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Summary: This study investigated osteoporosis risk factors among older Asian men with type-2 diabetes mellitus, hypertension, or hyperlipidaemia in primary care. Advanced age, dementia, depression, and polypharmacy were associated with higher risks for osteoporosis. Screening strategies targeting these factors are crucial for improving bone health as part of comprehensive preventive care. Purpose: Asian patients with type-2 diabetes mellitus (T2DM), hypertension, or hyperlipidaemia (DHL) are predominantly managed in primary care. They are also at risk of osteoporosis, but men are often under-screened and under-treated for this preventable bone disorder. This study aimed to identify the clinical characteristics and risk factors of osteoporosis among older men with DHL in primary care for early intervention. Methods: This retrospective study included men aged 65 years and older managed in public primary care clinics for their DHL between 1st July 2017 and 30th June 2018. Demographic, clinical, laboratory, and imaging data were extracted from their electronic medical records based on their International Classification of Diseases-10 (ICD-10) diagnosis codes. Descriptive statistical analyses, with statistical significance set at p < 0.05, were conducted, followed by generalized estimating equation (GEE) modelling. Results: Medical records of 17,644 men (83.1% Chinese, 16.9% minority ethnic groups, median age 71 years) were analysed. 2.3% of them had diagnosis of osteoporosis, 0.15% had fragility fracture, and 26.0% of those diagnosed with osteoporosis were treated with bisphosphonates. Their mean HbA1c was 6.9%; mean systolic and diastolic blood pressure were 133 and 69 mmHg. The GEE model showed that age (OR = 1.07, 95%CI = 1.05–1.09, p < 0.001), dementia (OR = 2.24, 95%CI = 1.33–3.77, p = 0.002), depression (OR = 2.38, 95%CI = 1.03–5.50, p = 0.043), and polypharmacy (OR = 6.85, 95%CI = 3.07–15.26, p < 0.001) were significantly associated with higher risks for osteoporosis. Conclusion: Age, dementia, depression, and polypharmacy are associated with osteoporosis risks in men with DHL. Strategies to incorporate osteoporosis screening among older men with these risk factors are needed to improve their bone health. [ABSTRACT FROM AUTHOR]

Electrosynthesis of adipic acid (a precursor for nylon-66) from KA oil (a mixture of cyclohexanone and cyclohexanol) represents a sustainable strategy to replace conventional method that requires harsh conditions. However, its industrial possibility is greatly restricted by the low current density and competitive oxygen evolution reaction. Herein, we modify nickel layered double hydroxide with vanadium to promote current density and maintain high faradaic efficiency (>80%) within a wide potential window (1.5 ~ 1.9 V vs. reversible hydrogen electrode). Experimental and theoretical studies reveal two key roles of V modification, including accelerating catalyst reconstruction and strengthening cyclohexanone adsorption. As a proof-of-the-concept, we construct a membrane electrode assembly, producing adipic acid with high faradaic efficiency (82%) and productivity (1536 μmol cm−2 h−1) at industrially relevant current density (300 mA cm−2), while achieving >50 hours stability. This work demonstrates an efficient catalyst for adipic acid electrosynthesis with high productivity that shows industrial potential. Here, authors use a membrane electrode assembly is conducted to produce adipic acid with high faradaic efficiency and productivity at an industrially relevant current density, while achieving >50 hours stability. [ABSTRACT FROM AUTHOR]

BACKGROUND: Voltage‐dependent anion‐selective channels (VDACs) serve as pore proteins within the mitochondrial membrane, aiding in the regulation of cell life and cell death. Although the occurrence of cell death is crucial for defense against virus infection, the function played by VDAC in Bombyx mori, in response to the influence of Bombyx mori nucleopolyhedrovirus (BmNPV), remains unclear. RESULTS: BmVDAC was found to be relatively highly expressed both during embryonic development, and in the Malpighian tubule and midgut. Additionally, the expression levels of BmVDAC were found to be different among silkworm strains with varying levels of resistance to BmNPV, strongly suggesting a connection between BmVDAC and virus infection. To gain further insight into the function of BmVDAC in BmNPV, we employed RNA interference (RNAi) to silence and overexpress it by pIZT/V5‐His‐mCherry. The results revealed that BmVDAC is instrumental in developing the resistance of host cells to BmNPV infection in BmN cell‐line cells, which was further validated as likely to be associated with initiating programmed cell death (PCD). Furthermore, we evaluated the function of BmVDAC in another insect, Spodoptera exigua. Knockdown of the BmVDAC homolog in S. exigua, SeVDAC, made the larvae more sensitive to BmNPV. CONCLUSION: We have substantiated the pivotal role of BmVDAC in conferring resistance against BmNPV infection, primarily associated with the initiation of PCD. The findings of this study shine new light on the molecular mechanisms governing the silkworm's response to BmNPV infection, thereby supporting innovative approaches for pest biocontrol. © 2024 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

Since certain types of diabetes are reversible and curable in the early stages, early detection is crucial for effective treatment. Exhaled breath analysis, a noninvasive technique, is increasingly recognized for its potential in health monitoring, providing insights into an organism's metabolic state more directly than blood glucose tests. This work developed an in situ method utilizing corona ion source mass spectrometry for real-time direct monitoring of volatile organic compounds (VOCs) in mouse exhaled breath. The method was used to track breath changes in two mouse models with streptozotocin-induced diabetes throughout disease progression. Notably, variations in certain VOCs in exhaled breath correlated with blood glucose levels (BGLs) during diabetes development. For instance, in the type 1 diabetes model, acetone levels remained stable within 8 days after hyperglycemia (not significant, n.s.) compared to those in controls but showed a significant increase after 10 days (p < 0.001). In the type 2 diabetes model, isopropanol levels decreased (p < 0.001) during the prediabetes phase, when BGL changes were not significant (n.s.) compared to those in the healthy state. These results indicate that specific substances in exhaled breath change prior to noticeable BGL alterations. This study thus established the viability of direct online mass spectrometry for breath analysis in early diabetes detection and showed that this technique has potential for identifying clear clinical markers for early diabetes screening. [ABSTRACT FROM AUTHOR]

