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Abstract Background Limited attempts have been made in trans‐areola single‐site endoscopic thyroidectomy (TASSET) due to technical challenges and the lengthy time for proficiency. This study aimed to define the learning curve of TASSET and to describe improvements in operative performance over time. Methods Based on 222 consecutive TASSET procedures, the learning curve was established according to the operation time by using cumulative sum analysis (CUSUM). The end‐point of learning curve was defined as the number of cases necessitated to reach the initial surgical proficiency stage. The demographic information, surgical and oncological outcomes, surgical stress, and postoperative complications were also analyzed. Results There were 70 cases of simple lobectomy for benign nodules and 152 cases of lobectomy with central neck dissection (CND) for malignancy. The mean operative time was 106.54 ± 38.07 min (range: 46–274 min). The learning curve identified two phases: the skill acquisition phase (Case 1–Case 41) and the proficiency phase (Case 42–Case 222). There were no significant differences in demographic information, drainage amount and duration, oncological outcomes, and postoperative complications between the two phases (p > 0.05). Both operation time and postoperative hospitalization decreased significantly in Phase 2 (154.63 ± 52.21 vs. 95.64 ± 22.96 min, p more...

Abstract Accumulation of amyloid beta protein (Aβ) in brain vessels damages blood brain barrier (BBB) integrity in cerebral amyloid angiopathy (CAA). Macrophage lineage cells scavenge Aβ and produce disease-modifying mediators. Herein, we report that Aβ40-induced macrophage-derived migrasomes are sticky to blood vessels in skin biopsy samples from CAA patients and brain tissue from CAA mouse models (Tg-SwDI/B and 5xFAD mice). We show that CD5L is packed in migrasomes and docked to blood vessels, and that enrichment of CD5L impairs the resistance to complement activation. Increased migrasome-producing capacity of macrophages and membrane attack complex (MAC) in blood are associated with disease severity in both patients and Tg-SwDI/B mice. Of note, complement inhibitory treatment protects against migrasomes-mediated blood-brain barrier injury in Tg-SwDI/B mice. We thus propose that macrophage-derived migrasomes and the consequent complement activation are potential biomarkers and therapeutic targets in CAA. more...

In order to improve the precision of the micro-seismic hypocenter location and the robustness of algorithms, the objective function construction and spatiotemporal region information use of the location algorithm based on time are studied. The simulation experiment is based on Numpy, the perfect arrival times subjoining random disturbance is used to simulate production situation. Result shows that the L1 and L2 objective functions deviate from the hypocenter and the deviation is quite common. To alleviate the pseudo source problem, the likelihood function of arrival times deviation is used as the basic function, and the information of space-time neighborhood is then combined as the new objective function. The distribution of 4-dimension area algorithm (D4DA) reduces the positioning errors by 14% and 26% respectively in the two calibration gun positioning. more...

Improving slope stability is one of the important ways to ensure the safe operation of open pit coal mines and improve the resource recovery rate. Through Bishop’s analysis, the derivation of the expression of slope stability coefficient of replacement layer was carried out, and the influence of depth and height of replacement layer on slope stability coefficient was analyzed by combining Geo-Slope numerical simulation to verify the derivation. The study shows that: the influence of the replacement depth on the slope stability coefficient is not obvious before the contact between the replacement layer and the slip surface and after the contact part is unchanged, and the slope stability coefficient increases when the replacement depth supports the contact between the replacement layer and the slip surface; the influence of the replacement height on the slope stability coefficient is not obvious before the contact between the replacement layer and the slip surface before the contact between the replacement layer and the slip surface, the effect of the replacement height on the slope stability coefficient is not obvious, and after the contact between the replacement layer and the slip surface exists, the replacement height and the slope stability coefficient are positively related. more...

