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Abstract Background The deformation of oral and maxillofacial region leads to not only the damage of morphology and function, but also a series of aesthetic and psychological problems, severely affecting the quality of life of patients. Oral tissue engineering refers to developing biomaterials for repair or regeneration, with the application of tissue engineering technologies. This has become an area of increasing prominence. Current biologically inert materials are insufficient to fulfill clinical requirements. Therefore, tissue-engineered biomaterials with bioactive, even bionic properties are desperately needed. Main body The complexity of the anatomy and the diversity of tissue types of oral and maxillofacial region pose great challenges to the regeneration, in the aspects of both biomaterials and manufacturing technologies. Biomaterials in clinical practice or research have evolved from natural materials to synthetic materials, from homogeneous materials to multiple composite materials. And now composite materials have increasingly demonstrated their advantages in terms of physicochemical and biological properties over conventional materials. In terms of manufacturing, traditional coating, sintering, and milling technologies can no longer satisfy the requirements for high-precision bionic structures of oral-tissue-engineering biomaterials. Scientists have turned to biofabrication technologies such as microfluidics and additive manufacturing. Short conclusion This review aims to summarize the noteworthy advancements made in biomaterials of oral tissue engineering. We outlined the current biomaterials and manufacturing technologies and focused on various applications of these materials that may be connected to clinical treatment and research. We also suggested the future direction of development for biomaterials in oral tissue engineering. In future, biomaterials characterized by precision, functionalization, and individualization will be manufactured through digital, microfluidic, and 3D printing technologies. Graphical abstract

Glucose oxidase (GOD) has been investigated as a potential additive for enhancing intestinal health and growth performance in poultry. However, limited research exists on the effects of ultra-high doses of GOD in practical poultry production. This study aimed to investigate the impact of high dietary GOD levels on broiler growth performance, antioxidant capacity, and intestinal microbiota. A total of 400 healthy, 1-day-old, slow-growing broiler chickens were randomly assigned to four treatment groups. The control group was fed a standard basal diet, while the other groups (G1, G2, and G3) were fed the basal diet supplemented with 4 U/g, 20 U/g, and 100 U/g of VTR GOD, respectively. The results showed that a dose of 100 U/g GOD significantly improved the final body weight and average daily feed intake (ADFI) (p

Objective: The study aims to present an observational study of clinical trials on Oral Potentially Malignant Disorders (OPMDs) and corresponding publications. Study design and setting: We searched the OPMDs-related clinical studies registered in the ClinicalTrials.gov database before March 1, 2024. Subsequently, we investigated the publication status of primary completed studies using PubMed and Google Scholar. Results: A total of 185 studies were identified for analysis, including 141 interventional studies and 44 observational studies. The most commonly studied disease type was oral lichen planus (OLP), accounting for 113 studies (61.1 %). Interventional studies on OPMDs were predominantly early-phased, blind, randomized, parallel and single-center. The primary purpose of these studies was treatment (106, 75.2 %). Among the treatments, herbal medicine (21, 19.8 %), photodynamic therapy (17, 16.0 %), and glucocorticoids (14, 13.2 %) were of greatest interest. In addition, 58 (63.0 %) of the primarily completed interventional studies were published, with a median time to publication of 33.6 months. Published interventional studies including OLP patients and factorial designs had shorter time to publication. However, these studies were less frequently published in high-impact journals and most primary results were positive. Conclusions: Clinical trials on OPMDs predominantly focused on OLP and herbal medicine. The quality of studies is unsatisfactory and publication rate is suboptimal. Improvements are needed in ClinicalTrials.gov registration standards, high-quality study design and more stringent publishing requirements.

The loss-of-function mutation of AT-rich interactive domain 1A (ARID1A) frequently occurs in various types of cancer, making it a promising therapeutic target. In the present study, we performed a screening of an FDA-approved drug library in ARID1A isogenic colorectal cancer (CRC) cells and discovered that ARID1A loss sensitizes CRC cells to floxuridine (FUDR), an antineoplastic agent used for treating hepatic metastases from CRC, both in vivo and in vitro. As a pyrimidine analogue, FUDR induces DNA damage by inhibiting thymidylate synthase (TS) activity. ARID1A, as a regulator of DNA damage repair, when lost, exacerbates FUDR-induced DNA damage, leading to increased cell apoptosis. Specifically, ARID1A deficiency impairs DNA damage repair by downregulating Chk2 phosphorylation, thereby sensitizing cancer cells to FUDR. Notably, we found that FUDR exhibited increased sensitivity in ARID1A-deficient cells compared to 5-fluorouracil (5-FU), a commonly used anticancer drug for CRC. This suggests that FUDR is superior to 5-FU in treating ARID1A-deficient CRC. In conclusion, ARID1A loss significantly heightens sensitivity to FUDR by promoting FUDR-induced DNA damage in CRC. These findings offer a novel therapeutic approach for the treatment of CRC characterized by ARID1A loss-of-function mutations.

Summary: Background: The use of real-time continuous glucose monitoring (rtCGM) technology remains largely investigational in the hospital setting. The current study aimed to evaluate the effectiveness of rtCGM in inpatients with diabetes who were treated with short-term continuous subcutaneous insulin infusion (CSII). Methods: In this randomized, parallel controlled trial conducted on the endocrinology wards in a tertiary hospital located in Shanghai, adults with type 1 and type 2 diabetes who required short-term CSII during hospitalization were randomly assigned (1:1) to receive either rtCGM-based glucose monitoring and management program or point-of-care (POC) standard of care (8 times/day) with blinded CGM. Primary outcome measure was the difference in the percentage of time within the target glucose range of 3.9–10 mmol/L (TIR, %). This study was registered at www.chictr.org.cn (ChiCTR2300068933). Findings: Among the 475 randomized participants (237 in the rtCGM group and 238 in the POC group), the mean age of was 60 ± 13 years, and the mean baseline glycated hemoglobin level was 9.4 ± 1.8%. The CGM-recorded mean TIR was 71.1 ± 15.8% in the rtCGM group and 62.9 ± 18.9% in the POC group, with a mean difference of 8.2% (95% confidence interval [CI]: 5.1–11.4%, P 10 mmol/L was significantly lower in the rtCGM group than in the POC group (28.3 ± 15.8% vs. 36.6 ± 19.0%, P

The main acne-causing bacteria are Propionibacterium acnes, Staphylococcus aureus and Staphylococcus epidermidis. Quorum sensing, an important factor for bacterial survival, is closely associated with expression of bacterial virulence factors and biofilm formation. Although the quorum sensing types of Staphylococcus aureus and Staphylococcus epidermidis have been identified, the quorum sensing types of Propionibacterium acnes are still controversial. Plant-orginated quorum sensing inhibitors with few side effects have a greater potential in the treatment of acne. This article reviews the progress on the mechanisms by which plant-originated quorum sensing inhibitors inhibit pathogenic bacteria of acne.

