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Objective To identify novel candidate genes whose expression is associated with bone mineral density (BMD) and body lean mass (LM) in children. Methods A tissue-specific transcriptome-wide association study (TWAS) was conducted utilizing a large-scale genome-wide association study (GWAS) dataset associated with BMD and LM and involving 10,414 participants. The measurement of BMD and LM phenotypes was made based on total-body dual-energy X-ray absorptiometry (TB-DXA) scans. TWAS was conducted by using FUSION software. Reference panels for muscle skeleton (MS), peripheral blood (NBL) and whole blood (YBL) were used for TWAS analysis. Functional enrichment and protein–protein interaction (PPI) analyses of the genes identified by TWAS were performed by using the online tool Metascape (http://metascape.org). Results For BMD, we identified 174 genes with P P = 1.46 × 10−9) and CHKB (P = 8.31 × 10−7). For LM, we identified 208 genes with P P = 3.03 × 10−12) and MRPS33 (P = 5.45 × 10−10). Gene ontology (GO) enrichment analysis of the BMD-associated genes revealed 200 GO terms, such as protein catabolic process (Log P = −5.09) and steroid hormone-mediated signaling pathway (Log P = −3.13). GO enrichment analysis of the LM-associated genes detected 287 GO terms, such as the apoptotic signaling pathway (Log P = −8.08) and lipid storage (Log P = −3.55). Conclusion This study identified several candidate genes for BMD and LM in children, providing novel clues to the genetic mechanisms underlying the development of childhood BMD and LM.

Although hepatitis B virus (HBV) infection remains the main cause of hepatocellular carcinoma (HCC) worldwide, metabolic syndrome, with its increase in prevalence, has become an important and significant risk factor for HCC. This study was designed to investigate the association of concurrent metabolic syndrome with long-term prognosis following liver resection for patients with HBV-related HCC.From a Chinese, multicenter database, HBV-infected patients who underwent curative resection for HCC between 2010 and 2020 were identified. Long-term oncological prognosis, including overall survival (OS), recurrence-free survival (RFS), and early (≤2 years of surgery) and late (2 years) recurrences were compared between patients with versus those without concurrent metabolic syndrome.Of 1753 patients, 163 (9.3%) patients had concurrent metabolic syndrome. Compared with patients without metabolic syndrome, patients with metabolic syndrome had poorer 5-year OS (47.5% vs. 61.0%; P = 0.010) and RFS (28.3% vs. 44.2%; P = 0.003) rates and a higher 5-year overall recurrence rate (67.3% vs. 53.3%; P = 0.024). Multivariate analysis revealed that concurrent metabolic syndrome was independently associated with poorer OS (hazard ratio: 1.300; 95% confidence interval: 1.018-1.660; P = 0.036) and RFS (1.314; 1.062-1.627; P = 0.012) rates, and increased rates of late recurrence (hazard ratio: 1.470; 95% confidence interval: 1.004-2.151; P = 0.047).In HBV-infected patients with HCC, concurrent metabolic syndrome was associated with poorer postoperative long-term oncologic survival outcomes. These results suggested that patients with metabolic syndrome should undergo enhanced surveillance for tumor recurrence even after 2 years of surgery to early detect late HCC recurrence. Whether improving metabolic syndrome can reduce postoperative recurrence of HCC deserves further exploration.

