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Abstract View graph construction aims to effectively organise disordered image dataset through image retrieval technique before structure from motion (SfM). Existing view graph construction methods usually fail to handle scenes with duplicate structure, because these methods solely treat the construction of view graph as a process of image‐pair‐wise matching and lack in exploiting images' topological details in dataset. In this paper, we handle this problem from a novel perspective to construct view graph in a global paradigm by introducing an end‐to‐end graph convolutional network (GCN). First, a location‐aware embedding module is introduced to encode images into a feature space that takes into account the feature's location by using Vision Transformer architecture, improving the distinction between features of duplicate structure. Second, graph convolutional network that consists of topological relationship preserving module and feature metric learning module is proposed. Topological relationship preserving network is proposed to help nodes maintain their connected neighbourhood features. By merging the topological connected information into images' embedding, our method can process image matching in a global mode, thus improving the disambiguation ability for images with duplicate scenes. Then a feature metric learning network is embedded into GCN to dynamically compute the linkage prediction among nodes based on their features. Finally, our method combines these three parts to jointly optimise nodes' features and linkage prediction in an end‐to‐end paradigm. We make qualitative and quantitative comparisons based on three public benchmark datasets and demonstrate that our proposed method performs favourably against other state‐of‐the‐art methods.

Electrocatalytic reduction of CO2 into multi-carbon alcohols of high economic merit offers an effective means to close the carbon cycle. Here the authors show the synergy between inorganic and organic phases derived from rationally designed molecular precursors to produce alcohols in high efficiency.

The purpose of this study was to investigate the effect of cystic areas of osteonecrosis of the femoral head (ONFH) on stress distribution and disease progression in the femoral head. A total of 85 patients (106 hips) diagnosed with Association Research Circulation Osseous stage II non-traumatic and non-surgical treatment were retrospectively analyzed. The presence of cystic areas and diameter of cystic areas were compared between the two groups. In addition, five spherical cystic areas of different diameters were constructed and the maximum stress was observed. There was a difference between the two groups in whether cystic areas appeared in the femoral head, with 49.1% in the collapse group showing cystic areas, which was significantly higher than that in the non-collapse group (18.4%) (P < 0.05). In addition, the diameter of the cystic areas was significantly larger in the collapsed group than in the non-collapsed group (P < 0.05). The maximum and mean von Mises stress value around the necrotic area and around the cystic area of the femoral head increased with the increase of the cystic diameter. Stress concentration areas can be generated around the cystic areas. The presence and increased diameter of the cystic areas accelerates the collapse of the ONFH femoral head.

Physical layer security (PLS) is considered one of the most promising solutions to solve the security problems of massive Internet of Things (IoTs) devices because of its lightweight and high efficiency. Significantly, the recent physical layer key generation (PLKG) scheme based on transmission delay proposed by Huang et al. (2021) does not have any restrictions on communication methods and can extend the traditional physical layer security based on wireless channels to the whole Internet scene. However, the secret-sharing strategy adopted in this scheme has hidden dangers of collusion attack, which may lead to security problems such as information tampering and privacy disclosure. By establishing a probability model, this article quantitatively analyzes the relationship between the number of malicious collusion nodes and the probability of key exposure, which proves the existence of this security problem. In order to solve the problem of collusion attack in Huang et al.’s scheme, this article proposes an anti-collusion attack defense method, which minimizes the influence of collusion attack on key security by optimizing parameters including the number of the middle forwarding nodes, the random forwarding times, the time delay measurement times and the out-of-control rate of forwarding nodes. Finally, based on the game model, we prove that the defense method proposed in this article can reduce the risk of key leakage to zero under the scenario of the “Careless Defender” and “Cautious Defender” respectively.

Electroreduction of CO2 into value-added chemicals and fuels utilizing renewable electricity offers a sustainable way to meet the carbon-neutral goal and a viable solution for the storage of intermittent green energy sources. At the core of this technology is the development of electrocatalysts to accelerate the redox kinetics of CO2 reduction reactions (CO2RR) toward high targeted-product yield at minimal energy input. This perspective focuses on a unique category of CO2RR electrocatalysts embodying both inorganic and organic components to synergistically promote the reaction activity, selectivity and stability. First, we summarize recent progress on the design and fabrication of organic/inorganic hybrids CO2RR electrocatalysts, with special attention to the assembly protocols and structural configurations. We then carry out a comprehensive discussion on the mechanistic understanding of CO2RR processes tackled jointly by the inorganic and organic phases, with respect to the regulation of mass and charge transport, modification of double-layer configuration, tailoring of intermediates adsorption, and establishment of tandem pathways. At the end, we outline future challenges in the rational design of organic/inorganic hybrids for CO2RR and further extend the scope to the device level. We hope this work could incentivize more research interests to construct organic/inorganic hybrids for mobilizing electrocatalytic CO2RR towards industrialization.

We report a case of a man in his early 50 s who was admitted to our hospital for anorexia. An imaging examination led to a preoperative diagnosis of a gastrointestinal stromal tumor and gallbladder stones. He underwent treatment by laparoscopic cholecystectomy and distal partial gastrectomy with lymph node dissection. The final histopathological diagnosis was gastric schwannoma and tubular adenoma of the gallbladder. Gastric schwannoma accounts for only 0.2% of all gastric tumors, and tubular adenoma constitutes only 2.2% of gallbladder tumors. This report describes the diagnosis and treatment process for this combination of tumors, thus providing a reference for similar cases.

