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A simple and effective method for determining five pyrethroid residues in herbal tea by ultrasound-enhanced temperature-controlled (UETC) ionic liquid dispersive liquid-liquid microextraction (IL-DLLME) coupled with high performance liquid chromatography-diode array detection (HPLC-DAD) was developed. The use of ultrasonication and heating improved the ability of the ionic liquid to extract the analytes. Various parameters that affect the extraction efficiency were investigated and optimized using single factor experiments and response surface design. The optimum conditions of the experiment were 121 µL of [HMIM][PF6] (extraction solvent), 794 µL of acetonitrile (dispersive solvent), a heating temperature of 40°C, a sonication time of 3.6 min and a pH of 2.9. Under optimized conditions, the linearity was in the range of 0.05–5 mg L −1 with correlation coefficients above 0.9993. The limits of detection and quantification were 1.25–1.35 µg L −1 and 5 µg L −1 , respectively. The mean recoveries of the five pyrethroids ranged from 74.02% to 109.01%, with RSDs below 9.04%. The proposed method was reliable for the analysis of pyrethroids in Chinese herbal tea.

Neuroinflammation and mitochondrial impairment play important roles in the neuropathogenesis of Parkinson's disease (PD). The activation of NLRP3 inflammasome and the accumulation of α-synuclein (α-Syn) are strictly correlated to neuroinflammation. Therefore, the regulation of NLRP3 inflammasome activation and α-Syn aggregation might have therapeutic potential. It has been indicated that Dl-3-n-butylphthalide (NBP) produces neuroprotection against some neurological diseases such as ischemic stroke. We here intended to explore whether NBP suppressed NLRP3 inflammasome activation and reduced α-Syn aggregation, thus protecting dopaminergic neurons against neuroinflammation. In our study, we established a MPTP-induced mouse model and 6-OHDA-induced SH-SY5Y cell model to examine the neuroprotective actions of NBP. We then performed behavioral tests to examine motor dysfunction in MPTP-exposed mice after NBP treatment. Western blotting, immunofluorescence staining, flow cytometry and RT-qPCR were conducted to investigate the expression of NLRP3 inflammasomes, neuroinflammatory cytokines, PARP1, p-α-Syn, and markers of microgliosis and astrogliosis. The results showed that NBP exerts a neuroprotective effect on experimental PD models. , NBP ameliorated behavioral impairments and reduced dopaminergic neuron loss in MPTP-induced mice. , treatment of SH-SY5Y cells with 6-OHDA (100uM,24 h) significantly decreased cell viability, increased intracellular ROS production, and induced apoptosis, while pretreatment with 5uM NBP could alleviated 6-OHDA-induced cytotoxicity, ROS production and cell apoptosis to some extent. Importantly, both and , NBP suppressed the activation of the NLRP3 inflammasome and the aggregation of α-Syn, thus inhibited neuroinflammation ameliorated mitochondrial impairments. In summary, NBP rescued dopaminergic neurons by reducing NLRP3 inflammasome activation and ameliorating mitochondrial impairments and increases in p-α-Syn levels. This current study may provide novel neuroprotective mechanisms of NBP as a potential therapeutic agent.

Imaging-based sensors convert physicochemical parameters of analytes into visible patterns, yet a high sensitivity remains constrained. Here, we introduce the concept of differential guided-mode resonance with thickness modulation at a tens-nanometer scale to greatly enhance the sensitivity, alleviating the sensitivity-dynamic range tradeoff. Experimental results reveal a sensitivity of up to a million-level pixels per refractive index unit (RIU), surpassing existing technologies by nearly three orders of magnitude, with a large dynamic range reconfigured by the incident angle. With the present method, a moderate value (about 100) of the Q factor suffices to make a record high sensitivity and the Figure of Merit (FOM) can reach 10 4 RIU −1 level. We also demonstrate a portable device, highlighting its potential for practical applications, including 2D distribution sensing. This method unlocks the potential of imaging-based sensors with both record high sensitivity and tremendous dynamic range for accurate medical diagnosis, biochemical analysis, dynamic pollution monitoring, etc. This paper presents an imaging-based sensor enabled by differential guided-mode resonance with nanoscale thickness modulation, achieving high sensitivity and expanded dynamic range for medical diagnostics and biochemical sensing.

