Current Issue : October-December Volume : 2026 Issue Number : 4 Articles : 5 Articles
Objective: To determine plasma cystatin C concentrations, urine osmolality and their relationship with disease severity in beta-thalassemia patients. Methods: A cross-sectional study was conducted on 234 patients with beta-thalassemia, including equal numbers (78 each) of beta-thalassemia major, intermedia, and minor cases, along with 78 healthy individuals matched for age, sex, and body mass index, who served as the control group. Plasma cystatin C concentrations were quantified in all subjects using the ELISA method, and urine osmolality level was measured automatically on a FISKE 210 machine (USA). Results: The proportion of beta-thalassemia patients with increased plasma cystatin C concentration was 39.3% and the proportion with a decreased urine osmolality level was 67.5% compared with the control group. Plasma ferritin had predictive value for increased plasma cystatin C concentration (cut-off point: 567.5 ng/mL; AUC = 0.803) and decreased urine osmolality level (cut-off point: 488.15 ng/mL; AUC = 0.820), p < 0.001. Plasma cystatin C concentration increased gradually and urine osmolality level decreased gradually from minor beta-thalassemia to intermedia beta-thalassemia to major beta-thalassemia patients, with p < 0.001. Conclusions: Increased plasma cystatin C concentrations and decreased urine osmolality levels are common and are associated with severity in beta-thalassemia patients....
Background: Although several risk factors have been reported for long COVID (LC), reliable biomarkers for this illness remain lacking. Insulin-like growth factor (IGF)-I, a major mediator of growth hormones, plays an important role in metabolism, neuroprotection, and systemic homeostasis, and therefore may be useful in predicting the severity and prognosis of LC. Methods: This study included patients who visited a specialized clinic for long COVID between 2022 and 2025 during the Omicron period and had serum IGF-I measurements taken. IGF-I levels were expressed as age- and sex-adjusted standard deviation scores (IGF-I SD), and patients were classified into low (SD < −1.0), normal (−1.0 ≤ SD < 1.0), and high (SD ≥ 1.0) groups. Clinical characteristics, patient-reported outcomes, laboratory data, and follow-up duration were analyzed. Results: A total of 811 patients were included (median 42 years; 52.5% female). Compared with the normal group, the low-IGF-I group exhibited higher fatigue (FAS: 37.0 vs. 34.0; p < 0.05) and depressive (SDS: 50.0 vs. 49.0; p < 0.05) status. Multivariable linear regression analyses identified lower IGFI SD as independently associated with higher scores of both FAS and SDS. IGF-I SD values showed negative correlations with ferritin (ρ = −0.125, p < 0.05) and TSH (ρ = −0.202, p < 0.01) and positive correlations with albumin (ρ = 0.227, p < 0.01) and FT4 (ρ = 0.165, p < 0.01). Among the 237 patients who completed follow-up, the median duration from the initial visit to recovery tended to be longer in the low-IGF-I group (221 days) compared with the normal (191 days) and high (109 days) groups, although these differences were not statistically significant overall. In patients aged < 50 years, the low-IGF-I group showed a relatively longer follow-up duration (p < 0.05). Furthermore, the low-IGF-I group had a longer time to recovery compared to the high-IGF-I group (p < 0.05), and this difference was more pronounced in patients under 50 years of age, with significant differences observed among the three IGF-I groups. Conclusions: Lower IGF-I levels in LC may be associated with greater fatigue and depressive symptoms and longer recovery time, particularly in younger patients. Further studies are needed to clarify the clinical significance of these findings....
