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Recently, luxury fashion brands can webcast fashion shows and analyze market feedback from social media exposure (SME). See now buy now (SNBN), a new product introduction system that allows consumers to purchase products after fashion shows, has been deemed a revolutionary movement in the fashion industry. Whether SNBN can replace see now buy later (SNBL), the traditional system in which consumers purchase products several months after fashion shows, is unclear. In this article we evaluate the value of demand learning through SME for SNBL and SNBN. We develop a stylish two-period model to characterize SNBL and SNBN with SME. We find that when the feedback accuracy and holding cost are sufficiently low, SNBN performs better than SNBL with SME. Furthermore, for SNBL, when the consumer valuation is relatively low, learning market responses from SME is effective and profit improvement with SME decreases. For SNBN, SME is not always effective. Our results imply that brands, such as Gucci, should sell trendy and fashionable items via SNBL without SME and classic products (products with high consumer preference) via SME. Brands, such as Burberry, should sell low holding cost products (e.g., shirts) through SNBN and high holding cost products (e.g., leather bags) through SNBL.

Feature extraction is one of the most important tasks in multi-label learning. The performance of multi-label classification can be effectively improved by reducing the dimension of multi-label datasets. Although research on multi-label feature extraction has received extensive attention and made significant progress, further improvement is still necessary. One of the concerns is robustness, where existing multi-label feature extraction algorithms are usually sensitive to noise and outliers. To address this issue, a robust multi-label relief feature selection algorithm based on fuzzy margin co-optimization, called ML-FS-FM, is proposed in this article. Under the multi-label learning framework, the classical fuzzy relief feature weighting algorithm is introduced to ML-FS-FM, which involves the mechanisms of fuzzy feature weighting, fuzzy nearest neighbor and fuzzy instance force coefficient, so as to effectively reduce the influence of noise and outliers, and to extract feature subsets that are beneficial to the classification task. The effectiveness of the proposed algorithm is verified by a large number of experiments on multi-label datasets.

Nowadays, carbon frameworks derived from natural biomaterials have attracted extensive attention for electromagnetic interference (EMI) shielding due to their renewability and affordability. However, it is critical and challenging to achieve effective regulation of shielding effectiveness (SE) as well as weaken the strong EM reflection of highly conductive biomass-based carbon materials. Herein, commercial cotton pads with oriented structure were selected as carbonaceous precursor to fabricate aligned carbon networks by pyrolysis, and the EMI SE of the samples with increased temperature of 800-1000°C can be accurately controlled in the effective range of ∼21.7-29.1, ∼27.7-37.1 and ∼32.7-43.3 dB with high reflection coefficient of >0.8 by changing the cross-angle between the electric-field direction of incident EM waves and the fiber-orientation direction due to the occurrence of opposite internal electric field. Moreover, the further construction of Salisbury absorber-liked double-layer structure could result in an ultra-low reflection coefficient of only ∼0.06 but enhanced SE variation range up to ∼38.7-49.3 dB during the adjustment of cross-angle, possibly due to the destructive interference of EM waves in the double-layer carbon networks. This work would provide a simple and effective way for constructing high-performance biomass carbon materials with adjustable EMI shielding and ultra-low reflectivity.

Amphipathic helix (AH)features the segregation of polar and nonpolar residues and plays important roles in many membrane-associated biological processes through interacting with both the lipid and the soluble phases. Although the AH structure has been discovered for a long time, few ab initio machine learning-based prediction models have been reported, due to the limited amount of training data. In this study, we report a new deep learning-based prediction model, which is composed of a residual neural network and the uneven-thresholds decision algorithm. It is constructed on 121 membrane proteins, in total 51640 residue samples, which are curated from an up-to-date membrane protein structure database. Through a rigid 10-fold nested cross-validation experiment, we demonstrate that our model can achieve promising predictions and exceed current state-of-the-art approaches in this field. This presents a new avenue for accurately predicting AHs. Analysis on the contribution of the input residues and some cases further reveals the high interpretability and the generalization of our model.

Using anteroposterior (AP) hip radiograph, we measured several indexes to investigate the association with bone mineral density (BMD) before THA and found a highly effective index to predict femoral BMD. This technique is helpful for both patients and clinicians to identify potential candidates with low BMD to whom DXA examination is particularly recommended. The purpose of the study is to identify patients with low bone mineral density (BMD) prior to total hip arthroplasty with the help of AP hip radiographs. Indexes on AP hip radiographs and T-scores from DXA examination of the lumbar spine and the affected hip were acquired from patients before THA. Indexes measured on AP hip radiographs including the canal calcar ratio (CCR), canal flare index (CFI), morphological cortical index (MCI), canal bone ratio (CBR), and canal bone area ratio (CBAR). The relevance between indexes and the T-score of femora was evaluated by correlation analysis, and the diagnostic value of indexes for osteopenia was examined by receiver operating characteristic (ROC) curves. A total of 81 patients were included. The average value of CBR-7, CBR-10, and CBAR (7–10) were highly related to the T-score of femora (r = − 0.592, r = − 0.634, and r = − 0.631, respectively, p

A novel cystine-knot peptide–based PET radiopharmaceutical, 18F-FP-R01-MG-F2 (knottin), was developed to selectively bind to human integrin αvβ6 which is overexpressed in pancreatic cancer. The purpose of this study is to evaluate the safety, biodistribution, dosimetry, and lesion uptake of 18F-FP-R01-MG-F2 in patients with pancreatic cancer. Fifteen patients (6 men, 9 women) with histologically confirmed pancreatic cancer were prospectively enrolled and underwent knottin PET/CT between March 2017 and February 2021 (ClinicalTrials.gov Identifier NCT02683824). Vital signs and laboratory results were collected before and after the imaging scans. Maximum standardized uptake values (SUVmax) and mean SUV (SUVmean) were measured in 24 normal tissues and pancreatic cancer lesions for each patient. From the biodistribution data, the organ doses and whole-body effective dose were calculated using OLINDA/EXM software. There were no significant changes in vital signs or laboratory values that qualified as adverse events or serious adverse events. At 1 h post-injection, areas of high 18F-FP-R01-MG-F2 uptake included the pituitary gland, stomach, duodenum, kidneys, and bladder (average SUVmean: 9.7–14.5). Intermediate uptake was found in the normal pancreas (average SUVmean: 4.5). Mild uptake was found in the lungs and liver (average SUVmean

As the cathode material of commercial lithium-ion batteries (LIBs) with the highest volumetric energy density, LiCoO2 is still widely used in the field of consumer electronics products. Although Li...

Motivation Coiled-coil is composed of two or more helices that are wound around each other. It widely exists in proteins and has been discovered to play a variety of critical roles in biology processes. Generally, there are three types of structural features in coiled-coil: coiled-coil domain (CCD), oligomeric state and register. However, most of the existing computational tools only focus on one of them. Results Here, we describe a new deep learning model, CoCoPRED, which is based on convolutional layers, bidirectional long short-term memory, and attention mechanism. It has three networks, i.e. CCD network, oligomeric state network, and register network, corresponding to the three types of structural features in coiled-coil. This means CoCoPRED has the ability of fulfilling comprehensive prediction for coiled-coil proteins. Through the 5-fold cross-validation experiment, we demonstrate that CoCoPRED can achieve better performance than the state-of-the-art models on both CCD prediction and oligomeric state prediction. Further analysis suggests the CCD prediction may be a performance indicator of the oligomeric state prediction in CoCoPRED. The attention heads in CoCoPRED indicate that registers a, b and e are more crucial for the oligomeric state prediction. Availability and implementation CoCoPRED is available at http://www.csbio.sjtu.edu.cn/bioinf/CoCoPRED. The datasets used in this research can also be downloaded from the website. Supplementary information Supplementary data are available at Bioinformatics online.

