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Background Diabetic retinopathy (DR) produces bleeding, exudation, and new blood vessel formation conditions. DR can damage the retinal blood vessels and cause vision loss or even blindness. If DR is detected early, ophthalmologists can use lasers to create tiny burns around the retinal tears to inhibit bleeding and prevent the formation of new blood vessels, in order to prevent deterioration of the disease. The rapid improvement of deep learning has made image recognition an effective technology; it can avoid misjudgments caused by different doctors’ evaluations and help doctors to predict the condition quickly. The aim of this paper is to adopt visualization and preprocessing in the ResNet-50 model to improve module calibration, to enable the model to predict DR accurately. Results This study compared the performance of the proposed method with other common CNNs models (Xception, AlexNet, VggNet-s, VggNet-16 and ResNet-50). In examining said models, the results alluded to an over-fitting phenomenon, and the outcome of the work demonstrates that the performance of the revised ResNet-50 (Train accuracy: 0.8395 and Test accuracy: 0.7432) is better than other common CNNs (that is, the revised structure of ResNet-50 could avoid the overfitting problem, decease the loss value, and reduce the fluctuation problem). Conclusions This study proposed two approaches to designing the DR grading system: a standard operation procedure (SOP) for preprocessing the fundus image, and a revised structure of ResNet-50, including an adaptive learning rating to adjust the weight of layers, regularization and change the structure of ResNet-50, which was selected for its suitable features. It is worth noting that the purpose of this study was not to design the most accurate DR screening network, but to demonstrate the effect of the SOP of DR and the visualization of the revised ResNet-50 model. The results provided an insight to revise the structure of CNNs using the visualization tool.

Chronic non-healing wounds have become a major worldwide healthcare burden. The impact of biofilms on chronic wound infection is well established. Despite increasing understanding of the underlying mechanism of biofilm formation in chronic wounds, current strategies for biofilm diagnosis in chronic wounds are still far from ideal. In this review, we briefly summarize the mechanism of biofilm formation and focus on current diagnostic approaches of chronic wound biofilms based on morphology, microbiology, and molecular assays. Innovative biotechnological approaches, such as wound blotting and transcriptomic analysis, may further shed light on this unmet clinical need. The continuous development of these sophisticated diagnostic approaches can markedly contribute to the future implementation of point-of-care biofilm detection in chronic wound care. The impact of biofilms on delayed wound healing has drawn increasing attention. Their importance led to the establishment of biofilm-based wound care where chronic wounds are treated using multipronged strategies to remove biofilms over wound beds to facilitate the recovery of epithelial integrity. Current clinical and preclinical diagnostic techniques fail to accurately identify pathogens and the precise location of biofilms over wound surfaces, rendering timely medical or surgical intervention to eradicate biofilms elusive. Wound blotting is a novel biotechnology that predicts wound outcomes and localizes biofilms on wound surfaces by determining the distribution pattern of tumor necrosis factor-alpha (TNF-α) and biofilm mucopolysaccharides. The rapid and objective analysis offered by this technique may assist clinicians in treating chronic wound biofilms.

Although the taxonomic composition of the human microbiome varies tremendously across individuals, its gene composition or functional capacity is highly conserved — implying an ecological property known as functional redundancy. Such functional redundancy has been hypothesized to underlie the stability and resilience of the human microbiome, but this hypothesis has never been quantitatively tested. The origin of functional redundancy is still elusive. Here, we investigate the basis for functional redundancy in the human microbiome by analyzing its genomic content network — a bipartite graph that links microbes to the genes in their genomes. We find that this network exhibits several topological features that favor high functional redundancy. Furthermore, we develop a simple genome evolution model to generate genomic content network, finding that moderate selection pressure and high horizontal gene transfer rate are necessary to generate genomic content networks with key topological features that favor high functional redundancy. Finally, we analyze data from two published studies of fecal microbiota transplantation (FMT), finding that high functional redundancy of the recipient’s pre-FMT microbiota raises barriers to donor microbiota engraftment. This work elucidates the potential ecological and evolutionary processes that create and maintain functional redundancy in the human microbiome and contribute to its resilience. Here, the authors develop a genome evolution model to investigate the origin of functional redundancy in the human microbiome by analyzing its genomic content network and illustrate potential ecological and evolutionary processes that may contribute to its resilience.

