The force-dependent filamin A-G3BP1 interaction regulates phase-separated stress granule formation.

Filamin A (FLNA) is an actin crosslinking protein that mediates mechanotransduction. External and internal mechanical forces, through the actin cytoskeleton, can induce conformational changes of the FLNA molecule to expose cryptic binding sites for its binding partners. Here, we identified Ras GTPase-activating protein SH3 domain-binding protein 1 (G3BP1) as a new FLNA mechanobinding partner. Unlike other FLNA binding partners to the mechanosensing domain repeat 21 (R21), G3BP1 requires an additional neighboring repeat R22 to interact. We demonstrated that their interaction occurs in the cytosol of living cells in an actin polymerization-dependent manner. We also mapped the FLNA-binding site on G3BP1 and found that a F360A point mutation in the RNA recognition motif disrupts the interaction. RNA interfered with the FLNA-G3BP1 interaction, and FLNA did not localize in RNA-rich stress granules (SGs). Disruption of the interaction was sufficient to promote phase-separated SG formation, and arsenite treatment further stimulated the formation of SGs. Taken together, these data identify G3BP1 as a new mechanobinding protein that interacts with the FLNA mechanosensing domain R21 and suggest that SG formation is partially regulated by mechanical force.

Mutual upregulation of HY5 and TZP in mediating phytochrome A signaling.

Phytochrome A (phyA) is the far-red (FR) light photoreceptor in plants that is essential for seedling de-etiolation under FR-rich environments, such as canopy shade. TANDEM ZINC-FINGER/PLUS3 (TZP) was recently identified as a key component of phyA signal transduction in Arabidopsis thaliana; however, how TZP is integrated into the phyA signaling networks remains largely obscure. Here, we demonstrate that ELONGATED HYPOCOTYL5 (HY5), a well-characterized transcription factor promoting photomorphogenesis, mediates FR light induction of TZP expression by directly binding to a G-box motif in the TZP promoter. Furthermore, TZP physically interacts with CONSTITUTIVE PHOTOMORPHOGENIC1 (COP1), an E3 ubiquitin ligase targeting HY5 for 26S proteasome-mediated degradation, and this interaction inhibits COP1 interaction with HY5. Consistent with those results, TZP post-translationally promotes HY5 protein stability in FR light, and in turn, TZP protein itself is destabilized by COP1 in both dark and FR light conditions. Moreover, tzp hy5 double mutants display an additive phenotype relative to their respective single mutants under high FR light intensities, indicating that TZP and HY5 also function in largely independent pathways. Together, our data demonstrate that HY5 and TZP mutually upregulate each other in transmitting the FR light signal, thus providing insights into the complicated but delicate control of phyA signaling networks.

Electron Reservoir Effect of Adjacent Fe Nanoclusters Boosts Atomic Fe Active Sites on Porous Carbon for the Both Electrocatalytic Oxygen Reduction and CO2 Reduction Reaction.

Electrochemical oxygen reduction reaction (ORR) and carbon dioxide reduction reaction (CO2RR) are greatly significant in renewable energy-related devices and carbon-neutral closed cycle, while the development of robust and highly efficient electrocatalysts has remained challenges. Herein, a hybrid electrocatalyst, featuring axial N-coordinated Fe single atom sites on hierarchically N, P-codoped porous carbon support and Fe nanoclusters as electron reservoir (FeNCs/FeSAs-NPC), is fabricated via in situ thermal transformation of the precursor of a supramolecular polymer initiated by intermolecular hydrogen bonds co-assembly. The FeNCs/FeSAs-NPC catalyst manifests superior oxygen reduction activity with a half-wave potential of 0.91 V in alkaline solution, as well as high CO2 to CO Faraday efficiency (FE) of surpassing 90% in a wide potential window from -0.40 to -0.85 V, along with excellent electrochemical durability. Theoretical calculations indicate that the electron reservoir effect of Fe nanoclusters can trigger the electron redistribution of the atomic Fe moieties, facilitating the activation of O2 and CO2 molecules, lowering the energy barriers for rate-determining step, and thus contributing to the accelerated ORR and CO2RR kinetics. This work offers an effective design of electron coupling catalysts that have advanced single atoms coexisting with nanoclusters for efficient ORR and CO2RR.

