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.

Neuropathic pain (NP) represents a considerable clinical challenge, profoundly impacting patients’ quality of life. Presently, pharmacotherapy serves as a primary approach for NP alleviation, yet its efficacy often remains suboptimal. Melatonin (MLT), a biologically active compound secreted by the pineal gland, has long been associated with promoting and maintaining sleep. Although recent studies suggest analgesic effects of MLT, the underlying mechanism remains largely unknown, particularly its impact on the cortex. In this study, we induced an NP model in mice through spared nerve injury (SNI) and observed a considerable, dose-dependent alleviation in NP symptoms following intraperitoneal or anterior cingulate cortex (ACC) administration of MLT. Our findings further indicated that the NP management of MLT is selectively mediated by MLT-related receptor 2 (MT₂R), rather than MT₁R, on neurons and microglia within the ACC. Transcriptome sequencing, complemented by bioinformatics analysis, implicated MLT in the modulation of Gα(i) and immune-inflammatory signals. Specifically, MLT inhibited the excitability level of pyramidal cells in the ACC by activating the Gα(i) signaling pathway. Simultaneously, MLT attenuated M₁ polarization and promoted M₂ polarization of microglia, thereby mitigating the inflammatory response and type II interferon response within the ACC. These findings unveil a hitherto unrecognized molecular mechanism: an MLT-mediated neuroimmune modulation pathway in the ACC mediated by MT₂R. This elucidation sheds light on the regulatory character of MLT in chronic nociceptive pain conditions, offering a prospective therapeutic strategy for NP management.

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.

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.

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.

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.

Recently, the high incidence of oral mucosal defects and the subsequent functional impairments have attracted widespread attention. Controlling scaffold geometry pattern has been proposed as a strategy to promote cell behavior and facilitate soft tissue repair. In this study, we innovatively construct an integrated dual-layer heterogeneous polycaprolactone (PCL) scaffold using melt electrowriting (MEW) technology. The outer layer was disordered, while the inner layer featured oriented fiber patterns: parallel (P-par), rhombic (P-rhomb), and square (P-sq). Our findings revealed that the P-rhomb and P-sq scaffolds exhibited superior surface wettability, roughness, and tensile strength compared to the pure disordered PCL scaffolds (P) and P-par. Compared to the commercial collagen membranes, the outer layer of PCL can effectively inhibit bacterial adhesion and biofilm formation. Furthermore, the P-rhomb and P-sq groups demonstrated higher gene and protein expression levels related to cell adhesion and cell migration rates than did the P and P-par groups. Among them, P-sq plays an important role in inducing the differentiation of gingival fibroblasts into myofibroblasts rich in α-smooth muscle actin (α-SMA). Additionally, P-sq could reduce inflammation, promote epithelial regeneration, and accelerate wound healing when used in full-thickness oral mucosal defects in rabbits. Overall, the integrated dual-layer heterogeneous PCL scaffold fabricated by MEW technology effectively inhibited bacterial adhesion and guided tissue regeneration, offering advantages for clinical translation and large-scale production. This promising material holds important potential for treating full-thickness mucosal defects in a bacteria-rich oral environments.

Introduction: Brain age prediction using neuroimaging data and machine learning algorithms holds significant promise for gaining insights into the development of neurodegenerative diseases. The estimation of brain age may be influenced not only by the imaging modality but also by multidomain clinical factors. However, the degree to which various clinical factors in individuals are associated with brain structure, as well as the comprehensive relationship between these factors and brain aging, is not yet clear. Methods: In this study, multimodal brain magnetic resonance imaging data and longitudinal clinical information were collected from 964 participants in a population-based cohort with 16 years of follow-up in northern China. We developed a machine learning-based algorithm to predict multimodal brain age and compared the estimated brain age gap (BAG) differences among the 5 groups characterized by varying exposures to these high-risk clinical factors. We then estimated modality-specific brain age in the hypertension group based on hypertension-related regional imaging metrics. Results: The results revealed a significantly larger BAG estimated from multimodal neuroimaging in subjects with 4 or 5 risk factors compared to other groups, suggesting an acceleration of brain aging under cumulative exposure to multiple risk factors. The estimated T1-based BAG exhibited a significantly higher level in the hypertensive subjects compared to the normotensive individuals. Conclusion: Our study provides valuable insights into a range of health factors across lifestyle, metabolism, and social context that are reflective of brain aging and also contributes to the advancement of interventions and public health initiatives targeted at the general population aimed at promoting brain health.

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.