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Colorectal cancer (CRC) is one of the main causes of cancer-related morbidity and mortality across the globe. Although serum biomarkers such as carcinoembryonic antigen (CEA) and carbohydrate antigen 19–9 (CA-199) have been prevalently used as biomarkers in various cancers, they are neither very sensitive nor highly specific. Repeated tissue biopsies at different times of the disease can be uncomfortable for cancer patients. Additionally, the existence of tumor heterogeneity and the results of local biopsy provide limited information about the overall tumor biology. Against this backdrop, it is necessary to look for reliable and noninvasive biomarkers of CRC. Circulating tumor cells (CTCs), which depart from a primary tumor, enter the bloodstream, and imitate metastasis, have a great potential for precision medicine in patients with CRC. Various efficient CTC isolation platforms have been developed to capture and identify CTCs. The count of CTCs, as well as their biological characteristics and genomic heterogeneity, can be used for the early diagnosis, prognosis, and prediction of treatment response in CRC. This study reviewed the existing CTC isolation techniques and their applications in the clinical diagnosis and treatment of CRC. The study also presented their limitations and provided future research directions.

The Internet of Vehicles (IoV) has a typical Internet of things architecture, which is the specific application of Internet of things (IoT) technology in the field of intelligent transportation. Virtual network embedding (VNE) is the effective allocation of physical network resources to the virtual network, and is a virtualization technology widely used in the data center of the IoV. The existing VNE algorithm ignores the attributes of the network itself. It only allocates resources according to the order in which the requests arrive, resulting in the problem of low utilization of physical resources. In this paper, we propose an efficient topology control scheme for mobile nodes in IoVs. We firstly present a novel hierarchy-based dynamic VNE model for IoV. Then a VNE algorithm based on hierarchical priority is established by considering the attributes of virtual network requests. Finally, a global resource capacity based dynamic VNE algorithm is designed. Compared with precious VNE algorithms, the proposed algorithm has a 19 percent to 23 percent increase in the resource utilization rate of nodes, and elevates the overall request acceptance rate and revenue overhead, and can reduce the average waiting time of virtual network requests.

Quantifying the influences of land use/cover (LULC) change on hydrological processes is important for rational utilization of water resources. The objective of this study was to evaluate the impacts of spatiotemporal LULC change on hydrological components in a typical agricultural area located in the North China Plain at both basin and sub-basin scales. LULC change was quantified, and the Soil and Water Assessment Tool was optimized using parameters associated with LULC conditions. We concluded that the urban and forest areas increased by 25.57 and 10.56%, with the cropland area decreased by 36.76%. About half of the surface runoff (SURQ) in the basin was generated from the urban area, with the SURQ increased significantly in the upstream and downstream of the basin where overlapped with urbanized areas. The proportions of evapotranspiration generated by cropland and forest areas increased slightly (0.89 and 0.55%, respectively), especially in sub-basins where the conversion of cropland to forest was obvious. Urban, forest, and cropland were the main types that generated water yield (WYLD). The proportion of WYLD generated on the urban area increased by 9.55% and decreased in other areas, which may be related to the combined effects of urbanization and forest reduction. Highlights The SWAT model was used under different scenarios for a typical agricultural area, North China Plain.; The influences of land use/cover change on key hydrological components were analyzed at both basin and sub-basin scales.; Urbanization and reforestation will affect changes in hydrological components.

This paper proposes a better semi-supervised semantic segmentation network using an improved generative adversarial network. It is important for the discriminator on the pixel level to know whether it correctly distinguishes the predicted probability map. However, currently there is no correlation between the actual credibility and the confidence map generated by the pixel-level discriminator. We study this problem and a new network is proposed, which includes one generator and two discriminators. One of the discriminators can output more reliable confidence maps on the pixel level and the other is trained to generate the probability on the image level, which is used as the dynamic threshold in the semi-supervised module instead of being set manually. In addition, the trusted region shared by the two discriminators is used to provide the semi-supervised reference. Through experiments on the PASCAL VOC 2012 and Cityscapes datasets, the proposed network brings better gains, proving the effectiveness of the network.

The reverse projection protocol results in fast phase-contrast imaging thanks to its compatibility with conventional computed-tomography scanning. Many researchers have proposed variants. However, all these reverse projection methods in grating-based phase-contrast imaging are built on the hypothesis of the synchronous phase of reference shifting curves in the whole field of view. The hypothesis imposes uniformity and alignment requirements on the gratings, thus the field of view is generally limited. In this paper, a generalized reverse projection method is presented analytically for the case of non-uniform reference in grating-based phase tomography. The method is demonstrated by theoretical derivation, numerical simulations and synchrotron radiation experiments. The influence of imaging position to sensitivity, and the phase-wrapping phenomenon are also discussed. The proposed method combines the advantages of the high efficiency of the reverse projection method and the universal applicability of the phase-stepping method. The authors believe that the method would be used widely in fast and dose-constrained imaging.

ObjectiveTo study the frequency and clinical features of sleep disturbances in amyotrophic lateral sclerosis (ALS) patients and compare sleep disorders between ALS with and without mutations.MethodsIn this case–control study, 204 ALS patients and 206 controls were included. We evaluated sleep quality using Pittsburgh Sleep Quality Index (PSQI). Excessive daytime sleepiness (EDS) was diagnosed according to Epworth Sleepiness Scale (ESS). Other characteristics, including rapid eye movement sleep behaviour disorder, restless legs syndrome (RLS), cognitive and psychological impairments, were also evaluated. All ALS patients underwent whole exome sequencing analysis to screen for ALS mutations and were divided into genetic ALS and non-genetic ALS subgroups based on the genetic testing results.ResultsA total of 114 men and 90 women ALS patients, with a mean onset age of 53.5±9.9 years, were included in this study. There were 21 mutations detected, contributing to 46.6% of familial amyotrophic lateral sclerosis (FALS) and 7.4% of sporadic amyotrophic lateral sclerosis (SALS). The PQSI and ESS scores were higher in ALS patients than in controls (PSQI 6.0 (3.0,10.0) vs 3.5 (2.0,5.0) (pConclusionsIn the current study, ALS patients with mutations were more likely to have sleep-wake disturbances than were those without mutations. The former group may benefit more from sleep management.

