Training Patterns Research Articles

Left fascicular pacing is not inferior to left bundle branch pacing in preserving ventricular mechanical synchrony and cardiac function

Abstract Background Left bundle branch pacing (LBBP) has emerged as a more physiological alternative to right ventricular pacing.However, capturing the pre-divisional LBB is not easy to accomplish. This study investigates if left fascicular pacing(LFP), defined as the capture of one of the LBB fascicles, could achieve comparable left ventricular (LV) mechanical synchronicity and cardiac function compared to LBBP. Methods Thirty-one patients with pacing indication for bradycardia were retrospectively collected: LBBP was successfully performed in 13 patients and 18 achieved LFP. All patients underwent echocardiography before and after implantation and at one-year follow-up. Left ventricular (LV) volumes, ejection fraction (EF) and global longitudinal strain (GLS) were measured. The lateral-septal (LW-SW) work difference was used as a measure of mechanical dyssynchrony. Septal flash, apical rocking and septal strain patterns were also assessed. Results Although LW-SW work difference were significantly higher in the LBBP groups than that in the LFP group at baseline(272±269 mmHg*% vs 25±279mmHg*%,p=0.02), a similar increase in LW-SW work difference was observed during follow-up(199±342 mmHg*% vs 371±384mmHg*%,p=0.21). In addition, both LFP and LBBP induced septal flash or apical rocking in some patients, and resulted in subtle changes in strain patterns, which were not significantly different between groups. At one year follow-up, LV ejection fraction (EF) remained almost unchanged in both LBBP and LFP patients(ΔLVEF: 1.1+3.1% vs -0.3±4.8%,p=0.35) , and global longitudinal strain (GLS) was slightly and equally decreased in LFP compared to LBBP (ΔLVGLS: -1.6±2.3% vs -1.2±2.7%,p=0.69). Conclusion LFP and LBBP did not differ in mechanical dyssynchrony or LV remodelling.

Electrocardiographic criteria for the diagnosis of left ventricular hypertrophy in patients with severe aortic stenosis

Abstract Introduction There is a lack of data regarding the performance of current electrocardiographic (EKG) criteria for left ventricular hypertrophy (LVH) in patients with severe aortic stenosis (AS). Purpose To test the performance of the current EKG scores to diagnosis LVH in AS patients, and also to compare the performance of a new proposed score. Methods The present study evaluated 80 patients with severe AS that underwent cardiac magnetic resonance to diagnose LVH, defined as left ventricular indexed mass of 95 g/m² for female and 115 g/m² for male patients. The EKG criteria used for left ventricular hypertrophy were Sokolow-Lyon criteria, Romhilt-Estes point score system, Cornell voltage criteria and Peguero-Lo Presti criteria. Results Among the 80 patients included in analysis, 58.7% were male and the mean age was 64±8 years. There was a high prevalence of comorbidities, highlighting diabetes (32.5%), hypertension (67.5%), atrial fibrillation (5.0%) and coronary artery disease (11.3%). Regarding echocardiogram, the median left ventricle ejection fraction was 64 (56-68)% and the median indexed aortic valve area was 0.43 (0.35-0.49) cm²/m². Cardiac magnetic resonance analysis demonstrated a mean left ventricle mass of 168±55g, and the LVH incidence was 26.3%. Regarding EKG, Strain pattern was found in 49.1% of the patients, Cornell voltage criteria was positive in 51.3%, Sokolow-Lyon criteria in 51.3%, Romhilt-Estes point score system in 42.5% and Peguero-Lo Presti criteria in 61.3%. Discriminative capacity of electrocardiographic criteria for LVH is shown in Figure 1. Peguero-Lo Presti score had the best diagnostic accuracy in the overall population and in male sex (AUC 0.776), while Cornell voltage criteria had the best diagnostic accuracy in female patients (AUC 0.776). Based on linear regression model, the proposed score was created to predict LVH at cardiac magnetic resonance: 48 + (1.3 x Deepest S wave) + (0.5 x S wave in V1 or V2 plus R wave in V5). The proposed score cutoff value of 90.5 mm had a sensitivity of 0.765 and specificity of 0.707 (for male sex: 0.769 and 0.655, respectively; for female sex: 0.750 and 0.759, respectively). Compared to the scores described in the literature, the proposed score had the best area AUC for the overall population (Figure 1), for female and male patients (AUC 0.796, 0.819 and 0.780, respectively). Conclusion In patients with severe AS, the proposed score had the best diagnostic accuracy compared to the scores described in the literature for LVH identification, followed by Peguero-Lo Presti score, even when analyzed based on gender. Besides, the proposed score had also acceptable sensitivity and specificity for LVH detection.AUC of electrocardiographic scores.

