Effects of gut microbiome on type 1 diabetes susceptibility and complications: A large-scale bidirectional Mendelian randomization and external validation study.

AIM: To assess and verify the effect of the gut microbiome on the susceptibility and complications of type 1 diabetes (T1D). MATERIALS AND METHODS: To achieve this aim, a two-sample and reverse Mendelian randomization (MR) analysis was conducted. In addition, an external validation study was performed using individual microbiome data of patients with T1D from the gutMEGA datasets and the National Clinical Research Center for Metabolic Diseases. The circulating metabolites facilitated two-sample MR analysis, mediation and multivariable MR analysis to evaluate the direct relationship between the gut microbiome and T1D complications. RESULTS: The MR analysis results from the discovery and validation phases confirmed that Veillonellaceae can potentially reduce the susceptibility of T1D. In the gutMEGA dataset, the average relative abundance of Veillonellaceae in patients with T1D was 0.66%, compared with 1.09% in the controls. Furthermore, the external validation, which included 60 patients with T1D and 30 matched healthy controls, found that the median relative abundance of Veillonellaceae was also lower than controls at 1.10% (95% CI 0.50%-1.80%). Specifically, the Eubacterium coprostanoligenes group, known for its ability to regulate cholesterol, was significantly associated with a lower risk of developing renal, neurological and ophthalmic complications in T1D. Moreover, high cholesterol in small high-density lipoprotein and cholesteryl esters in high-density lipoprotein were associated with a reduced risk of T1D renal and ophthalmic complications. The mediation and multivariable MR analysis combining cholesterol indicated that the E. coprostanoligenes group is the most dominant factor influencing T1D complications. CONCLUSIONS: Our findings supported the potential causal effect of gut microbiota on the susceptibility and complications of T1D.

Effect of Myelin Debris on the Phenotypic Transformation of Astrocytes after Spinal Cord Injury in Rats.

After spinal cord injury (SCI), the accumulation of myelin debris can serve as proinflammatory agents, hindering axon regrowth and exacerbating damage. While astrocytes have been implicated in the phagocytosis of myelin debris, the impact of this process on the phenotypic transformation of astrocytes and their characteristics following SCI in rats is not well understood. Here, we demonstrated that the conditioned medium of myelin debris can trigger apoptosis in rat primary astrocytes in vitro. Using a compressional SCI model in rats, we observed that astrocytes can engulf myelin debris through ATP-binding cassette transporter sub-family A member 1 (ABCA1), and these engulfed cells tend to transform into A1 astrocytes, as indicated by C3 expression. At 4 days post-injury (dpi), astrocytes rapidly transitioned into A1 astrocytes and maintained this phenotype from 4 to 28 dpi, while A2 astrocytes, characterized by S100, were only detected at 14 and 28 dpi. Reactive astrocytes, identified by Nestin, emerged at 4 and 7 dpi, whereas scar-forming astrocytes, marked by N-cadherin, were evident at 14 and 28 dpi. This study illustrates the distribution patterns of astrocyte subtypes and the potential interplay between astrocytes and myelin debris after SCI in rats. We emphasize that myelin debris can induce astrocyte apoptosis in vitro and promote the transformation of astrocytes into A1 astrocytes in vivo. These two classification methods are not mutually exclusive, but rather complementary.

Estimating the effect of lipid-lowering agents on novel subtypes of adult-onset diabetes.

AIMS: The aims of the present study were to assess the effects of lipid-lowering drugs [HMG-CoA reductase inhibitors, proprotein convertase subtilisin/kexin type 9 inhibitors, and Niemann-Pick C1-Like 1 (NPC1L1) inhibitors] on novel subtypes of adult-onset diabetes through a Mendelian randomisation study. MATERIALS AND METHODS: We first inferred causal associations between lipid-related traits [including high-density lipoprotein cholesterol, low-density lipoprotein cholesterol (LDL-C), triglycerides (TG), apolipoproteins A-I, and apolipoproteins B] and novel subtypes of adult-onset diabetes. The expression quantitative trait loci of drug target genes for three classes of lipid-lowering drugs, as well as genetic variants within or nearby drug target genes associated with LDL-C, were then utilised as proxies for the exposure of lipid-lowering drugs. Mendelian randomisation analysis was performed using summary data from genome-wide association studies of LDL-C, severe autoimmune diabetes, severe insulin-deficient diabetes (SIDD), severe insulin-resistant diabetes (SIRD), mild obesity-related diabetes (MOD), and mild age-related diabetes. RESULTS: There was an association between HMGCR-mediated LDL-C and the risk of SIRD [odds ratio (OR) = 0.305, 95% confidence interval (CI) = 0.129-0.723; p = 0.007], and there was an association of PCSK9-mediated LDL-C with the risk of SIDD (OR = 0.253, 95% CI = 0.120-0.532; p < 0.001) and MOD (OR = 0.345, 95% CI = 0.171-0.696; p = 0.003). Moreover, NPC1L1-mediated LDL-C (OR = 0.109, 95% CI = 0.019-0.613; p = 0.012) and the increased expression of NPC1L1 gene in blood (OR = 0.727, 95% CI = 0.541-0.977; p = 0.034) both showed a significant association with SIRD. These results were further confirmed by sensitivity analyses. CONCLUSIONS: In summary, the different lipid-lowering medications have a specific effect on the increased risk of different novel subtypes of adult-onset diabetes.

