Influenza D virus infection in China, 2022-2023.

Influenza D virus (IDV) plays an important role in the bovine respiratory disease (BRD) complex. Its potential for the zoonotic transmission is of particular concern. In China, IDV has previously been identified in agricultural animals by molecular surveys with no live virus isolates reported. In this study, live IDVs were successfully isolated from cattle in China, which prompted us to further investigate the national prevalence, antigenic property, and infection biology of the virus. IDV RNA was detected in 11.1% (51/460) of cattle throughout the country in 2022-2023. Moreover, we conducted the first IDV serosurveillance in China, revealing a high seroprevalence (91.4%, 393/430) of IDV in cattle during the 2022-2023 winter season. Notably, all the 16 provinces from which cattle originated possessed seropositive animals, and 3 of them displayed the 100% IDV-seropositivity rate. In contrast, a very low seroprevalence of IDV was observed in pigs (3%, 3/100) and goats (1%, 1/100) during the same period of investigation. Furthermore, besides D/Yama2019 lineage-like IDVs, we discovered the D/660 lineage-like IDV in Chinese cattle, which has not been detected to date in Asia. Finally, the Chinese IDVs replicated robustly in diverse cell lines but less efficiently in the swine cell line. Considering the nationwide distribution, high seroprevalence, and appreciably genetic diversity, further studies are required to fully evaluate the risk of Chinese IDVs for both animal and human health in China, which can be evidently facilitated by IDV isolates reported in this study.

Neuroprotective effect of acetoxypachydiol against oxidative stress through activation of the Keap1-Nrf2/HO-1 pathway.

BACKGROUND: Excessive oxidative stress in the brain is an important pathological factor in neurological diseases. Acetoxypachydiol (APHD) is a lipophilic germacrane-type diterpene extracted as a major component from different species of brown algae within the genus Dictyota. There have been no previous reports on the pharmacological activity of APHD. The present research aims to explore the potential neuroprotective properties of APHD and its underlying mechanisms. METHODS: The possible mechanism of APHD was predicted using a combination of molecular docking and network pharmacological analysis. PC12 cells were induced by H2O2 and oxygen-glucose deprivation/reoxygenation (OGD/R), respectively. Western blot, flow cytometry, immunofluorescence staining, and qRT-PCR were used to investigate the antioxidant activity of APHD. The HO-1 inhibitor ZnPP and Nrf2 gene silencing were employed to confirm the influence of APHD on the signaling cascade involving HO-1, Nrf2, and Keap1 in vitro. RESULTS: APHD exhibited antioxidant activity in both PC12 cells subjected to H2O2 and OGD/R conditions by downregulating the release of LDH, the concentrations of MDA, and ROS, and upregulating SOD, GSH-Px, and GSH concentrations. APHD could potentially initiate the Keap1-Nrf2/HO-1 signaling cascade, according to the findings from network pharmacology evaluation and molecular docking. Furthermore, APHD was observed to increase Nrf2 and HO-1 expression at both mRNA and protein levels, while downregulating the protein concentrations of Keap1. Both Nrf2 silencing and treatment with ZnPP reversed the neuroprotective effects of APHD. CONCLUSIONS: APHD activated antioxidant enzymes and downregulated the levels of LDH, MDA, and ROS in two cell models. The neuroprotective effect is presumably reliant on upregulation of the Keap1-Nrf2/HO-1 pathway. Taken together, APHD from brown algae of the genus Dictyota shows potential as a candidate for novel neuroprotective agents.

Improving the properties of whey protein isolate-zein nanogels with novel acidifiers: Re-dispersity, stability and quercetin bioavailability.

Low bioavailability of quercetin (Que) reduces its preclinical and clinical benefits. In order to improve Que bioavailability, a novel whey protein isolate (WPI)-zein nanogel was prepared by pH-driven self-assembly and heat-induced gelatinization. The results showed that hydrochloric acid can be substituted by both acetic acid and citric acid during the pH-driven process. After encapsulation, the bioavailability of Que in nanogels (composed of 70 % WPI) induced by different acidifiers increased to 19.89 % (citric acid), 21.65 % (hydrochloric acid) and 24.34 % (acetic acid), respectively. Comparatively, nanogels induced by acetic acid showed higher stability (pH and storage stability), re-dispersibility (75.62 %), Que bioavailability (24.34 %), and antioxidant capacity (36.78 % for DPPH scavenging rates). s improved performance of nanogels. In mechanism, acetic acid significantly balanced different intermolecular forces by weakening "acid-induced denaturation" effect. Moreover, the faster binding of Que and protein as well as higher protein molecular flexibility and randomness (higher ratio of random coil) was also observed in nanogels induced by acetic acid. All of these changes contributed to improve nanogels performances. Overall, WPI-zein nanogels induced by acetic acid might be a safe, efficiency and stable delivery system to improve the bioavailability of hydrophobic active ingredients.

