APEX-pHLA: A novel method for accurate prediction of the binding between exogenous short peptides and HLA class I molecules.

Human leukocyte antigen (HLA) molecules play critically significant role within the realm of immunotherapy due to their capacities to recognize and bind exogenous antigens such as peptides, subsequently delivering them to immune cells. Predicting the binding between peptides and HLA molecules (pHLA) can expedite the screening of immunogenic peptides and facilitate vaccine design. However, traditional experimental methods are time-consuming and inefficient. In this study, an efficient method based on deep learning was developed for predicting peptide-HLA binding, which treated peptide sequences as linguistic entities. It combined the architectures of textCNN and BiLSTM to create a deep neural network model called APEX-pHLA. This model operated without limitations related to HLA class I allele variants and peptide segment lengths, enabling efficient encoding of sequence features for both HLA and peptide segments. On the independent test set, the model achieved Accuracy, ROC_AUC, F1, and MCC is 0.9449, 0.9850, 0.9453, and 0.8899, respectively. Similarly, on an external test set, the results were 0.9803, 0.9574, 0.8835, and 0.7863, respectively. These findings outperformed fifteen methods previously reported in the literature. The accurate prediction capability of the APEX-pHLA model in peptide-HLA binding might provide valuable insights for future HLA vaccine design.

Proposal-Free Fully Convolutional Network: Object Detection Based on a Box Map.

Region proposal-based detectors, such as Region-Convolutional Neural Networks (R-CNNs), Fast R-CNNs, Faster R-CNNs, and Region-Based Fully Convolutional Networks (R-FCNs), employ a two-stage process involving region proposal generation followed by classification. This approach is effective but computationally intensive and typically slower than proposal-free methods. Therefore, region proposal-free detectors are becoming popular to balance accuracy and speed. This paper proposes a proposal-free, fully convolutional network (PF-FCN) that outperforms other state-of-the-art, proposal-free methods. Unlike traditional region proposal-free methods, PF-FCN can generate a "box map" based on regression training techniques. This box map comprises a set of vectors, each designed to produce bounding boxes corresponding to the positions of objects in the input image. The channel and spatial contextualized sub-network are further designed to learn a "box map". In comparison to renowned proposal-free detectors such as CornerNet, CenterNet, and You Look Only Once (YOLO), PF-FCN utilizes a fully convolutional, single-pass method. By reducing the need for fully connected layers and filtering center points, the method considerably reduces the number of trained parameters and optimizes the scalability across varying input sizes. Evaluations of benchmark datasets suggest the effectiveness of PF-FCN: the proposed model achieved an mAP of 89.6% on PASCAL VOC 2012 and 71.7% on MS COCO, which are higher than those of the baseline Fully Convolutional One-Stage Detector (FCOS) and other classical proposal-free detectors. The results prove the significance of proposal-free detectors in both practical applications and future research.

Uric acid metabolism promotes apoptosis against Bombyx mori nucleopolyhedrovirus in silkworm, Bombyx mori.

The white epidermis of silkworms is due to the accumulation of uric acid crystals. Abnormal silkworm uric acid metabolism decreases uric acid production, leading to a transparent or translucent phenotype. The oily silkworm op50 is a mutant strain with a highly transparent epidermis derived from the p50 strain. It shows more susceptibility to Bombyx mori nucleopolyhedrovirus (BmNPV) infection than the wild type; however, the underlying mechanism is unknown. This study analysed the changes in 34 metabolites in p50 and op50 at different times following BmNPV infection based on comparative metabolomics. The differential metabolites were mainly clustered in six metabolic pathways. Of these, the uric acid pathway was identified as critical for resistance in silkworms, as feeding with inosine significantly enhanced larval resistance compared to other metabolites and modulated other metabolic pathways. Additionally, the increased level of resistance to BmNPV in inosine-fed silkworms was associated with the regulation of apoptosis, which is mediated by the reactive oxygen species produced during uric acid synthesis. Furthermore, feeding the industrial strain Jingsong (JS) with inosine significantly increased the level of larval resistance to BmNPV, indicating its potential application in controlling the virus in sericulture. These results lay the foundation for clarifying the resistance mechanism of silkworms to BmNPV and provide new strategies and methods for the biological control of pests.