Bilinear Distance Feature Network for Semantic Segmentation in PowerLine Corridor Point Clouds.

Semantic segmentation of target objects in power transmission line corridor point cloud scenes is a crucial step in powerline tree barrier detection. The massive quantity, disordered distribution, and non-uniformity of point clouds in power transmission line corridor scenes pose significant challenges for feature extraction. Previous studies have often overlooked the core utilization of spatial information, limiting the network's ability to understand complex geometric shapes. To overcome this limitation, this paper focuses on enhancing the deep expression of spatial geometric information in segmentation networks and proposes a method called BDF-Net to improve RandLA-Net. For each input 3D point cloud data, BDF-Net first encodes the relative coordinates and relative distance information into spatial geometric feature representations through the Spatial Information Encoding block to capture the local spatial structure of the point cloud data. Subsequently, the Bilinear Pooling block effectively combines the feature information of the point cloud with the spatial geometric representation by leveraging its bilinear interaction capability thus learning more discriminative local feature descriptors. The Global Feature Extraction block captures the global structure information in the point cloud data by using the ratio between the point position and the relative position, so as to enhance the semantic understanding ability of the network. In order to verify the performance of BDF-Net, this paper constructs a dataset, PPCD, for the point cloud scenario of transmission line corridors and conducts detailed experiments on it. The experimental results show that BDF-Net achieves significant performance improvements in various evaluation metrics, specifically achieving an OA of 97.16%, a mIoU of 77.48%, and a mAcc of 87.6%, which are 3.03%, 16.23%, and 18.44% higher than RandLA-Net, respectively. Moreover, comparisons with other state-of-the-art methods also verify the superiority of BDF-Net in point cloud semantic segmentation tasks.

A 3D-printed flow-cell for on-grid purification of electron microscopy samples directly from lysate.

While recent advances in cryo-EM, coupled with single particle analysis, have the potential to allow structure determination in a near-native state from vanishingly few individual particles, this vision has yet to be realised in practise. Requirements for particle numbers that currently far exceed the theoretical lower limits, challenges with the practicalities of achieving high concentrations for difficult-to-produce samples, and inadequate sample-dependent imaging conditions, all result in significant bottlenecks preventing routine structure determination using cryo-EM. Therefore, considerable efforts are being made to circumvent these bottlenecks by developing affinity purification of samples on-grid; at once obviating the need to produce large amounts of protein, as well as more directly controlling the variable, and sample-dependent, process of grid preparation. In this proof-of-concept study, we demonstrate a further practical step towards this paradigm, developing a 3D-printable flow-cell device to allow on-grid affinity purification from raw inputs such as whole cell lysates, using graphene oxide-based affinity grids. Our flow-cell device can be interfaced directly with routinely-used laboratory equipment such as liquid chromatographs, or peristaltic pumps, fitted with standard chromatographic (1/16") connectors, and can be used to allow binding of samples to affinity grids in a controlled environment prior to the extensive washing required to remove impurities. Furthermore, by designing a device which can be 3D printed and coupled to routinely used laboratory equipment, we hope to increase the accessibility of the techniques presented herein to researchers working towards single-particle macromolecular structures.

Direction of Arrival Estimation and Highlighting Characteristics of Testing Wideband Echoes from Multiple Autonomous Underwater Vehicles.

