The thymus regulates skeletal muscle regeneration by directly promoting satellite cell expansion.

The thymus is the central immune organ, but it is known to progressively degenerate with age. As thymus degeneration is paralleled by the wasting of aging skeletal muscle, we speculated that the thymus may play a role in muscle wasting. Here, using thymectomized mice, we show that the thymus is necessary for skeletal muscle regeneration, a process tightly associated with muscle aging. Compared to control mice, the thymectomized mice displayed comparable growth of muscle mass, but decreased muscle regeneration in response to injury, as evidenced by small and sparse regenerative myofibers along with inhibited expression of regeneration-associated genes myh3, myod, and myogenin. Using paired box 7 (Pax7)-immunofluorescence staining and 5-Bromo-2'-deoxyuridine-incorporation assay, we determined that the decreased regeneration capacity was caused by a limited satellite cell pool. Interestingly, the conditioned culture medium of isolated thymocytes had a potent capacity to directly stimulate satellite cell expansion in vitro. These expanded cells were enriched in subpopulations of quiescent satellite cells (Pax7highMyoDlowEdUpos) and activated satellite cells (Pax7highMyoDhighEdUpos), which were efficiently incorporated into the regenerative myofibers. We thus propose that the thymus plays an essential role in muscle regeneration by directly promoting satellite cell expansion and may function profoundly in the muscle aging process.

Nonlinear Schrödinger waves in a disordered potential: Branched flow, spectrum diffusion, and rogue waves.

The problem of nonlinear Schrödinger (NLS) waves in a disordered potential arises in many physical occasions, such as hydrodynamics, optics, and cold atoms. It provides a paradigm for studying the interaction between nonlinearity and random effect, but the current results are far from perfect. In this paper, we systematically simulate the turbulent waves for the focusing NLS equation with dynamical (time-dependent) random potentials, where the enhanced branching structures evolve into branched soliton flows as the nonlinearity increases. In this process, the occurrence of rogue waves for short times results from the interplay of linear random focusing and modulation instability. While the nonlinear spectral analysis reveals that for longer times, it is due to a self-organization of larger solitons competing with breakup of intermediate solitons. On the other hand, we found that the strong nonlinearity can significantly increase the width of the linear (Fourier) spectrum for several time scales, but its spreading rate becomes suppressed, which has a dependence on the correlation length of the potential. We hope that our findings will facilitate a deeper understanding of the nonlinear waves interacting with disordered media.

A deep learning approach to characterize 2019 coronavirus disease (COVID-19) pneumonia in chest CT images.

OBJECTIVES: To utilize a deep learning model for automatic detection of abnormalities in chest CT images from COVID-19 patients and compare its quantitative determination performance with radiological residents. METHODS: A deep learning algorithm consisted of lesion detection, segmentation, and location was trained and validated in 14,435 participants with chest CT images and definite pathogen diagnosis. The algorithm was tested in a non-overlapping dataset of 96 confirmed COVID-19 patients in three hospitals across China during the outbreak. Quantitative detection performance of the model was compared with three radiological residents with two experienced radiologists' reading reports as reference standard by assessing the accuracy, sensitivity, specificity, and F1 score. RESULTS: Of 96 patients, 88 had pneumonia lesions on CT images and 8 had no abnormities on CT images. For per-patient basis, the algorithm showed superior sensitivity of 1.00 (95% confidence interval (CI) 0.95, 1.00) and F1 score of 0.97 in detecting lesions from CT images of COVID-19 pneumonia patients. While for per-lung lobe basis, the algorithm achieved a sensitivity of 0.96 (95% CI 0.94, 0.98) and a slightly inferior F1 score of 0.86. The median volume of lesions calculated by algorithm was 40.10 cm3. An average running speed of 20.3 s ± 5.8 per case demonstrated the algorithm was much faster than the residents in assessing CT images (all p < 0.017). The deep learning algorithm can also assist radiologists make quicker diagnosis (all p < 0.0001) with superior diagnostic performance. CONCLUSIONS: The algorithm showed excellent performance in detecting COVID-19 pneumonia on chest CT images compared with resident radiologists. KEY POINTS: • The higher sensitivity of deep learning model in detecting COVID-19 pneumonia were found compared with radiological residents on a per-lobe and per-patient basis. • The deep learning model improves diagnosis efficiency by shortening processing time. • The deep learning model can automatically calculate the volume of the lesions and whole lung.

