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The primary aim of this study was to investigate the alterations in the microbial community of KK-Ay mice following antibiotic treatment. A comparative analysis of the gut microbiota was conducted between KK-Ay mice treated with antibiotics and those without treatment. The microbial community dynamics in antibiotic-treated KK-Ay mice were meticulously assessed over an eight-week period using 16S rDNA sequencing analysis. Simultaneously, dynamic renal function measurements were performed. The results demonstrated a marked decrease in bacterial DNA abundance following antibiotic intervention, coupled with a substantial reduction in bacterial diversity and a profound alteration in microbial composition. These observed microbiota changes persisted in the KK-Ay mice throughout the eight-week post-antibiotic treatment period. Particularly noteworthy was the reemergence of bacterial populations after two weeks or more, resulting in a microbiota composition resembling that of untreated KK-Ay mice. This transition was characterized by a significant increase in the abundance of clostridia at the class level, Lachnospirales and Oscillospirales at the order level, and Lachnospiraceae, Oscillospiraceae, and Ruminococcaceae at the family level. Concurrently, there was a notable decrease in Clostridia_UCG-014. The observed alterations in the gut microbiota of antibiotic-treated KK-Ay mice suggest a dynamic response to antibiotic intervention and subsequent restoration towards the original untreated state. [ABSTRACT FROM AUTHOR]

In the face of accelerating urbanization, Urban Green Spaces (UGS) have become vital for sustaining urban ecosystems and the health and well-being of urban residents. This study offers a comprehensive analysis of the growth rate of urban green space (GRUGS) across various regions in China over a two-decade period, highlighting the interplay between urban development, population dynamics, and ecological sustainability. The research meticulously examines the impacts of urban built-up area expansion, population growth, and air pollution on GRUGS. It categorizes 291 Chinese cities into 15 urban agglomerations and utilizes data on urban built-up areas, population, and PM2.5 levels from 2000 to 2020. The findings reveal a mixed picture: while some regions demonstrate a robust commitment to integrating green spaces within urban growth, evident in high GRUGS values, others struggle to preserve green spaces amidst rapid urban expansion and population surges. This study underscores the necessity of tailored urban planning strategies that are region-specific and the ongoing need for innovation in urban development to achieve ecological sustainability. The insights garnered are invaluable for policymakers and urban planners, stressing the indispensable role of green spaces in enhancing urban life quality and securing sustainable urban environments. [ABSTRACT FROM AUTHOR]

PANoptosis, a burgeoning area of research, is a unique type of programmed cell death typified by pyroptosis, apoptosis, and necroptosis, yet it defies singular classification by any one mode of death. The assembly and activation of PANoptosomes are pivotal processes in PANoptosis, with several PANoptosomes already identified. Linkages between PANoptosis and the pathophysiology of various systemic illnesses are established, with increasing recognition of its association with oral ailments. This paper aims to deepen understanding by conducting a comprehensive analysis of the molecular pathways driving PANoptosis and exploring its potential implications in oral diseases. [ABSTRACT FROM AUTHOR]

In aquaculture, real-time and rapid detection of dead fish is important for early risk warning and improving aquaculture efficiency. However, the complex actual environment and uncontrollable fish movement have brought great challenges to the detection of dead fish. Therefore, this paper proposes a high-precision and lightweight dead fish-detection transformer (DF-DETR) based on machine vision and original RT-DETR (real-time detection transformer). The specific implementation is as follows: Firstly, the backbone of the original RT-DETR was replaced by the RepNCSPELAN module which extracts multi-scale features. This not only improves the model’s ability to detect targets of different sizes but also reduces the amount of model parameters. Secondly, the AIFI in the RT-DETR was improved to CascadedGroupAttention (CGA). By changing the original feature fusion method, different levels of features are grouped and attention mechanism is added, so as to capture more target features. Finally, the CCFM_CSP module was constructed to fuse important features using parallel dilated convolution with different expansion rates, which improves the detection accuracy. The experimental results show that the mAP@.5 of the proposed dead fish detection model DF-DETR can reach 96.6%, and the parameter amount is reduced by 27% compared with the original RT-DETR. In summary, the proposed DF-DETR model realizes real-time and high-precision dead fish detection, which can provide effective technical support for the development of intelligent inspection robots. [ABSTRACT FROM AUTHOR]