Converting the greenhouse gas CO2 to high value-added chemicals by photocatalysis has attracted much attention from scientists in recent decades. The performance of the photocatalytic CO2-reduction reaction is largely related to the properties of the photocatalyst. Layered double hydroxides (LDHs) have been widely used as photocatalysts in this reaction since Izumi, Teramura, and Tanaka's findings in the 2010s. Although much experimental work has been done, reaction mechanisms for CO2 reduction over LDHs have not been completely illustrated because of the complexity of the possible reaction pathways and products, limiting the selectivity of methanol. In this work, we first constructed a series of models representing M2M′–NO3–LDHs (M = Mg, Co, Ni, Zn; M′ = Al, Ga). After calculating their electronic properties (band structures, density of states, work functions, and band edge placements), together with their Gibbs free energy diagrams of CO2 reduction to the target product CH3OH and side products CO, HCOOH, HCHO, and CH4, it was found that the most favorable reaction pathway for the calculated LDHs is * + CO2 → CO2* → OCOH* → CO*/HCOOH* → CHO* → HCHO*/HCOH* → CH2OH* → CH3OH* → CH3* → CH4* → * + CH4. The main products for the calculated LDHs are CO and CH4. Although HCHO* and CH3OH* could be generated over most of the calculated LDHs, they could not facilely desorb while they could be easily further reduced, which may be the reason that HCHO and CH3OH are seldom found as products of photocatalytic CO2 reduction over LDHs without Cu. After that, we constructed a Cu atom-substituted model denoted as (ZnCu)2Ga–NO3–LDH. According to its Gibbs free energy diagram of photocatalytic CO2 reduction to CH3OH, the doping of Cu in the active site resulted in an improved Gibbs free energy change (ΔG) for the further reduction of CH3OH* to CH3*, which was deduced to be derived from the Jahn–Teller effect of divalent Cu. In general, this work proposes a reasonable reaction mechanism explaining the reaction selectivities to CO and CH4 for photocatalytic CO2 reduction over LDHs without Cu, and reveals the reason why Cu doping benefits producing CH3OH, facilitating the rational design of LDH-based photocatalysts towards selective CO2 reduction to CH3OH. [ABSTRACT FROM AUTHOR]

Molybdenum cofactor sulfurase (MoCoS) is a key gene involved in the uric acid metabolic pathway that activates xanthine dehydrogenase to synthesise uric acid. Uric acid is harmful to mammals but plays crucial roles in insects, one of which is the immune responses. However, the function of Bombyx mori MoCoS in response to BmNPV remains unclear. In this study, BmMoCoS was found to be relatively highly expressed in embryonic development, gonads and the Malpighian tubules. In addition, the expression levels of BmMoCoS were significantly upregulated in three silkworm strains with different levels of resistance after virus infection, suggesting a close link between them. Furthermore, RNAi and overexpression studies showed that BmMoCoS was involved in resistance to BmNPV infection, and its antivirus effects were found to be related to the regulation of uric acid metabolism, which was uncovered by inosine‐ and febuxostat‐coupled RNAi and overexpression. Finally, the BmMoCoS‐mediated uric acid pathway was preliminarily confirmed to be a potential target to protect silkworms from BmNPV infection. Overall, this study provides new evidence for elucidating the molecular mechanism of silkworms in response to BmNPV infection and new strategies for the prevention of viral infections in sericulture. [ABSTRACT FROM AUTHOR]

Wound infections may disrupt the normal wound-healing process. Large amounts of antibiotics are frequently used to prevent pathogenic infections; however, this can lead to resistance development. Biomaterials possessing antimicrobial properties have promising applications for reducing antibiotic usage and promoting wound healing. Silk sericin (SS) has been increasingly explored for skin wound healing applications owing to its excellent biocompatibility and antioxidant, antimicrobial, and ultraviolet-resistant properties. In recent years, SS-based composite biomaterials with a broader antimicrobial spectrum have been extensively investigated and demonstrated favorable efficacy in promoting wound healing. This review summarizes various antimicrobial agents, including metal nanoparticles, natural extracts, and antibiotics, that have been incorporated into SS composites for wound healing and elucidates their mechanisms of action. It has been revealed that SS-based biomaterials can achieve sustained antimicrobial activity by slow-release-loaded antimicrobial agents. The antimicrobial-loaded SS composites may promote wound healing through anti-infection, anti-inflammation, hemostasis, angiogenesis, and collagen deposition. The manufacturing methods, benefits, and limitations of antimicrobial-loaded SS materials are briefly discussed. This review aims to enhance the understanding of new advances and directions in SS-based antimicrobial composites and guide future biomedical research. [ABSTRACT FROM AUTHOR]

As the terminal of the power system, the distribution network is the main area where failures occur. In addition, with the integration of distributed generation, the traditional distribution network becomes more complex, rendering the conventional fault location algorithms based on a single power supply obsolete. Therefore, it is necessary to seek a new algorithm to locate the fault of the distributed power distribution network. In existing fault localization algorithms for distribution networks, since there are only two states of line faults, which can usually be represented by 0 and 1, most algorithms use discrete algorithms with this characteristic for iterative optimization. Therefore, this paper combines the advantages of the particle swarm algorithm and genetic algorithm and uses continuous real numbers for iteration to construct a successive particle swarm genetic algorithm (SPSO-GA) different from previous algorithms. The accuracy, speed, and fault tolerance of SPSO-GA, discrete particle swarm Genetic algorithm, and artificial fish swarm algorithm are compared in an IEEE33-node distribution network with the distributed power supply. The simulation results show that the SPSO-GA algorithm has high optimization accuracy and stability for single, double, or triple faults. Furthermore, SPSO-GA has a rapid convergence velocity, requires fewer particles, and can locate the fault segment accurately for the distribution network containing distorted information. [ABSTRACT FROM AUTHOR]

Structural annotation of small molecules in tandem mass spectrometry has always been a central challenge in mass spectrometry analysis, especially using a miniaturized mass spectrometer for on-site testing. Here, we propose the Transformer enabled Fragment Tree (TeFT) method, which combines various types of fragmentation tree models and a deep learning Transformer module. It is aimed to generate the specific structure of molecules de novo solely from mass spectrometry spectra. The evaluation results on different open-source databases indicated that the proposed model achieved remarkable results in that the majority of molecular structures of compounds in the test can be successfully recognized. Also, the TeFT has been validated on a miniaturized mass spectrometer with low-resolution spectra for 16 flavonoid alcohols, achieving complete structure prediction for 8 substances. Finally, TeFT confirmed the structure of the compound contained in a Chinese medicine substance called the Anweiyang capsule. These results indicate that the TeFT method is suitable for annotating fragmentation peaks with clear fragmentation rules, particularly when applied to on-site mass spectrometry with lower mass resolution. Tandem mass spectrometry spectra contain structural information of analyzed small molecules, however structural annotation and prediction from MS spectra remain challenging. Here, the authors combine the fragmentation tree models with a deep-learning transformer module, to annotate the fragmentation peaks and generate de novo molecular structures from a low-resolution mass spectrometer. [ABSTRACT FROM AUTHOR]

