Comparison of Bisphosphonates Versus Teriparatide in Therapy of the Glucocorticoid-Induced Osteoporosis (GIOP): A Meta-Analysis of Randomized Controlled Trials

Osteoporosis (OP) is characterized as decreased bone mineral density (BMD) and increased risk of bone fracture. Secondary OP resulting from excess endogenous or exogenous glucocorticoid is defined as glucocorticoid-induced osteoporosis (GIOP). Current therapeutic strategies for GIOP are similar to menopausal osteoporosis, including calcium and vitamin D supplementation, bisphosphonates, and parathyroid hormone (PTH) analogues (teriparatide). Previously, several published meta-analyses compared anti-osteoporotic agents for the menopausal or aging-dependent OP. However, the physiopathologic bone metabolism of GIOP is different. In this study, we investigated the efficacy of BMD enhancement, bone fracture rate and safety of bisphosphonates versus teriparatide in the therapy of GIOP. We searched databases including PubMed, Embase, and the Cochrane Library until Jan 2023, and selected ten random clinical trials (RCT)s that compared the efficacy and/or safety of bisphosphonate versus teriparatide for GIOP patients. Teriparatide therapy increased lumber spinal BMD by 3.96% (95% CI 3.01-4.9%, p<0.00001), 1.23% (95% CI 0.36-2.1%, p=0.006) at total hip, and 1.45% (95% CI 0.31-2.58%, p=0.01) at femoral neck, respectively, compared to bisphosphonates at 18-month therapy for GIOP. Teriparatide also reduced bone fracture especially in vertebral bone (p=0.0001, RR 6.27, 95% CI 2.44-16.07), and increased bone formation and resorption marker levels. There was no difference in the incidence of adverse effects in bisphosphonate and teriparatide groups. Teriparatide showed better performance over bisphosphonate in BMD enhancement, bone fracture reduction, and bone remodeling improvement, without increasing the incidence of adverse effects.

Disease perception and experience in people with diabetic retinopathy: A qualitative study

AIM

The aim of this study was to investigate the lived experience of people with diabetic retinopathy and to understand the impact of the disease on them including the practical problems faced in the day-to-day life.

DESIGN

Descriptive qualitative research.

METHODS

A convenience sample of 11 patients with diabetic retinopathy who were hospitalized in a tertiary hospitals in Shandong province of China were enrolled. Data were collected using semi-structured in-depth interviews. The six-stage thematic analysis of Braun and Clarke was used for data analysis.

RESULTS

Three themes and 12 sub-themes were extracted, namely: countdown to darkness (lack of disease knowledge, bystander's perspective, distrust of grassroots hospitals); Endless abyss (action restrictions, social isolation, stigma, lost of meaning in life, catastrophizing explanations, a heavy burden); Light chaser (craving for light, turning points in behaviour, self-adjustment).

Object-Occluded Human Shape and Pose Estimation With Probabilistic Latent Consistency

Occlusions between human and objects, especially for the activities of human-object interactions, are very common in practical applications. However, most of the existing approaches for 3D human shape and pose estimation require that human bodies are well captured without occlusions or with minor self-occlusions. In this paper, we focus on the problem of directly estimating the object-occluded human shape and pose from single color images. Our key idea is to utilize a partial UV map to represent an object-occluded human body, and the full 3D human shape estimation is ultimately converted as an image inpainting problem. We propose a novel two-branch network architecture to train an end-to-end regressor via a latent distribution consistency, which also includes a novel visible feature sub-net to extract the human information from object-occluded color images. To supervise the network training, we further build a novel dataset named as 3DOH50K. Several experiments are conducted to reveal the effectiveness of the proposed method. Experimental results demonstrate that the proposed method achieves state-of-the-art compared with previous methods. The dataset and codes are publicly available at https://www.yangangwang.com/papers/ZHANG-OOH-2020-03.html.