Abstract Reconstruction of irregular oral-maxillofacial bone defects with an inflammatory microenvironment remains a challenge, as chronic local inflammation can largely impair bone healing. Here, we used magnesium silicate nanospheres (MSNs) to load microRNA-146a-5p (miR-146a) to fabricate a nanobiomaterial, MSN+miR-146a, which showed synergistic promoting effects on the osteogenic differentiation of human dental pulp stem cells (hDPSCs). In addition, miR-146a exhibited an anti-inflammatory effect on mouse bone marrow-derived macrophages (BMMs) under lipopolysaccharide (LPS) stimulation by inhibiting the NF-κB pathway via targeting tumor necrosis factor receptor-associated factor 6 (TRAF6), and MSNs could simultaneously promote M2 polarization of BMMs. MiR-146a was also found to inhibit osteoclast formation. Finally, the dual osteogenic-promoting and immunoregulatory effects of MSN+miR-146a were further validated in a stimulated infected mouse mandibular bone defect model via delivery by a photocuring hydrogel. Collectively, the MSN+miR-146a complex revealed good potential in treating inflammatory irregular oral-maxillofacial bone defects.

Abstract Over the past two decades, there has been continuous advancement in the accuracy and complexity of continuous glucose monitoring devices. Continuous glucose monitoring provides valuable insights into blood glucose dynamics, and can record glucose fluctuations accurately and completely. Glycemic variability (GV) is a straightforward measure of the extent to which a patient's blood glucose levels fluctuate between high peaks and low nadirs. Many studies have investigated the relationship between GV and complications, primarily in the context of type 2 diabetes. Nevertheless, the exact contribution of GV to the development of diabetes complications remains unclear. In this literature review, we aimed to summarize the existing evidence regarding the measurement, target level, pathophysiological mechanisms relating GV and tissue damage, and population‐based studies of GV and diabetes complications. Additionally, we introduce novel methods for measuring GV, and discuss several unresolved issues of GV. In the future, more longitudinal studies and trials are required to confirm the exact role of GV in the development of diabetes complications.

Canine circovirus (CanineCV), which is a new mammalian circovirus first reported in the United States in 2012, mainly causes diarrhea and vomiting in dogs. As CanineCV evolves and new subtypes emerge, there is an urgent need for new detection technologies to improve the sensitivity and detection rates of viruses in complex scenarios. A chip digital PCR(cdPCR) assay was established for the detection of CanineCV in this study. The results showed good reproducibility, specificity and a linear relationship; the minimum detection limit of CanineCV by cdPCR was 6.62 copies/μL, which is 10 times more sensitive than quantitative real-time PCR (qPCR). The qPCR-positive detection rate was 1 %, while CanineCV cdPCR (2.1 %) exhibited a greater positive detection rate. Fifteen complete genomes were sequenced and subdivided into CanineCV-1 and CanineCV-3. In conclusion, we developed a rapid, reliable, and specific cdPCR method for screening and monitoring canine CV.

The ectoparasitoid Habrobracon hebetor (Hymenoptera: Braconidae) exhibits a broad parasitic capability towards various lepidopteran pests, with venom serving as a crucial virulent factor ensuring successful parasitization and subsequent host mortality. Analyzing the constituents of its venom is essential for elucidating the mechanisms underlying efficient host killing by this parasitoid and for exploring potentially functional venom proteins. Through a transcriptomic analysis, a total of 34 venom proteins were identified within the venom of H. hebetor, encompassing known components such as serine protease, metalloproteinase, esterase, and serine protease inhibitors commonly present in parasitoid venoms. Unique components like paralytic protein and ion transport peptide-like were identified, possibly specific to certain parasitoids, along with novel proteins with uncharacterized functions. Spatial gene expression profiling of the identified venom proteins using transcriptomic data, corroborated by quantitative PCR validation for 13 randomly selected proteins, revealed abundant expression levels in the venom apparatus, affirming them as genuine venom components. Notably, the paralytic protein exhibited prominent expression, with the highest FPKM (fragments per kilobase of transcript per million fragments mapped) value of 24,704.87 in the venom apparatus, indicative of its significant role in successful parasitism by H. hebetor. The identification of these venom proteins establishes a foundation for the further exploration of bioactive agents for pest management strategies.

Hepatocellular carcinoma (HCC) is a highly aggressive malignancy, with high recurrence rates and notorious resistance to conventional chemotherapy. Cancer stemness refers to the stem-cell-like phenotype of cancer cells and has been recognized to play important roles in different aspects of hepatocarcinogenesis. Small extracellular vesicles (sEVs) are small membranous particles secreted by cells that can transfer bioactive molecules, such as nucleic acids, proteins, lipids, and metabolites, to neighboring or distant cells. Recent studies have highlighted the role of sEVs in modulating different aspects of the cancer stemness properties of HCC. Furthermore, sEVs derived from diverse cellular sources, such as cancer cells, stromal cells, and immune cells, contribute to the maintenance of the cancer stemness phenotype in HCC. Through cargo transfer, specific signaling pathways are activated within the recipient cells, thus promoting the stemness properties. Additionally, sEVs can govern the secretion of growth factors from non-cancer cells to further maintain their stemness features. Clinically, plasma sEVs may hold promise as potential biomarkers for HCC diagnosis and treatment prediction. Understanding the underlying mechanisms by which sEVs promote cancer stemness in HCC is crucial, as targeting sEV-mediated communication may offer novel strategies in treatment and improve patient outcome.

ESG has emerged as a prominent method for evaluating enterprises, gaining increasing importance in recent years. It assesses a company's ability to promote sustainable economic development and fulfill its social responsibilities, encompassing three non-financial dimensions: environmental, social, and corporate governance. Regulatory authorities, industry associations, and investment institutions worldwide have placed growing emphasis on a company's ESG performance. From the perspective of career concern, this study conducted a multiple regression analysis using data from Chinese A-share companies listed in Shanghai and Shenzhen from 2011 to 2020. It used CEO shareholding and CEO political affiliation as moderating variables to examine the impact of CEO career concerns on the corporate environment, society, and corporate governance performance. Empirical testing of whether CEO career concerns promote or suppress the ESG performance in enterprises. The findings of this study reveal that CEOs with heightened career concerns tend to impede the ESG performance of their respective enterprises. Additionally, CEO shareholding and political affiliations exert a negative moderating influence on the relationship between CEO career concerns and ESG performance. This research significantly extends the investigation into factors influencing ESG performance, offering fresh perspectives that could inform improved CEO oversight, foster corporate transformation, and enhance ESG performance.