The traditional Mongolian medicine Erdun-Uril is a conventional combination of 29 herbs commonly used for the treatment of cerebrovascular ailments. It has the effects of reducing inflammation, counteracting oxidative stress, and averting strokes caused by persistent cerebral hypoperfusion. Prior research on Erdun-Uril has predominantly concentrated on its pharmacodynamics and mechanism of action; however, there has been a lack of systematic and comprehensive investigation into its chemical constituents. Therefore, it is crucial to establish an efficient and rapid method for evaluating the chemical constituents of Erdun-Uril. In this study, Erdun-Uril was investigated using UHPLC-Q-Exactive Orbitrap MS combined with parallel reaction monitoring for the first time. Eventually, a total of 237 compounds, including 76 flavonoids, 68 phenolic compounds, 19 alkaloids, 7 amino acids, etc., were identified based on the chromatographic retention time, bibliography data, MS/MS2 information, neutral loss fragments (NLFs), and diagnostic fragment ions (DFIs). And of these, 225 were reported for the first time in this study. This new discovery of these complex components would provide a reliable theoretical basis for the development of pharmacodynamics and quality standards of the Mongolian medicine Erdun-Uril. more...

Background: Type 2 diabetes mellitus (T2DM) is a metabolic syndrome characterized by chronic inflammation, insulin resistance, and islet cell damage. The prevention of T2DM and its associated complications is an urgent public health issue that affects hundreds of millions of people globally. Numerous studies suggest that disturbances in gut metabolites are important driving forces for the pathogenesis of diabetes. However, the functions and mechanisms of action of most commensal bacteria in T2DM remain largely unknown. Methods: The quantification of bile acids (BAs) in fecal samples was performed using ultra-performance liquid chromatography–tandem mass spectrometer (UPLC-MS/MS). The anti-diabetic effects of Bacteroides uniformis (B. uniformis) and its metabolites cholic acid (CA) and chenodeoxycholic acid (CDCA) were assessed in T2DM mice induced by streptozocin (STZ) plus high-fat diet (HFD). Results: We found that the abundance of B. uniformis in the feces and the contents of CA and CDCA were significantly downregulated in T2DM mice. B. uniformis was diminished in diabetic individuals and this bacterium was sufficient to promote the production of BAs. Colonization of B. uniformis and intragastric gavage of CA and CDCA effectively improved the disorder of glucose and lipid metabolism in T2DM mice by inhibiting gluconeogenesis and lipolysis in the liver. CA and CDCA improved hepatic glucose and lipid metabolism by acting on the Takeda G protein-coupled receptor 5 (TGR5)/adenosine monophosphate-activated protein kinase (AMPK) signaling pathway since knockdown of TGR5 minimized the benefit of CA and CDCA. Furthermore, we screened a natural product—vaccarin (VAC)—that exhibited anti-diabetic effects by promoting the growth of B. uniformis in vitro and in vivo. Gut microbiota pre-depletion abolished the favorable effects of VAC in diabetic mice. Conclusions: These data suggest that supplementation of B. uniformis may be a promising avenue to ameliorate T2DM by linking the gut and liver. more...

Tomato (Solanum lycopersicum L. cv. Zhongza NO. 9) was used as the experimental material to investigate the effects of nocturnal LED supplemental light with the photosynthetic photon flux density (PPFD) of 100, 200, 300 μmol·m−2·s−1, and the light time of 1, 2 h on the seedling quality in a controlled environment, with seedlings without nocturnal supplemental lighting serving as the control. The results demonstrate that an increase in PPFD at night progressively enhances the plant height and leaf number of tomato seedlings, while stem diameter and leaf area initially increase and subsequently decrease. Although light time and light period-of-time at night did not significantly affect seedling morphology, PPFD and light time notably influenced chlorophyll content and net photosynthetic rate. An optimal lighting energy amount at night augmented photosynthetic capacity. However, excessive PPFD induced photoinhibition in the leaves. Additionally, appropriate nocturnal LED supplemental lighting significantly improved the antioxidant capacity of the seedlings, increased proline content, reduced malondialdehyde content, and bolstered the self-protection mechanisms of the seedlings against nocturnal light stress. Both the PPFD and light time at night promoted biomass accumulation in tomato seedlings. Specifically, when supplemental lighting was applied for 2 h at an intensity of 200 μmol·m−2·s−1, both the fresh and dry weights of the shoot and root significantly increased, and the seedling health index was highest. Therefore, appropriate nocturnal LED supplemental lighting positively impacts the health index and photosynthate accumulation of tomato seedlings, but controlling PPFD is essential to avoid photoinhibition. more...