[Analysis of the clinical predictive value of lactate on the prognosis of patients with acute-on-chronic liver failure combined with infection]

Objective: To explore the predictive value of lactic acid for the adverse prognostic outcomes in patients with acute-on-chronic liver failure combined with infection. Methods: A retrospective analysis was conducted on the clinical data of 208 cases of ACLF combined with infection who were hospitalized from January 2014 to March 2016. Patients were divided into a survival group (n = 83) and a mortality group (n = 125) according to the results of a 90-day follow-up. The clinical data were statistically analyzed between the two groups. Multivariate logistic regression with two categorical variables was used to analyze the independent risk factors for 90-day disease mortality and establish a new prediction model. The receiver operating characteristic curve (ROC curve) was used to evaluate the predictive value of lactic acid, the MELD score, the MELD-Na score, lactic acid combined with the MELD score, lactic acid combined with the MELD-Na score, and the new model. Results: The 90-day mortality rate of 208 cases of ACLF combined with infection was 60.1%. There were statistically significant differences in white blood cell count, neutrophil count, total bilirubin (TBil), serum creatinine (Cr), blood urea nitrogen (BUN), blood ammonia, the international normalized ratio (INR), lactic acid (LAC), procalcitonin, the MELD score, the MELD-Na score, hepatic encephalopathy (HE), acute kidney injury (AKI), and bleeding between the two groups. Multivariate logistic regression analysis showed that TBil, INR, LAC, HE, and bleeding were independent risk factors for 90-day mortality in patients with ACLF combined with infection. After the establishment of MELD-LAC, MELD-Na-LAC, and a new prediction model, the ROC curve revealed that the AUC (95% confidence interval) of MELD-LAC and MELD-Na LAC were 0.819 (0.759 ~ 0.870) and 0.838 (0.780 ~ 0.886), respectively, and was superior than the MELD score [0.766 (0.702 ~ 0.823)] and MELD-Na score [0.788 (0.726 ~ 0.843)], with P < 0.05, while the new model had an AUC of 0.924, the sensitivity of 83.9%, specificity of 89.9%, and accuracy of 87.8%, which was higher than LAC, MELD score, MELD-Na score, MELD-LAC, and MELD-Na-LAC (P < 0.01). Conclusion: Lactic acid is an independent risk factor for mortality in patients with ACLF combined with infection, and it improves the clinical predictive value of MELD and MELD-Na for the prognosis of mortality.

Loss of tidal creek ecosystem vitality caused by tidal flat narrowing on the central Jiangsu coast, China

Globally, tidal flats are increasingly narrowing due to continuous reclamation and sea level rise. Nonetheless, the impact of tidal flat narrowing (TFN) on tidal creek systems that play a crucial role in the formation and shaping of tidal flats is not well understood, despite a cognition that the tidal flat-creek system is integrated and coevolved. In this study, based on the quantification and mapping of tidal creek ecosystem vitality (TCEV), we detected the state evolution of tidal creek systems in response to TFN process on the central Jiangsu coast (CJC), China. The results showed that two thirds of the original tidal flat width was lost from 1984 to 2020, with a narrowing rate of 210.9 m/yr. The seaward movement of seawall lines and the landward movement of low tide lines contributed 82.5 % and 17.5 % to this serious TFN process, respectively. Across the study period, the overall TCEV lost 82.3 % with a substantial transformation from high level to low level. In terms of three dimensions of structural complexity, functional integrity and spatial occupancy, the tidal creek system of CJC has greatly deviated from the high-quality state in 1984, which was significantly associated with TFN. For a natural mature tidal flat, the loss of its initial width seems acceptable when <1/3, but unacceptable when >1/2, which are two important thresholds corresponding to the lower and higher loss of TCEV, respectively. It is worried that the CJC tidal flat-creek system would fall into a vicious circle of state evolution. Therefore, efforts should be made to control irrational reclamation and perform ecological restoration based on an insight into the relationship between TCEV and TFN.