Background Enhanced recovery after surgery (ERAS) program advocates implementation of perioperative goal-directed fluid therapy and reduced application of colloidal fluids. It should be used reasonably selectively in high-risk patients despite the clear efficacy of human albumin (HA). Therefore, it is vital to identify the risk factors for the use of HA. This study aims to determine the incidence and risk factors of HA administration in patients undergoing total hip or knee arthroplasty (THA, TKA). Methods We identified patients undergoing THA or TKA in multiple institutions from 2014 to 2016 and collected patient demographics and perioperative variables. The criterion of HA administration was defined as a postoperative albumin level < 32 g/L or 32 to 35 g/L for at-risk patients. We compared 14 variables between patients who received HA administration and those who did not after stratification by the preoperative albumin (pre-ALB) level. Multivariable regressions identified the independent risk factors associated with HA administration. Results In total, 958 (20.3%) of 4713 patients undergoing THA and 410 (9.7%) of 4248 patients undergoing TKA received HA administration. In addition to pre-ALB < 35 g/L, preoperative anemia (odds ratio [OR] 2.12, P = 0.001; OR 1.39, P < 0.001) and drain use (OR 3.33, P = 0.001; OR 4.25, P < 0.001) were also independent risk factors for HA administration after THA regardless pre-ALB < 35 g/L or not, and patients undergoing TKA diagnosed of rheumatoid arthritis or ankylosing spondylitis tended to receive HA administration regardless pre-ALB < 35 g/L or not (OR 3.67, P = 0.002; OR 2.06, P < 0.001). Conclusions The incidence of HA administration was high in patients undergoing THA or TKA, and several variables were risk factors for HA administration. This finding may aid surgeons in preoperatively identifying patients requiring HA administration and optimizing perioperative managements.

Previous cross-sectional studies have demonstrated the high prevalence of depression and comorbidity in knee osteoarthritis (KOA), and KOA or its impact on lifestyle was seen as a potential trigger factor of depression and comorbidity. However, the exact onset and progression pattern of depression and comorbidity in KOA was still unknown.Group-based trajectory modeling (GBTM) analysis was conducted in the 2833 subjects selected from the osteoarthritis initiative (OAI) database. Eight-year trajectories were determined and described. Baseline characteristics were investigated in multi-variable regression to detect the risk factors of the unfavored trajectory.Stable trajectory (70.4%) and worsening trajectory (29.6%) were identified in comorbidity. The risk factors for the worsening trajectory membership were the obesity (OR = 1.47 CI = [1.20, 1.79], P 0.001), older age (OR = 1.74, CI = [1.41, 2.16], P 0.001), and smoke (OR = 1.30, CI = [1.08, 1.57], P 0.01) at baseline. Stable trajectory (52.0%), slow-worsening trajectory (40.5%), and fast-worsening trajectory (7.5%) were identified in depression symptoms. The risk factors for the fast-worsening trajectory membership were female (OR = 1.51 CI = [1.03, 2.20], P 0.05), lower income (OR = 1.52, CI = [1.01, 2.27], P 0.05), and smoke (OR = 1.30, CI = [1.08, 1.57], P 0.01) at baseline.A significant amount of KOA subjects tends to develop depression symptoms and comorbidity. Managing related risk factors, like weight loss or smoking cessation, might have considerable significance in preventing or delaying depression symptoms and comorbidity in KOA. Key Points • The first study investigating the trajectory of comorbidity progression in KOA. • Approximately 7.5% of KOA patients tend to develop depression symptoms quite rapidly, and 30% of KOA patients tend to develop comorbidity • Risk factors of worsening trajectories were identified: obesity, older age, smoking, female, and lower income.

Published studies have reported many inconsistent results regarding the comparison of same-day discharge total joint arthroplasty (TJA) and inpatient TJA. More notably, many recent studies comparing same-day discharge TJA with fast-track TJA presented higher rates of complications for same-day discharge TJA, which raises concerns about the safety of same-day discharge TJA. We systematically searched the MEDLINE, Embase, and Cochrane Central Register of Controlled Trials databases up to June 2020 for studies comparing mortality, readmission, and complications in same-day discharge and inpatient total hip or knee arthroplasty. Studies that used inpatient TJA as the control could be further divided into fast-track inpatient TJA (length of stay [LOS] ≤ 2 days) and traditional inpatient TJA (no restrictions on LOS). Relative risks were pooled to compare the outcomes of the same-day discharge group and the control group. According to selection criteria and quality assessment, 14 studies including 222,766 cases were identified. There was no significant difference in the risk of mortality (RR = 1.42, CI [0.67, 3.01]) or readmission (RR = 0.93, CI [0.79, 1.10]) between same-day discharge TJA and inpatient TJA. Compared with fast-track TJA, the rate of overall complications in same-day discharge TJA was significantly higher (RR = 1.67, CI [1.45, 1.93]), while the rates of overall complications were similar between same-day discharge and traditional inpatient TJA (RR = 0.83, CI [0.67, 1.03]). The overall safety of same-day discharge TJA is satisfactory; however, more complications were detected in same-day discharge TJA than that in fast-track TJA. Complications in same-day discharge TJA might be underestimated in some previous studies taking long-staying inpatient TJA as control. Being more cautious about complications is necessary in the care of same-day discharge TJA, and extensive prospective studies are needed to explore the optimized option that weighs both cost and complications.

Lower canal fill ratio was reported to correlate with aseptic loosening in many studies. However, the most widely used standard of fill ratio seemed inapplicable to Dorr type C femurs. We aimed to adapt the method of measuring the fill ratio in Dorr type C femurs and compare the outcomes among patients with different fill ratios. Twenty patients with Corail stems implanted in their Dorr type C femurs received spectrum CT to evaluate the whole-stem's fill ratio. Pearson Correlation Coefficient was calculated to assess the correlation between the fill ratio in X-ray film and spectrum CT. Then 87 THAs were involved in this study, divided into the fill ratio ≤ 80% group and the fill ratio > 80% group. Clinical and radiological outcomes were evaluated with a mean follow-up of 8.2 years. Fill ratio at 2 cm below the lesser trochanter in anterior–posterior X-ray film correlated with the whole-stem's fill ratio (r = 0.50, P = 0.02). Survival rate of stem, function scores, and radiological outcomes between the two groups showed no significant difference. In the fill ratio > 80% group, intraoperative fracture was significantly higher (19% VS 5%, P

Rationale: Posttranscriptional modifications are implicated in vascular remodeling of pulmonary hypertension (PH). m6A (N6-methyladenosine) is an abundant RNA modification that is involved in various biological processes. Whether m6A RNA modification and m6A effector proteins play a role in pulmonary vascular remodeling and PH has not been demonstrated.Objectives: To determine whether m6A modification and m6A effectors contribute to the pathogenesis of PH.Methods: m6A modification and YTHDF1 expression were measured in human and experimental PH samples. RNA immunoprecipitation analysis and m6A sequencing were employed to screen m6A-marked transcripts. Genetic approaches were employed to assess the respective roles of YTHDF1 and MAGED1 in PH. Primary cell isolation and cultivation were used for function analysis of pulmonary artery smooth muscle cells (PASMCs).Measurements and Main Results: Elevated m6A levels and increased YTHDF1 protein expression were found in human and rodent PH samples as well as in hypoxic PASMCs. The deletion of YTHDF1 ameliorated PASMC proliferation, phenotype switch, and PH development both in vivo and in vitro. m6A RNA immunoprecipitation analysis identified MAGED1 as an m6A-regulated gene in PH, and genetic ablation of MAGED1 improved vascular remodeling and hemodynamic parameters in SU5416/hypoxia mice. YTHDF1 recognized and promoted translation of MAGED1 in an m6A-dependent manner that was absent in METTL3-deficient PASMCs. In addition, MAGED1 silencing inhibited hypoxia-induced proliferation of PASMCs through downregulating PCNA.Conclusions: YTHDF1 promotes PASMC proliferation and PH by enhancing MAGED1 translation. This study identifies the m6A RNA modification as a novel mediator of pathological changes in PASMCs and PH.