We studied the characteristics of a four-channel multi-task reservoir computing (RC) system based on mutually-coupled and optically pumped spin vertical-cavity surface-emitting lasers (Spin-VCSELs). By analyzing bifurcation and state diagrams, we investigated the polarization dynamics of the system. Additionally, we examined the effects of key parameters such as coupling strength, injection strength, frequency detuning, optical pumping intensity, and pump polarization ellipticity on RC performance, with one-step time-series prediction as the benchmark. Our findings indicate that an increase in coupling strength results in a reduced frequency detuning range, accompanied by a lower normalized mean squared error (NMSE). Excessive coupling strength and optical pumping intensity are detrimental to RC performance. The influence of pump polarization ellipticity is smaller and exhibits a symmetry feature. Furthermore, the parameter optimization regime for orthogonal polarized optical coupling (OPOC) is wider than that for parallel polarized optical coupling (PPOC). Under optimized parameters, both PPOC and OPOC-based RC system can achieve NMSE as low as 0.033 and 0.041 respectively. This work can provide a valuable insight on the design and mechanism analysis for parallel and multi-task processing RC systems based on the platform of Spin-VCSELs. [ABSTRACT FROM AUTHOR]

Fusarium sacchari is a causal agent of sugarcane Pokkah boeng, an important fungal disease that causes a considerable reduction in yield and sugar content in susceptible varieties of sugarcane worldwide. Despite its importance, the fungal factors that regulate the virulence of this pathogen remain largely unknown. In our previous study, mapping of an insertional mutant defect in virulence resulted in the identification of a cutinase G-box binding protein gene, designated FsCGBP, that encodes a C2H2-type transcription factor (TF). FsCGBP was shown to localize in the nuclei, and the transcript level of FsCGBP was significantly upregulated during the infection process or in response to abiotic stresses. Deletion or silencing of FsCGBP resulted in a reduction in mycelial growth, conidial production, and virulence and a delay in conidial germination in the F. sacchari. Cutinase genes FsCUT2, FsCUT3, and FsCUT4 and the mitogen-activated protein kinase (MAPK) genes FsHOG1, FsMGV1, and FsGPMK1, which were significantly downregulated in ΔFsCGBP. Except for FsHOG1, all of these genes were found to be transcriptionally activated by FsCGBP using the yeast one-hybrid system in vitro. The deletion of individual cutinase genes did not result in any of the phenotypes exhibited in the ΔFsCGBP mutant, except for cutinase activity. However, disruption of the MAPK pathway upon deletion of FsMGV1 or FsGPMK1 resulted in phenotypes similar to those of the ΔFsCGBP mutant. The above results suggest that FsCGBP functions by regulating the MAPK pathway and cutinase genes, providing new insights into the mechanism of virulence regulation in F. sacchari. [ABSTRACT FROM AUTHOR]

Cardiopulmonary bypass has been speculated to elicit systemic inflammation to initiate acute lung injury (ALI), including acute respiratory distress syndrome (ARDS), in patients after cardiac surgery. We previously found that post-operative patients showed an increase in endothelial cell-derived extracellular vesicles (eEVs) with components of coagulation and acute inflammatory responses. However, the mechanism underlying the onset of ALI owing to the release of eEVs after cardiopulmonary bypass, remains unclear. Plasma plasminogen-activated inhibitor-1 (PAI-1) and eEV levels were measured in patients with cardiopulmonary bypass. Endothelial cells and mice (C57BL/6, Toll-like receptor 4 knockout (TLR4−/−) and inducible nitric oxide synthase knockout (iNOS−/−)) were challenged with eEVs isolated from PAI-1-stimulated endothelial cells. Plasma PAI-1 and eEVs were remarkably enhanced after cardiopulmonary bypass. Plasma PAI-1 elevation was positively correlated with the increase in eEVs. The increase in plasma PAI-1 and eEV levels was associated with post-operative ARDS. The eEVs derived from PAI-1-stimulated endothelial cells could recognize TLR4 to stimulate a downstream signaling cascade identified as the Janus kinase 2/3 (JAK2/3)-signal transducer and activator of transcription 3 (STAT3)-interferon regulatory factor 1 (IRF-1) pathway, along with iNOS induction, and cytokine/chemokine production in vascular endothelial cells and C57BL/6 mice, ultimately contributing to ALI. ALI could be attenuated by JAK2/3 or STAT3 inhibitors (AG490 or S3I-201, respectively), and was relieved in TLR4−/− and iNOS−/− mice. eEVs activate the TLR4/JAK3/STAT3/IRF-1 signaling pathway to induce ALI/ARDS by delivering follistatin-like protein 1 (FSTL1), and FSTL1 knockdown in eEVs alleviates eEV-induced ALI/ARDS. Our data thus demonstrate that cardiopulmonary bypass may increase plasma PAI-1 levels to induce FSTL1-enriched eEVs, which target the TLR4-mediated JAK2/3/STAT3/IRF-1 signaling cascade and form a positive feedback loop, leading to ALI/ARDS after cardiac surgery. Our findings provide new insight into the molecular mechanisms and therapeutic targets for ALI/ARDS after cardiac surgery. [ABSTRACT FROM AUTHOR]

