Accurate visualization and 3-dimensional (3D) morphological profiling of small model organisms can provide quantitative phenotypes benefiting genetic analysis and modeling of human diseases in tractable organisms. However, in the highly studied nematode Caenorhabditis elegans, accurate morphological phenotyping remains challenging because of notable decrease in image resolution of distant signal under high magnification and complexity in the 3D reconstruction of microscale samples with irregular shapes. Here, we develop a robust robotic system that enables the contactless, stable, and uniform rotation of C. elegans for multi-view fluorescent imaging and 3D morphological phenotyping via the precise reconstruction of 3D models. Contactless animal rotation accommodates a variety of body shapes and sizes found at different developmental stages and in mutant strains. Through controlled rotation, high-resolution fluorescent imaging of C. elegans structures is obtained by overcoming the limitations inherent in both widefield and confocal microscopy. Combining our robotic system with machine learning, we create, for the first time, precise 3D reconstructions of C. elegans at the embryonic and adult stages, enabling 3D morphological phenotyping of mutant strains in an accurate and comprehensive fashion. Intriguingly, our morphological phenotyping discovered a genetic interaction between 2 RNA binding proteins (UNC-75/CELF and MBL-1/MBNL), which are highly conserved between C. elegans and humans and implicated in neurological and muscular disorders. Our system can thus generate quantitative morphological readouts facilitating the investigation of genetic variations and disease mechanisms. More broadly, our method will also be amenable for 3D phenotypic analysis of other biological samples, like zebrafish and Drosophila larvae.

Intervening in the microbial environment holds promise for enhancing antitumor efficacy by reshaping the tumor microenvironment, yet few strategies have been reported. In a study led by Zou and coworkers, oral hydrogels are introduced to regulate the microbiota balance in the intestines and tumors, triggering an antitumor immune response. This work presents a microbiota-targeted drug delivery system that demonstrates notable efficacy in colon targeting and colon retention for the treatment of colorectal cancer. This represents a significant clinical advancement in treating colorectal cancer, which is particularly vulnerable to microbial infiltration.

Hydrogel microparticles have been proved to be curative to diabetic wounds. Current trends focus on the integration of bioactive matrix and their smart stimulus-responsive release to meet the complex demand of regeneration in diabetic wound. In this paper, we present novel stem cell exosome-encapsulated Chinese herb glycyrrhizic acid (GA) hydrogel microparticles for wound healing. The integrated GA endows the hydrogel microparticles with antibacterial properties, while the encapsulated exosomes impart them with pro-angiogenesis ability. In addition, as the black phosphorus is incorporated into these hybrid hydrogel microparticles, the release profile of GA and exosomes could be controllable under near-infrared irradiation due to the excellent photothermal effect of black phosphorus and the reversible phase transformation properties of GA. Based on these features, we have demonstrated that these microparticles can effectively kill bacteria, scavenge free radical, and promote angiogenesis from in vitro experiments. Besides, they could also markedly accelerate the wound healing process by down-regulating inflammation and promoting collagen deposition and angiogenesis in bacteria-infected in vivo diabetic wound. These results indicate that the proposed exosome-integrated GA hydrogel microparticles present great potential for clinical diabetic wound treatment.

Psychedelics have long been recognized not only for their profound impact on human consciousness but also for their potential therapeutic applications. This perspective explores the multifaceted relationship between psychedelics and consciousness, emphasizing their capacity to alter sensory perceptions, disrupt self-referential thought processes, and catalyze profound spiritual and existential experiences. As research advances, psychedelics are being integrated into therapeutic settings, challenging existing psychiatric models and offering new insights into the complex nature of consciousness and mental health. This emerging paradigm marks the need for careful regulation and ethical considerations in the therapeutic use of psychedelics, promising a more holistic approach to mental health disorders.

Ion selectivity is a fundamental feature for designing advanced nanopores/channel systems, for example, biosensors or selectively permeable membranes. Comparison between different studies is a way to find and design the nanopore/membrane with pronounced selectivity. However, there is a huge hurdle in comparing the ion selectivities between studies, resulting from different equations from diverse scopes of science. Here, the authors from “Addressing challenges in ion-selectivity characterization in nanopores” emphasized the misinterpretation of the traditionally used Nernst and Goldman–Hodgkin–Katz equations in the previous literature and suggested the use of uniform criteria to overcome this ambiguity. We highlight the potential future applications of using uniform criteria in describing ion selectivity, which is beneficial to developing a massive AI-based databank. This databank would be advantageous for predicting and designing the ion selectivity of nanopores/nanomaterials in question for various applications in biological and material sciences.