Interplay between strain pattern-based classification of dyssynchrony and myocardial scar in CRT patients

Abstract Introduction Echocardiography-derived septal strain patterns are valuable for predicting volumetric reverse remodelling and survival in patients undergoing cardiac resynchronization therapy (CRT). Nevertheless, presence of myocardial scarring in the left ventricle (LV) is known to attenuate CRT treatment response. Purpose This study aims to investigate the interplay between septal strain patterns and myocardial scarring in CRT candidates, and how they link to outcome after CRT. Methods In this prospective multicentre study, CRT candidates from five European institutions underwent pre-implantation assessments using speckle-tracking strain analysis on echocardiography and cardiac magnetic resonance imaging (CMR) with late gadolinium enhancement (LGE). Dyssynchrony was graded through analysis of septal strain curves, categorizing patients into five distinct patterns, denoted as strain Stage-0 through strain Stage-4 (Fig. A). LGE of the LV wall was quantitatively assessed using CMR (as a percentage). The study endpoints were volumetric reverse remodelling (volume responder = more than 15% decrease LV end-systolic volume) after one year, and all-time all-cause mortality. Results A total of 267 patients, with a mean age of 66±11 years (69% males, 90% left bundle branch block [LBBB]) presented with an average LV ejection fraction (EF) of 30±7%. With each stepwise increase in strain stage, global LV scarring decreased (p<0.01; Fig. B) and the proportion of volume responders increased (all p<0.0001; Fig. C). ROC curves demonstrated that the predictive power of strain stages for CRT volumetric response was not significantly improved when scarring percentage was added (AUC 0.78 [95% CI: 0.69-0.83] vs. 0.81 [95% CI: 0.71-0.90]; p>0.05; Fig. D). In a multivariate cox regression model – including clinical characteristics that were significantly related to survival in univariate analysis – a patients’ strain stage was the only significant predictor of survival, also outperforming scar burden as determinant of outcome (HR 0.68; p=0.041; Fig. E). Conclusions Septal strain patterns show a strong association with the extent of reverse remodelling and outcome in CRT-treated patients. An inverse relationship is observed between pre-implant strain stages and the extent of myocardial scarring. However, scar burden did not provide incremental predictive value over the strain stages. Strain-pattern-based dyssynchrony assessment is a meaningful predictive marker which integrates information on myocardial dysfunction due to dyssynchrony as well as scar burden.

Cardiac amyloidosis Echo-Score for patients with severe aortic stenosis. The AMY-TAVI trial

Abstract Background and Purpose A longitudinal strain pattern characterized by apical sparing (RELAPS>1) has been identified as indicative of cardiac amyloidosis (CA). We conducted an analysis to assess its diagnostic accuracy in individuals with severe aortic stenosis (AS) and explored novel echocardiographic variables for predictive value. Methods All patients diagnosed with AS who underwent transcatheter aortic valve implantation (TAVI) were prospectively enrolled. 2D-Speckle-tracking echocardiography was utilized to assess myocardial deformation parameters. Subsequent to TAVI, screening for CA was conducted through 99mTc-DPD scintigraphy and protein electrophoresis. Results A total of 324 patients were included (mean age 81.5 ± 5.8 years, 51% women). Among them, 38 individuals (11.7%) exhibited cardiac uptake in scintigraphy: 14 patients (4.3%) with grade 1, 13(4%) grade 2, and 11(3.4%) grade 3. RELAPS>1 was more prevalent in patients with AS-CA (74%vs.44%,p=0.006). We propose an echocardiographic prediction model (GRAM score) for CA in the context of AS that is more sensitive and specific than RELAPS >1 alone. This model incorporates the left ventricular mass index, maximum transvalvular aortic pressure gradient, RELAPS>1, and age (AUC: 0.85, 95% CI: 0.77–0.93). Conclusions While RELAPS >1 is more commonly observed in individuals with AS-CA, it is noteworthy that this pattern can also manifest in nearly half of AS patients without CA, diminishing its utility as a standalone screening tool. In light of this, our study puts forth a more sensitive and specific prediction score for identifying CA in patients with severe AS.GRAM score for predicting AS-CA

A study on sleep posture analysis using fibre bragg grating arrays based mattress.

