Explore the vast range of titles available.

Kidneys are one of the targets for SARS-CoV-2, it is reported that up to 36% of patients with SARS-CoV-2 infection would develop into acute kidney injury (AKI). AKI is associated with high mortality in the clinical setting and contributes to the transition of AKI to chronic kidney disease (CKD). Up to date, the underlying mechanisms are obscure and there is no effective and specific treatment for COVID-19-induced AKI. In the present study, we investigated the mechanisms and interactions between Quercetin and SARS-CoV-2 targets proteins by using network pharmacology and molecular docking. The renal protective effects of Quercetin on COVID-19-induced AKI may be associated with the blockade of the activation of inflammatory, cell apoptosis-related signaling pathways. Quercetin may also serve as SARS-CoV-2 inhibitor by binding with the active sites of SARS-CoV-2 main protease 3CL and ACE2, therefore suppressing the functions of the proteins to cut the viral life cycle. In conclusion, Quercetin may be a novel therapeutic agent for COVID-19-induced AKI. Inhibition of inflammatory, cell apoptosis-related signaling pathways may be the critical mechanisms by which Quercetin protects kidney from SARS-CoV-2 injury.

With the increasing demand for multispectral information acquisition, infrared multispectral imaging technology that is inexpensive and can be miniaturized and integrated into other devices has received extensive attention. However, the widespread usage of such photodetectors is still limited by the high cost of epitaxial semiconductors and complex cryogenic cooling systems. Here, we demonstrate a noncooled two-color infrared photodetector that can provide temporal-spatial coexisting spectral blackbody detection at both near-infrared and mid-infrared wavelengths. This photodetector consists of vertically stacked back-to-back diode structures. The two-color signals can be effectively separated to achieve ultralow crosstalk of ~0.05% by controlling the built-in electric field depending on the intermediate layer, which acts as an electron-collecting layer and hole-blocking barrier. The impressive performance of the two-color photodetector is verified by the specific detectivity (D*) of 6.4 × 109 cm Hz1/2 W−1 at 3.5 μm and room temperature, as well as the promising NIR/MWIR two-color infrared imaging and absolute temperature detection.

Inflammation and fibrosis are two pathological features of chronic kidney disease (CKD). Transforming growth factor-β (TGF-β) has been long considered as a key mediator of renal fibrosis. In addition, TGF-β also acts as a potent anti-inflammatory cytokine that negatively regulates renal inflammation. Thus, blockade of TGF-β inhibits renal fibrosis while promoting inflammation, revealing a diverse role for TGF-β in CKD. It is now well documented that TGF-β1 activates its downstream signaling molecules such as Smad3 and Smad3-dependent non-coding RNAs to transcriptionally and differentially regulate renal inflammation and fibrosis, which is negatively regulated by Smad7. Therefore, treatments by rebalancing Smad3/Smad7 signaling or by specifically targeting Smad3-dependent non-coding RNAs that regulate renal fibrosis or inflammation could be a better therapeutic approach. In this review, the paradoxical functions and underlying mechanisms by which TGF-β1 regulates in renal inflammation and fibrosis are discussed and novel therapeutic strategies for kidney disease by targeting downstream TGF-β/Smad signaling and transcriptomes are highlighted.

Continuous imaging of cardiac functions is highly desirable for the assessment of long-term cardiovascular health, detection of acute cardiac dysfunction and clinical management of critically ill or surgical patients 1 – 4 . However, conventional non-invasive approaches to image the cardiac function cannot provide continuous measurements owing to device bulkiness 5 – 11 , and existing wearable cardiac devices can only capture signals on the skin 12 – 16 . Here we report a wearable ultrasonic device for continuous, real-time and direct cardiac function assessment. We introduce innovations in device design and material fabrication that improve the mechanical coupling between the device and human skin, allowing the left ventricle to be examined from different views during motion. We also develop a deep learning model that automatically extracts the left ventricular volume from the continuous image recording, yielding waveforms of key cardiac performance indices such as stroke volume, cardiac output and ejection fraction. This technology enables dynamic wearable monitoring of cardiac performance with substantially improved accuracy in various environments. Innovations in device design, material fabrication and deep learning are described, leading to a wearable ultrasound transducer capable of dynamic cardiac imaging in various environments and under different conditions.