The identification of patients at high risk of developing postoperative complications is important to improve surgical safety. We sought to develop an individualized tool to predict post-hepatectomy major complications in hepatitis B virus (HBV)-infected patients with hepatocellular carcinoma (HCC).A multicenter database of patients undergoing hepatectomy for HCC were analyzed; 2/3 and 1/3 of patients were assigned to the training and validation cohorts, respectively. Independent risks of postoperative 30-day major complications (Clavien-Dindo grades III-V) were identified and used to construct a web-based prediction model, which predictive accuracy was assessed using C-index and calibration curves, which was further validated by the validation cohort and compared with conventional scores.Among 2762 patients, 391 (14.2%) developed major complications after hepatectomy. Diabetes mellitus, concurrent hepatitis C virus infection, HCC beyond the Milan criteria, cirrhosis, preoperative HBV-DNA level, albumin-bilirubin (ALBI), and aspartate transaminase to platelet ratio index (APRI) were identified as independent predictors of developing major complications, which were used to construct the online calculator ( http://www.asapcalculate.top/Cal11_en.html ). This model demonstrated good calibration and discrimination, with the C-indexes of 0.752 and 0.743 in the training and validation cohorts, respectively, which were significantly higher than those conventional scores (the training and validation cohorts: 0.565 ~ 0.650 and 0.568 ~ 0.614, all P 0.001).A web-based prediction model was developed to predict the probability of post-hepatectomy major complications in an individual HBV-infected patient with HCC. It can be used easily in the real-world clinical setting to help management-related decision-making and early warning, especially in areas with endemic HBV infection.

Computerized adaptive testing (CAT) targets to accurately assess the student’s proficiency in the required subject/area. The key issue is how to design a question selector that adaptively selects the best-suited questions for each student based on previous performance step by step. Most existing question selectors execute via greedy metric functions (e.g., question information and uncertainty), which can not effectively capture data characteristics. There also exist learning-based question selectors that redefine the CAT problem as a bilevel optimization problem, where the parameter learning of the question selector and the student proficiency estimation model are coupled, which is not flexible enough. To this end, in this paper, we propose a novel CAT framework with Decoupled Learning selector (DL-CAT). Specifically, we first use the currently estimated student ability and question characteristics as input and design a deep learning-based question selector to predict question selection scores. Then, to address the issue that there is no ground truth to measure the quality of the selected question, an approximate ground-truth and a pairwise rank loss function are specially designed to update the parameters of the question selector independently. Extensive experiments on two real datasets demonstrate that our proposed DL-CAT has certain advantages in effectiveness and significant advantages in efficiency.

Understanding the processes governing lateral terrestrial organic carbon transfer is confounded by the fact that organic carbon deposits on land have not yet been fully explored. Despite recent advances in understanding organic carbon deposition in aquatic ecosystems, the burial of organic carbon in dry depositional environments remains unclear. Here, combining large-scale field surveys and remote sensing techniques, we provide a robust estimate for sediment retention and organic carbon burial of check dams on the Chinese Loess Plateau. We find that the 50,226 active check dams have intercepted 10.2 ± 0.6 Pg eroded sediment during 1970-2020, which equals to 46% of the sediment load of Yellow River. Based on 86 deep sediment cores, we estimate that 21.6 ± 9.9 Tg of organic carbon was buried over the past 50 years by check dams with a burial rate of 468 ± 204 g C m−2 yr−1, approximately one order of magnitude higher than that of global lakes/reservoirs. We also find that the organic carbon burial efficiency of check dams (~80%) is significantly higher than in other depositional environments. We argue that organic carbon burial by check dams represents a significant terrestrial carbon sink and must be accounted for in global carbon budget.

A potentially curative hepatic resection is the optimal treatment for hepatocellular carcinoma (HCC), but most HCCs, even at an early stage, eventually recur after resection. This study investigates clinical features of initial recurrence and long-term prognosis of patients with recurrence after curative resection for early-stage HCC.From a multicenter database, patients who underwent curative hepatic resection for early-stage HCC [Barcelona Clinic Liver Cancer (BCLC) stage 0/A] were extracted. Time to initial recurrence, patterns of initial recurrence, and treatment modalities for recurrent tumors were investigated. Univariate and multivariate analysis were used to identify independent risks associated with postoperative recurrence, as well as post-recurrence survival (PRS) for patients with recurrence.Among 1424 patients, 679 (47.7%) developed recurrence at a median follow-up of 54.8 months, including 408 (60.1%) early recurrence (≤ 2 years after surgery) and 271 (39.9%) late recurrence (2 years). Independent risks of postoperative recurrence included cirrhosis, preoperative alpha-fetoprotein level400 ug/L, tumor size5 cm, multiple tumors, satellites, microvascular invasion, and intraoperative blood transfusion. Multivariate analysis revealed that receiving irregular recurrence surveillance, initial tumor beyond Milan criteria, early recurrence, BCLC stage B/C of the recurrent tumor, and noncurative treatments were independently associated with poorer PRS.Nearly half of patients with early-stage HCC experienced recurrence after resection. Understanding recurrence risks may help identify patients at high risk of recurrence who may benefit from future adjuvant therapies. Meaningful survival even after recurrence can still be achieved by postoperative regular surveillance and curative treatment.