Introduction: Self-efficacy in individuals optimizes their hypertension management. Electronic patient portals are being increasingly used to support chronic disease management, as they raise the health literacy of patients and enable them in self-management. However, the association between the use of patient portals and self-efficacy in hypertension management remains unclear. The study aimed to determine the association between self-efficacy among patients with hypertension who are managed in primary care and their demographic characteristics and usage patterns of patient portals. Method: A cross-sectional survey was conducted at a public primary care clinic in urban Singapore. Multi-ethnic adult patients with hypertension were invited to participate in a self-administered electronic questionnaire. Chi-square test was performed for bivariate analysis; adjusted logistic regression models were used for factors with P value <.1. Results: A total of 310 patients (66.8% Chinese, 55.5% males, mean age of 63.1 years) completed the survey. Patient portal users had higher self-efficacy scores than non-users (mean score=63 vs 60, maximum = 80, P =.011). The factors associated with increased patient portal access included younger age <65 years (absolute odds ratio [AOR] = 2.634, 95%CI = 1.432-4.847; P =.002), monthly income >$5000 (AOR = 2.324, 95%CI = 1.104-4.892; P =.026), and post-secondary education level (AOR = 3.128, 95%CI = 1.675-5.839; P <.001). Most patients (93.1%) used the portal to check medical appointments but only1.3% of them used it to record home blood pressure measurements (HBPM). Conclusions: Patient portal usage was associated with higher self-efficacy scores in patients with hypertension. These users were younger, more educated, and earned more than the non-users, but only 1.3% of them used it for HBPM documentation. [ABSTRACT FROM AUTHOR]

Alkali metal‐doped boron clusters have captured much attention because of their novel electronic properties and structural evolution. In the study of RbBn0/− (n = 2–12) clusters, the minimum global search of the potential energy surface and structure optimization at the level of PBE1PBE by using the CALYPSO method and Gaussian package coupled with DFT calculation; the geometrical structures and electronic properties are systematically investigated. At n = 8, the ground‐state structures are composed of an Rb atom above B atoms, forming a structurally stable pagoda cone. By stability analysis and charge transfer calculation, the RbB8− cluster shows more stability. It found that s‐p hybridization between Rb atom and B atoms as well as s‐p hybridization between B atoms is one of the reasons for the outstanding stability exhibited in the RbB80/− clusters by using DOS and HOMO–LUMO orbital contour maps. The chemical bonding of the RbB80/− groups was analyzed by using the AdNDP method, and B atoms with larger numbers readily form multi‐center chemical bonds with the Rb atom. From the results of the bonding analysis, the interaction between the Rb atom and B atoms strengthens the stability of the RbB80/− clusters. It is hoped that this work provides a direction for experimental manipulation. [ABSTRACT FROM AUTHOR]

In order to investigate the dynamic stress characteristics of runner and distributor of pump-turbine, this paper establishes the solid domain models of stay vanes, guide vanes and runner, and carries out the FSI-based computation of runner and distributor. The calculation results show that the stress concentration at the "T" junction between the runner blade and crown is related to the vortex development state at the runner inlet the dynamic and static interference between runner and guide vanes is the main source of pressure pulsation in the vaneless zone, where the main frequency is the blade passing frequency ; the dynamic stress of guide vanes and runner is generally high because the pump-turbine is easily involved in the unstable area while working under smaller GVO (guide vanes opening) or low head conditions. The dynamic stress of guide vanes is greater than that of the runner owing to its constraint guidance effect on water flow, and increased flow rate is beneficial to reducing the dynamic stress of the runner. So for the purpose of improving the dynamic stress of runner, the measures could be ime, in order to solve the limitation of Shapley value method in solving the problem of joint scheduling gain allocation of multi-stakeholder cascade power stations, the paper introduces the idea of aggregation dimension reduction. The idea of the model is as follows : the increment of the cascade power generation benefits before and after the joint dispatching of the upstream power station is taken as the compensation benefit. Firstly, four different objective allocation methods are used to calculate the characteristic parameter indexes of the power station to form the basic decision matrix of TOPSIS. The TOPSIS principle is used to obtain the relative satisfaction of the power station to each allocation method. At the same time, the coalition game theory is used to calculate the power generation benefits of all possible coalition modes of the power station, and the compensation benefit allocation results based on Shapley value are obtained. Finally, the allocation coefficient obtained by TOPSIS principle is combined with the allocation coefficient obtained by Shapley value method to form a comprehensive allocation weight, which is applied to the compensation benefit allocation of eight-stage power station in the upper reaches of the Heihe River. The engineering application example shows that the method not only considers the marginal contribution of the union power station to the whole and the satisfaction degree of each power station, but also takes into account the difference of the characteristic index of the power station, and reasonably quantifies and distributes the power generation compensation benefit among the power stations. The allocation result is fair and reasonable and easy to be accepted by all parties, which can promote the power stations at all levels in the basin to participate in the joint dispatching so as to achieve the goal of maximizing the overall benefit. It has an important reference significance for the distribution of compensation benefits of a large number of cascade hydropower stations. [ABSTRACT FROM AUTHOR]

Objective: We aimed to develop a tool for virtual orthodontic bracket removal based on deep learning algorithms for feature extraction from bonded teeth and to demonstrate its application in a bracket position assessment scenario. Materials and methods: Our segmentation network for virtual bracket removal was trained using dataset A, containing 978 bonded teeth, 20 original teeth, and 20 brackets generated by scanners. The accuracy and segmentation time of the network were tested by dataset B, which included an additional 118 bonded teeth without knowing the original tooth morphology. This tool was then applied for bracket position assessment. The clinical crown center, bracket center, and orientations of separated teeth and brackets were extracted for analyzing the linear distribution and angular deviation of bonded brackets. Results: This tool performed virtual bracket removal in 2.9 ms per tooth with accuracies of 98.93% and 97.42% (P < 0.01) in datasets A and B, respectively. The tooth surface and bracket characteristics were extracted and used to evaluate the results of manually bonded brackets by 49 orthodontists. Personal preferences for bracket angulation and bracket distribution were displayed graphically and tabularly. Conclusions: The tool's efficiency and precision are satisfactory, and it can be operated without original tooth data. It can be used to display the bonding deviation in the bracket position assessment scenario. Clinical significance: With the aid of this tool, unnecessary bracket removal can be avoided when evaluating bracket positions and modifying treatment plans. It has the potential to produce retainers and orthodontic devices prior to tooth debonding. [ABSTRACT FROM AUTHOR]