The study of fire simulation and emergency evacuation in cruise ships is a challenging aspect of cruise safety research. Investigating the impact of fire byproducts on passenger evacuation is a critical issue that urgently needs to be addressed. This paper utilizes PyroSim 2022 software to establish five fire cases, analysing the fire products concentration under each case. The influence of fire products on passenger evacuation was analysed using PathFinder. The results showed that when the fire source is in the stage area, the impact of fire byproducts on passenger evacuation is relatively minor. However, when the fire source is near the exit, especially in cases 1 and 2, fire byproducts tend to accumulate in the right area of the second floor, significantly affecting passenger evacuation. Moreover, during the evacuation process, a large number of passengers exhibit herd behaviour, leading to some passengers being unable to evacuate safely. To address the congestion issue, an optimized evacuation guidance plan is proposed, that can effectively improve evacuation efficiency and reduce the average congestion time per person. This has a positive role in enhancing the safety level of cruise ship fires. more...

This study sought to explore potential roles of endothelial ferroptosis in radiation-associated atherosclerosis (RAA) and molecular mechanisms behind this phenomenon. Here, an in vivo RAA mouse model was used and treated with ferroptosis inhibitors. We found that the RAA group had a higher plaque burden and a reduction in endothelial cells with increased lipid peroxidation compared to the control group, while ameliorated by liproxstatin-1. In vitro experiments further confirmed that radiation induced the occurrence of ferroptosis in human artery endothelial cells (HAECs). Then, proteomics analysis of HAECs identified domain-containing protein 2 (DDHD2) as a co-differentially expressed protein, which was enriched in the lipid metabolism pathway. In addition, the level of lipid peroxidation was elevated in DDHD2-knockdown HAECs. Mechanistically, a significant decrease in the protein and mRNA expression of glutathione peroxidase 4 (GPX4) was observed in HAECs following DDHD2 knockdown. Co-immunoprecipitation assays indicated a potential interaction between DDHD2 and nuclear factor erythroid 2-related factor 2 (Nrf2). The downregulation of Nrf2 protein was also detected in DDHD2-knockdown HAECs. In conclusion, our findings suggest that radiation-induced endothelial ferroptosis accelerates atherosclerosis, and DDHD2 is a potential regulatory protein in radiation-induced endothelial ferroptosis through the Nrf2/GPX4 pathway. more...

To achieve high-density tomato seedlings in a plant factory with artificial lighting, tomatoes (Solanum lycopersicum Mill. cv. “Zhongza NO.9”) were used as the experimental material. This study expected to analyze the effects of light intensity (150, 200, 250, and 300 μmol·m−2·s−1) and light time (12 and 14 h), as well as daily light integral (DLI, 10.80, 12.60, and 12.96 mol·m−2·d−1) and sowing density (50, 72, and 105 holes per tray), on seedling quality. The results indicated that biomass accumulation, seedling quality, and energy use efficiency of seedlings significantly improved with an increase in DLI. At a DLI of 12.96 mol·m−2·d−1, seedlings sown at a density of 72 holes per tray exhibited comparable growth characteristics and biomass accumulation to those sown at 50 holes per tray. However, under lower DLIs, seedlings at 50 holes per tray displayed superior growth morphology and seedling quality compared to those at 72 holes per tray. This indicates that increasing the DLI can partially mitigate the negative effects of higher sowing density on seedling quality. Light use efficiency (LUE) and energy use efficiency (EUE) were not significantly different between seedlings at 72 and 105 holes per tray but were higher than those at 50 holes per tray. Therefore, optimizing parameters such as DLI and sowing density can effectively enhance the seedling quality, spatial use efficiency, and light use efficiency in industrial seedling production. Based on the results of this study, a DLI of 12.96 mol·m−2·d−1 (achieved with a light intensity of 300 μmol·m−2·s−1 and a light time of 12 h) and sowing density of 72 holes per tray are recommended for cultivating high-quality tomato seedlings while reducing energy consumption. more...