Prolonged sleeping postures or unusual postures can lead to the development of various ailments such as subacromial impingement syndrome, sleep paralysis in the elderly, nocturnal gastroesophageal reflux, sore development, etc. Fibre Bragg Gratings (a variety of optical sensors) have gained huge popularity due to their small size, higher sensitivity and responsivity, and encapsulation flexibilities. However, in the present study, FBG Arrays (two FBGs with 10mm space between them) are employed as they are advantageous in terms of data collection, mitigating sensor location effects, and multiplexing features. In this work, Liquid silicone encapsulated FBG arrays are placed in the head (E), shoulder (C, D), and lower half body (A, B) region for analyzing the strain patterns generated by different sleeping postures namely, Supine (P1), Left Fetus (P2), Right Fetus (P3), and Over stomach (P4). These strain patterns were analyzed in two ways, combined (averaging the data from each FBG of the array) and Individual (data from each FBG was analyzed separately). Both analyses suggested that the FBGs in the arrays responded swiftly to the strain changes that occurred due to changes in sleeping postures. 3-D histograms were utilized to track the strain changes and analyze different sleeping postures. A discussion regarding closely related postures and long hour monitoring has also been included. Arrays in the lower half (A, B) and shoulder (C, D) regions proved to be pivotal in discriminating body postures. The average standard deviation of strain for the different arrays was in the range of 0.1 to 0.19 suggesting the reliable and appreciable strain-handling capabilities of the Liquid silicone encapsulated arrays.&#xD.

Strain and Deformation Analysis Using 3D Geological Finite Element Modeling with Comparison to Extensometer and Tiltmeter Observations

This study verifies the practicality of using finite element analysis for strain and deformation analysis in regions with sparse GNSS stations. A digital 3D terrain model is constructed using DEM data, and regional rock mass properties are integrated to simulate geological structures, resulting in the development of a 3D geological finite element model (FEM) using the ANSYS Workbench module. Gravity load and thermal constraints are applied to derive directional strain and deformation solutions, and the model results are compared to actual strain and tilt measurements from the Jiujiang Seismic Station (JSS). The results show that temperature variations significantly affect strain and deformation, particularly due to the elevation difference between the mountain base and summit. Higher temperatures increase thermal strain, causing tensile effects, while lower temperatures reduce thermal strain, leading to compressive effects. Strain and deformation patterns are strongly influenced by geological structures, gravity, and topography, with valleys experiencing tensile strain and ridges undergoing compression. The deformation trend indicates a southwestward movement across the study area. A comparison of FEM results with ten years of strain and tiltmeter data from JSS reveals a strong correlation between the model predictions and actual measurements, with correlation coefficients of 0.6 and 0.75 for strain in the NS and EW directions, and 0.8 and 0.9 for deformation in the NS and EW directions, respectively. These findings confirm that the 3D geological FEM is applicable for regional strain and deformation analysis, providing a feasible alternative in areas with limited GNSS monitoring. This method provides valuable insights into crustal deformation in regions with sparse strain and deformation measurement data.

Digitalisation Empowerment of Business to Digital Innovation in the Achievement of SDGs: A Survey on Creative Msme Actors in Indonesia

