Explore the vast range of titles available.

Sentiment analysis methods aim to evaluate users’ mental health conditions by analyzing their posted content (text, images, and audio) on social networks. However, given the diversity and complexity of social media information, traditional single-modal sentiment analysis techniques exhibit limitations in accurately interpreting users’ emotional states and may even lead to contradictory conclusions. To address this challenge, this paper proposes a Feature Fusion Based Transformer (FFBT) solution. The framework consists of three key steps: Firstly, RoBERTa and ResNet50 models are employed to extract features from textual and image data in social media posts, respectively. Then, a multimodal Transformer architecture facilitates feature alignment and fusion across different modalities. Finally, the fused features are fed into a fully connected network (FCN) for sentiment classification, ultimately determining the user’s emotional state. Experiments conducted on a custom dataset constructed from social media platform data demonstrate that FFBT outperforms existing sentiment analysis algorithms by 4.1% in accuracy and 5% in F1-scores, respectively.

Recently, more and more smart homes have become one of important parts of home infrastructure. However, most of the smart home applications are not interconnected and remain isolated. They use the cloud center as the control platform, which increases the risk of link congestion and data security. Thus, in the future, smart homes based on edge computing without using cloud center become an important research area. In this paper, we assume that all applications in a smart home environment are composed of edge nodes and users. In order to maximize the utility of users, we assume that all users and edge nodes are placed in a market and formulate a pricing resource allocation model with utility maximization. We apply the Lagrangian method to analyze the model, so an edge node (provider in the market) allocates its resources to a user (customer in the market) based on the prices of resources and the utility related to the preference of users. To obtain the optimal resource allocation, we propose a pricing-based resource allocation algorithm by using low-pass filtering scheme and conform that the proposed algorithm can achieve an optimum within reasonable convergence times through some numerical examples.

Metasurfaces have exhibited unprecedented degree of freedom in manipulating electromagnetic (EM) waves and thus provide fantastic front-end interfaces for smart systems. Here we show a framework for perception enhancement based on vision-driven metasurface. Human’s eye movements are matched with microwave radiations to extend the humans’ perception spectrum. By this means, our eyes can “sense” visual information and invisible microwave information. Several experimental demonstrations are given for specific implementations, including a physiological-signal-monitoring system, an “X-ray-glasses” system, a “glimpse-and-forget” tracking system and a speech reception system for deaf people. Both the simulation and experiment results verify evident advantages in perception enhancement effects and improving information acquisition efficiency. This framework can be readily integrated into healthcare systems to monitor physiological signals and to offer assistance for people with disabilities. This work provides an alternative framework for perception enhancement and may find wide applications in healthcare, wearable devices, search-and-rescue and others. Authors showcase a framework for visual perception enhancement system based on vision-driven metasurfaces. It can help humans obtain information in multiple frequency bands and allows the metasurface platform with more interesting functions.

Emerging evidence suggests that anesthesia and surgery may induce gut dysbiosis. Gut dysbiosis leads to imbalance in circulating contents of microbiota-derived metabolites and disrupts the integrity of the blood-brain barrier (BBB), contributing to postoperative cognitive dysfunction (POCD). The composition of gut microbiota may be influenced by various antibiotics. However, how perioperative use of antibiotics affects POCD needs more explorations. In the present study, we explored the effect of cefazolin, a common antibiotic used in perioperative period, on cognitive function, BBB integrity, gut bacteria and short chain fatty acids (SCFAs), a group of widely studied metabolites in aged mice, using 18-month-old male mice. Significant BBB disruptions and decreased levels of tight junction proteins, zonula occludens-1 (ZO-1) and Occludin (OCLN) were seen in the mice of POCD model. Cefazolin treatment attenuated these changes induced by anesthesia and surgery. Furthermore, cefazolin reversed the changes in several fecal bacteria (β - , γ/δ - , ε -Proteobacteria , and Bacteroidetes) as determined by qPCR tests. Analysis of plasma SCFAs showed that almost all types of SCFAs were reduced in POCD and cefazolin administration reversed the changes in expression of the two most abundant SCFAs (acetic and propionic acids). In conclusion, this study demonstrated that cefazolin improved POCD. Mechanistically, cefazolin suppressed the disruption of BBB, gut microbiota or SCFAs, thereby ameliorating POCD.