Efficient Computational Framework for Target-Specific Active Peptide Discovery: A Case Study on IL-17C Targeting Cyclic Peptides.

The development of potentially active peptides for specific targets is critical for the modern pharmaceutical industry's growth. In this study, we present an efficient computational framework for the discovery of active peptides targeting a specific pharmacological target, which combines a conditional variational autoencoder (CVAE) and a classifier named TCPP based on the Transformer and convolutional neural network. In our example scenario, we constructed an active cyclic peptide library targeting interleukin-17C (IL-17C) through a library-based in vitro selection strategy. The CVAE model is trained on the preprocessed peptide data sets to generate potentially active peptides and the TCPP further screens the generated peptides. Ultimately, six candidate peptides predicted by the model were synthesized and assayed for their activity, and four of them exhibited promising binding affinity to IL-17C. Our study provides a one-stop-shop for target-specific active peptide discovery, which is expected to boost up the process of peptide drug development.

Transcriptomic analysis of the fat body of resistant and susceptible silkworm strains, Bombyx mori (Lepidoptera), after oral treatment with fenpropathrin.

The widespread use of pyrethroid pesticides has brought serious economic losses in sericulture, but there is still no viable solution. The key to solving the problem is to improve silkworm resistance to pesticides, which depends on understanding the resistance mechanism of silkworms to pesticides. This study aimed to use transcriptomes to understand the underlying mechanism of silkworm resistance to fenpropathrin, which will provide a theoretical molecular reference for breeding pesticide-resistant silkworm varieties. In this study, the fat bodies of two strains with differential resistance after 12 h of fenpropathrin feeding were analyzed using RNA-Seq. After feeding fenpropathrin, 760 differentially expressed genes (DEGs) were obtained in the p50(r) strain and 671 DEGs in the 8y strain. The DEGs involved in resistance to fenpropathrin were further identified by comparing the two strains, including 207 upregulated DEGs in p50(r) and 175 downregulated DEGs in 8y. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed that these fenpropathrin-related DEGs are mainly enriched in the metabolism and transporter pathways. Moreover, 28 DEGs involved in the metabolic pathway and 18 in the transporter pathway were identified. Furthermore, organic cation transporter protein 6 (BmOCT6), a transporter pathway member, was crucial in enhancing the tolerance of BmN cells to fenpropathrin. Finally, the knockdown of the expression of the homologs of BmOCT6 in Glyphodes pyloalis (G. pyloalis) significantly decreased the resistant level of larvae to fenpropathrin. The findings showed that the metabolism and transporter pathways are associated with resistance to fenpropathrin in silkworm, and OCT6 is an effective and potential target not only for silkworm breeding but also for pest biocontrol.

The validation of the role of several genes related to Bombyx mori nucleopolyhedrovirus infection in vivo.

Bombyx mori nucleopolyhedrovirus (BmNPV) is one of primary silkworm pathogens and causes a serious damage of cocoon losses every year. Recent years, many works have been done to clarify the silkworm anti-BmNPV mechanism, and a significant progress has been made in screening and studying of genes and proteins related to BmNPV infection, but several of them lacked the proofs in vivo. In this study, to further validate the function of seven newly reported genes in vivo, including BmAtlatin-n, Bmferritin-heavy chain (BmFerHCH), Bmthymosin (BmTHY), Bmseroin1, Bmseroin2, Bmnuclear hormone receptors 96 (BmNHR96), and BmE3 ubiquitin-protein ligase SINA-like 10 (BmSINAL10), the response of them in the midgut, fat body, and hemolymph of differentially resistant strains (resistant strain YeA and susceptible strain YeB) at 48 h following BmNPV infection were analyzed. The results showed that the relative stable or upregulated expression level of BmAtlatin-n, BmTHY, Bmseroin1, and Bmseroin2 in YeA resistant strain following BmNPV infection further indicated their antiviral role in vivo, compared with susceptible YeB strain. Moreover, the significant downregulation of BmFerHCH, BmNHR96, and BmSINAL10 in both strains following BmNPV infection revealed their role in benefiting virus infection, as well as the upregulation of BmFerHCH in YeB midgut and BmSINAL10 in YeB hemolymph. These data could be used to complementary the proofs of the function of these genes in response to BmNPV infection.