Two-dimensional (2D) nonlayered materials have recently provoked a surge of interest due to their abundant species and attractive properties with promising applications in catalysis, nanoelectronics, and spintronics. However, their 2D anisotropic growth still faces considerable challenges and lacks systematic theoretical guidance. Here, we propose a general thermodynamics-triggered competitive growth (TTCG) model providing a multivariate quantitative criterion to predict and guide 2D nonlayered materials growth. Based on this model, we design a universal hydrate-assisted chemical vapor deposition strategy for the controllable synthesis of various 2D nonlayered transition metal oxides. Four unique phases of iron oxides with distinct topological structures have also been selectively grown. More importantly, ultra-thin oxides display high-temperature magnetic ordering and large coercivity. MnxFeyCo3-x-yO4 alloy is also demonstrated to be a promising room-temperature magnetic semiconductor. Our work sheds light on the synthesis of 2D nonlayered materials and promotes their application for room-temperature spintronic devices.

Background Zinc finger and scan domain containing 18 (ZSCAN18) belongs to the zinc finger transcription factor superfamily, which consists of hundreds of members that play critical roles in all steps of tumorigenesis. Methods This study aims to investigate the roles of ZSCAN18 in gastric cancer (GC). The expression level in GC and the clinicopathologic features of ZSCAN18 were detected by immunohistochemistry staining. Methylation of ZSCAN18 promoter in GC tissues and cell lines was analyzed via MassARRAY; the same method was used to detect GC cell lines demethylated by 5-aza-2′-deoxycytidine treatment. The biological function of ZSCAN18 in GC cells was verified by in vitro and in vivo experiments. The downstream molecular mechanism of ZSCAN18 was explored using RNA next-generation sequencing, immunofluorescence and chromatin immunoprecipitation. Results Our work revealed ZSCAN18 expression was markedly reduced in GC tissues compared with adjacent normal tissues as a result of hypermethylation in GC. Likewise, ZSCAN18 expression was significantly reduced in a panel of GC cell lines as a result of the densely methylated ZSCAN18 promoter. Functionally, ZSCAN18 overexpression inhibited the biological progression of GC cells, which was characterized by weaken proliferation, enhanced autophagy and suppressed tumor growth. ZSCAN18 acted as a transcription factor and played an important role in binding to the promoter of tumor protein 53-induced nuclear protein 2 (TP53INP2), and we also confirmed the anti-tumor effect of TP53INP2 in GC. Furthermore, the knockdown of TP53INP2 alleviated the inhibiting effects of ZSCAN18 in GC cells by in vitro and in vivo experiments. Conclusions Collectively, this study unveiled that ZSCAN18 played an anticancer role in GC by promoting autophagy and transcriptional regulation of TP53INP2 and provided a promising target for the diagnosis and treatment of GC.

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

Because of the rise of deep learning and neural networks, algorithms based on deep learning have also been developed and subtly applied in daily life. This paper hoped to use neural network-based face recognition with absolute distance estimation and research done with drones to achieve the target tracking effect through the recognition ability of neural networks. The aerial images were used to identify different people or behaviors through which distances could be calculated to establish the foundation for subsequent research and development. According to our experiments, performing the face recognition model and distance estimation met expected results, and it also had a specific accuracy rate from different angles and distances. In summary, identification and distance estimate had better accuracy within the effective length, and we could expect the speed and convenience of identification to be realized on other devices.

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.