Postoperative cognitive dysfunction (POCD) is a severe neurological complication after anesthesia and surgery. However, there is still a lack of effective clinical pharmacotherapy due to its unclear pathogenesis. Caffeic acid phenethyl ester (CAPE), which is obtained from honeybee propolis and medicinal plants, shows powerful antioxidant, anti-inflammatory, and immunomodulating properties. In this study, we aimed to evaluate whether CAPE mitigated cognitive impairment following anesthesia and surgery and its potential underlying mechanisms in aged mice. Here, isoflurane anesthesia and tibial fracture surgery were used as the POCD model, and H2O2-induced BV2 cells were established as the microglial oxidative stress model. We revealed that CAPE pretreatment suppressed oxidative stress and promoted the switch of microglia from the M1 to the M2 type in the hippocampus, thereby ameliorating cognitive impairment caused by anesthesia and surgery. Further investigation indicated that CAPE pretreatment upregulated hippocampal Sirt6/Nrf2 expression after anesthesia and surgery. Moreover, mechanistic studies in BV2 cells demonstrated that the potent effects of CAPE pretreatment on reducing ROS generation and promoting protective polarization were attenuated by a specific Sirt6 inhibitor, OSS_128167. In summary, our findings opened a promising avenue for POCD prevention through CAPE pretreatment that enhanced the Sirt6/Nrf2 pathway to suppress oxidative stress as well as favor microglia protective polarization.

Background Circulating cell-free DNA (cfDNA) is a pool of short DNA fragments mainly released from apoptotic hematopoietic cells. Nevertheless, the precise physiological process governing the DNA fragmentation and molecular profile of cfDNA remains obscure. To dissect the DNA fragmentation process, we use a human leukemia cell line HL60 undergoing apoptosis to analyze the size distribution of DNA fragments by shallow whole-genome sequencing (sWGS). Meanwhile, we also scrutinize the size profile of plasma cfDNA in 901 healthy human subjects and 38 dogs, as well as 438 patients with six common cancer types by sWGS. Results Distinct size distribution profiles were observed in the HL60 cell pellet and supernatant, suggesting fragmentation is a stepwise process. Meanwhile, C-end preference was seen in both intracellular and extracellular cfDNA fragments. Moreover, the cfDNA profiles are characteristic and conserved across mammals. Compared with healthy subjects, distinct cfDNA profiles with a higher proportion of short fragments and lower C-end preference were found in cancer patients. Conclusions Our study provides new insight into fragmentomics of circulating cfDNA processing, which will be useful for early diagnosis of cancer and surveillance during cancer progression.

Millimeter-Wave (MMW) imaging is a promising technique for contactless security inspection. However, the high cost of requisite large-scale antenna arrays hinders its widespread application in high-throughput scenarios. Here, we report a large-scale single-shot MMW imaging framework, achieving low-cost high-fidelity security inspection. We first analyzed the statistical ranking of each array element through 1934 full-sampled MMW echoes. The highest-ranked elements are preferentially selected based on the ranking, building the experimentally optimal sparse sampling strategy that reduces antenna array cost by one order of magnitude. Additionally, we derived an untrained interpretable learning scheme, realizing robust and accurate MMW image reconstruction from sparsely sampled echoes. Last, we developed a neural network for automatic object detection, and experimentally demonstrated successful detection of concealed centimeter-sized targets using 10% sparse array, whereas all the other contemporary approaches failed at such a low sampling ratio. With the strong detection ability and order-of-magnitude cost reduction, we anticipate that this technique provides a practical way for large-scale single-shot MMW imaging. The authors report a large-scale single-shot millimeter-wave imaging technique for low-cost high-fidelity security inspection. Experiments demonstrated successful detection of concealed centimeter-sized targets with order-of-magnitude cost reduction.

