Nitrofurantoin(NFT)is a nitrofuran antibiotic commonly used as a veterinary drug to treat bacterial infections in animals.However,due to the low solubility and bioaccumulation properties,NFT is prone to leave excessive residues in animal-derived foods and water systems,posing serious threats to human health and ecosystems.Therefore,there is an urgent need to develop an efficient and rapid detection method for NFT.In this work,nitrogen-doped carbon nanomaterials with unique bowl-like structures(N-CNBs)were synthesized via a hydrothermal-carbonization method.The morphology,surface structure,and specific surface area of N-CNBs were characterized using transmission electron microscopy(TEM),scanning electron microscopy(SEM),and X-ray photoelectron spectroscopy(XPS).The N-CNB modified glassy carbon electrode(N-CNB/GCE)was prepared,and the electrochemical test revealed that the N-CNB/GCE exhibited higher conductivity and larger electrochemical active surface area compared to bare GCE and nitrogen-doped hollow carbon nanosphere-modified electrode(N-HCNS/GCE).Additionally,the N-CNB/GCE demonstrated superior electrocatalytic activity toward NFT.An NFT electrochemical sensor was constructed based on N-CNB/GCE.The detection conditions of the sensor were optimized,and differential pulse voltammetry(DPV)was employed for NFT detection under optimal experimental conditions.The established NFT electrochemical sensor had a wide linear range of 0.4-500 μmol/L,a low detection limit(S/N=3)of 0.015 μmol/L and high selectivity,with excellent stability and reproducibility.The practical feasibility of this sensor was confirmed by analysis of NFT in milk and tap water samples,with spiked recoveries ranging from 94.2%to 108.9%.

This study investigates the genetic diversity and evolutionary relationships of different Artemisia argyi germplasm resources to provide a basis for germplasm identification, variety selection, and resource protection. A total of 192 germplasm resources of A. argyi were studied, and EST-based simple sequence repeat(EST-SSR) primers were designed based on transcriptomic data of A. argyi. Polymerase chain reaction(PCR) amplification was performed on these resources, followed by fluorescence capillary electrophoresis to detect genetic diversity and construct DNA fingerprints. From 197 pairs of primers designed, 28 pairs with polymorphic and clear bands were selected. A total of 278 alleles were detected, with an average of 9.900 0 alleles per primer pair and an average effective number of alleles of 1.407 2. The Shannon's diversity index(I) for the A. argyi germplasm resources ranged from 0.148 1 to 0.418 0, with an average of 0.255 7. The polymorphism information content(PIC) ranged from 0.454 5 to 0.878 0, with an average of 0.766 9, showing high polymorphism. Cluster analysis divided the A. argyi germplasm resources into three major groups: Group Ⅰ contained 136 germplasm samples, Group Ⅱ contained 45, and Group Ⅲ contained 11. Principal component analysis also divided the resources into three groups, which was generally consistent with the clustering results. Mantel test results showed that the genetic variation in A. argyi populations was to some extent influenced by geographic distance, but the effect was minimal. Structure analysis showed that 190 germplasm materials had Q≥ 0.6, indicating that these germplasm materials had a relatively homogeneous genetic origin. Furthermore, 8 core primer pairs were selected from the 28 designed primers, which could distinguish various germplasm types. Using these 8 core primers, DNA fingerprints for the 192 A. argyi germplasm resources were successfully constructed. EST-SSR molecular markers can be used to study the genetic diversity and phylogenetic relationships of A. argyi, providing theoretical support for the identification and molecular-assisted breeding of A. argyi germplasm resources.