Objective: This study aims to test and analyse the relationship patterns of digital business-based training, empowerment of MSME actors, digital self-efficacy and digital innovation in creative MSMEs for the achievement of SDGs in MSMEs in West Java and Banten Provinces, Indonesia. Theoretical Framework: Digital literacy is needed so that a person has the ability to access information related to digital-based media. MSMEs are required to have renewable digital-based business methods in order to provide optimal and satisfying services. When MSMEs have high digital literacy through digital-based training, they could increase high self-efficacy. Empowering MSMEs based on digital business is very necessary in the digital era. Human resources in the organisation is expected to have digital competencies (skills, knowledge, attitude). Also, employees are expected to increase digital self-efficacy in order to increase digital innovation and MSME performance in the long term. Method: This study uses quantitative method by distributing questionnaires to 250 natural colour batik MSMEs in West Java and Banten Provinces. 207 questionnaires are filled in completely and then processed with Partial Least Square statistical techniques. Results and Discussion: This study finds that digital-based business training has a significant positive impact on the empowerment of MSME actors, and digital self-efficacy of MSME actors. In addition, empowerment of MSME players has significant positive impact on digital innovation and digital self-efficacy. On the other hand, digital self-efficacy of MSME actors has significant positive impact on digital innovation and is able to mediate the effect of business digital-based training on digital innovation. However, empowerment of MSME actors cannot mediate the effect of business digital-based training on digital innovation. Research Implications: This study provide guidance for the government and MSME empowerment organisations to design more targeted digital-based training. In addition, this study highlights the importance of supporting technological infrastructure and providing wider access to digital technology, especially for creative MSMEs in Indonesia. This study also enriches the literature on the role of digital training on digital empowerment and digital self-efficacy. Likewise, it provides implications for the role of digital empowerment and digital self-efficacy in encouraging digital innovation. Originality/Value: This study offers a business digitalisation empowerment model for creative MSMEs in order to increase digital innovation for creative MSMEs in achieving SDGs in Indonesia. The research model considers digital-based business training, empowerment of MSME players, and digital self-efficacy.

Theoretical framework for learning through structural plasticity

A growing body of research indicates that structural plasticity mechanisms are crucial for learning and memory consolidation. Starting from a simple phenomenological model, we exploit a mean-field approach to develop a theoretical framework of learning through this kind of plasticity, capable of taking into account several features of the connectivity and pattern of activity of biological neural networks, including probability distributions of neuron firing rates, selectivity of the responses of single neurons to multiple stimuli, probabilistic connection rules, and noisy stimuli. More importantly, it describes the effects of stabilization, pruning, and reorganization of synaptic connections. This framework is used to compute the values of some relevant quantities used to characterize the learning and memory capabilities of the neuronal network in training and testing procedures as the number of training patterns and other model parameters vary. The results are then compared with those obtained through simulations with firing-rate-based neuronal network models. Published by the American Physical Society 2024

Discrimination of Left Atrial Strain Patterns in Hypertensive Heart Disease and Hypertrophic Cardiomyopathy: a Cardiac Magnetic Resonance Feature.

To assess left atrial (LA) strain parameters using cardiovascular magnetic resonance imaging feature tracking (cardiac MRI-FT) for differentiating hypertensive heart disease (HHD) from hypertrophic cardiomyopathy (HCM), which are two left ventricular hypertrophic diseases that could present with similar morphologies in early stage but differ in clinical symptoms and treatment strategies. 45 patients with HHD, 85 patients with HCM (non-obstructive hypertrophiccardiomyopathy [HNCM, n = 45] and obstructive hypertrophic cardiomyopathy [HOCM, n = 40]) and 30 healthy controls (HC) were retrospectively included. LA volumes, strain, and strain rate were determined by manually contouring on the two- and four-chamber views of the CMR-FT module using CVI 42 software. LA volume parameters including LA maximum, precontraction, and minimum volume index, and total, passive, and active emptying fractions were obtained using the biplane methods. The LA strain parameters, including total strain (εs), passive strain (εe), active strain (εa), peak positive strain rate (SRs), early peak negative strain rate (SRe), and late peak negative strain rate (SRa), were obtained from the LA strain curve. The LA strain and LA strain rate were impaired in both HHD group and HCM group, and they were the most severely impaired in the HOCM group. εs (AUC = 0.691, P = 0.006; the best cutoff value, 25.1%), εa (AUC = 0.654, P = 0.027; the best cutoff value, 10.5%), SRs (AUC = 0.710, P = 0.003; the best cutoff value, 0.81 1/s) and SRa (AUC = 0.667, P = 0.016; the best cutoff value, -1.30 1/s) showed significant differences in the identification between HHD and HNCM. All LA strain parameters were different in the identification between HHD and HOCM (all P < 0.05).LA strain parameters can be helpful for differentiating HHD from HCM, providing valuable insights for diagnosis.