Short-circuit impedance is an important economic and technical index to test the cost, efficiency and operation safety of transformers. Increasing the short-circuit impedance of the transformer can reduce the influence of the transformer fault current on the system. The short-circuit impedance of a general power transformer is 4~7%. When the short-circuit impedance is too small, the short-circuit current is too large, which will cause harm to electrical equipment. This paper proposes a method to adjust the short-circuit impedance by adding magnetic shunts of different thicknesses between the high and low voltage windings of the transformer. Compared with other methods, this method does not change the structure of the transformer core and winding, and is simple and efficient. In this paper, a three-dimensional simulation model of a single-phase multi-winding transformer is established by Altair Flux to study the influence of the thickness of magnetic shunts on the short-circuit impedance of a transformer. The feasibility of the proposed method is verified by comparing the simulation with the measured values. The magnetic shunt is also introduced into the three-phase transformer. The result shows that adding magnetic shunts of different thicknesses between the high and low voltage windings of the transformer will change the distribution and size of the leakage of the magnetic field. The short-circuit impedance increases significantly with the increase in the thickness of the magnetic shunt, but a certain number of magnetic shunts have minimal effects on the efficiency of the transformer. more...

The incidence of thyroid cancer is increasing worldwide. Fine-needle aspiration (FNA) cytology is widely applied with the use of extracted biological cell samples, but current FNA cytology is labor-intensive, time-consuming, and can lead to the risk of false-negative results. Surface-enhanced Raman spectroscopy (SERS) combined with machine learning algorithms holds promise for cancer diagnosis. In this study, we develop a label-free SERS liquid biopsy method with machine learning for the rapid and accurate diagnosis of thyroid cancer by using thyroid FNA washout fluids. These liquid supernatants are mixed with silver nanoparticle colloids, and dispersed in quartz capillary for SERS measurements to discriminate between healthy and malignant samples. We collect Raman spectra of 36 thyroid FNA samples (18 malignant and 18 benign) and compare four classification models: Principal Component Analysis–Linear Discriminant Analysis (PCA-LDA), Random Forest (RF), Support Vector Machine (SVM), and Convolutional Neural Network (CNN). The results show that the CNN algorithm is the most precise, with a high accuracy of 88.1%, sensitivity of 87.8%, and the area under the receiver operating characteristic curve of 0.953. Our approach is simple, convenient, and cost-effective. This study indicates that label-free SERS liquid biopsy assisted by deep learning models holds great promise for the early detection and screening of thyroid cancer. more...

This article aims to explore the most optimal pulsed laser energy density when using the pulsed laser deposition (PLD) process to prepare the MoS2 films. We gradually increased the pulsed laser energy density from 70 mJ·cm−2 to 110 mJ·cm−2 and finally determined that 100 mJ·cm−2 was the best-pulsed laser energy density for MoS2 films by PLD. The surface morphology and crystallization of the MoS2 films prepared under this condition are the best. The films consist of a high-crystallized 2H-MoS2 phase with strong (002) preferential orientation, and their direct optical band gap (Eg) is 1.614 eV. At the same time, the Si/MoS2 heterojunction prepared under the optimal pulsed laser energy density shows an opening voltage of 0.61 V and a rectification ratio of 457.0. more...

Background: Liver hepatocellular carcinoma (LIHC) is a solid primary malignancy with poor prognosis. This study discovered key prognostic genes based on T cell exhaustion and used them to develop a prognostic prediction model for LIHC. Methods: SingleR's annotations combined with Seurat was used to automatically annotate the single-cell clustering results of the LIHC dataset GSE166635 downloaded from the Gene Expression Omnibus (GEO) database and to identify clusters related to exhausted T cells. Patients were classified using ConsensusClusterPlus package. Next, weighted gene co-expression network analysis (WGCNA) package was employed to distinguish key gene module, based on which least absolute shrinkage and selection operator (Lasso) and multi/univariate cox analysis were performed to construct a RiskScore system. Kaplan-Meier (KM) analysis and receiver operating characteristic curve (ROC) were employed to evaluate the efficacy of the model. To further optimize the risk model, a nomogram capable of predicting immune infiltration and immunotherapy sensitivity in different risk groups was developed. Expressions of genes were measured by quantitative real-time polymerase chain reaction (qRT-PCR), and immunofluorescence and Cell Counting Kit-8 (CCK-8) were performed for analyzing cell functions. Results: We obtained 18,413 cells and clustered them into 7 immune and non-immune cell subpopulations. Based on highly variable genes among T cell exhaustion clusters, 3 molecular subtypes (C1, C2 and C3) of LIHC were defined, with C3 subtype showing the highest score of exhausted T cells and a poor prognosis. The Lasso and multivariate cox analysis selected 7 risk genes from the green module, which were closely associated with the C3 subtype. All the patients were divided into low- and high-risk groups based on the medium value of RiskScore, and we found that high-risk patients had higher immune infiltration and immune escape and poorer prognosis. The nomogram exhibited a strong performance for predicting long-term LIHC prognosis. In vitro experiments revealed that the 7 risk genes all had a higher expression in HCC cells, and that both liver HCC cell numbers and cell viability were reduced by knocking down MMP-9. Conclusion: We developed a RiskScore model for predicting LIHC prognosis based on the scRNA-seq and RNA-seq data. The RiskScore as an independent prognostic factor could improve the clinical treatment for LIHC patients. more...