Libman-Sacks endocarditis (LSE) is a cardiac condition characterized by the growth of verrucous vegetation. Although relatively rare in children, LSE is nevertheless a known cardiac manifestation of autoimmune diseases, including systemic lupus erythematosus (SLE). The mitral valve is the most commonly affected region, followed by the aortic valve, while the tricuspid and pulmonary valves are rarely affected. The management of established Libman-Sacks vegetation poses significant challenges, often necessitating surgical interventions, although surgery is not the primary treatment modality. Herein, we present the case of a 14-year-old Chinese female patient whose initial lupus manifestation included LSE, among other symptoms and signs that provided insights into the final diagnosis of SLE. After early comprehensive pharmacological treatment, tricuspid regurgitation and vegetation disappeared within 28 days without necessitating cardiac surgery, indicating that the resolution of LSE vegetation in this patient was achieved through a combination of immunosuppressive and anticoagulant therapy. These findings suggest the potential of this treatment approach as a viable model for the management of LSE in young patients.

When the gas pipeline leaks, it causes huge economic losses. This paper establishes a digital twin model of a pipeline based on the pressure signal generated by a pipeline leak and researches on pipeline leak detection. First, an online updating of the twin model is established to update the data of the physical information space and the parameters of the twin model online. Second, a visual model is established to display the spatial data of physical information of pipelines and output data of the digital twin of pipelines in real-time. If pipeline leakage is identified, an alarm would be triggered and a corresponding emergency rescue plan would be initiated based on the the leakage. Finally, the pipeline leakage identification model can be established by analysing the finite element model of the pipeline, and the sample data were obtained and preprocessed to extract the feature vectors. The training model of the Support vector machine (SVM) was used to classify the working conditions. Theoretical analysis and experimental results show that the method proposed in this paper has high detection accuracy, so it is feasible to judge gas pipeline leakage by using digital twin prediction.

This paper is concerned with the development of improved multi-strategy MPA-VMD method and its application in pipeline leakage detection. Aiming at the shortcomings of the marine predator algorithm (MPA) itself, which has a slow convergence speed and is easy to fall into local optimum, an improved MPA is proposed and used to find two important parameters in variational mode decomposition (VMD), and then dynamic entropy is used to select effective modes. In the initial stage of the population, a good point set strategy is adopted to enhance the search accuracy by increasing the diversity of the initial population; in the search process, a nonlinear convergence factor and the Cauchy distribution are introduced to optimize the predator step size to enhance the global search ability of the algorithm. The ability of the algorithm is enhanced to jump out of the local optimum, and the convergence speed of the algorithm is further improved; the effective mode after VMD is selected by the method of symbolic dynamic entropy. The experimental results show that compared with MPA-VMD, grey wolf optimization-VMD and particle swarm optimization-VMD methods, the devised method has improved signal-to-noise ratio, reduced mean square error and mean absolute error, and has better denoising effect.

Abstract. Glucose monitoring is an important part of medical care in diabetes mellitus, which not only helps assess glycemic control and treatment safety, but also assists with treatment adjustment. With the development of continuous glucose monitoring (CGM), the use of CGM has increased rapidly. With the wealth of glucose data produced by CGM, new metrics are greatly needed to optimally evaluate glucose status and guide the treatment. One of the parameters that CGM provides, time in range (TIR), has been recognized as a key metric by the international consensus. Before the adoption of TIR in clinical practice, several issues including the minimum length of CGM use, the setting of the target range, and individualized TIR goals are summarized. Additionally, we discussed the mounting evidence supporting the association between TIR and diabetes-related outcomes. As a novel glucose metric, it is of interest to compare TIR with other conventional glucose markers such as glycated hemoglobin A1c. It is anticipated that the use of TIR may provide further information on the quality of glucose control and lead to improved diabetes management.

BackgroundFunctional restoration of hemiplegic upper limbs is a difficult area in the field of neurological rehabilitation. Electrical stimulation is one of the treatments that has shown promising advancements and functional improvements. Most of the electrical stimulations used in clinical practice are surface stimulations. In this case, we aimed to investigate the feasibility of a minimally invasive, ultrasound-guided median nerve electrical stimulation (UG-MNES) in improving the upper limb motor function and activity of a patient with right-sided hemiparesis.Case presentationA 65-year-old male recovering from a left massive intracerebral hemorrhage after open debridement hematoma removal had impaired right limb movement, right hemianesthesia, motor aphasia, dysphagia, and complete dependence on his daily living ability. After receiving 3 months of conventional rehabilitation therapy, his cognitive, speech, and swallowing significantly improved but the Brunnstrom Motor Staging (BMS) of his right upper limb and hand was at stage I-I. UG-MNES was applied on the right upper limb for four sessions, once per week, together with conventional rehabilitation. Immediate improvement in the upper limb function was observed after the first treatment. To determine the effect of UG-MNES on long-term functional recovery, assessments were conducted a week after the second and fourth intervention sessions, and motor function recovery was observed after 4-week of rehabilitation. After completing the full rehabilitation course, his BMS was at stage V-IV, the completion time of Jebsen Hand Function Test (JHFT) was shortened, and the scores of Fugl-Meyer Assessment for upper extremity (FMA-UE) and Modified Barthel Index (MBI) were increased. Overall, the motor function of the hemiplegic upper limb had significantly improved, and the right hand was the utility hand. Electromyography (EMG) and nerve conduction velocity (NCV) tests were normal before and after treatment.ConclusionThe minimally invasive, UG-MNES could be a new alternative treatment in stroke rehabilitation for functional recovery of the upper limbs.

Abstract Wound healing is an urgent clinical challenge, particularly in the case of chronic wounds. Traditional approaches to wound healing have limited therapeutic efficacy due to lengthy healing times, risk of immune rejection, and susceptibility to infection. Recently, adipose‐derived mesenchymal stem cell‐derived exosomes (ADSC‐exos) have emerged as a promising modality for tissue regeneration and wound repair. In this study, the development of a novel extracellular matrix hydrogel@exosomes (ECM@exo) is reported, which entails incorporation of ADSC‐exos into an extracellular matrix hydrogel (ECM hydrogel). This solution forms a hydrogel at physiological temperature (≈37 °C) upon local injection into the wound site. ECM@exo enables sustained release of ADSC‐exos from the ECM hydrogel, which maintains high local concentrations at the wound site. The ECM hydrogel displays good biocompatibility and biodegradability. The in vivo and in vitro results demonstrate that ECM@exo treatment effectively reduces inflammation and promotes angiogenesis, collagen deposition, cell proliferation, and migration, thereby accelerating the wound healing process. Overall, this innovative therapeutic approach offers a new avenue for wound healing via a biological hydrogel with controlled exosome release.

This paper considers the problem of effective feature extraction of acoustic signals from oil and gas pipelines under different working conditions. A feature extraction of pipeline leakage detection method is proposed based on multi-feature entropy fusion and local linear embedding (LLE). First, seven kinds of commonly used entropy which can reflect the characteristics of the signal better are extracted from the pipeline signal through experiments, including permutation entropy, envelope entropy, approximate entropy, fuzzy entropy, energy entropy, sample entropy and dispersion entropy. The seven-dimensional feature vectors are obtained by feature fusion. Second, the LLE algorithm is used to reduce the dimension of the feature vector to complete the secondary feature extraction. Finally, the support vector machine (SVM) is used to identify the working conditions of the pipeline. The experimental results show that, compared with other dimensionality reduction methods, single-feature entropy method and multi-feature entropy fusion method, the proposed method can identify the types of pipeline working conditions effectively and reduce the problems of false negatives and false positives in pipeline leakage detection.

