Search Results (51)

Background/Objectives: Compared to in the general pregnant population, pregnancy in women with type 1 diabetes (T1D) is still associated with an increased number of perinatal complications affecting both the fetus and the mother. The Great Orchestra of Christmas Charity Foundation (GOCCF) program enables the use of continuous subcutaneous insulin infusion (CSII) enhanced by a hypo-stop function and real-time continuous glucose monitoring (rtCGM) during the preconception or early pregnancy period in patients with T1D. This observational study aimed to analyze the association between pregnancy planning and pregnancy outcomes in patients who qualified for the GOCCF program. Methods: Ninety-eight women with T1D, aged 21–41 years, who began using the CSII + rtCGM system at the planning/early pregnancy stage or at a later stage in the case of an unplanned pregnancy, were eligible for this study. We analyzed glucose control, the insulin requirements, the pregestational BMI, the maternal weight gain, the occurrence of preterm births, congenital malformations and the birthweight of newborns. Results: Women who planned their pregnancies had significantly better glycemic control before and throughout the entire pregnancy, and a significantly higher proportion of them achieved a TIR (time in range) > 70% (58.7% vs. 28.9%, p = 0.014) and TAR (time above range) < 25% (65.2% vs. 24.4%, p < 0.001). Their glucose variability at the end of the pregnancy was significantly lower (29.4 ± 5.5 vs. 31.9 ± 5.1, p = 0.030). They also gave birth later, at a mean of 37.8 ± 0.9 weeks compared to 36.9 ± 1.8 weeks in the non-planned group (p = 0.039). Preterm birth occurred in five women (10.4%) who planned their pregnancies and in fifteen women (30%) who did not, with p = 0.031. Conclusions: Pregnancy planning in women with type 1 diabetes (T1D) is associated with better glucose control before conception and throughout the entire pregnancy, resulting in better pregnancy outcomes. Full article

Diabetes mellitus (DM) is one of the most common endocrine disorders in dogs. Glycated albumin (GA), a biomarker of short-term glycemia, may offer a valuable tool for assessing glycemic control in dogs with DM. This pilot study evaluated the correlation between GA and conventional glycemic markers and continuous glucose monitoring (CGM)-derived metrics in dogs. A total of 30 dogs were included in this prospective pilot study, comprising dogs with diabetes mellitus (n = 10) and healthy controls (n = 20). Of these, 11 dogs that lacked anemia, hypoalbuminemia, or azotemia and whose owners consented to 14-day CGM were analyzed for sensor-based metrics (dogs with diabetes, n = 7; controls, n = 4). Across the full cohort, GA showed significant correlations with fructosamine and HbA1c, while within the CGM subset, GA was significantly associated with mean glucose level, TIR2, and TAR2. These findings suggest that GA, in conjunction with fructosamine and HbA1c, offers valuable insights into glycemic control over a 2-week period and could serve as a reliable biomarker for glucose monitoring in dogs with diabetes. Full article