The Poly( N -isopropylacrylamide) (PNIPAm) hydrogel has gained significant interest in the realms of tissue engineering and regenerative medicine due to its biocompatible characteristics and ability to replicate the properties of the natural extracellular matrix (ECM). The given environment possesses three-dimensional attributes that facilitate the proliferation and specialization of cells, making it suitable for the use of tissue engineering applications. The temperature-responsive nature of PNIPAm hydrogel enables it to encapsulate and release therapeutic ingredients in response to temperature fluctuations. This characteristic exhibits potential for the advancement of drug administration systems in regenerative medicine. PNIPAm hydrogel exhibits thermoresponsive properties that make it very suitable for applications in biofabrication techniques, such as 3D printing, and for replicating intricate tissue structures. Moreover, it shows significant potential in stem cell engineering by establishing a favorable setting that promotes cell growth and specialization. The material has the potential to be used as a scaffold for tissue regeneration, allowing its porosity structure and mechanical properties to be customized to meet various tissue needs. Researchers are currently studying the integration of bioactive compounds into PNIPAm hydrogel scaffolds to enhance tissue regeneration and cellular responses. This review provides a comprehensive overview of the uses of PNIPAm in tissue engineering, specifically highlighting its strengths in additive manufacturing.

NLRP3 inflammasomes- pyroptosis axis is activated by microcirculation dysfunction and touched off severe acute pancreatitis (SAP). Activation of PGC-1α can improve microcirculation dysfunction by promoting mitochondrial biogenesis. Resveratrol (RSV), one typical SIRT1 agonist, possesses the ability of alleviating SAP and activing PGC-1α. Therefore, the study was designated to explore whether the protective effect of RSV in SAP was though suppressing NLRP3 inflammasomes- pyroptosis axis via advancing SIRT1/PGC-1α-dependent mitochondrial biogenesis. The models of SAP were induced by treating with sodium taurodeoxycholate in rats and AR42J cells. The pathological injury, water content (dry/wet ratio) and microcirculation function of pancreas, activity of lipase and amylase were used to evaluate pancreatic damage. The expression of inflammatory cytokine was measured by ELISA and RT-PCR. The damage of mitochondrial was evaluated by measuring the changes in Mitochondrial Membrane Potential (ΔΨm), mitochondrial ROS, ATP content and MDA as well as relocation of mtDNA and the activity of SOD and GSH. The expressions of NLRP3 inflammasomes- pyroptosis axis proteins were detected by Western blotting as well as SIRT1/PGC-1α/NRF1/TFAM pathway protein. Moreover, the modification of PGC-1α was measured by co-immunoprecipitation. The results displayed that RSV can significantly improve the damage of pancreas and mitochondrial, decrease the expression of pro-inflammatory factor and the activation of NLRP3 inflammasomes- pyroptosis axis, promote the expression of an-inflammatory factor and the deacetylation of PGC-1α together with facilitating SIRT1/PGC-1α-mediating mitochondrial biogenesis. Therefore, the protective effect of RSV in SAP is though inactivation of NLRP3 inflammasomes- pyroptosis axis via promoting mitochondrial biogenesis in a SIRT1/PGC-1α-dependent manner.

Herein, we report the preparation of AgVO3 nanoparticles-decorated multi-shelled ZnO microspheres 0D/3D Z-scheme heterojunction photocatalysts via calcination of carbon sphere template and in situ growth method. The prepared ZnO/AgVO3 composites showed enhanced photocatalytic performance for photodegradation of ciprofloxacin (CIP) and photocatalytic reduction of Cr(VI) compared to the single-phase photocatalysts under the same irradiation conditions. Noticeably, the photocatalytic removal rate of CIP and Cr(VI) reached 90% at 90 min and 45 min, respectively, for the ZnO/AgVO3 composite with an optimal AgVO3 content. The photocatalytic removal rate for CIP and Cr(VI) was, respectively, about 2.43-fold and 4.84-fold as high as that of the pure ZnO. Furthermore, a reasonable degradation pathway for CIP has been proposed based on LC–MS results. The enhanced photocatalytic performance could be attributed to the extended visible-light absorption, promoted separation and transportation efficiency of the photogenerated electron–hole pairs. Significantly, the Z-scheme heterojunction was verified according to radical capture experiments and theoretical calculations based on the density functional theory (DTF) framework. We believe this work will give an innovative view for constructing multi-shelled 0D/3D photocatalytic systems for eliminating environmental pollutants and enhancing environmental remediation.

Synthetic aperture radar (SAR) enables precise object localization and imaging, which has propelled the rapid development of algorithms for maritime ship identification and detection. However, most current deep learning-based algorithms tend to increase network depth to improve detection accuracy, which may result in the loss of effective features of the target. In response to this challenge, this paper innovatively proposes an object-enhanced network, OE-YOLO, designed specifically for SAR ship detection. Firstly, we input the original image into an improved CFAR detector, which enhances the network’s ability to localize and perform object extraction by providing more information through an additional channel. Additionally, the Coordinate Attention mechanism (CA) is introduced into the backbone of YOLOv7-tiny to improve the model’s ability to capture spatial and positional information in the image, thereby alleviating the problem of losing the position of small objects. Furthermore, to enhance the model’s detection capability for multi-scale objects, we optimize the neck part of the original model to integrate the Asymptotic Feature Fusion (AFF) network. Finally, the proposed network model is thoroughly tested and evaluated using publicly available SAR image datasets, including the SAR-Ship-Dataset and HRSID dataset. In comparison to the baseline method YOLOv7-tiny, OE-YOLO exhibits superior performance with a lower parameter count. When compared with other commonly used deep learning-based detection methods, OE-YOLO demonstrates optimal performance and more accurate detection results.