Identification of the in vitro antiviral effect of BmNedd2-like caspase in response to Bombyx mori nucleopolyhedrovirus infection.

Bombyx mori nucleopolyhedrovirus (BmNPV) is one of the most serious pathogens in sericulture, and the underlying antiviral mechanism in silkworm is still unclear. Bombyx mori Nedd2-like caspase (BmNc) has been identified as a candidate antiviral gene from previous transcriptome data, since it is differentially expressed in the midgut of differentially resistant silkworm strains following BmNPV infection. However, the molecular mechanism by which BmNc responds to BmNPV is unknown. In this study, the relationship between BmNc and BmNPV was confirmed by its significantly different expression in different tissues of differentially resistant strains after BmNPV infection. Moreover, the antiviral role of BmNc was confirmed by the significantly higher fluorescence signals of BV-eGFP after knockdown of BmNc in BmN cells, and a reduced signal after overexpression. This was further verified by the capsid gene vp39 expression, DNA copy number, and GP64 protein level in the RNAi and overexpression groups. Furthermore, the antiviral phenomenon of BmNc was found to be associated with apoptosis. In brief, BmNc showed a relatively high expression level in the metamorphosis stages, and the effect of BmNc on BmNPV infection following RNAi and overexpression was eliminated after treatment with the inducer, Silvestrol, and the inhibitor, Z-DEVD-FMK, respectively. Therefore, it is reasonable to conclude that BmNc is involved in anti-BmNPV infection via the mitochondrial apoptosis pathway. The results provide valuable information for elucidating the molecular mechanism of silkworm resistance to BmNPV infection.

Geographical isolation and environmental heterogeneity contribute to the spatial genetic patterns of Quercus kerrii (Fagaceae).

Southwest China is one of the major global biodiversity hotspots. The Tanaka line, extending within southwestern China from its northwest to its southeast, is an important biogeographical boundary between the Sino-Japanese and Sino-Himalayan floristic regions. Understanding the evolutionary history of the regional keystone species would assist with both reconstructing historical vegetation dynamics and ongoing biodiversity management. In this research, we combined phylogeographic methodologies and species distribution models (SDMs) to investigate the spatial genetic patterns and distribution dynamics of Quercus kerrii, a dominant evergreen oak inhabiting southwest China lowland evergreen-broadleaved forests (EBLFs). A total of 403 individuals were sampled from 44 populations throughout southwest China. SDMs and mismatch distribution analysis indicated that Q. kerrii has undergone northward expansion since the Last Glacial Maximum (LGM). Quantitative analysis revealed that the range expansion of Q. kerrii since the LGM exceeded that of the sympatric mid-elevation species Quercus schottkyana, likely owing to their contrasting distribution elevations and habitat availabilities. The historical climate change since the LGM and the latitude gradient of the region played an important role in shaping the genetic diversity of Q. kerrii. The genetic differentiation index and genetic distance surface of Q. kerrii populations east of the Tanaka line exceeded those to its west. The long-term geographic isolation and environmental heterogeneity between the two sides of the Tanaka line might increase species divergence patterns and local adaptation. This study provides new insights into the historical dynamics of subtropical EBLFs and the changing biota of southwest China.

Novel sustainable steel fiber reinforced preplaced aggregate concrete incorporating Portland limestone cement.

This study proposes a novel approach by adding Portland limestone cement (PLC) to preplaced aggregate steel fiber reinforced concrete (PASFRC) to create a sustainable concrete that minimizes CO2 emissions and cement manufacturing energy usage. The method involves injected a flowable grout after premixing and preplacing steel-fibers and aggregates in the formwork. This study evaluates the mechanical properties of a novel sustainable concrete that uses PLC and steel fibers. To achieve the intended objective, long and short end-hooked steel fibers of 1%, 2%, 3%, and 6% were incorporated in PASFRC. Also, Analysis of variance (ANOVA) was used to examine the data. Results indicated that PLC and higher fiber doses increased the mechanical properties of PAC. At 90 days, PASFRC mixtures containing 6% long steel fibers demonstrated superior compressive, tensile, and flexural strengths, registering the highest values of 49.8 MPa, 7.7 MPa, and 10.9 MPa, respectively and differed by 188%, 166%, and 290%, respectively from fiberless PAC. The study confirmed the suitability and effectiveness of using PLC with steel fibers in PAC which significantly improved the mechanical properties of PASFRC. This was verified through analytical analysis and new empirical equations were proposed to predict the mechanical properties of PASFRC.