Construction adsorption and photocatalytic interfaces between C, O co-doped BN and Pd-Cu alloy nanocrystals for effective conversion of CO2 to CO

Photocatalytic reduction of carbon dioxide (CO₂) into fuels is an auspicious route to alleviate the energy and environmental crisis brought by the continuous depletion of fossil fuels. The CO₂ adsorption state on the surface of photocatalytic materials plays a significant role in its efficient conversion. The limited CO₂ adsorption capacity of conventional semiconductor materials inhibit their photocatalytic performances. In this work, a bifunctional material for CO₂ capture and photocatalytic reduction was fabricated by introducing palladium (Pd)-copper (Cu) alloy nanocrystals onto the surface of carbon, oxygen co-doped boron nitride (BN). The elemental doped BN with abundant ultra-micropores had high CO₂ capture ability, and CO₂ was adsorbed in the form of bicarbonate on its surface with the presence of water vapor. The Pd/Cu molar ratio had great impact on the grain size of Pd-Cu alloy and their distribution on BN. The CO₂ molecules tended to be converted to carbon monoxide (CO) at interfaces of BN and Pd-Cu alloys due to their bidirectional interactions to the adsorbed intermediate species while methane (CH₄) evolution might occur on the surface of Pd-Cu alloys. Owing to the uniform distribution of smaller Pd-Cu nanocrystals on BN, more effective interfaces were created in the Pd₅Cu₁/BN sample and it gave a CO production rate of 7.74 μmolg^-1h^-1 under simulated solar light irradiation, higher than the other PdCu/BN composites. This work can pave a new way for constructing effective bifunctional photo-catalysts with high selectivity to convert CO₂ to CO.

Progesterone levels associated with proteinuria in male diabetes mellitus patients: A cross-sectional retrospective study

INTRODUCTION

The relationship between progesterone (P) and diabetic nephropathy (DKD) is unclear. Herein, we investigated the relationship between progesterone and DKD in men and postmenopausal women with type 2 diabetes mellitus. MATERIALS AND METHODS: We recruited 3,556 male and postmenopausal female patients and obtained the dominance ratio (OR) and corresponding 95% confidence intervals (CIs) associated with progesterone by logistic regression analysis after adjusting for potentially confounding variants.

RESULTS

We found that progesterone levels were significantly lower in the massive proteinuria and microproteinuria groups compared with the non-DKD group for male patients. Also, microproteinuria and massive proteinuria prevalence were higher in the first (lowest) progesterone quartile than in the second to fourth quartiles. After adjusting for confounders, compared with the first (lowest) progesterone quartile group, the OR for the second to fourth quartiles in the male microproteinuria subgroup, were: Q2: 0.846 (95% CI: 0.581-1.233, P = 0.385); Q3: 0.667 (95% CI: 0.45-0988, P = 0.044); Q4: 0.597 (95% CI: 0.393-0.907, P = 0.016). In the male massive proteinuria subgroup, the OR for the third quartile group was 0.418 (95% CI: 0.201-0.867, P = 0.019). In contrast, no significant association was detected between progesterone and DKD prevalence in the female group.

CONCLUSIONS

Progesterone levels were negatively associated with DKD incidence in hospitalized male patients with type 2 diabetes mellitus.

Covalent Organic Framework/g-C3N4 van der Waals Heterojunction toward H2 Production

Photocatalytic water splitting into H₂ is the most economic and environmentally friendly strategy for H₂ production, and rationally constructing a heterojunction retains enormous influence on a photocatalytic system. Herein, 2D/2D covalent organic framework/graphitic carbon nitride (COF/CN) van der Waals heterojunctions were readily prepared via an ultrasonic method for high-efficiency visible-light photocatalytic H₂ production. The photocatalytic H₂ production performance of optimized COF/CN composites can reach up to 449.64 μmol·h^-1, which is approximately 5 times that of pure CN (89.08 μmol·h^-1). The characterization and experimental studies reveal that the synergistic effect between COF and CN contributes to promoting the interfacial migration and spatial separation of photoinduced e^--h⁺ pairs, further boosting the photocatalytic hydrogen production activity. This work may open a new window to design and fabricate effective heterojunction photocatalysts for photocatalytic energy conversion.