Recent advances in wearable ultrasound technologies have demonstrated the potential for hands-free data acquisition, but technical barriers remain as these probes require wire connections, can lose track of moving targets and create data-interpretation challenges. Here we report a fully integrated autonomous wearable ultrasonic-system-on-patch (USoP). A miniaturized flexible control circuit is designed to interface with an ultrasound transducer array for signal pre-conditioning and wireless data communication. Machine learning is used to track moving tissue targets and assist the data interpretation. We demonstrate that the USoP allows continuous tracking of physiological signals from tissues as deep as 164 mm. On mobile subjects, the USoP can continuously monitor physiological signals, including central blood pressure, heart rate and cardiac output, for as long as 12 h. This result enables continuous autonomous surveillance of deep tissue signals toward the internet-of-medical-things. A wearable ultrasound patch monitors subjects in motion using machine learning and wireless electronics.

Nanohertz gravitational waves (GWs) from supermassive binary black holes (SMBBHs), detectable via pulsar timing arrays (PTAs), offer a novel avenue to constrain dark energy. Based on cosmological simulations and semi-analytic galaxy formation models, this study explores the detectability of individual nanohertz SMBBH sources using next-generation PTAs and their potential for constraining dark energy under an optimistic scenario considering only the presence of white noise. By constructing light-cone SMBBH populations across hardening timescales ( τ H = 0.1 / 5 / 10  Gyr) and computing signal-to-noise ratios (SNR), we find advanced PTAs can resolve 10 2 – 10 3 sources with SNR > 8 (primarily at z < 1 with chirp masses of 10 8 – 10 10 M ⊙ ) . If electromagnetic counterparts can be identified, optimal configurations ( σ t = 50  ns, N p = 1000 , T obs = 30  yr with τ H ≤ 5  Gyr) could constrain the dark energy equation-of-state (EoS) parameter w to Δ w ∼ 0.023 –0.048,  where the constraints only exhibit weak dependence on τ H within 0.1–5 Gyr. If only 10 % of GW sources have detectable electromagnetic counterparts, constraints weaken to Δ w = 0.075 ( τ H = 0.1  Gyr) and Δ w = 0.162 ( τ H = 5  Gyr) under the most optimal parameter configuration. What’s more, conservative PTAs ( N p = 500 , σ t = 100 –200 ns) with additional 30-year data accumulation could double resolvable source counts and improve Δ w precision by ∼ 40 % .

The electroencephalogram (EEG) can reflect brain activity and contains abundant information of different anesthetic states of the brain. It has been widely used for monitoring depth of anesthesia (DoA). In this study, we propose a method that combines multiple EEG-based features with artificial neural network (ANN) to assess the DoA. Multiple EEG-based features can express the states of the brain more comprehensively during anesthesia. First, four parameters including permutation entropy, 95% spectral edge frequency, BetaRatio and SynchFastSlow were extracted from the EEG signal. Then, the four parameters were set as the inputs to an ANN which used bispectral index (BIS) as the reference output. 16 patient datasets during propofol anesthesia were used to evaluate this method. The results indicated that the accuracies of detecting each state were 86.4% (awake), 73.6% (light anesthesia), 84.4% (general anesthesia), and 14% (deep anesthesia). The correlation coefficient between BIS and the index of this method was 0.892 ( p < 0.001 ). The results showed that the proposed method could well distinguish between awake and other anesthesia states. This method is promising and feasible for a monitoring system to assess the DoA.

Background With the adoption of active aging as a national strategy in China, physical activity has emerged as a vital factor in fostering active aging due to its practicality, feasibility, and accessibility. Serving as a key means for older adults to maintain meaningful engagement in later life, physical activity significantly enhances their well-being. However, most existing studies emphasize discursive analysis and experimental interventions, lacking comprehensive empirical research on how the type, intensity, and frequency of physical activity relate to active aging. Notably, the impact of dynamic factors such as age, period, and cohort effects has been largely neglected. Therefore, this study aims to systematically examine these factors to refine physical activity intervention strategies and establish a scientific foundation for advancing active aging. Methods Based on data from the 2011–2018 China Health and Retirement Longitudinal Study, this study explores the evolving impact of physical activity levels on active aging among middle-aged and older adults (aged 45–90 years). Employing hierarchical age-period-cohort cross-classified random effects models, the analysis investigates how this relationship varies across age, observation period, and birth cohort. Results From a static standpoint, a significant correlation was observed between physical activity and active aging levels in middle-aged and older adults, with moderate physical activity showing the strongest effect (coef.= 0.013). From a dynamic perspective, the impact of physical activity on active aging was significant across age, period, and cohort ( P  < 0.001). In terms of age, there was a nonlinear relationship with active aging, where the decline was slower until the age of 55, after which it accelerated. However, a higher level of physical activity can play a role in slowing the decline of active aging. Regarding the period, the level of active aging fluctuated and increased between 2011 and 2018. The influence of low-intensity physical activity on active aging was more pronounced before 2015, while the impact of moderate and high-intensity physical activity grew after 2016. In terms of cohort, the active aging trajectory for middle-aged and older adults followed a “rise-decline-rise” pattern, with the effects of varying intensities of physical activity on active aging showing alternating trends. Conclusion Varying intensities of physical activity impact the process of active aging. Additionally, age, period, and cohort differences should also be taken into account to inform the development of targeted intervention strategies.