Site-selective fatty acid chain conjugation of the N-terminus of the recombinant human granulocyte colony-stimulating factor.

The clinical application of the recombinant human granulocyte colony-stimulating factor (rhG-CSF) is restricted by its short serum half-life. Herein, site-selective modification of the N-terminus of rhG-CSF with PAL-PEG3-Ph-CHO was used to develop a long-acting rhG-CSF. The optimized conditions for rhG-CSF modification with PAL-PEG3-Ph-CHO were: reaction solvent system of 3% (w/v) Tween 20 and 30 mM NaCNBH3 in acetate buffer (20 mmol/L, pH 5.0), molar ratio of PAL-PEG3-Ph-CHO to rhG-CSF of 6:1, temperature of 20°C, and reaction time of 12 h, consequently, achieving a PAL-PEG3-Ph-rhG-CSF product yield of 70.8%. The reaction mixture was purified via preparative liquid chromatography, yielding the single-modified product PAL-PEG3-Ph-rhG-CSF with a HPLC purity exceeding 95%. The molecular weight of PAL-PEG3-Ph-rhG-CSF was 19297 Da by MALDI-TOF-MS, which was consistent with the theoretical value. The circular dichroism analysis revealed no significant change in its secondary structure compared to unmodified rhG-CSF. The PAL-PEG3-Ph-rhG-CSF retained 82.0% of the in vitro biological activity of unmodified rhG-CSF. The pharmacokinetic analyses showed that the serum half-life of PAL-PEG3-Ph-rhG-CSF was 7.404 ± 0.777 h in mice, 4.08 times longer than unmodified rhG-CSF. Additionally, a single subcutaneous dose of PAL-PEG3-Ph-rhG-CSF presented comparable in vivo efficacy to multiple doses of rhG-CSF. This study demonstrated an efficacious strategy for developing long-acting rhG-CSF drug candidates.

Biomechanical role of bone grafting for calcaneal fracture fixation in the presence of bone defect: A finite element analysis.

BACKGROUND: The purpose of this study was to compare the biomechanical stress and stability of calcaneal fixations with and without bone defect, before and after bone grafting, through a computational approach. METHODS: A finite element model of foot-ankle complex was reconstructed, impoverished with a Sanders III calcaneal fracture without bone defect and with moderate and severe bone defects. Plate fixations with and without bone grafting were introduced with walking stance simulated. The stress and fragment displacement of the calcaneus were evaluated. FINDINGS: Moderate and severe defect increased the calcaneus stress by 16.11% and 32.51%, respectively and subsequently decreased by 10.76% and 20.78% after bone grafting. The total displacement was increased by 3.99% and 24.26%, respectively by moderate and severe defect, while that of posterior joint facet displacement was 86.66% and 104.44%. The former was decreased by 25.73% and 35.96% after grafting, while that of the latter was reduced by 88.09% and 84.78% for moderate and severe defect, respectively. INTERPRETATION: Our finite element prediction supported that bone grafting for fixation could enhance the stability and reduce the risk of secondary stress fracture in cases of bone defect in calcaneal fracture.

Skeletal Fracture Detection with Deep Learning: A Comprehensive Review.