Artemisia/classification* ; Microsatellite Repeats ; Genetic Variation ; Expressed Sequence Tags ; DNA Fingerprinting ; Phylogeny ; Polymorphism, Genetic ; DNA, Plant/genetics* ; Genetic Markers

Epilepsy is a chronic neurological disease caused by abnormal synchronous discharge of the brain, which is characterized by recurrent and transient neurological abnormalities, mainly manifested as loss of consciousness and limb convulsions, and can occur in people of all ages. At present, anti-epileptic drugs (AEDs) are still the main means of treatment, but their efficacy is limited by the problem of drug resistance, and long-term use can cause serious side effects, such as cognitive dysfunction and vital organ damage. Although surgical resection of epileptic lesions has achieved certain results in some patients, the high cost and potential risk of neurological damage limit its scope of application. Therefore, the development of safe, accurate and personalized non-invasive treatment strategies has become one of the key directions of epilepsy research. In recent years, photobiomodulation (PBM) has gained significant attention as a promising non-invasive therapeutic approach. PBM uses light of specific wavelengths to penetrate tissues and interact with photosensitive molecules within cells, thereby modulating cellular metabolic processes. Research has shown that PBM can enhance mitochondrial function, promote ATP production, improve meningeal lymphatic drainage, reduce neuroinflammation, and stimulate the growth of neurons and synapses. These biological effects suggest that PBM not only holds the potential to reduce the frequency of seizures but also to improve the metabolic state and network function of neurons, providing a novel therapeutic avenue for epilepsy treatment. Compared to traditional treatment methods, PBM is non-invasive and avoids the risks associated with surgical interventions. Its low risk of significant side effects makes it particularly suitable for patients with drug-resistant epilepsy, offering new therapeutic options for those who have not responded to conventional treatments. Furthermore, PBM’s multi-target mechanism enables it to address a variety of complex etiologies of epilepsy, demonstrating its potential in precision medicine. In contrast to therapies targeting a single pathological mechanism, PBM’s multifaceted approach makes it highly adaptable to different types of epilepsy, positioning it as a promising supplementary or alternative treatment. Although animal studies and preliminary clinical trials have shown positive outcomes with PBM, its clinical application remains in the exploratory phase. Future research should aim to elucidate the precise mechanisms of PBM, optimize light parameters, such as wavelength, dose, and frequency, and investigate potential synergistic effects with other therapeutic modalities. These efforts will be crucial for enhancing the therapeutic efficacy of PBM and ensuring its safety and consistency in clinical settings. This review summarizes the types of epilepsy, diagnostic biomarkers, the advantages of PBM, and its mechanisms and potential applications in epilepsy treatment. The unique value of PBM lies not only in its multi-target therapeutic effects but also in its adaptability to the diverse etiologies of epilepsy. The combination of PBM with traditional treatments, such as pharmacotherapy and neuroregulatory techniques, holds promise for developing a more comprehensive and multidimensional treatment strategy, ultimately alleviating the treatment burden on patients. PBM has also shown beneficial effects on neural network plasticity in various neurodegenerative diseases. The dynamic remodeling of neural networks plays a critical role in the pathogenesis and treatment of epilepsy, and PBM’s multi-target mechanism may promote brain function recovery by facilitating neural network remodeling. In this context, optimizing optical parameters remains a key area of research. By adjusting parameters such as wavelength, dose, and frequency, researchers aim to further enhance the therapeutic effects of PBM while maintaining its safety and stability. Looking forward, interdisciplinary collaboration, particularly in the fields of neuroscience, optical engineering, and clinical medicine, will drive the development of PBM technology and facilitate its transition from laboratory research to clinical application. With the advancement of portable devices, PBM is expected to provide safer and more effective treatments for epilepsy patients and make a significant contribution to personalized medicine, positioning it as a critical component of precision therapeutic strategies.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

OBJECTIVE: Hepatocellular carcinoma (HCC) is sensitive to ferroptosis, a new form of programmed cell death that occurs in most tumor types. However, the mechanism through which ferroptosis modulates HCC remains unclear. This study aimed to investigate the oncogenic role and prognostic value of FANCD2 and provide novel insights into the prognostic assessment and prediction of immunotherapy. METHODS: Using clinicopathological parameters and bioinformatic techniques, we comprehensively examined the expression of FANCD2 macroscopically and microcosmically. We conducted univariate and multivariate Cox regression analyses to identify the prognostic value of FANCD2 in HCC and elucidated the detailed molecular mechanisms underlying the involvement of FANCD2 in oncogenesis by promoting iron-related death. RESULTS: FANCD2 was significantly upregulated in digestive system cancers with abundant immune infiltration. As an independent risk factor for HCC, a high FANCD2 expression level was associated with poor clinical outcomes and response to immune checkpoint blockade. Gene set enrichment analysis revealed that FANCD2 was mainly involved in the cell cycle and CYP450 metabolism. CONCLUSION To the best of our knowledge, this is the first study to comprehensively elucidate the oncogenic role of FANCD2. FANCD2 has a tumor-promoting aspect in the digestive system and acts as an independent risk factor in HCC; hence, it has recognized value for predicting tumor aggressiveness and prognosis and may be a potential biomarker for poor responsiveness to immunotherapy.
