Emerging roles and potential application of PIWI-interacting RNA in urological tumors

The piRNA (PIWI-interacting RNA) is P-Element induced wimpy testis (PIWI)-interacting RNA which is a small molecule, non-coding RNA with a length of 24-32nt. It was originally found in germ cells and is considered a regulator of germ cell function. It can interact with PIWI protein, a member of the Argonaute family, and play a role in the regulation of gene transcription and epigenetic silencing of transposable factors in the nucleus. More and more studies have shown that piRNAs are abnormally expressed in a variety of cancer tissues and patient fluids, and may become diagnostic tools, therapeutic targets, staging markers, and prognostic evaluation tools for cancer. This article reviews the recent research on piRNA and summarizes the structural characteristics, production mechanism, applications, and its role in urological tumors, to provide a reference value for piRNA to regulate urological tumors

miR-216b Post-Transcriptionally Downregulates Oncogene KRAS and Inhibits Cell Proliferation and Invasion in Clear Cell Renal Cell Carcinoma

Background/Aims: Increasing evidence has shown that miR-216b plays an important role in human cancer progression. However, little is known about the function of miR-216b in renal cell carcinoma. Methods: The expression levels of miR-216b in renal cell carcinoma tissues and cell lines were examined by qRT-PCR. The biological role of miR-216b in renal cell carcinoma proliferation and/or metastasis was examined in vitro and in vivo. The target of miR-216b was identified by a dual-luciferase reporter assay. The expression level of KRAS protein was measured by western blotting. Results: The expression of miR-216b was downregulated in clear cell renal cell carcinoma (ccRCC) cell lines and specimens compared to the adjacent normal tissues. Furthermore, miR-216b can bind to the 3’untranslated region (UTR) of KRAS and inhibit the expression of KRAS through translational repression. The in vitro study revealed that miR-216b attenuated ccRCC cell proliferation and invasion. Furthermore, in vivo study also showed that miR-216b suppressed tumor growth. MiR-216b exerted its tumor suppressor function through inhibiting the KRAS-related MAPK/ERK and PI3K/AKT pathways. Conclusion: Our findings provide, for the first time, significant clues regarding the role of miR-216b as a tumor suppressor by targeting KRAS in ccRCC

Inter-Continental Transfer of Pre-Trained Deep Learning Rice Mapping Model and Its Generalization Ability

Monitoring of rice planting areas plays an important role in maintaining food security. With powerful automatic feature extraction capability, crop mapping based on deep learning methods has become one of the most important research directions of crop remote sensing recognition. However, the training of deep learning models often requires a large number of samples, which restricts the application of these models in areas with a lack of samples. To address this problem, based on time-series Sentinel-1 SAR data, this study pre-trained the temporal feature-based segmentation (TFBS) model with an attention mechanism (attTFBS) using abundant samples from the United States and then performed an inter-continental transfer of the pre-trained model based on a very small number of samples to obtain rice maps in areas with a lack of samples. The results showed that an inter-continental transferred rice mapping model was feasible to achieve accurate rice maps in Northeast China (F-score, kappa coefficient, recall, and precision were 0.8502, 0.8439, 0.8345, and 0.8669, respectively). The study found that the transferred model exhibited a strong spatiotemporal generalization capability, achieving high accuracy in rice mapping in the three main rice-producing regions of Northeast China. The phenological differences of rice significantly affected the generalization capability of the transferred model, particularly the significant differences in transplanting periods, which could have resulted in a decrease in the generalization capability of the model. Furthermore, the study found that the model transferred based on an extremely limited number of samples could attain a rice recognition accuracy equivalent to that of the model trained from scratch with a substantial number of samples, indicating that the proposed method possessed strong practicality, which could dramatically reduce the sample requirements for crop mapping based on deep learning models, thereby decreasing costs, increasing efficiency, and facilitating large-scale crop mapping in areas with limited samples