Abstract Background Growth differentiation factor 15 (GDF15) was newly discovered to be a promising target of metformin. The study was aimed to investigate the relationship between GDF15 and glycemic control after metformin treatment in patients with type 2 diabetes mellitus. Methods The study was a post-hoc analysis of AIM (the effect of Acarbose on glycemic variability in patients with type 2 diabetes mellitus using premixed Insulin compared to Metformin) study. The participants were randomly assigned to 12 weeks of metformin (MET) or acarbose (ACA) treatment combined with insulin. Serum GDF15 levels of 51 subjects from MET group and 53 subjects from ACA group were measured at baseline and after a 12-week treatment. Fasting plasma glucose (FPG), 2-h postprandial plasma glucose (2-h PG) and glycated hemoglobin A1c (HbA1c) were measured at baseline and endpoint. Results After a 12-week treatment, serum GDF15 levels significantly increased in MET group [baseline vs. endpoint, 936.70 (741.00, 1205.40) pg/mL vs. 1265.20 (1027.90, 1634.00) pg/mL, P 0.05). Spearman correlation coefficient and analysis of covariance after adjustment for baseline HbA1c levels showed that ΔGDF15 was not correlated with ΔFPG, Δ2-h PG and ΔHbA1c (all P > 0.05). Conclusion Serum GDF15 levels were significantly elevated after metformin treatment in patients with type 2 diabetes mellitus. However, the increase was not an indicator of the glucose-lowering effect of metformin. Trial registration Clinicaltrials.gov, NCT02438397 . Registered 8 May 2015.

Abstract Exosomes belong to a subpopulation of extracellular vesicles secreted by the dynamic multistep endocytosis process and carry diverse functional molecular cargoes, including proteins, lipids, nucleic acids (DNA, messenger and noncoding RNA), and metabolites to promote intercellular communication. Proteins and noncoding RNA are among the most abundant contents in exosomes; they have biological functions and are selectively packaged into exosomes. Exosomes derived from tumor, stromal and immune cells contribute to the multiple stages of cancer progression as well as resistance to therapy. In this review, we will discuss the biogenesis of exosomes and their roles in cancer development. Since specific contents within exosomes originate from their cells of origin, this property allows exosomes to function as valuable biomarkers. We will also discuss the potential use of exosomes as diagnostic and prognostic biomarkers or predictors for different therapeutic strategies for multiple cancers. Furthermore, the applications of exosomes as direct therapeutic targets or engineered vehicles for drugs are an important field of exosome study. Better understanding of exosome biology may pave the way to promising exosome-based clinical applications.

Abstract Aims/introduction We proposed a novel continuous glucose monitoring (CGM)‐based metric, area under the curve in range (AucIR), for integrating both the amplitude and duration of dysglycemia, and further compared AucIR with the emerging key CGM‐derived metric, time in range (TIR). Materials and methods A total of 2,030 adult patients with type 2 diabetes were enrolled during May 2020 to October 2021. AucIR and TIR were measured with 7‐day CGM data. Logistic regression analysis and the C‐statistic was carried out to assess the association of AucIR and TIR with diabetic retinopathy (DR). Results Both AucIR (r = −0.89) and TIR (r = −0.95) were strongly correlated with mean glucose levels. Compared with TIR, AucIR showed a tighter relationship with parameters of glycemic variability, including the coefficient of variation (r = −0.56), standard deviation (r = −0.89) and mean amplitude of glycemic excursions (r = −0.70). For each absolute 10% decrease in AucIR, the risk of DR was increased by 7% (95% confidence interval 1.02–1.13) after adjustment for confounders. With respect to TIR, each absolute 10% decrease was associated with an 8% (95% confidence interval 1.03–1.14) increased risk of DR. The model discrimination for DR, as measured by C‐statistic, did not differ significantly between the two metrics (P > 0.05). Conclusions AucIR did not provide added benefit over TIR in the assessment of DR risk among patients with type 2 diabetes. The potential value of AucIR needs to be explored in future studies.

Traffic flow prediction is a very important research field in intelligent transportation system. The traditional prediction methods have a very wide application in traffic flow prediction. However, in the short-term traffic flow prediction, due to the complexity of its influencing factors, the traditional prediction methods cannot predict the short-term traffic flow well. In this paper, the short-term traffic flow prediction model is constructed by using the short-term and short-term memory network, and the modal aliasing problem is solved by using the variational modal decomposition. From the experimental results, the method proposed in this paper is very suitable for short-term traffic flow prediction, and can achieve good prediction effect and accuracy.

It is essential to establish a digital twin scene, which helps to depict the dynamically changing geographical environment accurately. Digital twins could improve the refined management level of intelligent tunnel construction; however, research on geographical twin models primarily focuses on modeling and visual description, which has low analysis efficiency. This paper proposes a knowledge-guided intelligent analysis method for the geometric deformation of tunnel excavation profile twins. Firstly, a dynamic data-driven knowledge graph of tunnel excavation twin scenes was constructed to describe tunnel excavation profile twin scenes accurately. Secondly, an intelligent diagnosis algorithm for geometric deformation of tunnel excavation contour twins was designed by knowledge guidance. Thirdly, multiple visual variables were jointly used to support scene fusion visualization of tunnel excavation profile twin scenes. Finally, a case was selected to implement the experimental analysis. The experimental results demonstrate that the method in this article can achieve an accurate description of objects and their relationships in tunnel excavation twin scenes, which supports rapid geometric deformation analysis of the tunnel excavation profile twin. The speed of geometric deformation diagnosis is increased by more than 90% and the cognitive efficiency is improved by 70%. The complexity and difficulty of the deformation analysis operation are reduced, and the diagnostic analysis ability and standardization of the geographic digital twin model are effectively improved.