DeepCloth: Neural Garment Representation for Shape and Style Editing

Garment representation, editing and animation are challenging topics in the area of computer vision and graphics. It remains difficult for existing garment representations to achieve smooth and plausible transitions between different shapes and topologies. In this work, we introduce, DeepCloth, a unified framework for garment representation, reconstruction, animation and editing. Our unified framework contains 3 components: First, we represent the garment geometry with a "topology-aware UV-position map", which allows for the unified description of various garments with different shapes and topologies by introducing an additional topology-aware UV-mask for the UV-position map. Second, to further enable garment reconstruction and editing, we contribute a method to embed the UV-based representations into a continuous feature space, which enables garment shape reconstruction and editing by optimization and control in the latent space, respectively. Finally, we propose a garment animation method by unifying our neural garment representation with body shape and pose, which achieves plausible garment animation results leveraging the dynamic information encoded by our shape and style representation, even under drastic garment editing operations. To conclude, with DeepCloth, we move a step forward in establishing a more flexible and general 3D garment digitization framework. Experiments demonstrate that our method can achieve state-of-the-art garment representation performance compared with previous methods.

Untargeted metabolomic profiling identifies serum metabolites associated with type 2 diabetes in a cross-sectional study of the Alpha-Tocopherol, Beta-Carotene Cancer Prevention (ATBC) Study

Type 2 diabetes (T2D) is a complex chronic disease with substantial phenotypic heterogeneity affecting millions of individuals. Yet, its relevant metabolites and etiological pathways are not fully understood. The aim of this study is to assess a broad spectrum of metabolites related to T2D in a large population-based cohort. We conducted a metabolomic analysis of 4,281 male participants within the Alpha-Tocopherol, Beta-Carotene Cancer Prevention (ATBC) Study. The serum metabolomic analysis was performed using an LC-MS/GC-MS platform. Associations between 1,413 metabolites and T2D were examined using linear regression, controlling for important baseline risk factors. Standardized β-coefficients and standard errors (SEs) were computed to estimate the difference in metabolite concentrations. We identified 74 metabolites that were significantly associated with T2D based on the Bonferroni-corrected threshold (P < 3.5 × 10-5). The strongest signals associated with T2D were of carbohydrates origin, including glucose, 1,5-anhydroglucitol (1,5-AG), and mannose (β = 0.34, -0.91, and 0.41, respectively; all P < 10-75). We found several chemical class pathways that were significantly associated with T2D, including carbohydrates (P = 1.3 × 10-11), amino acids (P = 2.7 × 10-6), energy (P = 1.5 × 10-4), and xenobiotics (P = 1.2 × 10-3). The strongest subpathway associations were seen for fructose-mannose-galactose metabolism, glycolysis-gluconeogenesis-pyruvate metabolism, fatty acid metabolism (acyl choline), and leucine-isoleucine-valine metabolism (all P < 10-8). Our findings identified various metabolites and candidate chemical class pathways that can be characterized by glycolysis and gluconeogenesis metabolism, fructose-mannose-galactose metabolism, branched-chain amino acids, diacylglycerol, acyl cholines, fatty acid oxidation, and mitochondrial dysfunction.NEW & NOTEWORTHY These metabolomic patterns may provide new additional evidence and potential insights relevant to the molecular basis of insulin resistance and the etiology of T2D.

The risk of nonalcoholic fatty liver disease in gout patients with frequent flares: a retrospective cohort study

OBJECTIVE

Nonalcoholic fatty liver disease (NAFLD) is a common chronic disease that is related to high serum uric acid; however, the association between the frequency of gout flares and NAFLD risk remains unclear. This study aimed to investigate whether frequent gout flares were associated with incident NAFLD and analyze the interaction of frequency of gout flares and Adipo-IR on NAFLD in the gout Chinese population.