Plant species loss, driven by global changes and human activities, can have cascading effects on other trophic levels, such as arthropods, and alter the multitrophic structure of ecosystems. While the relationship between plant diversity and arthropod communities has been well-documented, few studies have explored the effects of species composition variation or plant functional groups. In this study, we conducted a long-term plant removal experiment to investigate the impact of plant functional group loss (specifically targeting tall grasses and sedges, as well as tall or short forbs) on arthropod diversity and their functional groups. Our findings revealed that the removal of plant functional groups resulted in increased arthropod richness, abundance and the exponential of Shannon entropy, contrary to the commonly observed positive correlation between plant diversity and consumer diversity. Furthermore, the removal of different plant groups had varying impacts on arthropod trophic levels. The removal of forbs had a more pronounced impact on herbivores compared to graminoids, but this impact did not consistently cascade to higher-trophic arthropods. Notably, the removal of short forbs had a more significant impact on predators, as evidenced by the increased richness, abundance, the exponential of Shannon entropy, inverse Simpson index and inverse Berger-Parker index of carnivores and abundance of omnivores, likely attributable to distinct underlying mechanisms. Our results highlight the importance of plant species identity in shaping arthropod communities in alpine grasslands. This study emphasizes the crucial role of high plant species diversity in controlling arthropods in natural grasslands, particularly in the context of plant diversity loss caused by global changes and human activities. more...

The dried root of Sophora davidii Kom. ex Pavol (Leguminosae, family) is a folk medicine and has long been used for the treatment of various diseases, including cough, hematochezia, sore throat, and dysentery. In this study, UHPLC-Q-Exactive Orbitrap mass spectrometry investigations were applied to obtain the profiling of the flavonoids in S. davidii. Finally, 108 compounds were identified, and 85 of them were firstly reported. Then, the in vitro antioxidant activity and tyrosinase activity of S. davidii were investigated using the DPPH radical scavenging ability, hydroxyl radical scavenging, and copper-reducing ability method and by measuring the rate of tyrosinase-catalyzed L-dopa oxidation. To our knowledge, this is the first study of S. davidii’s antioxidant activity, anti-tyrosinase activity, and systematic characterization of flavonoids. The current study will be of support for the usage of S. davidii in the future development of the pharmaceutical industry. more...

Qingqiao Kangdu granule (QQKDG), a traditional Chinese medicine (TCM), has been used clinically to treat various viral diseases, including flu, mumps, and viral hepatitis, owing to its abundant bioactivities. Nevertheless, the chemical components of QQKDG have not been sufficiently elucidated; consequently, the development of standards for quality evaluation and complete understanding of the pharmacological mechanisms of action are hindered. Therefore, a systematic approach must be developed to efficiently discover novel compounds and advance pharmacological research. In this regard, this study proposed an integrated strategy for the comprehensive characterization of the chemical components in QQKDG by UHPLC-Q-Exactive-MS coupled with feature-based molecular networking (FBMN) to improve annotation accuracy and achieve visualization. First, the chromatographic and mass spectrum conditions were optimized to obtain good separation and abundant signal response. Subsequently, an in-house library was established by searching for relevant literature to improve annotation confidence. Finally, the raw data acquired under optimized conditions were uploaded to the FBMN to achieve component visualization by connecting precursor ions of the same color, in which compounds have similar structural features. Thus, a total of 231 compounds, including 89 flavonoids, 36 phenolic acids, 26 phenylethanoid glycosides, 23 coumarins, 17 chlorogenic acid derivatives, 14 terpenoids, 10 alkaloids, 10 lignans and 6 other compounds, were characterized, and numerous novel compounds with new structures were explored. Thus, this study provides a strategy for comprehensive characterization, which can also be applied to other TCMs. more...