Abstract. Background:. Corneal confocal microscopy (CCM) is a noninvasive technique to detect early nerve damage of diabetic sensorimotor polyneuropathy (DSPN). Time in range (TIR) is an emerging metric of glycemic control which was reported to be associated with diabetic complications. We sought to explore the relationship between TIR and corneal nerve parameters in asymptomatic patients with type 2 diabetes (T2DM). Methods:. In this cross-sectional study, 206 asymptomatic inpatients with T2DM were recruited. After 7 days of continuous glucose monitoring, the TIR was calculated as the percentage of time in the glucose range of 3.9 to 10.0 mmol/L. CCM was performed to determine corneal nerve fiber density, corneal nerve branch density, and corneal nerve fiber length (CNFL). Abnormal CNFL was defined as ≤15.30 mm/mm2. Results:. Abnormal CNFL was found in 30.6% (63/206) of asymptomatic subjects. Linear regression analyses revealed that TIR was positively correlated with CCM parameters both in the crude and adjusted models (all P

Abstract. Background:. Little was known about the association among time in range (TIR), time above range (TAR), time below range (TBR), and cancer mortality among patients with type 2 diabetes. We aimed to investigate the association among TIR, TAR, TBR, and the risk of cancer mortality among patients with type 2 diabetes. Methods:. A total of 6225 patients with type 2 diabetes were prospectively recruited in Shanghai, China. TIR was measured with continuous glucose monitoring at baseline and was defined as the average percentage of time in the target glucose range during a 24 h period. Cox proportion hazard regression analysis was used to determine the association between TIR and the risk of cancer mortality. Results:. During a mean follow-up of 7.10 years, we confirmed 237 death events related to cancer. The multivariable-adjusted hazard ratio (HR) for cancer mortality was 1.32 (95% confidence interval [CI]: 1.01–1.75) in patients with TIR ≤70% compared with those with TIR >70%. When TIR was considered as a continuous variable, the multivariable-adjusted HR for cancer mortality associated with each 10% decrease in TIR was 1.07 (95% CI: 1.02–1.14). In the site-specific analysis, a significant association between TIR as a continuous variable and the risk of hepatocellular cancer was found (HR: 1.24; 95% CI: 1.09–1.41). However, no relationship between hemoglobin A1c and cancer mortality was observed (HR: 1.04; 95% CI: 0.97–1.10). Conclusions:. The present study found an inverse association of TIR with the risk of cancer mortality among patients with type 2 diabetes. New evidence of TIR was added into the clinical practice that TIR may be an optimal target of glycemic control among patients with type 2 diabetes.

WEE1 has emerged as an attractive target in epithelial ovarian cancer (EOC), but how EOC cells may alter their sensitivity to WEE1 inhibition remains unclear. Here, through a cell cycle machinery–related gene RNAi screen, we found that targeting outer dense fiber of sperm tails 2–like (ODF2L) was a synthetic lethal partner with WEE1 kinase inhibition in EOC cells. Knockdown of ODF2L robustly sensitized cells to treatment with the WEE1 inhibitor AZD1775 in EOC cell lines in vitro as well as in xenografts in vivo. Mechanistically, the increased sensitivity to WEE1 inhibition upon ODF2L loss was accompanied by accumulated DNA damage. ODF2L licensed the recruitment of PKMYT1, a functionally redundant kinase of WEE1, to the CDK1–cyclin B complex and thus restricted the activity of CDK1 when WEE1 was inhibited. Clinically, upregulation of ODF2L correlated with CDK1 activity, DNA damage levels, and sensitivity to WEE1 inhibition in patient-derived EOC cells. Moreover, ODF2L levels predicted the response to WEE1 inhibition in an EOC patient–derived xenograft model. Combination treatment with tumor-targeted lipid nanoparticles that packaged ODF2L siRNA and AZD1775 led to the synergistic attenuation of tumor growth in the ID8 ovarian cancer syngeneic mouse model. These data suggest that WEE1 inhibition is a promising precision therapeutic strategy for EOC cells expressing low levels of ODF2L.

Objective To explore the clinical value of autoantibody-based subgroup framework and the trend of autoantibody fluctuation in juvenile-onset SLE (JSLE).Methods Eighty-seven patients with JSLE were retrospectively collected and divided into subgroups via a two-step cluster based on the status of nine autoantibodies (double-stranded-DNA (dsDNA), nucleosome, histone, ribosomal P protein, Smith (Sm), u1-ribonucleoprotein (RNP), Sjögren’s syndrome antigen A (SSA)/Ro52, SSA/Ro60, Sjögren’s syndrome antigen B (SSB)/La). The final model selected in this study was based on adequate goodness of fit of the Silhouette coefficient and clinical interpretability. Clinical manifestations, organ involvements and disease activity were compared among the subgroups. Fluctuation in autoantibody status was also collected and analysed. Flare-free survival rates of the patients with positive/negative seroconversion and patients without seroconversion were studied by the Kaplan-Meier method and compared using a log-rank test.Results Two clusters were identified: subgroup 1 (positive anti-Sm/RNP group) and subgroup 2 (negative anti-Sm/RNP group). There were more lupus nephritis (LN) and neuropsychiatric SLE (NPSLE) cases in subgroup 1 than in subgroup 2. Patients in subgroup 1 exhibited higher SLE Disease Activity Index scores compared with those in subgroup 2. Furthermore, anti-ribosomal P protein (61.1%), anti-nucleosome (58.3%) and anti-dsDNA (54%) were most commonly positive autoantibodies. A progressive decrease in the frequency of patients with positive results was demonstrated during the follow-up years. The decrease was notable for anti-dsDNA, anti-nucleosome and anti-ribosomal P protein (remaining 27.27%, 38.89% and 45.00% positive in the fifth year, respectively). While for those negative at baseline diagnosis, the decrease in the frequency of negative results was progressive but modest. Kaplan-Meier curve showed that the flare-free survival of patients with positive seroconversion was significantly lower than those without seroconversion and those with negative seroconversion (p

Protein-bound uremic toxins (PBUTs) are associated with the progression of chronic kidney disease (CKD) and its associated morbidity and mortality. The conventional dialysis techniques are unable to efficiently remove PBUTs due to their plasma protein binding. Therefore, novel approaches are being developed, but these require validation in animals before clinical trials can begin. We conducted a systematic review to document PBUT concentrations in various models and species. The search strategy returned 1163 results for which abstracts were screened, resulting in 65 full-text papers for data extraction (rats (n = 41), mice (n = 17), dogs (n = 3), cats (n = 4), goats (n = 1), and pigs (n = 1)). We performed descriptive and comparative analyses on indoxyl sulfate (IS) concentrations in rats and mice. The data on large animals and on other PBUTs were too heterogeneous for pooled analysis. Most rodent studies reported mean uremic concentrations of plasma IS close to or within the range of those during kidney failure in humans, with the highest in tubular injury models in rats. Compared to nephron loss models in rats, a greater rise in plasma IS compared to creatinine was found in tubular injury models, suggesting tubular secretion was more affected than glomerular filtration. In summary, tubular injury rat models may be most relevant for the in vivo validation of novel PBUT-lowering strategies for kidney failure in humans.

Accurate and reliable fault location is necessary for ensuring the safe and reliable operation of the VSC-HVDC transmission system. This paper proposed a single-terminal fault location method based on the fault transient characteristics of the two-terminal VSCHVDC transmission system. The pole-to-pole transient fault process was divided into three stages, the time-domain expression of the DC current during the diode freewheel stage was used to locate the fault point, and a criterion for judging whether the fault evolves to the diode freewheel stage was proposed. Taking into account the enhancing effect of the opposite system to the fault current, theDCside pole-to-ground fault networkwas equated to a fourth-order circuit model, the relationship of fault distance with the characteristic roots of fault current differential equationwas derived, and the Prony algorithmwas utilized for datafitting to extract characteristic roots to realize fault location. A two-terminal VSC-HVDC transmission system was modelled in PSCAD/EMTDC. The simulation result verifies that the proposed principle can accurately locate the fault point on the VSC-HVDC transmission lines.