Two-Stage Micropyramids Enhanced Flexible Piezoresistive Sensor for Health Monitoring and Human-Computer Interaction.

High-performance flexible piezoresistive sensors are becoming increasingly essential in various novel applications such as health monitoring, soft robotics, and human-computer interaction. The evolution of the interfacial contact morphology determines the sensing properties of piezoresistive devices. The introduction of microstructures enriches the interfacial contact morphology and effectively boosts the sensitivity; however, the limited compressibility of conventional microstructures leads to rapid saturation of the sensitivity in the low-pressure range, which hinders their application. Herein, we present a flexible piezoresistive sensor featuring a two-stage micropyramid array structure, which effectively enhances the sensitivity while widening the sensing range. Owing to the synergistic enhancement effect resulting from the sequential contact of micropyramids of various heights, the devices demonstrate remarkable performance, including boosting sensitivity (30.8 kPa-1) over a wide sensing range (up to 200 kPa), a fast response/recovery time (75/50 ms), and an ultralong durability of 15,000 loading-unloading cycles. As a proof of concept, the sensor is applied to detect human physiological and motion signals, further demonstrating a real-time spatial pressure distribution sensing system and a game control system, showing great potential for applications in health monitoring and human-computer interaction.

Multifocal fluorescence video-rate imaging of centimetre-wide arbitrarily shaped brain surfaces at micrometric resolution.

Fluorescence microscopy allows for the high-throughput imaging of cellular activity across brain areas in mammals. However, capturing rapid cellular dynamics across the curved cortical surface is challenging, owing to trade-offs in image resolution, speed, field of view and depth of field. Here we report a technique for wide-field fluorescence imaging that leverages selective illumination and the integration of focal areas at different depths via a spinning disc with varying thickness to enable video-rate imaging of previously reconstructed centimetre-scale arbitrarily shaped surfaces at micrometre-scale resolution and at a depth of field of millimetres. By implementing the technique in a microscope capable of acquiring images at 1.68 billion pixels per second and resolving 16.8 billion voxels per second, we recorded neural activities and the trajectories of neutrophils in real time on curved cortical surfaces in live mice. The technique can be integrated into many microscopes and macroscopes, in both reflective and fluorescence modes, for the study of multiscale cellular interactions on arbitrarily shaped surfaces.

Bio-friendly long-term subcellular dynamic recording by self-supervised image enhancement microscopy.

Fluorescence microscopy has become an indispensable tool for revealing the dynamic regulation of cells and organelles. However, stochastic noise inherently restricts optical interrogation quality and exacerbates observation fidelity when balancing the joint demands of high frame rate, long-term recording and low phototoxicity. Here we propose DeepSeMi, a self-supervised-learning-based denoising framework capable of increasing signal-to-noise ratio by over 12 dB across various conditions. With the introduction of newly designed eccentric blind-spot convolution filters, DeepSeMi effectively denoises images with no loss of spatiotemporal resolution. In combination with confocal microscopy, DeepSeMi allows for recording organelle interactions in four colors at high frame rates across tens of thousands of frames, monitoring migrasomes and retractosomes over a half day, and imaging ultra-phototoxicity-sensitive Dictyostelium cells over thousands of frames. Through comprehensive validations across various samples and instruments, we prove DeepSeMi to be a versatile and biocompatible tool for breaking the shot-noise limit.

Association of immune checkpoint inhibitors therapy with arterial thromboembolic events in cancer patients: A retrospective cohort study.