The operation and performance of electrospray ionization (ESI) is affected by the surrounding environment. In this study, a compact sub-atmospheric pressure ESI (SAP-ESI) source was designed and fabricated using the 3D printing method. This source has a simple structure and is easy to operate, as the sample solution and auxiliary gas are continuously sucked into the source through the pressure difference. The compact and enclosed ionization chamber can reduce the fluctuation of the surrounding gas flow to ensure a remarkably stable (< 3%) electrospray. Moreover, the source can offer variable SAP conditions for ESI analysis. The yield of analyte ions increases with decreasing pressure, while the production of background ions is suppressed under these conditions. In the analysis of protein samples, SAP-ESI can increase the yield and charge state of ions, which may be due to the reduction of proton transfer between charged proteins and surrounding gas. The SAP-ESI source was then used to continuously monitor the extract aqueous solution of tea leaves, and to detect the carbendazim residues on the apple surface by coupling with the liquid extraction surface analysis technique. Experimental results demonstrate that the developed SAP-ESI is a stable, practical, and versatile ionization technique. [ABSTRACT FROM AUTHOR]

Psoriasis is an autoimmune skin disease that often co‐occurs with psychological morbidities such as anxiety and depression, and psychosocial issues also lead psoriasis patients to avoid other people. However, the precise mechanism underlying the comorbidity of psoriasis and anxiety is unknown. Also, whether the social avoidance phenomenon seen in human patients also exists in psoriasis‐like animal models remains unknown. In the present study, anxiety‐like behaviours and social avoidance‐like behaviours were observed in an imiquimod‐induced psoriasis‐like C57‐BL6 mouse model along with typical psoriasis‐like dermatitis and itch‐like behaviours. The 11.7T resting‐state functional magnetic resonance imaging showed differences in brain regions between the model and control group, and voxel‐based morphometry showed that the grey matter volume changed in the basal forebrain region, anterior commissure intrabulbar and striatum in the psoriasis‐like mice. Seed‐based resting state functional connectivity analysis revealed connectivity changes in the amygdala, periaqueductal gray, raphe nuclei and lateral septum. We conclude that the imiquimod‐induced psoriasis‐like C57‐BL6 mouse model is well suited for mechanistic studies and for performing preclinical therapeutic trials for treating anxiety and pathological social avoidance in psoriasis patients. [ABSTRACT FROM AUTHOR]

In this paper, we used CALYPSO program which is conjuncted with DFT to investigate Li doped small-sized neutral Bn clusters. From ground-state and low energy structures, the properties and geometric significance of Li-doped boron clusters are greatly affected. Except for LiB9, which adds a B atom on preceding LiB8 boron wheel, the ground-state clusters of LiBn are formed by replacing the terminal boron atom of the Bn+1 clusters in the same size with a Li atom or by adding a Li atom to the Bn clusters. The transition point from 2 to 3D configuration of LiBn clusters appears at n = 5. The stability of LiBn clusters was analyzed by calculating the average binding energy, Gibbs free energy, first-order differential energy, second-order differential energy, HOMO–LUMO gap (the energy gap between the highest occupied and lowest unoccupied molecular orbital) and charge transfer. The results show that the LiB11 cluster with excellent symmetry and planar structure is the relative most stable structure. Molecular orbital and chemical bonding analysis indicated that the main reason for the stability of the LiB11 cluster is mainly due to the strong s-p bonding of B–B. [ABSTRACT FROM AUTHOR]

The main aim of this paper is to develop a nonconvex optimization model for third‐order tensor completion under wavelet transform. On the one hand, through wavelet transform of frontal slices, we divide a large tensor data into a main part tensor and three detail part tensors, and the elements of these four tensors are about a quarter of the original tensors. Solving these four small tensors can not only improve the operation efficiency, but also better restore the original tensor data. On the other hand, by using concave correction term, we are able to correct for low rank of tubal nuclear norm (TNN) data fidelity term and sparsity of l1$$ {l}_1 $$‐norm data fidelity term. We prove that the proposed algorithm can converge to some critical point. Experimental results on image, magnetic resonance imaging and video inpainting tasks clearly demonstrate the superior performance and efficiency of our developed method over state‐of‐the‐arts including the TNN and other methods. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel tensor factorization-based method for the third-order tensor completion problem with spatio-temporal characterization. For this aim, we consider tensor fibered rank, which extends tubal rank, to improve the flexibility and accuracy of data characterization. Based on this rank, we apply a factorization-based method to complete the third-order low-rank tensors with spatio-temporal characteristics, which are intrinsic features of image, video and internet traffic tensor data. The model not only makes good use of the low-rank structure of tensors, but also takes into account the spatio-temporal characteristics of the data. Finally, we report numerical results on completing image, video and internet traffic data. The results demonstrate that our method outperforms some existing methods. [ABSTRACT FROM AUTHOR]

The Minimum Vertex Weighted Coloring (MinVWC) problem is an important generalization of the classic Minimum Vertex Coloring (MinVC) problem which is NP-hard. Given a simple undirected graph G = (V , E) , the MinVC problem is to find a coloring s.t. any pair of adjacent vertices are assigned different colors and the number of colors used is minimized. The MinVWC problem associates each vertex with a positive weight and defines the weight of a color to be the weight of its heaviest vertices, then the goal is the find a coloring that minimizes the sum of weights over all colors. Among various approaches, reduction is an effective one. It tries to obtain a subgraph whose optimal solutions can conveniently be extended into optimal ones for the whole graph, without costly branching. In this paper, we propose a reduction algorithm based on maximal clique enumeration. More specifically our algorithm utilizes a certain proportion of maximal cliques and obtains lower bounds in order to perform reductions. It alternates between clique sampling and graph reductions and consists of three successive procedures: promising clique reductions, better bound reductions and post reductions. Experimental results show that our algorithm returns considerably smaller subgraphs for numerous large benchmark graphs, compared to the most recent method named RedLS. Also, we evaluate individual impacts and some practical properties of our algorithm. Furthermore, we have a theorem which indicates that the reduction effects of our algorithm are equivalent to that of a counterpart which enumerates all maximal cliques in the whole graph if the run time is sufficiently long. [ABSTRACT FROM AUTHOR]