Impedance metasurfaces enable accurate regulation of acoustic fields. However, they can hardly supply a flexible response as such perfect operation is accompanied by stringent requirements on the design of unit cells. Actually, an arbitrary lossless and passive target impedance matrix requires the tuning of 3 independent real parameters. The set composed of a reflection phase, a transmission amplitude, and a transmission phase, enables the representation of an arbitrary impedance matrix, possibly possessing singular elements. In this paper, a mechanism of phase-amplitude-phase modulation (PAP modulation) is developed for the generic design of the unit cells of acoustic impedance metasurfaces. Adjustable acoustic impedance metasurfaces are further available under this framework. An impedance unit with 3 mobile parts is designed based on this idea. The assembled metasurface can handle different incidences for acoustic field manipulation at a given frequency. Beam steering and beam splitting are considered as demonstration examples and are verified by numerical simulation and experiment. PAP modulation enriches the design of acoustic impedance metasurfaces and extends the range of application of impedance theory.

Precise and timely detection of a crop's nutrient requirement will play a crucial role in assuring optimum plant growth and crop yield. The present study introduces a reliable deep learning platform called “Deep Learning-Crop Platform” (DL-CRoP) for the identification of some commercially grown plants and their nutrient requirements using leaf, stem, and root images using a convolutional neural network (CNN). It extracts intrinsic feature patterns through hierarchical mapping and provides remarkable outcomes in identification tasks. The DL-CRoP platform is trained on the plant image dataset, namely, Jammu University-Botany Image Database (JU-BID), available at https://github.com/urfanbutt. The findings demonstrate implementation of DL-CRoP—cases A (uses shoot images) and B (uses leaf images) for species identification for Solanum lycopersicum (tomato), Vigna radiata (Vigna), and Zea mays (maize), and cases C (uses leaf images) and D (uses root images) for diagnosis of nitrogen deficiency in maize. The platform achieved a higher rate of accuracy at 80–20, 70–30, and 60–40 splits for all the case studies, compared with established algorithms such as random forest, K-nearest neighbor, support vector machine, AdaBoost, and naïve Bayes. It provides a higher accuracy rate in classification parameters like recall, precision, and F1 score for cases A (90.45%), B (100%), and C (93.21), while a medium-level accuracy of 68.54% for case D. To further improve the accuracy of the platform in case study C, the CNN was modified including a multi-head attention (MHA) block. It resulted in the enhancement of the accuracy of classifying the nitrogen deficiency above 95%. The platform could play an important role in evaluating the health status of crop plants along with a role in precise identification of species. It may be used as a better module for precision crop cultivation under limited nutrient conditions.

Background: B-cell receptor-associated protein 31 (BCAP31) has protective effects against alveolar epithelial type II cells (AECII) damage by inhibiting mitochondrial injury in acute lung injury (ALI) induced by lipopolysaccharide (LPS), whereas the precise mechanism is still unclear. It is known that PTEN-induced putative kinase 1 (PINK1)/Parkin-mediated mitophagy can remove damaged mitochondria selectively, which may be involved in BCAP31 protection against mitochondrial injury. Methods: In the current study, ALI mice models were established by using surfactant protein C (Sftpc)-BCAP31 transgenic mice (BCAP31^TG mice) and AECII-specific BCAP31 knockout mice (BCAP31^CKO mice) treated with LPS. Results: BCAP31 expression in lung tissue and AECII were inhibited in ALI mice. Under LPS challenge, lower level of BCAP31 was found to correlate positively with pathological injury of the lung, respiratory dysfunction, mortality rates, inflammation response, and AECII damage. Further study showed that down-regulation of BCAP31 induced decreased phosphorylation of PINK1 via reduced binding to PINK1, thereby restraining PINK1/Parkin-mediated mitophagy. Down-regulation of mitophagy promoted mitochondrial injury, as shown by the increase in mitochondrial permeability transition pore opening rate, together with enhanced mitochondrial reactive oxygen species (mROS), which were accompanied by increased cellular apoptosis and reactive oxygen species (ROS). The increased cellular ROS contributed to the inflammatory response via activation of nuclear factor κB (NF-κB). In contrast, BCAP31 overexpression promoted phosphorylation of PINK1 and PINK1/Parkin-mediated mitophagy, thus blocking the mROS/ROS/NF-κB pathway, favoring a protective condition that ultimately led to the inhibition of AECII apoptosis and inflammatory response in LPS-induced ALI. Conclusion: Ultimately, BCAP31 alleviated ALI by activating PINK1/Parkin-mediated mitophagy and blocking the mROS/ROS/NF-κB pathway in AECII.

Exercise is one of the preferred management strategies for diabetic patients, but the exercise mode including type, intensity, and duration time is quite different for each patient because of individual differences. Inadequate exercise has no effect on the blood glucose control, while overexercise may cause serious side effects, such as hypoglycemia and loss of blood glucose control. In this work, we report a closed-loop feedback mode for exercise management in diabetes. A minimally invasive, biocompatible microneedle electrode patch was fabricated and used for continuously monitoring the glucose in the interstitial fluid. Further, in conjunction with using a wireless electrochemical device, the glucose signals can be analyzed to output the potency of exercise and give advice on exercise management. A custom exercise given by this closed-loop feedback mode can reduce the used dose of insulin and avoid side effect during and after exercise. We believe that this work can provide a novel comprehensive guidance for diabetic patients.