In recirculating aquaculture system, precise estimation of perch size from images is essential for developing intelligent management system. However, variations in fish postures and visual field lead to different fish sizes in RGB images, posing challenges for accurate fish detection and localization. To address the above issues, this paper proposes a nondestructive target detection and size measurement method for perch, based on depth information and RGB-D images. The details are as follows: firstly, the capture ability of perch key point features is augmented by a bi-level routing attention (BRA) mechanism. Secondly, the enhanced CSPDarknet53 to 2-Stage FPN(C2f) module and new detection layer are introduced into the model’s backbone and neck, further improving the learning ability of perch features and the recognition accuracy of small-size targets. Finally, based on the detected key point coordinates, the perch size is calculated by combining the three-dimensional transformation from depth camera and measurement model. The experimental results show that the mAP@.5:.95 for key point detection reaches 86.4%, which is 3.6% higher than the baseline model, and the average relative error of perch size measurement is ± 5%. The proposed model provides an important basis for developing scientific feeding strategies and harvest plans. [ABSTRACT FROM AUTHOR]

Ischaemia of the heart and limbs attributable to compromised blood supply is a major cause of mortality and morbidity. The mechanisms of functional angiogenesis remain poorly understood, however. Here we show that FNIP1 plays a critical role in controlling skeletal muscle functional angiogenesis, a process pivotal for muscle revascularization during ischemia. Muscle FNIP1 expression is down-regulated by exercise. Genetic overexpression of FNIP1 in myofiber causes limited angiogenesis in mice, whereas its myofiber-specific ablation markedly promotes the formation of functional blood vessels. Interestingly, the increased muscle angiogenesis is independent of AMPK but due to enhanced macrophage recruitment in FNIP1-depleted muscles. Mechanistically, myofiber FNIP1 deficiency induces PGC-1α to activate chemokine gene transcription, thereby driving macrophage recruitment and muscle angiogenesis program. Furthermore, in a mouse hindlimb ischemia model of peripheral artery disease, the loss of myofiber FNIP1 significantly improved the recovery of blood flow. Thus, these results reveal a pivotal role of FNIP1 as a negative regulator of functional angiogenesis in muscle, offering insight into potential therapeutic strategies for ischemic diseases. Functional revascularization is vital to the recovery of blood flow. Here, Sun et al. show that myofiber FNIP1 is a negative regulator of muscle functional angiogenesis and revascularization after ischemia by controlling macrophage recruitment. [ABSTRACT FROM AUTHOR]

To study the classification efficiency of using texture feature machine learning method in distinguishing solid lung adenocarcinoma (SADC) and tuberculous granulomatous nodules (TGN) that appear as solid nodules (SN) in non-enhanced CT images. 200 patients with SADC and TGN who underwent thoracic non-enhanced CT examination from January 2012 to October 2019 were included in the study, 490 texture eigenvalues of 6 categories were extracted from the lesions in the non-enhanced CT images of these patients for machine learning, the classification prediction model is established by using relatively the best classifier selected according to the fitting degree of learning curve in the process of machine learning, and the effectiveness of the model was tested and verified. The logistic regression model of clinical data (including demographic data and CT parameters and CT signs of solitary nodules) was used for comparison. The prediction model of clinical data was established by logistic regression, and the classifier was established by machine learning of radiologic texture features. The area under the curve was 0.82 and 0.65 for the prediction model based on clinical CT and only CT parameters and CT signs, and 0.870 based on Radiomics characteristics. The machine learning prediction model developed by us can improve the differentiation efficiency of SADC and TGN with SN, and provide appropriate support for treatment decisions. [ABSTRACT FROM AUTHOR]

The exponential device growth in industrial Internet of things (IIoT) has a noticeable impact on the volume of data generated. Edge-cloud computing cooperation has been introduced to the IIoT to lessen the computational load on cloud servers and shorten the processing time for data. General programmable logic controllers (PLCs), which have been playing important roles in industrial control systems, start to gain the ability to process a large amount of industrial data and share the workload of cloud servers. This transforms them into edge-PLCs. However, the continuous influx of multiple types of concurrent production data streams against the limited capacity of built-in memory in PLCs brings a huge challenge. Therefore, the ability to reasonably allocate memory resources in edge-PLCs to ensure data utilization and real-time processing has become one of the core means of improving the efficiency of industrial processes. In this paper, to tackle dynamic changes in arrival data rate over time at each edge-PLC, we propose to optimize memory allocation with Q-learning distributedly. The simulation experiments verify that the method can effectively reduce the data loss probability while improving the system performance. [ABSTRACT FROM AUTHOR]