Background Polycystic ovary syndrome (PCOS) is not only a kind of common endocrine syndrome but also a metabolic disorder, which harms the reproductive system and the whole body metabolism of the PCOS patients worldwide. In this study, we aimed to investigate the differences in serum metabolic profiles of the patients with PCOS compared to the healthy controls. Material and methods 31 PCOS patients and 31 matched healthy female controls were recruited in this study, the clinical characteristics data were recorded, the laboratory biochemical data were detected. Then, we utilized the metabolomics approach by UPLC-HRMS technology to study the serum metabolic changes between PCOS and controls. Results The metabolomics analysis showed that there were 68 downregulated and 78 upregulated metabolites in PCOS patients serum compared to those in the controls. These metabolites mainly belong to triacylglycerols, glycerophosphocholines, acylcarnitines, diacylglycerols, peptides, amino acids, glycerophosphoethanolamines and fatty acid. Pathway analysis showed that these metabolites were enriched in pathways including glycerophospholipid metabolism, fatty acid degradation, fatty acid biosynthesis, ether lipid metabolism, etc. Diagnosis value assessed by ROC analysis showed that the changed metabolites, including Leu–Ala/Ile–Ala, 3-(4-Hydroxyphenyl) propionic acid, Ile–Val/Leu–Val, Gly–Val/Val–Gly, aspartic acid, DG(34:2)_DG(16:0/18:2), DG(34:1)_DG(16:0/18:1), Phe–Trp, DG(36:1)_DG(18:0/18:1), Leu–Leu/Leu–Ile, had higher AUC values, indicated a significant role in PCOS. Conclusion The present study characterized the difference of serum metabolites and related pathway profiles in PCOS patients, this finding hopes to provide potential metabolic markers for the prognosis and diagnosis of this disease.

Background Analysis of single-cell RNA sequencing (scRNA-seq) data has revolutionized our understanding of cellular heterogeneity, yet current approaches face challenges in efficiency, interpretability, and connecting molecular insights to therapeutic applications. Despite advances in deep learning methods, identifying cell-type-specific functional gene sets remains difficult. Results In this study, we present scKAN, an interpretable framework for scRNA-seq analysis with two primary goals: accurate cell-type annotation and the discovery of cell-type-specific marker genes and gene sets. The key innovation is using the learnable activation curves of the Kolmogorov-Arnold network to model gene-to-cell relationships. This approach provides a more direct way to visualize and interpret these specific interactions compared to the aggregated weighting schemes typical of attention mechanisms. This architecture achieves superior performance in cell-type annotation, with a 6.63% improvement in macro F1 score over state-of-the-art methods. Additionally, it enables the systematic identification of functionally coherent cell-type-specific gene sets. We demonstrate the framework’s translational potential through a case study on pancreatic ductal adenocarcinoma, where gene signatures identified by scKAN led to a potential drug repurposing candidate, whose binding stability was supported by molecular dynamics simulations. Conclusions Our work establishes scKAN as an efficient and interpretable framework that effectively bridges single-cell analysis with drug discovery. By combining lightweight architecture with the ability to uncover nuanced biological patterns, our approach offers an interpretable method for translating large-scale single-cell data into actionable therapeutic strategies. This approach provides a robust foundation for accelerating the identification of cell-type-specific targets in complex diseases.