Recently, the major challenge in treating osteosarcoma patients is the metastatic disease, most commonly in the lungs. However, the underlying mechanism of recurrence and metastasis of osteosarcoma after surgical resection of primary tumor remains unclear. This study aims to investigate whether the pulmonary metastases characteristic of osteosarcoma is associated with surgical treatment and whether surgery contributes to the formation of pre‐metastatic niche in the distant lung tissue. In the current study, the authors observe the presence of circulating tumor cells in patients undergoing surgical resection of osteosarcoma which is correlated to tumor recurrence. The pulmonary infiltrations of neutrophils and Gr‐1+ myeloid cells are characterized to form a pre‐metastatic niche upon the exposure of circulating tumor cells after surgical resection. It is found that mitochondrial damage‐associated molecular patterns released from surgical resection contribute to the formation of pre‐metastatic niche in lung through IL‐1β secretion. This study reveals that surgical management for osteosarcoma, irrespective of the primary tumor, might promote the formation of postoperative pre‐metastatic niche in lung which is with important implications for developing rational therapies during peri‐operative period. [ABSTRACT FROM AUTHOR]

Halide ions have emerged as important surface active species that regulate the growth of nanomaterials and concomitant physicochemical properties. However, there are very few reports concerning anion exchange of halide ions for the growth and conversion of nanocrystals or nanoclusters. Herein, we present the transformations of silver(I) chalcogenide clusters induced by doping halide ions, which are particularly of interest because of individual pathways controlled by ion species and amounts. Based on the cluster transformation, we further developed a luminescence turn-on sensor with high selectivity, detecting Cl− and Br−. This work opens a new way of understanding the growth of clusters and developing their luminescence sensing applications. [ABSTRACT FROM AUTHOR]

Since natural restoration combined with artificial auxiliary measures may achieve a relatively rapid restoration effect at a lower cost, it has become an essential measure for the ecological restoration of rock slopes. Previous studies have focused heavily on the relationship between substrate nutrients and water conditions and the development of mosses on the rock surface, but quantitative characterization of substantial effect of rock surface texture (e.g., microrelief) on moss growth is absent. The undulating microrelief on the rock surface can increase the heterogeneity of the microhabitat, which may be an important factor affecting the development of moss-dominated biocrusts. In this study, the roughness of rock surfaces, moss coverage and biomass, weight and major nutrient contents of soils within the biocrusts were measured in the western mountainous area of Sichuan Province, Southwest China to further examine the role of rock surface microrelief in the biocrusts. The results showed that three main factors affecting the development of the biocrusts were bryophyte emergence, soil accumulation, and lithology. The presence of moss accelerates soil formation on rock surfaces and lead to the accumulation of nutrients so that all parts of the moss-dominated biocrusts system can develop synergistically. It was found that a microrelief structure with a roughness between 1.5 and 2.5 could gather soil and bryophyte propagules effectively, which may have a strong relationship with the angle of repose. When the roughness is 1.5, the corresponding undulation angle is very close to the theoretical minimum value of the undulation angle calculated according to the relationships between the undulation angle of the protrusion, slope and angle of repose. [ABSTRACT FROM AUTHOR]

To evaluate the clinical efficacy of carbon dioxide laser in the treatment of female stress urinary incontinence and analyze the influencing factors. A total of 46 patients with stress urinary incontinence treated in the Affiliated Hospital of Nantong University from March 2021 to August 2022 were included through strict inclusion criteria and exclusion criteria. All patients were treated with transvaginal carbon dioxide laser therapy, and Patient Global Impression of Change (PGI-C) was used to evaluate patients' subjective satisfaction after treatment. The efficacy was evaluated by patient's subjective assessment of leakage, IngelmanSundberg scale, 1-h urine pad test, and international consultation on incontinence questionnaire short form (ICI-Q-SF) before and after treatment, and the adverse reactions after treatment were recorded. The treatment effect was divided into "significant effect group" and "no significant effect group" by subjective satisfaction and post-treatment-related scale evaluation. After laser treatment, patients' subjective symptom improved, the volume of 1-h urine pad test was reduced, and the ICI-Q-SF score was decreased, and the differences were statistically significant (P < 0.05). There was no significant difference in IngelmanSundberg scale before and after treatment (P = 1.00). Multivariate logistic regression analysis showed that pad test volume was significantly correlated with treatment effect (P = 0.007). Transvaginal carbon dioxide laser is a safe and effective method for the treatment of mild to moderate stress urinary incontinence in females. The less severe the urinary leakage, the better the treatment effect. [ABSTRACT FROM AUTHOR]

In this paper, the geometric structure and physicochemical properties of Li2Bn0/− (n = 1–12) clusters were investigated using CALYPSO structure prediction software in combination with density functional theory at B3LYP/6-311G level. The results suggest that the doping of Li atoms has a significant effect on the ground state geometry of the Bn clusters. The stability changes with the increase in the number of boron atoms. Then two stable ground state structures, Li2B8 and Li2B9−, are selected for further analyzing their molecular orbitals and bonding properties. It is demonstrated that the stability of the Li2Bn0/− (n = 1–12) clusters originates from the s–p hybridization between B–B and Li–B. It is expected that this work can provide some references for future research on boron-based nanomaterials. [ABSTRACT FROM AUTHOR]

While flipped learning has attempted to explain the benefits of technology applied to educational settings, this study aims to validate research questions and test the theory of the learning strategies in flipped learning. A self-designed questionnaire, consisting of 17 critical indicators of online self-regulation, project-based learning and 5-competence development, was administered to collect data from 87 college students in China. The partial least squares structural equation modeling (PLS-SEM) was used to analyze the relative factors. The results indicated that an integrated model, combining online self-regulation and project-based learning, provided a marginally better explanatory power; project-based learning had a better prediction of 5-competence development than online self-regulation. An integrated model is proposed to detect the latent relationships among the data with structural equation modeling (SEM). The SEM provides a clear picture of the relations among the variables, and shows that online "Help seeking" in MOOC lecture videos and engagement in "Teamwork" in class are the key indicators of student engagement in flipped learning. This study adopted an innovative approach which emphasizes the diagnosis of students' engagement, and proposes an integrated model combining online self-regulation and project-based learning constructs for a theoretical framework to predict learning performance in flipped learning. [ABSTRACT FROM AUTHOR]

Low Tucker rank tensor completion has wide applications in science and engineering. Many existing approaches dealt with the Tucker rank by unfolding matrix rank. However, unfolding a tensor to a matrix would destroy the data's original multi‐way structure, resulting in vital information loss and degraded performance. In this article, we establish a relationship between the Tucker ranks and the ranks of the factor matrices in Tucker decomposition. Then, we reformulate the low Tucker rank tensor completion problem as a multilinear low rank matrix completion problem. For the reformulated problem, a symmetric block coordinate descent method is customized. For each matrix rank minimization subproblem, the classical truncated nuclear norm minimization is adopted. Furthermore, temporal characteristics in image and video data are introduced to such a model, which benefits the performance of the method. Numerical simulations illustrate the efficiency of our proposed models and methods. [ABSTRACT FROM AUTHOR]

The article presents questions and answers related to medical nutritional therapy in diabetes management, the relevance of this therapy in primary care, and when to refer patients to a dietitian.