Ambient temperature-independent dual-band mid-infrared radiation thermometry.

For temperature measurements of targets at low temperatures, dual-band radiation thermometry using mid-infrared detectors has been investigated extensively. However, the accuracy is greatly affected by the reflected ambient radiation and stray radiation, which depend on the ambient temperature. To ensure measurement accuracy, an improved dual-band measurement model is established by considering the reflected ambient radiation and the stray radiation. The effect of ambient temperature fluctuation on temperature measurement is then further analyzed in detail. Experimental results of measuring a gray-body confirm that the proposed method yields high accuracy at varying ambient temperatures. This method provides a practical approach to remove the effect of ambient temperature fluctuations on temperature measurements.

Coexistence of Gaussian and non-Gaussian statistics in vector integrable turbulence.

Integrable turbulence studies the complex dynamics of random waves for the nonlinear integrable systems, and it has become an important element in exploring the sophisticated turbulent phenomena. In the present work, based on the coupled nonlinear Schrödinger models, we have shown the coexistence of Gaussian and non-Gaussian single-point statistics in multiple wave components, which might be viewed as an exclusive feature for the vector integrable turbulence. This coexistent statistic can relate to different distributions of the vector solitonic excitations depending on the time-invariant nonlinear spectra. Our results are expected to shed light on a deeper understanding of the turbulent behaviors of vector waves and may motivate relevant experiments in the coupled optical or atomic systems.

Machine learning based ischemia-specific stenosis prediction: A Chinese multicenter coronary CT angiography study.

OBJECTIVES: To evaluate the performance of coronary computed tomography angiography (CCTA) derived characteristics including CT derived fractional flow reserve (CT-FFR) with FFR as a reference standard in identifying the lesion-specific ischemia by machine learning (ML) algorithms. METHODS: The retrospective analysis enrolled 596 vessels in 462 patients (mean age, 61 years ± 11 [SD]; 71.4 % men) with suspected coronary artery disease who underwent CCTA and invasive FFR. The data were divided into training cohort, internal validation cohort, external validation cohorts 1 and 2 according to participating centers. All CCTA-derived parameters, which contained 10 qualitative and 33 quantitative plaque parameters, were collected to establish ML model. The Boruta and unsupervised clustering algorithm were implemented to select important and non-redundant parameters. Finally, the eight features with the highest mean importance were included for further ML model establishment and decision tree building. Five models were built to predict lesion-specific ischemia: stenosis degree from CCTA, CT-FFR, ΔCT-FFR, ML model and nested model. RESULTS: Low-attenuation plaque, bend and lesion length were the main predictors of ischemia-specific lesions. Of 5 models, the ML model showed favorable discrimination for ischemia-specific lesions in the training and three validation sets (area under the curve [95 % confidence interval], 0.93 [0.90-0.96], 0.86 [0.79-0.94], 0.88 [0.83-0.94], and 0.90 [0.84-0.96], respectively). The nested model which combined the ML model and CT-FFR showed better diagnostic efficacy (AUC [95 %CI], 0.96 [0.94-0.99], 0.92 [0.86-0.99], 0.92 [0.86-0.99] and 0.94 [0.91-0.98], respectively; all P < 0.05), and net reclassification improvement (NRI) and integrated discrimination improvement (IDI) were significantly higher than CT-FFR alone. CONCLUSIONS: Comprehensive CCTA-derived multiparameter model could better predict the ischemia-specific lesions by ML algorithms compared to stenosis degree from CTA, CT-FFR and ΔCT-FFR. Decision tree can be used to predict myocardial ischemia effectively.

Switching of bound vector solitons for the coupled nonlinear Schrödinger equations with nonhomogenously stochastic perturbations.

We investigate the dynamics of the bound vector solitons (BVSs) for the coupled nonlinear Schrödinger equations with the nonhomogenously stochastic perturbations added on their dispersion terms. Soliton switching (besides soliton breakup) can be observed between the two components of the BVSs. Rate of the maximum switched energy (absolute values) within the fixed propagation distance (about 10 periods of the BVSs) enhances in the sense of statistics when the amplitudes of stochastic perturbations increase. Additionally, it is revealed that the BVSs with enhanced coherence are more robust against the perturbations with nonhomogenous stochasticity. Diagram describing the approximate borders of the splitting and non-splitting areas is also given. Our results might be helpful in dynamics of the BVSs with stochastic noises in nonlinear optical fibers or with stochastic quantum fluctuations in Bose-Einstein condensates.

