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Recent learning-based intrinsic image decomposition methods have achieved remarkable progress. However, they usually require massive ground truth intrinsic images for supervised learning, which limits their applicability on real-world images since obtaining ground truth intrinsic decomposition for natural images is very challenging. In this paper, we present an unsupervised framework that is able to learn the decomposition effectively from a single natural image by training solely with the image itself. Our approach is built upon the observations that the reflectance of a natural image typically has high internal self-similarity of patches, and a convolutional generation network tends to boost the self-similarity of an image when trained for image reconstruction. Based on the observations, an unsupervised intrinsic decomposition network (UIDNet) consisting of two fully convolutional encoder-decoder sub-networks, i.e., reflectance prediction network (RPN) and shading prediction network (SPN), is devised to decompose an image into reflectance and shading by promoting the internal self-similarity of the reflectance component, in a way that jointly trains RPN and SPN to reproduce the given image. A novel loss function is also designed to make effective the training for intrinsic decomposition. Experimental results on three benchmark real-world datasets demonstrate the superiority of the proposed method.

With the significant increase of e-commerce, freight transportation demand has surged significantly over the past decade. Most of the demand has been served by trucks in the United States. One major problem commonly identified across the country is the worsening truck parking availability because the increase of truck parking facilities has lagged behind the growth of trucking activities. The lack of parking spaces and real-time parking availability information greatly exacerbate the uncertainty of trips, and often results in illegal and potentially dangerous parking or overtime driving. This paper elaborates on pilot research on improving truck parking facilities cooperated with the Washington State Department of Transportation (WSDOT), building and testing the advanced Truck Parking Information and Management System (TPIMS) with the real-time user visualization and prediction function empowered by artificial intelligence. Furthermore, by analyzing the activities of truck drivers, the researchers aggregated the regularity of truck parking patterns by a customized sequential similarity methodology. A Truck Parking Occupancy Prediction (TPOP) neural network for time-variant occupancy prediction by deep learning and attributes embedding is proposed and integrated into the TPIMS. The TPOP achieves 5.82%, 5.07%, 4.84%, and 4.19% mean average percentage error (MAPE) for 16, 8, 4, and 2 minutes ahead of occupancy prediction respectively, significantly outperforms other state-of-the-art methods. Clearly, the proposed solutions can benefit both the truck drivers and government agencies by a more efficient and smart TPIMS.

The phenomenon of increasing accidents caused by reduced vigilance does exist. In the future, the high accuracy of vigilance estimation will play a significant role in public transportation safety. We propose a multimodal regression network that consists of multichannel deep autoencoders with subnetwork neurons (MCDAEsn). After we define two thresholds of ``0.35'' and ``0.70'' from the percentage of eye closure, the output values are in the continuous range of 0-0.35, 0.36-0.70, and 0.71-1 representing the awake state, the tired state, and the drowsy state, respectively. To verify the efficiency of our strategy, we first applied the proposed approach to a single modality. Then, for the multimodality, since the complementary information between forehead electrooculography and electroencephalography features, we found the performance of the proposed approach using features fusion significantly improved, demonstrating the effectiveness and efficiency of our method.

With the rapid development of clean energy and the deepening of the interaction between supply and demand, power grid investment upgrading measures involve many new elements, such as clean energy installation and distribution automation. Traditional investment decision-making models are difficult to establish and solve. In view of this, this paper analyzes the investment benefit mechanism directly from the perspective of investment input–output relationship, and designs an interactive auxiliary investment decision-making system based on correlation rule mining. The system constructs an investment benefit mapping model from power grid investment measures to benefit output by means of deep transfer learning, and provides three objective functions, which consider the optimal economy, performance improvement and comprehensive index optimization, thus assisting decision makers to formulate investment alternatives according to different investment needs. A case demonstrates the decision-making process based on an actual power grid, and verifies the practicability and effectiveness of the system.

The energy-conversion storage systems serve as crucial roles for solving the intermittent of sustainable energy. But, the materials in the battery systems mainly come from complex chemical process, accompanying with the inevitable serious pollutions and high energy-consumption. Natural mineral resources display various merits, such as unique architecture, adsorption capability and rich active sites, which have captured numerous attentions with remarkable advancements. Recently, the minerals compounds, containing 1D structure (halloysites, attapulgites, sepiolite), 2D structure (montmorillonite, vermiculite, molybdenite) and 3D structure (diatomite, pyrites), have been applied in plenty of fields. Aiming at their energy-storage applications, the significant utilizations in electrodes, separators, electrolyte and metal-protection were detailedly reviewed in lithium-ions battery, lithium-sulfur battery, solid-state battery and so on. However, it should be acknowledged that, the simple minerals hardly meet the demand of energy-storage systems, due to their inferior conductivity and less active substances. Thus, series of modified manners are applied for the evolution of phase (from silicate mineral to Si), the incorporating with carbon/polymer and the tailoring of surface traits, which were in-depth discussed as following. The work was expected to summarize the traits about mineral compounds from different architectures, whilst offering significant guidelines for exploring mineral-based materials in energy-storage systems.

Today's IoT platforms provide rich functionalities by integrating with popular third‐party services. Due to the complexity, it is critical to understand whether the IoT platforms have properly managed the authorisation in the cross‐cloud IoT environments. In this study, the authors report the first systematic study on authorisation management of IoT third‐party integration by: (1) presenting two attacks that leak control permissions of the IoT device in the integration of third‐party services; (2) conducting a measurement study over 19 real‐world IoT platforms and three major third‐party services. Results show that eight of the platforms are vulnerable to the threat. To educate IoT developers, the authors provide in‐depth discussion about existing design principles and propose secure design principles for IoT cross‐cloud control frameworks.

Hard coatings have been used to reduce the vibration levels of blisks in several studies. In the design process, coating-geometric mistuning and blade-substrate multi-mistuning are inevitable; and ...

Metastatic tumors (MTs) may show different characteristics of the immune microenvironment from primary tumors (PTs) in non-small cell lung cancer (NSCLC). The heterogeneity of immune markers in metastatic NSCLC and its associated factors has not been well demonstrated. In this study, 64 surgically resected specimens of paired PTs and MTs were obtained from 28 patients with NSCLC. Multiplex immunofluorescence (mIF; panel including programmed death-ligand 1 (PD-L1), Cytokeratin, CD8, and CD68) was performed on whole sections. The heterogeneity of the immune contexture of PD-L1 expression, infiltrating lymphocytes, and immune-to-tumor cell distances was quantified via digital image analysis. In a quantitative comparison of MTs and corresponding PTs, MTs showed higher PD-L1 expression levels, lower density of CD8+ cytotoxic T lymphocytes (CTLs), and longer spatial distance between CTLs and tumor cells. Subgroup analysis, which associated clinical factors, revealed that the heterogeneity of immune markers was more obvious in extrapulmonary, metachronous, and treated MTs, while fewer differences were observed in intrapulmonary, synchronous, and untreated MTs. In particular, MTs showed significantly higher PD-L1 expression and lower lymphocyte infiltration in metastatic NSCLC with EGFR mutations. Prognosis analysis showed that an increased density of CD8+ CTLs in MTs was associated with better overall survival (OS). Therefore, significant discrepancies in PD-L1 expression and lymphocyte infiltration in metastatic NSCLC are most likely associated with temporal heterogeneity with a history of anti-treatment and correlated with EGFR mutations. The detection of immune markers in re-obtained metastatic specimens may be required for immunotherapy prediction in these patients with metastatic NSCLC.