Abstract Aims/Introduction To define the target value for the percentage coefficient of variation for glucose (%CV) as a measure of glycemic variability (GV) in Chinese diabetes patients. Materials and Methods This retrospective study included 3,007 diabetes patients who underwent continuous glucose monitoring for 3 days. Type 2 diabetes was divided into groups according to the received treatment: group 1, non‐insulinotropic agent (n = 138); group 2, insulinotropic agent (n = 761); group 3, basal insulin therapy (n = 100); group 4, premixed insulin (n = 784); and group 5, intensive insulin therapy (n = 612). Type 1 diabetes patients were included as group 6 (n = 612). %CV and percentage of time per day within, below (3.9mmol/L; TBR3.9) and above (10.0 mmol/L) the target glucose range (3.9–10.0 mmol/L) were computed. TBR3.9 ≥4% was defined as excessive hypoglycemia. Results Type 2 diabetes with a premixed or intensive insulin regimen had an increased %CV compared with those receiving oral therapy or basal insulin. The upper limit of %CV in group 1 was 33%, which was adopted as the threshold to define excessive GV. For each treatment group, the percentage of people with TBR3.9 ≥4% was significantly greater in the subgroup with %CV >33% than ≤33% (P 70% and time per day above 10.0 mmol/L

Due to the large amount of noise in pipeline leakage signal, the accuracy of the leakage detection device's judgment will be reduced by direct leakage detection. Therefore, the noise reduction of pipeline leakage signal is critical for preprocessing technology of pipeline leakage detection. A denoising method combining adaptive variational mode decomposition (AVMD) and singular value decomposition (SVD) is proposed in this paper. First, the mode number and the penalty factor of VMD are searched automatically by AVMD. The AVMD algorithm is coupled to a fitness function based on improved refine composite multiscale dispersion entropy (RCMDE). Subsequently, a time–frequency matrix which obtains time–frequency subspace after SVD is constructed for all mode components decomposed by VMD, and the number of effective time–frequency subspaces is determined by the relative change rate of singular values, thereby the denoised signal is achieved. Finally, the experimental results show that the AVMD-SVD method proposed in this paper has the significant denoising effect and strong robustness.

Abstract Background The aim of this study was to investigate the association of visit-to-visit variability of hemoglobin A1c (HbA1c) and glycated albumin (GA) with the risk of lower extremity atherosclerotic disease (LEAD). Method We performed a prospective cohort study of 436 patients with type 2 diabetes (258 men and 178 women) with at least 3 measurements of HbA1c and GA prior to baseline investigation from the Department of Endocrinology and Metabolism, Shanghai Sixth People’s Hospital. Different HbA1c and GA variability markers were calculated. Multivariable Cox proportional hazard regression models were used to demonstrate the association between visit-to-visit HbA1c and GA variability and the risk of incident or progressive LEAD. Results During a mean follow-up period of 3.77 years, 112 participants developed LEAD. Multivariate-adjusted hazard ratios (HRs) of LEAD across tertiles of GA-CV values were 1.00, 1.06 (95% confidence interval [CI] 0.65–1.75), and 1.71 (95% CI 1.07–2.73) (P for trend = 0.042), respectively. When we used GA-VIM and GA-ARV values as exposures, similar positive associations with the risk of LEAD primary were found. Multivariate-adjusted HRs of LEAD for each 1 unit increase in GA-CV, GA-VIM and GA-ARV were 1.03 (95% CI 1.01–1.06), 1.32 (95% CI 1.03–1.69), and 1.07 (95%CI 1.01–1.15), respectively. However, there was no significant association between visit-to-visit variability of HbA1c and the risk of LEAD. Conclusions Visit-to-visit variability of GA may be an optimal biomarker in relation to LEAD risk among patients with type 2 diabetes.

Abstract High‐performance transition metal chalcogenides (TMCs) as electrocatalysts for two‐electron oxygen reduction reaction (2e‐ORR) in alkaline medium are promising for hydrogen peroxide (H2O2) production, but their synthesis remains challenging. In this work, a titanium‐doped zinc–cobalt sulfide hollow superstructure (Ti–ZnCoS HSS) is rationally designed as an efficient electrocatalyst for H2O2 electrosynthesis. Synthesized by using hybrid metal–organic frameworks (MOFs) as precursors after sulfidation treatment, the resultant Ti–ZnCoS HSS exhibits a hollow‐on‐hollow superstructure with small nanocages assembled around a large cake‐like cavity. Both experimental and simulation results demonstrate that the polymetallic composition tailors the d‐band center and binding energy with oxygen species. Moreover, the hollow superstructure provides abundant active sites and promotes mass and electron transfer. The synergistic d‐band center and superstructure engineering at both atomic and nanoscale levels lead to the remarkable 2e‐ORR performance of Ti–ZnCoS HSS with a high selectivity of 98%, activity (potential at 1 mA cm−2 of 0.774 V vs reversible hydrogen electrode (RHE)), a H2O2 production rate of 675 mmol h–1 gcat–1, and long‐term stability in alkaline condition, among the best 2e‐ORR electrocatalysts reported to date. This strategy paves the way toward the rational design of polymetallic TMCs as advanced 2e‐ORR catalysts.

Maximizing is characterized by aspirations for the highest standards. The current study explored the relationship between maximizing and risk-taking tendencies in decisions subject to risk. We propose that people first refer to expectation (i.e., the overall utility expected from an alternative) when taking risky decisions. If expectation clearly identifies the best option, maximizing will not be correlated with risk-taking tendencies. If not, people refer to maximizing to reach a decision. Maximizing will be positively associated with risk-taking tendencies because the “upper bound” of risky options helps achieve the goal of seeking the best. Four studies showed that risk-taking tendencies increased with maximizing when the options had similar expectations (Studies 1 to 3). When expectations between options were clearly different (vs. similar), the positive relationship between maximizing and risk-taking tendencies was reduced (Study 4). These findings provide an insight into how maximizing is related to risk seeking.

In this paper, an image denoising algorithm is presented based on the two-dimensional variational mode decomposition (2D-VMD) and the Hausdorff distance (HD). The procedure of the developed algorithm is that: (1) use the 2D-VMD to decompose the image into a number of intrinsic mode functions (IMFs); (2) use the HD and the probability density function (PDF) to distinguish the signal-dominant IMFs (S-D IMFs) and the noise-dominant IMFs (N-D IMFs), and then use the wavelet threshold denoising method to eliminate the noise in the N-D IMFs; and (3) use the denoised IMFs and the S-D IMFs to reconstruct the image and obtain the denoised image. The effectiveness of the proposed algorithm is verified on the oil pipeline images. Simulation results show that, compared with the median filtering, the wavelet threshold filtering, and the Rudin Osher Fatemi, the proposed algorithm has a better denoising effect in both subjective and objective evaluation.

