[6-Gingerol ameliorates adipose tissue insulin resistance in aging rats].

This study investigated the effects and mechanisms of 6-gingerol on adipose tissue insulin resistance in naturally aging rats with glycolipid metabolism disorders. Twenty-seven aging male SD rats were randomly divided into a model group(aged, n=9) and two groups treated with 6-gingerol at 0.05 mg·kg~(-1)(G-L, n=9) and 0.2 mg·kg~(-1)(G-H, n=9). Six young rats were randomly assigned to a normal control group(NC). Rats were treated for seven weeks by gavage. Non-esterified fatty acid(NEFA) and insulin content was determined by enzyme-linked immunosorbent assay(ELISA), and adipose tissue insulin resistance index(Adipo-IR) was calculated. HE staining was used to observe the size of adipocytes in epididymal white adipose tissue(eWAT). The gene and protein expression levels of adiponectin receptor 1(AdipoR1), AMP-activated protein kinase α(AMPKα), phosphorylated AMPK(p-AMPKα~(Thr172)), peroxisome proliferator-activated receptor-γ coactivator-1α(PGC-1α), phosphatidylinositol 3-kinase(PI3 K), protein kinase B(Akt), phosphorylated Akt(p-Akt~(Ser473)), tumor necrosis factor-α(TNF-α), c-Jun N-terminal kinase 1/2(JNK1/2), phosphorylated JNK1/2(p-JNK~(Thr183/Tyr185)), interleukin-1ß(IL-1ß), and interleukin-6(IL-6) in adiponectin(APN), insulin, and inflammatory factor signaling pathways were detected by Western blot and real-time RCR, respectively. The results showed that 6-gingerol at a high dose could significantly decrease the fasting plasma content of NEFA and insulin and reduce Adipo-IR. Additionally, 6-gingerol at a high dose significantly increased the protein and mRNA expression of APN, AdipoR1, PGC-1α, and PI3 K in eWAT, elevated the relative expression of p-AMPK~(Thr172) and p-Akt~(Ser 473), reduced the protein and mRNA expression of TNF-α, IL-1, and IL-6 in eWAT, and decreased the relative expression of p-JNK1 and p-JNK2. This study reveals that 6-gingerol can improve insulin sensitivity of adipose tissues in aging rats with glycolipid metabolism disorders, and this effect is presumedly achieved by enhancing the PI3 K/Akt signaling pathway, inhibiting adipose tissue inflammation, increasing APN synthesis, enhancing AdipoR1 expression, and activating its downstream AMPK/PGC-1α signaling pathway.

USP33 mediates Slit-Robo signaling in inhibiting colorectal cancer cell migration.

Originally discovered in neuronal guidance, the Slit-Robo pathway is emerging as an important player in human cancers. However, its involvement and mechanism in colorectal cancer (CRC) remains to be elucidated. Here, we report that Slit2 expression is reduced in CRC tissues compared with adjacent noncancerous tissues. Extensive promoter hypermethylation of the Slit2 gene has been observed in CRC cells, which provides a mechanistic explanation for the Slit2 downregulation in CRC. Functional studies showed that Slit2 inhibits CRC cell migration in a Robo-dependent manner. Robo-interacting ubiquitin-specific protease 33 (USP33) is required for the inhibitory function of Slit2 on CRC cell migration by deubiquitinating and stabilizing Robo1. USP33 expression is downregulated in CRC samples, and reduced USP33 mRNA levels are correlated with increased tumor grade, lymph node metastasis and poor patient survival. Taken together, our data reveal USP33 as a previously unknown tumor-suppressing gene for CRC by mediating the inhibitory function of Slit-Robo signaling on CRC cell migration. Our work suggests the potential value of USP33 as an independent prognostic marker of CRC.

Machine learning-enhanced gesture recognition through impedance signal analysis.

Gesture recognition is a crucial aspect in the advancement of virtual reality, healthcare, and human-computer interaction, and requires innovative methodologies to meet the increasing demands for precision. This paper presents a novel approach that combines Impedance Signal Spectrum Analysis (ISSA) with machine learning to improve gesture recognition precision. A diverse dataset that included participants from various demographic backgrounds (five individuals) who were each executing a range of predefined gestures. The predefined gestures were designed to encompass a broad spectrum of hand movements, including intricate and subtle variations, to challenge the robustness of the proposed methodology. The machine learning model using the K-Nearest Neighbors (KNN), Gradient Boosting Machine (GBM), Naive Bayes (NB), Logistic Regression (LR), Random Forest (RF), and Support Vector Machine (SVM) algorithms demonstrated notable precision in performance evaluations. The individual accuracy values for each algorithm are as follows: KNN, 86%; GBM, 86%; NB, 84%; LR, 89%; RF, 87%; and SVM, 87%. These results emphasize the importance of impedance features in the refinement of gesture recognition. The adaptability of the model was confirmed under different conditions, highlighting its broad applicability.

Cascading effects of seed-stem-individual spatial patterns along a grazing gradient.

Studying the seed trait-stem trait-individual spatial pattern system is helpful for understanding the developmental direction of plant dynamics and populations under grazing disturbance as well as the antagonistic relationship between animals and plants, but few systematic analyses of this spatial pattern system have been carried out. Kobresia humilis is the dominant species in alpine grasslands. We studied K. humilis seed traits and their relationship with K. humilis reproductive individuals, the relationship between reproductive and vegetative stems, and the weights and spatial patterns of reproductive and nonreproductive individuals under four grazing treatments: no grazing (control), light grazing, moderate grazing and heavy grazing. We explored the relationship among seed size and seed number with reproductive stems and vegetative stems along the grazing gradient and assessed the spatial pattern changes between reproductive and nonreproductive individuals. The results showed the following: (1) Seed size increased with increasing grazing intensity, and the coefficient of variation for seed size and seed number in the heavy grazing treatment was greater than 0.6. (2) The structural equation model showed that grazing treatment had a positive effect on seed number, seed size and reproductive stem number and a negative effect on reproductive stem weight. (3) Grazing treatment did not affect the resource allocation to reproductive stems and vegetative stems per unit length of reproductive K. humilis individuals. (4) Compared with the number of reproductive individuals in the no grazing treatment, the number in the heavy grazing treatment decreased significantly, and the negative correlation between reproductive individuals and nonreproductive individuals changed from a full-scale negative correlation to a small-scale negative correlation and a large-scale positive correlation. Our study showed that grazing could activate and change the resource allocation pattern of dominant species in a grassland and have significant positive effects on reproductive stem number, reproductive stem weight, seed number and seed size. Along a grazing intensity gradient, with the increase in distance between reproductive and nonreproductive individuals, the transformation of intraspecific relationships from a negative correlation to a positive correlation is an ecological strategy conducive to population survival.