Environmental pollution caused by microplastics (MPs) have become a non-negligible environmental problem and come into our notice recently. Herein, the nutrient elemental signature (ionome) of rice seedlings exposed to four levels of polyethylene microplastics (PE-MPs), and was analyzed by inductively coupled plasma optical emission spectroscopy (ICP-OES) or mass spectroscopy (ICP-MS) to determine the relationship between ionome and MPs. After 21 days of laboratory exposure, no shoots growth difference has shown among any doses of PE-MPs treatments, however, the roots growth was significantly inhibited after the medium and high doses of PE-MPs treatments. Further analysis showed that PE-MPs treatments could decrease the accumulation of one essential mineral element Mn and some non-essential mineral elements accumulation including As and Cd, while increase the accumulation of one essential mineral elements including Na in rice seedlings. This study is the first to document the variation of the rice seedlings ionome after exposing microplastics. [ABSTRACT FROM AUTHOR]

Nowadays, vehicles have been equipped with various kinds of sensors which produce so called big data constantly. Among them, multimedia contents form the major part of the total generated data. They are usually shared among vehicles in a region of interest with less concerns on delay criteria. Therefore, to reduce cost, these data will be delivered using a carry-and-forward method in a Vehicular Delay Tolerant Network. Since the volume of these data is not negligible, not only delivery utility but also memory space usage must be considered while designing forwarding strategy. ThrowBoxes have been utilized to increase encountering opportunities. In this paper, we develop an optimal data packet assignment algorithms to achieve global maximum delivery utilities among ThrowBoxes. We evaluate the proposed scheme with the real world data trace. The results show that our scheme achieves better performance in terms of delay, delivery ratio, cost and other metrics. [ABSTRACT FROM AUTHOR]

Mitochondrial proteolysis is an evolutionarily conserved quality-control mechanism to maintain proper mitochondrial integrity and function. However, the physiological relevance of stress-induced impaired mitochondrial protein quality remains unclear. Here, we demonstrate that LONP1, a major mitochondrial protease resides in the matrix, plays a role in controlling mitochondrial function as well as skeletal muscle mass and strength in response to muscle disuse. In humans and mice, disuse-related muscle loss is associated with decreased mitochondrial LONP1 protein. Skeletal muscle-specific ablation of LONP1 in mice resulted in impaired mitochondrial protein turnover, leading to mitochondrial dysfunction. This caused reduced muscle fiber size and strength. Mechanistically, aberrant accumulation of mitochondrial-retained protein in muscle upon loss of LONP1 induces the activation of autophagy-lysosome degradation program of muscle loss. Overexpressing a mitochondrial-retained mutant ornithine transcarbamylase (ΔOTC), a known protein degraded by LONP1, in skeletal muscle induces mitochondrial dysfunction, autophagy activation, and cause muscle loss and weakness. Thus, these findings reveal a role of LONP1-dependent mitochondrial protein quality-control in safeguarding mitochondrial function and preserving skeletal muscle mass and strength, and unravel a link between mitochondrial protein quality and muscle mass maintenance during muscle disuse. Mitochondrial function is important for muscle maintenance and function, and mitochondrial proteolysis maintains mitochondrial integrity and function. Here the authors report that that loss of LONP1-dependent mitochondrial proteolysis in muscle causes reduced muscle mass and strength via activation of autophagy. [ABSTRACT FROM AUTHOR]

Cerebral amyloid angiopathy (CAA) commonly found in the aged is pathologically characterized by β-amyloid (Aβ) deposition in the walls of arteries and capillaries of brain. In this study, four flexible multidentate benzyldiamine derivatives as potential probes for cerebrovascular Aβ deposition were designed and synthesized. In in vitro inhibition assays, the ligands 18–21 displayed high affinities for Aβ aggregates with Ki values of 1.45 ± 0.53 nM, 1.68 ± 0.35 nM, 1.16 ± 0.23 nM and 1.72 ± 0.19 nM, respectively. A significant improvement in the binding affinity over the monomer, compounds 9–12 or benzyldiamine derivatives, demonstrated the applicability of the multidentate approach. The underlying mechanism of these novel Aβ agents was explored by molecular docking technique, which theoretically verified the high affinities of the multidentate benzyldiamine derivatives for Aβ aggregates. Moreover, the molecular masses of the ligands 18–21 are more than 700 Dalton, which are believed to be hardly capable of penetrating blood brain barrier. In this regard, these ligands could be used to distinguish CAA from Alzheimer's disease which is another Aβ-related disorder disease. To convert these ligands to positron emission tomography imaging agents, we attempted to radiosynthesize [18F]18. Though the radiolabeling was not very successful, the preliminary results suggested that these newly proposed multidentate benzyldiamine derivatives may be used as potential Aβ imaging agents in cerebral amyloid angiopathy. [ABSTRACT FROM AUTHOR]