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease characterized by progressive injury of both upper and lower motor neurons. Recently, protein-truncating and missense mutations of DNAJC7 have been reported in European ALS cohorts. However, the contribution of DNAJC7 mutations in Asian patients with ALS remains unclear. Methods: DNAJC7 mutation screening was performed in a large Chinese cohort comprising 304 sporadic ALS (SALS), 16 familial ALS (FALS), and 6 ALS patients presenting with concomitant frontotemporal dementia (FTD). Results: Two rare missense variants of uncertain significance were identified. One was c.410A > G (p.K137R) detected in 1 SALS, which was absent in 2445 neurologically normal controls. The other variant, c.1106A > C (p.N369T), which is considered benign was found in 5 SALS patients with a detected frequency of 0.65% in control group. No pathogenic mutations of DNAJC7 were found in Chinese ALS cohort. Conclusions: Our results suggest that pathogenic mutations of DNAJC7 are rare in Chinese ALS patients.

As a mode of processing task request, edge computing paradigm can reduce task delay and effectively alleviate network congestion caused by the proliferation of Internet of things(IoT) devices compared with cloud computing. However, in the actual construction of the network, there are various edge autonomous subnets in the adjacent areas, which leads to the possibility of unbalance of server load among autonomous subnets during the peak period of task request. In this paper, a deep reinforcement learning algorithm is proposed to solve the complex computation offloading problem for the heterogeneous Edge Computing Server(ECS) collaborative computing. The problem is solved based on the real-time state of the network and the attributes of the task, which adopts Actor Critic and Policy Gradient's Deep Deterministic Policy Gradient(DDPG) to make optimized decisions of computation offloading. Considering multi-task, the heterogeneity of edge subnet and mobility of edge devices, the proposed algorithm can learn the network environment and generate the computation offloading decision to minimize the task delay.The simulation results show that the proposed DDPG-based algorithm is competitive compared with the Deep Q Network(DQN) algorithm and Asynchronous Advantage Actor-Critic(A3C) algorithm. Moreover, the optimal solutions are leveraged to analyze the influence of edge network parameters on task delay.

Analysis of circulating tumor cells (CTCs) can provide significant clinical information for tumors, which has proven to be helpful for cancer diagnosis, prognosis monitoring, treatment efficacy, and personalized therapy. However, CTCs are an extremely rare cell population, which challenges the isolation of CTCs from patient blood. Over the last few decades, many strategies for CTC detection have been developed based on the physical and biological properties of CTCs. Among them, nanostructured interfaces have been widely applied as CTC detection platforms to overcome the current limitations associated with CTC capture. Furthermore, aptamers have attracted significant attention in the detection of CTCs due to their advantages, including good affinity, low cost, easy modification, excellent stability, and low immunogenicity. In addition, effective and nondestructive release of CTCs can be achieved by aptamer-mediated methods that are used under mild conditions. Herein, we review some progress in the detection and release of CTCs through aptamer-functionalized nanostructured interfaces.

With the rapid development of Internet of Things (IoT) technology, Network Function Virtualization (NFV) is introduced in the edge network to provide flexible and personalized service. However, there still exist some problems to be solved, such as high cost, unbalanced load, and low availability. Therefore, a reliability-and-energy-balanced Service Function Chain (SFC) mapping and migration method is presented for IoT applications. First, aiming at improving network performance and reducing expenditure, an SFC mapping algorithm based on cost optimization, load balancing, and reliability is proposed to map SFC requests onto the network and provide backup. Second, aiming at optimizing resource configuration, an SFC migration method based on energy consumption and quality of service is proposed to integrate network resources. Simulation results show that the proposed method outperforms the compared algorithms by 15.5% and 24.55% in the acceptance ratio of SFC requests and the overall costs, respectively.

Background: Multiple non-invasive ventilation (NIV) modalities have been identified that may improve the prognosis of pediatric patients with acute lower respiratory infection (ALRI). However, the effect of NIV in children with ALRI remains inconclusive. Hence, this study aimed to evaluate the efficacy of various NIV strategies including continuous positive airway pressure (CPAP), high flow nasal cannula (HFNC), bilevel positive airway pressure (BIPAP), and standard oxygen therapy in children with ALRI and the need for supplemental oxygen.Methods: Embase, PubMed, Cochrane Library, and Web of Science databases were searched from inception to July 2021. Randomized controlled trials (RCTs) that compared different NIV modalities for children with ALRI and the need for supplemental oxygen were included. Data were independently extracted by two reviewers. Primary outcomes were intubation and treatment failure rates. Secondary outcome was in-hospital mortality. Pairwise and Bayesian network meta-analyses within the random-effects model were used to synthesize data. The certainty of evidence was assessed using the Grading of Recommendations Assessment, Development and Evaluation framework.Results: A total of 21 RCTs involving 5,342 children were included. Compared with standard oxygen therapy, CPAP (OR: 0.40, 95% CrI: 0.16–0.90, moderate quality) was associated with a lower risk of intubation. Furthermore, both CPAP (OR: 0.42, 95% CrI: 0.19–0.81, low quality) and HFNC (OR: 0.51, 95% CrI: 0.29–0.81, low quality) reduced treatment failure compared with standard oxygen therapy. There were no significant differences among all interventions for in-hospital mortality. Network meta-regression showed that there were no statistically significant subgroup effects.Conclusion: Among children with ALRI and the need for supplemental oxygen, CPAP reduced the risk of intubation when compared to standard oxygen therapy. Both CPAP and HFNC were associated with a lower risk of treatment failure than standard oxygen therapy. However, evidence is still lacking to show benefits concerning mortality between different interventions. Further large-scale, multicenter studies are needed to confirm our results.Systematic Review Registration: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=172156, identifier: CRD42020172156.

Breast tumor segmentation is a preliminary step for breast tumor diagnosis. It is expensive to obtain pixel-level labels for breast tumor segmentation. We aim to perform breast tumor segmentation in breast ultrasound (BUS) images with image-level labels. To this end, we propose a class activation mapping with level set (CAM-LS) method. Given a training dataset consisting of BUS images with or without breast tumors which naturally contain image-level labels, a classification network is trained for breast tumor recognition. Class activation maps (CAMs) are generated for positive predictions, which highlight discriminative regions of breast tumors. Anatomical constraints are used to reduce the search space for breast tumors. For breast tumor recognition, the proposed method achieves sensitivity of 92.0%, precision of 92.8%, specificity of 95.2%, accuracy of 93.9% and F1-score of 0.924. For breast tumor segmentation, the proposed method obtains Dice similarity coefficient (DSC) of 73.5 ± 18.0% and interaction-over-union (IoU) of 60.8 ± 19.7%. The proposed CAM-LS method performs automated breast tumor segmentation with image-level labels only and is demonstrated in the experiments to have good generalization on different ultrasound platforms.

