CSEs with volumes corresponding to 90 seed regions of interest of each participant were developed and fed into models for disease classification and depression severity prediction. We obtained a diagnostic accuracy \u3e 85% in the superior frontal gyrus (left dorsolateral and right orbital parts), left insula, and right middle occipital gyrus. With a mean root-mean-square error (RMSE) of 2.41, three separate models were required to predict depressive symptoms in the severe, moderate, and mild depression groups. The CSE volumes in the left inferior parietal lobule, left parahippocampal gyrus, and left postcentral gyrus performed best in each respective model. Combined complexity analysis and deep learning algorithms can classify patients with LLD from comparison older adults and predict symptom severity based on fMRI data. Such application can be utilized in precision medicine for disease detection and symptom monitoring in LLD

Predicting Suicidality in Late-Life Depression by 3D Convolutional Neural Network and Cross-Sample Entropy Analysis of Resting-State fMRI

BACKGROUND: Predicting suicide is a pressing issue among older adults; however, predicting its risk is difficult. Capitalizing on the recent development of machine learning, considerable progress has been made in predicting complex behavior such as suicide. As depression remained the strongest risk for suicide, we aimed to apply deep learning algorithms to identify suicidality in a group with late-life depression (LLD). METHODS: We enrolled 83 patients with LLD, 35 of which were non-suicidal and 48 were suicidal, including 26 with only suicidal ideation and 22 with past suicide attempts, for resting-state functional magnetic resonance imaging (MRI). Cross-sample entropy (CSE) analysis was conducted to examine the complexity of MRI signals among brain regions. Three-dimensional (3D) convolutional neural networks (CNNs) were used, and the classification accuracy in each brain region was averaged to predict suicidality after sixfold cross-validation. RESULTS: We found brain regions with a mean accuracy above 75% to predict suicidality located mostly in default mode, fronto-parietal, and cingulo-opercular resting-state networks. The models with right amygdala and left caudate provided the most reliable accuracy in all cross-validation folds, indicating their neurobiological importance in late-life suicide. CONCLUSION: Combining CSE analysis and the 3D CNN, several brain regions were found to be associated with suicidality

Presence of tumour capsule on contrast-enhanced CT is associated with improved outcomes of stereotactic body radiation therapy in hepatocellular carcinoma patients

Purpose Stereotactic body radiation therapy (SBRT) is a novel local therapy for the treatment of hepatocellular carcinoma (HCC). While effective, there is currently noreliable radiological marker to guide patient selection. In this study, we investigated the prognostic value of capsule appearanceon contrast-enhanced computed tomography (CT) for patients undergoing SBRT. Materials and Methods Between 2006 and 2017, 156 consecutive patients with Child-Pugh score class A/B and HCC ≥5cm that underwent SBRT were retrospectively analysed. Baseline triple-phase CTs of the abdomen were reviewed for the presence of capsule appearances and correlated with objective response rate (ORR), overall survival (OS), and pattern of treatment failure. Results Capsule appearance on CT was present in 83 (53.2%) patients.It was associated with improved ORR by Response Evaluation Criteria in Solid Tumours (RECIST) (60.2% vs 24.7%; p<0.001) andModified Response Evaluation Criteria in Solid Tumours(mRECIST) (ORR 78.3% vs 34.2%; p<0.001). The presence of a capsule was also associated with superior 2-year local control (89.1% vs. 51.4%; p<0.001) and 2-year OS (34.1% vs. 14.8%, p<0.01). Hepatic out-field failure was the dominant mode of progression, which was less common in patients with intact capsule (54.2% vs. 60.3%, p=0.01). Conclusion Capsule appearance on CT could potentially be a non-invasive prognostic marker for selecting HCC patients undergoing SBRT. Larger cohort is warranted to validate our findings

Sex-based differences in risk of ischaemic stroke or systemic embolism after BNT162b2 or CoronaVac COVID-19 vaccination in patients with atrial fibrillation: a self-controlled case series and nested case-control study