For rice as an agricultural crop, more tillers, or branches that carry grains, are desired, as is less demand for nitrogen fertilization. Unfortunately, for many rice varieties, the number of tillers depends on the amount of nitrogen fertilization. Wu et al. now show that nitrogen status affects chromatin function through modification of histones, a process in which the transcription factor NGR5 recruits polycomb repressive complex 2 to target genes. Some of these genes regulate tillering, such that with more nitrogen, the plants develop more tillers. NGR5 is regulated by proteasomal destruction and mediates hormone signaling. An increase in NGR5 levels can drive increases in rice tillering and yield without requiring increases in nitrogen-rich fertilizer. Science , this issue p. eaaz2046 Nitrogen fertilization of rice drives chromatin modifications that regulate expression of genes influencing plant shape and yield. Because environmentally degrading inorganic fertilizer use underlies current worldwide cereal yields, future agricultural sustainability demands enhanced nitrogen use efficiency. We found that genome-wide promotion of histone H3 lysine 27 trimethylation (H3K27me3) enables nitrogen-induced stimulation of rice tillering: APETALA2-domain transcription factor NGR5 (NITROGEN-MEDIATED TILLER GROWTH RESPONSE 5) facilitates nitrogen-dependent recruitment of polycomb repressive complex 2 to repress branching-inhibitory genes via H3K27me3 modification. NGR5 is a target of gibberellin receptor GIBBERELLIN INSENSITIVE DWARF1 (GID1)–promoted proteasomal destruction. DELLA proteins (characterized by the presence of a conserved aspartate-glutamate-leucine-leucine-alanine motif) competitively inhibit the GID1-NGR5 interaction and explain increased tillering of green revolution varieties. Increased NGR5 activity consequently uncouples tillering from nitrogen regulation, boosting rice yield at low nitrogen fertilization levels. NGR5 thus enables enhanced nitrogen use efficiency for improved future agricultural sustainability and food security.

The beating heart possesses the intrinsic ability to adapt cardiac output to changes in mechanical load. The century-old Frank–Starling law and Anrep effect have documented that stretching the heart during diastolic filling increases its contractile force. However, the molecular mechanotransduction mechanism and its impact on cardiac health and disease remain elusive. Here we show that the mechanically activated Piezo1 channel converts mechanical stretch of cardiomyocytes into Ca 2+ and reactive oxygen species (ROS) signaling, which critically determines the mechanical activity of the heart. Either cardiac-specific knockout or overexpression of Piezo1 in mice results in defective Ca 2+ and ROS signaling and the development of cardiomyopathy, demonstrating a homeostatic role of Piezo1. Piezo1 is pathologically upregulated in both mouse and human diseased hearts via an autonomic response of cardiomyocytes. Thus, Piezo1 serves as a key cardiac mechanotransducer for initiating mechano-chemo transduction and consequently maintaining normal heart function, and might represent a novel therapeutic target for treating human heart diseases. The beating heart adapts cardiac output to changes in mechanical load via incompletely understood mechanotransduction mechanisms. Here the authors show that the mechanosensitive Piezo1 channel serves as a mechanotransducer for directly converting mechanical stretch of cardiomyocytes into Ca 2+ and ROS signaling and consequently maintaining normal heart function.

The transport of ordinary fluids tends to be driven by pressure differentials, whereas for active or biological matter, transport may be isotropic or governed by the presence of specific chemical gradients. Wu et al. analyzed the emergence of spontaneous directional flows in active fluids containing a suspension of microtubules and clusters of the molecular motor kinesin, confined in a variety of microfluidic geometries (see the Perspective by Morozov). When confined in periodic toroidal channels and cylindrical domains, the flow was organized and persisted in a unidirectional motion, either clockwise or counterclockwise. Oddly, this behavior was independent of scale; as long as the aspect ratio of the geometry was chosen appropriately, flows were observed for a wide range of system dimensions. Science , this issue p. eaal1979 ; see also p. 1262 An isotropic fluid composed of nanosized motors organizes into an autonomous machine that pumps fluid through long channels. Transport of fluid through a pipe is essential for the operation of macroscale machines and microfluidic devices. Conventional fluids only flow in response to external pressure. We demonstrate that an active isotropic fluid, composed of microtubules and molecular motors, autonomously flows through meter-long three-dimensional channels. We establish control over the magnitude, velocity profile, and direction of the self-organized flows and correlate these to the structure of the extensile microtubule bundles. The inherently three-dimensional transition from bulk-turbulent to confined-coherent flows occurs concomitantly with a transition in the bundle orientational order near the surface and is controlled by a scale-invariant criterion related to the channel profile. The nonequilibrium transition of confined isotropic active fluids can be used to engineer self-organized soft machines.