METHODS

A total of 350 cases of gout patients were enrolled in this retrospective cohort study. Cox proportional hazard regression analyses were performed to determine the association between frequent gout flares and NAFLD during follow-up and analyze the interaction of frequency of gout flares and Adipo-IR on NAFLD. Receiver operating curves (ROC) were plotted to explore the diagnostic value of frequent gout flares and Adipo-IR on the occurrence of NAFLD.

RESULTS

NAFLD developed in 78 participants (22.3%) during follow-up. Logistic regression showed that Adipo-IR was an independent factor associated with frequent gout flares risk. The multivariate Cox regression analysis revealed that frequent gout flares and Adipo-IR were associated with NAFLD risk (HR: 7.88, 95% CI: 2.11-29.48, p < 0.01; HR: 1.058, 95% CI: 1.01-1.2, p < 0.05). And ROC showed that both of them had a great discriminant ability to diagnose NAFLD.

CONCLUSIONS

Our data showed an independent association between the frequency of gout flares or Adipo-IR and incident NAFLD. Frequent gout flares and elevated Adipo-IR had a good predictive capability towards NAFLD development and played a synergistic role in the development of NAFLD.

KEY POINTS

• Frequent gout flares and elevated Adipo-IR had a good diagnostic capability towards NAFLD development. • Frequent gout flares and Adipo-IR played a synergistic role in the development of NAFLD.

Electroencephalogram-Based Brain Connectivity Analysis in Prolonged Disorders of Consciousness

Background

Prolonged disorders of consciousness (pDOC) are common in neurology and place a heavy burden on families and society. This study is aimed at investigating the characteristics of brain connectivity in patients with pDOC based on quantitative EEG (qEEG) and extending a new direction for the evaluation of pDOC.

Methods

Participants were divided into a control group (CG) and a DOC group by the presence or absence of pDOC. Participants underwent magnetic resonance imaging (MRI) T1 three-dimensional magnetization with a prepared rapid acquisition gradient echo (3D-T1-MPRAGE) sequence, and video EEG data were collected. After calculating the power spectrum by EEG data analysis tool, DTABR ((δ + θ)/(α + β) ratio), Pearson's correlation coefficient (Pearson r), Granger's causality, and phase transfer entropy (PTE), we performed statistical analysis between two groups. Finally, receiver operating characteristic (ROC) curves of connectivity metrics were made.

Results

The proportion of power in frontal, central, parietal, and temporal regions in the DOC group was lower than that in the CG. The percentage of delta power in the DOC group was significantly higher than that in the CG, the DTABR in the DOC group was higher than that in the CG, and the value was inverted. The Pearson r of the DOC group was higher than that of CG. The Pearson r of the delta band (Z = -6.71, P < 0.01), theta band (Z = -15.06, P < 0.01), and alpha band (Z = -28.45, P < 0.01) were statistically significant. Granger causality showed that the intensity of directed connections between the two hemispheres in the DOC group at the same threshold was significantly reduced (Z = -82.43, P < 0.01). The PTE of each frequency band in the DOC group was lower than that in the CG. The PTE of the delta band (Z = -42.68, P < 0.01), theta band (Z = -56.79, P < 0.01), the alpha band (Z = -35.11, P < 0.01), and beta band (Z = -63.74, P < 0.01) had statistical significance.

Conclusion

Brain connectivity analysis based on EEG has the advantages of being noninvasive, convenient, and bedside. The Pearson r of DTABR, delta, theta, and alpha bands, Granger's causality, and PTE of the delta, theta, alpha, and beta bands can be used as biological markers to distinguish between pDOC and healthy people, especially when behavior evaluation is difficult or ambiguous; it can supplement clinical diagnosis.