Breast anatomical structures are distributed layer by layer in breast ultrasound (BUS) images. Breast anatomy decomposition (BRAND) has several clinical potentials in providing localization constraints for breast lesion detection and supporting multimodal registration. To take advantage of convolutional neural network (CNN) and reduce the requirements of manual labels, we propose a semi-supervised deep learning method for BRAND. A CNN is first trained on labeled training data. Pseudo labels for unlabeled training data are generated by smoothing the network's predictions with simple linear iterative clustering (SLIC) super-pixel algorithm. The proposed approach achieves Dice similarity coefficient (DSC) of 89.6 ± 9.3%, 88.2 ± 9.7%, 84.6 ± 17.7% and 89.5 ± 21.6% for subcutaneous fat, mammary gland, muscles and thorax layers, respectively, which outperforms the reported results. The proposed approach is demonstrated to be sufficient for BRAND in BUS images both with and without breast lesions.

The purpose of this systematic review is to evaluate the efficacy and safety of using potential drugs: remdesivir and glucocorticoid in treating children and adolescents with COVID-19 and intravenous immunoglobulin (IVIG) in treating MIS-C. We searched seven databases, three preprint platform, ClinicalTrials.gov, and Google from December 1, 2019, to August 5, 2021, to collect evidence of remdesivir, glucocorticoid, and IVIG which were used in children and adolescents with COVID-19 or MIS-C. A total of nine cohort studies and one case series study were included in this systematic review. In terms of remdesivir, the meta-analysis of single-arm cohort studies have shown that after the treatment, 54.7% (95%CI, 10.3 to 99.1%) experienced adverse events, 5.6% (95%CI, 1.2 to 10.1%) died, and 27.0% (95%CI, 0 to 73.0%) needed extracorporeal membrane oxygenation or invasive mechanical ventilation. As for glucocorticoids, the results of the meta-analysis showed that the fixed-effect summary odds ratio for the association with mortality was 2.79 (95%CI, 0.13 to 60.87), and the mechanical ventilation rate was 3.12 (95%CI, 0.80 to 12.08) for glucocorticoids compared with the control group. In terms of IVIG, most of the included cohort studies showed that for MIS-C patients with more severe clinical symptoms, IVIG combined with methylprednisolone could achieve better clinical efficacy than IVIG alone.Conclusions: Overall, the current evidence in the included studies is insignificant and of low quality. It is recommended to conduct high-quality randomized controlled trials of remdesivir, glucocorticoids, and IVIG in children and adolescents with COVID-19 or MIS-C to provide substantial evidence for the development of guidelines. What is Known:• The efficacy and safety of using potential drugs such as remdesivir, glucocorticoid, and intravenous immunoglobulin (IVIG) in treating children and adolescents with COVID-19/MIS-C are unclear. What is New:• Overall, the current evidence cannot adequately demonstrate the effectiveness and safety of using remdesivir, glucocorticoids, and IVIG in treating children and adolescents with COVID-19 or MIS-C.• We are calling for the publication of high-quality clinical trials and provide substantial evidence for the development of guidelines.

It has been commonly accepted that soybean domestication originated in East Asia. Although East Asia has the historical merit in soybean production, the USA has become the top soybean producer in the world since 1950s. Following that, Brazil and Argentina have been the major soybean producers since 1970s and 1990s, respectively. China has once been the exporter of soybean to Japan before 1990s, yet she became a net soybean importer as Japan and the Republic of Korea do. Furthermore, the soybean yield per unit area in East Asia has stagnated during the past decade. To improve soybean production and enhance food security in these East Asian countries, much investment has been made, especially in the breeding of better performing soybean germplasms. As a result, China, Japan, and the Republic of Korea have become three important centers for soybean genomic research. With new technologies, the rate and precision of the identification of important genomic loci associated with desired traits from germplasm collections or mutants have increased significantly. Genome editing on soybean is also becoming more established. The year 2019 marked a new era for crop genome editing in the commercialization of the first genome-edited plant product, which is a high-oleic-acid soybean oil. In this review, we have summarized the latest developments in soybean breeding technologies and the remarkable progress in soybean breeding-related research in China, Japan, and the Republic of Korea.

Objectives We aimed to develop radiomics with attribute bagging, which leverages multimodal ultrasound (US) images to improve the classification accuracy of breast tumors. Methods A retrospective study was conducted. B-mode US, shear wave elastographic, and contrast-enhanced US images of 178 patients with 181 tumors (67 malignant and 114 benign) were included. Radiomics with attribute bagging consisted of extraction of 1226 radiomic features and analysis of them with attribute bagging. Histologic examination results acted as the reference standard. Radiomics with several feature selection algorithms were used for comparison. Cross-validation and a holdout test were performed to evaluate their performances. Results The accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve of radiomics with attribute bagging with the multimodal US images were 84.12%, 92.86%, 78.80%, and 0.919, respectively, exceeding all the comparison methods. Conclusions Radiomics with attribute bagging combined with multimodal US images has the potential to be used for accurate diagnosis of breast tumors in the clinic.

Anorectal malformation (ARM) is known to be associated with maldevelopment of the enteric nervous system (ENS), and vitamin A (VA) and its metabolite retinoic acid (RA) play important roles in ENS development. Thus, our aim was to investigate serum VA levels in ARM newborns and RA receptor (RAR) expression in the rectum of ARM patients and animal models. Serum VA concentrations were detected in newly diagnosed ARM neonates (n = 32) and neonates with non-alimentary tract malformations (n = 30). Intestinal specimens were divided into three groups: rectum from ARM patients (n = 30), colon from a stoma (n = 30) and rectum from controls (n = 4). RAR mRNA expression was evaluated by RT-qPCR. Rectum specimens from ARM patients were divided into two groups by postoperative pathology: the normal and lesion ganglion cell groups. Immunohistochemistry and Western blot were employed to detect RARα protein expression in rectum specimens. In addition, the ARM mouse model was induced by all-trans retinoid acid (ATRA), and the expression levels of RARα and the neuronal marker NeuN in the rectum of mice on embryonic day 16.5–18.5 (E16.5–18.5) were investigated. The serum concentration of VA in ARM neonates was lower than that in control neonates (P

The recent development in plasmon-enhanced electrochemical hydrogen production provides an alternative approach to address the bottleneck of low hydrogen production efficiency in the conventional photocatalysis. To achieve high-efficiency plasmonic catalysis, the development of catalytically active Schottky heterostructure is essential. Herein, we propose a 3D bicontinuous nanoporous plasmonic heterostructure for hydrogen evolution reaction (HER) by growing HER-active monolayer MoS2 on the internal surfaces of plasmonic 3D nanoporous gold (MoS2@NPG). The catalytically active plasmonic heterostructure with a large specific surface area and high electric conductivity exhibits superior photoelectrochemical activities towards electrochemical hydrogen production at both low onset potential of −70 mV vs RHE and the Tafel slope of 38 mV dec−1 under visible light illumination. The outstanding HER performance can be attributed to the efficient transfer of plasmon-generated hot electrons from NPG to monolayer MoS2 as well as the effective electron–hole separation by the Schottky barriers at MoS2/NPG interfaces.