Pyrolysis is an important methodology for achieving efficient and clean utilization of coal. Lump coal pyrolysis demonstrates distinct advantages over pulverized coal processing, particularly in enhanced gas yield and superior coke quality. As a critical parameter in lump coal pyrolysis, particle size significantly influences heat transfer and mass transfer during pyrolysis, yet its governing mechanisms remain insufficiently explored. This research systematically investigates pyrolysis characteristics of the low-rank coal from Ordos, Inner Mongolia, across graded particle sizes (2–5 mm, 5–10 mm, 10–20 mm, and 20–30 mm) through pyrolysis experiments. Real-time central temperature monitoring of coal bed coupled with advanced characterization techniques—including X-ray diffraction (XRD), Raman spectroscopy, Brunauer–Emmett–Teller (BET) analysis, scanning electron microscopy (SEM), gas chromatography (GC), and GC–mass spectrometry (GC-MS)—reveals particle-size-dependent pyrolysis mechanisms. Key findings demonstrate that the larger particles enhance bed-scale convective heat transfer, accelerating temperature propagation from reactor walls to the coal center. However, excessive sizes cause significant intra-particle thermal gradients, impeding core pyrolysis. The 10–20 mm group emerges as optimal—balancing these effects to achieve uniform thermal attainment, evidenced by 20.99 vol% peak hydrogen yield and maximum char graphitization. Tar yield first demonstrates a tendency to rise and then decline, peaking at 14.66 wt.% for 5–10 mm particles. This behavior reflects competing mechanisms: enlarging particle size can improve bed permeability (reducing tar residence time and secondary reactions), but it can also inhibit volatile release and intensify thermal cracking of tar in oversized coal blocks. The BET analysis result reveals elevated specific surface area and pore volume with increasing particle size, except for the 10–20 mm group, showing abrupt porosity reduction—attributed to pore collapse caused by intense polycondensation reactions. Contrasting previous studies predominantly focused on less than 2 mm pulverized coal, this research selects large-size (from 2 mm to 30 mm) lump coal to clarify the effect of particle size on coal pyrolysis, providing critical guidance for industrial-scale lump coal pyrolysis optimization. Full article

Objectives: This study will characterize continuous glucose monitoring (CGM) data in patients with type 2 diabetes in China, and assess the relationship between CGM-derived indicators and diabetes-related clinical parameters. Methods: The data for this study were collected from a randomized trial in China (ChiCTR2000039424) from February 2020 to July 2022 in which patients wore a CGM device for 14 days. Glycemia risk index (GRI), coefficient of variation (CV), standard deviation (SD), mean amplitude of glycemic excursions (MAGE), time in range (TIR), time above range (TAR), time below range (TBR), and estimate glycated hemoglobin (eA1c) were analyzed. Ordinary least square linear regression and the Spearman method were used to test the relationship between CGM-derived indicators and diabetes-related clinical parameters. Results: In all, 528 patients with type 2 diabetes from a randomized controlled trial were analyzed. It was shown that CV, SD, and MAGE increased with age and diabetes duration, but decreased with an increase in body mass index. Higher fasting plasma glucose, higher baseline HbA1c, and higher insulin resistance levels were associated with higher GRI, SD, MAGE, TAR, and eA1c, and they were associated with lower TIR. In addition, higher HOMA-2β was associated with higher TIR and TBR, and with lower TAR and eA1c. Hemoglobin had positive correlations to SD, TAR, and eA1c. Conclusions: It was found that glucose variability increased with age and the duration of diabetes. However, glucose variability decreased with increased BMI. Meanwhile, greater glycemic variability was associated with worse islet function, higher baseline glucose level, and higher hemoglobin. Full article

Community-based citizen science plays a vital role in biodiversity conservation by engaging the public in scientific research while fostering environmental awareness. This study evaluates a citizen science project conducted in the Taoyuan Algal Reef (TAR) region of Taiwan, focusing on participants’ motivations, learning outcomes, and their relationship with behavioral intentions toward biodiversity conservation. Despite a small sample size, our findings provide valuable insights into the effectiveness of such initiatives. Learning and self-achievement emerged as the primary motivators for participation, with social interaction playing a secondary role. Using the structural equation model (SEM), we confirmed that attitude serves as a critical mediator between knowledge, sense of place, and behavioral intention. This supports the Knowledge-Attitude-Behavior (KAB) model, emphasizing that knowledge acquisition fosters attitudinal shifts that ultimately drive conservation behavior. Moreover, place-based learning was identified as a key component in strengthening participants’ sense of place and ecological awareness. Our findings suggest that aligning citizen science initiatives with participants’ motivations enhances engagement and long-term conservation efforts. Additionally, ongoing community monitoring not only contributes to scientific data collection but also empowers local communities in environmental decision-making. This study highlights the broader educational, social, and ecological benefits of community-based citizen science and underscores the need for systematic evaluations to optimize its impact. Full article