With the recent advancement in Industrial Internet of Things (IIoT), general programmable logic controllers (PLCs) have been playing more and more critical roles in industrial control systems (ICSs), such as providing local data processing, decentralized control and fault diagnosis. These so called edge-PLCs, directly receive the raw data from sensors embedded in factory equipments, put them into predefined memory space and perform analysis using programs such as the ladder logic. The challenge is how to allocate blocks in the fixed-size memory to different sensors so as to match irregular data flows. In this paper, we try to conduct performance analysis of different partition instances of the memory in the edge-PLC by modeling this problem as a multiple single-server queueing systems. We assume every sensing flow is independent of each other and has its dedicated processer. Changes can be made to partition instances to adapt to the external environment, such as the rising of order numbers or product category switching. Each state of the environment is defined by the finite state Markov chain and arrival of sensing data flows follow the stationary Poisson process. The data in the queue will expire after staying in the memory for a while. The duration of availability and service is modeled as the exponential distribution. The performance measured under different system states are analyzed in the simulation. [ABSTRACT FROM AUTHOR]

Antimicrobial genes play an important role as a primary defense mechanism in all multicellular organisms. We chose Bacillus subtilis as a target pathogen indicator and transferred the Aegilops tauschii Cosson cDNA library into B. subtilis cells. Expression of the candidate antimicrobial gene can inhibit B. subtilis cell growth. Using this strategy, we screened six genes that have an internal effect on the indicator bacteria. Then, the secreted proteins were extracted and tested; two genes, AtR100 and AtR472, were found to have strong external antimicrobial activities with broad-spectrum resistance against Xanthomonas oryzae pv. oryzicola, Clavibacter fangii, and Botrytis cinerea. Additionally, thermal stability tests indicated that the antimicrobial activities of both proteins were thermostable. Furthermore, these two proteins exhibited no significant hemolytic activities. To test the feasibility of application at the industrial level, liquid fermentation and spray drying of these two proteins were conducted. Powder dilutions were shown to have significant inhibitory effects on B. cinerea. Fluorescence microscopy and flow cytometry results showed that the purified protein impaired and targeted the cell membranes. This study revealed that these two antimicrobial peptides could potentially be used for replacing antibiotics, which would provide the chance to reduce the emergence of drug resistance. [ABSTRACT FROM AUTHOR]

Purpose: Glaucoma is a common chronic neurodegenerative disease, which could lead to visual loss. In this study, we aimed to investigate whether fisetin, a natural flavone with anti-inflammatory and antioxidant properties, is able to alleviate glaucoma.Methods: We employed a DBA/2J mouse model which was treated with or without fisetin. Pattern electroretinogram (P-ERG), visual evoked potentials (VEPs) and intraocular pressure (IOP) were evaluated. Quantitative real-time polymerase chain reaction and enzyme-linked immunosorbent assay (ELISA) were used to measure the expression levels of TNF-α, IL-1β and IL-6. Western blotting was performed to assess the activation of nuclear factor kappa-B (NF-κB).Results: We found that DBA/2J mice treated with fisetin (10-30 mg/kg) showed improved P-ERG and VEP amplitudes and reduced IOP compared to untreated DBA/2J mice. In addition, there were more survived retinal ganglion cells (RGCs) and less activated microglia in fisetin-treated DBA/2J mice than those in untreated mice. Furthermore, secreted protein levels and mRNA levels of TNF-α, IL-1β and IL-6 were significantly repressed by fisetin. The phosphorylated p65 level in the nucleus was dramatically reduced in fisetin-treated mice compared to it in untreated mice. Our results demonstrate that fisetin may exert its function through regulating cytokine productions and inhibiting NF-κB activation in the retina.Conclusion: In conclusion, fisetin is able to promote the visual functions of DBA/2J mice by inhibiting NF-κB activation. [ABSTRACT FROM AUTHOR]