This paper is concerned with the pipeline leakage detection problem. A pipeline signal feature extraction method based on improved variational mode decomposition (VMD) and multi-feature fusion are proposed. First of all, the mode number K-value of VMD decomposition is determined by combining the empirical mode decomposition (EMD) method and the centre frequency method. Next, according to the variance contribution rates, the effective mode components are selected from the mode components obtained by VMD, subsequently, the effective mode components are reconstructed to get the de-noised signal. Then, the characteristic parameters that might distinguish the different pipeline signals are selected from different aspects. Moreover, the selected characteristic parameters are formed feature vector to put into support vector machine (SVM) to recognize the different pipeline events. Finally, the laboratory pipeline samples are employed to verify the effectiveness and superiority of the proposed method.

The pathogenicity of foodborne Vibrio parahaemolyticus is a major concern for global public health. This study aimed to optimize the liquid–solid extraction of Wu Wei Zi extracts (WWZE) against Vibrio parahaemolyticus, identify its main components, and investigate the anti-biofilm action. The extraction conditions optimized by the single-factor test and response surface methodology were ethanol concentration of 69%, temperature at 91 °C, time of 143 min, and liquid–solid ratio of 20:1 mL/g. After high performance liquid chromatography (HPLC) analysis, it was found that the main active ingredients of WWZE were schisandrol A, schisandrol B, schisantherin A, schisanhenol, and schisandrin A–C. The minimum inhibitory concentration (MIC) of WWZE, schisantherin A, and schisandrol B measured by broth microdilution assay was 1.25, 0.625, and 1.25 mg/mL, respectively, while the MIC of the other five compounds was higher than 2.5 mg/mL, indicating that schisantherin A and schizandrol B were the main antibacterial components of WWZE. Crystal violet, Coomassie brilliant blue, Congo red plate, spectrophotometry, and Cell Counting Kit-8 (CCK-8) assays were used to evaluate the effect of WWZE on the biofilm of V. parahaemolyticus. The results showed that WWZE could exert its dose-dependent potential to effectively inhibit the formation of V. parahaemolyticus biofilm and clear mature biofilm by significantly destroying the cell membrane integrity of V. parahaemolyticus, inhibiting the synthesis of intercellular polysaccharide adhesin (PIA), extracellular DNA secretion, and reducing the metabolic activity of biofilm. This study reported for the first time the favorable anti-biofilm effect of WWZE against V. parahaemolyticus, which provides a basis for deepening the application of WWZE in the preservation of aquatic products.

Introduction Mining knowledge from continuous glucose monitoring (CGM) data to classify highly heterogeneous patients with type 2 diabetes according to their characteristics remains unaddressed. A refined clustering method that retrieves hidden information from CGM data could provide a viable method to identify patients with different degrees of dysglycemia and clinical phenotypes.Research design and methods From Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, we selected 908 patients with type 2 diabetes (18–83 years) who wore blinded CGM sensors (iPro2, Medtronic, California, USA). Participants were clustered based on CGM data during a 24-hour period by our method. The first level extracted the knowledge-based and statistics-based features to describe CGM signals from multiple perspectives. The Fisher score and variables cluster analysis were applied to fuse features into low dimensions at the second level. The third level divided subjects into subgroups with different clinical phenotypes. The four subgroups of patients were determined by clinical phenotypes.Results Four subgroups of patients with type 2 diabetes with significantly different statistical features and clinical phenotypes were identified by our method. In particular, individuals in cluster 1 were characterized by the lowest glucose level factor and glucose fluctuation factor, and the highest negative glucose factor and C peptide index. By contrast, cluster 2 had the highest glucose level factor and the lowest C peptide index. Cluster 4 was characterized by the greatest degree of glucose fluctuation factor, was the most insulin-sensitive, and had the lowest insulin resistance. Cluster 3 ranked in the middle concerning the CGM-derived metrics and clinical phenotypes compared with those of the other three groups.Conclusion A novel multilevel clustering approach for knowledge mining from CGM data in type 2 diabetes is presented. The results demonstrate that subgroups are adequately distinguished with notable statistical and clinical differences.

Information sharing on social media [i.e., electronic word-of-mouth, (eWOM) and face-to-face word-of-mouth (fWOM)] plays an important role in message dissemination. This study investigates the effectiveness of group norms in motivating eWOM and fWOM. Drawing upon the psychological distance and construal level literature, this study tests the impact of group norms, the interaction effect of norms type (descriptive vs. injunctive norms), and the group distance on eWOMand fWOM. Based on one field study and three laboratory experiments, this study finds that normative cues in messages are impactful in driving WOM and the impact becomes especially stronger when the psychological distance of the social group is congruent with that of norms type tied to the group. Specifically, an interaction effect emerges, such as distant (close) group injunctive (descriptive) norms, are more impactful in driving WOM than close (distant) group injunctive (descriptive) norms. Contrary to the conventional wisdom that a close group has greater impacts than distant groups in terms of social influence, this study shows that messages with distant groups are more (or at least equally) likely to be shared than with a close group when tied with injunctive norms. The findings suggest that group norms are perceived to be more relevant when there is a match between the psychological distance of the social group and the norms type tied to the group.

Chronic obstructive pulmonary disease (COPD), often caused by smoking, is a chronic lung disease with systemic manifestations including metabolic comorbidities. This study investigates adaptive and pathological alterations in adipose and skeletal muscle tissue following cigarette smoke exposure using in vivo and in vitro models. Mice were exposed to cigarette smoke or air for 72 days and the pre-adipose cell line 3T3-L1 was utilized as an in vitro model. Cigarette smoke exposure decreased body weight, and the proportional loss in fat mass was more pronounced than the lean mass loss. Cigarette smoke exposure reduced adipocyte size and increased adipocyte numbers. Adipose macrophage numbers and associated cytokine levels, including interleukin-1β, interleukine-6 and tumor necrosis factor-α were elevated in smoke-exposed mice. Muscle strength and protein synthesis signaling were decreased after smoke exposure; however, muscle mass was not changed. In vitro studies demonstrated that lipolysis and fatty acid oxidation were upregulated in cigarette smoke-exposed pre-adipocytes. In conclusion, cigarette smoke exposure induces a loss of whole-body fat mass and adipose atrophy, which is likely due to enhanced lipolysis.