Intracellular TMEM16A is necessary for myogenesis of skeletal muscle.

Transmembrane protein 16A (TMEM16A) localizes at plasma membrane and controls chloride influx in various type of cells. We here showed an intracellular localization pattern of TMEM16A molecules. In myoblasts, TMEM16A was primarily localized to the cytosolic compartment and partially co-localized with intracellular organelles. The global deletion of TMEM16A led to severe skeletal muscle developmental defect. In vitro observation showed that the proliferation of Tmem16a-/- myoblasts was significantly promoted along with activated ERK1/2 and Cyclin D expression; the myogenic differentiation was impaired accompanied by the enhanced caspase 12/3 activation, implying enhanced endoplasmic reticulum (ER) stress. Interestingly, the bradykinin-induced Ca2+ release from ER calcium store was significantly enhanced after TMEM16A deletion. This suggested a suppressing role of intracellular TMEM16A in ER calcium release whereby regulating the flux of chloride ion across the ER membrane. Our findings reveal a unique location pattern of TMEM16A in undifferentiated myoblasts and its role in myogenesis.

Nearly integrable turbulence and rogue waves in disordered nonlinear Schrödinger systems.

Integrable nonlinear Schrödinger (NLS) systems provide a platform for exploring the propagation and interaction of nonlinear waves. Extreme events such as rogue waves (RWs) are currently of particular interest. However, the presence of disorder in these systems is sometimes unavoidable, for example, in the forms of turbulent current in the ocean and random fluctuation in optical media, and its influence remains less understood. Here, we report numerical experiments of two nearly-integrable NLS equations with the effect of disorder showing that the probability of RW occurrence can be significantly increased by adding weak system noise. Linear and nonlinear spectral analyses are proposed to qualitatively explain those findings. Our results are expected to shed light on the understanding of the interplay between disorder and nonlinearity, and may motivate new experimental works in hydrodynamics, nonlinear optics, and Bose-Einstein condensates.

Anomalous diffusion of discrete solitons driven by evolving disorder.

Anomalous diffusion is simulated in this paper by studying the transport of discrete solitons in a lattice with evolving disorder. We find a Richardson-type diffusion for the small solitons and a regime of transient diffusion for larger solitons within the ensemble-averaged description. As a comparison, the time-averaged observables present a ballistic scaling for both cases. However, distribution of these observables changes remarkably with the soliton size. Our results suggest violation of ergodicity for the solitons' diffusive processes, which are expected to shed light on further understanding of the discreteness-disorder-nonlinearity interaction.

Intra-subunit Disulfide Determines the Conversion and Structural Stability of CRP Isoforms.

C-reactive protein (CRP) is a major human acute-phase reactant that is composed of five identical subunits. CRP dissociates into subunits at inflammatory loci forming monomeric CRP (mCRP) with substantially enhanced activities, which can be further activated by reducing the intra-subunit disulfide bond. However, conformational changes underlying the activation process of CRP are less well understood. Conformational changes accompanying the conversion of CRP to mCRP with or without reduction were examined with circular dichroism spectroscopy, fluorescence spectroscopy, electron microscopy, size-exclusion chromatography, and neoepitope expression. The conversion of CRP to mCRP follows a two-stage process. In the first stage, CRP dissociates into molten globular subunits characterized by intact secondary structure elements with greatly impaired tertiary packing. In the second stage, these intermediates completely lose their native subunit conformation and assemble into high-order aggregates. The inclusion of reductant accelerates the formation of molten globular subunits in the first step and promotes the formation of more compact aggregates in the second stage. We further show a significant contribution of electrostatic interactions to the stabilization of native CRP. The conformational features of dissociated subunits and the aggregation of mCRP may have a key impact on their activities.

Psychological morbidities and fatigue in patients with confirmed COVID-19 during disease outbreak: prevalence and associated biopsychosocial risk factors.