Objectives To explore the difference between tracheostomy and non‐tracheostomy and identify the risk factors associated with the need for tracheostomy after traumatic cervical spinal cord injury (TCSCI). Methods The demographic and injury characteristics of 456 TCSCI patients, treated in the Xinqiao Hospital from 2010 to 2019, were retrospective analyzed. Patients were divided into the tracheostomy group (n = 63) and the non‐tracheostomy group (n = 393). Variables included were age, gender,smoking history, mechanism of injury, concomitant injury, American Spinal Injury Association (ASIA) Impairment Scale, the neurological level of injury, Cervical Spine Injury Severity Score (CSISS), surgery, and length of stay in ICU and hospital. SPSS 25.0 (SPSS, Chicago, IL) was used for statistical analysis and ROC curve drawing. Chi‐square analysis was applied to find out the difference of variables between the tracheostomy and non‐tracheostomy groups. Univariate logistic regression analysis (ULRA) and multiple logistic regression analysis (MLRA) were used to identify risk factors for tracheostomy. The area under the ROC curve (AUC) was used to evaluate the performance of these risk factors. Results Of 456 patients who met the inclusion criteria, 63 (13.8%) underwent tracheostomy. There were differences in age (χ2 = 6.615, P = 0.032), mechanism of injury (χ2 = 9.87, P = 0.036), concomitant injury (χ2 = 6.131, P = 0.013),ASIA Impairment Scale (χ2 = 123.08, P, Identify risk factors for tracheostomy after TCSCI and help to make right decision to save life.

Integrating simultaneous wireless information and power transfer (SWIPT) and cognitive radio (CR) technologies into Internet of Things (IoT) networks, named SWIPT-enabled cognitive IoT networks, has become an effective approach to resolve the short lifetime of battery-constrained IoT devices (IoDs) and spectrum scarcity. In this type of networks, IoDs are regarded as secondary users (SUs) being charged with wireless power. To improve the sum throughput of IoDs, we allow IoDs to switch among spectrum sensing, SWIPT and information transmission adaptively. Correspondingly, three-dimensional resources, i.e., time (for performing the three actions), power (including power transmitted from an IoT controller to each IoD and power for receiving information and charging at each IoD) and spectrum, are jointly and adaptively allocated to maximize the sum throughput of IoDs. Since the formulated problem is a mixed-integer nonlinear program (MINLP), we adopt an auxiliary variable to convert the original problem into a tractable problem, which is then solved by an efficient algorithm involving the Lagrangian dual method, the subgradient method and the multiple one-dimensional search algorithm. Simulation results show our adaptive design yields superior performance in terms of the sum throughput of IoDs.

This review aimed to explore the concept, etiology, classification, classical cortical mapping, assessment, diagnosis and differential diagnosis, treatment, rehabilitation, mechanism, recovery, prognosis, and influencing factors for Chinese post‐stroke aphasia (PSA). The review emphasized the necessity and significance of neuroimaging assessment of brain and blood vessels and neuropsychological assessment in diagnosis and differential diagnosis of Chinese PSA. In addition, it suggested and recommended to use “dichotomies of internal and external, and anterior and posterior” as a starting point, based on the anatomic location of brain and blood vessels and their relationship with language area and language disorder. As a result, the formulated Chinese PSA classification was more suitable to guide the clinical treatment of cerebral stroke. Diagnosis, classification, and differential diagnosis of Chinese PSA types were performed according to the “dichotomy” and “four elements.” The formulated “flow diagram” enabled to determine the classification of Chinese PSA types. It was beneficial for patients to establish targeted and individualized rehabilitation training plans. This review introduced the use of memantine, piracetam, donepezil, etc. in PSA treatment, evaluated clinical studies conducted in China and abroad, investigated the mechanism of action related to the use of drugs in PSA treatment, and explored the therapeutic mechanism of rehabilitation training. It suggested the use drugs of memantine, piracetam, donepezil, etc. combine with non‐pharmacotherapy and rehabilitation training in clinical studies on PSA treatment and also in practical settings., This review aimed to explore the concept, etiology, classification, classical cortical mapping, assessment, diagnosis and differential diagnosis, treatment, rehabilitation, mechanism, recovery, prognosis, and influencing factors for Chinese post‐stroke aphasia (PSA).

Linlin Yang,1,2 Xin Chen,3 Zhiqi Liu,3 Wei Sun,3 Dexin Yu,3 Haiqin Tang,1,2,&ast; Zhiqiang Zhang3,&ast; 1Department of Geriatrics Cardiology, The First Affiliated Hospital of Anhui Medical University, Hefei, People’s Republic of China; 2Department of General Medicine, The First Affiliated Hospital of Anhui Medical University, Hefei, People’s Republic of China; 3Department of Urology, The Second Affiliated Hospital of Anhui Medical University, Hefei, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Haiqin TangDepartment of Geriatrics Cardiology, The First Affiliated Hospital of Anhui Medical University, No. 218 Jixi Road, Hefei, Anhui, 230022, People’s Republic of ChinaEmail tanghq_card@126.comZhiqiang ZhangDepartment of Urology, The Second Affiliated Hospital of Anhui Medical University, No. 678 Furong Road, Hefei, Anhui, 230032, People’s Republic of ChinaEmail zhangzq_urology@126.comObjective: This study aimed at exploring whether illness perceptions may mediate the relationship between depressive symptoms and lower urinary tract symptoms (LUTS) among benign prostatic hyperplasia (BPH) patients.Methods: The Patient Health Questionnaire (PHQ-9) for depression, the International Prostate Symptom Score (IPSS) for the severity of LUTS and the brief Illness Perception Questionnaire (B-IPQ) for illness perceptions (IPs) were used among the 157 BPH patients with LUTS. Pearson’s correlation test and hierarchical regression analyses were used to assess the correlations between LUTS, depressive symptoms and IPs.Results: Our study found that the severity of LUTS was associated with depressive symptoms and subscales of illness perception; meanwhile, IPs were associated with the level of education. A positive relationship was found between the scores of PHQ9 and the B-IPQ subscales of illness consequences, identity, timeline, concern and emotion; thus, a negative correlation was found between scores of PHQ9 and the B-IPQ subscales of illness coherence, personal control and treatment control. The hierarchical regression analysis showed IPSS and the B-IPQ subscales of illness consequences, concern and emotion were significantly associated with depression, and explained 85.1% of the variance in depressive symptoms (R2 = 0.851, p < 0.05).Conclusion: The relationship between LUTS and depressive symptoms may be mediated by the negative IPs, including consequences, concern and emotions. Clinicians should not only focus on the LUTS but also on the IPs to improve depressive symptoms among BPH patients.Keywords: lower urinary tract symptom, illness perceptions, benign prostatic hyperplasia, depression

Purpose: Phase I results of this phase I/II study showed that pamiparib 60 mg twice a day had antitumor activity and an acceptable safety profile in Chinese patients with advanced cancer, including epithelial ovarian cancer. Patients and Methods: This open-label phase II study was conducted in China and enrolled adult (≥18 years) patients with platinum-sensitive ovarian cancer (PSOC; disease progression occurring ≥6 months after last platinum treatment) or platinum-resistant ovarian cancer (PROC; disease progression occurring Results: In the total patient population (N = 113; PSOC, n = 90; PROC, n = 23), median age was 54 years (range, 34–79) and 25.6% of patients received ≥4 prior systemic chemotherapy lines. Median study follow-up was 12.2 months (range, 0.2–21.5). Eighty-two patients with PSOC and 19 patients with PROC were evaluable for efficacy. In patients with PSOC, 8 achieved a complete response (CR) and 45 achieved a partial response (PR); ORR was 64.6% [95% confidence interval (CI), 53.3–74.9]. In patients with PROC, 6 achieved a PR; ORR was 31.6% (95% CI, 12.6–56.6). Frequently reported grade ≥3 adverse events were hematologic toxicities, including anemia and decreased neutrophil count. Conclusions: Pamiparib 60 mg twice a day showed antitumor activity with durable responses in patients with PSOC or PROC with gBRCAmut, and had a manageable safety profile.