ObjectiveThis study aims to observe the changes of the umbilical venous–arterial index (VAI) and investigate its predictive power for fetal outcome during the second half of pregnancy.MethodsFetuses with gestational age (GA) at 24–39 weeks were collected. According to the outcome score, neonates with outcome scores of 0, 1, or 2 were assigned to the control group, whereas those with scores of 3–12 were assigned to the compromised group. VAI was calculated as the ratio of normalized umbilical vein blood flow volume and umbilical artery pulsatility index. Regression analysis was performed to obtain the best-fitting curves between VAI and GA in the controls. Doppler parameters and perinatal outcomes were compared in both groups. Receiver operating characteristic analysis was used to assess the diagnostic performance of the VAI.ResultsA total of 833 (95%) fetuses had Doppler parameters and pregnancy outcomes documented. Compared with the controls, the VAI was significantly lower in the compromised group (83.2 vs. 184.8 ml/min/kg, p

Abstract The broadband impedance of converters is an essential feature for the stability analysis of new energy sources. However, obtaining the impedance for photovoltaic (PV) converters with Maximum Power Point Tracking (MPPT) control is challenging because of their non‐linear control schemes and real‐time changing operating points. In this case, conventional linearized impedance modelling methods are not applicable, and conventional direct measurement approaches are highly time‐consuming. This paper proposes a few‐shot learning approach for quick access to PV converters’ impedance. The proposed method is based on the model agnostic meta‐learning (MAML) algorithm, suitable for MPPT‐controlled converters whose impedance changes with time, temperature, and irradiation. In the training process, it adjusts the initial model of the machine learning algorithm under different weather conditions. After completing the training, the initial model can adapt to a new condition with very few samples. Under this approach, with only a few data measured at several frequency points, broadband impedance for MPPT‐controlled converters under any weather conditions can be accurately predicted, avoiding time‐consuming measurements and inaccurate prediction of existing methods. Contrast simulation results show the effectiveness and superiority of the proposed method.

Metals such as Cu and Cr have good infrared reflection properties, but there are few reports on their effects on the optical properties of solar spectrum absorption layers. Herein, Cu and Cr infrared reflectors were deposited under AlCrNO absorbing layer by multi arc ion plating technology, and the effects of deposition parameters of infrared reflectors on coating properties were studied. The morphology, element composition and phase structure of the coating were analyzed by scanning electron microscope, energy dispersive spectrometer and X - ray diffraction. Results showed that compared with the coating without infrared reflection layer, the coating with Cu infrared reflection layer had the best performance, the absorptivity was increased by 1.7%, and the emissivity was reduced by 31.9%. Besides, the absorptivity and emissivity of coating with Cr infrared reflector were increased by 0.6% and 13%, respectively. Therefore, Cu was better than Cr as infrared reflector.

Photocatalytic technology has received increasing attention in recent years. A pivotal facet of photocatalytic technology lies in the development of photocatalysts. Porous metal–organic framework (MOF) materials, distinguished by their unique properties and structural characteristics, have emerged as a focal point of research in the field, finding widespread application in the photo-treatment and conversion of various substances. Fe-based MOFs have attained particular prominence. This review explores recent advances in the photocatalytic degradation of aqueous and gaseous substances. Furthermore, it delves into the interaction between the active sites of Fe-MOFs and pollutants, offering deeper insights into their mechanism of action. Fe-MOFs, as photocatalysts, predominantly facilitate pollutant removal through redox processes, interaction with acid sites, the formation of complexes with composite metal elements, binding to unsaturated metal ligands (CUSs), and hydrogen bonding to modulate their respiratory behavior. This review also highlights the focal points of future research, elucidating the challenges and opportunities that lie ahead in harnessing the characteristics and advantages of Fe-MOF composite catalysts. In essence, this review provides a comprehensive summary of research progress on Fe-MOF-based catalysts, aiming to serve as a guiding reference for other catalytic processes.

When examining the history of wind engineering, it is evident that many full-scale/model test comparisons have found noticeable differences between the results. Although understanding the causes of these differences is important for practical purposes, limited numerical and experimental conditions have often resulted in subjective explanations for full-scale/model test comparisons without scientific validation. To address this issue, this article suggests the use of the computational fluid dynamics technique or the multiple-fan actively controlled wind tunnel technique to quantitatively reveal the adverse effects that impact the reliability of the traditional atmospheric boundary layer wind tunnel tests for a large cooling tower, including not only the widely acknowledged influences (Reynolds number effects and turbulent flow characteristics effects) but also the non-stationarity effects that have potential influences. Established on the novel proposition, a new research scheme for future full-scale/model test wind effects comparisons for large cooling towers has been formulated based on the numerical or physical simulations of the sinusoidal flow fields. Using the Pengcheng cooling tower as a case study, the research recognized the very significant impact of Reynolds number effects, the non-stationarity effects that cannot be ignored, and the negligible effects of turbulent flow characteristics.

Metal-organic frameworks are promising catalysts for CO2 electroreduction, yet limited by their poor conductivity and stability. Here, Au nanoneedles are inserted into the metalloporphyrin framework to activate C-C coupling and stabilize the structure for much enhanced ethylene production.

Abstract Metal–organic frameworks (MOFs), which are synthesized through the self‐assembly of organic ligands and inorganic metals, have drawn considerable research interest owing to their unique properties and attractive structures. Many studies on various MOF derivatives, such as MOFs and cellulose aerogels, hydrogel composite materials, and bimetallic‐centered MOF materials, have provided the potential for wide application of MOFs. However, MOFs mostly exist in the form of powder particles, which are difficult to form. In addition, MOFs have problems with structural instability. MOF‐based gels can overcome this problem. MOF‐based gels also have significant advantages in secondary processing. In this review, synthetic methods for MOF‐based gels, particularly the synergistic effect with other materials, are introduced. The applications of MOF‐based hydrogels and aerogels in supercapacitors, water treatment, catalysis, adsorption, and energy storage are also discussed.