Multi-path Fusion in SFCF-Net for Enhanced Multi-frequency Electrical Impedance Tomography.

Multi-frequency electrical impedance tomography (mfEIT) offers a nondestructive imaging technology that reconstructs the distribution of electrical characteristics within a subject based on the impedance spectral differences among biological tissues. However, the technology faces challenges in imaging multi-class lesion targets when the conductivity of background tissues is frequency-dependent. To address these issues, we propose a spatial-frequency cross-fusion network (SFCF-Net) imaging algorithm, built on a multi-path fusion structure. This algorithm uses multi-path structures and hyper-dense connections to capture both spatial and frequency correlations between multi-frequency conductivity images, which achieves differential imaging for lesion targets of multiple categories through cross-fusion of information. According to both simulation and physical experiment results, the proposed SFCF-Net algorithm shows an excellent performance in terms of lesion imaging and category discrimination compared to the weighted frequency-difference, U-Net, and MMV-Net algorithms. The proposed algorithm enhances the ability of mfEIT to simultaneously obtain both structural and spectral information from the tissue being examined and improves the accuracy and reliability of mfEIT, opening new avenues for its application in clinical diagnostics and treatment monitoring.

hBcl2 overexpression in BMSCs enhances resistance to myelin debris-induced apoptosis and facilitates neuroprotection after spinal cord injury in rats.

After spinal cord injury (SCI), the accumulation of myelin debris at the lesion exacerbates cell death and hinders axonal regeneration. Transplanted bone marrow mesenchymal stem cells (BMSCs) have been proven to be beneficial for SCI repair, but they are susceptible to apoptosis. It remains unclear whether this apoptotic process is influenced by myelin debris. Here, we constructed rat BMSCs overexpressing human B-cell lymphoma 2 (hBcl2) alone (hBcl2 group), BMSCs overexpressing hBcl2 with an endoplasmic reticulum-anchored segment (hBcl2-cb) (cb group), and a negative control group (NC group) for transplantation in this study. Immunocytochemistry staining validated the successful expression of hBcl2 in BMSCs within the hBcl2 group and cb group. All BMSCs from each group exhibited the ability to phagocytize myelin debris. Nevertheless, only BMSCs derived from the hBcl2 group exhibited heightened resistance to apoptosis and maintained prolonged viability for up to 5 days when exposed to myelin debris. Notably, overexpression of hBcl2 protein, rather than its endoplasmic reticulum-anchored counterpart, significantly enhanced the resistance of BMSCs against myelin debris-induced apoptosis. This process appeared to be associated with the efficient degradation of myelin debris through the Lamp1+ lysosomal pathway in the hBcl2 group. In vivo, the hBcl2 group exhibited significantly higher numbers of surviving cells and fewer apoptotic BMSCs compared to the cb and NC groups following transplantation. Furthermore, the hBcl2 group displayed reduced GFAP+ glial scarring and greater preservation of NF200+ axons in the lesions of SCI rats. Our results suggest that myelin debris triggers apoptosis in transplanted BMSCs, potentially elucidating the low survival rate of these cells after SCI. Consequently, the survival rate of transplanted BMSCs is improved by hBcl2 overexpression, leading to enhanced preservation of axons within the injured spinal cord.

Early detection of acute ischemic stroke using Contrast-enhanced electrical impedance tomography perfusion.