Soil nitrogen-hydrolyzing enzymes catalyzes a key rate-limiting step in regulating the circulation of soil nutrient elements. The response of soil nitrogen (N)-hydrolyzing enzyme activities to environmental changes has been investigated in different geographic scales or ecosystems. Global warming has increased the frequency of soil freeze-thaw (FT) events, resulting in drastic changes in soil enzyme activities. Clarifying the changes in soil N-hydrolyzing enzymes under freeze-thaw conditions is essential for improving the N cycling and utilization efficiency in soil. However, how soil N-hydrolyzing enzymes respond to FT remains unclear. This study was aimed to analyze the influence of FT on soil N-hydrolyzing enzyme activity in Mollisols. The results showed that soil physicochemical properties and enzyme activities were changed after freeze-thaw events, and freeze-thaw temperature (FTF) had a greater impact on these properties than the number of freeze-thaw cycles (FTC). Correlation analysis showed that total organic carbon (TOC), total nitrogen (TN), total phosphorus (TP) and pH were the major factors affecting enzyme activities in FT events. Soil N-hydrolyzing enzyme activity was mainly regulated by environmental factors, which can directly and indirectly affect the soil enzyme activity. In the soil ecosystem, pH, TOC, TN and TP were important factors in counteracting damage to enzyme activity from FT effects and a suitable environment and adequate nutrients can limit damage to enzymes from FT events. The findings will better predictions the changing patterns of climate change on soil N-hydrolyzing enzyme activity.

Background Fusarium wilt of banana is a soil-borne disease caused by Fusarium oxysporum formea speciales (f.sp.) cubense with the Tropical Race 4 (FOC TR4), which seriously restricts the development of the banana industry. The utilization of antagonistic microorganisms to inhibit the propagation of pathogens has become a hot research topic in the field of biological prevention and control because of its green and efficient advantages. Results In this study, 60 siderophore strains from banana rhizosphere soil were screened. Three strains showing antifungal activity were screened out using FOC TR4 as the antagonistic pathogen. Among them, the strain Gxun-6 showed the highest antifungal activity, of up to 68.8%. It also showed significant inhibitory effect on the other 8 plant pathogens tested, thereby demonstrating broad-spectrum antifungal activity. Combined with colony morphology, physiological and biochemical analysis, and 16S rRNA evolutionary tree analysis, Gxun-6 was identified as Bacillus siamensis . Pot experiments showed that this strain had remarkable Fusarium wilt prevention and growth-promoting effect on banana. The control effect can reach 88.26%. The fresh weight increased by 25.36%. Conclusions The strain had strong Fusarium wilt control and growth promoting effects on banana and can be used as a strain resource for developing banana.

SIRT3 is a key NAD+-dependent protein deacetylase in the mitochondria of mammalian cells, functioning to prevent cell aging and transformation via regulation of mitochondrial metabolic homeostasis. However, SIRT3 is also found to express in some human tumors; its role in these SIRT3-expressing tumor cells needs to be elucidated. This study demonstrated that the expression of SIRT3 was elevated in a group of gastric cancer cells compared to normal gastric epithelial cells. Although SIRT3 expression levels were increased in the gastric tumor tissues compared to the adjacent non-tumor tissues, SIRT3 positive cancer cells were more frequently detected in the intestinal type gastric cancers than the diffuse type gastric cancers, indicating that SIRT3 is linked with subtypes of gastric cancer. Overexpression of SIRT3 promoted cell proliferation and enhanced ATP generation, glucose uptake, glycogen formation, MnSOD activity and lactate production, which were inhibited by SIRT3 knockdown, indicating that SIRT3 plays a role in reprogramming the bioenergetics in gastric tumor cells. Further analysis revealed that SIRT3 interacted with and deacetylated the lactate dehydrogenase A (LDHA), a key protein in regulating anaerobic glycolysis, enhancing LDHA activity. In consistence, a cluster of glycolysis-associated genes was upregulated in the SIRT3-overexpressing gastric tumor cells. Thus, in addition to the well-documented SIRT3-mediated mitochondrial homeostasis in normal cells, SIRT3 may enhance glycolysis and cell proliferation in SIRT3-expressing cancer cells.