With the acceleration of globalization, trade between countries has become more and more frequent; as a kind of commonly used heavy lifting equipment, the influence of the quayside crane on environment during the production stage has attracted wide attention. In this paper, the world’s largest quayside crane manufacturer was selected as the study object. The environmental load of five workshops (NC pre-treatment workshop, assembling workshop, sand milling workshop, painting workshop and steel structure workshop) involved in the quayside crane (QC) production stage was studied by using the ReCiPe model; the normalized values of the 14 overall pollutants in each workshop were 1248.64, 576.75, 214.27, 85.26 and 76.69, respectively. The results showed that the sand milling workshop was the biggest electricity consumer of all processes. The sensitivity analysis revealed that the environmental pollution load was the most sensitive to the electricity consumption; the scenario analysis indicated that with the proportion of China’s renewable resources in the process of electricity generation becoming larger and larger, in comparison with that of in 2015, up to 2050, the quantity of PM 2.5 generated during the production process of QC will drop from 832 to 408 kg (high-speed development)/342 kg (low-speed development), and it is expected that the China’s haze problem could be effectively curbed in the future. Finally, the research results of this article also pointed out the direction for the future technical innovation of the QC industry.

Localized surface plasmon resonance (LSPR) excitation enhanced chemical and electrochemical reactions represent a promising pathway for solar-to-chemical energy conversion. However, plasmonic catalysts usually suffer from low collection efficiency of hot charge carries generated by LSPR excitation due to short lifetime of hot carriers and fast electron-hole recombination. Schottky barriers between plasmonic catalysts and semiconducting supports have been utilized to prevent the electron-hole recombination. However, the interfacial barriers also hinder low-energy hot charge collection and thus affect solar-to-chemical energy conversion efficiency. Here we report that bicontinuous nanoporous gold as a Schottky barriers-free direct plasmonic catalyst can significantly enhance electro-oxidation of alcohol molecules. A high energetic hole yield of 0.486% is achieved, which is 4 times higher than that of discrete plasmonic AuAg nanoparticles. The direct plasmonic catalyst offers the highest methanol oxidation current density of 531 µA cm−2 among all known Au catalysts. This work provides compelling evidence that higher hot carrier collection efficiency can be achieved from direct plasmonic electrocatalysis without the assistance of Schottky junctions and has important implications in developing high efficiency plasmonic catalysts for photo-enhanced electrochemical reactions.

Background POU3F4 is the causative gene for X-linked deafness-2 (DFNX2), characterized by incomplete partition type III (IP-III) malformation of the inner ear. The purpose of this study was to investigate the clinical characteristics and molecular findings in IP-III patients by Sanger or nanopore single-molecule sequencing. Methods Diagnosis of IP-III was mainly based on clinical characteristics including radiological and audiological findings. Sanger sequencing of POU3F4 was carried out for these IP-III patients. For those patients with negative results for POU3F4 Sanger sequencing, nanopore long-read single-molecule sequencing was used to identify the possible pathogenic variants. Hearing intervention outcomes of hearing aids (HAs) fitting and cochlear implantation (CI) were also analyzed. Aided pure tone average (PTA) was further compared between two groups of patients according to their different locations of POU3F4 variants: in the exon region or in the upstream region. Results In total, 18 male patients from 14 unrelated families were diagnosed with IP-III. 10 variants were identified in POU3F4 by Sanger sequencing and 6 of these were reported for the first time (p.Gln181*, p.Val215Gly, p.Arg282Gln, p.Gln316*, c.903_912 delins TGCCA and p.Arg205del). Four different deletions that varied from 80 to 486 kb were identified 876–1503 kb upstream of POU3F4 by nanopore long-read single-molecule sequencing. De novo genetic mutations occurred in 21.4% (3/14) of patients with POU3F4 mutations. Among these 18 patients, 7 had bilateral HAs and 10 patients received unilateral CI. The mean aided PTA for HAs and CI users were 41.1 ± 5.18 and 40.3 ± 7.59 dB HL respectively. The mean PTAs for patients with the variants located in the exon and upstream regions were 39.6 ± 6.31 versus 43.0 ± 7.10 dB HL, which presented no significant difference (p = 0.342). Conclusions Among 14 unrelated IP-III patients, 28.6% (4/14) had no definite mutation in exon region of POU3F4. However, possible pathogenic deletions were identified in upstream region of this gene. De novo genetic mutations occurred in 21.4% (3/14) of patients with POU3F4 mutation. There was no significant difference of hearing intervention outcomes between the IP-III patients with variants located in the exon region and in the upstream region.

Objectives This study aimed to screen the significant sonographic features for differentiation of benign and malignant superficial lymph nodes (LNs) by logistic regression analysis and fit a model to diagnose LNs. Methods A total of 204 pathological LNs were analyzed retrospectively. All the LNs underwent conventional ultrasound (US) and contrast-enhanced ultrasound (CEUS) examinations. A total of 16 suspicious sonographic features were used to assess LNs. All variables that were statistically related to the diagnosis of LNs were included in the logistic regression analysis in order to ascertain the significant features of diagnosing LNs, and to establish a logistic regression analysis model. Results The significant features in the logistic regression analysis model of diagnosing malignant LNs were absence of echogenic hilus, age, and absence of hilum after enhancement. According to the results of logistic regression analysis, the formula to predict whether LNs were malignant was established. The area under the receiver operating curve (ROC) was 0.908 and the accuracy, sensitivity, and specificity were 85.0%, 92.9%, and 85.3%, respectively. Conclusion The logistic regression model for the significant sonographic features of conventional US and CEUS is an effective and accurate diagnostic tool for differentiating malignant and benign LNs.