Background Posterior dislocation (PD) is a common complication after total hip arthroplasty (THA), and the Allis maneuver is the most widely used method for reduction. However, this classic maneuver has some disadvantages. The aim of the present study was to investigate whether a modified lateral position (MLP) reduction maneuver provides an easier and safer method for PD reduction than the Allis maneuver. Methods Between August 2019 and September 2021, a series of 88 consecutive PD patients who underwent THA were retrospectively evaluated. The patients were divided into the MLP reduction group and Allis reduction group according to the electronic health medical record. The success rate of closed reduction, Harris hip score (HHS), and radiographic outcomes were determined. Satisfaction scores, doctor safety events and complications were also determined and compared between the groups. The mean follow-up period was 1.66 ± 0.88 years. Results The success rate of reduction in the MLP group was significantly 12.5% higher than that in the Allis group (P = 0.024). Periprosthetic fracture and implant loosening were retrospectively identified in 2 hips and 1 hip, which all occurred in the Allis group. The mean doctor and patient SAPS scores in the MLP group were 84.00 points and 76.97 points, respectively, which were significantly higher than those in the Allis group (72.12, P = 0.008 and 63.28 points, P = 0.001). Four adverse events were reported in the Allis group, compared with 0 in the MLP group. Conclusions For PD after THA, the MLP reduction maneuver can effectively increase the reduction success rate, satisfaction, and doctor safety without increasing the risk of complications compared with the traditional Allis supine reduction maneuver. Trial registration This study was registered in the Chinese Clinical Trial Registry (ChiCTR2100054562) in December 19th 2021.

Background There is a discourse on whether air pollution mixture or air pollutant components are causally linked to increased mortality. In particular, there is uncertainty on whether the association of NO2 with mortality is independent of fine particulate matter (PM2.5). Furthermore, effect modification by temperature on air pollution-related mortality also needs more evidence. Methods We used the Chinese Longitudinal Healthy Longevity Study (CLHLS), a prospective cohort with geographical and socio-economic diversity in China. The participants were enrolled in 2008 or 2009 and followed up in 2011-2012, 2014, and 2017-2018. We used remote sensing and ground monitors to measure nitrogen dioxide (NO2), fine particulate matter (PM2.5) , and temperature. We used the Cox-proportional hazards model to examine the association between component and composite air pollution and all-cause mortality, adjusted for demographic characteristics, lifestyle, geographical attributes, and temperature. We used the restricted cubic spline to visualize the concentration–response curve. Results Our study included 11 835 individuals with an average age of 86.9 (SD: 11.4) at baseline. Over 55 606 person-years of follow-up, we observed 8 216 mortality events. The average NO2 exposure was 19.1 μg/m3 (SD: 14.1); the average PM2.5 exposure was 52.8 μg/m3 (SD: 15.9). In the single pollutant models, the mortality HRs (95% CI) for 10 μg/m3 increase in annual average NO2 or PM2.5 was 1.114 (1.085, 1.143) and 1.244 (1.221, 1.268), respectively. In the multi-pollutant model co-adjusting for NO2 and PM2.5, the HR for NO2 turned insignificant: 0.978 (0.950, 1.008), but HR for PM2.5 was not altered: 1.252 (1.227, 1.279). PM2.5 and higher mortality association was robust, regardless of NO2. When acccounting for particulate matter, NO2 exposure appeared to be harmful in places of colder climates and higher seasonal temperature variation. Conclusions We see a robust relationship of PM2.5 exposure and premature mortality in advance aged individuals, however, NO2 exposure and mortality was only harmful in places of colder climate such as northeast China, indicating evidence of effect modification by temperature. Analysis of NO2 without accounting for its collinearity with PM2.5, may lead to overestimation.