Objective: The coronavirus disease 2019 (COVID-19) - a novel and highly infectious pneumonia - has now spread across China and beyond for over four months. However, its psychological impact on patients is unclear. We aim to examine the prevalence and associated risk factors for psychological morbidities and fatigue in patients with confirmed COVID-19 infection. Methods: Amidst the disease outbreak, 41 out of 105 COVID-19 patients in a local designated hospital in China were successfully assessed using a constellation of psychometric questionnaires to determine their psychological morbidities and fatigue. Several potential biopsychosocial risk factors (including pre-existing disabilities, CT severity score of pneumonia, social support, coping strategies) were assessed through multivariable logistic regression analyses to clarify their association with mental health in patients. Results: 43.9% of 41 patients presented with impaired general mental health, 12.2% had post-traumatic stress disorder (PTSD) symptoms, 26.8% had anxiety and/or depression symptoms, and 53.6% had fatigue. We did not find any association between pneumonia severity and psychological morbidities or fatigue in COVID-19 patients. However, high perceived stigmatization was associated with an increased risk of impaired general mental health and high perceived social support was associated with decreased risk. Besides, negative coping inclination was associated with an increased risk of PTSD symptoms; high perceived social support was associated with a decreased risk of anxiety and/or depression symptoms. Conclusions: Psychological morbidities and chronic fatigue are common among COVID-19 patients. Negative coping inclination and being stigmatized are primary risk factors while perceived social support is the main protective factor.

Risk factors for adverse clinical outcomes with COVID-19 in China: a multicenter, retrospective, observational study.

Background: The risk factors for adverse events of Coronavirus Disease-19 (COVID-19) have not been well described. We aimed to explore the predictive value of clinical, laboratory and CT imaging characteristics on admission for short-term outcomes of COVID-19 patients. Methods: This multicenter, retrospective, observation study enrolled 703 laboratory-confirmed COVID-19 patients admitted to 16 tertiary hospitals from 8 provinces in China between January 10, 2020 and March 13, 2020. Demographic, clinical, laboratory data, CT imaging findings on admission and clinical outcomes were collected and compared. The primary endpoint was in-hospital death, the secondary endpoints were composite clinical adverse outcomes including in-hospital death, admission to intensive care unit (ICU) and requiring invasive mechanical ventilation support (IMV). Multivariable Cox regression, Kaplan-Meier plots and log-rank test were used to explore risk factors related to in-hospital death and in-hospital adverse outcomes. Results: Of 703 patients, 55 (8%) developed adverse outcomes (including 33 deceased), 648 (92%) discharged without any adverse outcome. Multivariable regression analysis showed risk factors associated with in-hospital death included ≥ 2 comorbidities (hazard ratio [HR], 6.734; 95% CI; 3.239-14.003, p < 0.001), leukocytosis (HR, 9.639; 95% CI, 4.572-20.321, p < 0.001), lymphopenia (HR, 4.579; 95% CI, 1.334-15.715, p = 0.016) and CT severity score > 14 (HR, 2.915; 95% CI, 1.376-6.177, p = 0.005) on admission, while older age (HR, 2.231; 95% CI, 1.124-4.427, p = 0.022), ≥ 2 comorbidities (HR, 4.778; 95% CI; 2.451-9.315, p < 0.001), leukocytosis (HR, 6.349; 95% CI; 3.330-12.108, p < 0.001), lymphopenia (HR, 3.014; 95% CI; 1.356-6.697, p = 0.007) and CT severity score > 14 (HR, 1.946; 95% CI; 1.095-3.459, p = 0.023) were associated with increased odds of composite adverse outcomes. Conclusion: The risk factors of older age, multiple comorbidities, leukocytosis, lymphopenia and higher CT severity score could help clinicians identify patients with potential adverse events.

Transient diffusion and two-regime localization of discrete breatherlike excitations in nonlinear Schrödinger lattice with disorder.

We systematically simulate and analyze the motion of discrete breatherlike excitations (DBEs) in the nonlinear Schrödinger lattice with random potentials. A universal transient diffusion of the DBEs is observed for short timescales (t≲10^{3}). For longer timescales (t up to 10^{5}), the DBEs become localized. Such localization, depending on the DBE powers, has two different regimes: Regime I is the Anderson-like localization induced by the disorder, while Regime II is an enhanced localization attributed to both the disorder and discreteness. Our study is expected to shed light on understanding the interplay between disorder and strong nonlinearity, from the diffusive transport and localization properties of nonlinear localized excitations in random media.

[Myocardial bridging on dual-source CT: comparison with conventional coronary angiography].