Breast tumor segmentation is an important step in the diagnostic procedure of medical physicians and computer-aided diagnosis systems. We propose a two-step deep learning framework for breast tumor segmentation in breast ultrasound (BUS) images which requires only a few manual labels. The first step is breast anatomy decomposition handled by a semi-supervised semantic segmentation technique. The input BUS image is decomposed into four breast anatomical structures, namely fat, mammary gland, muscle and thorax layers. Fat and mammary gland layers are used as constrained region to reduce the search space for breast tumor segmentation. The second step is breast tumor segmentation performed in a weakly-supervised learning scenario where only image-level labels are available. Breast tumors are first recognized by a classification network and then segmented by the proposed class activation mapping and deep level set (CAM-DLS) method. For breast anatomy decomposition, the proposed framework achieves Dice similarity coefficient (DSC) of 83.0 ± 11.8%, 84.3 ± 10.0%, 80.7 ± 15.4% and 91.0 ± 11.4% for fat, mammary gland, muscle and thorax layers, respectively. For breast tumor recognition, the proposed framework achieves sensitivity of 95.8%, precision of 92.4%, specificity of 93.9%, accuracy of 94.8% and F1-score of 0.941. For breast tumor segmentation, the proposed framework achieves DSC of 77.3% and intersection-over-union (IoU) of 66.0%. In conclusion, the proposed framework could efficiently perform breast tumor recognition and segmentation simultaneously in a weakly-supervised setting with anatomical constraints.

Background: The efficacy and safety of using potential drugs such as remdesivir, glucocorticoid, and intravenous immunoglobulin (IVIG) in treating children and adolescents with COVID-19 is unclear. Methods: We searched seven databases, three preprint platform, ClinicalTrials.gov, and Google from December 1, 2019, to March 2, 2021, to collect evidence of remdesivir, glucocorticoid, and IVIG which were used in children and adolescents with COVID-19. Findings: A total of six cohort studies and one case series study were included in this systematic review. In terms of remdesivir, the meta-analysis of single-arm cohort studies have shown that, after the treatment, 37·1% (95%CI, 0·0% to 74·5%) experienced adverse events, 5·9% (95%CI, 1·5% to 10·2%) died, 37.2% (95%CI, 0% to 76·0%) needed extracorporeal membrane oxygenation (ECMO) or invasive mechanical ventilation (IMV). As for glucocorticoids, the results of the meta-analysis showed that the fixed-effect summary odds ratio (OR) for the association with mortality was 2·79 (95%CI, 0·13 to 60·87), and the mechanical ventilation rate was 3·12 (95%CI, 0·80 to 12·08) for glucocorticoids compared with the control group. In terms of IVIG, the two included cohort studies showed that for MIS-C patients with more severe clinical symptoms, IVIG combined with methylprednisolone could achieve better clinical efficacy than IVIG alone. Interpretation: Overall, the current evidence in the included studies is insignificant and of low quality, which does not adequately demonstrate the effectiveness and safety of using remdesivir, glucocorticoids, and IVIG in treating children and adolescents with COVID-19 or MIS-C. Funding Information: This work was supported by grants from the National Clinical Research Center for Child Health and Disorders (Children’s Hospital of Chongqing Medical University, Chongqing, China) (grant number NCRCCHD-2020-EP-01); Special Fund for Key Research and Development Projects in Gansu Province in 2020; the Fourth Batch of “Special Project of Science and Technology for Emergency Response to COVID-19” of Chongqing Science and Technology Bureau; special funding for prevention and control of emergency of COVID-19 from Key Laboratory of Evidence-Based Medicine and Knowledge Translation of Gansu Province (grant number No. GSEBMKT-2020YJ01); The Fundamental Research Funds for the Central Universities (lzujbky-2020-sp14). Declaration of Interests: None.

We studied the formation and attenuation of GHz elastic waves in free-standing nanoporous gold films by MeV ultrafast electron diffraction and finite element simulations. By tracing the evolution of the high frequency acoustic waves in time domain, we found that the bicontinuous nanoporous structure in nanoporous gold films results in three-dimensionally acoustic response with low coherence, leading to fast attenuation of the elastic waves in comparison with solid gold films. The morphologically dominated dynamics indicates the nanoporosity plays an important role in the high-frequency acoustic energy relaxation, which shines a light on the applications of dealloyed nanoporous materials in nanodevices and sensors as GHz and THz acoustic filters and dampers.

The logistics traceability system can cover the whole process of the product from the source of production to the consumption cycle. By distinguishing the key nodes of the product in the logistics sales process, the data information of the production and storage of the corresponding product is collected and entered at the corresponding node, so that the entire process is visible and controllable. On the basis of determining the overall system plan, this paper designs and develops the UHF RFID reader system and traceability system platform. In terms of the reader system, by analyzing its core functions and performance index requirements, the overall design scheme and frame structure of the reader system’s software and hardware are determined. The main control circuit is based on the STM32F103RET6 single-chip microcomputer; the RF transceiver circuit is based on the MagicRF M100. Simultaneously, we design a variety of communication circuits including LoRa and RJ45 to facilitate wireless communication with the traceability platform. In terms of software, through the research and analysis of the EPC Class-1 Generation-2 protocol standard, the multitag anticollision algorithm—Q algorithm—is adopted. This algorithm has the advantages of high recognition efficiency and a large number of successfully recognized tags per unit time. According to the design plan, the system is wirelessly networked in the B/S mode and the product information collected through RFID technology is transmitted to the management level to dynamically understand the information dynamics of logistics in real time. Using radio frequency, computer network, communication, and other technologies, the hardware and software systems of the system are integrated. The performance indicators of the hardware system are tested through experiments, and the design indicators are compared to prove the feasibility of the equipment application. After setting up the local area network and configuring the server configuration, the traceability system was accessed and the verification of the basic functions of the system was completed. The test results show that the low-cost universal RFID wireless logistics terminal has high accuracy and real-time performance in the process of logistics traceability.