Annealing can usually inhibit the formation of an unstable brookite mesophase in the crystal structure, enhancing the growth of an anatase titanium dioxide (TiO2) thin film. In this study, after a TiO2 solution was prepared with and without a small amount (1 wt%) of the organic solvent dimethylformamide (DMF), TiO2 films were obtained by dynamic spin-coating and were annealed at temperatures of 300, 500, and 700 °C. The structural and optical properties as well as the surface morphologies of the films were studied. The experimental results show that the TiO2 film annealed at 500 °C exhibits a polycrystalline anatase and brookite multiphase and usefully inhibits the formation of the brookite mesophase when annealed at 700 °C. Moreover, adding the DMF effectively contributes to the formation of the polycrystalline phase at 300 °C. The compactness of the annealed TiO2 film was improved by adding 1 wt% DMF, as shown by topographic images obtained by atomic force microscopy, leading to decreased transmittance and increased absorbance. The band gap (Eg) values of all the samples were also estimated. The variation of Eg was evidenced by the structural change and the redshift of the absorption edge. [ABSTRACT FROM AUTHOR]

With the rapid development of autonomous driving technology, future road traffic must be composed of autonomous vehicles and artificial vehicles. Although autonomous vehicles have greatly improved road capacity, few studies have involved capacity at signal-controlled intersections, and most of the studies are based on experimental simulation. As such, there is a need to more scientifically analyze the impact of autonomous vehicles on road and intersection capacity. Based on three theories of flow-density relationships, traffic flow equilibrium analysis, and the following model, this paper firstly deduces the flow-density relationship of different vehicle types in a single environment. Secondly, flow-density relationships under different proportions of self-driving vehicles are derived. Through the derivation of these two models, the basic road saturation flow rates under different permeabilities of self-driving vehicles, can be obtained. Based on these results, a revised calculation model for the capacity of signalized intersections with different proportions of autonomous vehicles is proposed, which is essentially to revise the basic saturation flow rate under different permeabilities of autonomous vehicles. By using SUMO 1.15.0 traffic simulation software, the theoretical models are individually tested. The results show that the error rate between the theoretical calculation results and the SUMO simulation results, is less than 16%. This study can provide a basis for the calculation of basic capacity of roads and intersections in a future man-machine hybrid driving environment, and provide theoretical guidance for traffic management and control. [ABSTRACT FROM AUTHOR]

Transition‐metal‐based oxyhydroxides are efficient catalysts in biomass electrooxidation towards fossil‐fuel‐free production of valuable chemicals. However, identification of active sites remains elusive. Herein, using cobalt oxyhydroxide (CoOOH) as the archetype and the electrocatalyzed glucose oxidation reaction (GOR) as the model reaction, we track dynamic transformation of the electronic and atomic structure of the catalyst using a suite of operando and ex situ techniques. We reveal that two types of reducible Co3+‐oxo species are afforded for the GOR, including adsorbed hydroxyl on Co3+ ion (μ1‐OH−Co3+) and di‐Co3+‐bridged lattice oxygen (μ2‐O−Co3+). Moreover, theoretical calculations unveil that μ1‐OH−Co3+ is responsible for oxygenation, while μ2‐O−Co3+ mainly contributes to dehydrogenation, both as key oxidative steps in glucose‐to‐formate transformation. This work provides a framework for mechanistic understanding of the complex near‐surface chemistry of metal oxyhydroxides in biomass electrorefining. [ABSTRACT FROM AUTHOR]

Transition‐metal‐based oxyhydroxides are efficient catalysts in biomass electrooxidation towards fossil‐fuel‐free production of valuable chemicals. However, identification of active sites remains elusive. Herein, using cobalt oxyhydroxide (CoOOH) as the archetype and the electrocatalyzed glucose oxidation reaction (GOR) as the model reaction, we track dynamic transformation of the electronic and atomic structure of the catalyst using a suite of operando and ex situ techniques. We reveal that two types of reducible Co3+‐oxo species are afforded for the GOR, including adsorbed hydroxyl on Co3+ ion (μ1‐OH−Co3+) and di‐Co3+‐bridged lattice oxygen (μ2‐O−Co3+). Moreover, theoretical calculations unveil that μ1‐OH−Co3+ is responsible for oxygenation, while μ2‐O−Co3+ mainly contributes to dehydrogenation, both as key oxidative steps in glucose‐to‐formate transformation. This work provides a framework for mechanistic understanding of the complex near‐surface chemistry of metal oxyhydroxides in biomass electrorefining. [ABSTRACT FROM AUTHOR]

Low rank matrix and tensor completion problems are to recover the incomplete two and higher order data of low rank structures. The essential problem in the matrix and tensor completion problems is how to improve the efficiency. For a matrix completion problem, we establish a relationship between matrix rank and tensor tubal rank, and reformulate matrix completion problem as a third order tensor completion problem. For the reformulated tensor completion problem, we adopt a two-stage strategy based on tensor factorization algorithm. In this way, a matrix completion problem of big size can be solved via some matrix computations of smaller sizes. For a third order tensor completion problem, to fully exploit the low rank structures, we introduce the double tubal rank which combines the tubal rank of two tensors, original tensor and the reshaped tensor of the mode-3 unfolding matrix of original tensor. Based on this, we propose a reweighted tensor factorization algorithm for third order tensor completion. Extensive numerical experiments demonstrate that the proposed methods outperform state-of-the-art methods in terms of both accuracy and running time. [ABSTRACT FROM AUTHOR]