OBJECTIVES/HYPOTHESIS This study aimed to examine the prognostic value of elective neck dissection (END) in T1-2 clinical negative cervical lymph node (cN0 ) oropharyngeal cancer (OPC) patients. STUDY DESIGN An observational retrospective study. METHODS This retrospective study included 845 patients diagnosed with T1-2 cN0 OPC during 2010-2015 from Surveillance, Epidemiology, and End Results database. Univariable and multivariable Cox regression models were used to evaluate the prognostic roles of END. Furthermore, propensity score matching was used to balance the covariates between the END and observation (OBS) groups, and subgroup analyses were conducted in the matched cohorts. The primary endpoint was overall survival (OS). RESULTS Our study showed that END was an independent prognostic factor associated with a better 3-year OS compared with OBS in human papillomavirus (HPV)-positive cohort (adjusted hazard ratio [HR], 0.464; 95% confidence interval [CI], 0.235-0.916; P = .027). However, we found no prognostic value of END in HPV-negative cohort (adjusted HR, 0.837; 95% CI, 0.535-1.310; P = .435). In the subgroup analyses, we found that younger patients (≤65 years old) and patients with nontonsillar tumors in HPV-positive cohort were more likely to benefit from END, while patients with tonsillar tumors in HPV-negative cohort may benefit from END. CONCLUSIONS We found that patients with HPV-positive T1-2 cN0 OPC could benefit from END in terms of OS, especially younger patients and those with nontonsillar tumors. Patients with HPV-negative T1-2 cN0 OPC could not benefit from END in terms of OS, while those with tonsillar tumors may benefit from END. LEVEL OF EVIDENCE 3 Laryngoscope, 2021.

The heterogeneity of programmed death-ligand 1 (PD-L1) status between core needle biopsies (CNBs) from one tumor has not been well studied before. The current study attempts to find out the best index using multiple core biopsies from one tumor which can better reflect the actual PD-L1 status. Random CNB was performed in surgical specimens from 170 consecutive non-small cell lung cancer samples. Fifty-one cases (41 cases with PD-L1 positive and 10 cases with PD-L1 negative) and 216 matched CNBs were analyzed by DAKO 22C3 PharmDx Link 48 Autostainer. The PD-L1 status was compared between the surgical specimens and matched CNBs. Heterogeneity of PD-L1 status between CNBs from one tumor was observed in 56% of PD-L1 positive cases. Different tumor proportion score (TPS) statistical forms with regard to the highest, mean, median, weighted average TPS, as well as TPS showed by the longest biopsy specimen and the biopsy with most tumor volume were compared. At a cut-off of 1%, the concordance rates were 94.1%, 88.2%, 90.2%, 86.3%, 86.3%, and 86.3%; At a cut-off of 50%, the concordance rates were 92.2%, 86.3%, 84.3%, 82.4%, 82.4%, and 86.3%, respectively. The CNB with the highest TPS can best represent PD-L1 status estimated by whole surgical specimen. The highest TPS among the multiple biopsies is a robust evaluation of the PD-L1 status, but not mean TPS, at the 1% and 50% cut-offs.

Trisomy 21 is a common birth defect in humans. Screening for trisomy 21 is one of the most important tasks in routine prenatal care and robust noninvasive diagnostics are needed in clinical practice. Urinary proteomics offers a new research platform for diagnostics innovation in this context. We report here new biomarker candidates using urinary proteomics profiling. Specifically, we used liquid chromatography-tandem mass spectrometry (LC-MS/MS) to analyze the proteomes of urine samples from 19 pregnant women (aged 28-44 years) carrying fetuses with trisomy 21 and 22 healthy pregnant women (aged 27-42 years) carrying fetuses with normal karyotype. We identified more than 50 differentially expressed proteins between the trisomy 21 group and healthy group, and most of these proteins were associated with the embryonic development. Importantly, tissue inhibitor of metalloproteinases 2 (TIMP2) and lysosomal-associated membrane protein 2 (LAMP2) were further selected as potential urinary protein biomarkers. We found that the combination of TIMP2 and LAMP2 could differentiate fetuses with trisomy 21 from healthy controls with a sensitivity of 74%, a specificity of 82%, and an area under the receiver operating characteristic curves (AUC) value of 0.82 (95% confidence interval, 0.69-0.95). We conclude that TIMP2 and LAMP2 offer promise as biomarker candidates and warrant further clinical research in larger study samples. These findings further our understanding of the pathological processes involved in fetal trisomy 21 and are poised to accelerate the development of new noninvasive potential biomarkers for trisomy 21 prenatal screening.

The lymph node ratio (LNR) has been considered a better prognostic factor than traditional N staging in patients with gastric cancer (GC), but its accuracy is unclear for those who receive neoadjuvant therapy (NAT). We aimed to compare the node ratio (Nr) staging with the ypN staging and to thereby develop a modified staging system incorporating Nr staging. A total of 1791 patients who underwent gastrectomy after NAT in the Surveillance, Epidemiology, and End Results database were retrospectively analyzed. ypTNrM staging was established based on the overall survival (OS). The Nr staging was generated using 0.2 and 0.5 as the cutoff values of LNR and represented patients with more homogeneous OS compared with ypN staging. The 5-year OS rates for ypTNrM stages IA, IB, II, IIIA, and IIIB were 70.2%, 54.2%, 36.0%, 21.2%, and 6.6%, respectively, compared with 58.8%, 39.1%, and 21.6% for ypTNM stages I, II, and III, respectively. Compared with the ypTNM staging system, the ypTNrM staging system had a lower misclassification rate (3.0% vs. 50.9%) and better prognostic predictive power (C-index: 0.645 vs. 0.589, P

Background Auriculocondylar syndrome (ACS) is a rare disorder characterized by micrognathia, mandibular condyle hypoplasia, and auricular abnormalities. Only 6 pathogenic variants of GNAI3 have been identified associated with ACS so far. Here, we report a case of prenatal genetic diagnosis of ACS carrying a novel GNAI3 variant. Case presentation A woman with 30 weeks of gestation was referred to genetic counseling for polyhydramnios and fetal craniofacial anomaly. Severe micrognathia and mandibular hypoplasia were identified on ultrasonography. The mandibular length was 2.4 cm, which was markedly smaller than the 95th percentile. The ears were low-set with no cleft or notching between the lobe and helix. The face was round with prominent cheeks. Whole-exome sequencing identified a novel de novo missense variant of c.140G > A in the GNAI3 gene. This mutation caused an amino acid substitution of p.Ser47Asn in the highly conserved G1 motif, which was predicted to impair the guanine nucleotide-binding function. All ACS cases with GNAI3 mutations were literature reviewed, revealing female-dominated severe cases and right-side-prone deformities. Conclusion Severe micrognathia and mandibular hypoplasia accompanied by polyhydramnios are prenatal indicators of ACS. We expanded the mutation spectrum of GNAI3 and summarized clinical features to promote awareness of ACS.