AIMS: Patients with atrial fibrillation (AF) have a higher risk of ischemic stroke or systemic embolism with a greater risk for female patients. This study aims to evaluate the risk of ischemic stroke or systemic embolism and bleeding following COVID-19 vaccination in patients with AF and the sex differences. METHODS AND RESULTS: Self-controlled case series (SCCS) analysis was conducted to evaluate the risk of ischemic stroke or systemic embolism and bleeding following BNT162b2 or CoronaVac in patients with AF, using the territory-wide electronic medical records from the Hospital Authority and vaccination records from the Department of Health in Hong Kong. Patients with a primary diagnosis of ischemic stroke or systemic embolism or bleeding in the inpatient setting between February 23, 2021 and March 31, 2022 were included. A nested case-control analysis was also conducted with each case randomly matched with ten controls according to sex, age, Charlson comorbidity index and date of hospital admission. Conditional Poisson regression was used in the SCCS analysis and conditional logistic regression was used in nested case-control analysis to assess the risks and all analyses were stratified by sex and type of vaccines. Among 51 158 patients with AF, we identified an increased risk of ischemic stroke or systemic embolism after the first dose of BNT162b2 in SCCS analysis during 0-13 days (incidence rate ratio 6.60[95% CI 1.51-28.77]) and 14-27 days (6.53[95% CI 1.31-32.51]), and nested case-control analysis during 0-13 days (adjusted odds ratio 6.21 [95% CI 1.14-33.91]) and 14-27 days (5.52 [95% CI 1.12-27.26]) only in female patients. The increased risk in female patients following the first dose of CoronaVac was only detected during 0-13 days (3.88 [95% CI 1.67-9.03]) in the nested case-control analysis. No increased risk of ischemic stroke or systemic embolism was identified in male patients and no increased risk of bleeding was detected in all patients with AF for both vaccines. An increased risk of ischemic stroke or systemic embolism after COVID-19 was also observed in both females (17.42 [95% CI 5.08-59.73]) and males (6.63 [95% CI 2.02-21.79]). CONCLUSIONS: The risk of ischemic stroke or systemic embolism after COVID-19 vaccination was only increased in female patients with AF. However, as the risk after COVID-19 was even higher, proactive uptake of COVID-19 vaccines is recommended to prevent the potential severe outcomes after infection

The central role of natural killer cells in mediating acute myocarditis after mRNA COVID-19 vaccination

BACKGROUND: Vaccine-related acute myocarditis is recognized as a rare and specific vaccine complication following mRNA-based COVID-19 vaccinations. The precise mechanisms remain unclear. We hypothesized that natural killer (NK) cells play a central role in its pathogenesis. METHODS: Samples from 60 adolescents with vaccine-related myocarditis were analyzed, including pro-inflammatory cytokines, cardiac troponin T, genotyping, and immunophenotyping of the corresponding activation subsets of NK cells, monocytes, and T cells. Results were compared with samples from 10 vaccinated individuals without myocarditis and 10 healthy controls. FINDINGS: Phenotypically, high levels of serum cytokines pivotal for NK cells, including interleukin-1β (IL-1β), interferon α2 (IFN-α2), IL-12, and IFN-γ, were observed in post-vaccination patients with myocarditis, who also had high percentage of CD57 NK cells in blood, which in turn correlated positively with elevated levels of cardiac troponin T. Abundance of the CD57 NK subset was particularly prominent in males and in those after the second dose of vaccination. Genotypically, killer cell immunoglobulin-like receptor (KIR) KIR2DL5B(-)/KIR2DS3(+)/KIR2DS5(-)/KIR2DS4del(+) was a risk haplotype, in addition to single-nucleotide polymorphisms related to the NK cell-specific expression quantitative trait loci DNAM-1 and FuT11, which also correlated with cardiac troponin T levels in post-vaccination patients with myocarditis. CONCLUSION: Collectively, these data suggest that NK cell activation by mRNA COVID-19 vaccine contributed to the pathogenesis of acute myocarditis in genetically and epidemiologically vulnerable subjects