Positron emission tomography (PET) imaging of apoptosis can noninvasively detect cell death in vivo and assist in monitoring tumor response to treatment in patients. While extensive efforts have been devoted to addressing this important need, no apoptosis PET imaging agents have yet been approved for clinical use. This study reports an improved 18F-labeled caspase-sensitive nanoaggregation tracer ([18F]-C-SNAT4) for PET imaging of tumor response to chemo- and immunotherapies in preclinical mouse models. We rationally designed and synthesized a new PET tracer [18F]-C-SNAT4 to detect cell death both in vitro and in vivo. In vitro radiotracer uptake studies were performed on drug-sensitive and -resistant NSCLC cell lines (NCI-H460 and NCI-H1299, respectively) treated with cisplatin at different doses. In vivo therapy response monitoring by [18F]-C-SNAT4 PET imaging was evaluated with two treatment modalities—chemotherapy and immunotherapy in two tumor xenografts in mice. Radiotracer uptake in the tumors was validated ex vivo using γ-counting and cleaved caspase-3 immunofluorescence. This [18F]-C-SNAT4 PET tracer was facilely synthesized and displayed improved serum stability profiles. [18F]-C-SNAT4 cellular update was elevated in NCI-H460 cells in a time- and dose-dependent manner, which correlated well with cell death. A significant increase in [18F]-C-SNAT4 uptake was measured in NCI-H460 tumor xenografts in mice. In contrast, a rapid clearance of [18F]-C-SNAT4 was observed in drug-resistant NCI-H1299 in vitro and in tumor xenografts. Moreover, in BALB/C mice bearing murine colon cancer CT26 tumor xenografts receiving checkpoint inhibitors, [18F]-C-SNAT4 showed its ability for monitoring immunotherapy-induced apoptosis and reporting treatment-responding mice from non-responding. The uptake of [18F]-C-SNAT4 in tumors received chemotherapy and immunotherapy is positively correlated with the tumor apoptotic level and the treatment efficacy. [18F]-C-SNAT4 PET imaging can monitor tumor response to two different treatment modalities and predict the therapeutic efficacy in preclinical mouse models.

Objectives To investigate the proportion of insulin‐dependent diabetes mellitus (IDDM) patients among diabetic patients undergoing total joint arthroplasty (TJA) and whether insulin dependence is associated with postoperative complications. Methods A systematic literature search was performed in EMBASE, PubMed, Ovid, Medline, the Cochrane Library, Web of Science, the China Science and Technology Journal Database, and China National Knowledge Infrastructure from the inception dates to 10 September 2019. Observational studies reporting adverse events with IDDM following TJA were included. Primary outcomes were cardiovascular complications, pulmonary complications, kidney complications, wound complications, infection, and other complications within 30 days of surgery. Secondary outcomes were the proportion of IDDM patients among diabetic patients undergoing TJA and its time trend. Results A total of 19 studies involving 85,689 participants were included. Among patients undergoing TJA, 26% of diabetic patients had IDDM. Compared with non‐insulin‐dependent diabetes (NIDDM), the incidences of cardiac arrest (risk ratio [RR], 2.346; 95% confidence interval [CI], 1.553 to 3.546), renal failure (relative risk [RR], 2.758; 95% CI, 1.830 to 4.156), deep incisional surgical site infection (RR, 1.968; 95% CI, 1.107 to 3.533), wound dehiscence (RR, 2.209; 95% CI, 1.830 to 4.156), and death (RR, 2.292; 95% CI, 1.568 to 3.349) were all significantly increased in IDDM. A significant time trend was witnessed for the prevalence of IDDM (P = 0.014). There was no statistical significance for organ/space surgical site infection, thrombotic events (deep venous thrombosis/ pulmonary embolism), and revision rates. Conclusion Insulin‐dependent diabetes is an independent high‐risk factor for increased adverse outcomes relative to NIDDM, suggesting that hierarchical and optimal blood glucose management may contribute to reducing the adverse complications after surgery for these patients. In addition, because the risk of sepsis, deep wound infection, organ/space surgical site infection, urinary tract infection, renal insufficiency, and renal failure significantly increase after TJA in IDDM patients, more active postoperative antimicrobial prophylaxis may be needed on the premise of protecting renal function., Results of the meta‐analysis.

BackgroundWhether the cement should be used in the total knee arthroplasty (TKA) was still in controversy. This meta-analysis was performed to compare the efficacy of two kinds of fixation.MethodsRandomized controlled trials (RCTs), prospective/retrospective observational studies from PubMed (on 2019 September), EMBASE (on 2019 September), and the Cochrane Central Register of Controlled Trials (CENTRAL) and Web of Science (on 2019 September) were searched. Only studies followed more than 2 years was included for the review. The PRISMA guidelines and Cochrane Handbook were adopted to assess the quality of the results reported in included studies to ensure that the results of our meta-analysis were reliable and veritable. The continuous and dichotomous outcomes were collected in a standard form, and the data were analyzed by Review Manager 5.3 software. Finally, the results were presented in the Forest plots.ResultsTwenty-six studies involving 2369 patients in cementless TKA and 2654 patients in cemented TKA were included. The rate of revision was not significantly different in two groups (p= 0.55). More than eight reasons caused revision were found in our study, the aseptic loosing was the most common, followed by the periprosthetic joint infection (PJI), neither was significantly different (p= 0.88 and 0.45, respectively). While significantly better long-term functional recovery was found in cementless TKA in terms of Knee Society Function Score (p= 0.004) and manipulation under anesthesia (p= 0.007).ConclusionCementless fixation did not decrease the rate of revision after the total knee arthroplasty compared with the cemented fixation, while the long-term functional recovery was significantly better in the cementless group.

Jia Yu,1,* Hongyan Sun,2,* Jinhua Zhu,3,* Xintong Wei,1 Hongfei Shi,2 Bin Shen,3 Liyun Ren,1 Yan He,1 Rongyan Zhang,3 Mingzhi Zhang,1 Hao Peng1,4 1Department of Epidemiology, School of Public Health, Medical College of Soochow University, Suzhou, People’s Republic of China; 2Center for Disease Prevention and Control of Tianning District, Changzhou, People’s Republic of China; 3Center for Disease Prevention and Control of Wujiang District, Suzhou, People’s Republic of China; 4Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Soochow University, Suzhou, People’s Republic of China*These authors contributed equally to this workCorrespondence: Hao PengDepartment of Epidemiology, School of Public Health, Medical College of Soochow University, 199 Renai Road, Industrial Park, Suzhou, 215123, People’s Republic of ChinaTel +86 512 6588 0078Fax +86 512 6588 0052Email penghao@suda.edu.cnObjective: The relationship between obesity and hyperuricemia has been demonstrated by many studies. However, whether or to what extent metabolic condition influents the association between obesity and hyperuricemia was not clear. Here, we aimed to examine the association between obese-metabolic phenotype and hyperuricemia in a large sample of Chinese adults.Methods: According to BMI and metabolic syndrome, obese-metabolic phenotype was defined as metabolically unhealthy obesity (MUO), metabolically healthy obesity (MHO), metabolically unhealthy non-obesity (MUNO) and metabolically healthy non-obesity (MHNO)in the Tianning cohort (N=5072). We conducted a cross-sectional analysis between obese-metabolic phenotype and hyperuricemia, followed by a Mendelian Randomization analysis using GWAS summary data to confirm the causality between uric acid and BMI.Results: The average level of serum UA showed 41.87-higher μmol/L in participants with MHO (β=41.87, P< 0.001) and 63.18-higher μmol/L in participants with MUO (β=63.18, P< 0.001), compared to those with MHNO. Compared to participants with MHNO, those with MUO had the highest likelihood to have hyperuricemia (OR=4.56, P< 0.001), followed by those with MHO (OR=3.32, P< 0.001). Mendelian randomization analysis indicated that uric acid was more likely to be a consequence of BMI (β=0.059, P=6.54× 10− 154).Conclusion: MUO, in comparison with MHO, was significantly associated with hyperuricemia in Chinese adults.Keywords: metabolic syndrome, obesity, serum uric acid, hyperuricemia