YQBS Improves Cognitive Dysfunction in Diabetic Rats: Possible Association with Tyrosine and Tryptophan Metabolism

OBJECTIVE

This study is aimed to determine the metabolomic effects of the hybrid medicine formula Yi-Qi-Bu-Shen (YQBS) on the neurotransmitter aspects of cognitive impairment in diabetic rats.

METHODS

In the current study, streptozotocin (STZ) was used to induce diabetic animal model in male Sprague Dawley (SD) rats. After successful establishment of diabetic SD rats' model, age-matched healthy SD rats and diabetic SD rats were treated with low and high doses of YQBS, and then tested for learning memory ability and analyzed for pathological changes. In addition, neurotransmitter metabolic changes in hippocampal subdivisions of rats from different treated groups were analyzed using liquid chromatography-mass spectrometry (LC-MS) technique.

RESULTS

YQBS could significantly improve memory-cognitive impairment in diabetic rats as evidenced by the shortening of latency to target and the reduction of latency first entrance to target. Moreover, YQBS also improved the pathological alterations in the hippocampal region in the brains of diabetic rats. Metabolomic analysis showed that the expression of noradrenaline hydrochloride was down-regulated and the expressions of levodopa and 5-hydroxytryptophan were up-regulated in the hippocampal tissues of diabetic rats treated with YQBS.

CONCLUSION

These findings demonstrate that YQBS has protective effects against diabetic cognitive dysfunction, which might act through alteration in tyrosine and tryptophan metabolism.

Cardiovascular-renal protective effect and molecular mechanism of finerenone in type 2 diabetic mellitus

Chronic kidney diseases (CKD) and cardiovascular diseases (CVD) are the main complications in type 2 diabetic mellitus (T2DM), increasing the risk of cardiovascular and all-cause mortality. Current therapeutic strategies that delay the progression of CKD and the development of CVD include angiotensin-converting enzyme inhibitors (ACEI), angiotensin II receptor blockers (ARB), sodium-glucose co-transporter 2 inhibitors (SGLT-2i) and GLP-1 receptor agonists (GLP-1RA). In the progression of CKD and CVD, mineralocorticoid receptor (MR) overactivation leads to inflammation and fibrosis in the heart, kidney and vascular system, making mineralocorticoid receptor antagonists (MRAs) as a promising therapeutic option in T2DM with CKD and CVD. Finerenone is the third generation highly selective non-steroidal MRAs. It significantly reduces the risk of cardiovascular and renal complications. Finerenone also improves the cardiovascular-renal outcomes in T2DM patients with CKD and/or chronic heart failure (CHF). It is safer and more effective than the first- and second-generation MRAs due to its higher selectivity and specificity, resulting in a lower incidence of adverse effects including hyperkalemia, renal insufficiency and androgen-like effects. Finerenone shows potent effect on improving the outcomes of CHF, refractory hypertension, and diabetic nephropathy. Recently studies have shown that finerenone may have potential therapeutic effect on diabetic retinopathy, primary aldosteronism, atrial fibrillation, pulmonary hypertension and so on. In this review, we discuss the characteristics of finerenone, the new third-generation MRA, and compared with the first- and second-generation steroidal MRAs and other nonsteroidal MRAs. We also focus on its safety and efficacy of clinical application on CKD with T2DM patients. We hope to provide new insights for the clinical application and therapeutic prospect.

Circadian rhythm of plasminogen activator inhibitor-1 and cardiovascular complications in type 2 diabetes

Cardiovascular complications are a common death cause in type 2 diabetes patients, as they are often combined. Plasminogen-activator Inhibitor 1 (PAI-1) participates in the development and progression of cardiovascular complications in diabetes. Insulin resistance increases PAI-1 production, and high PAI-1 levels lead to an environment conducive to thrombosis and earlier and more severe vascular disease. Current evidence also suggests that PAI-1 has a rhythmic profile of circadian fluctuations and acrophase in the morning within a single day, which might explain the high morning incidence of cardiovascular events. Thus, PAI-1 is a possible drug target. Although several PAI-1 inhibitors have been developed, none have yet been allowed for clinical use. Research on rhythm has also led to the concept of "chronotherapy", a rhythm-based drug regimen expected to improve the treatment of cardiovascular complications in diabetic patients. Herein, we searched several databases and reviewed relevant articles to describe the circadian rhythm characteristics and endogenous molecular mechanisms of PAI-1, its relationship with insulin resistance, the causes of cardiovascular complications caused by PAI-1, and the current development of PAI-1 inhibitors. We also summarized the possibility of using the circadian rhythm of PAI-1 to treat cardiovascular complications in diabetic patients.