BACKGROUND: Immune checkpoint inhibitors (ICIs) have emerged as a standard treatment for various malignancies. However, research indicates blocking the immune checkpoint pathway may exacerbate atherosclerotic lesions. OBJECTIVES: We aimed to investigate whether ICI therapy increases the risk of arterial thromboembolic events (ATEs). METHODS: A retrospective cohort study was conducted on patients with histologically confirmed cancer at our institution between 2018 and 2021, using the propensity score matching method. The primary endpoint was ATEs occurrence, comprising acute coronary syndrome, stroke/transient ischemic attack, and peripheral arterial thromboembolism. Subgroup analyses assessed whether the ICI treatment effect on ATEs varied over time by limiting the maximum follow-up duration. Logistic regression analysis identified ATE risk factors in ICI-treated patients. RESULTS: Overall, the ICI group (n = 2877) demonstrated an ATEs risk 2.01 times higher than the non-ICI group (RR, 2.01 [95% CI (1.61-2.51)]; p < 0.001). Subgroup analysis revealed no significant increase in ATEs risk for ICI-treated patients within 1 year (Limited to a max 9-month follow-up, p = 0.075). However, ATEs risk in the ICI group rose by 41% at 1 year (p = 0.010) and 97% at 4 years (p ≤ 0.001). Age, diabetes, hypertension, peripheral atherosclerosis, atrial fibrillation, chronic ischemic heart disease, distant cancer metastasis, and ICI treatment cycles contributed to ATEs risk elevation in ICI-treated patients. CONCLUSION: ICI-treated patients may exhibit a higher risk of ATEs, especially after 1 year of treatment.

Large depth-of-field ultra-compact microscope by progressive optimization and deep learning.

The optical microscope is customarily an instrument of substantial size and expense but limited performance. Here we report an integrated microscope that achieves optical performance beyond a commercial microscope with a 5×, NA 0.1 objective but only at 0.15 cm3 and 0.5 g, whose size is five orders of magnitude smaller than that of a conventional microscope. To achieve this, a progressive optimization pipeline is proposed which systematically optimizes both aspherical lenses and diffractive optical elements with over 30 times memory reduction compared to the end-to-end optimization. By designing a simulation-supervision deep neural network for spatially varying deconvolution during optical design, we accomplish over 10 times improvement in the depth-of-field compared to traditional microscopes with great generalization in a wide variety of samples. To show the unique advantages, the integrated microscope is equipped in a cell phone without any accessories for the application of portable diagnostics. We believe our method provides a new framework for the design of miniaturized high-performance imaging systems by integrating aspherical optics, computational optics, and deep learning.

Miniaturized Flexible Non-Contact Interface Based on Heat Shrinkage Technology.

High-performance miniaturized flexible sensors are becoming increasingly important in wearable electronics. However, miniaturization of devices often requires high-precision manufacturing processes and equipment, which limits the commercialization of flexible sensors. Therefore, revolutionary technologies for manufacturing miniaturized flexible sensors are highly desired. In this work, a new method for manufacturing miniaturized flexible humidity sensor by utilizing heat shrinkage technology is presented. This method successfully achieves much smaller sensor and denser interdigital electrode. Utilizing this method, a miniaturized flexible humidity sensor and array are presented, fabricated by anchoring nano-Al2 O3 into carbon nano-tube as the humidity sensitive film. This heat shrinkage technology, forming wrinkle structure on the humidity sensitive film, endows the sensor with a high sensitivity over 200% (ΔR/R0 ) at humidity levels ranging from 0 to 90%RH and a fast recovery time (0.5 s). The sensor allows non-contact monitoring human respiration and alerting in case of an asthma attack and the sensor array can be adaptively attached to the wrist as a non-contact human-machine interface to control the mechanical hand or computer. This work provides a general and effective heat shrinkage technology for the development of smaller and more efficient flexible circuits and sensor devices.

Wrinkle Clamp Down on Structure Crack Strain Sensor Based on High Poisson's Ratio Material for Home Health Monitoring and Human-Machine Interaction.

Flexible wearable crack strain sensors are currently receiving significant attention because they can be used in a wide range of physiological signal monitoring and human-machine interaction applications. However, sensors with high sensitivity, great repeatability, and wide sensing range remain challenging. Herein, a tunable wrinkle clamp down structure (WCDS) crack strain sensor based on high Poisson's ratio material with high sensitivity, high stability, and wide strain range is proposed. Based on the high Poisson's ratio of the acrylic acid film, the WCDS was prepared by a prestretching process. The wrinkle structures can clamp down the crack to improve the cyclic stability of the crack strain sensor while maintaining its high sensitivity. Moreover, the tensile properties of the crack strain sensor are improved by introducing wrinkles in the bridge-like gold stripes connecting each separated gold flake. Owing to this structure, the sensitivity of the sensor can reach 3627, stable operation over 10 000 cycles is achieved, and the strain range can reach about 9%. In addition, the sensor exhibits low dynamic response and good frequency characteristics. Because of its demonstrated excellent performance, the strain sensor can be used in pulse wave and heart rate monitoring, as well as posture recognition and game control.

A highly adaptive real-time water wave sensing array for marine applications.