Avalanche photodiodes (APDs) have drawn huge interest in recent years and have been extensively used in a range of fields including the most important one—optical communication systems due to their time responses and high sensitivities. This article shows the evolution and the recent development of A III B V , A II B VI , and potential alternatives to formerly mentioned—“ third wave ” superlattices (SL) and two-dimensional (2D) materials infrared (IR) APDs. In the beginning, the APDs fundamental operating principle is demonstrated together with progress in architecture. It is shown that the APDs evolution has moved the device’s performance towards higher bandwidths, lower noise, and higher gain-bandwidth products. The material properties to reach both high gain and low excess noise for devices operating in different wavelength ranges were also considered showing the future progress and the research direction. More attention was paid to advances in A III B V APDs, such as AlInAsSb, which may be used in future optical communications, type-II superlattice (T2SLs, “Ga-based” and “Ga-free”), and 2D materials-based IR APDs. The latter—atomically thin 2D materials exhibit huge potential in APDs and could be considered as an alternative material to the well-known, sophisticated, and developed A III B V APD technologies to include single-photon detection mode. That is related to the fact that conventional bulk materials APDs’ performance is restricted by reasonably high dark currents. One approach to resolve that problem seems to be implementing low-dimensional materials and structures as the APDs’ active regions. The Schottky barrier and atomic level thicknesses lead to the 2D APD dark current significant suppression. What is more, APDs can operate within visible (VIS), near-infrared (NIR)/mid-wavelength infrared range (MWIR), with a responsivity ~80 A/W, external quantum efficiency ~24.8%, gain ~10 5 for MWIR [wavelength, λ  = 4 μm, temperature, T  = 10–180 K, Black Phosphorous (BP)/InSe APD]. It is believed that the 2D APD could prove themselves to be an alternative providing a viable method for device fabrication with simultaneous high-performance—sensitivity and low excess noise.

Background With more than 600,000 mortalities each year, colorectal cancer (CRC) is the third most commonly diagnosed type of cancer worldwide. Recently, mechanisms involving noncoding RNAs have been implicated in the development of CRC. Methods We examined expression levels of lncRNA CRNDE and miR-181a-5p in 64 cases of CRC tissues and cell lines by qRT-PCR. Gain-of-function and loss-of-function assays were performed to examine the effect of CRNDE and miR-181a-5p on proliferation and chemoresistance of CRC cells. Using fluorescence reporter and western blot assays, we also explored the possible mechanisms of CRNDE in CRC cells. Results In this study, we found that the expression levels of the CRNDE were upregulated in CRC clinical tissue samples. We identified microRNA miR-181a-5p as an inhibitory target of CRNDE. Both CRNDE knockdown and miR-181a-5p overexpression in CRC cell lines led to inhibited cell proliferation and reduced chemoresistance. We also determined that β-catenin and TCF4 were inhibitory targets of miR-181a-5p, and that Wnt/β-catenin signaling was inhibited by both CRNDE knockdown and miR-181a-5p overexpression. Significantly, we found that the repression of cell proliferation, the reduction of chemoresistance, and the inhibition of Wnt/β-catenin signaling induced by CRNDE knockdown would require the increased expression of miR-181a-5p. Conclusions Our study demonstrated that the lncRNA CRNDE could regulate the progression and chemoresistance of CRC via modulating the expression levels of miR-181a-5p and the activity of Wnt/β-catenin signaling.