BackgroundUp to 45.9% of polyps are missed during colonoscopy, which is the major cause of post-colonoscopy colorectal cancer (CRC). Computer-aided detection (CADe) techniques based on deep learning might improve endoscopists’ performance in detecting polyps. We aimed to evaluate the effectiveness of the CADe system in assisting endoscopists in a real-world clinical setting.MethodsThe CADe system was trained to detect colorectal polyps, recognize the ileocecal region, and monitor the speed of withdrawal during colonoscopy in real-time. Between 17 January 2021 and 16 July 2021. We recruited consecutive patients aged 18–75 years from three centers in China. We randomized patients in 1:1 groups to either colonoscopy with the CADe system or unassisted (control). The primary outcomes were the sensitivity and specificity of the endoscopists. We used subgroup analysis to examine the polyp detection rate (PDR) and the miss detection rate of endoscopists.ResultsA total of 1293 patients were included. The sensitivity of the endoscopists in the experimental group was significantly higher than that of the control group (84.97 vs. 72.07%, p < 0.001), and the specificity of the endoscopists in these two groups was comparable (100.00 vs. 100.00%). In a subgroup analysis, the CADe system improved the PDR of the 6–9 mm polyps (18.04 vs. 13.85%, p < 0.05) and reduced the miss detection rate, especially at 10:00–12:00 am (12.5 vs. 39.81%, p < 0.001).ConclusionThe CADe system can potentially improve the sensitivity of endoscopists in detecting polyps, reduce the missed detection of polyps in colonoscopy, and reduce the risk of CRC.RegistrationThis clinical trial was registered with the Chinese Clinical Trial Registry (Trial Registration Number: ChiCTR2100041988).Clinical trial registrationwebsite www.chictr.org.cn, identifier ChiCTR2100041988. more...

R-spondin 1 (RSPO1), which encodes a secretory-activating protein, is a promising therapeutic target for various tumors. The aim of this study was to establish a robust RSPO1-related signature specific to esophageal cancer (ESCA). Our comprehensive study involved meticulous analysis of RSPO1 expression in ESCA tissues and validation across ESCA cell lines and clinical samples using The Cancer Genome Atlas (TCGA) and GTEx databases. Using TCGA-ESCA dataset, we employed single-sample gene set enrichment analysis (ssGSEA) to elucidate the complex interaction between RSPO1 expression and the abundance of 22 specific immune cell types infiltrating ESCA. The biological significance of RSPO1 was further elucidated using KEGG, GO, and GSEA, demonstrating its relevance to pivotal tumor and immune pathways. This study culminated in the construction of prognostic nomograms enriched by calibration curves, facilitating the projection of individual survival probabilities at intervals of one, three, and five years. A substantial decrease in RSPO1 expression was observed within ESCA tissues and cell lines compared to their normal esophageal counterparts, and a significant decrease in the proportion of activated dendritic cells was evident within ESCA, accompanied by an augmented presence of macrophages and naive B cells relative to normal tissue. GSEA and KEGG analyses showed that RSPO1 was associated with tumor and immune pathways. Additionally, an independent prognostic risk score based on the RSPO1-related gene signature was developed and validated for patients with ESCA. Finally, RT-qPCR and western blotting were performed to confirm RSPO1 expression in normal and ESCA cell lines and tissue samples. In summary, our investigation underscores the pivotal role of RSPO1 in orchestrating tumor immunity and proposes RSPO1 as a prospective target for immunotherapeutic interventions in ESCA. Furthermore, the intricate profile of the two RSPO1-related genes has emerged as a promising predictive biomarker with notable potential for application in ESCA. more...

The number of dispersion curves increases significantly when the scale of a short-period dense array increases. Owing to a substantial increase in data volume, it is important to quickly evaluate dispersion curve quality as well as select the available dispersion curve. Accordingly, this study quantitatively evaluated dispersion curve quality by training a convolutional neural network model for ambient noise tomography using a short-period dense array. The model can select high-quality dispersion curves that exhibit a ≤ 10% difference between the results of manual screening and the proposed model. In addition, this study established a dispersion curve loss function by analyzing the quality of the dispersion curve and the corresponding influencing factors, thereby estimating the number of available dispersion curves for the existing observation systems. Furthermore, a Monte Carlo simulation experiment is used to illustrates the station-pair interval distance probability density function, which is independent of station number in the observational system with randomly deployed stations. The results suggested that the straight-line length should exceed 15 km to ensure that loss rate of dispersion curves remains < 0.5, while maintaining the threshold ambient noise tomography accuracy within the study area. more...

