Phenolic Acids-Rich Fractions from Agaricus bitorguis (Quél.) Sacc. Chaidam ZJU-CDMA-12 Mycelia Modulate Hypoxic Stress on Hypoxia-Damaged PC12 Cells

Hypoxia is a common pathological process in various clinical diseases. However, there is still a lack of effective anti-hypoxia active substances. Agaricus bitorguis (Quél.) Sacc Chaidam (ABSC) is a rare wild edible macrofungus that grows underground at high altitudes. Herein, intracellular phenolic acids-rich fractions (IPA) were extracted from ABSC ZJU-CDMA-12, and the structural characterization and anti-hypoxia activity of IPA on PC12 cells were elucidated as well. The results of HPLC-Q-TOF-MS illustrated that five kinds of IPA were isolated from ABSC, including (−)-epicatechin gallate, arabelline, yunnaneic acid D, 2′-O-p-hydroxybenzoyl-6′-O-trans-caffeoylgardoside,4′-O-methylgallocatechin-(4->8)-4′-O-methylepigallocatechin. IPA extracted from ABSC proved to show anti-hypoxia activity on hypoxia-damaged PC12 cells. Hypoxia enhanced reactive oxygen species (ROS) generation and reduced the mitochondrial membrane potential (ΔΨm) in PC12 cells, resulting in the inhibition of survival and induction of apoptosis in PC12 cells. Measurements of 100 μg/mL and 250 μg/mL IPA could significantly reduce hypoxia-induced damage in PC12 cells by decreasing overproduced intracellular ROS, improving ΔΨm, and reducing cell apoptosis rate. Our findings indicated that the IPA from ABSC potentially could be used as novel bioactive components applied to anti-hypoxia functional foods or medicines

Two-Stream Networks for Contrastive Learning in Hyperspectral Image Classification

In the domain of hyperspectral image (HSI) classification, the majority of deep learning methods have necessitated a substantial number of manually annotated samples to achieve outstanding results. However, the process of annotating HSI is conducted at the pixel-level, rendering it not only time-consuming but also financially burdensome. In light of this circumstance, contrastive learning methods that harness unlabeled samples by assigning pseudolabels through pretext tasks have garnered significant attention. Nevertheless, current contrastive learning methods primarily concentrate on exploring spatial diversity among surface samples in natural images, while neglecting the spectral diversity of point targets in HSI, resulting in insufficiently comprehensive feature exploration. In addition, due to the distinct learning objectives between upstream and downstream tasks, this leads to insufficient generalization when transferring to downstream tasks. To tackle these challenges, we propose a two-stream contrastive learning network for few-shot HSI classification. During the pretraining phase, one stream is deployed to probe spatial diversity among samples, whereas the other stream delves into spectral diversity. Subsequently, for transferring to downstream classification tasks, a multilevel fusion network was introduced. It can integrate shallow network features with higher generalization capabilities and deeper network features that are more task-specific. The fused features exhibit an improved performance when employed for classification tasks. Experimental results on four publicly available datasets illustrate that our approach outperforms state-of-the-art methodologies

Fatty Acid Desaturation Is Suppressed in Mir-26a/b Knockout Goat Mammary Epithelial Cells by Upregulating <i>INSIG1</i>

MicroRNA-26 (miR-26a and miR-26b) plays a critical role in lipid metabolism, but its endogenous regulatory mechanism in fatty acid metabolism is not clear in goat mammary epithelial cells (GMECs). GMECs with the simultaneous knockout of miR-26a and miR-26b were obtained using the CRISPR/Cas9 system with four sgRNAs. In knockout GMECs, the contents of triglyceride, cholesterol, lipid droplets, and unsaturated fatty acid (UFA) were significantly reduced, and the expression of genes related to fatty acid metabolism was decreased, but the expression level of miR-26 target insulin-induced gene 1 (INSIG1) was significantly increased. Interestingly, the content of UFA in miR-26a and miR-26b simultaneous knockout GMECs was significantly lower than that in wild-type GMECs and miR-26a- and miR-26b-alone knockout cells. After decreasing INSIG1 expression in knockout cells, the contents of triglycerides, cholesterol, lipid droplets, and UFAs were restored, respectively. Our studies demonstrate that the knockout of miR-26a/b suppressed fatty acid desaturation by upregulating the target INSIG1. This provides reference methods and data for studying the functions of miRNA families and using miRNAs to regulate mammary fatty acid synthesis

