RFAConv: Innovating Spatital Attention and Standard Convolutional Operation

Spatial attention has been widely used to improve the performance of convolutional neural networks by allowing them to focus on important information. However, it has certain limitations. In this paper, we propose a new perspective on the effectiveness of spatial attention, which is that it can solve the problem of convolutional kernel parameter sharing. Despite this, the information contained in the attention map generated by spatial attention is not sufficient for large-size convolutional kernels. Therefore, we introduce a new attention mechanism called Receptive-Field Attention (RFA). While previous attention mechanisms such as the Convolutional Block Attention Module (CBAM) and Coordinate Attention (CA) only focus on spatial features, they cannot fully address the issue of convolutional kernel parameter sharing. In contrast, RFA not only focuses on the receptive-field spatial feature but also provides effective attention weights for large-size convolutional kernels. The Receptive-Field Attention convolutional operation (RFAConv), developed by RFA, represents a new approach to replace the standard convolution operation. It offers nearly negligible increment of computational cost and parameters, while significantly improving network performance. We conducted a series of experiments on ImageNet-1k, MS COCO, and VOC datasets, which demonstrated the superiority of our approach in various tasks including classification, object detection, and semantic segmentation. Of particular importance, we believe that it is time to shift focus from spatial features to receptive-field spatial features for current spatial attention mechanisms. By doing so, we can further improve network performance and achieve even better results. The code and pre-trained models for the relevant tasks can be found at https://github.com/Liuchen1997/RFAConv.Comment: 14 pages, 5 figure

AKConv: Convolutional Kernel with Arbitrary Sampled Shapes and Arbitrary Number of Parameters

Neural networks based on convolutional operations have achieved remarkable results in the field of deep learning, but there are two inherent flaws in standard convolutional operations. On the one hand, the convolution operation be confined to a local window and cannot capture information from other locations, and its sampled shapes is fixed. On the other hand, the size of the convolutional kernel is fixed to k $\times$ k, which is a fixed square shape, and the number of parameters tends to grow squarely with size. It is obvious that the shape and size of targets are various in different datasets and at different locations. Convolutional kernels with fixed sample shapes and squares do not adapt well to changing targets. In response to the above questions, the Alterable Kernel Convolution (AKConv) is explored in this work, which gives the convolution kernel an arbitrary number of parameters and arbitrary sampled shapes to provide richer options for the trade-off between network overhead and performance. In AKConv, we define initial positions for convolutional kernels of arbitrary size by means of a new coordinate generation algorithm. To adapt to changes for targets, we introduce offsets to adjust the shape of the samples at each position. Moreover, we explore the effect of the neural network by using the AKConv with the same size and different initial sampled shapes. AKConv completes the process of efficient feature extraction by irregular convolutional operations and brings more exploration options for convolutional sampling shapes. Object detection experiments on representative datasets COCO2017, VOC 7+12 and VisDrone-DET2021 fully demonstrate the advantages of AKConv. AKConv can be used as a plug-and-play convolutional operation to replace convolutional operations to improve network performance. The code for the relevant tasks can be found at https://github.com/CV-ZhangXin/AKConv.Comment: 10 pages, 5 figure

Comparative study of a novel proximal femoral bionic nail and three conventional cephalomedullary nails for reverse obliquity intertrochanteric fractures: a finite element analysis

PurposeConventional cephalomedullary nails (CMNs) are commonly employed for internal fixation in the treatment of reverse obliquity intertrochanteric (ROI) fractures. However, the limited effectiveness of conventional CMNs in addressing ROI fractures results in significant implant-related complications. To address challenges associated with internal fixation, a novel Proximal Femoral Bionic Nail (PFBN) has been developed.MethodsIn this study, a finite element model was constructed using a normal femoral specimen, and biomechanical verification was conducted using the GOM non-contact optical strain measurement system. Four intramedullary fixation approaches—PFBN, Proximal Femoral Nail Antirotation InterTan nail (ITN), and Gamma nail (Gamma nail)—were employed to address three variations of ROI fractures (AO/OTA 31-A3). The biomechanical stability of the implant models was evaluated through the calculation of the von Mises stress contact pressure and displacement.ResultsCompared to conventional CMNs, the PFBN group demonstrated a 9.36%–59.32% reduction in the maximum VMS at the implant. The A3.3 ROI fracture (75% bone density) was the most unstable type of fracture. In comparison to conventional CMNs, PFBN demonstrated more stable data, including VMS values (implant: 506.33 MPa, proximal fracture fragment: 34.41 MPa), contact pressure (13.28 MPa), and displacement (17.59 mm).ConclusionCompared to the PFNA, ITN, and GN, the PFBN exhibits improvements in stress concentration, stress conduction, and overall model stability in ROI fractures. The double triangle structure aligns better with the tissue structure and biomechanical properties of the proximal femur. Consequently, the PFBN has significant potential as a new fixation strategy for the clinical treatment of ROI fractures