Objective: In addition to the split hand sign, other split phenomena of different muscles also exist in amyotrophic lateral sclerosis (ALS). We analyzed the incidence of split phenomena in multiple antagonistic muscle groups in ALS patients and explored whether clinical factors affected their occurrence. Methods: 618 ALS patients were included from a single ALS center. Muscle strength in upper and lower limbs was evaluated using the modified Medical Research Council (MRC) scoring system (range from 1 to 13). Split phenomena between different antagonistic muscle groups were summarized, and the correlations with clinical factors were analyzed. Results: Split phenomena were detected in 22.3% antagonistic muscles for flexion and extension of the elbow, 11.9% for the wrist, 23.9% for fingers, 18.2% for the ankle, and 14.7% for toes. These manifestations were characterized by preferential wasting of the elbow, wrist, and finger extensor muscles compared with the flexor muscles, and the ankle and toe dorsiflexor muscles compared with the plantar flexor muscles. The presence of muscle wasting was more common when the muscle strength was stronger than a modified MRC grade 6. No definite correlation was found between split phenomena and clinical factors, including age-at-onset, gender, disease duration, the region of onset, and pyramidal tract damage. Discussion: Split phenomena of antagonistic muscle groups widely exist in ALS patients. No definitive and consistent clinical factors were observed that affected the occurrence of these phenomena.

Shadow detection is an important and challenging task in computer vision. However, the current shadow detection method has limited semantic information extraction and has low detection accuracy for small shadow regions. Therefore, we propose a new shadow detection network that extracts both global semantic information and the context of the middle layer in a targeted manner. We use the single network structure of the encoder-decoder. The encoder module uses resnet-101 to extract features. The decoder module extracts semantic information by using the feature block with attention, which fuses the attention mechanism and divides the feature map, and uses the feature block after up-sampling to increase the resolution for feature extraction, so as to make it pay attention to the features of small shadow regions and improve the detection of small shadow regions. Furthermore, weight generator module and weight fusion module are used to combine the generated weight maps with the initial output of the network to further extract global context information. Finally, we use the pointrend module to complete the boundary refinement. We evaluate our network on the two benchmark datasets of SBU and UCF. The experimental results show that our method is superior to the state-of-the-art methods and the balance error rates on the two datasets are reduced by 20.0% and 10.7%, respectively.

REST technology has become a mainstream interface implementation technology in the field of Internet Web applications and network management, and conformance testing is an indispensable link to ensure that REST interfaces can work normally. In the current situation where there is little research on the automatic generation of REST interface test cases that support semantics, based on the practice of REST interface testing, this paper proposes the formal definition of REST interface documents, test cases and semantic relations, and the method of automatically generates semantic-supported REST interface test cases. This method can reduce the workload of testers during REST interface testing and improve the efficiency of interface testing.

To mitigate the projected global warming in the 21st century, it is well-recognized that society needs to cut CO2 emissions and other short-lived warming agents aggressively. However, to stabilize the climate at a warming level closer to the present day, such as the “well below 2 ∘C” aspiration in the Paris Agreement, a net-zero carbon emission by 2050 is still insufficient. The recent IPCC special report calls for a massive scheme to extract CO2 directly from the atmosphere, in addition to decarbonization, to reach negative net emissions at the mid-century mark. Another ambitious proposal is solar-radiation-based geoengineering schemes, including injecting sulfur gas into the stratosphere. Despite being in public debate for years, these two leading geoengineering schemes have not been directly compared under a consistent analytical framework using global climate models. Here we present the first explicit analysis of the hydroclimate impacts of these two geoengineering approaches using two recently available large-ensemble (>10 members) model experiments conducted by a family of state-of-the-art Earth system models. The CO2-based mitigation simulation is designed to include both emission cuts and carbon capture. The solar-radiation-based mitigation simulation is designed to inject sulfur gas strategically at specified altitudes and latitudes and run a feedback control algorithm to avoid common problems previously identified such as the overcooling of the tropics and large-scale precipitation shifts. Our analysis focuses on the projected aridity conditions over the Americas in the 21st century in detailed terms of the potential mitigation benefits, the temporal evolution, the spatial distribution (within North and South America), the relative efficiency, and the physical mechanisms. We show that sulfur injection, in contrast to previous notions of leading to excessive terrestrial drying (in terms of precipitation reduction) while offsetting the global mean greenhouse gas (GHG) warming, will instead mitigate the projected drying tendency under RCP8.5. The surface energy balance change induced by sulfur injection, in addition to the well-known response in temperature and precipitation, plays a crucial role in determining the overall terrestrial hydroclimate response. However, when normalized by the same amount of avoided global warming in these simulations, sulfur injection is less effective in curbing the worsening trend of regional land aridity in the Americas under RCP8.5 when compared with carbon capture. Temporally, the climate benefit of sulfur injection will emerge more quickly, even when both schemes are hypothetically started in the same year of 2020. Spatially, both schemes are effective in curbing the drying trend over North America. However, for South America, the sulfur injection scheme is particularly more effective for the sub-Amazon region (southern Brazil), while the carbon capture scheme is more effective for the Amazon region. We conclude that despite the apparent limitations (such as an inability to address ocean acidification) and potential side effects (such as changes to the ozone layer), innovative means of sulfur injection should continue to be explored as a potential low-cost option in the climate solution toolbox, complementing other mitigation approaches such as emission cuts and carbon capture (Cao et al., 2017). Our results demonstrate the urgent need for multi-model comparison studies and detailed regional assessments in other parts of the world.

Aspect-level sentiment analysis can provide more detailed information than general sentiment analysis, because it aims to predict the sentiment polarities of the given aspects or entities in text. The state-of-the-art neural models use RNN with attention seems a good method for the characteristics of this task in English, but because of the complexity of Chinese texts and the difference between Chinese and English, English learning outcomes cannot be directly applied to Chinese. After re-examining the drawbacks of attention mechanism and obstacles that Chinese aspect-level sentiment analysis, we build upon line of research and propose three approaches overcome these issues. First, we propose a mixed vector to enhance the information embedded in Chinese word embedding. Second, we introduce an attention weight calculate method for target representation that better captures the semantic meaning of the opinion target. Third, we use CNN to extract local information in the text. The experimental results show that our model consistently outperforms the state-of-the-art methods on Chinese reviews.

The bubbles in the liquid film are important to improve the chemical reaction rate and the efficiency of heat and mass transfer. However, bubbles in annular flow have not been studied intensively like waves on film surface or droplets. Planar Laser-induced Fluorescence (PLIF) was employed to investigate the film bubbles in vertical upward annular flow. The subject of this paper is to study the correlation between the area, the gas holdup of bubbles in the liquid film and gas-liquid superficial velocity. The results show that the above parameters decrease with the increase of the gas superficial velocity, however, with the increase of liquid superficial velocity they are not always increasing. The variation of these parameters with the liquid superficial velocity is also diverse under different gas superficial velocity. The statistical characteristics of bubble area are studied and it can reveal how the mean bubble area decreases as the flow conditions change.