Abstract Aims/Introduction The relationship between glycemic variability (GV) and diabetic complications has gained much interest and remains under debate. Furthermore, the association of GV with diabetic complications has not been examined in latent autoimmune diabetes of the adult (LADA). Therefore, we evaluated the relationships among several metrics of GV with diabetic retinopathy (DR) in patients with LADA and type 2 diabetes mellitus. Materials and Methods A total of 192 patients with LADA and 2,927 patients with type 2 diabetes mellitus were enrolled. After continuous glucose monitoring for 72 h, three metrics of GV including standard deviation, coefficient of variation and mean amplitude of glycemic excursions were calculated. DR was assessed by fundus photography performed with a digital non‐mydriatic camera. Results The prevalence of DR was 20.3 and 26.4% in LADA and type 2 diabetes mellitus patients (P

Periodontitis is a multifactorial chronic infectious disease leading to a host immune response involving inflammatory cytokines, especially IL-1β, which is the main reason for further developing this disease. IL-1 receptor antagonist (IL-1ra) binds IL-1 receptor, inhibiting IL-1β signaling and reducing the levels of other cytokines closely related to periodontitis, such as IL-6 and TNF-α. Therefore, the use of IL-1ra to inhibit periodontitis development in a system, ensuring its sustained release, might be an effective way to combat this disease. Hence, in this study, a novel IL-1ra-loaded dextran/PLGA microsphere was developed to allow the sustained release of IL-1ra and enhance the anti-inflammatory properties. Therefore, this study’s purposes were to develop a novel periodontal treatment for inhibition and treatment of periodontitis and evaluate the sustained-release effect and anti-inflammatory properties of IL-1ra-loaded dextran/PLGA microspheres in vitro by cell experiments and in vivo by animal experiments. The results showed that IL-1ra-loaded dextran/PLGA microspheres were non-toxic both in vitro and in vivo and could be used as a safe and effective treatment. In addition, these microspheres could significantly prolong the half-life of IL-1ra drug, exerting a useful anti-inflammatory effect in macrophages stimulated with P. gingivalis lipopolysaccharide and in rats with periodontitis. In conclusion, IL-1ra-loaded dextran/PLGA microsphere might be a useful tool to combat periodontal disease.

Fintech has not changed the nature and risk attributes of financial business. Its openness, interoperability, and other characteristics trigger the concealment, infectivity, universality and sudden characteristics of financial risk more obviously, and the potential systemic risk more complexly. This paper adopts fuzzy set analysis to conduct a comprehensive review of Fintech risk. It is found that the technology risk, moral hazard and legal risk, with a weight of up to 80%, are the dominant factors affecting the Fintech risk, while other prominent credit risk, market risk and operational risk in the traditional financial field account for a small proportion, but they still cannot be ignored. The research of this paper enriches the relevant research on the quantification of Fintech risk, and helps to strengthen risk prevention from the aspect of enhancing the safety of Fintech infrastructure, improving the legal system, sound the regulatory framework and strengthening industry self-discipline.

Background. Fulminant type 1 diabetes mellitus (FT1DM) onsets abruptly and usually occurs within 1 week after the onset of hyperglycemic symptoms. Glycated albumin (GA) and 1,5-anhydroglucitol (1,5-AG) are indicators that reflect short-term glucose levels. This study was aimed at investigating whether the 1,5-AG/GA index (AGI) is a suitable indicator for early FT1DM identification. Methods. A total of 226 subjects were enrolled, all with glycated hemoglobin A1c HbA1c

Objective. The aim of this study was to explore the association of 1,5-anhydroglucitol with acute C peptide response (ACPR) to arginine among patients with type 2 diabetes. Methods. Patients with type 2 diabetes were enrolled from the Department of Endocrinology and Metabolism, Shanghai Sixth People’s Hospital. ACPR was assessed using arginine stimulation test. Decreased β-cell function was defined as ACPR

Nocturnal hypoglycemia is a serious complication of insulin-treated diabetes, and it is often asymptomatic. A novel CGM metric-gradient was proposed in this paper, and a method of combining mean sensor glucose (MSG) and gradient was presented for the prediction of nocturnal hypoglycemia. For this purpose, the data from continuous glucose monitoring (CGM) encompassing 1,921 patients with diabetes were analyzed, and a total of 302 nocturnal hypoglycemic events were recorded. The MSG and gradient values were calculated, respectively, and then combined as a new metric (i.e., MSG+gradient). In addition, the prediction was conducted by four algorithms, namely, logistic regression, support vector machine, random forest, and long short-term memory. The results revealed that the gradient of CGM showed a downward trend before hypoglycemic events happened. Additionally, the results indicated that the specificity and sensitivity based on the proposed method were better than the conventional metrics of low blood glucose index (LBGI), coefficient of variation (CV), mean absolute glucose (MAG), lability index (LI), etc., and the complex metrics of MSG+LBGI, MSG+CV, MSG+MAG, and MSG+LI, etc. Specifically, the specificity and sensitivity were greater than 96.07% and 96.03% at the prediction horizon of 15 minutes and greater than 87.79% and 90.07% at the prediction horizon of 30 minutes when the proposed method was adopted to predict nocturnal hypoglycemic events in the aforementioned four algorithms. Therefore, the proposed method of combining MSG and gradient may enable to improve the prediction of nocturnal hypoglycemic events. Future studies are warranted to confirm the validity of this metric.

Establishing accurate electrical load prediction is vital for pricing and power system management. However, the unpredictable behavior of private and industrial users results in uncertainty in these power systems. Furthermore, the utilization of renewable energy sources, which are often variable in their production rates, also increases the complexity making predictions even more difficult. In this paper an interval type-2 intuitionist fuzzy logic system whose parameters are trained in a hybrid fashion using gravitational search algorithms with the ridge least square algorithm is presented for short-term prediction of electrical loading. Simulation results are provided to compare the performance of the proposed approach with that of state-of-the-art electrical load prediction algorithms for Poland, and five regions of Australia. The simulation results demonstrate the superior performance of the proposed approach over seven different current state-of-the-art prediction algorithms in the literature, namely: SVR, ANN, ELM, EEMD-ELM-GOA, EEMD-ELM-DA, EEMD-ELM-PSO and EEMD-ELM-GWO.

Abstract Mesenchymal stem cells (MSCs) are capable of exerting strong therapeutic potential for the treatment of supraspinatus tendon tear. However, MSC therapy remains underutilized and perhaps underrated due to the limited evidence of dynamic visualization of cellular behavior in vivo. Here, second near‐infrared fluorescence imaging with biocompatible PbS quantum dots (QDs) provides a cellular migration map and information on the biodistribution and clearance processes of three densities of intra‐articularly injected, labeled MSCs to treat supraspinatus tendon tear in mice. Intra‐articular injection avoids entrapment of MSCs by filter organs and reduces the QD‐induced organ toxicity. Notably, the MSCs share a similar migration direction, but the moderate density group is somewhat more efficient, showing the longest residence time and highest cell retention rate around the footprint during the repair stage. Furthermore, quantitative kinetic investigation demonstrates that labeled MSCs are cleared by feces and urine. Histomorphometric analysis demonstrates that the moderate density group achieves maximum therapeutic effect and labeled MSCs do not induce any injury or inflammation to major organs, which suggests that administration of too many or few MSCs may decrease their effectiveness. Such an imaging approach provides spatiotemporal evidence for response to MSC therapy in vivo, facilitating the optimization of MSC therapy.