Endothelial cell activation, injury and dysfunction have been regarded as one of the initial key events in the pathogenesis of atherosclerosis. Lipopolysaccharide (LPS), an important mediator of inflammation, can cause endothelial cell damage and apoptosis. Naringin (Nar), one major flavanone glycoside from citrus fruits, shows various pharmacological actions, but the effect of Nar on LPS-induced damage in human umbilical vein endothelial cells (HUVECs) remains unknown. The present results showed that Nar significantly improved the survival rate of HUVECs, and decreased reactive oxygen species and intracellular Ca levels caused by LPS compared with model group. In addition, Nar obviously decreased cytochrome c release from mitochondria into cytosol. Moreover, Nar significantly down-regulated the protein or mRNA levels of IL-1, IL-6, TNF-α, VCAM-1, ICAM-1, NF-κB, AP-1, cleaved-3,-7,-9, p53, Bak and Bax, and up-regulated the expressions of Bcl-xl, Bcl-2 to suppress inflammation and apoptosis. Furthermore, Nar obviously inhibited phosphorylation levels of JNK, ERK and p38 MAPK. In conclusion, Nar exhibited potent effects against LPS-induced damage in HUVECs through the modulation of oxidative stress, inflammation, apoptosis and MAPK pathways, which should be developed as a potent candidate for the treatment of atherosclerosis in the future. [ABSTRACT FROM AUTHOR]

To investigate the response of phytoplankton size structure to changes of environmental factors, total and size-fractionated (pico-, nano- and micro-phytoplankton) Chl a concentrations were studied in autumn in Xiamen Bay of China. Total Chl a concentration was higher in west area than that in east area, similar to the spatial distribution of SiO-Si and DIN concentration. Comparing different water areas, the proportion of micro-Chl a and size index of phytoplankton were highest in the Da'deng water with lowest DIN and PO-P. The highest value of pico-Chl a concentration and proportion was in the nutrient-rich West water. Compared with historical results in Xiamen Bay, nano-phytoplankton was still the dominant contributor in the bay, and pico-phytoplankton proportion increased in the West water. Besides nutrient increasing, it might be relative to global climate warming. Based on historical data from 1954 to 2010, phytoplankton community under observation of microscope also showed a miniaturizing trend. Correlations between phytoplankton and environmental factors indicated that nutrient availability, temperature and irradiance probably impacted size structure of phytoplankton community in Xiamen Bay. It implies that more studies are needed to explore how environmental factors especially eutrophication and global climate change affect size structure of phytoplankton community and the subsequent impact on the marine ecosystem structure in the future. [ABSTRACT FROM AUTHOR]

Triptolide is a traditional Chinese medicinal herb-derived antineoplastic agent. However, its antitumor activity against gynecologic carcinomas has not yet been well described. It is the purpose of this article to investigate the effect and mechanism of triptolide in human ovarian cancer using both A2780 (p53 wild) and OVCAR-3 (p53 mutated) cells. Our results showed that triptolide exerted a potent inhibitory effect on the growth and proliferation of both cell lines in a dose- and time-dependent manner and that the effect was independent of the expression of p53. In contrast, triptolide had only a marginal cytotoxicity in noncancerous ovary cells, lung fibroblast cells, and macrophage cells, indicating differential inhibitory effects of the drug on cell growth between ovarian cancer cells and normal tissue cells. Exposure of the ovarian cancer cells to triptolide induced apoptosis, as evaluated by annexin V/propidium iodide-labeled flow cytometry. Triptolide-induced apoptosis was accompanied by cytochrome c release and caspase-3 activation and was associated with downregulation of Bcl-2 and upregulation of Bax. Cell cycle analysis demonstrated that treatment with triptolide induced cell cycle S phase arrest in A2780 cells and G2/M phase arrest in OVCAR-3 cells. Further detection by Western blotting revealed that the cell cycle arrest by triptolide in both cell lines occurred in concert with increased expression of p21. This study shows that triptolide selectively kills ovarian cancer cells with different p53 status predominantly through regulating the coordinate and dynamic cellular processes of proliferation and apoptosis, thereby making it a promising chemotherapeutic agent against a broad spectrum of ovarian carcinomas. [ABSTRACT FROM AUTHOR]