Small auxin up RNA (SAUR) is a large gene family that is widely distributed among land plants. In this study, a comprehensive analysis of the SAUR family was performed in sweet cherry, and the potential biological functions of PavSAUR55 were identified using the method of genetic transformation. The sweet cherry genome encodes 86 SAUR members, the majority of which are intron-less. These genes appear to be divided into seven subfamilies through evolution. Gene duplication events indicate that fragment duplication and tandem duplication events occurred in the sweet cherry. Most of the members mainly underwent purification selection pressure during evolution. During fruit development, the expression levels of PavSAUR16/45/56/63 were up-regulated, and conversely, those of PavSAUR12/61 were down-regulated. Due to the significantly differential expressions of PavSAUR13/16/55/61 during the fruitlet abscission process, they might be the candidate genes involved in the regulation of physiological fruit abscission in sweet cherry. Overexpression of PavSAUR55 in Arabidopsis produced earlier reproductive growth, root elongation, and delayed petal abscission. In addition, this gene did not cause any change in the germination time of seeds and was able to increase the number of lateral roots under abscisic acid (ABA) treatment. The identified SAURs of sweet cherry play a crucial role in fruitlet abscission and will facilitate future insights into the mechanism underlying the heavy fruitlet abscission that can occur in this fruit crop. more...

Abstract The employment of stem cells and hydrogel is widespread in contemporary clinical approaches to treating diabetic foot ulcers. However, the hypoxic conditions in the surrounding lesion tissue lead to a low stem cell survival rate following transplantation. This research introduces a novel hydrogel with superior oxygen permeability and biocompatibility, serving as a vehicle for developing a stem cell transplantation system incorporating oxygen-releasing microspheres and cardiosphere-derived stem cells (CDCs). By optimizing the peroxidase fixation quantity on the microsphere surface and the oxygen-releasing microsphere content within the transplantation system, intracellular oxygen levels were assessed using electron paramagnetic resonance (EPR) under simulated low-oxygen conditions in vitro. The expression of vascularization and repair-related indexes were evaluated via RT-PCR and ELISA. The microspheres were found to continuously release oxygen for three weeks within the transplantation system, promoting growth factor expression to maintain intracellular oxygen levels and support the survival and proliferation of CDCs. Moreover, the effect of this stem cell transplantation system on wound healing in a diabetic foot mice model was examined through an in vivo animal experiment. The oxygen-releasing microspheres within the transplantation system preserved the intracellular oxygen levels of CDCs in the hypoxic environment of injured tissues. By inhibiting the expression of inflammatory factors and stimulating the upregulation of pertinent growth factors, it improved the vascularization of ulcer tissue on the mice’s back and expedited the healing of the wound site. Overall, the stem cell transplantation system in this study, based on hydrogels containing CDCs and oxygen-releasing microspheres, offers a promising strategy for the clinical implementation of localized stem cell delivery to improve diabetic foot wound healing. more...

Abstract Background Skip metastasis is a special type of lateral lymph node metastasis, which is not classified definitely by the eighth edition of the AJCC TNM staging system. The aim of the research was to study the prognosis of skip metastasis in PTC patients, and carry out a more appropriate N staging for skip metastasis. Methods Study subjects were 3167 patients with papillary thyroid carcinoma (PTC), who underwent thyroidectomy at three clinical centers from 2016 to 2019. We identified two well‐balanced cohorts matched on the basis of propensity score. Results During a median follow‐up of 42 months, recurrence occurred in 68 (4.3%) patients with lymph node metastasis. 34 cases recurred in 1120 patients with central lymph node metastasis (N1a), and 34 recurred in 461 patients with lateral lymph node metastasis (N1b), among which 73 patients were diagnosis with skip metastasis. The RFS of N1a was significantly lower than that of N1b (p more...

