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Electrophysiology and optogenetics are pivotal in neuroscience for probing and modulating neural activities, playing a vital role in unraveling the complexities of brain functionality. Despite their importance, the efficacy of existing devices is hampered by insufficient functional integration, pronounced foreign body reactions, and physical constraints that impede natural animal behaviors. Here, we develop a multifunctional, ultraflexible neural probe designed for simultaneous electrophysiological monitoring and optical neural modulation, along with mechanical properties that are conducive to flexibility and compliance. By integrating a wireless neural signal acquisition and stimulation circuit, we achieved wireless recording of brain signals in mice and wireless optogenetic control over their locomotor behavior. The multifunctional ultraflexible probe presented in this study holds substantial promise for closed-loop brain-machine interfaces and deepening our understanding of neural circuit functions. This innovative approach addresses the aforementioned limitations by a comprehensive solution for in vivo neural interrogation and manipulation, marking a significant advancement in the tools available for neuroscience research.

With the application of computer vision in the field of agricultural disease recognition, the convolutional neural network is widely used in grape leaf disease recognition and has achieved remarkable results. However, most of the grape leaf disease recognition models have the problem of weak generalization ability. In order to overcome this challenge, this paper proposes an image identification method for grape leaf diseases in different domains based on Fourier domain adaptation. Firstly, Fourier domain adaptation is performed on the labeled source domain data and the unlabeled target domain data. To decrease the gap in distribution between the source domain data and the target domain data, the low-frequency spectrum of the source domain data and the target domain data is swapped. Then, three convolutional neural networks (AlexNet, VGG13, and ResNet101) were used to train the images after style changes and the unlabeled target domain images were classified. The highest accuracy of the three networks can reach 94.6%, 96.7%, and 91.8%, respectively, higher than that of the model without Fourier transform image training. In order to reduce the impact of randomness, when selecting the transformed image, we propose using farthest point sampling to select the image with low feature correlation for the Fourier transform. The final identification result is also higher than the accuracy of the network model trained without transformation. Experimental results showed that Fourier domain adaptation can improve the generalization ability of the model and obtain a more accurate grape leaf disease recognition model.

Vaginitis is the most common disease in gynecology. Vaginal dysbiosis is a main reason of bacteria vaginitis (BV), as the disrupted microecological environment facilitates the growth of various vaginal pathogens. The most dominant bacteria in the vaginal microbiota are lactic acid bacteria, which are important for maintaining vaginal health. At present, antibiotics and other drugs are often used in clinical treatment, but there are many adverse reactions and easy to relapse, and the intervention of probiotics can help restore vaginal microbiota and alleviate BV. This study is a human clinical trial of 50 patients with bacterial vaginitis (BV). The alleviation effect of applying a postbiotic gel for one week in BV was evaluated. Changes in patients’ clinical indicators of BV (properties of vaginal secretion) and the vaginal microbiota after using the postbiotic gel were monitored. Our results showed that apply the postbiotic gel improved the symptoms of BV, indicated by improvement in the abnormalities of patients’ vaginal secretions. After applying the gel, the relative abundance of vaginal lactobacilli increased compared to baseline. Significant negative correlations were found between lactobacilli and potential vaginal pathogens (including Gardnerella, Prevotella, and Atopobium), as well as the abnormalities of the vaginal secretion. Overall, our results showed that applying the postbiotic gel ameliorated BV, and the symptom improvement was accompanied by significant changes in the bacterial vaginal microbiota. Our study provides valuable clinical data in managing BV.

Flexible intracortical probes offer important opportunities for stable neural interfaces by reducing chronic immune responses, but their advances usually come with challenges of difficult implantation and limited recording span. Here, we reported a mechanically adaptive and deployable intracortical probe, which features a foldable fishbone-like structural design with branching electrodes on a temperature-responsive shape memory polymer (SMP) substrate. Leveraging the temperature-triggered soft-rigid phase transition and shape memory characteristic of SMP, this probe design enables direct insertion into brain tissue with minimal footprint in a folded configuration while automatically softening to reduce mechanical mismatches with brain tissue and deploying electrodes to a broader recording span under physiological conditions. Experimental and numerical studies on the material softening and structural folding-deploying behaviors provide insights into the design, fabrication, and operation of the intracortical probes. The chronically implanted neural probe in the rat cortex demonstrates that the proposed neural probe can reliably detect and track individual units for months with stable impedance and signal amplitude during long-term implantation. The work provides a tool for stable neural activity recording and creates engineering opportunities in basic neuroscience and clinical applications. [ABSTRACT FROM AUTHOR]