Falling film is widely applied in many industries, such as evaporation, condensation, chemical reaction and distillation. In order to investigate the influence of the liquid temperature on the wave characteristics in the free-falling film that is subjected to the sensible heating, instantaneous measurements of the film thickness using planar laser-induced fluorescence are performed. Experiments are carried out at liquid temperature that ranges from 24 °C to 52 °C. The spatiotemporal flow structure of falling film is reconstructed and analyzed at different temperatures. It is found that the frequency and the amplitudes of the large waves change with the temperature simultaneously, and the substrate regions become more smoother and wider with the temperature rising. The profiles of film thickness probability density function and the power spectrum density function are presented and discussed.

To mitigate the projected global warming in the 21st century, it is well recognized that society needs to cut CO2 emission and other short-lived warming agents aggressively. However, to stabilize the climate at a warming level closer to the present day, such as the well below 2 °C aspiration in the Paris agreement, a net-zero carbon emission by 2050 is still insufficient. The recent IPCC special report calls for a massive scheme to extract CO2 directly from the atmosphere, in addition to the decarbonization, to reach negative net emission at the mid-century mark. Another ambitious proposal is the solar radiation-based geoengineering schemes, including injecting sulfur gas into the stratosphere. Despite being in the public debate for years, these two leading geoengineering schemes have not been carefully examined under a consistent numerical modeling framework. Here we present a comprehensive analysis of climate impacts of these two geoengineering approaches using two recently available large-ensemble (> 10 members) model experiments conducted by a family of state-of-art Earth system models. The CO2-based mitigation simulation is designed to include both emissions cut and carbon capture. The solar radiation-based mitigation simulation is designed to inject the sulfur gas strategically at specified altitudes and latitudes and run a feedback control algorithm, to avoid common problems previously identified such as the over-cooling of the Tropics and large-scale precipitation shifts. Our analysis focuses on the projected aridity conditions over the Americas in the 21st century, in detailed terms of the mitigation potential, the temporal evolution, the spatial distribution (within North and South America), the relative efficiency, and the physical mechanisms. We show that sulfur injection, in contrast to previous notions of leading to excessive terrestrial drying (in terms of precipitation reduction) while offsetting the global mean greenhouse gas (GHG) warming, will instead mitigate the projected drying tendency under RCP8.5. The surface energy balance change induced by Sulfur injection, in addition to the well-known response in temperature and precipitation, plays a crucial role in determining the overall terrestrial hydroclimate response. However, when normalized by the same amount of avoided global warming, in these simulations, sulfur injection is less effective in limiting the worsening trend of regional land aridity in the Americas, when compared with carbon capture. Temporally, the climate benefit of Sulfur injection will emerge more quickly, even when both schemes are hypothetically started in the same year of 2020. Spatially, both schemes are effective in curbing the drying trend over North America. However, for South America, the Sulfur Injection scheme is particularly more effective for the sub-Amazon region (South Brazil), while the Carbon Capture scheme is more effective for the Amazon region. We conclude that despite the apparent limitations (such as inability to address ocean acidification) and potential side effects (such as changes to the ozone layer), innovative means of Sulfur Injection should continue to be explored as a potential low-cost option in the climate solution toolbox, complementing other mitigation approaches such as emissions cut and carbon capture (Cao et al., 2017). Our results demonstrate the urgent need for multi-model comparison studies and detailed regional assessment in other parts of the world.

Purpose To explore the surgical effects of endoscopic facial nerve decompression in Bell's palsy. Materials and methods This retrospective study included 15 patients with Bell's palsy. All had grade VI (House-Brackmann grading system) complete unilateral facial paralysis before surgery and a >95% reduction in amplitude on electroneurography testing compared to the unaffected side. Their MRI results indicated perineural edema in the geniculate ganglion area. Endoscopic decompression surgery was performed soon after they presented at our hospital. The time between onset of facial paralysis and surgery ranged from 25 to 93 days. All patients had no relevant surgical history or ear diseases. Results At 1-year follow-up, 13 of the 15 (87%) patients had recovered to normal or near-normal facial function (House-Brackmann grade I-II), and all patients had reached House-Brackmann grade III or lower facial function. No obvious air-bone gap or sensorineural hearing loss occurred after surgery, and there were no severe complications or synkinesis. Conclusions Endoscopic transcanal facial nerve decompression provides a less traumatic and improved exposure of the geniculate ganglion, and may also help prevent permanent severe facial sequela. Results of intraoperative facial nerve stimulation may be related to the length of time required for recovery. The optimal time of surgery after onset of paralysis needs to be investigated further, to identify a post-drug surgical therapy which may be more acceptable for patients. Patients' response to conservative treatments should be assessed as soon as possible so as not to delay surgery.

Background: Ongoing efforts have been made to identify new neuroimaging markers to track amyotrophic lateral sclerosis (ALS) progression. This study aimed to explore the monitoring value of multimodal magnetic resonance imaging (MRI) in the disease progression of ALS. Methods: From September 2015 to March 2017, ten patients diagnosed with ALS in Peking Union Medical College Hospital completed head MRI scans at baseline and during follow-up. Multimodal MRI analyses, including gray matter (GM) volume measured by voxel-based morphometry; cerebral blood flow (CBF) evaluated by arterial spin labeling; functional connectivity, including low-frequency fluctuation (fALFF) and regional homogeneity (ReHo), measured by resting-state functional MRI; and integrity of white-matter (WM) fiber tracts evaluated by diffusion tensor imaging, were performed in these patients. Comparisons of imaging metrics were made between baseline and follow-up using paired t-test. Results: In the longitudinal comparisons, the brain structure (GM volume of the right precentral gyri, left postcentral gyri, and right thalami) and perfusion (CBF of the bilateral temporal poles, left precentral gyri, postcentral gyri, and right middle temporal gyri) in both motor and extramotor areas at follow-up were impaired to different extents when compared with those at baseline (all P < 0.05, false discovery rate adjusted). Functional connectivity was increased in the motor areas (fALFF of the right precentral gyri and superior frontal gyri, and ReHo of right precentral gyri) and decreased in the extramotor areas (fALFF of the bilateral middle frontal gyri and ReHo of the right precuneus and cingulate gyri) (all P < 0.001, unadjusted). No significant changes were detected in terms of brain WM measures. Conclusion: Multimodal MRI could be used to monitor short-term brain changes in ALS patients. Key words: Amyotrophic Lateral Sclerosis; Disease Progression; Monitoring Value; Multimodal Magnetic Resonance Imaging