Percolation network study of highly sensitive buckled elastomeric piezoresistive sensors

Abstract Flexible pressure sensors are needed for future artificial electronic skin applications. Carbon black (CB)-enhanced elastomers are known for their unique conductivity, allowing for special uses in sensor technology. This research analyzes the sensitivity of elastomeric sensors reinforced with CB, under a pre-strained buckle, using a modified percolation network model to enhance performance in sensing applications. The finite element method is employed to analyze the piezoresistive characteristics of the sensors across various thicknesses. The research involves analyzing the strain patterns of buckled piezoresistive sensors when an indenter applies a load, and how this influences the sensors’ resistivity. The mechanical parameter is directly correlated to the sensor sensitivity through the maximum principal strain. The model shows a good agreement with the experimental data. The pressure sensitivity resulting from indenter compressive contact is 0.03 and 0.0061 kPa−1 in the pressure range of 0–1 and 0–5 kPa for wavy and straight 1000 μm buckled sensors, respectively. The results show that the film with 50% taller waves has a 40%–60% narrower pressure sensing ranges. Moreover, results indicate that adding waves to the geometry of the sensor improves the piezoresistive behavior by increasing the relative displacements of edges. Results also reveal more stable performance from fewer waves and a higher working range by thicker sensors.

Tectonic Activity Analysis of the Laji-Jishi Shan Fault Zone: Insights from Geomorphic Indices and Crustal Deformation Data

Fault segmentation plays a critical role in assessing seismic hazards, particularly in tectonically complex regions. The Laji-Jishi Shan Fault Zone (LJSFZ), located on the northeastern margin of the Tibetan Plateau, is a key structure that accommodates regional tectonic stress. This study integrates geomorphic indices, cross-fault deformation rate profiles, and 3D crustal electrical structure data to analyze the varying levels of tectonic activity across different segments of the LJSFZ. We extracted 160 drainage basins along the strike of the LJSFZ from a 30 m resolution digital elevation model and calculated geomorphic indices, including the hypsometric integral (HI), stream length-gradient index (SL), and channel steepness index (ksn), to assess the variations in tectonic activity intensity along the strike of the LJSFZ. The basins were categorized based on river flow directions to capture potential differences across the fault zone. Our results show that the eastern basins of the LJSFZ exhibit the strongest tectonic activity, demonstrated by significantly higher SL and ksn values compared to other regions. A detailed segmentation analysis along the northern Laji Shan Fault and eastern Jishi Shan Fault identified distinct fault segments characterized by variations in SL and ksn indices. Segments with high SL values (&gt;500) correspond to higher crustal uplift rates (~3 mm/year), while segments with lower SL values exhibit lower uplift rates (~2 mm/year), as confirmed by cross-fault deformation profiles derived from GNSS and InSAR data. This correlation demonstrates that geomorphic indices effectively reflect fault activity intensity. Additionally, 3D crustal electrical structure data further indicate that highly conductive mid- to lower-crustal materials originating from the interior of the Tibetan Plateau are obstructed at segment L3 of the LJSFZ. This obstruction leads to localized intense uplift and enhanced fault activity. These findings suggest that while the regional stress–strain pattern of the northeastern Tibetan Plateau is the primary driver of the segmented activity along the Laji-Jishi Shan belt, the direction of localized crustal flow is a critical factor influencing fault activity segmentation.

Pola Implementasi Pelatihan Batik Cap Interaktif Motif Khas Pacitan untuk Anak Usia Sekolah Dasar

The implementation pattern of interactive stamp batik training with typical motifs of Pacitan Regency for elementary school children is designed based on adaptive learning and digital technopreneurship. The purpose of this training is to introduce batik skills from an early age and equip children with technological and entrepreneurial skills. Using a qualitative descriptive approach, data was collected through observation, interviews, and document analysis. The results showed a significant increase in children's understanding and skills in making batik stamps, as well as a greater appreciation of local cultural heritage. Training also contributes to the development of technology-based entrepreneurial skills. Challenges related to limited access to technology and training materials have been successfully overcome with an adaptive and collaborative approach.