A cerebral contrast-enhanced electrical impedance tomography perfusion method is developed for acute ischemic stroke during intravenous thrombolytic therapy. Several clinical contrast agents with stable impedance characteristics and high-conductivity contrast were screened experimentally as electrical impedance contrast agent candidates. The electrical impedance tomography perfusion method was tested on rabbits with focal cerebral infarction, and its capability for early detection was verified based on perfusion images. The experimental results showed that ioversol 350 performed significantly better as an electrical impedance contrast agent than other contrast agents (p < 0.01). Additionally, perfusion images of focal cerebral infarction in rabbits confirmed that the electrical impedance tomography perfusion method could accurately detect the location and area of different cerebral infarction lesions (p < 0.001). Therefore, the cerebral contrast-enhanced electrical impedance tomography perfusion method proposed herein combines traditional, dynamic continuous imaging with rapid detection and could be applied as an early, rapid-detection, auxiliary, bedside imaging method for patients after a suspected ischemic stroke in both prehospital and in-hospital settings.

Effective Electrical Impedance Tomography Based on Enhanced Encoder-Decoder Using Atrous Spatial Pyramid Pooling Module.

Electrical impedance tomography (EIT) is a noninvasive and radiation-free imaging method. As a "soft-field" imaging technique, in EIT, the target signal in the center of the measured field is frequently swamped by the target signal at the edge, which restricts its further application. To alleviate this problem, this study presents an enhanced encoder-decoder (EED) method with an atrous spatial pyramid pooling (ASPP) module. The proposed method enhances the ability to detect central weak targets by constructing an ASPP module that integrates multiscale information in the encoder. The multilevel semantic features are fused in the decoder to improve the boundary reconstruction accuracy of the center target. The average absolute error of the imaging results by the EED method reduced by 82.0%, 83.6%, and 36.5% in simulation experiments and 83.0%, 83.2%, and 36.1% in physical experiments compared with the errors of the damped least-squares algorithm, Kalman filtering method, and U-Net-based imaging method, respectively. The average structural similarity improved by 37.3%, 42.9%, and 3.6%, and 39.2%, 45.2%, and 3.8% in the simulation and physical experiments, respectively. The proposed method provides a practical and reliable means of extending the application of EIT by solving the problem of weak central target reconstruction under the effect of strong edge targets in EIT.

Fingolimod (FTY720) Hinders Interferon-γ-Mediated Fibrotic Scar Formation and Facilitates Neurological Recovery After Spinal Cord Injury.

Following spinal cord injury (SCI), fibrotic scar inhibits axon regeneration and impairs neurological function recovery. It has been reported that T cell-derived interferon (IFN)-γ plays a pivotal role in promoting fibrotic scarring in neurodegenerative disease. However, the role of IFN-γ in fibrotic scar formation after SCI has not been declared. In this study, a spinal cord crush injury mouse was established. Western blot and immunofluorescence showed that IFN-γ was surrounded by fibroblasts at 3, 7, 14, and 28 days post-injury. Moreover, IFN-γ is mainly secreted by T cells after SCI. Further, in situ injection of IFN-γ into the normal spinal cord resulted in fibrotic scar formation and inflammation response at 7 days post-injection. After SCI, the intraperitoneal injection of fingolimod (FTY720), a sphingosine-1-phosphate receptor 1 (S1PR1) modulator and W146, an S1PR1 antagonist, significantly reduced T cell infiltration, attenuating fibrotic scarring via inhibiting IFN-γ/IFN-γR pathway, while in situ injection of IFN-γ diminished the effect of FTY720 on reducing fibrotic scarring. FTY720 treatment inhibited inflammation, decreased lesion size, and promoted neuroprotection and neurological recovery after SCI. These findings demonstrate that the inhibition of T cell-derived IFN-γ by FTY720 suppressed fibrotic scarring and contributed to neurological recovery after SCI.

The Prevalence of Metabolically Unhealthy Normal Weight and Its Influence on the Risk of Diabetes.