OBJECTIVE: To assess the ability to detect myocardial bridging (MB) of dual-source computed tomography (DSCT) compared with conventional coronary angiography (CAG). METHODS: Both DSCT coronary angiography (DSCTCA) and CAG were performed on 53 patients diagnosed or suspected as with coronary artery disease (CAD), 45 males and 8 females, aged 36-87. 4D cine mode was performed on 16 of these 53 patients with MB shown on DSCTCA, and the CAG data were reviewed retrospectively by automatic cine method. The MB findings by both methods were compared. The diameters of segments proximal to and distal to MB, tunneled coronary arteries at systolic and diastolic phases were measured, and stenosis rate of tunneled coronary arteries was computed according to the equation. The relationship between stenosis rate of tunneled artery and milking effect on 4D cine mode was analyzed. RESULTS: Of the 53 patients who had undergone CAG; 4 images of MB were detected in 3 patients based on the CAG findings, with a detection rate of 5.7%, significantly than that by DSCT (30.2%, 21 images of MB in 16 patients, chi2 = 10. 837, P = 0.001). 4D cine mode showed various degrees of "milking effect" and abnormal blood flow in 16 patients with MB. The stenosis rate of tunneled artery during systole was related to the "milking effect" rate on 4D cine mode of DSCTCA (r = 0.640, P = 0.006). CONCLUSION: More vividly and reliably showing the "milking effect" than CAG, DSCT can be used as a routine screening method to detect or exclude MB.

Soliton mobility in disordered lattices.

We investigate soliton mobility in the disordered Ablowitz-Ladik (AL) model and the standard nonlinear Schrödinger (NLS) lattice with the help of an effective potential generalizing the Peierls-Nabarro potential. This potential results from a deviation from integrability, which is due to randomness for the AL model, and both randomness and lattice discreteness for the NLS lattice. The statistical properties of such a potential are analyzed, and it is shown how the soliton mobility is affected by its size. The usefulness of this effective potential in studying soliton dynamics is demonstrated numerically. Furthermore, we propose two ways to enhance soliton transport in the presence of disorder: one is to use specific realizations of randomness, and the other is to consider a specific soliton pair.

Soliton trapping in a disordered lattice.

In recent years, the competition between randomness and nonlinearity was extensively explored. In the present paper, the dynamics of solitons of the Ablowitz-Ladik model in the presence of a random potential is studied. In the absence of the random potential, it is an integrable model and the solitons are stable. As a result of the random potential, this stability is destroyed. In a certain regime, for short times, particlelike dynamics with constant mass is found; in another regime, particlelike dynamics with varying mass takes place. In particular, an effective potential is found that predicts correctly changes in the direction of motion of the soliton. This potential is a scaling function of time and strength of the potential, leading to a relation between the first time when the soliton changes direction and the strength of the random potential.

Yolk-type Au@Fe3O4@C nanospheres for drug delivery, MRI and two-photon fluorescence imaging.

Nearly monodispersed yolk-type Au@Fe3O4@C nanospheres with hollow cores of 50 nm in diameter were prepared through coating Au@SiO2 nanoparticles with Fe3O4@C double layers, followed by dissolving SiO2. The cytotoxicity of the nanospheres was evaluated by MTT assay, demonstrating a high biocompatibility. The yolk-type nanospheres show a high DOX loading content of 1237 mg g(-1). The coexistence of Fe3O4 and Au also makes the nanospheres as dual probes for MR imaging with a specific relaxivity (r2*) of 384.38 mM(-1) s(-1) and optical fluorescence imaging using a near-infrared (NIR) excitation.

Synthesis of carbon-coated, porous and water-dispersive Fe3O4 nanocapsules and their excellent performance for heavy metal removal applications.

Porous Fe(3)O(4)@C nanocapsules with a diameter of about 120 nm (about 50 nm cavity) were synthesized by combining a sacrificial template method with solvothermal treatment. The N(2) adsorption-desorption isotherms reveals their mesoporous structure and large BET surface area (159.8 m(2) g(-1)). The magnetic investigation indicates their superparamagnetic nature and high saturation magnetization (55.93 emu g(-1)). The nanocapsules also exhibit negative zeta potential (-27.59 mV) and possess carboxyl groups on the outer carbon layer, which keeps them highly dispersive in aqueous solution and provides a chelating function for metal ions. The heavy metals removal test demonstrates the excellent affinity of nanocapsules, the high efficiency for different metals (>90%), 79 mg g(-1) adsorption capacity for Pb(2+) and ultrafast removal process (Pb(2+), 99.57% within 1 minute). Protected by a porous carbon layer, the nanocapsules display excellent acidic resistance and adsorption properties even in an acidic solution (pH = 3). Moreover, the metal ions can be easily adsorbed and desorbed through manipulating the pH value for adsorbent regeneration and heavy metal recycling.