The ocean accounts for about 70% of the Earth's surface area. In recent years, there has been increasing research into large-scale power generation device networks for ocean energy and the number of mobile sensing nodes in the ocean is expected to increase with the operation of the Internet of Things (IoT). Since water waves are low-frequency intermittent energy, they are suitable for harvesting and sensing by a triboelectric nanogenerator (TENG) with high conversion efficiency, flexible structural design, and environmental friendliness. Furthermore, TENG-units are suitable for large-scale water waves. We proposed a 6 × 4 cross-vertical double-layer electrode array device to sense and restore the water wave state. The design of this structure can refine the waveform display while reducing the electrode interfaces and achieving efficient and accurate sensing of the water wave. Then we developed a complete display system combined with the device and demonstrated the superior performance of each unit and the whole array both on a curved surface and underwater. It can be expected that the device and the system will have great potential in maritime applications.

Flexible Triboelectric Tactile Sensor Based on a Robust MXene/Leather Film for Human-Machine Interaction.

With the rapid development of Internet of Things (IoT) technology in recent years, self-actuated sensor systems without an external power supply such as flexible triboelectric nanogenerator (TENG)-based strain sensors have received wide attention due to their simple structure and self-powered active sensing properties. However, to satisfy the practical applications of human wearable biointegration, flexible TENGs impose higher requirements for establishing a balance between material flexibility and good electrical properties. In this work, the strength of the MXene/substrate interface was greatly improved by utilizing leather with a unique surface structure as the substrate material, resulting in a mechanically strong and electrically conductive MXene film. Due to the natural fiber structure of the leather surface, the surface of the MXene film with a rough structure was obtained, which improved the electrical output performance of the TENG. The electrode output voltage of MXene film on leather based on single-electrode TENG can reach 199.56 V and the maximum output power density can reach 0.469 mW/cm2. Combined with laser-assisted technology, the efficient array preparation of MXene and graphene was achieved and applied to various human-machine interface (HMI) applications.

Mesoscale volumetric light field (MesoLF) imaging of neuroactivity across cortical areas at 18 Hz.

Various implementations of mesoscopes provide optical access for calcium imaging across multi-millimeter fields-of-view (FOV) in the mammalian brain. However, capturing the activity of the neuronal population within such FOVs near-simultaneously and in a volumetric fashion has remained challenging since approaches for imaging scattering brain tissues typically are based on sequential acquisition. Here, we present a modular, mesoscale light field (MesoLF) imaging hardware and software solution that allows recording from thousands of neurons within volumes of 4000 × 200 µm, located at up to 400 µm depth in the mouse cortex, at 18 volumes per second. Our optical design and computational approach enable up to hour-long recording of ~10,000 neurons across multiple cortical areas in mice using workstation-grade computing resources.

Rapid detection of neurons in widefield calcium imaging datasets after training with synthetic data.

Widefield microscopy can provide optical access to multi-millimeter fields of view and thousands of neurons in mammalian brains at video rate. However, tissue scattering and background contamination results in signal deterioration, making the extraction of neuronal activity challenging, laborious and time consuming. Here we present our deep-learning-based widefield neuron finder (DeepWonder), which is trained by simulated functional recordings and effectively works on experimental data to achieve high-fidelity neuronal extraction. Equipped with systematic background contribution priors, DeepWonder conducts neuronal inference with an order-of-magnitude-faster speed and improved accuracy compared with alternative approaches. DeepWonder removes background contaminations and is computationally efficient. Specifically, DeepWonder accomplishes 50-fold signal-to-background ratio enhancement when processing terabytes-scale cortex-wide functional recordings, with over 14,000 neurons extracted in 17 h.

Mesoscale volumetric light-field (MesoLF) imaging of neuroactivity across cortical areas at 18 Hz.

Various implementations of mesoscopes provide optical access for calcium imaging across multi-millimeter fields of view in the mammalian brain; however, capturing the activity of the neuronal population within such fields of view near-simultaneously and in a volumetric fashion has remained challenging as approaches for imaging scattering brain tissues typically are based on sequential acquisition. Here we present a modular, mesoscale light-field (MesoLF) imaging hardware and software solution that allows recording from thousands of neurons within volumes of ⌀ 4 × 0.2 mm, located at up to 350 µm depth in the mouse cortex, at 18 volumes per second and an effective voxel rate of ~40 megavoxels per second. Using our optical design and computational approach we show recording of ~10,000 neurons across multiple cortical areas in mice using workstation-grade computing resources.

Optimal Timing of Cranioplasty and Predictors of Overall Complications After Cranioplasty: The Impact of Brain Collapse.