Background Mitral regurgitation (MR) quantification by the proximal isovelocity surface area (PISA) method remains challenging. Using computer models, the authors evaluated the accuracy of different PISA methods and quantified their errors. Methods Five functional MR computer models of different geometric and tethering abnormalities were created, validated, and treated as phantom models, from which the reference values were directly obtained. Virtual two-dimensional (2D) PISA and three-dimensional (3D) PISA (both peak and integrated values) were performed on these phantom models. By comparing virtual PISA results with reference values, the accuracy of different PISA methods was evaluated, and their sources of errors were quantified. Results Compared with reference values of regurgitant flow rate, excellent correlations were found for true PISA (r = 0.99, bias = 32.3 ± 35.3 mL/sec), 3D PISA (r = 0.97, bias = −24.4 ± 55.5 mL/sec), followed by multiplane 2D hemicylindrical PISA (r = 0.88, bias = −24.1 ± 85.4 mL/sec) and hemiellipsoidal PISA (r = 0.91, bias = −55.7 ± 96.6 mL/sec). Weaker correlations were found for single-plane 2D hemispherical PISA (parasternal long-axis: r = 0.71, bias = −77.6 ± 124.5 mL/sec; apical two-chamber: r = 0.69, bias = −52.0 ± 122.0 mL/sec; apical four-chamber: r = 0.82, bias = −65.5 ± 107.3 mL/sec). For regurgitant volume quantification, integrated PISA was more accurate than peak PISA. The bias of 3D PISA improved from −12.7 ± 7.8 mL (peak PISA) to −2.1 ± 5.3 mL (integrated PISA). Conclusions For functional MR quantification, 2D hemispherical PISA had significant underestimation, multiplane 2D hemiellipsoidal and hemicylindrical PISA showed improved accuracy, and 3D PISA was the most accurate. The PISA method is subject to both systematic underestimation due to the Doppler angle effect and systematic overestimation when regurgitant flow is not perpendicular to PISA contour. Integrated PISA is able to capture dynamic MR and is therefore more accurate than peak PISA. The sum of regurgitant flow rates is the most feasible way to perform integrated PISA.

Introduction There is no consensus for interpretation of p16 immunohistochemistry (IHC) in cytology preparations. Our study aims to assess p16 IHC staining in formalin-fixed cytology cell blocks (CBs) from head and neck squamous cell carcinoma (HNSCC) fine-needle aspiration (FNA) specimens in comparison with surgical pathology p16 staining and to determine the reproducibility of p16 IHC scoring in CBs. Methods A total of 40 FNAs from 2014 to 2019 of HNSCC with p16 IHC were obtained. CB p16 staining was scored independently by 5 cytopathologists as interval percentages of tumor cell positivity. Receiver operating characteristic (ROC) curves were examined to determine optimal cutoffs for each pathologist based on sensitivity and specificity values. Gwet’s coefficient (AC1) was calculated to assess inter-rater reliability. Results Greater than 10% was the lowest threshold to reach 100% specificity with high sensitivity (55%-84%) in all 5 raters. Rater performances were similar, with areas under the curve (AUCs) ranging from 0.89 to 0.95. Using the >10% threshold, Gwet’s AC1 = 0.72 (95% CI: 0.56-0.89). Diagnostic performance improved further when low-cellularity cases were excluded, with AUC ranging from 0.94 to 0.99 and Gwet's AC1 = 0.79 (95% CI: 0.61-0.98). Conclusion p16 IHC performed on cytology CBs can serve as a surrogate marker for the detection of HPV with high sensitivity and specificity levels. Using a threshold lower than that recommended for surgical pathology for the interpretation of p16 positivity may be appropriate for FNA cytology CB preparations. All cytopathologists in our study displayed reproducible high sensitivity and specificity values at the >10% threshold.

Porous materials can effectively improve the thermal insulation performance of materials. Therefore, this study used pure Ti foil, pure Al powder, and pure Nb powder as raw materials. Layered porous high Nb-TiAl alloys have been prepared by vacuum hot-pressing sintering and multi-step heat treatment (low-temperature heat treatment and high-temperature heat treatment). The materials are composed of α2-Ti3Al, γ-TiAl, and Al3Nb. Holes are formed in the Al3Nb layer. The thermal insulation and tensile properties are measured at high temperature. The results show that the thermal insulation performance of the layered porous high Nb-TiAl alloy sheet is better than that of the layered high Nb-TiAl alloy (non-porous) and the traditional TiAl alloy. In this work, the materials achieved a good mechanical property-insulation performance synergy.

It is necessary to manually measure many parameters of eyes when an ophthalmologist diagnoses, which is time consuming, unsanitary, subjective and unrepeatable. Those manually achieved parameters often risk clinical trials in challenges on objectivity, resulting in unreliable clinical conclusions. We designed a two-phase algorithm to automatically measure these parameters instead of manual measurement to facilitate the diagnosis procedure of ptosis, eyelid retraction and other eye pathologies. Firstly, cornea, sclera, and internal and external canthus were identified using a multi-task convolutional neural network (CNN). Then we used the identification results to calculate a series of eye parameters needed in clinic. Totally 9 widely accepted parameters were calculated, including the height of ocular fissure, the longitudinal and transverse diameters of cornea, etc. The experimental results showed that most of parameters had achieved good accuracy, and most errors were less than 2 mm. We found that our approach can improve the measurements accuracy of eyelid, conjunctiva, cornea, sclera, and internal and external canthus, and promote efficiency and efficacy of relative clinical researches.

Purpose In this study, the authors argue that because of female traits, the proportion of female directors in the board helps the governing body make more cautious decisions, thus improving the investment efficiency of the firm. Therefore, this research aims to propose the mediating role of caution in reexamining the relationship between the proportion of female directors and the efficiency of the investment of a firm. Design/methodology/approach This study uses data on 100 nonfinancial listed firms in Malaysia between 2015 and 2018. The authors use several multivariate regression analyses to test the mediating effect. Findings The result shows that female directors significantly affect investment efficiency. Moreover, the findings in this research confirm the mediating role of caution in the relationship between the proportion of female directors and the efficiency of firm investment. Practical implications This study proves that increasing the proportion of females in the board of directors is an effective governance method to improve the investment efficiency of listed firms in Malaysia. Originality/value In general, this study contributes to the literature by extending the current understanding of risk propensity differences between male and female directors and introducing the concept of caution.

Dual-color emission in a single perovskite layer would make perovskite light-emitting devices (PLEDs) more competitive compared with other display technologies. However, due to the carrier dynamics in a blended perovskite film and the low reaction activation energy of the halide exchange reaction, it is very difficult to achieve the dual-color emission in a perovskite layer. Here, dual-color electroluminescence (EL) emission in a single perovskite layer has been realized by slowing the energy transfer from wide-bandgap energy levels to narrow-bandgap energy levels. Moreover, the EL spectra can be controlled by modulating the composition of the perovskite layer. When the amount of CH3NH3I(MAI) in the precursor was varied, white emission with CIE coordinates of (0.33, 0.34) could be achieved. Our work proposes a new strategy for white emission from PLEDs. Also, the analysis and discussion of carrier dynamics in this work may help to enhance our understanding of the working mechanism of PLEDs.