CONTEXT: Diabetes is a major health problem and metabolically unhealthy is an important risk factor. OBJECTIVE: To conduct the first nationally representative study on epidemiological data of metabolically unhealthy normal weight (MUNW) focused only on nondiabetic subjects and determine the predictive effect on diabetes in China. METHODS: A longitudinal study was conducted using data from the Rich Healthcare Group in China. Metabolic status was determined by the revised National Cholesterol Education Program Adult Treatment Panel III criteria, and individuals with 2 or more criteria were categorized as MUNW and diagnosed with metabolic syndrome (MetS) if they met 3 or more. RESULTS: Of a total of 63 830 nondiabetic normal-weight individuals, 8935 (14.0%) were classified as MUNW and 1916 (3.00%) were diagnosed with MetS. After adjusting for potential confounders, individuals with MUNW had a greater diabetes risk (4.234, 95% CI 3.089-5.803) than those without MUNW during an average of 3.10 years of follow-up. Also, the multivariable-adjusted hazard ratios for developing diabetes were 3.069 (95% CI 1.790-5.263), 7.990 (95% CI 4.668-13.677), and 11.950 (95% CI 6.618-21.579) for participants with 1, 2, and 3 or more components, respectively, compared with those without any components. Further analyses suggested that the number of MetS components present is associated with the risk of diabetes, especially in metabolically unhealthy normal-weight young male adults. Multivariable-adjusted hazard ratios (95% CI) for incident diabetes among individuals with 1, 2, and at least 3 components were 4.45 (1.45-13.72), 9.82 (3.05-31.64), and 15.13 (3.70-61.84) for participants aged ≤44 years, and 3.55 (1.81-6.97), 8.52 (4.34-16.73), and 13.69 (6.51-28.77) for male participants, respectively. CONCLUSIONS: The prevalence of MUNW is 14% in Chinese normal-weight nondiabetic individuals, and active intervention is necessary for this category of people. The presence of MUNW significantly increases the risk of diabetes, and the risk of diabetes is associated with the number of MetS components present in the patient.

Serum Metabolomics Reveals a Potential Benefit of Methionine in Type 1 Diabetes Patients with Poor Glycemic Control and High Glycemic Variability.

Glycemic variability (GV) in some patients with type 1 diabetes (T1D) remains heterogeneous despite comparable clinical indicators, and whether other factors are involved is yet unknown. Metabolites in the serum indicate a broad effect of GV on cellular metabolism and therefore are more likely to indicate metabolic dysregulation associated with T1D. To compare the metabolomic profiles between high GV (GV-H, coefficient of variation (CV) of glucose ≥ 36%) and low GV (GV-L, CV < 36%) groups and to identify potential GV biomarkers, metabolomics profiling was carried out on serum samples from 17 patients with high GV, 16 matched (for age, sex, body mass index (BMI), diabetes duration, insulin dose, glycated hemoglobin (HbA1c), fasting, and 2 h postprandial C-peptide) patients with low GV (exploratory set), and another 21 (GV-H/GV-L: 11/10) matched patients (validation set). Subsequently, 25 metabolites were significantly enriched in seven Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways between the GV-H and GV-L groups in the exploratory set. Only the differences in spermidine, L-methionine, and trehalose remained significant after validation. The area under the curve of these three metabolites combined in distinguishing GV-H from GV-L was 0.952 and 0.918 in the exploratory and validation sets, respectively. L-methionine was significantly inversely related to HbA1c and glucose CV, while spermidine was significantly positively associated with glucose CV. Differences in trehalose were not as reliable as those in spermidine and L-methionine because of the relatively low amounts of trehalose and the inconsistent fold change sizes in the exploratory and validation sets. Our findings suggest that metabolomic disturbances may impact the GV of T1D. Additional in vitro and in vivo mechanistic studies are required to elucidate the relationship between spermidine and L-methionine levels and GV in T1D patients with different geographical and nutritional backgrounds.

Fast Iterative Shrinkage-Thresholding Algorithm with Continuation for Brain Injury Monitoring Imaging Based on Electrical Impedance Tomography.

Electrical impedance tomography (EIT) is low-cost and noninvasive and has the potential for real-time imaging and bedside monitoring of brain injury. However, brain injury monitoring by EIT imaging suffers from image noise (IN) and resolution problems, causing blurred reconstructions. To address these problems, a least absolute shrinkage and selection operator model is built, and a fast iterative shrinkage-thresholding algorithm with continuation (FISTA-C) is proposed. Results of numerical simulations and head phantom experiments indicate that FISTA-C reduces IN by 63.2%, 47.2%, and 29.9% and 54.4%, 44.7%, and 22.7%, respectively, when compared with the damped least-squares algorithm, the split Bergman, and the FISTA algorithms. When the signal-to-noise ratio of the measurements is 80-50 dB, FISTA-C can reduce IN by 83.3%, 72.3%, and 68.7% on average when compared with the three algorithms, respectively. Both simulation and phantom experiments suggest that FISTA-C produces the best image resolution and can identify the two closest targets. Moreover, FISTA-C is more practical for clinical application because it does not require excessive parameter adjustments. This technology can provide better reconstruction performance and significantly outperforms the traditional algorithms in terms of IN and resolution and is expected to offer a general algorithm for brain injury monitoring imaging via EIT.