Deep learning models have shown great promise in diagnosing skeletal fractures from X-ray images. However, challenges remain that hinder progress in this field. Firstly, a lack of clear definitions for recognition, classification, detection, and localization tasks hampers the consistent development and comparison of methodologies. The existing reviews often lack technical depth or have limited scope. Additionally, the absence of explainable facilities undermines the clinical application and expert confidence in results. To address these issues, this comprehensive review analyzes and evaluates 40 out of 337 recent papers identified in prestigious databases, including WOS, Scopus, and EI. The objectives of this review are threefold. Firstly, precise definitions are established for the bone fracture recognition, classification, detection, and localization tasks within deep learning. Secondly, each study is summarized based on key aspects such as the bones involved, research objectives, dataset sizes, methods employed, results obtained, and concluding remarks. This process distills the diverse approaches into a generalized processing framework or workflow. Moreover, this review identifies the crucial areas for future research in deep learning models for bone fracture diagnosis. These include enhancing the network interpretability, integrating multimodal clinical information, providing therapeutic schedule recommendations, and developing advanced visualization methods for clinical application. By addressing these challenges, deep learning models can be made more intelligent and specialized in this domain. In conclusion, this review fills the gap in precise task definitions within deep learning for bone fracture diagnosis and provides a comprehensive analysis of the recent research. The findings serve as a foundation for future advancements, enabling improved interpretability, multimodal integration, clinical decision support, and advanced visualization techniques.

Multilayer structure covalent organic frameworks (COFs) linking by double functional groups for advanced K+ batteries.

Covalent organic frameworks (COFs) are regarded as the potential and promising anode materials for potassium ion batteries (PIBs) on account of their robust and porous crystalline structure. In this work, multilayer structural COF connected by double functional groups, including imine and amidogent through a simple solvothermalprocess, have been successfully synthesized. The multilayer structure of COF can provide fast charge transfer and combine the merits of imine (the restraint of irreversible dissolution) and amidogent (the supply of more active sites). It presents superior potassium storage performance, including the high reversible capacity of 229.5 mAh g-1 at 0.2 A g-1 and outstanding cycling stability of 106.1 mAh g-1 at the high current density of 5.0 A g-1 after 2000 cycles, which is superior to the individual COF. The structural advantages of the covalent organic framework linking by double functional groups (d-COF) can develop a new road for that COF anode material for PIBs in further research.

Fumarate mitigates disruption induced by fenpropathrin in the silkworm Bombyx mori (Lepidoptera): A metabolomics study.

The silkworm Bombyx mori L. is a model organism of the order Lepidoptera. Understanding the mechanism of pesticide resistance in silkworms is valuable for Lepidopteran pest control. In this study, comparative metabolomics was used to analyze the metabolites of 2 silkworm strains with different pesticide resistance levels at 6, 12, and 24 h after feeding with fenpropathrin. Twenty-six of 27 metabolites showed significant differences after fenpropathrin treatment and were classified into 6 metabolic pathways: glycerophospholipid metabolism, sulfur metabolism, glycolysis, amino acid metabolism, the urea cycle, and the tricarboxylic acid (TCA) cycle. After analyzing the percentage changes in the metabolic pathways at the 3 time points, sulfur metabolism, glycolysis, and the TCA cycle showed significant responses to fenpropathrin. Confirmatory experiments were performed by feeding silkworms with key metabolites of the 3 pathways. The combination of iron(II) fumarate + folic acid (IF-FA) enhanced fenpropathrin resistance in silkworms 6.38 fold, indicating that the TCA cycle is the core pathway associated with resistance. Furthermore, the disruption of several energy-related metabolic pathways caused by fenpropathrin was shown to be recovered by IF-FA in vitro. Therefore, IF-FA may have a role in boosting silkworm pesticide resistance by modulating the equilibrium between the TCA cycle and its related metabolic pathways.

[Biomechanical analysis of four internal fixations for Pauwels â ¢ femoral neck fractures with defects].