The electrochemical CO2 reduction reaction (CO2RR) on Cu catalyst holds great promise for converting CO2 into valuable multicarbon (C2+) compounds, but still suffers poor selectivity due to the sluggish kinetics of forming carbon–carbon (C–C) bonds. Here we reported a perovskite oxide-derived Cu catalyst with abundant grain boundaries for efficient C–C coupling. These grain boundaries are readily created from the structural reconstruction induced by CO2-assisted La leaching. Using this defective catalyst, we achieved a maximum C2+ Faradaic efficiency of 80.3% with partial current density over 400 mA cm−2 in neutral electrolyte in a flow-cell electrolyzer. By combining the structural and spectroscopic investigations, we uncovered that the in-situ generated defective sites trapped by grain boundaries enable favorable CO adsorption and thus promote C–C coupling kinetics for C2+ products formation. This work showcases the great potential of perovskite materials for efficient production of valuable multicarbon compounds via CO2RR electrochemistry.

Nowadays, digital construction has become popular when bringing convenience and efficiency to the traditional building construction industry. The primary tool of digital construction is the building information model (BIM). However, from the perspective of general contractors, unresolved puzzles still hinder obtaining the benefits of digital construction. When establishing a unified BIM from submodels provided by subcontractors, there will possibly be incomplete or inconsistent data during model merging. But extracting submodels from unified BIM often includes redundant data, thus making models less usable for subcontractors. It is also difficult for general contractors to effectively and accurately utilize resource information and submodel changes. This paper proposed solutions that depend on the widely adopted industry foundation classes standard to ensure the universality of our methods. First, a model merging algorithm is proposed to support the continuous merge of submodels created by different subcontractors. Second, an instance-level model extraction method based on strongly related entities is proposed, which extracts model instances to the minimum submodel and meets the subcontractor requirements at the same time. Third, the new model storage and indexing method are designed to reduce the complexity of model data and support rapid data retrieval, and a new BIM change detection method based on object metadata is provided. The proposed methods were applied by the general contractor of a large airport project during the construction stage. The application results proved that the proposed methods could ensure the quality of established deepening design models and extracted submodels and significantly reduce human labor by improving efficiency when utilizing BIM, which in turn supported key scenarios throughout the digital construction workflow.

AimsThe present systematic review and meta-analysis of randomized controlled trials (RCTs) was conducted to investigate the effect of low volume high-intensity interval training (LVHIIT) on the metabolic and cardiorespiratory outcomes in patients with type 2 diabetes mellitus (T2DM).MethodsRelevant articles were sourced from PubMed, EBSCO, Web of Science, Embase, and the Cochrane Library from inception to October 2022. The study search strategy and all other processes were implemented in accordance with the PRISMA statement.ResultsFive randomized controlled trials that satisfied the inclusion criteria were included in this meta-analysis. The LVHIIT group had significantly lower fasting blood glucose levels (RR= -1.21; 95% CI= -2.02— -0.40, p = 0.0032) and HbA1c levels (RR= -0.65; 95% CI= -1.06— -0.23, p = 0.002) and higher levels of insulin resistance indicator HOMA-IR (RR= -1.34; 95% CI = -2.59— -0.10, p = 0.03) than the control group. Moreover, our results show that LVHIIT can reduce body mass (RR = -0.94, 95% CI = -1.37— -0.51, p

Abstract Background Quantitative reverse transcription-polymerase chain reaction (qRT-PCR) is the most sensitive technique for evaluating gene expression levels. Choosing appropriate reference genes (RGs) is critical for normalizing and evaluating changes in the expression of target genes. However, uniform and reliable RGs for breast cancer research have not been identified, limiting the value of target gene expression studies. Here, we aimed to identify reliable and accurate RGs for breast cancer tissues and cell lines using the RNA-seq dataset. Methods First, we compiled the transcriptome profiling data from the TCGA database involving 1217 samples to identify novel RGs. Next, ten genes with relatively stable expression levels were chosen as novel candidate RGs, together with six conventional RGs. To determine and validate the optimal RGs we performed qRT-PCR experiments on 87 samples from 11 types of surgically excised breast tumor specimens (n = 66) and seven breast cancer cell lines (n = 21). Five publicly available algorithms (geNorm, NormFinder, ΔCt method, BestKeeper, and ComprFinder) were used to assess the expression stability of each RG across all breast cancer tissues and cell lines. Results Our results show that RG combinations SF1 + TRA2B + THRAP3 and THRAP3 + RHOA + QRICH1 showed stable expression in breast cancer tissues and cell lines, respectively, and that they displayed good interchangeability. We propose that these combinations are optimal triplet RGs for breast cancer research. Conclusions In summary, we identified novel and reliable RG combinations for breast cancer research based on a public RNA-seq dataset. Our results lay a solid foundation for the accurate normalization of qRT-PCR results across different breast cancer tissues and cells.

Abstract Background Immunochemotherapy is a potent anti-tumor strategy, however, how to select therapeutic drugs to enhance the combined therapeutic effect still needs to be explored. Methods and results Herein, a magnetic resonance nanoprobe (MnP@Lip) with STING (Stimulator of INterferon Genes) activation character was synthesized and co-administered with platinum-based chemotherapeutics for enhanced immunochemotherapy. MnP@Lip nanoparticles was prepared by simple fabrication process with good reproducibility, pH-sensitive drug release behavior and biocompatibility. In vitro experiments elucidated that Mn2+ can promote the polarization of M0 and/or M2 macrophages to M1 phenotype, and promote the maturation of BMDC cells. Upon Mn2+ treatment, the STING pathway was activated in tumor cells, mouse lung epithelial cells, and immune cells. More importantly, anti-tumor experiments in vivo proved that MnP@Lip combined with platinum-based chemotherapeutics increased T cells infiltration in the tumor microenvironment, and inhibited tumor growth in the orthotopic therapeutic and postoperative tumor models. Conclusions This kind of therapeutic strategy that combined MnP@Lip nanoparticles with platinum-based chemotherapeutics may provide a novel insight for immunochemotherapy. Graphical Abstract

The substrate-catalyst interaction plays a critical role in steering the pathway of electrochemical CO2 reduction. Here the authors show the crystalline states of copper in reconstructed metal-organic frameworks were induced and stabilized by Ketjen Black conducting support, promoting C2H4 production.