A pilot study of contrast-enhanced electrical impedance tomography for real-time imaging of cerebral perfusion.

Background: Real-time detection of cerebral blood perfusion can prevent adverse reactions, such as cerebral infarction and neuronal apoptosis. Our previous clinical trial have shown that the infusion of therapeutic fluid can significantly change the impedance distribution in the brain. However, whether this alteration implicates the cerebral blood perfusion remains unclear. To explore the feasibility of monitoring cerebral blood perfusion, the present pilot study established a novel cerebral contrast-enhanced electrical impedance tomography (C-EIT) technique. Materials and methods: Rabbits were randomly divided into two groups: the internal carotid artery non-occlusion (ICAN) and internal carotid artery occlusion (ICAO) groups. Both of groups were injected with glucose, an electrical impedance-enhanced contrast agent, through the right internal carotid artery under EIT monitoring. The C-EIT reconstruction images of the rabbits brain were analyzed according to the collected raw data. The paired and independent t-tests were used to analyze the remodeled impedance values of the left and right cerebral hemispheres within and between studied groups, respectively. Moreover, pathological examinations of brain were performed immediately after C-EIT monitoring. Results: According to the reconstructed images, the impedance value of the left cerebral hemisphere in the ICAN group did not change significantly, whereas the impedance value of the right cerebral hemisphere gradually increased, reaching a peak at approximately 10 s followed by gradually decreased. In the ICAO group, the impedance values of both cerebral hemispheres increased gradually and then began to decrease after reaching the peak value. According to the paired t-test, there was a significant difference (P < 0.001) in the remodeling impedance values between the left and right hemispheres in the ICAN group, and there was also a significant difference (P < 0.001) in the ICAO group. According to the independent t-test, there was a significant difference (P < 0.001) of the left hemispheres between the ICAN and ICAO groups. Conclusion: The cerebral C-EIT proposed in this pilot study can reflect cerebral blood perfusion. This method has potential in various applications in the brain in the future, including disease progression monitoring, collateral circulation judgment, tumor-specific detection, and brain function research.

Analysis of detrended fluctuation function derived from continuous glucose monitoring may assist in distinguishing latent autoimmune diabetes in adults from T2DM.

Background: We aimed to explore the performance of detrended fluctuation function (DFF) in distinguishing patients with latent autoimmune diabetes in adults (LADA) from type 2 diabetes mellitus (T2DM) with glucose data derived from continuous glucose monitoring. Methods: In total, 71 LADA and 152 T2DM patients were enrolled. Correlations between glucose parameters including time in range (TIR), mean glucose, standard deviation (SD), mean amplitude of glucose excursions (MAGE), coefficient of variation (CV), DFF and fasting and 2-hour postprandial C-peptide (FCP, 2hCP) were analyzed and compared. Receiver operating characteristics curve (ROC) analysis and 10-fold cross-validation were employed to explore and validate the performance of DFF in diabetes classification respectively. Results: Patients with LADA had a higher mean glucose, lower TIR, greater SD, MAGE and CV than those of T2DM (P<0.001). DFF achieved the strongest correlation with FCP (r = -0.705, P<0.001) as compared with TIR (r = 0.485, P<0.001), mean glucose (r = -0.337, P<0.001), SD (r = -0.645, P<0.001), MAGE (r = -0.663, P<0.001) and CV (r = -0.639, P<0.001). ROC analysis showed that DFF yielded the greatest area under the curve (AUC) of 0.862 (sensitivity: 71.2%, specificity: 84.9%) in differentiating LADA from T2DM as compared with TIR, mean glucose, SD, MAGE and CV (AUC: 0.722, 0.650, 0.800, 0.820 and 0.807, sensitivity: 71.8%, 47.9%, 63.6%, 72.7% and 78.8%, specificity: 67.8%, 83.6%, 80.9%, 80.3% and 72.4%, respectively). The kappa test indicated a good consistency between DFF and the actual diagnosis (kappa = 0.551, P<0.001). Ten-fold cross-validation showed a stable performance of DFF with a mean AUC of 0.863 (sensitivity: 78.8%, specificity: 77.8%) in 10 training sets and a mean AUC of 0.866 (sensitivity: 80.9%, specificity: 84.1%) in 10 test sets. Conclusions: A more violent glucose fluctuation pattern was marked in patients with LADA than T2DM. We first proposed the possible role of DFF in distinguishing patients with LADA from T2DM in our study population, which may assist in diabetes classification.