OBJECTIVE: To investigate the biomechanical characteristics of different internal fixations for Pauwels type Ⅲ femoral neck fracture with defect, and provide reference for the treatment of femoral neck fracture. METHODS: Three-dimensional (3D) finite element models of femoral neck fractures were established based on CT images, including fracture and fracture with defects. Four internal fixations were simulated, namely, inverted cannulated screw(ICS), ICS combined with medial buttress plate, the femoral neck system (FNS) and FNS combined with medial buttress plate. The von Mises stress, model stiffness and fracture displacements of fracture models under 2 100 N axial loads were measured and compared. RESULTS: When femoral neck fracture was fixed by ICS and FNS, the peak stress was mainly concentrated on the surface of the screw near the fracture line, and the peak stress of FNS is higher than that of ICS;When the medial buttress plate was combined, the peak stress was increased and transferred to medial buttress plate, with more obvious of ICS fixation. For the same fracture model, the stiffness of FNS was higher than that of ICS. Compared with femoral neck fracture with defects, fracture model showed higher stiffness in the same internal fixation. The use of medial buttress plate increased model stiffness, but ICS increased more than FNS. The fracture displacement of ICS model exceeded that of FNS. CONCLUSION: For Pauwels type Ⅲ femoral neck fracture with defects, FNS had better biomechanical properties than ICS. ICS combined with medial buttress plate can better enhance fixation stability and non-locking plate is recommended. FNS had the capability of shear resistance and needn't combine with medial buttress plate.

Bombyx mori Ecdysone Receptor B1 May Inhibit BmNPV Infection by Triggering Apoptosis.

Bombyx mori nucleopolyhedrovirus (BmNPV) is a serious threat to sericulture. Nevertheless, no effective control strategy is currently available. The innate immunity of silkworm is critical in the antiviral process. Exploring its molecular mechanism provides theoretical support for the prevention and treatment of BmNPV. Insect hormone receptors play an essential role in regulating host immunity. We found a correlation between Bombyx mori ecdysone receptor B1 (BmEcR-B1) and BmNPV infection, whereas the underlying mechanism remains unclear. In this study, the expression patterns and sequence characteristics of BmEcR-B1 and its isoform, BmEcR-A, were initially analyzed. BmEcR-B1 was found to be more critical than BmEcR-A in silkworm development and responses to BmNPV. Moreover, RNAi and an overexpression in BmN cells showed BmEcR-B1 had antiviral effects in the presence of 20-hydroxyecdysone (20E); Otherwise, it had no antiviral activity. Furthermore, BmEcR-B1 was required for 20E-induced apoptosis, which significantly suppressed virus infection. Finally, feeding 20E had no significant negative impacts on larval growth and the cocoon shell, suggesting the regulation of this pathway has practical value in controlling BmNPV in sericulture. The findings of this study provide important theoretical support for understanding the mechanism of the silkworm innate immune system in response to BmNPV infection.

The importance of the thickness of femoral lateral wall for treating intertrochanteric fractures: a finite elements analysis.

To explore how the thickness of the femoral lateral wall influences the effectiveness of internal fixation systems used to treat intertrochanteric fractures. CT images of the pelvis and femur of a male adult were used to construct an intertrochanteric fracture model (AO/OTA 31-A2) with various thicknesses of the femoral lateral wall (FLW). Four finite element (FE) models were created with the lateral femoral walls being 10 mm, 20 mm, 30 mm, and 40 mm thick. The fracture models were fixed with a dynamic hip screw (DHS), a proximal femoral nail anti-rotation (PFNA), and a proximal femoral locking compression plate (P-FLCP). A simulated vertical load was applied to the femoral head. The stress and displacement of the implant and femur in each model were recorded for comparison. The FE analysis of the intertrochanteric fracture models showed that the PFNA system could provide better stability than the DHS and P-FLCP with the same thickness of FLW. The FLW provided buttress support to the femoral head and neck when using a DHS and PFNA, and the buttress strength was proportional to the thickness of FLW. The maximum stress in the DHS model was recorded on the DHS plate which accommodated the lag screw. For the PFNA model, the maximum stress appeared at the connection between the nail and blade. In the P-FLCP model, the maximum stresses were highly concentrated at the connection between the cephalic nails and the proximal plate. The thickness of the femoral lateral wall should be considered an important factor when selecting a suitable internal fixation system for intertrochanteric fractures. Based on the FE analysis, intramedullary fixation, such as PFNA, experiences lower stress levels and a moderate displacement in comparison to DHS and P-FCLP when used to treat intertrochanteric fractures.

Co-substitution in a Prussian blue analog with a hollow heterostructure for ultrahigh capacity and rate capability aqueous Zn2+ batteries.