To explore reasons and solutions for the rancidity of peanut nougat in storage, this paper investigates the oxidation stability of shelled peanuts and unshelled peanut stored in different temperatures and the quality of nougats prepared by adding peanuts treated in different ways. The results show that when raw peanuts are stored at temperatures of 25 ℃, 37 ℃ and 60 ℃, the oxidation rate of shelled raw peanuts is slower than that of unshelled raw peanuts. The peroxide value of shelled peanuts does not change significantly and is stable below 2 mmol/kg, while the peroxide value of roasted cooked peanuts changes faster when stored at 60 ℃, and the change of the shelled peanuts is slower than that of the unshelled peanuts. The oxidation rate of baked shelled peanuts is slower than that of unshelled, which could potentially prolong the shelf life of peanut nougats made of them.

Abstract Ferroptosis is a new form of regulated cell death (RCD), and its emergence has provided a new approach to the progression and drug resistance of breast cancer (BRCA). However, there is still a great gap in the study of ferroptosis-related genes in BRCA, especially luminal-type BRCA patients. We downloaded the mRNA expression profiles and corresponding clinical data of BRCA patients from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) and The Cancer Genome Atlas (TCGA) databases. Then, we built a prognostic multigene signature with ferroptosis-related differentially expressed genes (DEGs) in the METABRIC cohort and validated it in the TCGA cohort. The predictive value of this signature was investigated in terms of the immune microenvironment and the probability of a response to immunotherapy and chemotherapy. The patients were divided into a high-risk group and a low-risk group according to the ferroptosis-associated gene signature, and the high-risk group had a worse overall survival (OS). The risk score based on the 10 ferroptosis-related gene-based signature was determined to be an independent prognostic predictor in both the METABRIC and TCGA cohorts (HR, 1.41, 95% CI, 1.14–1.76, P = 0.002; HR, 2.19, 95% CI, 1.13–4.26, P = 0.02). Gene set enrichment analysis indicated that the term “cytokine-cytokine receptor interaction” was enriched in the high-risk score subgroup. Moreover, the immune infiltration scores of most immune cells were significantly different between the two groups, the low-risk group was much more sensitive to immunotherapy, and six drugs might have potential therapeutic implications in the high-risk group. Finally, a nomogram incorporating a classifier based on the 10 ferroptosis-related genes, tumor stage, age and histologic grade was established. This nomogram showed favorable discriminative ability and could help guide clinical decision-making for luminal-type breast carcinoma.

Effective treatment of water pollution is an economic and social requirement globally. Humic acid (HA) is a popular mitigator for such waters. However, the combined effect of HA and restorative plants on cadmium (Cd) remediation is not well understood. Therefore, we experimented on Cd remediation using HA along with vetiver grass and HA-vetiver grass. We observed that vetiver grass effectively removed Cd at 15～30 mg/L. The accumulation capacity of the root was significantly higher than the shoots (P organelle > soluble substance (F1 > F2 > F3). The plant’s accumulation capacity against 25 mg/L Cd was higher than for other treatments. The root accumulation capacity was much higher (702.3 mg/L) than those without added HA. However, upon adding 200 and 250 mg/L HA, the phytoremediation of Cd in the root and shoot significantly reduced (P

Serverless computing has become increasingly popular recently due to its cost efficiency and flexibility. However, running serverless computing functions in the cloud can incur high end-to-end service latency and operational costs. Running them on edge servers may significantly reduce service latency but is limited by computing power and memory availability. Given the limitations of cloud and edge environments for performing serverless computing, this paper proposes a joint function warm-up and request routing scheme to perform serverless computing functions on edge and cloud collaboratively. The key idea of the new scheme is to maximize the hit ratio of serverless computing requests, thereby reducing the cold-start latency that dominates the overall serving latency. This scheme explicitly considers allocating server memory and operation budget for executing concurrent requests during the scheduling. The proposed scheme has been evaluated through extensive simulations. Its effectiveness has been proved by comparison with the upper-bound results.

Purpose: Three-dimensional (3D) printing technology has emerged as a new treatment method due to its precision and personalization. This study aims to explore the application of a 3D-printed personalized porous tantalum cone for reconstructing the bone defect in total knee arthroplasty (TKA) revision.Methods: Between November 2017 and October 2020, six patients underwent bone reconstruction using 3D-printed porous tantalum cones in TKA revision. The knee function was assessed using the Hospital for Special Surgery (HSS) score pre- and postoperatively. The pain was measured by the visual analog scale (VAS) pre- and postoperatively. The quality of life was measured using the 36-Item Short Form Health Survey (SF-36) to pre- and postoperatively evaluate the relief of pain. Operation time, intraoperative blood loss, postoperative drainage volume, and complications were also recorded. At the last follow-up, all patients received X-ray and computed tomography (CT) to confirm the effect of bone reconstruction.Results: After an average follow-up duration of 26.3 months, no patients developed any operation-related complications. The average intraoperative blood loss and postoperative drainage volumes were 250.1 ± 76.4 ml and 506.7 ± 300.8 ml, respectively. At the last follow-up, the HSS score was significantly higher than that before operation, indicating that the knee function was significantly improved (p < 0.001). During the follow-up, the mean VAS score decreased and the mean SF-36 score increased, both of which were significantly improved compared with preoperative conditions (p < 0.001). Radiological examination at the final follow-up showed that cones implanted into the joint were stable and bone defects were effectively reconstructed.Conclusion: This study demonstrated that 3D-printed porous tantalum cones could effectively reconstruct bone defects and offer anatomical support in TKA revision. Further studies are still needed to confirm the long-term effect of 3D-printed tantalum cones for reconstructing bone defects.