Sugarcane leaf blight (SLB), a major fungal leaf disease of sugarcane (Saccharum spp.), has been attributed to Stagonospora tainanensis. In December 2020 and May 2021, signs of leaf blight were observed on sugarcane in the fields of Chongzuo City, in the Guangxi Province of China. Lesions on the leaves were characterized by yellow or dark red spots in the center. Fungal species were isolated, purified and subjected to pathogenicity evaluation on the sugarcane plants. An isolate that caused symptoms the same as those observed in the field was initially identified as S. tainanensis (Leptosphaeria taiwanensis, perfect state) based on its morphological characteristics both of asexual and sexual stages. Dark brown and nearly spherical pycnidia with conidia of long ellipsoidal, hyaline, one to four cells and 29.27 to 54.39 μm long and 9.03 to 16.12 μm wide were found on corn meal agar medium. Ascomata with asci of cylindrical to clavate, a short stipe and eight spores slightly constricted at the septum, with the size of the spore ranging from 36 to 44 μm long and 8.5 to 12 μm wide, were formed on the sugarcane-leaf-decoction saccharose agar medium. The identity of the species was further confirmed by rDNA ITS and TEF-1α sequencing. The optimal temperature for mycelial growth was 25 °C and the optimal pH was 6.0. The pathogen grew well in a medium with oats as the carbon source and yeast extract as the nitrogen source, but poorly in a medium with urea as the nitrogen source. This study is the first to identify the sugarcane leaf blight pathogen in Guangxi, and the first publication describing the biological characterization of S. tainanensis. The occurrence of sugarcane leaf blight should alert sugarcane breeders and plant pathologists to consider integrating control of this potentially important disease into the agenda of their breeding and disease control programs. [ABSTRACT FROM AUTHOR]

This paper proposes the first lattice to price multiasset double‐barrier options when barriers, volatilities, correlations, and interest rates are all time varying. The nodes are strategically placed to both match the volatilities and align with the two barriers per asset for fast convergence. The branching probabilities are provably valid. The size of our lattice is O(nk+1) $O({n}^{k+1})$, where n $n$ is the number of time steps and k $k$ is the number of assets, and is only O(n1+k∕2) $O({n}^{1+k\unicode{x02215}2})$ for continuously monitored double‐barrier knock‐out options. [ABSTRACT FROM AUTHOR]

Projects about magnesium-based doped of transition metal have constantly attracted much attention in cluster science, while the research of Co, Fe, Ni doped Mid-Sized Mg16 clusters has not been reported. Here, the geometric construction and electronic properties of neutral and negative Mg16X (X = Co, Fe, Ni) clusters were researched by unbiased CALYPSO structure search codes and subsequent DFT calculations at the B3PW91 level. The results show that Fe and Co atoms are more likely to replace the central bits of the caged Mg170/− cluster, but the excellent and stable configuration of the Mg170/− cluster is perfectly maintained. Simultaneously, the doping of Co and Fe can cause the cluster to produce the corresponding magnetic moment. The caged Mg16Co− clusters with a central Co atom have good binding energy, local charge transfer and HOMO–LUMO gap according to stability analysis, which indicates that Mg16Co− clusters has better relative stability. In addition, it is found that there is an intense interaction between Mg-3s, p and Co-3d AO (molecular orbitals) through the analysis of molecular orbitals and adaptive natural density partitioning (AdNDP), which may be the main reason for the high stability of Mg16Co− clusters. [ABSTRACT FROM AUTHOR]

The systems of alkali metal atom doped boron have been investigative topics over the years because of their diverse configurations and unique properties. Based on this, with the assistance of the CALYPSO software facilitates the structure prediction process, our group went into the geometric structures and bonding characteristics of the NaBn (n = 1-12) clusters. From the structural analysis, the participation of the Na atom does not dramatically change the configurations of the clusters, and the NaBn (n = 1-12) clusters maintain the parallel planar configuration evolution model with the pure boron clusters. The local most stable structures emerge at n = 3, 5, 8, the NEC result shows electrons transfer from Na-3s and B-2s orbitals to B-2p orbitals, indicating the s-p hybridisation exists between Na-B, B-B atoms, and the DOS analysis also prove this point. In the subsequent bonding analysis of the NaB3 and NaB8 clusters, the high proportions of B-2s, B-2p, or Na-3s orbitals at HOMO, LUMO, demonstrate the formation of strong B-B, Na-B covalent bonds, which is the benefit to forming high stability. Last, the calculations of ICSS show, perpendicular to the boron ring plane direction, the NaB3 exhibits strong aromaticity while the NaB8 shows anti-aromaticity. [ABSTRACT FROM AUTHOR]

C24H16N11O3Sm, monoclinic, P21/c (no. 14), a = 6.745(6) Å, b = 21.943(19) Å, c = 16.132(14) Å, β = 95.362(13)°, V = 2378(4) Å3, Z = 4, Rgt(F) = 0.0446, wRref(F2) = 0.1162, T = 296 K. [ABSTRACT FROM AUTHOR]

C48H32N26Bi2, triclinic, P 1 ‾ (no. 2), a = 9.781(5) Å, b = 11.667(6) Å, c = 11.973(7) Å, α = 83.816(10)°, β = 74.471(10)°, γ = 66.120(8)°, V = 1203.7 (11) Å3, Z = 1, Rgt(F) = 0.0435, wRref(F2) = 0.1035, T = 293 K. [ABSTRACT FROM AUTHOR]

Introduction: The early diagnosis of major depressive disorder (MDD) is very important for patients that suffer from severe and irreversible consequences of depression. It has been indicated that functional connectivity (FC) analysis based on functional magnetic resonance imaging (fMRI) data can provide valuable biomarkers for clinical diagnosis. However, previous studies mainly focus on brain disease classification in small sample sizes, which may lead to dramatic divergences in classification accuracy. Methods: This paper attempts to address this limitation by applying the deep graph convolutional neural network (DGCNN) method on a large multi-site MDD dataset. The resting-state fMRI data are acquired from 830 MDD patients and 771 normal controls (NC) shared by the REST-meta-MDD consortium. Results: The DGCNN model trained with the binary network after thresholding, identified MDD patients from normal controls and achieved an accuracy of 72.1% with 10-fold cross-validation, which is 12.4%, 9.8%, and 7.6% higher than SVM, RF, and GCN, respectively. Moreover, the process of dataset reading and model training is faster. Therefore, it demonstrates the advantages of the DGCNN model with low time complexity and sound classification performance. Discussion: Based on a large, multi-site dataset from MDD patients, the results expressed that DGCNN is not an extremely accurate method for MDD diagnosis. However, there is an improvement over previous methods with our goal of better understanding brain function and ultimately providing a biomarker or diagnostic capability for MDD diagnosis. [ABSTRACT FROM AUTHOR]