Background: Before the COVID-19 pandemic, acute respiratory infections (ARIs) in children were mainly characterised by three pathogens: respiratory syncytial viruses (RSV), influenza viruses and rhinoviruses. The impact of the COVID-19 pandemic and the measures taken in Germany (especially until the end of 2021) on the incidence of ARI in children and adolescents aged 0 to 14 years and the pathogens causing them has not yet been comprehensively analysed. Methods: The evaluation is based on data from population-based, virological and hospital-based surveillance instruments up to the end of 2022. Results: After the onset of the COVID-19 pandemic in early 2020, ARI rates remained almost consistently below prepandemic levels until autumn 2021, with only rhinoviruses continuously continuing to cause ARI. Only when the Omicron variant became predominant in 2022, there were measurable COVID-19 rates at population level in children, although COVID-19 hospitalisation rates remained comparatively low. RSV and influenza waves were initially absent and then occurred ‘out of season’, but were more severe than usual. Conclusions: While the measures taken were effective in inhibiting the number of respiratory infections for almost 1.5 years, moderately frequent but rather mild COVID-19 cases occurred when measures were lifted. When Omicron emerged in 2022 COVID-19 became moderately frequent but led predominantly to mild illnesses. For RSV and influenza, the measures resulted in changes in their annual timing and intensity. more...

Because structural parameter matching has a strong influence on the service behavior of planetary roller screw mechanisms (PRSM), understanding how to effectively design the structural parameters of PRSM is highly important in practical industrial applications. This study proposes a parameter optimization model based on a crow search algorithm (CSA) to solve the structural parameter matching problem of PRSM. The relationship between the main structural parameters of PRSM can be deduced according to the working principle and geometric conditions. The screw, roller, and nut space spiral surface equation are established by considering the influence of the meshing point position of PRSM on thread meshing clearance. The relationship between the meshing point position and PRSM tooth thickness is obtained using the tangent contact condition of the spiral surface. To achieve no backlash meshing and improve PRSM transmission accuracy, the thread tooth thickness of the screw, roller, and nut can be adjusted. According to the meshing relationship between the thread pair and the gear pair of PRSM, the structural parameters of the annular gear and the gear at the end of the roller are determined. The normal vectors at the meshing point of the screw, roller, and nut are calculated using space spiral surface equations. To test the strength of the PRSM, static analysis of the roller is used to deduce the force relations between the main parts of the PRSM. PRSM structural parameters serve as design variables. An optimization goal is to reduce the outer diameter of the nut, the nominal diameter of the screw, and the length of the roller. The spatial structure constraints and component strength constraints of PRSM are considered. The CSA was introduced to be the optimization algorithm. The parameter optimization model of PRSM is established for achieving optimum matching of the optimization variables. Finally, using the proposed optimization model, three groups of PRSM structural parameters are obtained for three different types of load. In this study, the optimization results are compared with a foreign PRSM product manual to validate the effectiveness of the optimization model. The results show that the PRSM structural parameters obtained from the proposed model are essentially consistent with those from the foreign PRSM product manual. Furthermore, the proposed model provides the structural parameters of thread teeth, which are not included in the foreign product manual. The proposed PRSM optimization model is promising for its application in actual production. more...

With limited number of labeled samples, hyperspectral image (HSI) classification is a difficult Problem in current research. The graph neural network (GNN) has emerged as an approach to semi-supervised classification, and the application of GNN to hyperspectral images has attracted much attention. However, in the existing GNN-based methods a single graph neural network or graph filter is mainly used to extract HSI features, which does not take full advantage of various graph neural networks (graph filters). Moreover, the traditional GNNs have the problem of oversmoothing. To alleviate these shortcomings, we introduce a deep hybrid multi-graph neural network (DHMG), where two different graph filters, i.e., the spectral filter and the autoregressive moving average (ARMA) filter, are utilized in two branches. The former can well extract the spectral features of the nodes, and the latter has a good suppression effect on graph noise. The network realizes information interaction between the two branches and takes good advantage of different graph filters. In addition, to address the problem of oversmoothing, a dense network is proposed, where the local graph features are preserved. The dense structure satisfies the needs of different classification targets presenting different features. Finally, we introduce a GraphSAGE-based network to refine the graph features produced by the deep hybrid network. Extensive experiments on three public HSI datasets strongly demonstrate that the DHMG dramatically outperforms the state-of-the-art models. more...