Endocrine最新文献

Purpose: This review aims to provide updated information regarding the role of thyroid and leptin hormones and their crosstalk in affecting the male reproductive function in hypothyroid and obesity conditions.

Method: A wide literature search was made using online search engines on published articles using keywords including thyroid hormone, hypothyroidism, leptin hormone, hyperleptinemia, obesity, the relationship between thyroid and leptin hormones and male reproduction, and hypothyroidism, obesity, and male reproduction.

Results: All information pertaining thyroid and leptin hormone effects on male reproduction, hypothyroidism, hyperleptinemia, and obesity effect on male fertility as well as the related molecular mechanisms are obtained.

Conclusion: Thyroid and leptin hormones individually play a significant role in male reproduction. Alterations of these hormones' levels could adversely affect the male reproductive functions. PI3K/AKT signaling was found to be the major signaling pathway involved in mediating the effect of both hormones on male reproduction. Impaired crosstalk between the two hormones may occur in hypothyroidism with obesity which would contribute towards male reproductive dysfunction.

Background: Diabetic ketoacidosis (DKA) is often treated with intravenous regular insulin infusion (IVRII). Subcutaneous fast-acting insulin analogues (FAIAs); either alone or combined with subcutaneous long-acting insulin (LAI); might be useful to treat DKA. Our meta-analysis updated on their benefits and safety in DKA.

Methods: We searched major electronic databases for randomised trials on subcutaneous FAIAs ± subcutaneous LAI vs IVRII in DKA. Primary outcomes were all-cause in-hospital mortality, time to resolution of DKA and hyperglycemia, in-hospital DKA recurrence and hospital readmission for DKA post-discharge. Secondary outcomes included resource utilisation and patient satisfaction. Safety outcomes were adverse events. Reviewers assessed risk of bias and quality of evidence using GRADE. We performed a priori subgroup and trial sequential analyses on primary outcomes.

Results: Seven trials enrolled 351 mainly adult patients (255/351) with mild to moderate DKA. No trials studied subcutaneous FAIA and subcutaneous LAI. Their risk of bias was high or unclear in several domains. No all-cause in-hospital mortality and DKA recurrence were reported. No trial investigated hospital readmission for DKA post-discharge. There was no difference in mean time to resolution of DKA (mean difference = -0.70, 95% CI -2.18 to 0.79 h, p = 0.36) or hyperglycemia [blood glucose < 250 mg/dL (13.9 mmol/L)] (mean difference = -0.17, 95% CI -1.10 to 0.76 h, p = 0.72) between subcutaneous FAIA and IVRII groups. There were largely no subgroup effects. Both groups had similar secondary outcomes. Hypoglycemia was the most common adverse event. Quality of evidence was low to very-low for all outcomes. The only possible trial sequential analysis for time to resolution of DKA was inconclusive.

Conclusions: There was low- to very-low quality evidence that subcutaneous FAIA did not affect patient-centered outcomes in mainly adult patients with mild to moderate DKA compared to IVRII.

Diabetes mellitus (DM) is a complex metabolic disorder characterized by chronic hyperglycemia, which derives from either insufficient insulin production [type 1 diabetes mellitus (T1DM)] or both impaired insulin sensitivity along with inadequate insulin production [type 2 diabetes mellitus (T2DM)] and affects millions of people worldwide. In addition to the adverse effects of DM on classical target organs and tissues, skeletal health can also be adversely affected. There is considerable evidence linking DM with osteoporosis. The fracture risk in patients with DM differs upon the type of diabetes, and it appears to be related to the type of anti-diabetic treatment. Antidiabetic drugs may have various effects on bone health. Most of them have neutral or even favorable effects on bone metabolism with the exception of thiazolidinediones (TZDs). Some studies suggest that TZDs may have negative impact on bone health by decreasing bone formation and increasing the fracture risk. There are also limited studies linking the use of canagliflozin, a Sodium-glucose contransporter-2 inhibitor (SGLT2i), with increased fracture risk. On the other hand, therapies that are based on incretin effect, like Dipeptidyl peptidase-4 inhibitors (DPP-4i) and Glucagon-like peptide-1 receptor agonizts (GLP-1RAs) might have positive effects on bone health by promoting bone formation. Herein we review the impact of antidiabetic drugs on bone health, highlighting the potential benefits and risks associated with these medications in an attempt to contribute to the development of personalized treatment strategies for individuals with DM.

Purpose: Cardiometabolic disorders are non-classical complications of hypercalcemic primary hyperparathyroidism (HC-PHPT), but whether this risk connotes normocalcemic PHPT (NC-PHPT) remains to be elucidated. We investigated cardiometabolic alterations in both forms of PHPT, looking for their association with indices of disease activity.

Methods: Patients with HC-PHPT (n = 17), NC-PHPT (n = 17), and controls (n = 34) matched for age, sex, and BMI were assessed for glucose, lipid, blood pressure alterations, and history of cardiovascular events to perform a case-control study at an ambulatory referral center for Bone Metabolism Diseases.