Trichoderma reesei RUT-C30 is a well-known high-yielding cellulase-producing fungal strain that converts lignocellulose into cellulosic sugar for resource regeneration. Calcium is a ubiquitous secondary messenger that regulates growth and cellulase production in T. reesei. We serendipitously found that adding Sr2+ to the medium significantly increased cellulase activity in the T. reesei RUT-C30 strain and upregulated the expression of cellulase-related genes. Further studies showed that Sr2+ supplementation increased the cytosolic calcium concentration and activated the calcium-responsive signal transduction pathway of Ca2+–calcineurin-responsive zinc finger transcription factor 1 (CRZ1). Using the plasma membrane Ca2+ channel blocker, LaCl3, we demonstrated that Sr2+ induces cellulase production via the calcium signaling pathway. Supplementation with the corresponding concentrations of Sr2+ also inhibited colony growth. Sr2+ supplementation led to an increase in intracellular reactive oxygen species (ROS) and upregulated the transcriptional levels of intracellular superoxide dismutase (sod1) and catalase (cat1). We further demonstrated that ROS content was detrimental to cellulase production, which was alleviated by the ROS scavenger N-acetyl cysteine (NAC). This study demonstrated for the first time that Sr2+ supplementation stimulates cellulase production and upregulates cellulase genes via the calcium signaling transduction pathway. Sr2+ leads to an increase in intracellular ROS, which is detrimental to cellulase production and can be alleviated by the ROS scavenger NAC. Our results provide insights into the mechanistic study of cellulase synthesis and the discovery of novel inducers of cellulase. Graphical Abstract

The friction pendulum bearing (FPB) is commonly used as a base isolation system in buildings. The FPB is a passive control method and can protect the structures from a specified dynamic load, but is not suitable to other cases and types of dynamic loading. An innovative distributed tunable friction pendulum system (DTFPS) is proposed and studied. The DTFPS contains multiple bearings, most of which are conventional FPBs, whereas the rest are tunable friction pendulum bearings (TFPBs). The TFPB has a sliding surface with a high friction coefficient and an adjustable pressure system. The oil pressure in the TFPB can be tuned by the adjustable pressure system, thus the friction force in the DTFPS can be changed accordingly. Theoretical analysis and dynamic tests were carried out to study the performance of the DTFPS. Both theoretical and test results show that the friction force in the DTFPS can be tuned online. Numerical simulations were conducted for a base-isolated building equipped with the DTFPS. The H-inf method, which considers different time delays, was adopted to control the friction force of the DTFPS. With 0.02 s of time delay, the DTFPS can reduced the displacement of the isolation layer without significantly increase the floor acceleration and inter-story displacement of superstructure. The control effect of the H-inf control was improved up to 139%, compared with passive control.

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

Osteoarthritis (OA) is a prevalent degenerative joint disease characterized by cartilage loss and accounts for a major source of pain and disability worldwide. However, effective strategies for cartilage repair are lacking, and patients with advanced OA usually need joint replacement. Better comprehending OA pathogenesis may lead to transformative therapeutics. Recently studies have reported that exosomes act as a new means of cell-to-cell communication by delivering multiple bioactive molecules to create a particular microenvironment that tunes cartilage behavior. Specifically, exosome cargos, such as noncoding RNAs (ncRNAs) and proteins, play a crucial role in OA progression by regulating the proliferation, apoptosis, autophagy, and inflammatory response of joint cells, rendering them promising candidates for OA monitoring and treatment. This review systematically summarizes the current insight regarding the biogenesis and function of exosomes and their potential as therapeutic tools targeting cell-to-cell communication in OA, suggesting new realms to improve OA management.

Background Osteoporosis is a common metabolic bone disease that is characterized by low bone mass. However, limited efforts have been made to explore the functional relevance of the blood proteome to bone mineral density across different life stages. Methods Using genome-wide association study summary data of the blood proteome and two independent studies of bone mineral density, we conducted a genetic correlation scan of bone mineral density and the blood proteome. Linkage disequilibrium score regression analysis was conducted to assess genetic correlations between each of the 3283 plasma proteins and bone mineral density. Results Linkage disequilibrium score regression identified 18 plasma proteins showing genetic correlation signals with bone mineral density in the TB-BMD cohort, such as MYOM2 (coefficient = 0.3755, P value = 0.0328) among subjects aged 0 ~ 15, POSTN (coefficient = − 0.5694, P value = 0.0192) among subjects aged 30 ~ 45 and PARK7 (coefficient = − 0.3613, P value = 0.0052) among subjects aged over 60. Conclusions Our results identified multiple plasma proteins associated with bone mineral density and provided novel clues for revealing the functional relevance of plasma proteins to bone mineral density.