Metabolic syndrome associated with higher glycemic variability in type 1 diabetes: A multicenter cross-sectional study in china.

Aims: The comorbidity of metabolic syndrome (MetS) and type 1 diabetes mellitus (T1DM) is an obstacle to glucose control in patients with T1DM. We compared glycemic profiles using continuous glucose monitoring (CGM) systems in patients with T1DM with or without MetS. Methods: This was a multicenter cross-sectional study of patients with T1DM (N = 207) with or without MetS. CGM data were collected from study enrollment until discharge during a 1-week study session. We analyzed baseline HbA1c, average glucose, estimated HbA1c, time in range (TIR), time above range (TAR), time below range (TBR), coefficient of variation (CV), postprandial glucose excursions (PPGE) and other glycemic variability (GV) metrics. Logistic regression was developed to investigate the association between MetS and CGM metrics. Results: The results showed higher average baseline HbA1c levels, and a higher percentage of patients with baseline HbA1c levels ≥7.5%, in the T1DM with MetS group. Furthermore, MetS was associated with GV, which indicated a higher CV in patients with T1DM with MetS. However, our results showed that TAR, TIR, TBR and other GV metrics were comparable between the two groups. The T1DM with MetS group also had a higher proportion of patients with high CV (≥ 36%) than the group without MetS. In multivariable logistic regression analysis, the presence of MetS was a risk factor for high CV (≥ 36%) in our study participants. Conclusions: T1DM patients with MetS in our study had better ß-cell function. However, MetS was associated with worse glycemic control characterized by higher GV and HbA1c levels. Efforts should be expanded to improve treatment of MetS in patients with T1DM to achieve better glycemic control.

The continuous spectrum of glycaemic variability changes with pancreatic islet function: A multicentre cross-sectional study in China.

AIMS: To investigate glycaemic variability (GV) patterns in patients with type 1 diabetes (T1D), type 2 diabetes (T2D), and latent autoimmune diabetes in adults (LADA). MATERIALS AND METHODS: A total of 842 subjects (510 T1D, 105 LADA, 227 T2D) were enrolled and underwent 1 week of continuous glucose monitoring (CGM). Clinical characteristics and CGM parameters were compared among T1D, LADA, and T2D. LADA patients were divided into two subgroups based on glutamic acid decarboxylase autoantibody titres (≥180 U/mL [LADA-1], <180 U/mL [LADA-2]) and compared. The C-peptide cut-offs for predicting a coefficient of variation (CV) of glucose ≥36% and a time in range (TIR) > 70% were determined using receiver operating characteristic analysis. RESULTS: Twenty-seven patients (9 T1D, 18 T2D) were excluded due to insufficient CGM data. Sex, diabetes duration and HbA1c were comparable among the three groups. Fasting and 2-h postprandial C-peptide (FCP, 2hCP) increased sequentially across T1D, LADA, and T2D. T1D and LADA patients had comparable TIR and GV, whereas those with T2D had much higher TIR and lower GV (p < 0.001). The GV of LADA-1 was close to that of T1D, while the GV of LADA-2 was close to that of T2D. CP exhibited the strongest negative correlation with GV. The cut-offs of FCP/2hCP for predicting a CV ≥ 36% and TIR >70% were 121.6/243.1 and 128.9/252.8 pmol/L, respectively. CONCLUSIONS: GV presented a continuous spectrum across T1D, LADA-1, LADA-2, and T2D. More frequent glucose monitoring is suggested for patients with impaired insulin secretion. CLINICAL TRAIL REGISTRATION: Chinese Clinical Trial Registration (ChiCTR) website approved by WHO; http://www.chictr.org.cn/ - ChiCTR2200065036.

Corrigendum: Effect of the Chinese New Year public holiday on the glycemic control of T1DM with intensive insulin therapy.

[This corrects the article DOI: 10.3389/fendo.2022.915482.].

Effect of the Chinese New Year Public Holiday on the Glycemic Control of T1DM With Intensive Insulin Therapy.