Large amounts of nitrogen fertilizer are annually applied to improve soybean yield. However, the overuse of nitrogen fertilizers has resulted in significant environmental pollution. Biological nitrogen fixation is an ecological and environmentally friendly method to increase soybean yield. However, the signaling pathway and function of genes in the plant host regulated by rhizobia under the symbiotic relationship remain unknown. In this study, the chromosome region in soybean responsive to Sinorhizobium fredii HH103 was identified using chromosome-segment-substituted lines produced from a cross between cultivated soybean SN14 and wild soybean Zyd00006. In addition, candidate genes associated with nodulation traits and regulated by S. fredii HH103 were identified. In total, three quantitative trait loci (QTLs) containing 68 genes were identified on chromosomes 02, 05, and 20. The differentially expressed genes among the QTL regions were determined using RNA-seq and qRT-PCR. Glyma. 05G240500, a potential gene responding to S. fredii HH103 and positively regulating soybean nodulation, was identified. To explore the relationships between haplotypes and soybean nodulation phenotypes, SNPs found in the regulatory areas of Glyma.05G240500 haplotype were investigated. Our study revealed the role of Glyma.05G240500 in symbiosis and provided a reference for facilitating symbiotic nitrogen fixation in the field and for marker-assisted selection.

To investigate whether parameters from IDEAL-IQ/amide proton transfer MRI (APTWI) could help predict histopathological factors of rectal cancer. Preoperative IDEAL-IQ and APTWI sequences of 67 patients with rectal cancer were retrospectively analyzed. The intra-tumoral proton density fat fraction (PDFF), R2* and magnetization transfer ratio asymmetry (MTRasym (3.5 ppm)) were measured according to the histopathological factors of rectal cancer. The relationship between MR parameters and histopathological factors were analyzed, along with diagnostic performance of MR parameters. PDFF, R2* and MTRasym (3.5 ppm) were statistically different between T1+T2/T3+T4 stages, non-metastatic/metastatic lymph nodes, lower/higher tumor grade and negative/positive status of MRF and EMVI (p < 0.001 for PDFF, p = 0.000–0.015 for R2* and p = 0.000–0.006 for MTRasym (3.5 ppm)). There were positive correlations between the above parameters and the histopathological features of rectal cancer (r = 0.464–0.723 for PDFF (p < 0.001), 0.299–0.651 for R2* (p = 0.000–0.014), and 0.337–0.667 for MTRasym (3.5 ppm) (p = 0.000–0.005)). MTRasym (3.5 ppm) correlated moderately and mildly with PDFF (r = 0.563, p < 0.001) and R2* (r = 0.335, p = 0.006), respectively. PDFF provided a significantly higher diagnostic ability than MTRasym (3.5 ppm) for distinguishing metastatic from non-metastatic lymph nodes (z = 2.407, p = 0.0161). No significant differences were found in MR parameters for distinguishing other histopathological features (p > 0.05). IDEAL-IQ and APTWI were associated with histopathological factors of rectal cancer, and might serve as non-invasive biomarkers for characterizing rectal cancer.

Automatic modulation classification (AMC) is a signal processing technology used to identify the modulation type of unknown signals without prior information such as modulation parameters for drone communications. In recent years, deep learning (DL) has been widely used in AMC methods due to its powerful feature extraction ability. The significant performance of DL-based AMC methods is highly dependent on large amount of data. However, with the increasingly complex signal environment and the emergence of new signals, several recognition tasks have difficulty obtaining sufficient high-quality signals. To address this problem, we propose an AMC method based on a deep residual neural network with masked modeling (DRMM). Specifically, masked modeling is adopted to improve the performance of a deep neural network with limited signal samples. Both complex-valued and real-valued residual neural networks (ResNet) play an important role in extracting signal features for identification. Several typical experiments are conducted to evaluate our proposed DRMM-based AMC method on the RadioML 2016.10A dataset and a simulated dataset, and comparison experiments with existing AMC methods are also conducted. The simulation results illustrate that our proposed DRMM-based AMC method achieves better performance in the case of limited signal samples with low signal-to-noise ratio (SNR) than other existing methods.

ObjectiveTo assess the specificity of P50 auditory-evoked potential in schizophrenic patients with violent and aggressive behaviors， so as to provide objective biological markers for predicting violent behaviors of schizophrenic patients.MethodsA total of135 schizophrenic patients who met the diagnostic criteria of the International Classification of Diseases， tenth edition （ICD-10） were divided into aggressive group （n=70） and non-aggressive group （n=65） according to the assessment results of the Modified Overt Aggression Scale （MOAS）， meantime， another 60 healthy individuals matched for age and gender were set as healthy group. Then the P50 auditory-evoked potentials of all selected individuals were measured using EP/EMG system （MEB-9200， Nihon Kohden， Japan）.ResultsAmp S2 of the aggressive group was significantly higher than those of the non-aggressive group and healthy control group， with statistical differences ［（9.86±6.04）μV vs. （7.06±3.88）μV， P=0.004； （9.86±6.04）μV vs. （7.82±3.87）μV， P=0.031］. The proportion of S2/S1 ratio ≥0.5 was 72.88%， 43.86% and 30.00% in aggressive group， non-aggressive group and healthy group， which was the highest in aggressive group， with statistical differences （P