The team developed the newly compiled eight methods and five steps of Tai Chi (EMFSTC), which includes introductory routines to Tai Chi characterized by simple structures. This study examined the effectiveness of EMFSTC practice on balance control. A total of 31 participants were randomly assigned to EMFSTC (n = 15, age = 66.4 ± 1.7 years, received 16-week EMFSTC practice) or control (n = 16, age = 66.7 ± 1.8 years, received no practice) groups. Significant group by training interactions were observed. After EMFSTC practice, balance control improved, as indicated by decreased root mean square and mean velocity of center of pressure, proprioception threshold during knee extension, and plantar tactile sensitivity threshold at the arch. EMFSCT can be an effective rehabilitation modality to improve balance control among older adults.

Efficient learning of spikes plays a valuable role in training spiking neural networks (SNNs) to have desired responses to input stimuli. However, current learning rules are limited to a binary form of spikes. The seemingly ubiquitous phenomenon of burst in nervous systems suggests a new way to carry more information with spike bursts in addition to times. Based on this, we introduce an advanced form, the augmented spikes, where spike coefficients are used to carry additional information. How could neurons learn and benefit from augmented spikes remains unclear. In this paper, we propose two new efficient learning rules to process spatiotemporal patterns composed of augmented spikes. Moreover, we examine the learning abilities of our methods with a synthetic recognition task of augmented spike patterns and two practical ones for image classification. Experimental results demonstrate that our rules are capable of extracting information carried by both the timing and coefficient of spikes. Our proposed approaches achieve remarkable performance and good robustness under various noise conditions, as compared to benchmarks. The improved performance indicates the merits of augmented spikes and our learning rules, which could be beneficial and generalized to a broad range of spike-based platforms.

Background Acupuncture is an important component of traditional Chinese medicine which is used to treat an array of health conditions. This study evaluates the effectiveness of acupuncture in the management of restless leg syndrome (RLS). Methods A comprehensive literature survey was conducted in electronic databases to identify studies evaluating the effectiveness of acupuncture in the treatment of RLS. Cure, marked effect, effective, ineffective, and total effective rates of individual studies were pooled to achieve their respective overall estimates and a meta-analysis of mean change from baseline in International Restless Legs Syndrome Rating Scale (IRLSRS) was performed. Results A total of 18 studies were included in this meta-analysis, among which 640 RLS patients were treated with acupuncture alone or combined with other therapies (acupuncture group) and 447 RLS patients were treated with non-acupuncture therapies (control group). Cure, marked effect, and effective rates were 47.8% [95% confidence interval (CI): 38.3% to 57.3%], 27.4% (95% CI: 20.3% to 34.8%), and 24.2% (95% CI: 16.9% to 31.5%) in patients treated with acupuncture either alone or combination with other treatments, and 21.7% (95% CI: 20.7% to 22.7%), 28.0% (95% CI: 20.0% to 32.9%), and 22.3% (95% CI: 17.0% to 27.6%) in patients treated with non-acupuncture therapies, respectively. The ineffective rate was 4.7% (95% CI: 4.3% to 5.0%) in the acupuncture group and 32.9% (95% CI: 22.2% to 43.7%) in non-acupuncture groups. IRLSRS scores improved significantly after acupuncture treatment [mean change from baseline -9.45 (95% CI: -18.42 to -0.49); P=0.04]. Discussion Although the overall quality of the included studies was low, the results of this meta-analysis suggested that acupuncture is an effective treatment option for RLS. Well-designed randomized controlled trials especially those involving a sham-acupuncture arm are needed to confirm these outcomes.

PURPOSE: Without a standard test for pancreatic carcinomas, this highly lethal disease is normally diagnosed at its advanced stage, leading to a low survival rate of patients. Trophoblast cell-surface antigen 2 (Trop-2), a transmembrane glycoprotein, is associated with cell proliferation and highly expressed in most of solid epithelial tumors, including pancreatic cancer. A non-invasive method of imaging Trop-2 would greatly benefit clinical diagnosis and monitoring of pancreatic cancer. In the current study, (89)Zr-labeled anti-Trop-2 antibody (AF650) was recruited for the systemic evaluation of Trop-2 as an immunoPET target for pancreatic cancer imaging. METHODS: AF650 was conjugated with desferrioxamine (DFO) and then radiolabeled with (89)Zr. Trop-2 expression levels were determined in three pancreatic cancer cell lines (BxPC-3, MIA PaCa-2, and AsPC-1) via western blot, flow cytometry, saturation binding assay, and immunofluorescence staining. The targeting capacity of (89)Zr-DFO-AF650 was evaluated in mouse models with subcutaneous xenograft of pancreatic cancers via PET imaging and bio-distribution studies. In addition, a Trop-2-positive orthotopic cancer model was recruited for further validating the targeting specificity of (89)Zr-DFO-AF650. RESULTS: BxPC-3 cells expressed high levels of Trop-2, while AsPC-1 and MIA PaCa-2 cells expressed low levels of Trop-2. Additionally, (89)Zr-DFO-AF650 exhibited high specificity to Trop-2 in BxPC-3 cells (K(d) = 22.34 ± 2.509 nM). In subcutaneous xenograft models, about 28.8 ± 7.63%ID/g tracer accumulated in the BxPC-3 tumors at 120 h post injection, which was much higher than those reaching MIA PaCa-2 (6.76 ± 2.08%ID/g) and AsPC-1 (3.51 ± 0.69%ID/g) tumors (n = 4). More importantly, (89)Zr-DFO-AF650 could efficiently distinguish primary tumors in the orthotopic BxPC-3 cancer model, showing high correlation between PET imaging and bio-distribution and sensitivity. CONCLUSIONS: (89)Zr-DFO-AF650 can be effectively used to detect pancreatic cancer via Trop-2-mediated immunoPET in vivo, clearly revealing the great potential of Trop-2-based non-invasive imaging in pancreatic cancer detection and treatment monitoring.

Sleep spindles have been implicated in sleep protection, depression and anxiety. However, spindle-related brain imaging mechanism underpinning the deficient sleep protection and emotional regulation in insomnia disorder (ID) remains elusive. The aim of the current study is to investigate the relationship between spindle-related brain activations and sleep quality, symptoms of depression and anxiety in patients with ID. Participants (n = 46, 28 females, 18–60 years) were recruited through advertisements including 16 with ID, according to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, and 30 matched controls. Group differences in spindle-related brain activations were analyzed using multimodality data acquired with simultaneous electroencephalography and functional magnetic resonance imaging during sleep. Compared with controls, patients with ID showed significantly decreased bilateral spindle-related brain activations in the cingulate gyrus (familywise error corrected p ˂ 0.05, cluster size 4401 mm3). Activations in the cingulate gyrus were negatively correlated with Pittsburgh Sleep Quality Index scores (r = -0.404, p = 0.005) and Self-Rating Anxiety Scale scores (r = -0.364, p = 0.013), in the pooled sample. These findings underscore the key role of spindle-related brain activations in the cingulate gyrus in subjective sleep quality and emotional regulation in ID.

Based on the dynamic expressions of permeability and porosity of the coal seam derived in the paper, a multiphysical field coupling numerical model of gas migration under the interaction of stress field and seepage field was established. The gas drainage project #3 Coal Seam operated by Sima Coal Industry Co., Ltd., was selected as the study object. Taking different drainage time periods in various positions of drainage holes into consideration, combined with the advance situation of the 1207 working face in the Sima Coal Mine, a mixed layout gas drainage scheme featured with the effective borehole spacing was obtained through the COMSOL multiphysics simulation. In addition, a series of field industrial tests were performed to validate the research result, revealing that comprehensively considering the extraction time of coal and optimizing the layout of extraction boreholes can effectively improve the engineering economic benefits.