Multiple autonomous underwater vehicles (AUVs) have gradually become the trend in underwater operations. Identifying and detecting these new underwater multi-targets is difficult when studying underwater moving targets. A 28-element transducer is used to test the echo of multiple AUVs with different layouts in a lake. The characteristics of the wideband echo signals are studied. Under the condition that the direction of arrival (DOA) is not known, an autofocus coherent signal subspace (ACCSM) method is proposed. The focusing matrix is constructed based on the received data. The spatial spectrum of the array signal of multiple AUVs at different attitudes is calculated. The algorithm estimates the DOA of the echo signals to overcome the shortcomings of traditional wideband DOA estimation and improve its accuracy. The results show that the highlights are not only related to the number of AUVs, but are also modified by scale and attitude. The contribution of the microstructure of the target in the overall echo cannot be ignored. Different parts of the target affect the number of highlights, thus resulting in varying numbers of highlights at different attitude angle intervals. The results have significant implications for underwater multi-target recognition.

The relationship between culture-related grief beliefs, prolonged grief disorder and suicide ideation among Shidu parents in rural China.

BACKGROUND: There are many one-child families in China due to the one-child policy. Parents who have lost their only child and are unable to conceive another child or unwilling to adopt a child are called Shidu parents in China. The death of an only child puts Shidu parents at the risk of mental illness and even suicide. Few studies have explored the influence of cultural beliefs and prolonged grief disorder on suicide ideation. METHODS: This study involved rural Shidu parents from Sujiatun district of Shenyang, China. Questionnaires consisted of the Prolonged Grief questionnaire - 13 (PG-13), the Culture-related Grief Beliefs of Shidu Parents Questionnaire (CBSQ), one question from the baseline National Comorbidity Survey (NCS) to measure suicide ideation and demographic and bereavement-related information. Bivariate logistic regression analyses were conducted to explore associated factors of suicide ideation. RESULTS: Sixty-nine (28.8%) of the 240 Shidu parents reported having suicide ideation. Having chronic disease (OR = 5.509, p < 0.01), having religious belief (OR = 3.923, p < 0.05) and having a grandchild (OR = 2.552, p < 0.05) were associated with an increased risk of suicide ideation. Destiny belief (a subscale of CBSQ) was negatively associated with suicide ideation (OR = 0.818, p < 0.05). Prolonged grief disorder (OR = 9.280, p < 0.01) and perceived stigma (a subscale of CBSQ) (OR = 1.200, p < 0.05) was positively associated with suicide ideation after adjusting for controlling variables. CONCLUSIONS: Suicide ideation is prevalent in rural Shidu parents. Reducing perceived stigma and alleviating prolonged grief disorder may decrease the risk of suicide among rural Shidu parents.

Mobile phone addiction and depression among Chinese medical students: the mediating role of sleep quality and the moderating role of peer relationships.

The literature has shown that mobile phone addiction is an important risk factor for depression. However, the internal mechanisms of mobile phone addiction leading to depression are still not clear. This study examined the mediating role of sleep quality and moderating role of peer relationships in the association between mobile phone addiction and depression. A sample of 450 Chinese medical students were recruited to complete measures of mobile phone addiction, depression, sleep quality and peer relationships. In this study, SPSS 25.0 and macro PROCESS were used to conduct statistical analysis on the collected data. The results showed that sleep quality partially mediated the association between mobile phone addiction and depression. Moreover, the effect of sleep quality on depression was moderated by peer relationships. The present study can advance our understanding of how and when mobile phone addiction leads to depression. Limitations and implications of this study are discussed.

Synthesis of Zn2+-Pre-Intercalated V2O5·nH2O/rGO Composite with Boosted Electrochemical Properties for Aqueous Zn-Ion Batteries.

Layered vanadium-based materials are considered to be great potential electrode materials for aqueous Zn-ion batteries (AZIBs). The improvement of the electrochemical properties of vanadium-based materials is a hot research topic but still a challenge. Herein, a composite of Zn-ion pre-intercalated V2O5·nH2O combined with reduced graphene oxide (ZnVOH/rGO) is synthesized by a facile hydrothermal method and it shows improved Zn-ion storage. ZnVOH/rGO delivers a capacity of 325 mAh·g-1 at 0.1 A·g-1, and this value can still reach 210 mAh·g-1 after 100 cycles. Additionally, it exhibits 196 mAh·g-1 and keeps 161 mAh·g-1 after 1200 cycles at 4 A·g-1. The achieved performances are much higher than that of ZnVOH and VOH. All results reveal that Zn2+ as "pillars" expands the interlayer distance of VOH and facilitates the fast kinetics, and rGO improves the electron flow. They both stabilize the structure and enhance efficient Zn2+ migration. All findings demonstrate ZnVOH/rGO's potential as a perspective cathode material for AZIBs.

