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Mitochondrial dynamics and function are important for cell survival regulation under stress. In this study, we report that cerebral ischemia/reperfusion (I/R) injury significantly reduced mitochondrial function through reduced PTEN‐induced kinase 1 (PINK1) expression, ATP (Adenosine triphosphate) levels, and increased oxidative stress compared to sham rats. PINK1 overexpression mice significantly improved mitochondrial function by increased mitochondrial complex I, II, and III activities and ATP levels with concomitant decline in reactive oxygen species levels. PINK1 overexpression mice after I/R injury significantly reduced apoptosis through downregulation of cytochrome c, p53 expressions compared to cerebral I/R injury rats. Furthermore, we showed from parkin siRNA studies that PINK1 regulated phosphorylation parkin is critical to the protection against cerebral I/R injury. Altogether, we show that PINK1 mediated parkin regulation is key to the protection against cerebral I/R injury through regulation of mitochondrial function and apoptosis. [ABSTRACT FROM AUTHOR]

Gastric cancer is the third most common cause of cancer-related death. Accurate preoperative prediction of lymph node metastasis (LNM) in primary gastric cancer strongly influences the choice of surgical approach and the prognosis of gastric cancer patients. To develop and validate a deep learning-based model to analyze routine histological slides of patients with primary gastric cancer as well as clinical data to predict the occurrence of LNM preoperatively. Radical surgery slides from 309 patients and biopsy slides from 157 patients were collected from Fujian Cancer Hospital, along with radical surgery slides from 306 patients from The Cancer Genome Atlas (TCGA). Clinical data, including age, gender, lauren classification, and tumor location, were collected. These datasets were used to develop and validate a deep learning-based model. Five models were trained via cross-validation, with a mean area under the receiver operating characteristic curve (AUC) (standard deviation [SD]) of 0.877 (0.048) achieved. There was a significant difference in scores between both classes (LNM positive [N+] and LNM negative [N0]) (p < 0. 001). we validated the performance of the model on biopsy slides and achieved a mean AUC (SD) of 0.725 (0.020). In the analysis of clinical data, the lauren classification was demonstrated to be an independent risk factor for predicting LNM. Our study confirmed that deep learning-based image analysis could preoperatively predict LNM in patients with primary gastric cancer, combining histological slides at different magnification scales and relevant clinical data, showing superiority over individual modality prediction. [ABSTRACT FROM AUTHOR]

Tiny crosslink in chitosan (CS)/poly-(γ-glutamic acid) (γ-PGA) hydrogel leads to some disadvantages including low mechanical strength and high swelling. To enhance the crosslink of CS/γ-PGA hydrogel, amino acid (AA) was introduced to remove the drawbacks. The results indicated that AA can dramatically increase the crosslink and mechanical properties of CS/γ-PGA hydrogel, and AA chain length and concentration have a drastic effect on them. Particularly, 0.5 % β-Alanine (β-Ala) decreased the hydrogel by 70 % in porosity, 52 % in water solubility, and 30 % in swelling, but increased by 2.2-fold in elastic modulus, 2.08-fold in stress, and 1.53-fold in water retention. The porosity of the hydrogel correlates positively with the elastic modulus but negatively with the crosslinking degree. The effect of pH on CS/β-Ala/γ-PGA hydrogel was investigated in the load and release of benzalkonium chlorides (BAC). β-Ala strengthened pH response of the hydrogel in BAC load and release. The loading capacity increased with pH value, and 0.5 % β-Ala increased the hydrogel by 1.25-fold in the release capacity in alkaline environment, suggesting a good buffering effect of β-Ala on pH variation to accelerate the transportation of BAC. CS/β-Ala/γ-PGA hydrogel will be competently applied as a potential material for wound dressing in alkaline environment. • β-Ala as a buffer can counteract the detrimental effect of pH variation on the structure and behavior of CS/γ-PGA hydrogel. • β-Ala as a bridge can enhance the crosslinking degree of CS/γ-PGA hydrogel and increase the elastic modulus by 2.2-fold. • β-Ala as a carrier can increase the capacity of CS/γ-PGA hydrogel to release BAC by 25 % in alkaline environment. [ABSTRACT FROM AUTHOR]

Perineural invasion (PNI) is the process of neoplastic invasion of the nerves and is a prognostic factor in gastric cancer. However, such examination is a labor-intensive task in high-resolution digital pathological images. To alleviate this problem, we propose a multi-task deep learning-based framework to highlight diagnostically significant PNI regions in whole slide images (WSIs) of human gastric cancer tissue sections. The proposed framework includes a gastric cancer segmentation model, neural detection model, and PNI decision-making module, which realizes the segmentation of the gastric cancer region while completing the task of identifying PNI. Adequate comparative experiments were performed on our own gastric cancer PNI dataset called GC-PNI. Experiments have shown that our proposed model can effectively diagnose PNI with a high sensitivity of 0.972 and a specificity of 0.933, illustrating the potential of this practical application. • Proposing a deep learning framework for perineural invasion recognition in whole slide images of gastric cancer. • Designing a PNI decision-making module for recognizing perineural invasion. • The proposed framework achieved better performance. • Creating GC-PNI dataset for perineural invasion and gastric cancer. [ABSTRACT FROM AUTHOR]

• Screen-printed electrodes are composed of MoS 2 nanoparticles decorated EEG. • High-performance flexible planar MoS 2 /EEG MSCs have been successfully developed. • MoS 2 /EEG MSCs reveal excellent flexibility and cycling stability. • MoS 2 /EEG MSCs have a remarkable area specific capacitance of 13.6 mF cm−2. • Screen-printed planar MoS 2 /EEG MSCs have highly integrated function. Flexible planar micro-supercapacitors (MSCs) are favored in wearable electronics for energy storage components due to their great advantages in miniaturization, integration, and flexibility. However, the fabrication process of MSCs is usually complicated, and simple, fast and practical techniques for the preparation of MSCs still face challenges. Herein, a simple and efficient screen printing technique is creatively employed for fabrication of high-performance flexible planar MSCs based on pseudocapacitive MoS 2 nanoparticles decorated highly conductive electrochemically exfoliated graphene (MoS 2 /EEG) hybrid electrodes. The as-assembled MoS 2 /EEG MSCs reveal a noteworthy areal capacitance of 13.6 mF cm–2, a super high energy density of 1.478 mW h cm–2 with a high power density of 0.08 W cm–2, and outstanding cycling stability with capacitance attenuation of only 10% of after 10,000 charge and discharge cycles. Briefly, such screen-printed planar MoS 2 /EEG MSCs have good scalability, excellent mechanical properties, and fine performance consistency, which are most promising as an important micro-power energy storage component for flexible integrated electronic devices. [Display omitted] [ABSTRACT FROM AUTHOR]