The rapid development of autonomous driving in recent years presents many challenges for scene understanding. As an essential step towards scene understanding, semantic segmentation has received increased attention in the past few years. Although deep learning based approaches have achieved great success in improving the segmentation accuracy, most of them suffer from an inefficiency problem and can hardly be applied to real-time applications. In this paper, we analyze the computational cost of Convolutional Neural Network (CNN) and find that the inefficiency of CNNs is mainly caused by their wide structure rather than deep structure. In addition, the success of pruning based model compression methods proves that there are many redundant channels in CNNs. Thus, we design a narrow while deep backbone network to improve the efficiency of semantic segmentation. By casting our network to fully convolutional network (FCN32) segmentation architecture, the basic structure of most segmentation methods, we achieve 61.5% mIoU on Cityscapes validation dataset with only 4.2G floating-point operations (FLOPs) on $1024\times 2048$ inputs, which already outperforms one of the earliest real-time deep learning based segmentation methods: ENet (58.3% mIoU, 3.8G FLOPs on $640\times 360$ inputs). By further refining the output resolution of our network to the 1/8 of the input resolution with a simple encoder-decoder structure, we achieve 65.3% mIoU on Cityscapes test set with 14.0G FLOPs and 39.9 frames per second (FPS) on Titan X card. We have made our model publicly available at https://github.com/zgyang-hnu/NDNet .

Purpose: To examine the refractive lens power (RLP) and lens thickness and their associated factors in children from North-Western China.Methods: Children from two schools (primary school and junior high school) in the North-Western Chinese province of Qinghai underwent a comprehensive ophthalmic examination including biometry and cycloplegic refractometry. The RLP was calculated using Bennett’s equation. Results: The study included 596 (77.9%) individuals (mean age: 11.0±2.8 years; range: 6-16 years) with a mean axial length of 23.65±1.24mm (range: 20.02-27.96mm). Mean lens thickness was 3.30±0.16mm (range: 2.85-3.99mm) and mean RLP was 24.85±1.98D (range: 19.40-32.97). In univariate analysis, girls as compared to boys had a significantly thicker lens and greater RLP, shorter axial length, smaller corneal curvature radius and shorter corneal curvature radius (all PP=0.11) and corneal thickness (P=0.16). RLP was positively associated with refractive error (correlation coefficient r=0.33; PPPPβ=−0.07), female sex (Pβ=−0.08), shorter axial length (Pβ=−0.48) and higher lens thickness (Pβ=0.42). Conclusions: In Chinese children, RLP with a mean of 24.85±1.98D decreases with older age, male sex, longer axial length, and thinner lens thickness. Changes in RLP and axial length elongation are important players in the emmetropization and myopization.

This article proposes a novel approach to replace the fixed projection planes existed in the previous researches to reduce motion artifacts obtained from the human face by a normal webcam for monitoring heart rate in a real-time fashion. The novel projection plane is adaptively changed with the light intensity change to eliminate the color distortion induced by motion. In this article, the state-of-the-art semantic segmentation Deeplabv3+ is implemented to segment the skin pixels from the facial region that is detected by several trackers (Boosting, MIL, TLD, Median Flow, Mosse, and CSRT) to boost the computational time compared to the conventional face detection by Haar-Like features. Image and digital signal processing techniques are also applied to eliminate possible noise for obtaining a clean pulse signal. The proposed approach is compared with other existing approaches (Green, PCA, Chrom, and POS) in multiple challenges. From the experiments conducted, the Deeplabv3+ outperforms the conventional $K$ -means for different kinds of skin segmentation. Moreover, the proposed approach is quite robust and stable in the stationary case (with the accuracy 96%), dim-lighting environment and the long-distance up to 4-m away without zooming in camera. Besides, multiple head-movement simulations and motions of fitness are conquered by the APP approach as shown in the experiments. Thus, it can be concluded that the proposed approach is applicable to surveillance or healthcare applications.

Various reports have shown that the rate of road traffic accidents has increased due to reduced driver vigilance. Therefore, an accurate estimation of the driver’s alertness status plays an important part. To estimate vigilance, we adopt a novel strategy that is a deep autoencoder with subnetwork nodes (DAE SN ). The proposed network model is designed not only for sparse representation but also for dimension reduction. Some hidden layers are not calculated by randomly acquired, but by replacement technologies. Unlike the traditional electrooculogram (EOG) signals, the forehead EOG (EOG F ) signals are collected through forehead electrodes that do not have to surround the eyes, which has a convenient and effective practical application. The root-mean-square error (RMSE) and correlation coefficient (COR) while separately using three EOG F features improved to 0.11/0.79, 0.10/0.83, and 0.11/0.80, respectively. Implemented in an experimental environment, percentage of eye closure over time is calculated in real time through SMI eye-tracking-glasses, up to 120 frames/s. In addition, the time to extract features from the raw signal and display the prediction is only 34 ms, that is the level of the driver’s fatigue can be detected quickly. The experimental study shows that the proposed model for vigilance analysis has better robustness and learning capability.

To investigate the clinical feasibility of single-breath-hold (SBH) T2-weighted (T2WI) liver MRI with deep learning-based reconstruction in the evaluation of image quality and lesion delineation, compared with conventional multi-breath-hold (MBH) T2WI.One hundred and fifty-two adult patients with suspected liver disease were prospectively enrolled. Two independent readers reviewed images acquired with conventional MBH-T2WI and SBH-T2WI at 3.0 T MR scanner. For image quality analyses, motion artifacts scores and boundary sharpness scores were compared using nonparametric Wilcoxon matched pairs tests between MBH-T2WI and SBH-T2WI. With the reference standard, 89 patients with 376 index lesions were included for lesion analyses. The lesion detection rates were compared by chi-square test, the lesion conspicuity scores and lesion-liver contrast ratio (CR) were compared using nonparametric Wilcoxon matched pairs tests between the two sequences.For both readers, motion artifacts scores of SBH-T2WI were significantly lower than MBH-T2WI (P 0.001). Boundary sharpness scores of SBH-T2WI were significantly higher than MBH-T2WI (P 0.001). The lesion detection rates for SBH-T2WI were significantly higher than MBH-T2WI (P 0.001); the differences of lesion detection rates between the two sequences were statistically significant for small (≤ 10 mm) liver lesions (P 0.001), while not significant for larger (10 mm) lesions (P 0.05). Lesion conspicuity scores were significantly higher on SBH-T2WI than MBH-T2WI in the entire cohort as well as in both stratified subgroups of lesions ≤10 mm and 10 mm (P 0.001 for all). CRs for focal liver lesions were also significantly higher with SBH-T2WI (P 0.001).The SBH-T2WI sequence with deep-learning based reconstruction showed promising performance as it provided significantly better image quality, lesion detectability, lesion conspicuity and contrast within a single breath-hold, compared with the conventional MBH-T2WI.