We recorded NO-N, NO-N, NH-N, PO-P, SiO-Si, salinity, and temperature data at 10 stations in the Dongshan Bay in May, June, July, August, October, and November 2008, analyzing nutrient and eutrophication characteristics. The mean concentration of dissolved inorganic nitrogen (DIN) was 0.30-0.40 mg/dm; generally, NO-N was the main form in most areas. The mean concentrations of PO-P and SiO-Si were 0.040-0.060 mg/dm and 1.00-1.50 mg/dm, respectively. We proved that the majority of the SiO-Si in the Dongshan Bay came from the Zhangjiang River, with some coming from the Bachimen Strait. DIN originated from both the Zhangjiang River and the Bachimen Strait. Most PO-P originated from the Bachimen Strait, and some came from the Zhangjiang River. We found that P was an overall limiting factor to the phytoplankton community in most of the Dongshan Bay, and that Si and N were in surplus. However, near the Bachimen Strait Si became a limiting factor, especially for diatoms, while P and N were in comparative surplus. We used a potential eutrophication assessment method to analyze eutrophication, and showed that the most serious eutrophication occurred near the Zhangjiang River estuary and near the Bachimen Strait. In 2008, DIN levels were four times higher than that in 1988; PO-P levels were threefold higher, while SiO-Si was approximately double. Dissolved nutrients increased between 1988 and 2008. DIN increased at the greatest rate comparing to PO-P and SiO-Si, thus the N/P and N/Si mol ratios increased. Further studies on the effects of high DIN concentrations on the phytoplankton communities and marine ecosystems of the Dongshan Bay are needed. [ABSTRACT FROM AUTHOR]

The Editor-in-Chief of Documenta Ophthalmologica is publishing an editorial expression of concern for the manuscript "Fisetin rescues retinal functions by suppressing inflammatory response in a DBA/2J mouse model of glaucoma" by Li et al. (2019) [1]. [ABSTRACT FROM AUTHOR]

Molecular analysis by parallel tandem mass spectrometry (MS/MS) imaging contributes to the in situ characterization of biosynthetic intermediates which is crucial for deciphering the metabolic pathways in living organisms. We report the first use of TOF-SIMS MS/MS imaging for the cellular localization and characterization of biosynthetic intermediates of bioactive γ-lactones rubrynolide and rubrenolide in the Amazonian tree Sextonia rubra (Lauraceae). Five γ-lactones, including previously reported rubrynolide and rubrenolide, were isolated using a conventional approach and their structural characterization and localization at a lateral resolution of ~400 nm was later achieved using TOF-SIMS MS/MS imaging analysis. 2D/3D MS imaging at subcellular level reveals that putative biosynthetic γ-lactones intermediates are localized in the same cell types (ray parenchyma cells and oil cells) as rubrynolide and rubrenolide. Consequently, a revised metabolic pathway of rubrynolide was proposed, which involves the reaction between 2-hydroxysuccinic acid and 3-oxotetradecanoic acid, contrary to previous studies suggesting a single polyketide precursor. Our results provide insights into plant metabolite production in wood tissues and, overall, demonstrate that combining high spatial resolution TOF-SIMS imaging and MS/MS structural characterization offers new opportunities for studying molecular and cellular biochemistry in plants. [ABSTRACT FROM AUTHOR]

Moving vehicles have been sensing all kinds of data on the road in which multimedia data possesses a large portion. These data is often forwarded to vehicles in a region of interest or the monitoring center in an opportunistic manner. With respect to the large volume content, the storage space of relay vehicles is becoming the bottleneck of achieving higher performance, e.g., a data chunk may be rejected or dropped due to insufficient storage of intermediate vehicles. Thus, previous work that only focuses on the delivery metric without considering the data size is not likely to work efficiently in the proposed scenario. As deploying stationary infrastructures is of very large cost and not feasible everywhere, in this paper, we focus on the inter-vehicle data forwarding problem with storage and communication capacity constraints. First, we considered the situation when the vehicles are distributed sparsely. The multi-copy routing challenge is modeled as a multiple knapsack problem. Then, it is extended to a dense scenario. An optimization to the broadcast data forwarding is investigated. With the real data trace, the experiments show that our scheme achieves better performance than the competitors in terms of delay and delivery ratio. A better balance between duplication and performance is also achieved by the multi-copy algorithm. [ABSTRACT FROM AUTHOR]