Prostate cancer is one of the most common malignancies worldwide, yet limited tools exist for prognostic risk stratification of the disease. Identification of new biomarkers representing intrinsic features of malignant transformation and development of prognostic imaging technologies are critical for improving treatment decisions and patient survival. In this study, we analyzed radical prostatectomy specimens from 422 patients with localized disease to define the expression pattern of methionine aminopeptidase II (MetAP2), a cytosolic metalloprotease that has been identified as a druggable target in cancer. MetAP2 was highly expressed in 54% of low-grade and 59% of high-grade cancers. Elevated levels of MetAP2 at diagnosis were associated with shorter time to recurrence. Controlled self-assembly of a synthetic small molecule enabled design of the first MetAP2-activated PET imaging tracer for monitoring MetAP2 activity in vivo. The nanoparticles assembled upon MetAP2 activation were imaged in single prostate cancer cells with post-click fluorescence labeling. The fluorine-18–labeled tracers successfully differentiated MetAP2 activity in both MetAP2-knockdown and inhibitor-treated human prostate cancer xenografts by micro-PET/CT scanning. This highly sensitive imaging technology may provide a new tool for noninvasive early-risk stratification of prostate cancer and monitoring the therapeutic effect of MetAP2 inhibitors as anticancer drugs. Significance: This study defines MetAP2 as an early-risk stratifier for molecular imaging of aggressive prostate cancer and describes a MetAP2-activated self-assembly small-molecule PET tracer for imaging MetAP2 activity in vivo.

Background: Laryngeal squamous cell carcinoma (LSCC) is one of the most common malignancy in the respiratory tract and could reduce the quality of life seriously like dyspnea, dysphonia and dysphagia. Moreover, 5-year survival rate has decreased over the past 40 years. This study was designed to identify mRNAs that related to prognosis in LSCC to enable early detection and outcome improvement. Methods: Gene expression profiles from Gene Expression Omnibus (GEO) (GSE59102, GSE84957) and The Cancer Genome Atlas (TCGA) were analyzed to identify differentially expressed genes (DEGs) with the help of bioinformatics tools. Functional enrichment analyses including Gene Ontology (GO) and pathway analysis were carried out to investigate the role of those genes and underlying molecular mechanisms in LSCC. Cox's regression analyses (univariate, LASSO and multivariate in order) were utilized to identify DEGs related with patients' overall survival and a 4-mRNA-based prognostic risk score model was established. Univariate and multivariate Cox's regression analyses were then performed on LSCC data (90 patients left) to identify independent predictors of OS, including the signature and clinicopathologic variables. The prognostic value of the gene signature was further validated and the genes were analyzed by GEPIA to get pan-cancer expression profiles. Results: 444 differentially expressed mRNAs (250 up-regulated, 194 down-regulated) were identified based on the threshold of fold change > 2 and adjusted p value < 0.05. Univariate Cox's regression analysis showed that high risk score (HR: 3.056, 95% confidence interval [CI]: 0.135-0.649, p

Objectives: Furin has been associated with hypertension through unclear underlying mechanisms. FURIN promoter methylation may participate in the underlying mechanisms, but no evidence supports this possibility. Here, we performed a prospective analysis to study the association between FURIN promoter methylation and incident hypertension. Methods: DNA methylation levels in the FURIN promoter were quantified by target bisulfite sequencing using peripheral blood from 1043 participants in the Gusu cohort (mean age: 50 years, 30% men) who were free of hypertension at baseline. After an average of 4 years of follow-up, 149 (14.3%) participants developed hypertension. Multiple testing was controlled for by measuring the false-discovery rate. Results: Of the eight CpG loci assayed, DNA methylation levels at Chr15: 91416118 were significantly associated with incident hypertension after adjusting for covariates and multiple testing (hazard ratio [HR] = 1.38, 95% confidence interval [CI]: 1.17–1.64, q = 0.001). The weighted truncated-product method, which combines single CpG associations, revealed that DNA methylation at multiple CpG sites was jointly associated with incident hypertension (P < 0.001). Using the average methylation level of all CpG sites as a surrogate for FURIN promoter methylation revealed a similar association (HR = 1.36, 95% CI: 1.08–1.72, P = 0.009). Almost all CpG methylations negatively correlated with serum furin levels, which mediated approximately 29.44% of the association between FURIN promoter methylation and incident hypertension. Conclusions: These results suggest that FURIN promoter hypermethylation is associated with an increased risk for hypertension in Chinese adults, partially through suppressing furin expression or excretion.

BackgroundRNA-binding proteins (RBPs) play crucial roles in various biological processes. Deep learning-based methods have been demonstrated powerful on predicting RBP sites on RNAs. However, the training of deep learning models is very time-intensive and computationally intensive.ResultsHere we present a deep learning-based RBPsuite, an easy-to-use webserver for predicting RBP binding sites on linear and circular RNAs. For linear RNAs, RBPsuite predicts the RBP binding scores with them using our updated iDeepS. For circular RNAs (circRNAs), RBPsuite predicts the RBP binding scores with them using our developed CRIP. RBPsuite first breaks the input RNA sequence into segments of 101 nucleotides and scores the interaction between the segments and the RBPs. RBPsuite further detects the verified motifs on the binding segments gives the binding scores distribution along the full-length sequence.ConclusionsRBPsuite is an easy-to-use online webserver for predicting RBP binding sites and freely available athttp://www.csbio.sjtu.edu.cn/bioinf/RBPsuite/.

This study examines how fear appeals (moderate vs. high) and temporal frames (proximal vs. distal) interactively influenced consumers' attitude and purchase intention in the framework of eco-friendly clothing advertising in China. For that purpose, empirical analyses were performed by collecting data from 640 consumers across Mainland China. Results revealed that consumers who perceived eco-friendly clothing as highly relevant to themselves expressed more favorable attitude toward the advertising that employed moderate-level fear appeals than the advertising that employed high-level fear appeals. As for consumers with a low level of perceived personal relevance, they showed the most favorable attitude toward the brand when being exposed to high-level fear appeals with a distal frame, and the least favorable attitude toward the brand when being exposed to moderate-level fear appeals with a distal frame. These research results provide significant theoretical and practical implications for scholars and eco-friendly marketing professionals.

Purpose Glucocorticoids are a mainstay to control postoperative pain, inflammation, nausea and vomiting (PONV) in total knee arthroplasty (TKA). Understanding the optimal dose and route of glucocorticoids administration in TKA is of great significance in speedy functional recovery. We aimed to summarize, evaluate and rank order the efficacy of glucocorticoids regimens in TKA. Methods Electronic databases (PubMed et al.) were systematically searched from inception up to April 30, 2020. The primary outcomes were visual analogue scale (VAS), range of motion (ROM) and knee society score (KSS). C-reactive Protein (CRP) and PONV were also evaluated. Multivariable Bayesian random effects models were used to synthesize and rank the comparative efficacy of glucocorticoids regimens. Results A total of 34 eligible randomized controlled trials with 11 different glucocorticoids regimens were assessed. Overall inconsistency and heterogeneity were acceptable. Multiple medium dose perioperative intravenous injection (IV) ranked first in the analgesia network and a single high doses of preoperative IV ranked first in the inflammation and PONV network. There was no statistically significant increase in ROM or KSS in all the glucocorticoid formulations and doses compared with controls on postoperative day 30. Conclusions Glucocorticoid multiple intravenous injection was preferable to a single intravenous injection (preoperative and postoperative), periarticular injection and intra-articular injection in analgesia. Based on the available evidence, a medium dose of hydrocortisone of 2–4 mg/kg is optimal.