Abstract Background Anti-Ku is a rare antibody which can be positive in some rheumatic diseases and it might be related to cardiac involvement. Polymyositis is an inflammatory myopathy, and its cardiac involvement seldom presents as myopericarditis and anti-Ku positive. Case presentation In this case, we report a mid-aged woman with chest pain, upper limbs weakness and fever unrelated with infection. The diagnosis of this case was unquestionably myopericarditis supported by ECG, cardiac MRI and negative findings in coronary arteries. Diagnosis of polymyositis was further clarified by the evidence of persistently increased CK, degeneration of proximal muscle in MRI, muscular dystrophy with lymphocytes infiltration in muscle biopsy. In the analysis of autoantibodies, we surprisingly discovered positive anti-Ku. Glucocorticoid and mycophenolate mofetil were then prescribed for polymyositis. Patient follow-up indicated remission of both myopericarditis and polymyositis. We finally clarified this rare case as a positive anti-Ku polymyositis with myopericarditis as cardiac involvement. Conclusion This report presents a rare case with anti-Ku positive polymyositis and the cardiac involvement of polymyositis was manifested as myopericarditis. Therefore, positive anti-Ku might explain the myopericarditis as cardiac involvement in polymyositis. More cases and longer duration of follow-up is required for the comprehensive understanding of the disease.

Abstract Background Some driver oncogenes are still unknown in non-small-cell lung cancer (NSCLC). DNAJC19, a major component of the translocation machinery of mitochondrial membranes, is a disease-associated protein. Herein, we report the role of DNAJC19 in NSCLC cell growth and metastasis. Methods Immunohistochemistry (IHC) was performed to investigate DNAJC19 expression in NSCLC clinical samples. For knockdown or overexpression assays in A549 or NCI-H1299 lung cancer cells, lentiviral vectors were used. After assessment of cell functions, DNAJC19-knockdown A549 cells were further applied to establish mouse xenograft and metastasis tumor models. Assessments based on the RNA-seq data, western blotting, PCR and IHC were performed for the mechanistic study. Results Expression of DNAJC19 was higher in tumors than in noncancerous adjacent tissues. Survival analysis indicated that low DNAJC19 levels were correlated with an increased progression-free survival rate. ShRNA-mediated knockdown of DNAJC19 markedly inhibited cell growth, viability, migration and invasion. Moreover, RNA-seq analysis revealed that the PI3K/AKT signaling pathway was involved in molecular events when A549 cells were treated with shDNAJC19. In addition, DNAJC19 knockdown decreased PI3Kp85a, AKT and p-AKT expression in A549 cells, and cellular functions were greatly rescued in DNAJC19-knockdown A549 cells by ectopic overexpression of AKT. Furthermore, tumor xenograft growth and lung metastasis were markedly repressed in the shDNAJC19 group compared to the control group. As expected, the expression levels of DNAJC19, PI3K and AKT in xenograft mouse samples were also lower in the shDNAJC19 group than in the shCtrl group. Conclusions DNAJC19 greatly promotes NSCLC cell growth and lung metastasis by regulating PI3K/AKT signaling, providing a novel therapeutic target for treating NSCLC patients.

Abstract Background Pancreatic ductal adenocarcinoma (PDAC) is a fatal disease with molecular heterogeneity, inducing differences in biological behavior, and therapeutic strategy. NGS profiles of pathogenic alterations in the Chinese PDAC population are limited. We conducted a retrospective study to investigate the predictive role of DNA damage repair (DDR) mutations in precision medicine. Methods The NGS profiles were performed on resected tissues from 195 Chinese PDAC patients. Baseline clinical or genetic characteristics and survival status were collected. The Kaplan–Meier survival analyses were performed by the R version 3.6.1. Results The main driver genes were KRAS, TP53, CDKN2A, and SMAD4. Advanced patients with KRAS mutation showed a worse OS than KRAS wild-type (p = 0.048). DDR pathogenic deficiency was identified in 30 (15.38%) of overall patients, mainly involving BRCA2 (n = 9, 4.62%), ATM (n = 8, 4.10%) and RAD50 genes (n = 3, 1.54%). No significance of OS between patients with or without DDR mutations (p = 0.88). But DDR mutation was an independent prognostic factor for survival analysis of advanced PDAC patients (p = 0.032). For DDR mutant patients, treatment with platinum-based chemotherapy (p = 0.0096) or olaparib (p = 0.018) respectively improved the overall survival. No statistical difference between tumor mutation burden (TMB) and DDR mutations was identified. Treatment of PD-1 blockades did not bring significantly improved OS to DDR-mutated patients than the naive DDR group (p = 0.14). Conclusions In this retrospective study, we showed the role of germline and somatic DDR mutation in predicting the efficacy of olaparib and platinum-based chemotherapy in Chinese patients. However, the value of DDR mutation in the prediction of hypermutation status and the sensitivity to the PD-1 blockade needed further investigation.