Background: Diabetes affects over 460 million people worldwide and represents a growing public health challenge driven largely by dietary and lifestyle factors. While Type 2 diabetes (T2D) is more prevalent, Type 1 diabetes (T1D) presents unique therapeutic challenges, particularly in younger individuals. Advances in diabetes management, such as continuous glucose monitoring (CGM), insulin pumps (IP), and, more recently, smart multiple dose injection (MDI) pens, have significantly enhanced glycemic control and improved patients’ quality of life. Aim: This study aims to evaluate the baseline characteristics of patients switching from MDI therapy to the Medtronic Smart MDI system [composed of a smart insulin pen (InPenTM) and a connected CGM Medtronic SimpleraTM sensor] and to assess its impact on glycemic outcomes over different time periods (14, 30, and 90 days). Methods: A retrospective observational study was conducted among adults with T1D who initiated Medtronic Smart MDI therapy. Participants were enrolled voluntarily at the Diabetes and Nutrition Clinic in Ast Fermo, Marche Region, Italy. Glycemic parameters were monitored using CGM data and analyzed with descriptive statistics, including mean, standard deviation (SD), and interquartile range (IQR). Comparisons across time periods were performed using the Wilcoxon signed-rank test, with statistical significance set at p < 0.05. Results: This study included 21 participants with a mean age of 51.5 years, a mean BMI of 24.7, and a mean duration of T1D of 21.9 years. The transition from a traditional MDI system to the Smart MDI system resulted in significant improvements in key glycemic parameters: mean Sensor Glucose (SG) decreased from 171.0 mg/dL to 153.5 mg/dL (p = 0.035), Time In Range (TIR) increased from 58.0% to 64.4% (p = 0.005), and time above range (TAR; >180 mg/dL) decreased from 39.0% to 34.2% (p = 0.015). No significant differences were observed in the time below range (TBR). Conclusions: The transition to the Medtronic Smart MDI system significantly enhanced glycemic control by lowering mean glucose levels and increasing TIR. These findings highlight its efficacy in improving hyperglycemia management while maintaining a stable risk of hypoglycemia. Full article

Background: This study addresses hypoglycemia in adults with inherited metabolic disorders (IMDs), highlighting the importance of intermittently scanned continuous glucose monitoring (isCGM). Despite the elevated risk of hypoglycemia in an important group of these diseases, the use of isCGM remains uncommon and there is limited evidence supporting its effectiveness. Methods: A longitudinal quasi-experimental study was performed in 18 adults with IMDs, evaluating the use of isCGM for 2 months. Time in hypoglycemia (TBR), hyperglycemia (TAR), and time in range (TIR) were monitored, in addition to symptomatic and asymptomatic hypoglycemic events. Follow-up visits were performed at 7 days, 14 days, and 2 months. Results: TBR < 70 mg/dL was significantly reduced from 1.5% at baseline to 0% at 2 months. A decrease in the number and duration of hypoglycemic events was also observed. In some IMD subgroups, isCGM enabled detection of asymptomatic hypoglycemia and adjustment to dietary management, improving glycemic control. Conclusions: isCGM is effective in detecting and reducing hypoglycemia in adults with IMDs, optimizing nutritional therapy, and improving the quality of life of patients and their families. Full article

This study focused on the investigation of soil samples from the alluvial zone of the Sava River, located near the heating plant in New Belgrade, Serbia. Using gas chromatography with flame ionization detection (GC-FID), a broad range of alkanes, including linear n-alkanes (C₁₀ to C₃₃) and isoprenoids, was analyzed in all samples. The obtained datasets were effectively made simpler by applying multivariate statistical analysis. Various geochemical indices (CPI, ACL, AI, TAR, etc.) and ratios (S/L, Paq, Pwax, etc.) were calculated and used to distinguish between biogenic and anthropogenic contributions. This approach added a higher level of precision to the source identification of hydrocarbons and provided a detailed geochemical characterization of the investigated soil. The results showed that the topsoil had a high content of TPH (average value, 90.65 mg kg⁻¹), potentially related to an accidental oil spill that occurred repeatedly over extended periods. The uncommon n-alkane profiles reported for the investigated soil samples are probably the result of inputs related to anthropogenic sources, emphasizing that petroleum was the main source of the short-chain n-alkanes. The methodology developed in this study was proven to be efficient for the assessment of the environmental quality of the soil in an urban part of New Belgrade, but it can also be a useful tool for soil monitoring and for a pollution assessment in other (sub)urban areas. Full article