BACKGROUND: The optimal timing of cranioplasty (CP) and predictors of overall postoperative complications are still controversial. OBJECTIVE: To determine the optimal timing of CP. METHODS: Patients were divided into collapsed group and noncollapsed group based on brain collapse or not, respectively. Brain collapse volume was calculated in a 3-dimensional way. The primary outcomes were overall complications and outcomes at the 12-month follow-up after CP. RESULTS: Of the 102 patients in this retrospective observation cohort study, 56 were in the collapsed group, and 46 were in the noncollapsed group. Complications were noted in 30.4% (n = 31), 24 (42.9%) patients in the collapsed group and 7 (15.2%) patients in the noncollapsed group, with a significant difference ( P = .003). Thirty-three (58.9%) patients had good outcomes (modified Rankin Scale 0-3) in the collapsed group, and 34 (73.9%) patients had good outcomes in the noncollapsed group without a statistically significant difference ( P = .113). Brain collapse ( P = .005) and Karnofsky Performance Status score at the time of CP ( P = .025) were significantly associated with overall postoperative complications. The cut-off value for brain collapse volume was determined as 11.26 cm 3 in the receiver operating characteristic curve. The DC-CP interval was not related to brain collapse volume or postoperative complications. CONCLUSION: Brain collapse and lower Karnofsky Performance Status score at the time of CP were independent predictors of overall complications after CP. The optimal timing of CP may be determined by tissue window based on brain collapse volume instead of time window based on the decompressive craniectomy-CP interval.

Significance of Preoperative Nerve Reconstruction Using Diffusion Tensor Imaging Tractography for Facial Nerve Protection in Vestibular Schwannoma.

OBJECTIVE: The facial nerve trace on the ipsilateral side of the vestibular schwannoma was reconstructed by diffusion tensor imaging tractography to identify the adjacent relationship between the facial nerve and the tumor, and to improve the level of intraoperative facial nerve protection. METHODS: The clinical data of 30 cases of unilateral vestibular schwannoma who underwent tumor resection via retrosigmoid approach were collected between January 2019 and December 2020. All cases underwent magnetic resonance imaging examination before operation. Diffusion tensor imaging and anatomical images were used to reconstruct the facial nerve track of the affected side, so as to predict the course of the nerve and its adjacent relationship with the tumor, to compare the actual trace of the facial nerve during operation, verify the degree of coincidence, and evaluate the nerve function (House-Brackmann grade) after surgery. RESULTS: The facial nerve of 27 out of 30 cases could be displayed by diffusion tensor imaging tractography, and the tracking rate was 90% (27/30). The intraoperative locations of facial nerve shown in 25 cases were consistent with the preoperative reconstruction results. The coincidence rate was 92.6% (25/27). The facial nerves were located on the anterior middle part of the tumor in 14 cases, anterior upper part in eight cases, anterior lower part in seven cases, and superior polar in one case. Intraoperative facial nerve anatomy was preserved in 30 cases. Among the 30 patients, total resection was performed in 28 cases and subtotal resection in two cases. The facial nerve function was evaluated 2 weeks after operation, and the results showed grade I in 12 cases, grade II in 16 cases and grade III in two cases. CONCLUSION: Preoperative diffusion tensor imaging tractography can clearly show the trajectory and adjacent position of the facial nerve on the side of vestibular schwannoma, which is beneficial to accurately identify and effectively protect the facial nerve during the operation, and is worthy of clinical application and promotion.

Real-time denoising enables high-sensitivity fluorescence time-lapse imaging beyond the shot-noise limit.

A fundamental challenge in fluorescence microscopy is the photon shot noise arising from the inevitable stochasticity of photon detection. Noise increases measurement uncertainty and limits imaging resolution, speed and sensitivity. To achieve high-sensitivity fluorescence imaging beyond the shot-noise limit, we present DeepCAD-RT, a self-supervised deep learning method for real-time noise suppression. Based on our previous framework DeepCAD, we reduced the number of network parameters by 94%, memory consumption by 27-fold and processing time by a factor of 20, allowing real-time processing on a two-photon microscope. A high imaging signal-to-noise ratio can be acquired with tenfold fewer photons than in standard imaging approaches. We demonstrate the utility of DeepCAD-RT in a series of photon-limited experiments, including in vivo calcium imaging of mice, zebrafish larva and fruit flies, recording of three-dimensional (3D) migration of neutrophils after acute brain injury and imaging of 3D dynamics of cortical ATP release. DeepCAD-RT will facilitate the morphological and functional interrogation of biological dynamics with a minimal photon budget.