Reliable knowledge graph fact prediction via reinforcement learning

Abstract Knowledge graph (KG) fact prediction aims to complete a KG by determining the truthfulness of predicted triples. Reinforcement learning (RL)-based approaches have been widely used for fact prediction. However, the existing approaches largely suffer from unreliable calculations on rule confidences owing to a limited number of obtained reasoning paths, thereby resulting in unreliable decisions on prediction triples. Hence, we propose a new RL-based approach named EvoPath in this study. EvoPath features a new reward mechanism based on entity heterogeneity, facilitating an agent to obtain effective reasoning paths during random walks. EvoPath also incorporates a new postwalking mechanism to leverage easily overlooked but valuable reasoning paths during RL. Both mechanisms provide sufficient reasoning paths to facilitate the reliable calculations of rule confidences, enabling EvoPath to make precise judgments about the truthfulness of prediction triples. Experiments demonstrate that EvoPath can achieve more accurate fact predictions than existing approaches

Analysis of winter diet in Guizhou golden monkey (Rhinopithecus brelichi) using DNA metabarcoding data

Abstract The Guizhou golden monkey (Rhinopithecus brelichi) is a critically endangered wildlife species, and understanding its diet composition may be useful for assessing its feeding strategies. DNA metabarcoding was used to determine the dietary diversity of R. brelichi. DNA was extracted from 31 faecal samples and amplified chloroplast rbcL and mitochondrial COI DNA was sequenced using the Illumina NovaSeq platform. A comparative analysis of the sequences revealed that the five most abundant plant genera were Magnolia, Morinda, Viburnum, Tetradium and Eurya. In winter, R. brelichi mostly consumed shrubs, herbs and shrubs/trees according to the habit of plant genera with higher abundances comparatively. The five most abundant families in animal diet were Psychodidae, Trichinellidae, Staphylinidae, Scarabaeidae and Trichoceridae. This study is the first to show the composition of the winter animal diets of R. brelichi based on DNA metabarcoding. These results provide an important basis for understanding the diet of wild R. brelichi, which inhabits only the Fanjingshan National Nature Reserve, China

Discrete Events of Ionosomes at the Water/Toluene Micro-Interface

Emulsification is a powerful technique for dispersing one fluid (water or oil) in the form of tiny droplets within an immiscible continuous fluid (oil or water). Hence, emulsion is an essential component of medicine, food, and shampoo, to name a few. An emulsifier, e. g., a surfactant, is normally added inside emulsions to stabilize the water/oil interfaces. Ionosomes, nanoscopic water droplets enclosed solely by an ionic bilayer, in which one layer formed from small and more mobile hydrated ions residing in the inner aqueous side and another layer formed from lipophilic bulky counter-ions riveted tightly in the adjacent outer oil side, were generated and in-situ counted "one at a time" at a polarized water/toluene micro-interface. Chemical polarization through the biphasic distribution of an antagonistic salt proved the proposed ionic bilayer structure of ionosomes. Promotion effect on Li+-ionosomes revealed by single-entity electrochemistry for quaternary ammonium cations with different alkyl chain length and with different concentration sheds new light on the mechanism of ionosomes. Fusion of a Li+-ionosome with the polarized soft micro-interface follows the bulk electrolysis model

Single-neuron representation of learned complex sounds in the auditory cortex

The sensory responses of cortical neuronal populations following training have been extensively studied. However, the spike firing properties of individual cortical neurons following training remain unknown. Here, we have combined two-photon Ca2+ imaging and single-cell electrophysiology in awake behaving mice following auditory associative training. We find a sparse set (~5%) of layer 2/3 neurons in the primary auditory cortex, each of which reliably exhibits high-rate prolonged burst firing responses to the trained sound. Such bursts are largely absent in the auditory cortex of untrained mice. Strikingly, in mice trained with different multitone chords, we discover distinct subsets of neurons that exhibit bursting responses specifically to a chord but neither to any constituent tone nor to the other chord. Thus, our results demonstrate an integrated representation of learned complex sounds in a small subset of cortical neurons