ECOMAN: an open-source package for geodynamic and seismological modelling of mechanical anisotropy

Abstract. Mechanical anisotropy related to rock fabrics is a proxy for constraining the Earth's deformation patterns. However, the forward and inverse modelling of mechanical anisotropy in 3D large-scale domains has been traditionally hampered by the intensive computational cost and the lack of a dedicated, open-source computational framework. Here we introduce ECOMAN (Exploring the COnsequences of Mechanical ANisotropy), a software package for modelling strain- and stress-induced rock fabrics and testing the effects of the resulting elastic and viscous anisotropy on seismic imaging and mantle convection patterns. Differently from existing analogous software, ECOMAN can model strain-induced fabrics across all mantle levels and is optimised to run efficiently on multiple CPUs. It also enables modelling of shape preferred orientation (SPO)-related structures that can be superimposed over lattice/crystallographic preferred orientation (LPO/CPO) fabrics, which allows the consideration of the mechanical effects of fluid-filled cracks, foliated and lineated grain-scale fabrics, and rock-scale layering. One of the most important innovations is the Platform for Seismic Imaging (PSI), a set of programs for performing forward and inverse seismic modelling in isotropic–anisotropic media using real or synthetic seismic datasets. The anisotropic inversion strategy is capable of recovering parameters describing a tilted transversely isotropic (TTI) medium, which is required to reconstruct 3D structures and mantle strain patterns and to validate geodynamic models.

Strain Patterns With Ultrasound for Assessment of Abdominal Aortic Aneurysm Vessel Wall Biomechanics

BackgroundAbdominal aortic aneurysms (AAAs) are an important cause of death. Small AAAs are surveyed with ultrasound (US) until a defined diameter threshold, often triggering a computer tomography scan and surgical repair. Nevertheless, 5%–10% of AAA ruptures are below threshold, and some large AAAs never rupture. AAA wall biomechanics may reveal vessel wall degradation with potential for patient-centred risk assessment. This clinical study investigated AAA vessel wall biomechanics and deformation patterns, including reproducibility. MethodsIn 50 patients with AAA, 183 video clips were recorded by two sonographers. Prototype software extracted AAA vessel wall principal strain characteristics and patterns. Functional principal component analysis (FPCA) derived strain pattern statistics. ResultsStrain patterns demonstrated reduced AAA wall strains close to the spine. The strain pattern “topography” (i.e., curve phases or “peaks” and “valleys”) had a 3.9 times lower variance than simple numeric assessment of strain amplitudes, which allowed for clustering in two groups with FPCA. A high mean reproducibility of these clusters of 87.6% was found. Median pulse pressure-normalised mean principal strain (PPPS) was 0.038%/mm Hg (interquartile range: 0.029–0.051%/mm Hg) with no correlation to AAA size (Spearman's ρ = 0.02, false discovery rate-p = 0.15). Inter-operator reproducibility of PPPS was poor (limits of agreement: ±0.031%/mm Hg). DiscussionStrain patterns challenge previous numeric stiffness measures based on anterior-posterior-diameter and are reproducible for clustering. This study's PPPS aligned with prior findings, although clinical reproducibility was poor. In contrast, US-based strain patterns hold promising potential to enhance AAA risk assessment beyond traditional diameter-based metrics.

Comparing continuum and direct fiber models of soft tissues: An ocular biomechanics example reveals that continuum models may artificially disrupt the strains at both the tissue and fiber levels

Collagen fibers are the main load-bearing component of soft tissues but difficult to incorporate into models. Whilst simplified homogenization models suffice for some applications, a thorough mechanistic understanding requires accurate prediction of fiber behavior, including both detailed fiber-level strains and long-distance transmission. Our goal was to compare the performance of a continuum model of the optic nerve head (ONH) built using conventional techniques with a fiber model we recently introduced which explicitly incorporates the complex 3D organization and interaction of collagen fiber bundles [1]. To ensure a fair comparison, we constructed the continuum model with identical geometrical, structural, and boundary specifications as for the fiber model. We found that: 1) although both models accurately matched the intraocular pressure (IOP)-induced globally averaged displacement responses observed in experiments, they diverged significantly in their ability to replicate specific 3D tissue-level strain patterns. Notably, the fiber model faithfully replicated the experimentally observed depth-dependent variability of radial strain, the ring-like pattern of meridional strain, and the radial pattern of circumferential strain, whereas the continuum model failed to do so; 2) the continuum model disrupted the strain transmission along each fiber, a feature captured well by the fiber model. These results demonstrate limitations of the conventional continuum models that rely on homogenization and affine deformation assumptions, which render them incapable of capturing some complex tissue-level and fiber-level deformations. Our results show that the strengths of explicit fiber modeling help capture intricate ONH biomechanics. They potentially also help modeling other fibrous tissues. Statement of SignificanceUnderstanding the mechanics of fibrous tissues is crucial for advancing knowledge of various diseases. This study uses the ONH as a test case to compare conventional continuum models with fiber models that explicitly account for the complex fiber structure. We found that the fiber model captured better the biomechanical behaviors at both the tissue level and the fiber level. The insights gained from this study demonstrate the significant potential of fiber models to advance our understanding of not only glaucoma pathophysiology but also other conditions involving fibrous soft tissues. This can contribute to the development of therapeutic strategies across a wide range of applications.