Partial femoral head replacement: a new innovative hip-preserving approach for treating osteonecrosis of the femoral head and its finite element analysis

Purpose: Controversy remains regarding the optimal treatment for stage III Osteonecrosis of the femoral head (ONFH). This study presents, for the first time, the precise treatment of stage III ONFH using the “substitute the beam for a pillar” technique and performs a comparative finite element analysis with other hip-preserving procedures.Methods: A formalin-preserved femur of male cadavers was selected to obtain the CT scan data of femur. The proximal femur model was reconstructed and assembled using Mimics 20.0, Geomagic, and UG-NX 12.0 software with four different implant types: simple core decompression, fibula implantation, porous tantalum rod implantation, and partial replacement prosthesis. The finite element simulations were conducted to simulate the normal walking gait, and the stress distribution and displacement data of the femur and the implant model were obtained.Results: The peak von Mises stress of the femoral head and proximal femur in the partial replacement of the femoral head (PRFH) group were 22.8 MPa and 37.4 MPa, respectively, which were 3.1%–38.6% and 12.8%–37.4% lower than those of the other three surgical methods.Conclusion: The PRFH group exhibits better mechanical performance, reducing stress and displacement in the ONFH area, thus maintaining femoral head stability. Among the four hip-preserving approaches, from a biomechanical perspective, PRFH offers a new option for treating ONFH

National incidence of traumatic fractures in China: a retrospective survey of 512 187 individuals

Background Traumatic fractures place a substantial burden on health-care systems worldwide. Although detailed information about incidence, distribution, and risk factors for traumatic fractures is vital for planning and prevention, in China, national data are unavailable. We aimed to do an up-to-date national survey on the population-weighted incidence of traumatic fractures in China. Methods The China National Fracture Study (CNFS) was a retrospective epidemiological study that recruited a nationally representative sample from eight provinces, 24 urban cities, and 24 rural counties in China using stratified random sampling and the probability proportional to size method. All eligible household members who had lived in their current residence for 6 months or longer were personally interviewed by trained research teams about traumatic fractures of the trunk, arms, or legs (not including the skull, sternum, and ribs) that had occurred in 2014. Telephone surveys were used for participants who were non-contactable after repeated visits. Fracture cases were verified by clinical records, medical history, and radiographs by orthopaedic surgeons and radiologists. We estimated incidence rates for traumatic fractures for the overall population and for subgroups by age and sex, as well as by demographic factors such as ethnic origin, occupation, geographical region, and residency category. We also studied potential associations between fractures and various factors of interest, such as age, ethnic origin, education, smoking, alcohol drinking, sleep time per day, and history of previous fracture. Data were weighted during statistical analysis to ascertain the national incidence rate. This study is registered with the Chinese Clinical Trial Registry, number ChiCTR-EPR-15005878. Findings Between Jan 19, 2015, and May 16, 2015, 535 836 individuals were selected and invited to participate in the study. Questionnaires from 23 649 (4%) individuals were excluded due to missing items, insufficient responses, or logical errors. Following exclusions, 512 187 (96%) individuals participated in the CNFS, consisting of 259 649 (51%) boys and men and 252 538 (49%) girls and women. Of these individuals, 1763 individuals had experienced traumatic fractures during 2014 (n=1833). The population-weighted incidence rate of traumatic fractures of the trunk, arms, or legs was 3·21 (95% CI 2·83–3·59) per 1000 population in 2014 (3·65, 3·12–4·18 in men and 2·75, 2·46–3·04 in women). For all ages, sleeping less than 7 h per day was identified as a risk factor for traumatic fractures. We identified previous fracture history as a risk factor for adults aged 15 years and older. Alcohol consumption incurred a risk effect for men aged 15 years and older and women aged 15–64 years. Interpretation Our results provide detailed information about fracture incidence, distribution, and risk factors, which can now be used as an up-to-date clinical evidence base for national health-care planning and preventive efforts in China and elsewhere. Specific public health policies that focus on decreasing alcohol consumption, prohibiting drunk driving, promoting smoking cessation, and encouraging individuals to obtain sufficient sleep and maintain a healthy bodyweight should be urgently implemented to help reduce the risk of traumatic fractures

MMP1 and MMP7 as Potential Peripheral Blood Biomarkers in Idiopathic Pulmonary Fibrosis

Naftali Kaminski and colleagues find increased levels of specific proteins in the bloodstream of individuals with idiopathic pulmonary fibrosis, and suggest that these proteins may ultimately provide a biomarker for the disease