Loess Strata Distribution Characteristics and Paleoclimate Spatial Pattern during the Last Interglacial in the Luohe River Basin

Paleoclimate studies of loess in China have focused mostly on the time series of a single borehole or profile. However, research on loess strata and regional paleoenvironmental patterns could facilitate a deeper understanding of loess as a paleoenvironmental indicator and provide new insights into interpreting loess in sedimentary records of the paleoclimate. In this study, we determined the spatial pattern and regional characteristics of the paleoclimate during the Last Interglacial period in the Luohe River Basin, Shaanxi Province, China. We selected four representative boreholes in the study area (ZK04, ZK18, ZK13, and ZK19) from different landforms and zones, distributed from the northwest to the southeast, as well as three classic profiles (JB, JD, and LC). From north to south, comparative analyses were conducted of the loess strata, magnetic susceptibility, and grain size, and we analyzed the distribution characteristics of loess and paleosols in different geomorphological regions. The results showed that both the thickness and the sedimentation rate of loess in this river basin decreased from north to south. There were few paleosol horizons in the northern Liangmao area, but numerous such horizons in the southern plateau, and the degree of paleosol development increased from north to south. The magnetic susceptibility increased, whereas the particle composition tended to become thinner from north to south. The climate fluctuations of the Last Glacial recorded by the loess and paleosols in different regions were inconsistent

Dual-Branch Spectral&#x2013;Spatial Adversarial Representation Learning for Hyperspectral Image Classification With Few Labeled Samples

Recently, deep learning methods, particularly the convolutional neural networks, have been extensively employed for extracting spectral&#x2013;spatial features in hyperspectral image (HSI) classification tasks, yielding promising results. Conventional methods often use small image patches as input and combine spectral and spatial features with fixed strategies. However, the equal treatment of all pixels within heterogeneous patches can negatively impact feature extraction performance. In this article, we propose a semisupervised dual-branch spectral&#x2013;spatial adversarial representation learning (SSARL) method for HSI classification. SSARL adaptively assigns attention weights to different pixels and adds a spectral constraint to spatial features. Our approach consists of three main components: 1) a dual-branch framework designed to independently extract spectral and spatial information from pixel and patch samples; 2) a class consistency loss that adaptively combines spectral and spatial classification results, mitigating the adverse effects of heterogeneous patches and enabling appropriate feature selection for various situations; and 3) the deep learning model on the labeled sample size by adding the adversarial representation module and conditional entropy to two branches, reducing the deep learning model&#x0027;s reliance on labeled sample size. Experimental results demonstrate that SSARL outperforms competitive methods on small-sized (0.3&#x0025;&#x2013;5&#x0025;) labeled samples and exhibits superior performance for boundary test pixels

Climate change recorded by the grain size end member since MIS 3 in Jingbian area

As a typical multisource sediment, the grain size distribution of loess presents multi-peak distribution.End member analysis can be used to separate the end member components representing different sediment sources and sedimentary dynamics from the complex sediment size, which has been widely used in loess research.In this paper, Paterson parametric end member model was used to separate and explained the end member size of Sandaogou profile located in the southeastern margin of the Mu Us Desert.The analyzed results indicated that the Sandaogou loess in Jingbian was divided into four end members: EM1(8.93 μm) was the background dust; EM2(25.18 μm) was a component related to monsoon circulation.EM3(39.91 μm) and EM4(56.37 μm) were components related to winter wind.Among them, EM3 was the main component of loess in the loess plateau and EM4 was roughly the same grain size as modern sandstorms.Through the analysis of the curves of the end member components with age, the following conclusions were drawn: the profile recorded that the Jingbian area had experienced MIS 3(32.8-29.8 ka BP), LGM(29.8-22.8 ka BP), last deglacial(22.8-11.3 ka BP) and Holocene(8.7-1.7 ka BP) since MIS 3. Three climatic rapid change evented and cycles Dansgaard-Oeschger in deglaciation Heinrich 1(16.2-13.8 ka BP), Bølling-Allerød(13.8-12.8 ka BP) and Younger Dryas(12.8-11.3 ka BP) were recorded.The profile also recorded three major expansion-contraction cycles during last glacial period of the Mu Us Desert, and three dry sand events during the Holocene(8.7-8.2 ka, 6.0-5.0 ka, and 3.5-2.5 ka)