Results: NC-PHPT, in comparison to controls, showed similar glucose (mean ± SD, 88 ± 11 vs 95 ± 22 mg/dl), total cholesterol (199 ± 25 vs 207 ± 36 mg/dl), and systolic blood pressure levels (SBP, 132 ± 23 vs 132 ± 19 mmHg), together with a comparable frequency of glucose alterations (6% vs 9%), lipid disorders (41% vs 50%) and hypertension (53% vs 59%, p = NS for all comparisons). Conversely, all these abnormalities were more prevalent in HC-PHPT vs controls (p < 0.05). When compared to NC-PHPT, HC-PHPT showed higher glucose (113 ± 31 mg/dl), total cholesterol (238 ± 43 mg/dl), and SBP levels (147 ± 15 mmHg) as well as an increased frequency of glucose (41%) and lipid alterations (77%) and a higher number of cardiovascular events (18% vs 0%, p < 0.05 for all comparisons). Among indices of PHPT activity, calcium levels displayed a significant correlation with glucose (R = 0.46) and SBP values (R = 0.60, p < 0.05).

Conclusion: NC-PHPT is not associated with cardiovascular alterations. The predominant pathogenetic role of hypercalcemia in the development of cardiometabolic disorders could account for the absence of such alterations in NC-PHPT.

Objective: Polycystic Ovarian Syndrome (PCOS) is a complex endocrine disorder that affects women of reproductive age. Several candidate genes have been shown to be associated with PCOS. Previous studies have shown that variations in CYP11A1 and CYP19A1 genes are associated with hormonal dysregulation associated with PCOS in different ethnic populations. This study aims to investigate the genomic association between SNPs rs4077582 of CYP11A1 and rs700519 of CYP19A1 and the development of PCOS in Pakistani population.

Methods: A total of 280 subjects were recruited for the study, including 142 PCOS cases diagnosed based on Rotterdam criteria and 138 age-matched controls. The anthropometric, hormonal and biochemical parameters of all subjects were analyzed. Genomic DNA was extracted and genotyping of the selected SNPs was performed using Sanger sequencing. Further, we also examined the genotypic-phenotypic correlation analysis for various clinical and biochemical parameters for SNP rs4077582 of CYP11A1.

Results: We found significant differences in allele frequency (OR = 0.42, 95% CI = 0.30-0.60, χ² = 16.3693, p = 0.000052) and genotypic frequency (χ² = 26.4376, p = 0.00001) between PCOS women and controls for SNP rs4077582 of CYP11A1. Genotype-phenotype correlation analysis showed a significant difference in FAI (p = 0.005), testosterone (p = 0.001), androstenedione (p = 0.005) and urea (p = 0.049) levels between the three genotypes. No association between SNP rs700519 of CYP19A1 and PCOS was observed.

Conclusion: Our results suggest the role of SNP rs4077582 of CYP11A1 gene in the clinical manifestation of PCOS in Pakistani women.

Papillary thyroid cancer (PTC) is the predominant form of malignant tumor affecting the thyroid gland.

Aim: This study aimed to identify candidate biomarkers for papillary thyroid carcinoma using an integrative analysis of bioinformatics and machine learning (ML).

Material and method: The PTC datasets GSE6004, GSE3467, and GSE33630 (species: Homo sapiens) were downloaded from NCBI and analyzed using the limma package to obtain DEGs. Once DEGs were identified, GO and KEGG enrichment analyses were performed as the first step in the bioinformatics process. Subsequently, a protein-protein interaction (PPI) network was constructed according to the common genes in bioinformatics and machine learning using STRING to elucidate the important genes involved in PTC pathogenesis. In machine learning, finding genes entails feature selection to identify the key genes that distinguish biological states. Hybrid feature selection will be used for this. In the second step, the original data sets were preprocessed to detect and correct missing and noisy data; after that, all data were merged. Following performing Linear and Discriminative Hybrid Feature Selection (LDHFS) on the processed dataset, machine learning algorithms such as Random Forest (RF), Naive Bayes (NB), and Support Vector Machines (SVM) are utilized.

Results: Bioinformatics and machine learning analyses indicate that the genes RXRG, CDH2, ETV5, QPCT, LRP4, FN1, and LPAR5 are integral to the progression of thyroid cancer. This study attained the highest accuracy utilizing the RF algorithm, achieving an accuracy rate of 94.62%, a Kappa value of 91.36%, and an AUC value of 96.13%. These results offer additional evidence and confirmation for the genetic alterations of these genes. These findings may accelerate the development of prospective therapeutic and diagnostic methods in future research.

Conclusions: Bioinformatics and machine learning techniques identified the common genes "RXRG, CDH2, ETV5, QPCT, LRP4, FN1, and LPAR5" as PTC biomarkers, providing novel reference markers for the diagnosis and treatment of PTC patients. The model is anticipated to possess significant predictive value and assist in the early diagnosis and screening of clinical PTC. These insights enhance the field of PTC management and offer guidance for future research.