Aims: There is limited evidence that evaluates the glycemic control of type 1 diabetes mellitus (T1DM) during the Chinese New Year public holiday in China. The Chinese New Year public holiday represents various challenges to glycemic control, especially in T1DM patients, in China. We aimed to assess the effect of the Chinese New Year public holiday on several glucose metrics using flash glucose monitoring (FGM) in patients with T1DM. Methods: Complete FGM data for 1 week before, 1 week during and 1 week after the Chinese New Year public holiday were available for 71 T1DM patients treated with multiple daily insulin injection (MDI) therapy (n = 51) or continuous subcutaneous insulin infusion (CSII) treatment (n = 20). The mean age of the study participants was 13 (9, 30) years. Of note, 59.2% of the patients (n = 42) were adults, and 40.8% of the patients (n = 29) were minors. The interval between each two adjacent periods was one week. The indicators of mean glucose, glucose variability and time in different glycemic ranges were analyzed. Results: The Chinese New Year public holiday was associated with an increase in mean blood glucose (8.4 ± 1.7 vs. 9.2 ± 2.5; P < 0.001) and time above range (TAR) (27.9% ± 16.6% vs. 35.0% ± 22.3%; P< 0.001) but a decrease in time in range (TIR) (65.1% ± 15.5% vs. 58.0% ± 19.0%; P < 0.001) and coefficient of variation (CV) (65.1% ± 15.5% vs. 58.0% ± 19.0%; P < 0.001). There was no significant difference in time below range (TBR). The glycemic control deteriorated during the Chinese New Year public holiday in our study population regardless of age. Interestingly, in the CSII group, none of the metrics of glucose control significantly changed during the Chinese New Year public holiday. Conclusions: These results suggested that less self-management may worsen glycemic control in the short term, indicating a need for more refined management algorithms during the Chinese New Year public holiday for T1DM patients.

Advances of deep learning in electrical impedance tomography image reconstruction.

Electrical impedance tomography (EIT) has been widely used in biomedical research because of its advantages of real-time imaging and nature of being non-invasive and radiation-free. Additionally, it can reconstruct the distribution or changes in electrical properties in the sensing area. Recently, with the significant advancements in the use of deep learning in intelligent medical imaging, EIT image reconstruction based on deep learning has received considerable attention. This study introduces the basic principles of EIT and summarizes the application progress of deep learning in EIT image reconstruction with regards to three aspects: a single network reconstruction, deep learning combined with traditional algorithm reconstruction, and multiple network hybrid reconstruction. In future, optimizing the datasets may be the main challenge in applying deep learning for EIT image reconstruction. Adopting a better network structure, focusing on the joint reconstruction of EIT and traditional algorithms, and using multimodal deep learning-based EIT may be the solution to existing problems. In general, deep learning offers a fresh approach for improving the performance of EIT image reconstruction and could be the foundation for building an intelligent integrated EIT diagnostic system in the future.

Protective effects of hydrogen-rich saline against renal ischemia-reperfusion injury by increased expression of heme oxygenase-1 in aged rats.

OBJECTIVE: Oxygen free radicals (ROS) are considered to be one of the important factors involved in the pathophysiology of aged renal ischemia-reperfusion (I/R) injury. Hydrogen gas has been reported to alleviate I/R injury by scavenging free radicals. The aim of this study was to evaluate the effect of hydrogen-rich saline (HRS) on renal I/R injury in aged rats. MATERIALS AND METHODS: A rat model of renal I/R injury was induced by 45-min occlusion of the bilateral renal pedicles and 24-h reperfusion. Physiological saline or HRS (8 ml/kg) was administered intraperitoneally 5 min before reperfusion. Parameters indicating renal function (blood urea nitrogen (BUN) and serum creatinine (SCr)) and those indicating oxidative stress (tissue levels of malondialdehyde (MDA) and 8-hydroxy-deoxyguanosine (8-OHdG), tissue activities of superoxide dismutase (SOD), and tissue expression of heme oxygenase-1 (HO-1)) were measured. RESULTS: After I/R injury, BUN, SCr, tissue levels of MDA and 8-OHdG, and gene expression of HO-1 were all significantly increased while tissue activities of SOD were significantly decreased. HRS reversed these changes, with the exception of HO-1 expression, which was increased further, and improved renal morphology. CONCLUSIONS: HRS improves the renal response to I/R in aged rats, possibly by reducing oxidative stress and upregulating HO-1 gene expression.