A Reappraisal of Nappe Structures and Strain Patterns in the Core of the Variscan Orogen (French Massif Central)

AbstractMajor influences on the architecture of orogens include the overall thermal conditions of orogeny (hot vs. cold) and the angle of collision (orthogonal vs. oblique). In the French Massif Central of the Variscan orogen, a cold‐orogen style crustal nappe architecture was interpreted in the Haut‐Allier, located in the core of the orogen. Based on this model, the Variscan orogenic crust is described as the superposition of three main allochthonous tectonic units juxtaposed along major thrust faults. However, based on a detailed structural analysis, we have found instead that the region is dominated by a network of anastomosing conjugate and coeval dextral and sinistral shear zones striking WNW‐ESE and ENE‐WSW, respectively. The dextral WNW‐trending shear zones are predominant, whereas the sinistral NE shear zones are mainly located in the eastern part of the massif. Between these sub‐vertical shear zones, a sub‐horizontal foliation is observed. Our results indicate that all planar fabrics were partially synchronous during suprasolidus low‐pressure‐high‐temperature conditions. Strain partitioning occurred from high‐temperature suprasolidus conditions to subsolidus retrogression and may represent orogen‐parallel flow, suggesting hot‐orogen style. These results call into question the validity of the crustal nappe model in the Haut‐Allier. Based on new structural data and related observations, we propose a new model in which metamorphic gaps between tectonic units are explained by the juxtaposition of different structural domains by displacement along strike‐slip shear zones.

Comparing Echocardiographic Strain Imaging in Cardiac Amyloid and End-Stage Renal Disease Patients.

Diagnosing cardiac amyloidosis (CA) is difficult due to nonspecific clinical symptoms and echocardiographic findings. Prior studies have suggested that apical sparing strain patterns may be diagnostically useful. With increasing strain usage, it remains unclear how specific this pattern is to diagnose CA. We analyzed strain patterns between CA and end-stage renal disease (ESRD) patient populations. Patients with ESRD proven negative for CA (n=19) were compared to CA patients with CKD stage 3 or less (n=25). The ESRD cohort was stratified based on time on dialysis. Echocardiographic longitudinal strain (LS) parameters were collected, including regional and global LS, echocardiographic, and demographic parameters. Relative apical LS was calculated using the following equation: average apical LS/(average mid LS+average basal LS). No significant differences were found regarding regional strain or relative apical strain. Our study showed a sensitivity of 80% and specificity of 42% when using a relative apical strain ratio of >1. All groups demonstrated an apical sparing strain pattern visually on the bulls-eye plot. ESRD demonstrates significant overlapping findings across various imaging modalities compared to CA. We demonstrated that relative apical sparing strain is nonspecific for CA among patients with ESRD. Our study calls into question the clinical value of relative apical-sparing stain patterns in identifying CA in an ESRD population and suggests that diagnostic evaluation should be driven by strong clinical suspicion and other imaging and demographic variables.

Myocardial mechanical function measured by cardiac magnetic resonance in patients with heart failure

