Development and validation of a prognostic model for assessing long COVID risk following Omicron wave-a large population-based cohort study.

BACKGROUND: Long coronavirus disease (COVID) after COVID-19 infection is continuously threatening the health of people all over the world. Early prediction of the risk of Long COVID in hospitalized patients will help clinical management of COVID-19, but there is still no reliable and effective prediction model. METHODS: A total of 1905 hospitalized patients with COVID-19 infection were included in this study, and their Long COVID status was followed up 4-8 weeks after discharge. Univariable and multivariable logistic regression analysis were used to determine the risk factors for Long COVID. Patients were randomly divided into a training cohort (70%) and a validation cohort (30%), and factors for constructing the model were screened using Lasso regression in the training cohort. Visualize the Long COVID risk prediction model using nomogram. Evaluate the performance of the model in the training and validation cohort using the area under the curve (AUC), calibration curve, and decision curve analysis (DCA). RESULTS: A total of 657 patients (34.5%) reported that they had symptoms of long COVID. The most common symptoms were fatigue or muscle weakness (16.8%), followed by sleep difficulties (11.1%) and cough (9.5%). The risk prediction nomogram of age, diabetes, chronic kidney disease, vaccination status, procalcitonin, leukocytes, lymphocytes, interleukin-6 and D-dimer were included for early identification of high-risk patients with Long COVID. AUCs of the model in the training cohort and validation cohort are 0.762 and 0.713, respectively, demonstrating relatively high discrimination of the model. The calibration curve further substantiated the proximity of the nomogram's predicted outcomes to the ideal curve, the consistency between the predicted outcomes and the actual outcomes, and the potential benefits for all patients as indicated by DCA. This observation was further validated in the validation cohort. CONCLUSIONS: We established a nomogram model to predict the long COVID risk of hospitalized patients with COVID-19, and proved its relatively good predictive performance. This model is helpful for the clinical management of long COVID.

MICU3 regulates mitochondrial Ca2+-dependent antioxidant response in skeletal muscle aging.

Age-related loss of skeletal muscle mass and function, termed sarcopenia, could impair the quality of life in the elderly. The mechanisms involved in skeletal muscle aging are intricate and largely unknown. However, more and more evidence demonstrated that mitochondrial dysfunction and apoptosis also play an important role in skeletal muscle aging. Recent studies have shown that mitochondrial calcium uniporter (MCU)-mediated mitochondrial calcium affects skeletal muscle mass and function by affecting mitochondrial function. During aging, we observed downregulated expression of mitochondrial calcium uptake family member3 (MICU3) in skeletal muscle, a regulator of MCU, which resulted in a significant reduction in mitochondrial calcium uptake. However, the role of MICU3 in skeletal muscle aging remains poorly understood. Therefore, we investigated the effect of MICU3 on the skeletal muscle of aged mice and senescent C2C12 cells induced by D-gal. Downregulation of MICU3 was associated with decreased myogenesis but increased oxidative stress and apoptosis. Reconstitution of MICU3 enhanced antioxidants, prevented the accumulation of mitochondrial ROS, decreased apoptosis, and increased myogenesis. These findings indicate that MICU3 might promote mitochondrial Ca2+ homeostasis and function, attenuate oxidative stress and apoptosis, and restore skeletal muscle mass and function. Therefore, MICU3 may be a potential therapeutic target in skeletal muscle aging.

Hovering of model insects: simulation by coupling equations of motion with Navier-Stokes equations.

When an insect hovers, the centre of mass of its body oscillates around a point in the air and its body angle oscillates around a mean value, because of the periodically varying aerodynamic and inertial forces of the flapping wings. In the present paper, hover flight including body oscillations is simulated by coupling the equations of motion with the Navier-Stokes equations. The equations are solved numerically; periodical solutions representing the hover flight are obtained by the shooting method. Two model insects are considered, a dronefly and a hawkmoth; the former has relatively high wingbeat frequency (n) and small wing mass to body mass ratio, whilst the latter has relatively low wingbeat frequency and large wing mass to body mass ratio. The main results are as follows. (i) The body mainly has a horizontal oscillation; oscillation in the vertical direction is about 1/6 of that in the horizontal direction and oscillation in pitch angle is relatively small. (ii) For the hawkmoth, the peak-to-peak values of the horizontal velocity, displacement and pitch angle are 0.11 U (U is the mean velocity at the radius of gyration of the wing), 0.22 c=4 mm (c is the mean chord length) and 4 deg., respectively. For the dronefly, the corresponding values are 0.02 U, 0.05 c=0.15 mm and 0.3 deg., much smaller than those of the hawkmoth. (iii) The horizontal motion of the body decreases the relative velocity of the wings by a small amount. As a result, a larger angle of attack of the wing, and hence a larger drag to lift ratio or larger aerodynamic power, is required for hovering, compared with the case of neglecting body oscillations. For the hawkmoth, the angle of attack is about 3.5 deg. larger and the specific power about 9% larger than that in the case of neglecting the body oscillations; for the dronefly, the corresponding values are 0.7 deg. and 2%. (iv) The horizontal oscillation of the body consists of two parts; one (due to wing aerodynamic force) is proportional to 1/cn2 and the other (due to wing inertial force) is proportional to wing mass to body mass ratio. For many insects, the values of 1/cn2 and wing mass to body mass ratio are much smaller than those of the hawkmoth, and the effects of body oscillation would be rather small; thus it is reasonable to neglect the body oscillations in studying their aerodynamics.