TANDEM ZINC-FINGER/PLUS3 Is a Key Component of Phytochrome A Signaling.

Phytochrome A (phyA) is the primary plant photoreceptor responsible for perceiving and mediating various responses to far-red (FR) light and is essential for survival in canopy shade. In this study, we identified two Arabidopsis thaliana mutants that grew longer hypocotyls in FR light. Genetic analyses showed that they were allelic and their FR phenotypes were caused by mutations in the gene named TANDEM ZINC-FINGER/PLUS3 (TZP), previously shown to encode a nuclear protein involved in blue light signaling and phyB-dependent regulation of photoperiodic flowering. We show that the expression of TZP is dramatically induced by light and that TZP proteins are differentially modified in different light conditions. Furthermore, we show that TZP interacts with both phyA and FAR-RED ELONGATED HYPOCOTYL1 (FHY1) and regulates the abundance of phyA, FHY1, and ELONGATED HYPOCOTYL5 proteins in FR light. Moreover, our data indicate that TZP is required for the formation of a phosphorylated form of phyA in the nucleus in FR light. Together, our results identify TZP as a positive regulator of phyA signaling required for phosphorylation of the phyA photoreceptor, thus suggesting an important role of phosphorylated phyA in inducing the FR light response.

DGCR8/ZFAT-AS1 Promotes CDX2 Transcription in a PRC2 Complex-Dependent Manner to Facilitate the Malignant Biological Behavior of Glioma Cells.

Studies have found that RNA-binding proteins (RBPs) and long non-coding RNAs (lncRNAs) are dysregulated and play an important regulatory role in the development of tumors. Based on The Cancer Genome Atlas (TCGA) database, our findings from experiments, and the evidence of previous studies, we screened DiGeorge syndrome critical region gene 8 (DGCR8), ZFAT antisense RNA 1 (ZFAT-AS1), and caudal type homeobox 2 (CDX2) as research candidates. In the present study, DGCR8 and CDX2 were highly expressed and ZFAT-AS1 was markedly downregulated in glioma tissues and cells. DGCR8 or CDX2 knockdown or ZFAT-AS1 overexpression suppressed glioma cell proliferation, migration, and invasion and facilitated apoptosis. DGCR8 might decrease ZFAT-AS1 expression by attenuating its stability in a manner of inducing its cleavage. Importantly, ZFAT-AS1 could inhibit CDX2 transcription by mediating the methylation of histone H3 on lysine 27 (H3K27me3) modification induced by PRC2 in the CDX2 promoter region. In addition, CDX2 transcriptionally activated DGCR8 expression by binding to its promoter regions, forming a positive feedback loop of DGCR8/ZFAT-AS1/CDX2. In conclusion, DGCR8/ZFAT-AS1 promotes CDX2 transcription in a PRC2 complex-dependent manner to facilitate the malignant biological behavior of glioma cells.

Feasibility of Mobile Laser Scanning towards Operational Accurate Road Rut Depth Measurements.

This paper studied the applicability of the Roamer-R4DW mobile laser scanning (MLS) system for road rut depth measurement. The MLS system was developed by the Finnish Geospatial Research Institute (FGI), and consists of two mobile laser scanners and a Global Navigation Satellite System (GNSS)-inertial measurement unit (IMU) positioning system. In the study, a fully automatic algorithm was developed to calculate and analyze the rut depths, and verified in 64 reference pavement plots (1.0 m × 3.5 m). We showed that terrestrial laser scanning (TLS) data is an adequate reference for MLS-based rutting studies. The MLS-derived rut depths based on 64 plots resulted in 1.4 mm random error, which can be considered adequate precision for operational rutting depth measurements. Such data, also covering the area outside the pavement, would be ideal for multiple road environment applications since the same data can also be used in applications, from high-definition maps to autonomous car navigation and digitalization of street environments over time and in space.