Cathelicidins are short cationic host defense peptides and play a central role in host innate immune system. Here we identified two novel cathelicidins, Cl-CATH2 and 3, from Columba livia. Evolutionary analysis of avian cathelicidins via phylogenetic tree and Ka/Ks calculations supported the positive selection that prompted evolution of CATH2 to CATH1 and 3, which originate from common ancestor and could belong to one superfamily. Cl-CATH2 and 3 both adopt amphipathic α-helical comformations identified by circular dichroism and the 3D structures built by Rosetta. Cl-CATH2 of CATH2 family with the most expression abundance in bird, exhibited relatively weak antimicrobial activity, but acted instead on the innate immune response without showing undesirable toxicities. In macrophages primed by LPS, Cl-CATH2 significantly down-regulated the gene and protein expressions of inducible nitric oxide synthase and pro-inflammatory cytokines while enhancing the anti-inflammatory cytokine, acting through MAPK and NF-κB signaling pathways. Molecular docking shows for the first time that cathelicidin binds to the opening region of LPS-binding pocket on myeloid differentiation factor 2 (MD-2) of toll-like receptor (TLR)4-MD-2 complex, which in turn inhibits the TLR4 pathway. Our results, therefore, provide new insight into the mechanism underlying the blockade of TLR4 signaling by cathelicidins. [ABSTRACT FROM AUTHOR]