Many studies have found that vitamin D deficiency has a high incidence rate worldwide, but we found few studies on the role of vitamin D in spinal degenerative diseases. We investigated the determinants of preoperative vitamin D deficiency and its effects on postoperative outcomes among patients undergoing elective lumbar spine surgery.360 patients treated from July 2017 to July 2018 were retrospectively identified for inclusion. The patients' fasting serum levels of 25(OH)D, N-terminal midfragment of osteocalcin (N-MID), and β typeⅠcollagen carboxyl terminal peptide (β-CTX) were measured by electrochemiluminescence before the operation. The visual analogue scale (VAS), Japanese Orthopaedic Association (JOA) and Oswestry Disability Index scores (ODI) were used to evaluate the clinical outcomes. Standard demographic data and all perioperative complications occurring within 3 months follow-up after operation were recorded.The mean serum level of 25(OH)D was 20.81 ± 8.55 ng/mL, the rates of deficiency (20 ng/ml) was 53.6%. The abnormal proportion of N-MID and β-CTX were 8.61% and 34.44%, bone turnover markers serum level was higher in older age groups (p 0.05). Female sex (p 0.001), a high body mass index (BMI) (p = 0.012), lack of vitamin D supplementation (p = 0.018), smoking (p = 0.033), moderate (p 0.001) to severe pain (p = 0.005) were significant predictors of vitamin D deficiency after the multivariate analysis. The VAS, JOA and ODI scores showed significantly better outcomes compared to deficient group at post-operative and final follow-up (p 0.05).Vitamin D deficiency was common in patients undergoing elective lumbar spine surgery. Female sex, high BMI, lack of vitamin D supplementation, smoking and moderate to severe pain were risk factors for vitamin D deficiency. Moreover, preoperative hypovitaminosis D (20 ng/ml) was correlated with worse surgical outcomes in short-term.

BACKGROUND Conventional plain X-ray images of rats, the most common animals used as degeneration models, exhibit unclear vertebral structure and blurry intervertebral disc spaces due to their small size, slender vertebral bodies. AIM To apply molybdenum target X-ray photography in the evaluation of caudal intervertebral disc (IVD) degeneration in rat models. METHODS Two types of rat caudal IVD degeneration models (needle-punctured model and endplate-destructed model) were established, and their effectiveness was verified using nuclear magnetic resonance imaging. Molybdenum target inspection and routine plain X-ray were then performed on these models. Additionally, four observers were assigned to measure the intervertebral height of degenerated segments on molybdenum target plain X-ray images and routine plain X-ray images, respectively. The degeneration was evaluated and statistical analysis was subsequently conducted. RESULTS Nine rats in the needle-punctured model and 10 rats in the endplate-destructed model were effective. Compared with routine plain X-ray images, molybdenum target plain X-ray images showed higher clarity, stronger contrast, as well as clearer and more accurate structural development. The McNemar test confirmed that the difference was statistically significant (P = 0.031). In the two models, the reliability of the intervertebral height measured by the four observers on routine plain X-ray images was poor (ICC < 0.4), while the data obtained from the molybdenum target plain X-ray images were more reliable. CONCLUSION Molybdenum target inspection can obtain clearer images and display fine calcification in the imaging evaluation of caudal IVD degeneration in rats, thus ensuring a more accurate evaluation of degeneration.

Purpose This study was aimed to discover the combined effects of single nucleotide polymorphisms (SNPs) within the C-reactive protein (CRP) gene and potential environmental factors on the risk and prognosis for diabetic foot osteomyelitis (DFO). Methods A total of 1734 diabetes mellitus patients, 681 with DFO and 1053 without DFO, were successfully recruited, as well as 1261 healthy control individuals. Participants data were recorded regarding age, gender, smoking and drinking history, body mass index (BMI), hypertension, cacosmia, and ulceration. A total of 11 SNPs within the CRP gene were designated for exploration, by logistic regression analyses, of how they might interact with environmental factors to affect susceptibility to DFO. Results Frequencies of smoking and drinking, and incidence of hypertension, cacosmia, or ulceration displayed marked differences (all PG), allele G of rs1800947 (C>G), and allele T of rs3093059 (T>C) and rs1130864 (C>T) exhibited a trend to increase risk of DFO (all PG), allele G of rs1800947 (C>G) and rs3093068 (G>C), and allele T of rs1130864 (C>T) were significant predictors of poor prognosis among DFO patients (P1). Conclusion Genetic mutations within CRP functioned interactively with external factors to affect DFO risk.

Signal peptides play an important role in guiding and transferring transmembrane proteins and secreted proteins. In recent years, with the explosive growth of protein sequences, computationally predicting signal peptides and their cleavage sites from protein sequences is highly desired. In this work, we present an improved approach, Signal-3L 3.0, for signal peptide recognition and cleavage-site prediction using a 3-layer hybrid method of integrating deep learning algorithms and window-based scoring. There are three main components in the Signal-3L 3.0 prediction engine: (1) a deep bidirectional long short-term memory (Bi-LSTM) network with a soft self-attention learns abstract features from sequences to determine whether a query protein contains a signal peptide; (2) the statistics propensity window-based cleavage site screening method is applied to generate the set of candidate cleavage sites; (3) the prediction of a conditional random field with a hybrid convolutional neural network (CNN) and Bi-LSTM is fused with the window-based score for identifying the final unique cleavage site. Experimental results on the benchmark datasets show that the new deep learning-driven Signal-3L 3.0 yields promising performance. The online server of Signal-3L 3.0 is available at http://www.csbio.sjtu.edu.cn/bioinf/Signal-3L/.

Sustainability is crucially important in the textiles and apparel (TA) supply chains. In this paper, we evaluate the impact of clean technology adoption and environmental taxes on the TA supply chains. First, we consider a monopoly case, where a two-echelon supply chain consists of one buyer and one manufacturer. We find that raising the environmental tax rate motivates the manufacturer to invest in green technologies. We then extend our model to examine the duopoly case. We find that in the duopoly case, if the buyer's market share is sufficiently small (large), the optimal greenness level for this buyer's product decreases (increases) in the environmental tax rate; whereas if the two products market shares are relatively equal, the optimal greenness levels for both products buyers increase in the environmental tax rate. The existence of the spillover effect reduces the cost and improves the product greenness. Consumer welfare can be improved if the efficiency of green technology adoption and the coefficient of greenness level on market demand are sufficiently high. This result implies that if the government cares about consumers, the manufacturer should be encouraged to enhance the cost reduction ability in terms of green technology, and consumer education about sustainability consciousness should be enhanced.

In a networked discrete event system, communication between a plant and a supervisor/agent is carried out via a wired/wireless communication network, in which communication delays are unavoidable. Hence, how to obtain state estimates under communication delays is an important problem. The existing methods assume that there is only one communication channel and, thus, the first-in, first-out (FIFO) property is satisfied. In complex systems distributed over several locations, several channels are often used to send the event occurrences to the (central) supervisor/agent, in which the FIFO property holds only for each channel and communication delays may be different for different channels. To address these new challenges, this paper investigates the state estimation problem in multichannel networked discrete event systems. Two methods are proposed. The first method is relatively simpler and computes only conservative estimates. The second method is more complex, but it computes the exact state estimates. Examples are given to illustrate the results.

