Serum thyroxine (T4), triiodothyronine (T3), and thyroid-stimulating hormone (TSH) measurements are widely used to detect antithyroid effects in rodent toxicity studies. However, the assays used to measure these hormones are costly and highly variable depending on the blood sampling and measurement conditions. We previously demonstrated that histopathological evaluation detects the effects of thyroid peroxidase (TPO) inhibitors and thyroid hormone metabolism promoters more sensitively than serum hormone measurements. Here, we examined whether this approach can also improve early detection of antithyroid chemicals that inhibit iodide uptake, an essential step in thyroid hormone synthesis. We compared histopathological and immunohistochemical findings with serum hormone measurements in 6-week-old male Sprague-Dawley rats (five per group) administered ammonium perchlorate (APC) or potassium thiocyanate (PTC) in drinking water for 28 days. Serum T4 decreased at 1000 ppm APC and 5000 ppm PTC, T3 decreased at 1000 ppm APC, and TSH increased at ≥ 100 ppm APC. In contrast, follicular cell hypertrophy was detected at ≥ 10 ppm APC and 5000 ppm PTC, indicating greater sensitivity compared with serum hormone measurements. Decreased T3 and T4 immunostaining showed a sensitivity comparable with that of serum hormone changes, whereas thyroid sodium/iodide symporter (NIS)-immunopositive areas increased at doses that produced no detectable changes in serum hormone levels, suggesting that NIS immunostaining represents the most sensitive marker of iodide uptake inhibition. These results suggest that combining histopathological and immunohistochemical analyses enables sensitive detection of antithyroid effects and provides mechanistic information that cannot be obtained from serum hormone measurements alone.

Rice-paddy amphibians are routinely exposed to neonicotinoids, yet whether such exposure causes endocrine, mitochondrial, and neuromuscular toxicity remains poorly understood. Herein, we combined field surveillance across 39 rice-paddy sites in Zhejiang, China, with a 60-day exposure of adult Pelophylax nigromaculatus to thiamethoxam. Field monitoring in July detected all five neonicotinoids in 69.2% of rice-paddy water samples with summed thiamethoxam-equivalent concentrations ranging from 52.18 to 1282.69 μg/L, while concentrations in wild tadpoles ranged from 6.45 to 113.39 μg/kg. Laboratory thiamethoxam exposure (0.5 and 5 mg/L) resulted in predominant hepatic accumulation and detectable brain residues. Notably, thiamethoxam reduced serum T3, T4, FT3, and FT4, increased L-tyrosine, epinephrine, and dopamine, with dysregulation of HPT-axis-related genes. In skeletal muscle, thiamethoxam inhibited mitochondrial membrane potential, respiratory chain complexes I, II, III, V, as well as basal and maximal mitochondrial respiration (up to 55%). These defects coincided with fragmented AChR clusters, reduced receptor content, and impaired gastrocnemius force across 20-60 Hz in the 5 mg/L group. Some responses varied between sexes, with AChR fluorescence intensity significantly reduced only in females in 5 mg/L. Structural equation modeling supported a thyroid to mitochondrial pathway, in which thiamethoxam reduced integrated thyroid hormone status (β = -0.91), while thyroid hormone status positively predicted mitochondrial membrane potential (β = 0.79) and maximal respiration (β = 0.71). These findings identify thyroid hormone-linked mitochondrial dysfunction as a mechanistic bridge between thiamethoxam exposure and neuromuscular impairment.

Breast cancer remains the leading cause of cancer death among women worldwide, and metabolic reprogramming is increasingly recognized as a hallmark of this disease. Folylpolyglutamate Synthase (FPGS), a key enzyme in folate metabolism, catalyzes the polyglutamylation that retains folate inside cells; however, its role in breast cancer tumorigenesis remains largely unknown. Here, we show that FPGS is markedly upregulated in breast cancer tissues and that high FPGS expression is associated with poor patient survival. FPGS drives breast cancer cell proliferation in vitro and tumor growth in vivo by enhancing mitophagy, an effect mediated through suppression of the mTOR signaling pathway. Mechanistically, FPGS interacts with Cyclin-dependent kinase 9 (CDK9) and stabilizes it by deubiquitination, which in turn sustains mitophagy and promotes tumor progression. Pharmacological inhibition of CDK9 or mitophagy abolishes FPGS-driven proliferation, while CDK9 inhibitor treatment suppresses tumor growth in vivo. These findings identify the FPGS-CDK9-mTOR axis as a critical regulator of mitophagy and breast cancer progression, highlighting FPGS as both a candidate diagnostic biomarker and a potential therapeutic target for breast cancer.

The study evaluated changes in extraocular muscles (EOMs) following orbital decompression in patients with thyroid-associated orbitopathy (TAO) using computed tomography (CT)-based volumetric analysis. Patients who underwent orbital decompression with available preoperative and postoperative orbital CT scans were retrospectively reviewed. Decompression procedures were classified as medial, inferomedial, balanced, or three-wall decompression. Volumes of individual EOMs were calculated from coronal CT images, and temporal changes were assessed by locally estimated scatterplot smoothing regression, with associated clinical factors analyzed using multivariate linear regression. A total of 307 orbits from 171 patients were analyzed. Medial rectus muscle volume increased significantly across all surgical groups, while superior rectus volume decreased after three-wall decompression and inferior rectus volume decreased following medial and balanced decompression. EOM volumetric changes stabilized approximately 150 days postoperatively. Female sex, prior high-dose intravenous (IV) steroid therapy, and prolonged duration of TAO were independently associated with increased postoperative EOM volume, whereas smoking showed a borderline association. These findings indicate that orbital decompression induces distinct and time-dependent EOM volumetric changes, reflecting postoperative soft-tissue remodeling influenced by specific clinical factors.