Shape-Memory-Reduced Graphene/Chitosan Cryogels for Non-Compressible Wounds

In this study, an antibacterial and shape-memory chitosan cryogel with high blood absorption and fast recovery from non-compressible wounds was prepared using a one-step method. Herein, we prepared a shape-memory-reduced graphene/chitosan (rGO-CTS) cryogel using a one-step method with a frozen mixing solution of chitosan, citric acid, dopamine, and graphene oxide, before treating it with alkaline solutions. The alkaline solution not only promoted the double cross-linking of chitosan but also induced dopamine to form polydopamine-reducing graphene oxide. Scanning electron microscope (SEM) images showed that the rGO-CTS cryogel possessed a uniform porous network structure, attributing excellent water-induced shape-memory properties. Moreover, the rGO-CTS cryogel exhibited good mechanical properties, antibacterial activity, and biocompatibility. In mouse liver trauma models, the rGO-CTS cryogel showed good blood clotting and hemostatic capabilities. Therefore, this composite cryogel has great potential as a new hemostatic material for application to non-compressible wounds

A high performance contra-rotating energy harvester and its wireless sensing application toward green and maintain free vehicle monitoring

Intelligent transportation necessitates advanced perception and cognitive systems that can provide continuous feedback from the vehicle. However, sensors relying on batteries face challenges such as high maintenance costs and environmental issues due to the limited lifespan of the power source. To overcome these challenges, this paper reports an efficient battery-free solution for transportation monitoring. The solution utilizes a speed-amplified rotary energy harvester (SAREH) to power various wireless Bluetooth sensors, enabling continuous monitoring of the vehicle's motion state. The SAREH combines a contra-rotating mechanism with a friction pendulum, resulting in excellent power output in a compact design. Experimental results demonstrate the ability of SAREH to extract power from vehicles operating at speeds ranging from 180 to 1260 rpm. The maximum power output and corresponding power density are measured as 712 mW and 34 mW cm−3, respectively. The prototype successfully powers portable electronics and supports battery-free navigation, triaxial acceleration, and temperature multi-sensors during real road and railway simulation tests. Additionally, the SAREH operates as a highly sensitive speed sensor and an early-warning system for detecting the vehicle's motion state. These results represent a significant advancement in intelligent transportation systems by showcasing the practicality of self-powered wireless monitoring capabilities on vehicles

A Qualitative Study on the Psychological Experience of Caregivers of COVID-19 Patients

BACKGROUND: The coronavirus disease 2019 (COVID-19) is spreading rapidly, bringing pressure and challenges to nursing staff. OBJECTIVE: To explore the psychology of nurses caring for COVID-19 patients. METHOD: Using a phenomenological approach, we enrolled 20 nurses who provided care for COVID-19 patients in the First Affiliated Hospital of Henan University of Science and Technology from 20 January to 10 February 2020. The interviews were conducted face-to-face or by telephone and were analysed by Colaizzi's 7-step method. RESULTS: The psychological experience of nurses caring for COVID-19 patients can be summarized into four themes. Firstly, negative emotions present in early stage consisting of fatigue, discomfort, and helplessness was caused by high-intensity work, fear and anxiety, and concern for patients and family members. Secondly, self-coping styles included psychological and life adjustment, altruistic acts, team support, and rational cognition. Thirdly, we found growth under pressure, which included increased affection and gratefulness, development of professional responsibility, and self-reflection. Finally, we showed that positive emotions occurred simultaneously with negative emotions. CONCLUSIONS: During an epidemic outbreak, positive and negative emotions of the front-line nurses interweaved and coexisted. In the early stage, negative emotions were dominant and positive emotions appeared gradually. Self-coping styles and psychological growth played an important role in maintaining mental health of nurses