Distributed energy resources, together with information and communication technologies, have transformed the traditional electricity consumers into proactive consumers, namely prosumers. Prosumers can exchange their surplus energy with consumers through peer-to-peer (P2P) energy sharing. In this paper, the framework of P2P energy exchange in active distribution networks is developed using a multi-round double auction (MRDA) with average pricing mechanism (APM) integrated with distributional locational marginal price. The advantages of the proposed P2P framework include, 1) modeling and integration of the costs of voltage regulation, congestion, and power loss into the payments of agents for each transaction; 2) the entire distribution network clustered into multiple zones with transactions cleared at different levels, which decreases the additional costs for successful transactions, reduces the computational time, and increases the number of successful transactions; and 3) the matching algorithm encourages more prosumers and consumers to participate in P2P energy sharing and increases the efficiency and benefit from P2P market. The proposed MRDA-APM framework is validated by testing on the 33-node and 141-node distribution test systems. Simulation results demonstrate the effectiveness of the proposed mechanism for P2P energy exchange from both technical and computational viewpoints.

The development of infrared stealth clothing technology and materials has been widely studied. However, the research of near-infrared stealth clothing still faces some challenges including complex preparation processes, narrow spectral ranges, and poor antidetection efficiency. To solve these questions, a CoGaZnSe multilayer film used for anti-near-infrared detection is designed and prepared by pulse laser deposition (PLD) at different pressures from 2 to 12 Pa. Microstructures of the film can transform from amorphous to crystal at different Ar atmospheres demonstrated by X-ray diffraction, Raman spectroscopy, and theoretical calculations. The films with different transmittances from 10 to 95% are combined with multilayer films for reducing the infrared reflection, which results in the lowest energy loss per unit thickness of 1.01 × 10-11 dB/cm. The light propagation in the multilayer is calculated by finite-difference time domain, revealing the regular sinusoidal propagation and absorption in multilayers. The multilayer films are coated on the surface of common clothing materials and tested using an infrared detector in the range of 400-6000 nm. The results prove that the quantum efficiency of infrared detection can be effectively reduced by CoGaZnSe multilayer films, especially for wool (83% in the range of 400-1800 nm and 86% in the range of 2000-6000 nm). Finally, a physical model is established to discover the mechanism of the antireflection and infrared effect and a theory of anti-infrared radiation. This research provides a new idea and method supporting the stealth technology and materials, which improves the efficiency of anti-infrared detection and makes it feasible to be applied in military, detection, and stealth technology.

Thyroid carcinoma (THCA) is the most common endocrine malignancy, and its incidence is increasing worldwide. Several studies have explored whether the tumor immune microenvironment and immune-related genes (IRGs) influence the prognosis of patients with THCA and can be used to predict the response to immune checkpoint inhibitors (ICIs). We developed an IRG prognostic/risk signature using a bioinformatics method, and its predictive capacity was validated in patients in the test set and the total set. Subsequently, we analyzed the correlation between this IRG prognostic signature and tumor-infiltrating immune cells, tumor mutation burden (TMB), and immune checkpoint protein expression in patients with THCA. With a multivariate analysis, the IRG prognostic signature, which comprised eight IRGs, was identified as an independent prognostic factor. High-risk patients had poor overall survival compared with low-risk patients. Plasma cells, monocytes, and dendritic cells infiltrated differently according to the IRG prognostic signature. The low-risk group had a higher TMB and immunophenoscore (IPS), which indicated a better response to ICIs. The qRT-PCR validated eight IRGs with differential expression in thyroid cancer and normal tissues. We conclude that the IRG prognostic signature may be a useful tool to predict survival and response to ICIs. However, further testing is required to assess the predictive capacity of this IRG prognostic signature.

Wei Sun,1,&ast; Zujin Luo,1,&ast; Jiawei Jin,1 Zhixin Cao,1 Yingmin Ma2 1Department of Respiratory and Critical Care Medicine, Beijing Chaoyang Hospital, Capital Medical University, Beijing, People’s Republic of China; 2Department of Respiratory and Critical Care Medicine, Beijing Youan Hospital, Capital Medical University, Beijing, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Yingmin MaDepartment of Respiratory and Critical Care Medicine, Beijing Youan Hospital, Capital Medical University, Beijing, People’s Republic of ChinaTel +86-10-13501185982Email ma.yingmin@163.comPurpose: To determine the effectiveness of neutrophil/lymphocyte ratio (NLR), compared to traditional inflammatory markers, for predicting noninvasive mechanical ventilation (NIMV) failure in acute exacerbation of chronic obstructive pulmonary disease (AECOPD) patients.Patients and Methods: We conducted this retrospective observational study including 212 AECOPD patients who required NIMV during hospitalization from January 2015 to December 2020 in the department of respiratory and critical care medicine of Beijing Chao-Yang Hospital (west campus). We reviewed the medical record to determine if NIMV succeeded or failed for each patient, and compared NLR with traditional markers (leukocyte, C-reactive protein [CRP] and procalcitonin [PCT]) between NIMV failure and NIMV success group. Receiver-operating characteristic (ROC) curve and multivariate logistic regression analysis were used to assess the accuracy of these markers for predicting NIMV failure.Results: A total of 38 (17.9%) patients experienced NIMV failure. NLR was a more sensitive biomarker to predict NIMV failure (AUC, 0.858; 95% CI 0.785– 0.931) than leukocyte counts (AUC, 0.723; 95% CI 0.623– 0.823), CRP (AUC, 0.670; 95% CI 0.567– 0.773) and PCT (AUC, 0.719; 95% CI 0.615– 0.823). There was statistically positive correlation between NLR and leukocytes count (r=0.35, p< 0.001), between NLR and CRP (r=0.258, p< 0.001), between NLR and PCT (r=0.306, p< 0.001). The cutoff value of NLR to predict NIMV failure was 8.9 with sensitivity 0.688, specificity 0.886 and diagnostic accuracy 0.868. NLR> 8.9 (odds ratio, 10.783; 95% CI, 2.069– 56.194; P=0.05) was an independent predictor of NIMV failure in the multivariate logistic regression model.Conclusion: NLR may be an effective marker for predicting NIMV failure in AECOPD patients, and the patients with NLR> 8.9 should be handled with caution since they are at higher risk of NIMV failure and require intubation. Further study with a larger sample size and with more data is necessary to confirm our study.Keywords: COPD, noninvasive mechanical ventilation, neutrophil/lymphocyte ratio, predictor, failure, NIMV, NLR, chronic obstructive pulmonary disease

High-performance electromagnetic (EM) wave absorption property could be achieved by architecture design of nanomaterials. Herein, two layer hybrid Co0.2Fe2.8O4/carbon nanofibers with porous three-dimensional (3D) hierarchical structure were synthesized successfully through facile electrospinning, carbonization and mild chemical treatment. The Co0.2Fe2.8O4 particles grew along the carbon nanofibers, forming the enhanced heterogeneous interfaces and high specific areas. As expected, the EM wave absorbent showed an excellent absorbing capability. The composites achieved a maximum reflection loss (RL) of −43.45 dB at 11.1 GHz with thickness of 3.0 mm. More importantly, the effective bandwidth (RL ≤ −10dB) was 5.85 GHz, covering 30% of the entire measured bandwidth. The absorption intensity and bandwidth were superior to other typical CoFe-based composites. The intrinsic mechanism of the absorption revealed that the polarization losses, magnetic losses, magnetic natural resonance and exchanged resonance losses contributed to the high-performance microwave absorption. Moreover, good impedance matching and complex transmission paths that generated from unique porous network also played an important role. This study is expected to guide future exploration on designing and synthesizing high performance EM wave absorbents.