Humans ; Carcinoma, Hepatocellular/diagnosis* ; Liver Neoplasms/diagnosis* ; Immunotherapy ; Fanconi Anemia Complementation Group D2 Protein/metabolism* ; Prognosis ; Male ; Female ; Middle Aged ; Biomarkers, Tumor/metabolism*

OBJECTIVES: This study aimed to investigate the impact of foam macrophages (FMs) on the intracellular survival of Mycobacterium tuberculosis (MTB) and identify the molecular mechanisms influencing MTB survival. METHODS: An in vitro FM model was established using oleic acid induction. Transcriptomic and metabolomic analyses were conducted to identify the key molecular pathways involved in FM-mediated MTB survival. RESULTS: Induced FMs effectively restricted MTB survival. Transcriptomic and metabolomic profiling revealed distinct changes in gene and metabolite expression in FMs during MTB infection compared with normal macrophages. Integrated analyses identified significant alterations in the cyclic adenosine monophosphate (cAMP) signaling pathway, indicating that its activation contributes to the FM-mediated restriction of MTB survival. CONCLUSIONS FMs inhibit MTB survival. The cAMP signaling pathway is a key contributor. These findings enhance the understanding of the role of FMs in tuberculosis progression, suggest potential targets for host-directed therapies, and offer new directions for developing diagnostic and therapeutic strategies against tuberculosis.
Mycobacterium tuberculosis/physiology* ; Transcriptome ; Metabolomics ; Foam Cells/microbiology* ; Humans ; Metabolome ; Tuberculosis/microbiology* ; Gene Expression Profiling

BACKGROUND: Prior studies have shown that drivers with type 2 diabetes are more likely to be involved in motor vehicle collisions (MVCs) compared to the general population. Certain meteorological factors have been increasingly recognized as contributors to MVC risk. This study aims to examine the association of MVCs with temperature, rainfall, wind speed, and sunshine duration among drivers with type 2 diabetes. METHODS: Using Taiwan's National Health Insurance data (2019-2021), we identified individuals diagnosed with type 2 diabetes and linked their records to the Police-Reported Traffic Accident Registry to obtain daily MVC counts. Meteorological data were sourced from the Central Weather Administration. Associations between daily weather conditions and MVCs were assessed using a Distributed Lag Non-Linear Model. RESULTS: Over the 1,096-day study period, 170,468 MVC events involving drivers with type 2 diabetes were recorded. A U-shaped association was observed between same-day temperature and MVC rates. Compared with the reference temperature of 17.5 °C, both lower temperatures (≤15 °C; rate ratio [RR] = 1.014-1.053) and higher temperatures (≥30 °C; RR = 1.062) were associated with increased MVC risk. Rainfall showed an inverse relationship with MVCs. Compared with 70 mm of rainfall, the lowest MVC rate occurred at 129 mm (RR = 0.873), while the highest was on rain-free days (0 mm; RR = 1.068). Stronger effects were observed when lag periods up to 14 days were considered. Wind speed and sunshine duration were not significantly associated with MVC risk. CONCLUSIONS These findings suggest that drivers with type 2 diabetes should exercise greater caution on days with extreme temperatures or in days with lesser rainfall, as these conditions may elevate MVC risk.