Generation of the pitch moment during the controlled flight after takeoff of fruitflies.

In the present paper, the controlled flight of fruitflies after voluntary takeoff is studied. Wing and body kinematics of the insects after takeoff are measured using high-speed video techniques, and the aerodynamic force and moment are calculated by the computational fluid dynamics method based on the measured data. How the control moments are generated is analyzed by correlating the computed moments with the wing kinematics. A fruit-fly has a large pitch-up angular velocity owing to the takeoff jump and the fly controls its body attitude by producing pitching moments. It is found that the pitching moment is produced by changes in both the aerodynamic force and the moment arm. The change in the aerodynamic force is mainly due to the change in angle of attack. The change in the moment arm is mainly due to the change in the mean stroke angle and deviation angle, and the deviation angle plays a more important role than the mean stroke angle in changing the moment arm (note that change in deviation angle implies variation in the position of the aerodynamic stroke plane with respect to the anatomical stroke plane). This is unlike the case of fruitflies correcting pitch perturbations in steady free flight, where they produce pitching moment mainly by changes in mean stroke angle.

Floquet stability analysis of the longitudinal dynamics of two hovering model insects.

Because of the periodically varying aerodynamic and inertial forces of the flapping wings, a hovering or constant-speed flying insect is a cyclically forcing system, and, generally, the flight is not in a fixed-point equilibrium, but in a cyclic-motion equilibrium. Current stability theory of insect flight is based on the averaged model and treats the flight as a fixed-point equilibrium. In the present study, we treated the flight as a cyclic-motion equilibrium and used the Floquet theory to analyse the longitudinal stability of insect flight. Two hovering model insects were considered-a dronefly and a hawkmoth. The former had relatively high wingbeat frequency and small wing-mass to body-mass ratio, and hence very small amplitude of body oscillation; while the latter had relatively low wingbeat frequency and large wing-mass to body-mass ratio, and hence relatively large amplitude of body oscillation. For comparison, analysis using the averaged-model theory (fixed-point stability analysis) was also made. Results of both the cyclic-motion stability analysis and the fixed-point stability analysis were tested by numerical simulation using complete equations of motion coupled with the Navier-Stokes equations. The Floquet theory (cyclic-motion stability analysis) agreed well with the simulation for both the model dronefly and the model hawkmoth; but the averaged-model theory gave good results only for the dronefly. Thus, for an insect with relatively large body oscillation at wingbeat frequency, cyclic-motion stability analysis is required, and for their control analysis, the existing well-developed control theories for systems of fixed-point equilibrium are no longer applicable and new methods that take the cyclic variation of the flight dynamics into account are needed.

Aerodynamic force generation and power requirements in forward flight in a fruit fly with modeled wing motion.