IEEE journal of selected topics in quantum electronics 28(1), 1501710 (2022). doi:10.1109/JSTQE.2021.3117586, Published by IEEE, New York, NY

Rationale It remains unknown whether long-term ozone exposure can impair lung function. Objectives To investigate the associations between long-term ozone exposure and adult lung function in China. Methods Lung function results and diagnosis of small airways dysfunction (SAD) were collected from a cross-sectional study, China Pulmonary Health Study (N=50,991). We used multivariate linear and logistic regression models to examine the associations of long-term ozone exposure with lung function parameters and SAD, respectively, adjusting for demographic characteristics, individual risk factors, and longitudinal trend. We then performed a stratification analysis by chronic obstructive pulmonary disease (COPD). Measurements and main results We observed each 1-standard deviation (SD, 4.9 ppb) increase in warm-season ozone concentrations was associated with a 14.2 mL/s [95% confidence interval (CI): 8.8, 19.6] decrease in forced expiratory flow at 75th percentile of vital capacity and a 29.5 mL/s (95% CI: 19.6, 39.5) decrease in mean forced expiratory flow between the 25th and 75th percentile of vital capacity. The odds ratio of SAD was 1.09 (95% CI: 1.06, 1.11) for a 1-SD increase in warm-season ozone concentrations. Meanwhile, we observed a significant association with a decreased ratio of expiratory volume in 1 second to forced vital capacity (FEV1/FVC) but not with FEV1 or FVC. The association estimates were greater in the COPD group than in the non-COPD group. Conclusion We found independent associations of long-term ozone exposure with impaired small airways function and higher SAD risks, while the associations with airflow obstruction were weak. COPD patients appear to be more vulnerable.

Bisphosphonate has great potential in KOA therapy, but whether the anti-resorption mechanism of bisphosphonate aggravates sclerosis of subchondral bone remains unclear. We found that bisphosphonate use did not increase sclerosis of subchondral bone in established KOA, perhaps resolving some concerns about bisphosphonate in patients with KOA.Introduction: Most studies have focused on the protective effect of bisphosphonate on early knee osteoarthritis (KOA) through its anti-resorption mechanism in osteoclasts. However, late KOA has a decreased rate of resorption, which is the opposite of early KOA. The risk of subchondral bone sclerosis in late KOA after using bisphosphonate has not been investigated using morphometry.Methods: Forty-five patients who had ever used bisphosphonate (or 33 patients with current use) were matched with controls through propensity matching methods, including age, body mass index (BMI), sex, health status (12-Item Short Form Survey physical health score), physical activity level (Physical Activity Scale for the Elderly score), vitamin D use, and calcium use. At the baseline and 12-month (or 18-month) follow-up, bone mineral density (BMD) of the tibia and hip was measured by dual-energy X-ray absorptiometry (DXA), and medial tibial subchondral bone morphometry: bone volume fraction (BV/TV), trabecular thickness (Tb.Th), trabecular number (Tb.N), and trabecular separation (Tb.Sp) were calculated based on 3-T trabecular MRI. Data were obtained from the Bone Ancillary Study in the Osteoarthritis Initiative (OAI) project.Results: The yearly percentage change in hip BMD of the current bisphosphonate-use group was significantly greater than that of the non-bisphosphonate-use group (0.7% vs. −1%, P = 0.02). The other outcomes (BV/TV, Tb.N, Tb.Sp, Tb.Th, tibia medial BMD, and tibia lateral BMD) between the two groups presented no significant difference. The non-bisphosphonate-use group experienced a significant increase in Tb.Th [2%, 95% CI = (1%, 4%), P = 0.01], while the bisphosphonate-use group presented no significant change [1%, 95% CI = (−2%, 4%), P = 0.54].Conclusions: Bisphosphonate use did not increase sclerosis of subchondral bone in established KOA. Bisphosphonate might have a stage-dependent effect on subchondral bone in KOA initiation and progression.

Introduction: Chronic pelvic pain is a highly prevalent pain condition among women, but identifying the exact cause of pelvic pain remains a significant diagnostic challenge. In this study, we explored a new diagnostic approach with PET/MRI of the sigma-1 receptor, a chaperone protein modulating ion channels for activating nociceptive processes.Methods: Our approach is implemented by a simultaneous PET/MRI scan with a novel radioligand [18F]FTC-146, which is highly specific to the sigma-1 receptor. We recruited 5 chronic pelvic pain patients and 5 healthy volunteers and compared our PET/MRI findings between these two groups.Results: All five patients showed abnormally increased radioligand uptake on PET compared to healthy controls at various organs, including the uterus, vagina, pelvic bowel, gluteus maximus muscle, and liver. However, on MRI, only 2 patients showed abnormalities that could be potentially associated with the pain symptoms. For a subset of patients, the association of pain and the abnormally increased radioligand uptake was further validated by successful pain relief outcomes following surgery or trigger point injections to the identified abnormalities.Conclusion: In this preliminary study, sigma-1 receptor PET/MRI demonstrated potential for identifying abnormalities associated with chronic pelvic pain. Future studies will need to correlate samples with imaging findings to further validate the correlation between S1R distribution and pathologies of chronic pelvic pain.Trial Registration: The clinical trial registration date is June 2, 2018, and the registration number of the study is NCT03195270 (https://clinicaltrials.gov/ct2/show/NCT03556137).

Objective To verify whether an elevated preoperative international normalized ratio (INR) increases transfusion and complications independently in primary total hip arthroplasty (THA) with the management of an enhanced recovery after surgery (EARS) protocol. Methods We retrospectively reviewed the database of adults who underwent primary THA between 2014 and 2018 by the same surgeon. A total of 552 patients were assigned into three groups by preoperative INR class: INR ≤ 0.9, 0.9 0.05). Conclusions Elevated preoperative INR cannot increase transfusion or complication rates independently in primary THA with the management of the ERAS protocol. With the improvement in the ERAS protocol and the use of tranexamic acid (TXA), an INR, Elevated preoperative INR cannot increase transfusion or complication rates independently in primary THA with the management of the ERAS protocol. With the improvement in the ERAS protocol and the use of tranexamic acid (TXA), an INR

Background Current evidence does not recommend screening urine culture and curing asymptomatic bacteriuria (ASB) before joint arthroplasty. The bacteriuria count on pre-operative urinalysis is a more common clinical parameter. We aimed to investigate whether the bacteriuria count on preoperative urinalysis can increase postoperative wound complications in primary total hip arthroplasty (THA). Methods We conducted a retrospective study that included patients who underwent primary THA in our institution from 2012 to 2018. We obtained preoperative urinalysis results before THA during the same hospitalization and identified patients with abnormal urinalysis. Receiver operating characteristic (ROC) curves were first generated to evaluate the predicted value of leukocyte esterase (LE), nitrite, bacteriuria, and pyuria in the urinalysis for superficial wound infection. Then, all included patients were divided into two groups according to the preoperative urinalysis: a bacteriuria-positive group and a bacteriuria-negative group. The primary outcome was the superficial wound infection rate within 3 months postoperatively, and the secondary outcomes included wound leakage, prosthetic joint infection (PJI), pulmonary infection, urinary tract infection (UTI), readmission rate within 3 months postoperatively, and length of stay (LOS) during hospitalization. We utilized univariable analyses to compare the outcomes between the two groups. A multivariable logistic regression model was generated to explore the potential association between bacteriuria and the risk of superficial wound infection, wound leakage, and readmission rate controlling for baseline values. Results A total of 963 patients were included in the study. One hundred sixty patients had abnormal urinalysis. The AUCs for LE, nitrite, bacteriuria, and pyuria were 0.507 (95% confidence interval (CI), 0.315 to 0.698), 0.551 (0.347 to 0.756), 0.675 (0.467 to 0.882), and 0.529 (0.331 to 0.728), respectively. Bacteriuria was diagnostically superior to LE, nitrite, and pyuria. Among the 963 patients, 95 had a positive bacteriuria on preoperative urinalysis, and only 9 (9.5%) had a positive urine culture. Compared with the bacteriuria-negative group, the bacteriuria-positive group had a higher superficial wound infection rate (4.2% vs. 0.6%, P = 0.008), higher wound leakage rate (11.6% vs. 4.5%, P = 0.007), higher readmission rate (5.3% vs. 1.3%, P = 0.015) within 3 months postoperatively and longer LOS (6.19 ± 2.89 days vs. 5.58 ± 2.14 days, P = 0.011). After adjustment, the bacteriuria-positive group had a significantly increased risk of superficial wound infection (OR = 7.587, 95%CI: 2.002 to 28.755, P = 0.003), wound leakage (OR = 3.044, 95%CI: 1.461 to 6.342, P = 0.003), and readmission (OR = 4.410, 95%CI: 1.485 to 13.097, P = 0.008). Conclusion Preoperative bacteriuria positivity on urinalysis significantly increased the risk of postoperative wound complications, readmission, and LOS in primary THA regardless of the result of the urine culture. Urinalysis is a fast and cost-acceptable test whose advantages have been underestimated. Level of evidence Level III, observational study.