Humans ; Diabetes Mellitus, Type 2/epidemiology* ; Taiwan/epidemiology* ; Accidents, Traffic/statistics & numerical data* ; Male ; Middle Aged ; Female ; Weather ; Aged ; Adult ; Temperature ; Risk Factors

OBJECTIVE: To investigate the therapeutic potential of pseudolaric acid B (PAB) on non-alcoholic fatty liver disease (NAFLD) and its underlying molecular mechanism in vitro and in vivo. METHODS: Eight-week-old male C57BL/6J mice (n=32) were fed either a normal chow diet (NCD) or a high-fat diet (HFD) for 8 weeks. The HFD mice were divided into 3 groups according to a simple random method, including HFD, PAB low-dose [10 mg/(kg·d), PAB-L], and PAB high-dose [20 mg/(kg·d), PAB-H] groups. After 8 weeks of treatment, glucose metabolism and insulin resistance were assessed by oral glucose tolerance test (OGTT) and insulin tolerance test (ITT). Biochemical assays were used to measure the serum and cellular levels of total cholesterol (TC), triglycerides (TG), aspartate aminotransferase (AST), alanine aminotransferase (ALT), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C). White adipose tissue (WAT), brown adipose tissue (BAT) and liver tissue were subjected to hematoxylin and eosin (H&E) staining or Oil Red O staining to observe the alterations in adipose tissue and liver injury. PharmMapper and DisGeNet were used to predict the NAFLD-related PAB targets. Peroxisome proliferator-activated receptor alpha (PPARα) pathway involvement was suggested by Kyoto Encyclopedia of Genes and Genomes (KEGG) and search tool Retrieval of Interacting Genes (STRING) analyses. Luciferase reporter assay, cellular thermal shift assay (CETSA), and drug affinity responsive target stability assay (DARTS) were conducted to confirm direct binding of PAB with PPARα. Molecular dynamics simulations were applied to further validate target engagement. RT-qPCR and Western blot were performed to assess the downstream genes and proteins expression, and validated by PPARα inhibitor MK886. RESULTS: PAB significantly reduced serum TC, TG, LDL-C, AST, and ALT levels, and increased HDL-C level in HFD mice (P<0.01). Target prediction analysis indicated a significant correlation between PAB and PPARα pathway. PAB direct target binding with PPARα was confirmed through luciferase reporter assay, CETSA, and DARTS (P<0.05 or P<0.01). The target engagement between PAB and PPARα protein was further confirmed by molecular dynamics simulations and the top 3 amino acid residues, LEU321, MET355, and PHE273 showed the most significant changes in mutational energy. Subsequently, PAB upregulated the genes expressions involved in lipid metabolism and mitochondrial biogenesis downstream of PPARα (P<0.05 or P<0.01). Significantly, the PPARα inhibitor MK886 effectively reversed the lipid-lowering and PPARα activation properties of PAB (P<0.05 or P<0.01). CONCLUSION PAB mitigates lipid accumulation, ameliorates liver damage, and improves mitochondrial biogenesis by binding with PPARα, thus presenting a potential candidate for pharmaceutical development in the treatment of NAFLD.
Animals ; PPAR alpha/metabolism* ; Non-alcoholic Fatty Liver Disease/pathology* ; Male ; Mice, Inbred C57BL ; Lipid Metabolism/drug effects* ; Diterpenes/therapeutic use* ; Organelle Biogenesis ; Diet, High-Fat ; Humans ; Mice ; Liver/metabolism* ; Insulin Resistance ; Mitochondria/metabolism* ; Molecular Docking Simulation