AimStrain analysis offers a valuable tool to assess myocardial mechanics, allowing for the detection of impairments in heart function. This study aims to evaluate the pattern of myocardial strain in patients with heart failure (HF). MethodsIn the present study, myocardial strain was measured by cardiac magnetic resonance imaging feature tracking in 35 control subjects without HF and 195 HF patients. The HF patients were further categorized as HF with preserved ejection fraction (HFpEF, n=80), with mid-range ejection fraction (HFmrEF, n=34), and with reduced ejection fraction (HFrEF, n=81). Additionally, quantitative tissue evaluation parameters, including native T1 relaxation time and extracellular volume (ECV), were examined. ResultsCompared to controls, patients in all HF groups (HFpEF, HFmrEF, and HFrEF) demonstrated impaired left ventricular (LV) strains and systolic and diastolic strain rates in all three directions (radial, circumferential, and longitudinal) (p < 0.05 for all). LV strains also showed significant correlations with left ventricular ejection fraction and brain natriuretic peptide levels (p < 0.001 for all). Notably, septal contraction was significantly affected in HFpEF compared to controls. While LV torsion was slightly increased in HFpEF, it was decreased in HFrEF. Native T1 relaxation times and ECV fractions were significantly higher in HFrEF compared to HFpEF (p < 0.05). Overall, myocardial strain parameters demonstrated good performance in differentiating HF categories. ConclusionsThe myocardial strain impairments exhibit a spectrum of severity in patients with HFpEF, HFmrEF, and HFrEF compared to controls. Assessment of myocardial mechanics using strain analysis may offer a clinically useful tool for monitoring the progression of systolic and diastolic dysfunction in HF patients.

Cross-resistance patterns in field strains of the sheep blowfly following laboratory-based selection pressure with dicyclanil or imidacloprid

Control of the sheep blowfly relies largely on the use of insecticides applied prophylactically in advance of expected fly activity. However, the blowfly has shown an ability to develop resistance to some of these insecticides. Recent reports of the co-occurrence of resistance to both dicyclanil and imidacloprid in in vitro bioassays with field-collected fly strains has raised the possibility that the two resistances may represent cross-resistance linked by a common mechanism. We investigated this by imposing insecticide selection pressure on larvae of two insecticide-resistant field strains over a number of generations using either dicyclanil or imidacloprid and then measuring changes in sensitivity to both the selecting chemical and the alternate chemical. Larvae selected over six generations with each chemical showed significant increases in resistance to the selecting chemical: resistance ratios at the IC50 5.5 - 8.1-fold higher for dicyclanil, and 3.1 - 3.8-fold for imidacloprid. The larvae also showed significant increases in levels of resistance towards the alternate chemical: resistance ratios 2.6 - 3.1-fold higher towards dicyclanil following selection with imidacloprid, and 2.2 - 3.2-fold higher towards imidacloprid following selection with dicyclanil. The increases in resistance to both chemicals after exposure to either suggests a common mechanism of resistance, at least in our laboratory-selected populations. Assays with the cytochrome P450 inhibitor aminobenzotriazole showed that this synergist was able to remove the increased resistance to both compounds in strains selected with either compound, suggesting that cytochrome P450 is responsible for the resistance observed to both chemicals. Our results confirm that cross-resistance exists between dicyclanil and imidacloprid in the sheep blowfly, and hence the two compounds should be considered as related entities in insecticide rotation strategies for flystrike control.

Utilizing echocardiography and unsupervised machine learning for heart failure risk identification

BackgroundGlobal longitudinal strain (GLS) is recognized as a powerful predictor of heart failure (HF). However, the entire strain curve may entail important prognostic information regarding HF risk that might be undiscovered by only focusing on the peak strain value. ObjectiveThe hypothesis of the present study was, that analysis of the entire strain curve using unsupervised machine learning (uML) would reveal novel ventricular deformation patterns capable of predicting incident HF independently of GLS. MethodsLongitudinal strain curves from 3710 subjects from the general population without prevalent HF were analyzed using uML. ResultsMean age was 56 years and 43 % were male. During a median follow-up of 5.3 years, 92 subjects (2.5 %) developed HF. The uML algorithm generated a hierarchical clustering tree (HCT) resulting in 10 different clusters. Generally, the strain curves displayed reduced early diastolic strain to peak-strain ratio with an increasing incidence rate of HF. In multivariable Cox regressions, cluster 9 was significantly associated with increased risk of HF when compared to cluster 2–5, and 7–8 [For cluster 3: HR 8.95, 95 %CI: 2.08;38.48, P = 0.003] even though the subjects of cluster 9 were younger, displayed healthier clinical baseline characteristics, and only had slightly reduced GLS. The mean strain curve of cluster 9 displayed an early systolic lengthening followed by a late and reduced contraction specifically related to the basal lateral segment. ConclusionThe unsupervised machine learning algorithm identified unknown strain patterns beyond GLS presumably related to increased risk of HF.