Bioorthogonal catalysis mediated by transition metals has inspired a new subfield of artificial chemistry complementary to enzymatic reactions, enabling the selective labelling of biomolecules or in situ synthesis of bioactive agents via non-natural processes. However, the effective deployment of bioorthogonal catalysis in vivo remains challenging, mired by the safety concerns of metal toxicity or complicated procedures to administer catalysts. Here, we describe a bioorthogonal catalytic device comprising a microneedle array patch integrated with Pd nanoparticles deposited on TiO2 nanosheets. This device is robust and removable, and can mediate the local conversion of caged substrates into their active states in high-level living systems. In particular, we show that such a patch can promote the activation of a prodrug at subcutaneous tumour sites, restoring its parent drug's therapeutic anticancer properties. This in situ applied device potentiates local treatment efficacy and eliminates off-target prodrug activation and dose-dependent side effects in healthy organs or distant tissues.

Developing low-energy input route for conversion of methane (CH4) to value-added methanol (CH3OH) at room temperature is important in environment and industry. Bonding in electron donor-acceptor hybrid can potentially promote charge transfer and photocatalytic efficiency of CH4 conversion. Herein, bonding in electron donor rhodamine B (RhB)-acceptor (TiO2) hybrid (RhB/TiO2) significantly promotes the selectivity of photocatalytic oxidation of CH4 to CH3OH and utilization of visible light (low-energy photons) at ambient condition. Even under green light irradiation (λ = 550 nm), the noble-metal-free RhB/TiO2 hybrid synthesized presents enhanced oxidation of CH4 to CH3OH with a generation rate of 143 µmol·g−1·h−1 and selectivity of 94%. This work demonstrates the possibility and feasibility of noble-metal-free catalysts for activating CH4 under visible light at room temperature.

Air pollution is a serious environmental problem that has attracted much attention. Air quality prediction can provide useful information for urban environmental governance decision-making and residents’ daily health control. However, existing research methods have suffered from a weak ability to capture the spatial correlations and fail to model the long-term temporal dependencies of air quality. To overcome these limitations, we propose a multi-scale spatiotemporal graph convolution network (MST-GCN), which consists of a multi-scale block, several spatial-temporal blocks and a fusion block. We first divide the extracted features into several groups based on their domain categories, and represent the spatial correlations across stations as two graphs. Then we combine the grouped features and the constructed graphs in pairs to form a multi-scale block that feeds into spatial-temporal blocks. Each spatial-temporal block contains a graph convolution layer and a temporal convolution layer, which can model the spatial correlations and long-term temporal dependencies. To capture the group interactions, we use a fusion block to fuse multiple groups. Extensive experiments on a real-world dataset demonstrate that our model achieves the highest performance compared with state-of-the-art and baseline models for air quality prediction.

First-principles spin-polarized density functional theory (DFT) is employed to investigate the effect of two nearest V substitution doping on magnetism of two dimension (2D) monolayer CrSi2. Calculation of formation energy confirms that all V-doped monolayer CrSi2 are thermodynamically stable. A total density of states, near Fermi level, are derived mainly from 3d states of V atom. Additionally, calculated magnitudes of overlap populations and average transfer charge confirm that the chemical bonds are extremely weak covalent bands with strong ionic component. The total magnetic moment of the system reduces with V–V distances in the case of two V atoms doped monolayer CrSi2, indicating that the nearest-neighbor V atoms substitutions doping monolayer CrSi2 might be a promising candidate in future application of spintronics.

Performance regressions of large-scale software systems often lead to both financial and reputational losses. In order to detect performance regressions, performance tests are typically conducted in an in-house (non-production) environment using test suites with predefined workloads. Then, performance analysis is performed to check whether a software version has a performance regression against an earlier version. However, the real workloads in the field are constantly changing, making it unrealistic to resemble the field workloads in predefined test suites. More importantly, performance testing is usually very expensive as it requires extensive resources and lasts for an extended period. In this work, we leverage black-box machine learning models to automatically detect performance regressions in the field operations of large-scale software systems. Practitioners can leverage our approaches to complement or replace resource-demanding performance tests that may not even be realistic in a fast-paced environment. Our approaches use black-box models to capture the relationship between the performance of a software system (e.g., CPU usage) under varying workloads and the runtime activities that are recorded in the readily-available logs. Then, our approaches compare the black-box models derived from the current software version with an earlier version to detect performance regressions between these two versions. We performed empirical experiments on two open-source systems and applied our approaches on a large-scale industrial system. Our results show that such black-box models can effectively and timely detect real performance regressions and injected ones under varying workloads that are unseen when training these models. Our approaches have been adopted in practice to detect performance regressions of a large-scale industry system on a daily basis.