Tetralogy of Fallot (TOF) is a congenital heart disease characterized by abnormal cardiomyocyte differentiation in the right ventricular outflow tract (RVOT), and HA117 is a novel long noncoding RNA (lncRNA) with anti-differentiation roles.To investigate the potential association of HA117 with TOF, we collected 84 RVOT tissues from patients with TOF. We determined the expression of HA117 in RVOT samples from TOF patients and collected clinical data to conduct a cross-sectional and short-term follow-up study.McGoon ratio, Nakata index, and left ventricular end-diastolic volume index (LVEDVI) were negatively correlated with the expression of HA117 based on subgroup analysis, correlation analysis and logistic regression analysis. Additionally, cardiopulmonary bypass (CPB) time and ICU stay were longer in patients with higher expression of HA117 than in patients with lower expression of HA117. Furthermore, percentage improvement in SPO2 was significantly reduced in patients with increased HA117 expression at 6 months after surgery.Our results suggested that the increased expression of the novel lncRNA HA117 is a risk factor for unfavorable McGoon ratio, Nakata index and LVEDVI in TOF patients. Additionally, an increased expression of HA117 might lead to adverse short-term outcomes in TOF patients. Keywords: HA117, Tetralogy of Fallot, Long noncoding RNA, McGoon ratio, Nakata index

X-ray grating interferometry can provide substantially increased contrast over traditional attenuation-based techniques in biomedical applications, and therefore novel and complementary information. Recently, special attention has been paid to quantitative phase retrieval in X-ray grating interferometry, which is mandatory to perform phase tomography, to achieve material identification, etc. An innovative approach, dubbed “Reverse Projection” (RP), has been developed for quantitative phase retrieval. The RP method abandons grating scanning completely, and is thus advantageous in terms of higher efficiency and reduced radiation damage. Therefore, it is expected that this novel method would find its potential in preclinical and clinical implementations. Strictly speaking, the reverse projection method is applicable for objects exhibiting only absorption and refraction. In this contribution, we discuss the phase retrieval with the reverse projection method for general objects with absorption, refraction and scattering simultaneously. Especially, we investigate the influence of the object's scattering on the retrieved refraction signal. Both theoretical analysis and numerical experiments are performed. The results show that the retrieved refraction signal is the product of object's refraction and scattering signals for small values. In the case of a strong scattering, the reverse projection method cannot provide reliable phase retrieval. Those presented results will guide the use of the reverse projection method for future practical applications, and help to explain some possible artifacts in the retrieved images and/or reconstructed slices.

With the rapid development of deep learning and computer-vision, accurate identification of medical imaging has become one of the most important factors in medical diagnosis and decision-making. To this end, we propose a data-driven approach named Evolutionary Convolutional Deep Network (ECDN) to detect malaria parasites, which can use evolutionary algorithms to automatically generate deep neural networks, and optimized its network topology structure during the evolution process. Extensive experiments based on the large-scale thin-blood smear images data validate the effectiveness of ECDN for detecting malaria. To be specific, it has the advantage of being able to automatically generate an optimal network structure without the need for any prior knowledge of constructing a neural network, as compared to a traditional artificial convolution network. The experimental results show that the model robustness of ECDN is better. When the training set and test set are divided according to the ratio of 6 and 4, the best result is achieved, and the accuracy rate reaches 99.98%, which provides an important basis for this research.

Objective: Split-hand sign is a useful clinical and electrophysiological feature in the diagnosis of amyotrophic lateral sclerosis (ALS). We proposed a novel split-hand index (SI) using F-wave pers...

Objectives To explore the cause of long survival but early onset and other prognostic factors among Chinese sporadic amyotrophic lateral sclerosis (ALS) patients. Methods Patients with ALS were recruited and followed up from Jan 2013 to Jan 2017. Phenotype and survival were compared among different age-at-onset groups. Candidate prognostic factors were analyzed by Kaplan-Meier method, Cox regression and Royston Parmar (RP) model dealing with breaches of proportional hazard assumption. Results In the cohort of 531 patients, mean age-at-onset was 53.68 years (SD:10.85) and overall estimated median survival time was 59 months (95% CI: 48.29–69.71). Pairwise comparison showed that patients above 65 years at onset were more frequently bulbar onset (adjusted residual: 3.0), less frequently lumbosacral onset (adjusted residual: −3.0), and had shorter survival compared with other age groups (p = 0.002). Cox and RP model demonstrated independent prognostic variables including age at onset, bulbar onset, diagnostic delay, MRC-score at first diagnosis and region of residence. Conclusions This clinic-based study suggested that Chinese sporadic ALS patients had relatively long survival probably due to young age and less bulbar onset cases. Short diagnostic delay, low MRC-score and northern residence were also predicative of short survival. Reallocation of resources is needed to optimize quality care and prolong survival time.

The F-wave test allows for the non-invasive assessment of spinal motoneuron excitability. We investigated the difference in spinal motoneuron dysfunction between the first dorsal interosseous (FDI) and abductor digit minimi (ADM) muscles by investigating F-waves and to assess the contribution of spinal mechanisms to split-hand syndrome in patients with amyotrophic lateral sclerosis (ALS). Sixty-five consecutive ALS patients and twenty age- and gender-matched healthy controls (HCs) were enrolled. Motor nerve conduction studies and F-waves were performed bilaterally on median and ulnar nerves in all subjects. HCs revealed prominently longer F-wave latencies, lower chronodispersion, mean F-wave amplitude, and mean and maximal F/M amplitude ratio (P < 0.001) in the FDI compared to the ADM. However, no significant differences in almost all F-wave parameters between the FDI and ADM were observed in ALS patients with affected hands except the minimal and mean F-wave latency. These data suggest that excitability is greatly changed in the spinal motoneurons innervating the FDI. Furthermore, the mean F-wave amplitude (r = 0.454, P = 0.002) of the FDI was significantly correlated with the FDI/ADM CMAP amplitude ratio in ALS patients with affected hands but not of the ADM. Our findings suggested that the dysfunction of spinal motoneurons between the FDI and ADM was different in ALS, and spinal motoneuron dysfunction was associated with development of the split-hand phenomenon.