A MEMS IMU De-Noising Method Using Long Short Term Memory Recurrent Neural Networks (LSTM-RNN).

Microelectromechanical Systems (MEMS) Inertial Measurement Unit (IMU) containing a three-orthogonal gyroscope and three-orthogonal accelerometer has been widely utilized in position and navigation, due to gradually improved accuracy and its small size and low cost. However, the errors of a MEMS IMU based standalone Inertial Navigation System (INS) will diverge over time dramatically, since there are various and nonlinear errors contained in the MEMS IMU measurements. Therefore, MEMS INS is usually integrated with a Global Positioning System (GPS) for providing reliable navigation solutions. The GPS receiver is able to generate stable and precise position and time information in open sky environment. However, under signal challenging conditions, for instance dense forests, city canyons, or mountain valleys, if the GPS signal is weak and even is blocked, the GPS receiver will fail to output reliable positioning information, and the integration system will fade to an INS standalone system. A number of effects have been devoted to improving the accuracy of INS, and de-nosing or modelling the random errors contained in the MEMS IMU have been demonstrated to be an effective way of improving MEMS INS performance. In this paper, an Artificial Intelligence (AI) method was proposed to de-noise the MEMS IMU output signals, specifically, a popular variant of Recurrent Neural Network (RNN) Long Short Term Memory (LSTM) RNN was employed to filter the MEMS gyroscope outputs, in which the signals were treated as time series. A MEMS IMU (MSI3200, manufactured by MT Microsystems Company, Hebei, China) was employed to test the proposed method, a 2 min raw gyroscope data with 400 Hz sampling rate was collected and employed in this testing. The results show that the standard deviation (STD) of the gyroscope data decreased by 60.3%, 37%, and 44.6% respectively compared with raw signals, and on the other way, the three-axis attitude errors decreased by 15.8%, 18.3% and 51.3% individually. Further, compared with an Auto Regressive and Moving Average (ARMA) model with fixed parameters, the STD of the three-axis gyroscope outputs decreased by 42.4%, 21.4% and 21.4%, and the attitude errors decreased by 47.6%, 42.3% and 52.0%. The results indicated that the de-noising scheme was effective for improving MEMS INS accuracy, and the proposed LSTM-RNN method was more preferable in this application.

Performance Analysis of a Deep Simple Recurrent Unit Recurrent Neural Network (SRU-RNN) in MEMS Gyroscope De-Noising.

Microelectromechanical System (MEMS) Inertial Measurement Unit (IMU) is popular in the community for constructing a navigation system, due to its small size and low power consumption. However, limited by the manufacturing technology, MEMS IMU experiences more complicated noises and errors. Thus, noise modeling and suppression is important for improving accuracy of the navigation system based on MEMS IMU. Motivated by this problem, in this paper, a deep learning method was introduced to MEMS gyroscope de-noising. Specifically, a recently popular Recurrent Neural Networks (RNN) variant Simple Recurrent Unit (SRU-RNN) was employed in MEMS gyroscope raw signals de-noising. A MEMS IMU MSI3200 from MT Microsystem Company was employed in the experiments for evaluating the proposed method. Following two problems were furtherly discussed and investigated: (1) the employed SRU with different training data length were compared to explore whether there was trade-off between the training data length and prediction performance; (2) Allan Variance was the most popular MEMS gyroscope analyzing method, and five basic parameters were employed to describe the performance of different grade MEMS gyroscope; among them, quantization noise, angle random walk, and bias instability were the major factors influencing the MEMS gyroscope accuracy, the compensation results of the three parameters for gyroscope were presented and compared. The results supported the following conclusions: (1) considering the computation brought from training dataset, the values of 500, 3000, and 3000 were individually sufficient for the three-axis gyroscopes to obtain a reliable and stable prediction performance; (2) among the parameters, the quantization noise, angle random walk, and bias instability performed 0.6%, 6.8%, and 12.5% improvement for X-axis gyroscope, 60.5%, 17.3%, and 34.1% improvement for Y-axis gyroscope, 11.3%, 22.7%, and 35.7% improvement for Z-axis gyroscope, and the corresponding attitude errors decreased by 19.2%, 82.1%, and 69.4%. The results surely demonstrated the effectiveness of the employed SRU in this application.