Neurosyphilis-induced dementia represents a severe manifestation of tertiary syphilis, characterized by cognitive and neuropsychiatric impairments. This condition arises from the progression of syphilis to the central nervous system, where the spirochete causes damage through invasion, chronic inflammation, and neurodegeneration. The pathophysiology involves chronic inflammatory responses, direct bacterial damage, and proteinopathies. Treponema pallidum triggers an inflammatory cascade, resulting in neuronal injury and synaptic dysfunction. Abnormal protein accumulations, including TAR DNA-binding protein 43 (TDP-43) and tau, contribute to neuronal loss and cognitive decline. Seizures, psychiatric symptoms, and motor deficits further complicate the progression of dementia. Diagnosis includes clinical assessment, cerebrospinal fluid analysis, and neuroimaging. Diagnostic tests include CSF-VDRL, FTA-ABS, and neuroimaging techniques such as MRI and PET scans, which help detect structural changes and confirm neurosyphilis. Management of neurosyphilis-induced dementia involves antibiotic therapy and psychotropic medications to address both infectious and symptomatic components. While penicillin remains the cornerstone of treatment, psychotropic agents, including haloperidol, risperidone, quetiapine, and divalproex sodium, can manage psychiatric symptoms. However, careful monitoring is required due to potential side effects and interactions with ongoing treatment. Overall, early diagnosis and comprehensive management are crucial for mitigating the cognitive and neuropsychiatric impairments associated with neurosyphilis-induced dementia. Full article

Background: Effective self-management is crucial in diabetes care. This study investigates the impact of Personal Health Records (PHR) on diabetes management and person self-management behaviors. Methods: Retrospective cohort study was conducted involving individuals with diabetes using insulin and prescribed FreeStyle Libre^®. Participants were categorized into PHR users and non-users. Key metrics such as HbA1c, Time in Range (TIR), Time above Range (TAR), and body weight were analyzed. Results: Among 212 intermittently scanned continuous glucose monitoring (isCGM) users, 25 individuals used PHR. Comparing 21 individuals using a PHR with 42 matched controls, the TIR significantly increased (ΔTIR 17.2% vs. 1.90%, p = 0.020), and HbA1c levels showed a greater decrease (ΔHbA1c −0.83% vs. −0.22%, p = 0.023). A significant reduction was also observed in TAR among PHR users (ΔTAR −17.6% vs. −1.63%, p = 0.017). There were no significant changes in body weight (ΔBW −0.51 kg vs. −1.60 kg, p = 0.578). Conclusions: PHR systems demonstrate potential in improving diabetes management by enhancing self-management practices and glycemic control. Although the sample size of PHR users was relatively low, PHR should be more widely used. The study underscores the need for further research on PHR’s long-term impact and its applicability in diverse diabetic populations. Full article