Nickel and manganese co-substitution into hollow Prussian blue nanocubes (H-PBMN) has been successfully carried out via utilizing a high-concentration polymer template to grow manganese-Prussian blue (PBM) and nickel-Prussian blue (PBN) through a slow nucleation process. Due to the hollow structure and double metal co-substitution, the properties of the electrode material have been optimized, and it presents an ultrahigh capacity of 138.4 mA h g-1 at 0.05 A g-1.

[Characteristics of femoral neck fractures in young and middle-aged adults based on fracture mapping technology].

Objective: To analyze the characteristics of femoral neck fractures in young and middle-aged adults by means of medical image analysis and fracture mapping technology to provide reference for fracture treatment. Methods: A clinical data of 159 young and middle-aged patients with femoral neck fractures who were admitted between December 2018 and July 2019 was analyzed. Among them, 99 patients were male and 60 were female. The age ranged from 18 to 60 years, with an average age of 47.9 years. There were 77 cases of left femoral neck fractures and 82 cases of right sides. Based on preoperative X-ray film and CT, the fracture morphology was observed and classified according to the Garden classification standard and Pauwels' angle, respectively. Mimics19.0 software was used to reconstruct the three-dimensional models of femoral neck fracture, measure the angle between the fracture plane and the sagittal plane of the human body, and observe whether there was any defect at the fracture end and its position on the fracture surface. Through reconstruction, virtual reduction, and image overlay, the fracture map was established to observe the fracture line and distribution. Results: According to Garden classification standard, there were 6 cases of type Ⅰ, 61 cases of type Ⅱ, 54 cases of type Ⅲ, and 38 cases of type Ⅳ. According to the Pauwels' angle, there were 12 cases of abduction type, 78 cases of intermediate type, and 69 cases of adduction type. The angle between fracture plane and sagittal plane of the human body ranged from -39° to +30°. Most of them were Garden type Ⅱ, Ⅳ and Pauwels intermediate type. The fracture blocks were mainly in the form of a triangle with a long base and mainly distributed below the femoral head and neck junction area. Twenty-six cases (16.35%) were complicated with bone defects, which were mostly found in Garden type Ⅲ, Ⅳ, and Pauwels intermediate type, located at the back of femoral neck and mostly involved 2-4 quadrants. The fracture map showed that the fracture line of the femoral neck was distributed annularly along the femoral head and neck junction. The fracture line was dense above the femoral neck and scattered below, involving the femoral calcar. Conclusion: The proportion of displaced fractures (Garden type Ⅲ, Ⅳ) and unstable fractures (Pauwels intermediate type, adduction type) is high in femoral neck fractures in young and middle-aged adults, and comminuted fractures and bone defects further increase the difficulty of treatment. In clinical practice, it is necessary to choose treatment plan according to fracture characteristics. Anatomic reduction and effective fixation are the primary principles for the treatment of femoral neck fracture in young and middle-aged adults.

A method to classify bone marrow cells with rejected option.

Bone marrow cell morphology has always been an important tool for the diagnosis of blood diseases. Still, it requires years of experience from a suitable person. Furthermore, the outcomes of their recognition are subjective and there is no objective quantitative standard. As a result, developing a deep learning automatic classification system for bone marrow cells is extremely important. However, typical classification machine learning systems only produce classification answers, and will not refuse to generate predictions when the prediction reliability is low. It will pose a big problem in some high-risk systems such as bone marrow cell recognition. This paper proposes a bone marrow cell classification method with rejected option (CMWRO) to classify 11 bone marrow cells. CMWRO is based on convolutional neural networks, ICP and SoftMax (CNN-ICP-SoftMax), containing a classifier with rejected option. When the rejected rate (RR) of tested samples is 0.3143, it can ensure that the precision, sensitivity, accuracy of the accepted samples reach 0.9921, 0.9917 and 0.9944 respectively. And the rejected samples will be handled by other ways, such as identified by doctors. Besides, the method has a good filtering effect on cell types that the classifier is not trained, such as abnormal cells and cells with less sample distribution. It can reach more than 82% in filtering efficiency. CMWRO improves the doctors' trust in the results of accepted samples to a certain extent. They only need to carefully identify the samples that CMWRO refuses to recognize, and finally combines the two results. It can greatly improve the efficiency and accuracy of bone marrow cell recognition.