Using anthropometric parameters to predict insulin resistance among patients without diabetes mellitus.

Anthropometric parameters are widely used in the clinical assessment of hypertension, type 2 diabetes, and cardiovascular disease. However, few studies have compared the association between different anthropometric parameters and insulin resistance (IR). This study was aimed at investigating the relationship between 6 indicators, including body mass index (BMI), calf circumference (CC), arm circumference (AC), thigh circumference (TC), waist circumference (WC), waist-height ratio (WHtR), and IR. Homeostasis Model Assessment of Insulin Resistance (HOMA-IR) was used to measure IR. Weighted linear regression was used to assess the relationship between different parameters and IR. The receiver operating characteristic curve (ROC) was employed to compare the strength of the relationship between different anthropometric parameters and IR. A total of 8069 participants were enrolled in our study, including 4873 without IR and 3196 with IR. The weighted linear regression results showed that BMI, CC, AC, TC and WC were significantly correlated with IR, except WHtR. After adjusting for multiple confounding factors, we found that BMI, AC and WC were significantly positively correlated with IR, while TC was significantly negatively correlated with IR. Logistic regression results showed that a larger TC was associated with a decreased risk of IR. In addition, BMI and WC had similar areas under the curve (AUC: 0.780, 95% CI 0.770-0.790; AUC: 0.774, 95% CI 0.763-0.784, respectively), which were higher than TC and AC (AUC: 0.698, 95% CI 0.687-0.710, AUC: 0.746, 95% CI 0.735-0.757, respectively). To our knowledge, this is the first study to report a negative correlation between TC and IR among patients without diabetes mellitus. Therefore, TC may be a new tool to guide public health and a clinical predictor of IR in non-diabetic patients.

Functional biomacromolecules-based microneedle patch for the treatment of diabetic wound.

Diabetic wounds are a common complication of diabetes. The prolonged exposure to high glucose and oxidative stress in the wound environment increases the risk of bacterial infection and abnormal angiogenesis, leading to amputation. Microneedle patches have shown promise in promoting the healing of diabetic wounds through transdermal drug delivery. These patches target the four main aspects of diabetic wound treatment: hypoglycemia, antibacterial action, inflammatory regulation, and tissue regeneration. By overcoming the limitations of traditional administration methods, microneedle patches enable targeted therapy for deteriorated tissues. The design of these patches extends beyond the selection of needle tip material and biomacromolecule encapsulated drugs; it can also incorporate near-infrared rays to facilitate cascade reactions and treat diabetic wounds. In this review, we comprehensively summarize the advantages of microneedle patches compared to traditional treatment methods. We focus on the design and mechanism of these patches based on existing experimental articles in the field and discuss the potential for future research on microneedle patches.

Fabrication of a ZIF-on-lamella-zeolite architecture as a highly efficient catalyst for aldol condensation.

Designing composite catalysts that harness the strengths of individual components while mitigating their limitations is a fascinating yet challenging task in catalyst engineering. In this study, we aimed to enhance the catalytic performance by anchoring ZIF-67 nanoparticles of precise sizes onto lamella Si-MWW zeolite surfaces through a stepwise regrowth process. Co ions were initially grafted onto the zeolite surface using ultrasonication, followed by a seed-assisted secondary growth method. Si-MWW proved to be the ideal zeolite support due to its thin layered structure, large external surface area and substantial lateral dimensions. The abundant Si-OH groups on its surface played a crucial role in securely binding Co ions, limiting size growth and preventing undesirable ZIF-67 aggregation. The resulting ZIF-67/MWW composite with finely dispersed nano-scale ZIF-67 particles exhibited a remarkable catalytic performance and stability in the aldol condensation reactions involving acetone and various aldehydes. This approach holds promise for designing MOF/zeolite composite catalysts.