Despite the implementation of numerous interventions to enhance urban traffic safety, the estimation of the risk of traffic crashes resulting in life-threatening and economic costs remains a significant challenge. In light of the above, an online inference method for traffic crash risk based on the self-developed TAR-DETR and WOA-SA-SVM methods is proposed. The method’s robust data inference capabilities can be applied to autonomous mobile robots and vehicle systems, enabling real-time road condition prediction, continuous risk monitoring, and timely roadside assistance. First, a self-developed dataset for urban traffic object detection, named TAR-1, is created by extracting traffic information from major roads around Hainan University in China and incorporating Russian car crash news. Secondly, we develop an innovative Context-Guided Reconstruction Feature Network-based Urban Traffic Objects Detection Model (TAR-DETR). The model demonstrates a detection accuracy of 76.8% for urban traffic objects, which exceeds the performance of other state-of-the-art object detection models. The TAR-DETR model is employed in TAR-1 to extract urban traffic risk features, and the resulting feature dataset was designated as TAR-2. TAR-2 comprises six risk features and three categories. A new inference algorithm based on WOA-SA-SVM is proposed to optimize the parameters (C, g) of the SVM, thereby enhancing the accuracy and robustness of urban traffic crash risk inference. The algorithm is developed by combining the Whale Optimization Algorithm (WOA) and Simulated Annealing (SA), resulting in a Hybrid Bionic Intelligent Optimization Algorithm. The TAR-2 dataset is inputted into a Support Vector Machine (SVM) optimized using a hybrid algorithm and used to infer the risk of urban traffic crashes. The proposed WOA-SA-SVM method achieves an average accuracy of 80% in urban traffic crash risk inference. Full article

This narrative review explores the current landscape of blood biomarkers in Frontotemporal dementia (FTD). Neurofilament light chain (NfL) may be useful in the differentiation of behavioral variant FTD from primary psychiatric disorders (PPDs) or dementia with Lewy bodies (DLB). In prodromal FTD and presymptomatic mutation carriers (GRN, MAPT, C9orf72), elevated NfL may herald pheno-conversion to full-blown dementia. Baseline NfL correlates with steeper neuroanatomical changes and cognitive, behavioral and functional decline, making NfL promising in monitoring disease progression. Phosphorylated neurofilament heavy chain (pNfH) levels have a potential limited role in the demarcation of the conversion stage to full-blown FTD. Combined NfL and pNfH measurements may allow a wider stage stratification. Total tau levels lack applicability in the framework of FTD. p-tau, on the other hand, is of potential value in the discrimination of FTD from Alzheimer’s dementia. Progranulin concentrations could serve the identification of GRN mutation carriers. Glial fibrillary acidic protein (GFAP) may assist in the differentiation of PPDs from behavioral variant FTD and the detection of GRN mutation carriers (additional research is warranted). Finally, TAR DNA-binding protein-43 (TDP-43) appears to be a promising diagnostic biomarker for FTD. Its potential in distinguishing TDP-43 pathology from other FTD-related pathologies requires further research. Full article

This study investigates glucose conditions preceding and following various hypoglycemia levels in individuals with type 1 diabetes using open-source automated insulin delivery (AID) systems. It also seeks to evaluate relationships between hypoglycemia and subsequent glycemic variability. Methods: Analysis of continuous glucose monitor (CGM) data from 122 adults with type 1 diabetes using open-source AID from the OpenAPS Data Commons was conducted. This study comprehensively analyzed the effects of hypoglycemia on glycemic variability, covering time periods before and after hypoglycemia. Results: Glucose variability normalization post-hypoglycemia can take up to 48 h, with severe hypoglycemia (41–50 mg/dL) linked to prolonged normalization. A cyclical pattern was observed where hypoglycemia predisposes individuals to further hypoglycemia, even with AID system use. A rise in glucose levels often precedes hypoglycemia, followed by an elevated mean time above range (TAR) post-hypoglycemia, indicating a ‘rebound’ effect. The experimental results are further validated on T1DEXI data (n = 222), originating from commercial AID systems. Different hypoglycemia categorization approaches did not show significant differences in glycemic variability outcomes. The level of hypoglycemia does influence the pattern of subsequent glucose fluctuations. Conclusion: Hypoglycemia, especially at lower levels, significantly impacts subsequent glycemic variability, even with the use of open-source AID systems. This should be studied further with a broader set of commercial AID systems to understand if these patterns are true of all types of AID systems. If these patterns occur in all types of AID systems, it underscores potential opportunities for enhancements in AID algorithms and highlights the importance of educating healthcare providers and people with diabetes about post-hypoglycemia glucose variability. Full article