Aerodynamic force generation and power requirements in forward flight in a fruit fly with modeled wing motion were studied using the method of computational fluid dynamics. The Navier-Stokes equations were solved numerically. The solution provided the flow velocity and pressure fields, from which the vorticity wake structure and the unsteady aerodynamic forces and torques were obtained (the inertial torques due to the acceleration of the wing-mass were computed analytically). From the flow-structure and force information, insights were gained into the unsteady aerodynamic force generation. On the basis of the aerodynamic and inertial torques, the mechanical power was obtained, and its properties were investigated. The unsteady force mechanisms revealed previously for hovering (i.e. delayed stall, rapid acceleration at the beginning of the strokes and fast pitching-up rotation at the end of the strokes) apply to forward flight. Even at high advance ratios, e.g. J=0.53-0.66 (J is the advance ratio), the leading edge vortex does not shed (at such advance ratios, the wing travels approximately 6.5 chord lengths during the downstroke). At low speeds (J approximately equal to 0.13), the lift (vertical force) for weight support is produced during both the down- and upstrokes (the downstroke producing approximately 80% and the upstroke producing approximately 20% of the mean lift), and the lift is contributed mainly by the wing lift; the thrust that overcomes the body drag is produced during the upstroke, and it is contributed mainly by the wing drag. At medium speeds (J approximately equal to 0.27), the lift is mainly produced during the downstroke and the thrust mainly during the upstroke; both of them are contributed almost equally by the wing lift and wing drag. At high speeds (J approximately equal to 0.53), the lift is mainly produced during the downstroke and is mainly contributed by the wing drag; the thrust is produced during both the down- and upstrokes, and in the downstroke, is contributed by the wing lift and in the upstroke, by the wing drag. In forward flight, especially at medium and high flight speeds, the work done during the downstroke is significantly greater than during the upstroke. At advance ratios J approximately equal to 0.13, 0.27 and 0.53, the work done during the downstroke is approximately 1.6, 2.8 and 4.2 times as much as that during the upstroke, respectively. At J=0 (hovering), the body-mass-specific power is approximately 29 W kg(-1); at J=0.13 and 0.27, the power is approximately 10% less than that of hovering; at J=0.40, the power is approximately the same as that of hovering; when J is further increased, the power increases sharply. The graph of power against flying speeds is approximately J-shaped. From the graph of power against flying speeds, it is predicted that the insect usually flies at advance ratios between zero and 0.4, and for fast flight, it would fly at an advance ratio between 0.4 and 0.53.

Unsteady aerodynamic forces of a flapping wing.

The unsteady aerodynamic forces of a model fruit fly wing in flapping motion were investigated by numerically solving the Navier-Stokes equations. The flapping motion consisted of translation and rotation [the translation velocity (u(t)) varied according to the simple harmonic function (SHF), and the rotation was confined to a short period around stroke reversal]. First, it was shown that for a wing of given geometry with u(t) varying as the SHF, the aerodynamic force coefficients depended only on five non-dimensional parameters, i.e. Reynolds number (Re), stroke amplitude (Phi), mid-stroke angle of attack (alpha(m)), non-dimensional duration of wing rotation (Delta tau(r)) and rotation timing [the mean translation velocity at radius of the second moment of wing area (U), the mean chord length (c) and c/U were used as reference velocity, length and time, respectively]. Next, the force coefficients were investigated for a case in which typical values of these parameters were used (Re=200; Phi=150 degrees; alpha(m)=40 degrees; Delta tau(r) was 20% of wingbeat period; rotation was symmetrical). Finally, the effects of varying these parameters on the force coefficients were investigated. In the Re range considered (20-1800), when Re was above approximately 100, the lift ((L)) and drag ((D)) coefficients were large and varied only slightly with Re (in agreement with results previously published for revolving wings); the large force coefficients were mainly due to the delayed stall mechanism. However, when Re was below approximately 100, (L) decreased and (D) increased greatly. At such low Re, similar to the case of higher Re, the leading edge vortex existed and attached to the wing in the translatory phase of a half-stroke; but it was very weak and its vorticity rather diffused, resulting in the small (L) and large (D). Comparison of the calculated results with available hovering flight data in eight species (Re ranging from 13 to 1500) showed that when Re was above approximately 100, lift equal to insect weight could be produced but when Re was lower than approximately 100, additional high-lift mechanisms were needed. In the range of Re above approximately 100, Phi from 90 degrees to 180 degrees and Delta tau(r) from 17% to 32% of the stroke period (symmetrical rotation), the force coefficients varied only slightly with Re, Phi and Delta tau(r). This meant that the forces were approximately proportional to the square of Phi n (n is the wingbeat frequency); thus, changing Phi and/or n could effectively control the magnitude of the total aerodynamic force. The time course of (L) (or (D)) in a half-stroke for u(t) varying according to the SHF resembled a half sine-wave. It was considerably different from that published previously for u(t), varying according to a trapezoidal function (TF) with large accelerations at stroke reversal, which was characterized by large peaks at the beginning and near the end of the half-stroke. However, the mean force coefficients and the mechanical power were not so different between these two cases (e.g. the mean force coefficients for u(t) varying as the TF were approximately 10% smaller than those for u(t) varying as the SHF except when wing rotation is delayed).