hUCMSCs carrying exenatide prevent T1DM by improving intestinal microflora composition and islet tissue damage repair

BACKGROUND

Exenatide is a stable analogue of glucagon-like peptide 1 that can reduce postprandial hyperglycemia and has been utilized as adjunctive therapy for type 1 diabetes mellitus (T1DM). The human umbilical cord is a rich source of MSCs, and human umbilical cord mesenchymal stem cells (hUCMSCs) also show potential to enhance insulin secretion. Here, we aimed to explore the effects of hUCMSCs carrying exenatide in T1DM and further identify the possible mechanisms involved.

METHODS

hUCMSCs were isolated from human umbilical cord tissues, identified, and transduced with recombinant lentivirus carrying exenatide to obtain exenatide-carrying hUCMSCs (hUCMSCs@Ex-4).

RESULTS

The results showed that hUCMSCs@Ex-4 restored the blood glucose levels and body weight of NOD mice, and repressed immune cell infiltration and islet tissue changes. Additionally, in T1DM mice, treatment with hUCMSCs@Ex-4 reduced the blood glucose levels and promoted repair of islet tissue damage. Moreover, hUCMSCs@Ex-4 attenuated renal tissue lesions in T1DM mice. Applying bioinformatic analysis, the effects of hUCMSCs@Ex-4 were suggested to correlate with decreased abundance of pro-inflammatory intestinal bacteria and increased abundance of anti-inflammatory intestinal bacteria.

CONCLUSION

Overall, the study indicated that hUCMSCs carrying exenatide might improve beneficial intestinal microflora abundance and promote islet tissue damage repair, thereby alleviating T1DM.

Establishment and validation of a clinical model for predicting diabetic ketosis in patients with type 2 diabetes mellitus

Background

Diabetic ketosis (DK) is one of the leading causes of hospitalization among patients with diabetes. Failure to recognize DK symptoms may lead to complications, such as diabetic ketoacidosis, severe neurological morbidity, and death.

Purpose

This study aimed to develop and validate a model to predict DK in patients with type 2 diabetes mellitus (T2DM) based on both clinical and biochemical characteristics.

Methods

A cross-sectional study was conducted by evaluating the records of 3,126 patients with T2DM, with or without DK, at The Affiliated Hospital of Qingdao University from January 2015 to May 2022. The patients were divided randomly into the model development (70%) or validation (30%) cohorts. A risk prediction model was constructed using a stepwise logistic regression analysis to assess the risk of DK in the model development cohort. This model was then validated using a second cohort of patients.

Results

The stepwise logistic regression analysis showed that the independent risk factors for DK in patients with T2DM were the 2-h postprandial C-peptide (2hCP) level, age, free fatty acids (FFA), and HbA1c. Based on these factors, we constructed a risk prediction model. The final risk prediction model was L= (0.472a - 0.202b - 0.078c + 0.005d - 4.299), where a = HbA1c level, b = 2hCP, c = age, and d = FFA. The area under the curve (AUC) was 0.917 (95% confidence interval [CI], 0.899-0.934; p<0.001). The discriminatory ability of the model was equivalent in the validation cohort (AUC, 0.922; 95% CI, 0.898-0.946; p<0.001).

Conclusion

This study identified independent risk factors for DK in patients with T2DM and constructed a prediction model based on these factors. The present findings provide an easy-to-use, easily interpretable, and accessible clinical tool for predicting DK in patients with T2DM.