Background/Objectives: Traditional glycemic monitoring in type 2 diabetes is limited, whereas continuous glucose monitoring (CGM) offers better insights into glucose fluctuations. This study aimed to determine the correlations and relative contributions of fasting plasma glucose (FPG) and postprandial plasma glucose (PPG) levels to hyperglycemia. Methods: We utilized CGM and recorded carbohydrate intake data from lifestyle diaries of 59 patients enrolled in the Diabetes and Lifestyle Cohort Twente (DIALECT-2). Correlations between FPG and the glucose management indicator (GMI), FPG and Time Above Range (TAR), PPG and GMI, and PPG and TAR were conducted. Daily and mealtime relative contributions of PPG and FPG to glycated hemoglobin (HbA_1c) and GMI were determined, considering two ranges: on target (<7.0%, 53 mmol/mol) and not on target (≥7.0%, 53 mmol/mol). Correlations between mealtime PPG and carbohydrate consumption were examined. Results: FPG and PPG correlated with GMI (r = 0.82 and 0.41, respectively, p < 0.05). The relative contribution of PPG in patients with HbA_1c, GMI, and TAR values not on target was lower than in patients with HbA_1c, GMI, and TAR values on target. When analyzing different mealtimes, patients with target GMI values had a higher PPG (73 ± 21%) than FPG after breakfast (27 ± 21%, p < 0.001). Individuals with elevated GMI levels had lower PPG after lunch (30 ± 20%), dinner (36 ± 23%), and snacks (34 ± 23%) than FPG. PPG after breakfast positively correlated (r = 0.41, p < 0.01) with breakfast carbohydrate intake. Conclusions: Both PPG and FPG contribute to hyperglycemia, with PPG playing a larger role in patients with better glycemic control, especially after breakfast. Targeting PPG may be crucial for optimizing glucose management. Full article

Background/Objectives: Obesity and overweight have become increasingly prevalent in different populations of people with type 1 diabetes (PwT1D). This study aimed to assess the effect of body weight on glycaemic indices in PwT1D. Methods: Adult PwT1D using continuous glucose monitoring (CGM) and followed up at a regional academic diabetes centre were included. Body weight, body mass index (BMI), waist circumference, glycated haemoglobin (HbA1c), and standard CGM glycaemic indices were recorded. Glycaemic indices were compared according to BMI, and correlation and linear regression analysis were performed to estimate the association between measures of adiposity and glycaemic indices. Results: A total of 73 PwT1D were included (48% normal weight, 33% overweight, and 19% obese). HbA1c was 7.2% (5.6–10), glucose management indicator (GMI) 6.9% (5.7–8.9), coefficient of variation (CV) for glucose 39.5% ± 6.4, mean glucose 148 (101–235) mg/dL, TIR (time in range, glucose 70–180 mg/dL) 66% (25–94), TBR₇₀ (time below range, 54–69 mg/dL) 4% (0–16), TBR₅₄ (<54 mg/dL) 1% (0–11), TAR₁₈₀ (time above range, 181–250 mg/dL) 20% ± 7, and TAR₂₅₀ (>250 mg/dL) 6% (0–40). Glycaemic indices and achievement (%) of optimal glycaemic targets were similar between normal weight, overweight, and obese patients. BMI was associated negatively with GMI, mean glucose, TAR₁₈₀, and TAR₂₅₀ and positively with TIR; waist circumference was negatively associated with TAR₂₅₀. Conclusions: CGM-derived glycaemic indices were similar in overweight/obese and normal weight PwT1D. Body weight and BMI were positively associated with better glycaemic control. PwT1D should receive appropriate ongoing support to achieve optimal glycaemic targets whilst maintaining a healthy body weight. Full article