This study proposes a design for a wearable guide device for blind or visually impaired persons on the basis of video streaming and deep learning. This work mainly aims to provide supplementary assistance to white canes used by visually impaired persons and offer them increased freedom of movement and independence using the proposed wearable device. The considerable amount of environmental information provided by the device also ensures enhanced safety for its users. Computer vision in the proposed device uses an RGB camera instead of the RGBD camera commonly used in computer vision. Deep learning is applied to convert RGB images into depth images and calculate the plane for detecting indoor objects and safe walking routes. A convolutional neural network (CNN) is adopted, and its neural network structure, which is similar to that of the human brain, simulates a neural transmission mechanism similar to that triggered in human learning. Therefore, this system can learn a large number of feature routes and then generate a model from the learning result. The proposed system can help blind or visually impaired persons identify flat and safe walking routes.

Improving robots with self-learning ability is one of the critical challenges for the researchers in the area of cognitive robotics and artificial general intelligence. This robot will decide when, where, and what to learn in a continuous visual environment by itself. Here we focus on the procedural knowledge learning, which is sequential and considered harder to understand compared with declarative knowledge in the cognitive system. Inspired by the architecture of the human brain which has integrated well different kinds of cognitive functions, a Brain-inspired Active Learning Architecture (BALA) is proposed for procedural knowledge understanding based on Baxter robot and human interaction. The BALA model contains four main parts: inspired by Primary Visual Pathway, a Convolutional Neural Network (CNN) is constructed for spatial information abstraction; inspired by the Hippocampus Pathway (especially the recurrent loops in CA3 sub-region), a Recurrent Neural Network (RNN) is built for sequential information processing related with procedural knowledge; inspired by the Prefrontal Cortex, a Knowledge Graph based on Bag Of Words (BOW) is constructed for declarative knowledge generation and association; inspired by the Basal Ganglia Pathway, we select Q matrix for Reinforcement Learning (RL). The CNN and RNN parts will be firstly pre-trained on ImageNet dataset and standard Youtube Video-Scene dataset respectively. Then, the RNN, Knowledge Graph, and Q matrix will be dynamically updated in the Baxter robot’s interactive learning procedure with human cooperators. The BALA could actively and incrementally recognize different kinds of procedural knowledge. In 22-type daily-life videos with procedure knowledge (e.g., opening the door, wiping the table, or taking the phone), the BALA model gets the best performance compared with standard CNN, RNN, RL, and other integrative methods. The BALA model is a small step on integrative intelligence interaction between the Baxter robot and human cooperator.

Yttria-stabilized zirconia (YSZ) thermal barrier coatings (TBCs) were prepared by atmospheric plasma spraying (APS). SEM–EBSD–Raman spectroscopy evaluated the relationship between the crystallinity, stresses, and cracks in YSZ coatings. Cracks were more likely to form in locations having poor crystallinity, due to the tensile stresses. Analysis between the formation of cracks and stresses shows that transgranular cracks are more likely created in areas with poor crystallinity. Moreover, intergranular cracks are more likely to occur around columnar grains, because the tensile stresses of columnar grains are greater than those of equiaxed grains. Resultantly, the formation and propagation of cracks can be controlled by controlling the cooling rate and grain shape.