ObjectiveOur study aims to measure the cortical correlates of swallowing execution in patients with dysphagia after repetitive transcranial magnetic stimulation (rTMS) therapy using functional near-infrared spectroscopy (fNIRS), and observe the change of pattern of brain activation in stroke patients with dysphagia after rTMS intervention. In addition, we tried to analyze the effect of rTMS on brain activation in dysphagia patients with different lesion sides. This study also concentrated on the effect of stimulating the affected mylohyoid cortical region by 5 Hz rTMS, providing clinical evidence for rTMS therapy of dysphagia in stroke patients.MethodsThis study was a sham-controlled, single-blind, randomized controlled study with a blinded observer. A total of 49 patients completed the study, which was randomized to the rTMS group (n = 23) and sham rTMS group (n = 26) by the random number table method. The rTMS group received 5 Hz rTMS stimulation to the affected mylohyoid cortical region of the brain and the sham rTMS group underwent rTMS using the same parameters as the rTMS group, except for the position of the coil. Each patient received 2 weeks of stimulation followed by conventional swallowing therapy. Standardized Swallowing Assessment (SSA), Fiberoptic Endoscopic Dysphagia Severity Scale (FEDSS), Penetration-Aspiration Scale (PAS), and functional oral intake status were assessed at two times: baseline (before treatment) and 2 weeks (after intervention). Meanwhile, we use the fNIRS system to measure the cerebral hemodynamic changes during the experimental procedure.ResultsThe rTMS group exhibited significant improvement in the SSA scale, FEDSS scale, and PAS scale after rTMS therapy (all P < 0.001). The sham rTMS group had the same analysis on the same scales (all P < 0.001). There was no significant difference observed in clinical assessments at 2 weeks after baseline between the rTMS group and sham rTMS group (all P > 0.05). However, there were statistically significant differences between the two groups in the rate of change in the FEDSS score (P = 0.018) and PAS score (P = 0.004), except for the SSA score (P = 0.067). As for the removal rate of the feeding tube, there was no significant difference between the rTMS group and sham rTMS group (P = 0.355), but there was a significant difference compared with the baseline characteristics in both groups (PrTMS < 0.001, PshamrTMS = 0.002). In fNIRS analysis, the block average result showed differences in brain areas RPFC (right prefrontal cortex) and RMC (right motor cortex) significantly between the rTMS group and sham rTMS group after intervention (Pchannel30 = 0.046, Pchannel16 = 0.006). In the subgroup analysis, rTMS group was divided into left-rTMS group and right-rTMS group and sham rTMS group was divided into sham left-rTMS group and sham right-rTMS group. The fNIRS results showed no significance in block average and block differential after intervention between the left-rTMS group and sham left-rTMS group, but differences were statistically significant between the right-rTMS group and sham right-rTMS group in block average: channel 30 (T = −2.34, P = 0.028) in LPFC (left prefrontal cortex) and 16 (T = 2.54, P = 0.018) in RMC. After intervention, there was no significance in left-rTMS group compared with baseline, but in right-rTMS group, channel 27 (T = 2.18, P = 0.039) in LPFC and 47 (T = 2.17, P = 0.039) in RPFC had significance in block differential. In the sham rTMS group, neither sham left-rTMS group and sham right-rTMS group had significant differences in block average and block differential in each brain area after intervention (P > 0.05).ConclusionsThe present study confirmed that a 5-Hz rTMS is feasible at the affected mylohyoid cortical region in post-stroke patients with dysphagia and rTMS therapy can alter cortical excitability. Based on previous studies, there is a dominant hemisphere in swallowing and the results of our fNIRS analysis seemed to show a better increase in cortical activation on the right side than on the left after rTMS of the affected mylohyoid cortical region. However, there was no difference between the left and right hemispheres in the subgroup analysis. Nevertheless, the present study provides a novel and feasible method of applying fNIRS to assessment in stroke patients with dysphagia.

PurposeThis study aimed to determine the effect of neoadjuvant chemotherapy (NAC) on circulating levels of reproductive hormones and evaluate the correlation of hormone changes after NAC with hormone receptors expression alterations and relapse-free survival (RFS) outcomes in breast cancer.MethodsInformation from 181 breast cancer patients who received NAC was retrospectively analyzed. For hormones parameters, the median and interquartile range (IQR) were provided at baseline and the end of NAC then was compared by Wilcoxon signed-rank test. Categorical variables were represented as numbers and percentages and were compared via two-sided chi-square and Fisher's tests. The RFS outcomes were compared between patients according to hormone changes using the log-rank test. Univariate and multivariate survival analyses with hazard ratios (HR) and 95% confidence intervals (95% CI) were carried out using Cox regression.ResultsSex steroids including estradiol, progesterone, testosterone, and dehydroepiandrosterone sulfate (DHEAS) levels decreased significantly after NAC among both premenopausal and postmenopausal patients (all P

The inflammation aroused by implants is the main cause of implant failure. Therefore, the design paradigm of implants has changed from “inertia” to “immunomodulatory”. Although multiple bioactive ions exert effects on osteogenesis, how magnesium ions (Mg2+) manipulate immune response via inducing macrophage polarization and subsequently promote osteogenesis needs further investigation. In this study, phase-transited lysozyme (PTL) is deposited onto the surface of titanium (Ti) to construct a functional coating and magnesium chloride solution at 2.5 mM, 5 mM and 10 mM was utilized to produce PTL coatings with different concentrations of Mg2+ (PTL-Mg2.5, PTL-Mg5 and PTL-Mg10). The characterization of the magnesium-doped PTL coatings (PTL-Mg) was tested by scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDX) and inductively coupled plasma atomic emission spectroscopy (ICP-AES). In addition, we utilized a co-culture system of macrophages and rat bone merrow mesenchymal stem cells (BMSCs) to investigate the osteoimmunomodulatory effects of PTL-Mg coatings. The results showed that compared with other groups, PTL-Mg5 group can create a favorable osteoimmune microenvironment by regulating macrophages polarization and release of inflammatory cytokines, then promote adhesion, proliferation and osteogenic differentiation of BMSCs. The in vivo results further verified the most excellent osteointegration ability of PTL-Mg5 in rat femur lateral condyle defects. This work indicates a promising way for design paradigm of implants with immunomodulatory properties by inducing PTL-Mg5 coating on Ti, providing a new strategy for implants surface modification.