Effect of Process Parameters on Properties of Cold-Sprayed Zn-Al Composite Coatings

Al-Zn composite coating can provide effective cathodic protection for E235 steel. This study aims to obtain the Al-Zn composite coating with the best anti-corrosion performance by optimizing the spraying temperature, spraying distance and powder-feeding motor speed. The Al and Zn powders were analyzed by scanning electron microscope (SEM), and the microstructure of the coatings prepared by different process parameters was observed by optical microscope. The mechanical and anticorrosive properties of the coating were evaluated using hardness, porosity, thickness and electrochemical tests. According to the experimental results, when the spraying temperature, spraying distance and powder-feeding motor speed were 500 °C, 27 mm and 1.5 r/min, respectively, the hardness of the coating was 67 HV, the porosity was 0.57% and the thickness was 0.588 mm. The EIS test results show that the coating has the maximum polarization resistance, and therefore the coating has good corrosion resistance at this parameter.

Recent advances in supported acid/base ionic liquids as catalysts for biodiesel production

Biodiesel is considered a potential substitute for fossil diesel because of its unique environmentally friendly and renewable advantages. The efficient and durable heterogeneous catalysts are vital to greenly and efficiently drive the biodiesel production process. The ionic liquid-functionalized materials, possessing the characteristics of both homogeneous and heterogeneous catalysts, are one of the promising substitutions for conventional homogeneous acid/base catalysts for producing biodiesel. This mini-review focuses on recent advances in supported acid/base ionic liquids to synthesize ionic liquid-functionalized materials for producing biodiesel. The methods of immobilizing ionic liquids on supports were summarized. The merits and demerits of various supports were discussed. The catalytic activities of the ionic liquid-functionalized materials for biodiesel production were reviewed. Finally, we proposed the challenges and future development direction in this area.

Neural network training method for materials science based on multi-source databases

The fourth paradigm of science has achieved great success in material discovery and it highlights the sharing and interoperability of data. However, most material data are scattered among various research institutions, and a big data transmission will consume significant bandwidth and tremendous time. At the meanwhile, some data owners prefer to protect the data and keep their initiative in the cooperation. This dilemma gradually leads to the “data island” problem, especially in material science. To attack the problem and make full use of the material data, we propose a new strategy of neural network training based on multi-source databases. In the whole training process, only model parameters are exchanged and no any external access or connection to the local databases. We demonstrate its validity by training a model characterizing material structure and its corresponding formation energy, based on two and four local databases, respectively. The results show that the obtained model accuracy trained by this method is almost the same to that obtained from a single database combining all the local ones. Moreover, different communication frequencies between the client and server are also studied to improve the model training efficiency, and an optimal frequency is recommended.

Metal-polyphenol cross-linked titanium carbide membranes with stable interlayer spacing for efficient wastewater treatment

Membranes based on transition metal carbides/nitrides (MXenes) have significant water treatment potential because of their unique molecular sieving properties and excellent permeation performance. However, hydrophilic MXenes swell upon water immersion, and improving their stability remains challenging. In this study, a Fe³⁺-tannic acid (TA) complex was used as a cross-linker and surface modifier to prepare high-performance titanium carbide (Ti₃C₂T_x) MXene laminar membranes. Fe³⁺-TA formation on the nanosheets increased the interlayer spacing and stabilized the laminar structure. The membrane with the highest performance among the as-prepared membranes exhibited a high water permeance of 90.5 L/m^-2(-|-)h^-1 bar^-1 (which is twice that of the pristine Ti₃C₂T_x membrane) and good separation efficiency (methyl blue rejection rate: ∼99.8 %; Na₂SO₄ rejection rate: ∼5.0 %). Furthermore, the Fe³⁺-TA complex enhanced the membrane hydrophilicity, resulting in excellent antifouling properties. This study provides an environmentally friendly and facile method for fabricating two-dimensional loose nanofiltration membranes for textile wastewater treatment.