Background: Various machine learning (ML) models based on resting-state functional MRI (Rs-fMRI) have been developed to facilitate differential diagnosis of mild cognitive impairment (MCI) and Alzheimer's disease (AD). However, the diagnostic accuracy of such models remains understudied. Therefore, we conducted this systematic review and meta-analysis to explore the diagnostic accuracy of Rs-fMRI-based radiomics in differentiating MCI from AD.PubMed, Embase, Cochrane, and Web of Science were searched from inception up to February 8, 2024, to identify relevant studies. Meta-analysis was conducted using a bivariate mixed-effects model, and sub-group analyses were carried out by the types of ML tasks (binary classification and multi-class classification tasks).In total, 23 studies, comprising 5,554 participants were enrolled in the study. In the binary classification tasks (twenty studies), the diagnostic accuracy of the ML model for AD was 0.99 (95%CI: 0.34 ~ 1.00), with a sensitivity of 0.94 (95%CI: 0.89 ~ 0.97) and a specificity of 0.98 (95%CI: 0.95 ~ 1.00). In the multi-class classification tasks (six studies), the diagnostic accuracy of the ML model was 0.98 (95%CI: 0.98 ~ 0.99) for NC, 0.96 (95%CI: 0.96 ~ 0.96) for early mild cognitive impairment (EMCI), 0.97 (95%CI: 0.96 ~ 0.97) for late mild cognitive impairment (LMCI), and 0.95 (95%CI: 0.95 ~ 0.95) for AD.The Rs-fMRI-based ML model can be adapted to multi-class classification tasks. Therefore, multi-center studies with large samples are needed to develop intelligent application tools to promote the development of intelligent ML models for disease diagnosis.Methods: Various machine learning (ML) models based on resting-state functional MRI (Rs-fMRI) have been developed to facilitate differential diagnosis of mild cognitive impairment (MCI) and Alzheimer's disease (AD). However, the diagnostic accuracy of such models remains understudied. Therefore, we conducted this systematic review and meta-analysis to explore the diagnostic accuracy of Rs-fMRI-based radiomics in differentiating MCI from AD.PubMed, Embase, Cochrane, and Web of Science were searched from inception up to February 8, 2024, to identify relevant studies. Meta-analysis was conducted using a bivariate mixed-effects model, and sub-group analyses were carried out by the types of ML tasks (binary classification and multi-class classification tasks).In total, 23 studies, comprising 5,554 participants were enrolled in the study. In the binary classification tasks (twenty studies), the diagnostic accuracy of the ML model for AD was 0.99 (95%CI: 0.34 ~ 1.00), with a sensitivity of 0.94 (95%CI: 0.89 ~ 0.97) and a specificity of 0.98 (95%CI: 0.95 ~ 1.00). In the multi-class classification tasks (six studies), the diagnostic accuracy of the ML model was 0.98 (95%CI: 0.98 ~ 0.99) for NC, 0.96 (95%CI: 0.96 ~ 0.96) for early mild cognitive impairment (EMCI), 0.97 (95%CI: 0.96 ~ 0.97) for late mild cognitive impairment (LMCI), and 0.95 (95%CI: 0.95 ~ 0.95) for AD.The Rs-fMRI-based ML model can be adapted to multi-class classification tasks. Therefore, multi-center studies with large samples are needed to develop intelligent application tools to promote the development of intelligent ML models for disease diagnosis.Findings: Various machine learning (ML) models based on resting-state functional MRI (Rs-fMRI) have been developed to facilitate differential diagnosis of mild cognitive impairment (MCI) and Alzheimer's disease (AD). However, the diagnostic accuracy of such models remains understudied. Therefore, we conducted this systematic review and meta-analysis to explore the diagnostic accuracy of Rs-fMRI-based radiomics in differentiating MCI from AD.PubMed, Embase, Cochrane, and Web of Science were searched from inception up to February 8, 2024, to identify relevant studies. Meta-analysis was conducted using a bivariate mixed-effects model, and sub-group analyses were carried out by the types of ML tasks (binary classification and multi-class classification tasks).In total, 23 studies, comprising 5,554 participants were enrolled in the study. In the binary classification tasks (twenty studies), the diagnostic accuracy of the ML model for AD was 0.99 (95%CI: 0.34 ~ 1.00), with a sensitivity of 0.94 (95%CI: 0.89 ~ 0.97) and a specificity of 0.98 (95%CI: 0.95 ~ 1.00). In the multi-class classification tasks (six studies), the diagnostic accuracy of the ML model was 0.98 (95%CI: 0.98 ~ 0.99) for NC, 0.96 (95%CI: 0.96 ~ 0.96) for early mild cognitive impairment (EMCI), 0.97 (95%CI: 0.96 ~ 0.97) for late mild cognitive impairment (LMCI), and 0.95 (95%CI: 0.95 ~ 0.95) for AD.The Rs-fMRI-based ML model can be adapted to multi-class classification tasks. Therefore, multi-center studies with large samples are needed to develop intelligent application tools to promote the development of intelligent ML models for disease diagnosis.Conclusions: Various machine learning (ML) models based on resting-state functional MRI (Rs-fMRI) have been developed to facilitate differential diagnosis of mild cognitive impairment (MCI) and Alzheimer's disease (AD). However, the diagnostic accuracy of such models remains understudied. Therefore, we conducted this systematic review and meta-analysis to explore the diagnostic accuracy of Rs-fMRI-based radiomics in differentiating MCI from AD.PubMed, Embase, Cochrane, and Web of Science were searched from inception up to February 8, 2024, to identify relevant studies. Meta-analysis was conducted using a bivariate mixed-effects model, and sub-group analyses were carried out by the types of ML tasks (binary classification and multi-class classification tasks).In total, 23 studies, comprising 5,554 participants were enrolled in the study. In the binary classification tasks (twenty studies), the diagnostic accuracy of the ML model for AD was 0.99 (95%CI: 0.34 ~ 1.00), with a sensitivity of 0.94 (95%CI: 0.89 ~ 0.97) and a specificity of 0.98 (95%CI: 0.95 ~ 1.00). In the multi-class classification tasks (six studies), the diagnostic accuracy of the ML model was 0.98 (95%CI: 0.98 ~ 0.99) for NC, 0.96 (95%CI: 0.96 ~ 0.96) for early mild cognitive impairment (EMCI), 0.97 (95%CI: 0.96 ~ 0.97) for late mild cognitive impairment (LMCI), and 0.95 (95%CI: 0.95 ~ 0.95) for AD.The Rs-fMRI-based ML model can be adapted to multi-class classification tasks. Therefore, multi-center studies with large samples are needed to develop intelligent application tools to promote the development of intelligent ML models for disease diagnosis. [ABSTRACT FROM AUTHOR]

The paper describes the structure and failure of toxic goods wagon. Furthermore, the connection and corrosion of the wagon sun shield were investigated on site. According to the field analysis, the aerodynamic model of a group of five vehicles was established, and the stress of the sun shield under the aerodynamic load was analyzed. The finite element model was built and the static simulation analysis of four kinds of working cases was carried out. Two kinds of sun shield specimens with different thickness were manufactured, and the wagon was tested under the normal bolt condition and missed bolts condition. Based on the above research, the paper proposes the optimized scheme. Finally, the connection scheme of the sun shield is modified. The modified sun shield works well in service. [ABSTRACT FROM AUTHOR]