Background: Hypoparathyroidism is a rare endocrine disease characterized by insufficient parathyroid hormone (PTH) secretion by the parathyroid glands, leading to hypocalcemia. In contrast to most hormone deficiencies for which hormone replacement is currently the mainstay of therapy, hypoparathyroidism has conventionally been treated with calcium supplements and active analogs of vitamin D. Although the advent of a replacement therapy with 1-34 and 1-84 PTH represented a major step in the therapeutic history of hypoparathyroidism, several new molecules and different management strategies have recently been developed.

Purpose: This review investigates the therapeutic approaches currently under investigation for the treatment of hypoparathyroidism. Clinical trials results have been considered and discussed.

Purpose: Large language models (LLMs) are pivotal in artificial intelligence, demonstrating advanced capabilities in natural language understanding and multimodal interactions, with significant potential in medical applications. This study explores the feasibility and efficacy of LLMs, specifically ChatGPT-4o and Claude 3-Opus, in classifying thyroid nodules using ultrasound images.

Methods: This study included 112 patients with a total of 116 thyroid nodules, comprising 75 benign and 41 malignant cases. Ultrasound images of these nodules were analyzed using ChatGPT-4o and Claude 3-Opus to diagnose the benign or malignant nature of the nodules. An independent evaluation by a junior radiologist was also conducted. Diagnostic performance was assessed using Cohen's Kappa and receiver operating characteristic (ROC) curve analysis, referencing pathological diagnoses.

Results: ChatGPT-4o demonstrated poor agreement with pathological results (Kappa = 0.116), while Claude 3-Opus showed even lower agreement (Kappa = 0.034). The junior radiologist exhibited moderate agreement (Kappa = 0.450). ChatGPT-4o achieved an area under the ROC curve (AUC) of 57.0% (95% CI: 48.6-65.5%), slightly outperforming Claude 3-Opus (AUC of 52.0%, 95% CI: 43.2-60.9%). In contrast, the junior radiologist achieved a significantly higher AUC of 72.4% (95% CI: 63.7-81.1%). The unnecessary biopsy rates were 41.4% for ChatGPT-4o, 43.1% for Claude 3-Opus, and 12.1% for the junior radiologist.

Conclusion: While LLMs such as ChatGPT-4o and Claude 3-Opus show promise for future applications in medical imaging, their current use in clinical diagnostics should be approached cautiously due to their limited accuracy.

The approval in 2017 by the European Medicines Agency (EMA) and in 2018 by the US Food and Drug Administration (FDA) of radioligand therapy (RLT) led to its wide application in therapeutic management of neuroendocrine neoplasms (NENs). However, the indications are currently limited to certain specific histotypes belonging to the broader NEN's family, mainly advanced well-differentiated gastro-entero-pancreatic NENs. As a consequence, several other tumors of the NEN spectrum that can potentially benefit, due to their biological characteristics, from RLT are still ineligible and can be considered "RLT-orphans". Among those, the subgroup of NENs originating from the sympathetic-adrenal-medullary (SAM) axis can be listed. This paper discusses the state of art and perspectives of the theragnostic applications in pheochromocytomas and paragangliomas, considering both the traditional theragnostic model - with radiolabelled metaiodobenzylguanidine (MIBG) - and the innovative one with radiolabeled somatostatin analogs (SSAs), that will hopefully become available for these patients in the near future.

Purpose: α-Klotho has been linked to insulin resistance (IR) in basic research. However, experimental evidence is inconsistent, and there is a lack of data from human research. This study seeks to elucidate the association of α-Klotho with IR in a nationwide, multiracial population.

Methods: A total of 5289 participants aged 40-79 years were included in the National Health and Nutrition Examination Survey (NHANES) spanning 2007-2016. Serum α-Klotho was measured using enzyme-linked immunosorbent assays (ELISA), and IR was evaluated by the homeostatic model assessment of insulin resistance (HOMA-IR). Weighted multivariate logistic and linear regression analysis, subgroup analysis stratified by demographic characteristics, medical condition or obesity status, and sensitivity analysis using propensity score matching (PSM) were performed. Restricted cubic splines (RCS) were performed to explore the nonlinear relationship.

Results: In the fully adjusted logistic regression model, a significant positive association was observed between log-transformed α-Klotho and IR (OR = 3.63, 95% CI: 1.56, 8.45), particularly in males or nonobese individuals (P_interaction < 0.05). In the linear regression model, log₁₀(α-Klotho) was associated with fasting blood glucose (FBG, β = 1.25, 95% CI: 0.74, 1.76) and glycosylated hemoglobin (HbA1c, β = 0.49, 95% CI: 0.20, 0.77). RCS revealed an inverse L-shaped dose-response relationship of α-Klotho with FBG and HbA1c (P_nonlinear <0.05). Beyond the inflection point of log₁₀(α-Klotho) at 2.79, β coefficients sharply rose for these glycaemic control indicators.

Conclusion: The study provides clinical evidence supporting a positive association between α-Klotho and IR. Moreover, the inverse L-shaped relationship suggests that α-Klotho should reach a certain level to predict glycaemic changes effectively.