Background The aim of this study was to apply proteomic methodology for the analysis of proteome changes in women with polycystic ovary syndrome (PCOS). Material and methods All the participators including 31 PCOS patients and 31 healthy female as controls were recruited, the clinical characteristics data was recorded at the time of recruitment, the laboratory biochemical data was detected. Then, a data-independent acquisition (DIA)-based proteomics method was performed to compare the serum protein changes between PCOS patients and controls. In addition, Western blotting was used to validate the expression of identified proteomic biomarkers. Results There were 80 proteins differentially expressed between PCOS patients and controls significantly, including 54 downregulated and 26 upregulated proteins. Gene ontology and Kyoto Encyclopedia of Genes and Genomes analysis showed that downregulated proteins were enriched in platelet degranulation, cell adhesion, cell activation, blood coagulation, hemostasis, defense response and inflammatory response terms; upregulated proteins were enriched in cofactor catabolic process, hydrogen peroxide catabolic process, antioxidant activity, cellular oxidant detoxification, cellular detoxification, antibiotic catabolic process and hydrogen peroxide metabolic process. Receiver operating characteristic curves analysis showed that the area under curve of Histone H4 (H4), Histone H2A (H2A), Trem-like transcript 1 protein (TLT-1) were all over than 0.9, indicated promising diagnosis values of these proteins. Western blotting results proved that the detected significant proteins, including H4, H2A, TLT-1, Peroxiredoxin-1, Band 3 anion transport protein were all differently expressed in PCOS and control groups significantly. Conclusion These proteomic biomarkers provided the potentiality to help us understand PCOS better, but future studies comparing systemic expression and exact role of these candidate biomarkers in PCOS are essential for confirmation of this hypothesis.

Background Cholangiocarcinoma (CCA) is an aggressive malignancy with limited treatment options and poor prognosis. Platelet-Derived Growth Factor CC (PDGF-CC) has been implicated in the progression of various tumors, but its specific role in CCA is not well understood. This study aims to investigate the expression and function of PDGF-CC in CCA and evaluate its potential as a therapeutic target. Methods We conducted gene expression analysis using the GEPIA database to compare PDGF-CC mRNA levels in CCA tissues and normal tissues. Serum samples from CCA patients were analyzed for PDGF-CC protein levels, and immunohistochemistry was used to assess PDGF-CC expression in tissue samples. The impact of PDGF-CC on CCA cell behavior was examined by knocking out PDGF-CC in HuCCT1 and QBC939 cell lines, followed by assessments of cell proliferation, migration, invasion, and colony formation in vitro. Additionally, the effects of PDGF-CC knockout were evaluated in xenograft models. The therapeutic potential of PDGF-CC inhibition was further explored using pharmacological inhibitors and antibodies. Results PDGF-CC mRNA and protein levels were significantly elevated in CCA tissues and patient sera compared to normal controls. Immunohistochemical analysis confirmed increased PDGF-CC expression in CCA tissues. High PDGF-CC expression correlated with poor overall survival in CCA patients, as shown by Kaplan-Meier analysis. Functional assays revealed that PDGF-CC knockout significantly reduced proliferation, migration, invasion, and colony formation in HuCCT1 and QBC939 cells, the lines with the highest PDGF-CC levels. In vivo, PDGF-CC knockout markedly decreased tumor growth in xenograft models. Pharmacological inhibition of PDGF-CC mirrored the effects of genetic knockout, suggesting it as a viable therapeutic strategy. Conclusions This study underscores the critical role of PDGF-CC in CCA progression and supports the potential of PDGF-CC inhibitors as a therapeutic approach. Given the association between high PDGF-CC expression and poor prognosis, targeting PDGF-CC may improve outcomes for CCA patients. Further clinical investigations are warranted to develop PDGF-CC-targeted therapies for CCA.