Background: Whole-body plethysmography (WBP) is the gold standard for measuring lung volume, but its clinical application is limited as it requires expensive equipment and is not simple to use. Studies have shown that the single-breath helium dilution (SBHD) method, which is commonly used in clinical practice, significantly underestimates lung volume in patients with obstructive lung disease (OLD). By comparing the differences in lung volume measured using SBHD and WBP, we aimed to establish a correction equation for the SBHD method to determine the total lung volume in patients with OLD of different severities.Methods: From 628 patients with OLD simultaneously subjected to SBHD and WBP, 407 patients enrolled between January 2018 and November 2019 were in the training group and 221 enrolled between December 2019 and December 2020 were in the prospective verification cohort. The multiple linear regression equation was used for data in the training group to establish a correction equation for SBHD to determine the total lung volume, and this was validated in the prospective validation cohort.Results: There was a moderate positive correlation between total lung capacity (TLC) determined using the SBHD [TLC (SBHD)] and WBP methods [TLC (WBP)] (r = 0.701; P < 0.05), and the differences between TLC (SBHD) and TLC (WBP) (ΔTLC) were related to the severity of obstruction. As the severity of obstruction increased, the TLC was underestimated by the SBHD method. We established the following correction equation: TLC (adjusted SBHD) (L) = −0.669 + 0.756*TLC(SBHD)(L) – 0.047*FEV1FVC+0.039*height (cm)–0.009*weight(kg)(r2 = 0.753 and adjusted r2 = 0.751). Next, we validated this equation in the validation cohort. With the correction equation, no statistical difference was observed between TLC (adjusted SBHD) and TLC (WBP) among the obstruction degree groups (P > 0.05).Conclusions: The SBHD method is correlated with WBP to measure the total lung volume, but the SBHD method presents limitations in determining the total lung volume in patients with obstructive lung disease. Here, we established an effective and reliable correction equation in order to accurately assess the total lung volume of patients with OLD using the SBHD method.

In order to improve the driver’s physiological and psychological state, the driver’s mental load which is caused by sight distance, lighting, and other factors in the tunnel environment should be quantified via modeling the spatiotemporal data. The experimental schemes have been scientifically designed based on methods of traffic engineering and human factor engineering, which aims to test the driver’s spatiotemporal data of eye movement and ECG (electrocardiogram) index in the tunnel environment. Firstly, the changes in the driver’s spatiotemporal data are analyzed to judge the changing trend of the driver’s workload in the tunnel environment. The results show that the cubic spline interpolation function model can fit the dynamic changes of average pupil diameter and heart rate (HR) growth rate well, and the goodness of fit for the model group is above 0.95. So, tunnel environment makes the driver’s typical physiological indicators fluctuate in the coordinates of time and space, which can be modeled and quantified. Secondly, in order to analyze the classification of tunnel risk level, a fusion model has been built based on the functions of average pupil diameter and HR growth rate. The tunnel environmental risk level has been divided into four levels via the fusion model, which can provide a guidance for the classification of tunnel risk level. Furthermore, the fusion model allows tunnel design and construction personnel to adopt different safety design measures for different risk levels, and this method can effectively improve the economy of tunnel operating safety design.

Transmembrane proteins (TMPs) play important roles in many biological processes, such as cell recognition and communication. Their structures are crucial for revealing complex functions but are hard to obtain. A variety of computational algorithms have been proposed to fill the gap by predicting structures from primary sequences. In this study, we mainly focus on α-helical TMP and develop a multiscale deep learning pipeline, MemBrain 3.0, to improve topology prediction. This new protocol includes two submodules. The first module is transmembrane helix (TMH) prediction, which features the capability of accurately predicting TMH with the tail part through the incorporation of tail modeling. The prediction engine contains a multiscale deep learning model and a dynamic threshold strategy. The deep learning model is comprised of a small-scale residue-based residual neural network and a large-scale entire-sequence-based residual neural network. Dynamic threshold strategy is designed to binarize the raw prediction scores and solve the under-split problem. The second module is orientation prediction, which consists of a support vector machine (SVM) classifier and a new Max-Min assignment (MMA) strategy. One typical merit of MemBrain 3.0 is the decision mode composed of the dynamic threshold strategy and the MMA strategy, which makes it more effective for hard TMHs, such as half-TMH, back-to-back TMH, and long-TMH. Systematic experiments have demonstrated the efficacy of the new model, which is available at: www.csbio.sjtu.edu.cn/bioinf/MemBrain/.

For the past decade, cryogenic electron microscopy (cryo-EM) has become an important technology to determine three-dimensional (3D) structures of biomacromolecules. Many software tools have been developed for cryo-EM image processing and 3D reconstruction, covering various computational tasks in cryo-EM data analysis. Despite the recent progress, most of these software tools focus on a single task, such as automatic particle picking or image clustering, whereas software packages covering the whole pipeline of cryo-EM data processing are still few. In this study, we developed a fully automatic single-particle reconstruction and analysis toolkit for cryo-EM data, named SPREAD, which integrates 2D image classification, 3D initial model generation, model selection, and 3D refinement. In SPREAD, we adopt our previously proposed network-based clustering algorithm for 2D image classification, NCEM, and the reference-free resolution measurement method SRes to realize the automatic model ranking and selection procedure. Projection orientation assignment is one of the key steps in initial model generation and 3D refinement. In SPREAD, we use the network-based image similarity metric and introduce a new probabilistic-based orientation searching method, named peak finding, to enhance assignment of the projection orientations. For dealing with both the particle images and projection images in the 3D refinement using SPREAD, we build a mixture image network containing both of these types of images on the basis of the peak-finding results, and then similarities for node pairs are recomputed by a superposed random walk on the network. SPREAD achieves a fully automatic workflow in which nearly no expert domain knowledge and interactive manual operation are involved. Our software can accessed for free at http://www.csbio.sjtu.edu.cn/bioinf/SPREAD/ for academic use.