BACKGROUND: Cytokines play critical roles in the inflammatory processes underlying liver failure. The relevance of interleukin-35 (IL-35), an anti-inflammatory cytokine, in liver failure remains uncharacterized. This study was conducted to investigate whether the IL-35 level in patients with prophase of liver failure (PLF) is associated with prognosis and the possible mechanism of immune regulation for IL-35. METHODS: This retrospective study enrolled 42 patients with PLF at the Department of Infection, First Affiliated Hospital of Soochow University between January 2016 and December 2018. Thirty patients with hepatitis and 30 healthy controls were also enrolled. We divide patients with prophase of liver failure into improvement group who recovered quickly (n=33) and deteriorate group who deteriorated to overt liver failure (n=9). Serum IL-35 level was measured by enzyme-linked immunosorbent assay (ELISA). The ratio of regulatory T cells to T-helper type-17 cells (Treg/Th17) in peripheral blood was determined by flow cytometry. RESULTS: Serum IL-35 level was higher in patients with PLF who showed subsequent improvement than in patients with PLF who showed deterioration to overt liver failure. The Treg/Th17 ratio was higher in patients with PLF who showed improvement than in patients with PLF who developed overt liver failure. The serum IL-35 level and Treg/Th17 ratio were positively correlated in patients with PLF. CONCLUSIONS: High serum IL-35 level is associated with better prognosis in patients with PLF.

Background Improved prognostic prediction is needed to stratify patients with early hepatocellular carcinoma (EHCC) to refine selection of adjuvant therapy. We aimed to develop a machine learning (ML)-based model to predict survival after liver resection for EHCC based on readily available clinical data. Methods We analyzed data of surgically resected EHCC (tumor≤5 cm without evidence of extrahepatic disease or major vascular invasion) patients from the Surveillance, Epidemiology, and End Results (SEER) Program to train and internally validate a gradient-boosting ML model to predict disease‐specific survival (DSS). We externally tested the ML model using data from 2 Chinese institutions. Patients treated with resection were matched by propensity score to those treated with transplantation in the SEER-Medicare database. Results A total of 2778 EHCC patients treated with resection were enrolled, divided into 1899 for training/validation (SEER) and 879 for test (Chinese). The ML model consisted of 8 covariates (age, race, alpha-fetoprotein, tumor size, multifocality, vascular invasion, histological grade and fibrosis score) and predicted DSS with C-Statistics >0.72, better than proposed staging systems across study cohorts. The ML model could stratify 10-year DSS ranging from 70% in low-risk subset to 5% in high-risk subset. Compared with low-risk subset, no remarkable survival benefits were observed in EHCC patients receiving transplantation before and after propensity score matching. Conclusion An ML model trained on a large-scale dataset has good predictive performance at individual scale. Such a model is readily integrated into clinical practice and will be valuable in discussing treatment strategies., Graphical Abstract

Background Cancer‐associated fibroblasts (CAFs) with different gene profiles from normal fibroblasts (NFs) have been implicated in tumor progression. Angiopoietin‐like protein 4 (ANGPTL4) has been shown to regulate tumor angiogenesis and metastasis, and predict poor prognosis. However, the ANGPTL4 expression in CAFs, especially in gallbladder CAFs (GCAFs) and its relationship with patient prognosis is unclear. Methods Affymetrix gene profile chip analysis in vitro was performed to detect the different gene expression profiles between GCAFs and NFs. RT‐qPCR, immunohistochemistry, and western blotting were performed to investigate the different expression levels of ANGPTL4 in GCAFs/NFs in vitro and in an in vivo nude mouse model of xenograft tumors. Finally, the ANGPTL4 expression was investigated in the stroma of different lesion tissues of the human gallbladder by immunohistochemistry, especially the expression in GCAFs in vivo by co‐immunofluorescence, and their prognostic significance in patients with gallbladder cancer (GBC) was assessed. Results ANGPTL4 was upregulated in both GCAFs in vitro and in the xenograft stroma of nude mice in vivo, and its expression was also significantly upregulated in human GBC stroma co‐localized with the interstitial markers fibroblast secreted protein‐1 and α‐smooth muscle actin. In addition, the elevated ANGPTL4 expression in GCAFs was correlated with tumor differentiation, liver metastasis, venous invasion and Nevin staging, and GBC patients with an elevated ANGPTL4 expression in GACFs were found to have a lower survival rate. Conclusions Increased ANGPTL4 expression in GCAFs correlates with poor patient prognosis, which indicates a potential therapeutic target for human GBCs., ANGPTL4 expression was upregulated in GCAF, which was significantly related to the degree of clinical GBC differentiation, liver metastasis, venous invasion, and Nevin staging, and GBC patients with elevated ANGPTL4 expression in GCAF had lower survival rate.

Idiopathic pulmonary fibrosis (IPF) mainly occurs in elderly people over the age of sixty. IPF pathogenesis is associated with alveolar epithelial cells (AECs) senescence. Activation of PI3K/AKT signaling induced by insulin-like growth factor 1 (IGF1) participates in AEC senescence and IPF by releasing CTGF, TGF-β1, and MMP9. Our previous study demonstrated that core fucosylation (CF) modification, catalyzed by a specific core fucosyltransferase (FUT8) can regulate the activation of multiple signaling pathways, and inhibiting CF can alleviate pulmonary fibrosis in mice induced by bleomycin. However, whether CF is involved in IGF1-mediated AEC senescence in IPF remains unclear. In this study, we found that the IGF1/PI3K/AKT signaling pathway was activated in IPF lung tissue. Meanwhile, CF was present in senescent AECs. We also showed that IGF1 could induce AECs senescence with enhanced CF in vivo and in vitro. Inhibiting CF alleviated AECs senescence and pulmonary fibrosis induced by IGF1. In addition, activation of IGF1/PI3K/AKT signaling depends on CF. In conclusion, this study confirmed that CF is an important target regulating the IGF1 signaling pathway in AEC senescence and IPF, which might be a candidate target to treat IPF in the future.

Background Studies of the impact of increased hemoglobin on spontaneous intracerebral hemorrhage (ICH) are limited. The present study aimed to explore the effect of increased hemoglobin on ICH. Methods A retrospective single-center study using medical records from a database processed by univariate and multivariate analyses was performed in the People’s Hospital of Tibet Autonomous Region in Lhasa, Tibet, China. Results The mean hemoglobin level in 211 patients with ICH was 165.03 ± 34.12 g/l, and a median hematoma volume was 18.5 ml. Eighty-eight (41.7%) patients had large hematomas (supratentorial hematoma ≥ 30 ml; infratentorial hematoma ≥ 10 ml). No differences in ICH risk factors between the groups with different hemoglobin levels were detected. Increased hemoglobin was independently associated with large hematomas [odds ratio (OR) 1.013, P = 0.023]. Increased hemoglobin was independently associated with ICH with subarachnoid hemorrhage (OR 1.014, P = 0.016), which was more pronounced in men (OR 1.027, P = 0.002). Increased hemoglobin was independently associated with basal ganglia hemorrhage and lobar hemorrhage in men (OR 0.986, P = 0.022; OR 1.013, P = 0.044, respectively) but not in women (P > 0.1). Conclusions Increased hemoglobin was independently associated with large hemorrhage volume. Increased hemoglobin was independently associated with lobar hemorrhage in men and ICH with subarachnoid hemorrhage, which was more pronounced in men. Additional studies are needed to confirm our findings and explore potential mechanisms.