DeePMD-kit v2: A software package for Deep Potential models

DeePMD-kit is a powerful open-source software package that facilitates molecular dynamics simulations using machine learning potentials (MLP) known as Deep Potential (DP) models. This package, which was released in 2017, has been widely used in the fields of physics, chemistry, biology, and material science for studying atomistic systems. The current version of DeePMD-kit offers numerous advanced features such as DeepPot-SE, attention-based and hybrid descriptors, the ability to fit tensile properties, type embedding, model deviation, Deep Potential - Range Correction (DPRc), Deep Potential Long Range (DPLR), GPU support for customized operators, model compression, non-von Neumann molecular dynamics (NVNMD), and improved usability, including documentation, compiled binary packages, graphical user interfaces (GUI), and application programming interfaces (API). This article presents an overview of the current major version of the DeePMD-kit package, highlighting its features and technical details. Additionally, the article benchmarks the accuracy and efficiency of different models and discusses ongoing developments.Comment: 51 pages, 2 figure

Genome-wide imputation study identifies novel HLA locus for pulmonary fibrosis and potential role for auto-immunity in fibrotic idiopathic interstitial pneumonia.

To access publisher's full text version of this article, please click on the hyperlink in Additional Links field or click on the hyperlink at the top of the page marked Files. This article is open access.Fibrotic idiopathic interstitial pneumonias (fIIP) are a group of fatal lung diseases with largely unknown etiology and without definitive treatment other than lung transplant to prolong life. There is strong evidence for the importance of both rare and common genetic risk alleles in familial and sporadic disease. We have previously used genome-wide single nucleotide polymorphism data to identify 10 risk loci for fIIP. Here we extend that work to imputed genome-wide genotypes and conduct new RNA sequencing studies of lung tissue to identify and characterize new fIIP risk loci.We performed genome-wide genotype imputation association analyses in 1616 non-Hispanic white (NHW) cases and 4683 NHW controls followed by validation and replication (878 cases, 2017 controls) genotyping and targeted gene expression in lung tissue. Following meta-analysis of the discovery and replication populations, we identified a novel fIIP locus in the HLA region of chromosome 6 (rs7887 P meta  = 3.7 × 10(-09)). Imputation of classic HLA alleles identified two in high linkage disequilibrium that are associated with fIIP (DRB1*15:01 P = 1.3 × 10(-7) and DQB1*06:02 P = 6.1 × 10(-8)). Targeted RNA-sequencing of the HLA locus identified 21 genes differentially expressed between fibrotic and control lung tissue (Q < 0.001), many of which are involved in immune and inflammatory response regulation. In addition, the putative risk alleles, DRB1*15:01 and DQB1*06:02, are associated with expression of the DQB1 gene among fIIP cases (Q < 1 × 10(-16)).We have identified a genome-wide significant association between the HLA region and fIIP. Two HLA alleles are associated with fIIP and affect expression of HLA genes in lung tissue, indicating that the potential genetic risk due to HLA alleles may involve gene regulation in addition to altered protein structure. These studies reveal the importance of the HLA region for risk of fIIP and a basis for the potential etiologic role of auto-immunity in fIIP.National Heart, Lung and Blood Institute R01-HL095393 R01-HL097163 P01-HL092870 RC2-HL101715 U01-HL089897 U01-HL089856 U01-HL108642 P50-HL089493

Egr-1 Regulates Autophagy in Cigarette Smoke-Induced Chronic Obstructive Pulmonary Disease

Background: Chronic obstructive pulmonary disease (COPD) is a progressive lung disease characterized by abnormal cellular responses to cigarette smoke, resulting in tissue destruction and airflow limitation. Autophagy is a degradative process involving lysosomal turnover of cellular components, though its role in human diseases remains unclear. Methodology and Principal Findings: Increased autophagy was observed in lung tissue from COPD patients, as indicated by electron microscopic analysis, as well as by increased activation of autophagic proteins (microtubule-associated protein-1 light chain-3b, LC3B, Atg4, Atg5/12, Atg.7). Cigarette smoke extract (CSE) is an established model for studying the effects of cigarette smoke exposure in vitro. In human pulmonary epithelial cells, exposure to CSE or histone deacetylase (HDAC) inhibitor rapidly induced autophagy. CSE decreased HDAC activity, resulting in increased binding of early growth response-1 (Egr-1) and E2F factors to the autophagy gene LC3B promoter, and increased LC3B expression. Knockdown of E2F-4 or Egr-1 inhibited CSE-induced LC3B expression. Knockdown of Egr-1 also inhibited the expression of Atg4B, a critical factor for LC3B conversion. Inhibition of autophagy by LC3B-knockdown protected epithelial cells from CSE-induced apoptosis. Egr-1-1- mice, which displayed basal airspace enlargement, resisted cigarette-smoke induced autophagy, apoptosis, and emphysema. Conclusions: We demonstrate a critical role for Egr-1 in promoting autophagy and apoptosis in response to cigarette smoke exposure in vitro and in vivo. The induction of autophagy at early stages of COPD progression suggests novel therapeutic targets for the treatment of cigarette smoke induced lung injury. © 2008 Chen et al