To assess the safety, biodistribution, and radiation dosimetry of the novel positron emission tomography (PET) radiopharmaceutical 1-((2-fluoro-6-[[18F]]fluorophenyl)sulfonyl)-4-((4-methoxyphenyl)sulfonyl)piperazine ([18F]DASA-23) in healthy volunteers. We recruited 5 healthy volunteers who provided a written informed consent. Volunteers were injected with 295.0 ± 8.2 MBq of [18F]DASA-23 intravenously. Immediately following injection, a dynamic scan of the brain was acquired for 15 min. This was followed by serial whole-body PET/MRI scans acquired up to 3 h post-injection. Blood samples were collected at regular intervals, and vital signs monitored pre- and post-radiotracer administration. Regions of interest were drawn around multiple organs, time-activity curves were calculated, and organ uptake and dosimetry were estimated with OLINDA/EXM (version 1.1) software. All subjects tolerated the PET/MRI examination, without adverse reactions to [18F]DASA-23. [18F]DASA-23 passively crossed the blood-brain barrier, followed by rapid clearance from the brain. High accumulation of [18F]DASA-23 was noted in organs such as the gallbladder, liver, small intestine, and urinary bladder, suggesting hepatobiliary and urinary clearance. The effective dose of [18F]DASA-23 was 23.5 ± 5.8 μSv/MBq. We successfully completed a pilot first-in-human study of [18F]DASA-23. Our results indicate that [18F]DASA-23 can be used safely in humans to evaluate pyruvate kinase M2 levels. Ongoing studies are evaluating the ability of [18F]DASA-23 to visualize intracranial malignancies, NCT03539731. ClinicalTrials.gov , NCT03539731 (registered 28 May 2018)

The efficacy of partial retention of well-fixed components during two-stage exchange for chronic total hip arthroplasty (THA) infection has remained unknown. A total of 14 patients with chronic infected THA were treated with damage control two-stage revision, including selective retention of the well-fixed femoral or acetabular component, aggressive debridement, antibiotic-laden cement spacer, antibiotic therapy, and delayed reimplantation. Indications for this treatment included chronic infected THAs with ingrown femoral or acetabular component and positive microbial growth with sensitive antibiotics. We excluded patients with acute infection; negative microbial growth; positive pathogen with high-virulence bacterial infections and multiple drug-resistant bacteria such as methicillin-resistant Staphylococcus aureus, fungi, and Mycobacterium tuberculosis; sinus formation; a prior failure for periprosthetic joint infection (PJI) treatment; and obvious bone resorption in both femoral and acetabulum side. During the study period, this represented 3.3% (14/425) of the patients treated for infected THA. Minimum follow-up was three years. None of the 14 patients in this series were lost to follow-up. Successful treatment was defined according to a modified Delphi-based international multidisciplinary consensus. No repeated debridement and recurrence of infection occurred during the study period; no patient need chronic antibiotic suppression. Successful treatment of chronic PJI was achieved in all patients. Despite the high peri-operative complication rate, no severe consequences were observed. The mean Harris Hip Score was 86 (range, 82–92; SD, 3.3). The selective partial implant retention two-stage revision for chronic PJI may be a treatment option in properly selected patients with low virulence bugs.

On June 30th of 2019, China Association for Science and Technology announced the list of twenty questions that are considered either of guiding importance for frontiers of sciences or playing crucial roles in technological and industrial innovation. Among which the question 4 is “materials electrochemistry for high energy density power batteries”. This article is an interpretation of this question, including a basic overview of the current technology, industry and market of lithium ion battery for powering electric vehicles, the trends of future development, and where the scientific problems are. Along with the rapid economic development in the last a few decades, the vehicle market in China has grown dramatically in recent years. The total number of vehicles in China is already exceeding 0.2 billion, which makes twenty percent of the total number in the world. And this number keeps increasing at a fast pace since the number of vehicle per capital in China is still much lower than those of developed countries (the average number of vehicles per thousand person at year 2016: China-140, USA-797, Japan-591, Korea-376). The huge number of vehicles in China consume a large amount of fuel oil (about 50% of the total fuel oil consumption of China every year are attributed to vehicles), which is prepared from petroleum, a scarce resource in China. Fossil fuel consumption also causes severe air pollution that threatens people’s health and results in global environmental concerns considering the consequences arising from the excessive emission of Greenhouse Gases such as CO2. Development of electric vehicles (EVs) to replace fossil fuel consuming vehicles is a promising solution to tackle the fossil energy exhaustion, global warming, and environment pollution problems, realizing a low-carbon society, and is also an opportunity for China to develop the automobile industry. However, the energy density of the current power batteries used in the EVs is still much lower than that of the fossil energy, which causes the so-called “range anxiety” in EV drivers, hindering the mass-market penetration of EVs. Therefore, overcoming the “range anxiety” by developing higher energy density power batteries is a critical technological challenge for innovative revolution of the vehicle market. Usually, driving ranges of at least 500 km are required for EVs to achieve wide customer acceptance. However, the state-of-the-art lithium-ion battery, which has the highest energy density among all mass-produced rechargeable battery systems, barely meets this requirement when battery safety and cycle lifetime are also concerned. Since the energy density of rechargeable batteries is in principle determined by the active anode and cathode materials, the development of new materials chemistry and electrochemistry is the central scientific task for the popularization of EVs. A survey of currently or potentially available active materials is thus helpful in making a technologically sound forecast of battery energy density as well as in setting up EV development roadmap. In this paper, we briefly go through the materials electrochemistry for current and future active materials for lithium ion batteries and lithium metal batteries, thus including both intercalation and conversion reaction mechanisms, and assess the potential of these active materials in the coming decade to achieve energy density as high as 300 Wh/kg or even higher. The scientific questions and technological challenges that need to be addressed to achieve the goal are analyzed and emphasized. We hope this article will help the readers to unravel the complex power battery market, and potentially inspire researchers in the field to solve the “materials electrochemistry for high energy density power batteries” problem.

Hydrogen is considered to be a hazardous substance. Hydrogen sensors can be used to detect the concentration of hydrogen and provide an ideal monitoring means for the safe use of hydrogen energy. Hydrogen sensors need to be highly reliable, so fault identification and diagnosis for gas sensors are of vital practical significance. However, traditional machine learning methods for fault diagnosis are based on features extracted by experts, prior knowledge requirements and the sensitivity of system changes. In this study, a new convolutional neural network (CNN) using the random forest (RF) classifier is proposed for hydrogen sensor fault diagnosis. First, the 1-D time-domain data of fault signals are converted into 2-D gray matrix images; this process does not require noise suppression and no signal information is lost. Secondly, the features of the gray matrix images are automatically extracted by using a CNN, which does not rely on expert experience. Dropout and zero-padding are used to optimize the structure of the CNN and reduce overfitting. Random forest, which is robust and has strong generalization ability, is introduced for the classification of gas sensor signal modes, in order to obtain the final diagnostic results. Finally, we design and implement a prototype hydrogen sensor array for experimental verification. The accuracy of fault diagnosis in hydrogen sensors is 100% under noisy environment with the proposed method, which is superior of CNN without RF and other methods. The results show that the proposed CNN with RF method provides a good solution for hydrogen sensor fault diagnosis.

Objectives. To investigate the relationship between external knee adduction moment (KAM) and knee osteoarthritis (OA) symptoms according to static alignment and pelvic drop. Methods. Ninety-five participants with symptomatic knee OA were included. Radiographic severity was graded by Kellgren and Lawrence (KL) scale. The hip-knee-ankle (HKA) angle was used to assess limb alignment from a full-length lower-limb radiograph. KAM-related variables (peak KAM and KAM impulse) and pelvic drop angle were determined from 3D gait analysis. Symptoms were assessed via visual analog scale (VAS) for pain and hospital for special surgery (HSS) score for physical function. The relationship between KAM and symptoms was evaluated according to radiographic severity and pelvic drop using linear models. Results. According to the more affected knee in the varus group, both the two KAM-related measures (peak KAM and KAM impulse) were positively associated with greater VAS pain and were negatively associated with HSS score. Only peak KAM was correlated with VAS and HSS in the valgus group. VAS pain score of the more affected knee was positively correlated with pelvic drop angle. Stratified by pelvic drop angle, KAM-related variables were more positively associated with VAS pain and negatively associated with HSS score for patients with pelvic drop angle ≤3 degrees. The relationships between KAM and symptoms according to radiographic disease severity remained confusing. Conclusions. Static alignment and pelvic drop angle significantly affected relationships between KAM-related variables and knee OA symptoms, which may explain the confusing results as shown by previous studies.