Abstract Background The aim of this study was to evaluate the relationship between pre-treatment plasma fibrinogen (Fib) level and pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) in breast cancer patients and to assess the role of plasma Fib as a predictive factor. Methods Data from 1004 consecutive patients with invasive breast cancer who received NAC and subsequent surgery were retrospectively analysed. Both univariate and multivariate analyses based on logistic regression model were performed to identify clinicopathological factors associated with pCR to NAC. Cox regression model was used to determine the correlation between clinical or pathological parameters and recurrence-free survival (RFS). The Kaplan-Meier method and the log-rank test were applied in the survival analysis. Results The median value of Fib, rather than other plasma coagulation parameters, was significantly increased in non-pCR patients compared with pCR patients (P = 0.002). Based on the cut-off value estimated by the receiver operating characteristic (ROC) curve analysis, patients were divided into low or high Fib groups (Fib 5 cm group (77.5% vs 58.4%, log-rank, P = 0.0168). Conclusions This study demonstrates that low pre-treatment plasma Fib (Fib

The aim of this study is to investigate an implementation method and the results of a voxel-based self-adaptive prescription dose optimization algorithm for intensity-modulated radiotherapy.

Gamma-aminobutyric acid (GABA) is a non-protein amino acid known for its role in the nervous system of animals. However, research has also revealed its presence and function in plants recently. In plants, GABA is a signal molecule involved in multiple physiological processes, including stress response, growth, and development. This review aims to present a thorough summary of the current knowledge regarding the role of GABA in plants. We begin by discussing the biosynthesis and transport of GABA in plants, followed by a detailed examination of its signaling mechanisms. Additionally, we explore GABA's potential roles in various plant physiological processes, such as abiotic stress response, and its potential application in horticultural plants. Finally, we highlight current challenges and future directions for research in this area. Overall, this review offers a comprehensive understanding of the significance of GABA in plants and its potential implications for plant physiology and crop improvement.

Soybean is a cereal crop with high protein and oil content which serves as the main source of plant-based protein and oil for human consumption. The symbiotic relationship between legumes and rhizobia contributes significantly to soybean yield and quality, but the underlying molecular mechanisms remain poorly understood, hindering efforts to improve soybean productivity. In this study, we conducted a transcriptome analysis and identified 22 differentially expressed genes (DEGs) from nodule-related quantitative trait loci (QTL) located in chromosomes 12 and 19. Subsequently, we performed functional characterisation and haplotype analysis to identify key candidate genes among the 22 DEGs that are responsive to nitrate. Our findings identified GmTCP (TEOSINTE-BRANCHED1/CYCLOIDEA/PCF) and GmNLP (NIN-LIKE PROTEIN) as the key candidate genes that regulate the soybean nodule phenotype in response to nitrogen concentration. We conducted homologous gene mutant analysis in Arabidopsis thaliana, which revealed that the homologous genes of GmTCP and GmNLP play a vital role in regulating root development in response to nitrogen concentration. We further performed overexpression and gene knockout of GmTCP and GmNLP through hairy root transformation in soybeans and analysed the effects of GmTCP and GmNLP on nodulation under different nitrogen concentrations using transgenic lines. Overexpressing GmTCP and GmNLP resulted in significant differences in soybean hairy root nodulation phenotypes, such as nodule number (NN) and nodule dry weight (NDW), under varying nitrate conditions. Our results demonstrate that GmTCP and GmNLP are involved in regulating soybean nodulation in response to nitrogen concentration, providing new insights into the mechanism of soybean symbiosis establishment underlying different nitrogen concentrations.

Jatropha curcas var. nigroviensrugosus CV Yang (Jn) exhibits wrinkled leaves and higher flowering and fruiting rates compared to Jatropha curcas L. (Jc). Teosinte branched1/Cincinnata/Proliferating cell factors (TCPs) are known to play crucial roles in plant development and physiological processes. However, it remains unknown whether or not the TCP gene family regulates in leaf development of Jc and Jn. Here, we systematically performed a genome-wide analysis of the Jc TCP family and investigated the differences in the expression of TCP in different leaf morphologies. In total, our results showed that 18 TCP members were identified in the whole genome sequence of Jatropha curcas L.; Jc TCP genes were classified into two categories by phylogenetic tree construction, among which there were 11 members in the Class I subfamily, seven members in the Class Ⅱ subfamily. It was shown that 12 members of Jc TCP genes were located at the seven chromosomes, and proteins belonging to the same TCP group exhibit higher similarity than those from different groups. Furthermore, the expression profiles of 15 TCP genes were discovered at different leaf developmental stages of Jc and Jn. Jc TCP 4, Jc TCP 5, Jc TCP 8, Jc TCP 13, Jc TCP 14, and Jc TCP 16 showed significantly different expressions, and can be used as candidate genes for regulating leaf development. Therefore, the TCP genes play important roles in regulating the leaf development in Jc, and the manipulation of Jc TCP genes can potentially be an important tool used for the genetic improvement of the leaf.

Abstract Background Ultra-processed foods have now become dominant in the global food system. Whether their consumption is associated with cardiovascular mortality remains controversial. Moreover, data on ultra-processed foods and cardiovascular outcomes are scarce in the US population. We aimed to examine the association of ultra-processed food consumption with cardiovascular mortality in a US population. Methods A population-based cohort of 91,891 participants was identified from the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial. Dietary data were collected through a validated 137-item food frequency questionnaire. Ultra-processed foods were defined by the NOVA classification. Cox regression was used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for cardiovascular mortality. Restricted cubic spline regression was used to test nonlinearity. Subgroup analyses were conducted to identify the potential effect modifiers. Results After an average follow-up of 13.5 years (1,236,049.2 person-years), 5490 cardiovascular deaths were documented, including 3985 heart disease deaths and 1126 cerebrovascular deaths. In the fully adjusted model, participants in the highest vs. the lowest quintiles of ultra-processed food consumption had higher risks of death from cardiovascular disease (HRquintile 5 vs. 1, 1.50; 95% CI, 1.36–1.64) and heart disease (HRquintile 5 vs. 1, 1.68; 95% CI, 1.50–1.87) but not cerebrovascular disease (HRquintile 5 vs. 1, 0.94; 95% CI, 0.76–1.17). A nonlinear dose–response pattern was observed for overall cardiovascular and heart disease mortality (all P nonlinearity