Background: Autoimmune encephalitis (AE) is an increasingly well recognized disorder in the past decade both in adults and in children, yet pediatric data are still limited. A full peripheral blood cell count is a routine examination that provides valuable information regarding the immune system. Thus, there are peripheral blood cell count (PBCC)-derived ratios that reflect systemic inflammatory activity and they have been associated with disease severity in adults: the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), systemic immune–inflammation index (SII), systemic inflammation response index (SIRI), and aggregate index of systemic inflammation (AISI). Methods: This study is a retrospective chart review of children under 18 years diagnosed with definite or probable AE and treated in our institution from 1 January 2018 until 1 December 2025. Only patients with available PBCC results at the time of the first hospital admission after neurological/psychiatric symptom onset were included. An age-matched control group was created by selecting the results of PBCC of patients presenting for routine pediatric follow-ups with normal inflammatory and hematologic parameters. The group means were compared using an independent-samples t-test or the Mann–Whitney U test for non-normally distributed data. Analysis of the receiver operating characteristics curve (ROC curve) was conducted, followed by the area under the curve ROC curve (AUC). Results: A total of 45 children with AE and 150 controls were included in the study. Of these, 22 patients (49%) had probable AE and 23 patients (51%) had definite AE. The NLR, PLR, SII, SIRI and AISI values were significantly higher in AE patients compared with the controls, but the AUC values (~0.58–0.66) indicate poor-to-fair discriminative ability. Youden’s index-based cut-off values were associated with high specificity and modest sensitivity. The likelihood ratios in the range of 2–3 (LR+) and 0.6–0.7 (LR−) suggest weak rule-in capacity and limited rule-out utility. Conclusions: Our results suggest that at the time of the initial hospitalization, children with AE already show altered peripheral immune cell profiles compared to their age-matched peers. The high specificity and the low sensitivity of the inflammatory indices make them more suitable for supporting the AE diagnosis in suggestive clinical circumstances, but not for screening. These results represent a foundation for further investigation of the roles that these indices have both as diagnostic and prognostic factors for these children....
Background: Patients with inflammatory bowel disease (IBD) exhibit a hypercoagulable state with increased thrombotic risk. Previous studies demonstrated elevated thrombin generation in pediatric IBD, paradoxically accompanied by prolonged lag time during active disease. We hypothesized that elevated tissue factor pathway inhibitor (TFPI) levels during active inflammation contribute to this paradox. Methods: We prospectively enrolled 25 pediatric patients (10 Crohn’s disease [CD], 15 ulcerative colitis [UC]) aged 7–18 years with newly diagnosed IBD. Blood samples were collected at diagnosis and in remission. Thrombin generation was assessed using calibrated automated thrombography. Plasma levels of TFPI, tissue factor activity (TFA), vascular endothelial growth factor (VEGF), and interleukin-6 (IL-6) were measured. Results: TFPI levels correlated positively with thrombin generation lag time (r = 0.43, padj < 0.05) and disease activity scores (r = 0.54, padj < 0.05) in patients with active disease (PCDAI/PUCAI > 0). Longitudinal analysis of 16 patients achieving remission revealed elevated TFPI and prolonged lag time during active disease compared to quiescence (both padj < 0.05), while TFA did not change significantly. VEGF decreased significantly upon remission (padj < 0.05), whereas IL-6 showed no significant change. Conclusions: Elevated TFPI levels during active IBD likely contribute to the paradoxical prolongation of thrombin generation lag time. TFPI normalization upon remission reflects vascular inflammation resolution, suggesting TFPI as a potential biomarker and therapeutic target....
Breast cancer is the most common cancer globally and often diagnosed at advanced stages in Indonesia. Metabolomic profiling has emerged as a promising approach for identifying biomarkers associated with breast cancer (BC). However, the specificity and clinical applicability of candidate metabolites remain under investigation. This study investigates untargeted plasma metabolomic profiles of breast cancer patients to find candidate metabolite signatures of breast cancer. Plasma samples from 24 breast cancer patients and 24 healthy controls (HC) were analyzed using untargeted Gas Chromatography-Mass Spectrometry (GC-MS). A machine learning (ML) approach was utilized to validate the metabolites. Differential metabolites were identified and analyzed to explore altered metabolic pathways associated with BC. Several metabolites, including D-glucose, citric acid, lactic acid, L-hydroxyproline, and glutamic acid, were significantly different between BC and HC groups. Those metabolites correlated with arginine/proline metabolism, glycolysis, and alanine/aspartate/glutamate pathways. ML validation yielded favorable results for these metabolites as candidate metabolite signatures of breast cancer (AUC > 0.8, accuracy > 80%). Further subset analysis showed reduced dihydrouracil in late stage. Untargeted plasma metabolomic analysis combined with machine learning effectively identified a potential candidate metabolite signature for breast cancer. These findings improve understanding of breast cancer metabolic alterations and highlight promising pathways for early diagnosis. Nevertheless, further validation in larger, well-controlled studies is required to establish their diagnostic utility....
Loading....