Objective This study introduces a surgical technique involving the use of 3D-printed all-metal prostheses combined with mesh patches for the treatment of distal radial giant cell tumors, analyzing and evaluating the midterm outcomes for patients undergoing this treatment. The experience provides insights into the application of prosthesis replacement for reconstructing distal radial defects. Methods From January 2018 to January 2021, our center treated five cases of distal radial giant cell tumors using 3D-printed all-metal prostheses combined with mesh patches. Postoperative pain, range of motion, and grip strength were evaluated for all patients. Oncological outcomes, complications, and degenerative changes in the wrist joint were also assessed. Functional outcomes were evaluated based on the Mayo wrist score system. Results The average follow-up period was 40.8 months (range: 32-66months). At the last follow-up, the mean range of motion (ROM) in the affected wrists was 20° extension, 21.6° flexion, 71.2° pronation, and 50° supination. The mean grip strength on the affected side was 64.2% compared to the unaffected side, with a Mayo score of 70. There were no incidences of aseptic loosening, wrist subluxation, or infections post-prosthesis replacement, although two cases presented with distal radioulnar joint dislocation. Of these, one case demonstrated ulnar impaction syndrome with positive ulnar variance and lunate bone degenerative changes on the 12-month postoperative radiographs. No recurrences or metastases were observed. Conclusion Utilizing 3D-printed metal prostheses and mesh grafts for the treatment of Campanacci Grade III or recurrent giant cell tumors of the distal radius is an effective approach. This strategy provides favorable functional outcomes during the early to mid stages of treatment, while also maintaining a low risk of complications. The concurrent use of mesh grafts facilitates early postoperative exercise, thereby accelerating functional recovery. Moreover, the intraoperative protection or reconstruction of joint ligaments, along with precise matching of the prostheses, contributes to a reduction in the risk of complications.

Ongoing research on the sensitivity and integration of refractive index‐based biosensors has resulted in significant advancements. Here, the study presents an enhanced surface plasmon resonance biosensor that integrates imaging technology and features dual‐parameter interrogation (intensity and phase) with guided mode coupling. By depositing a silica‐waveguide‐layer on a metal‐layer, two‐mode coupling is established to generate a high Q resonance and induce a phase mutation. The sensing performance experiment demonstrated a phase sensing sensitivity of 1.1 × 105 degree RIU−1, Q‐value of the resonant peak up to 314, and figure of merit of 300 RIU−1, superior to most standard plasmonic sensors. An in‐line phase‐polarization modulation scheme combined with imaging technology is proposed to extract the resonant phase carrying refractive index information. Additionally, a pair‐prism module is designed to optimize the sensing system configuration. Meanwhile, dual‐parameters interrogation including the intensity and phase are demonstrated, which offers potential for complementary and multi‐sensing fusion applications. The intensity interrogation also shows a considerable sensitivity of 7.2 × 104 a.u. RIU−1. Furthermore, it is combined with microfluidic chip to detect of alpha‐synuclein protein closely related to Parkinson's disease, and the limit of detection can reach 300 pg mL−1 level, which indicated a considerable potential for high‐throughput diagnosis application. A plasmonic biosensor with guided mode coupling is presented that integrates imaging technology and features dual‐parameters interrogation (intensity and phase). This sensing platform shows a superior figure of merit and sensitivity for dual‐parameters interrogation, which is also validated by the  biosensing experiment. It may give full play in the field of biochemical analysis and disease diagnosis in the future.

Walking is the final phase of the morning commute, during which commuters are exposed to vehicular emissions. This study proposes a novel analytical model to evaluate how emission exposure affects commuters’ departure time choices and parking behavior. Different from traditional bottleneck models, our model includes a nonlinear term in the generalized cost function to account for emission exposure. The findings reveal that, at user equilibrium, rational commuters seeking to minimize their own generalized costs will park outward, resulting in undesired scenarios in which all walking commuters suffer from emission exposure. However, we show that in a system-optimal scenario, emission exposure can be eliminated if commuters park inward; the schedule delay cost is minimized in such a parking order. To achieve this outcome, we propose a new spatiotemporal parking pricing scheme designed to reduce the overall system cost and incentivize inward parking patterns. Case studies using empirical data show that this pricing approach, independent of specific parking orders, effectively encourages inward parking, thereby minimizing emissions and improving commuter welfare. Hopefully, findings from this research can provide insights to the development of effective roadside parking pricing strategies.