Liquid-liquid phase separation of TZP promotes PPK-mediated phosphorylation of the phytochrome A photoreceptor.

Phytochrome A (phyA) is the plant far-red (FR) light photoreceptor and plays an essential role in regulating photomorphogenic development in FR-rich conditions, such as canopy shade. It has long been observed that phyA is a phosphoprotein in vivo; however, the protein kinases that could phosphorylate phyA remain largely unknown. Here we show that a small protein kinase family, consisting of four members named PHOTOREGULATORY PROTEIN KINASES (PPKs) (also known as MUT9-LIKE KINASES), directly phosphorylate phyA in vitro and in vivo. In addition, TANDEM ZINC-FINGER/PLUS3 (TZP), a recently characterized phyA-interacting protein required for in vivo phosphorylation of phyA, is also directly phosphorylated by PPKs. We reveal that TZP contains two intrinsically disordered regions in its amino-terminal domain that undergo liquid-liquid phase separation (LLPS) upon light exposure. The LLPS of TZP promotes colocalization and interaction between PPKs and phyA, thus facilitating PPK-mediated phosphorylation of phyA in FR light. Our study identifies PPKs as a class of protein kinases mediating the phosphorylation of phyA and demonstrates that the LLPS of TZP contributes significantly to more production of the phosphorylated phyA form in FR light.

The association of central and extremity circumference with all-cause mortality and cardiovascular mortality: a cohort study.

Background: Central obesity increases the risk of several diseases, including diabetes, cardiovascular disease (CVD), and cancer. However, the association between extremity obesity and mortality has not been extensively evaluated. The objective of this study was to investigate the quantitative effects of waist circumference (WC), arm circumference (AC), calf circumference (CC), and thigh circumference (TC) on all-cause mortality and CVD mortality. Methods: The study used data from the National Health and Nutrition Examination Survey (NHANES) sample survey from 1999 to 2006. A total of 19,735 participants were included in the study. We divided the participants into four groups (Q1-Q4) and used Q1 as a reference to compare the risk of all-cause mortality and CVD mortality in Q2-Q4. COX proportional hazard regression model was used to analyze the relationship between WC, AC, CC and TC on all-cause and CVD mortality. In addition, we conducted a stratified analysis of gender. Results: After a mean follow-up of 11.8 years, we observed a total of 3,446 deaths, of which 591 were due to cardiovascular disease. The results showed that for both men and women, compared to the first group, the risk of all-cause mortality was significantly higher in the other three groups of WC and significantly lower in the other three groups of AC, CC, and TC. Similar results were observed after adjusting for confounding factors such as demographics. Conclusions: Our results show that all-cause and CVD mortality are positively associated with measures of central obesity and negatively associated with measures of extremity obesity, and that AC, CC, and TC can be used as potential tools to measure prognosis in the general population.

The Role of Microsphere Structures in Bottom-Up Bone Tissue Engineering.

Bone defects have caused immense healthcare concerns and economic burdens throughout the world. Traditional autologous allogeneic bone grafts have many drawbacks, so the emergence of bone tissue engineering brings new hope. Bone tissue engineering is an interdisciplinary biomedical engineering method that involves scaffold materials, seed cells, and "growth factors". However, the traditional construction approach is not flexible and is unable to adapt to the specific shape of the defect, causing the cells inside the bone to be unable to receive adequate nourishment. Therefore, a simple but effective solution using the "bottom-up" method is proposed. Microspheres are structures with diameters ranging from 1 to 1000 µm that can be used as supports for cell growth, either in the form of a scaffold or in the form of a drug delivery system. Herein, we address a variety of strategies for the production of microspheres, the classification of raw materials, and drug loading, as well as analyze new strategies for the use of microspheres in bone tissue engineering. We also consider new perspectives and possible directions for future development.