Various types of theoretical algorithms have been proposed for 6D pose estimation, e.g., the point pair method, template matching method, Hough forest method, and deep learning method. However, they are still far from the performance of our natural biological systems, which can undertake 6D pose estimation of multi-objects efficiently, especially with severe occlusion. With the inspiration of the Müller-Lyer illusion in the biological visual system, in this paper, we propose a cognitive template-clustering improved LineMod (CT-LineMod) model. The model uses a 7D cognitive feature vector to replace standard 3D spatial points in the clustering procedure of Patch-LineMod, in which the cognitive distance of different 3D spatial points will be further influenced by the additional 4D information related with direction and magnitude of features in the Müller-Lyer illusion. The 7D vector will be dimensionally reduced into the 3D vector by the gradient-descent method, and then further clustered by K-means to aggregately match templates and automatically eliminate superfluous clusters, which makes the template matching possible on both holistic and part-based scales. The model has been verified on the standard Doumanoglou dataset and demonstrates a state-of-the-art performance, which shows the accuracy and efficiency of the proposed model on cognitive feature distance measurement and template selection on multiple pose estimation under severe occlusion. The powerful feature representation in the biological visual system also includes characteristics of the Müller-Lyer illusion, which, to some extent, will provide guidance towards a biologically plausible algorithm for efficient 6D pose estimation under severe occlusion.

Yttria-stabilized zirconia (YSZ), 15 wt.%Al2O3-doped YSZ (YSZ-15 wt.%Al2O3), and 35 wt.%Al2O3-doped YSZ (YSZ-35 wt.%Al2O3) coatings were prepared by atmospheric plasma spraying. Composition and microstructure of the coatings were characterized. Moreover, the effect of composition and microstructure on the thermal conductivities and thermal expansion coefficients (TECs) of the coatings was investigated. The YSZ-15 wt.%Al2O3 coatings possess much lower thermal conductivity compared to YSZ coating which is attributed to the smaller grains, more oxygen vacancies and the large atomic weight difference between Al and Zr. The mentioned factors improve the phonon scattering thereby reducing the thermal conductivity. The lower TECs of YSZ-15 wt.%Al2O3 coatings are attributed to the smaller lattice parameters due to the substitutional Al3+ doping at Zr4+ sites. The decrease in lattice parameter values increases the crystal lattice energy. And the TEC is inversely proportional to the lattice energy. Moreover, the TEC of the YSZ-35 wt.%Al2O3 coating is much lower than the YSZ coating, which is due to the precipitation of Al2O3 and the formation of amorphous phases. Compared to ZrO2 phase, the Al2O3 phase possesses lower TECs values. The amorphous phase can account for larger expansion tolerance compared to the corresponding crystalline phase due to its loose atomic arrangement.

Martensitic transformation was investigated by the combination of electron backscatter diffraction and in situ atomic force microscope (AFM). The metastable tetragonal phase in the plasma-sprayed 3 mol% Y2O3-ZrO2 coating showed a strong basal texture with the {001}t plane parallel to the surface. The habit plane (108)t of a pair of V-arranged monoclinic variants was determined on the basis of the lattice correspondence of (001)m//(100)t, [100]m//[010]t, and [010]m//[001]t and an included angle of 14°. Additionally, the direction of residual stress in the coatings was revealed by the periodic corrugation patterns of AFM, which matched approximately with 10° deflection of the basal texture. This was further confirmed by an in situ reverse transformation from the monoclinic phase to tetragonal phase and the formation of parallel microcracks after stress release during heat treatment.

Bacterial flagella are perceived by the innate immune systems of plants1 and animals2 alike, triggering resistance. Common to higher plants is the immunoreceptor FLAGELLIN-SENSING 2 (FLS2)3, which detects flagellin via its most conserved epitope, flg22. Agrobacterium tumefaciens, which causes crown gall disease in many crop plants, has a highly diverged flg22 epitope and evades immunodetection by plants so far studied. We asked whether, as a next step in this game of 'hide and seek', there are plant species that have evolved immunoreceptors with specificity for the camouflaged flg22Atum of A. tumefaciens. In the wild grape species Vitis riparia, we discovered FLS2XL, a previously unknown form of FLS2, that provides exquisite sensitivity to typical flg22 and to flg22Atum. As exemplified by ectopic expression in tobacco, FLS2XL can limit crown gall disease caused by A. tumefaciens.