N6-methyladenosine (m6A) RNA modification and histone lactylation are important regulators of gene expression and cancer progression, but their interplay in lung cancer associated with benzo[a]pyrene (BaP) remains unclear. Integrating clinical bioinformatics with cellular and in vivo analyses, we found that BaP enhanced migration and invasion while inducing a ferroptosis-resistant phenotype in lung cancer cells. Pharmacological modulation with Erastin and Ferrostatin-1 further supported ferroptosis involvement. BaP decreased FTO and increased YTHDF2 expression. FTO overexpression and YTHDF2 knockdown enhanced ferroptosis-associated lipid oxidation and suppressed migration and invasion, while their combined intervention attenuated BaP-associated experimental metastatic progression in vivo. Mechanistically, FTO overexpression reduced m6A enrichment on KEAP1 mRNA, whereas YTHDF2 associated with KEAP1 transcripts and accelerated their decay. Disruption of the A2108 RRACH motif attenuated YTHDF2-responsive repression of the KEAP1 reporter. KEAP1 knockdown attenuated FTO effects under BaP exposure. Upstream analyses supported AHR-dependent FTO regulation and a glycolysis-associated lactate-H3K18la contribution to YTHDF2 upregulation. Collectively, these findings support an m6A-sensitive FTO/YTHDF2-KEAP1-NRF2 framework contributing to ferroptosis defense and BaP-associated lung cancer malignant progression.

Effective monitoring of thyroid cancer treatment requires timely detection of clinically meaningful changes across complex, multistage care pathways. Traditional monitoring approaches often rely on static thresholds and periodic assessments, limiting their sensitivity to subtle yet important process deviations and potentially delaying clinical intervention. This study aimed to develop and evaluate an integrated, data-driven framework that combines deep learning-based risk prediction with genetic algorithm-optimized statistical process monitoring to enhance thyroid cancer treatment surveillance. Informative clinical variables were first identified using the Information Functions algorithm, and a Multilayer Perceptron (MLP) neural network was then employed to predict patient-specific treatment risk, capturing nonlinear relationships within longitudinal electronic medical record data. The resulting risk estimates were sequentially incorporated into Exponentially Weighted Moving Average (EWMA) control charts to enable continuous process monitoring. To further improve chart performance, a genetic algorithm was used to optimize EWMA parameters, enhancing accuracy and sensitivity while maintaining chart stability. The results demonstrate that the MLP model outperforms conventional machine learning approaches in risk prediction across multiple evaluation metrics. Genetic algorithm-optimized EWMA charts exhibit smoother trajectories, improved stability, and more reliable detection of clinically meaningful deviations compared with non-optimized charts. The consistency of these improvements across multiple features suggests that GA-based optimization enhances overall control chart performance rather than feature-specific behavior. This hybrid framework demonstrates the feasibility of integrating machine learning-derived risk prediction with optimized statistical process control for longitudinal treatment monitoring. The proposed approach supports proactive treatment surveillance, risk-stratified follow-up, timely clinical intervention, and data-driven decision-making in thyroid cancer care. Furthermore, the framework has the potential to enable continuous and adaptive monitoring across complex multi-stage treatment pathways if integrated with electronic medical record (EMR) systems in future implementations.

Next-generation sequencing (NGS) has markedly expanded the mutational spectrum of monogenic congenital hypothyroidism (CH), but has also led to the identification of numerous variants of uncertain significance, limiting the clinical utility of genetic testing. We previously developed an SLC5A5-specific machine learning-based predictor that improved the interpretation of missense variants associated with CH. Here, we systematically evaluated the pathogenicity of all CH-associated SLC5A5 variants reported in the literature using an integrated multidisciplinary framework based on the American College of Medical Genetics and Genomics (ACMG) guidelines. Among the 63 identified SLC5A5 variants, 5% were classified as benign, 16% as likely benign, 15% as of uncertain significance, 37% as likely pathogenic, and 27% as pathogenic. The computational variant effect predictor AlphaMissense was the most appropriate tool for predicting the functional impact of SLC5A5 missense variants. Experimental functional assays assessing the functional impact of SLC5A5 missense variants on radioiodide accumulation were instrumental in reclassifying variants of uncertain significance into clinically actionable categories. Moreover, patients' phenotype revealing reduced to absent thyroid radioiodide accumulation provided valuable phenotypic evidence supporting variant classification, which highlights the diagnostic value of thyroid scintigraphy in CH-associated SLC5A5 variants. Overall, our findings highlight the value of a multidisciplinary pathogenicity evaluation based on the ACMG guidelines, integrating computational predictions, functional assays, and phenotypic data into a standardized and evidence-based framework for the accurate interpretation of SLC5A5 variants, thereby representing a significant advance in the molecular diagnosis of congenital hypothyroidism.