Phosgene is a highly reactive chemical substance and a prevalent chemical warfare agent,and it is vitally important for rapid and accurate detection of phosgene to counteract terrorist threats and industrial accidents.In this work,a phosgene probe,designated as SX-Pho,which incorporated benzimidazole and hydroxyl groups as recognition motifs,was prepared through Suzuki coupling and Debus-Radziszewski methodologies to incorporate an electron-donating carbazole moiety.This probe exhibited a large Stokes shift(Approximately 130 nm).Upon exposure to triphosgene/triethylamine conditions(in situ phosgene generation),the fluorescence emission of probe at 470 nm underwent significant quenching,with a 20-fold reduction in intensity,while the fluorescence lifetime decreased from 3.30 ns to 3.06 ns.Concentration titration experiments demonstrated that SX-Pho achieved a lower detection limit of 57.8 nmol/L with high specificity and interference resistance.Preton nuclear magnetic resonance spectroscopy(1H NMR),high-resolution mass spectrometry,and density functional theory(DFT)calculations confirmed the cyclization reaction between hydroxyl groups,imines,and phosgene.The extent of overlap between the highest occupied molecular orbital(HOMO)and the lowest unoccupied molecular orbital(LUMO)was notably decreased,leading to the suppression of radiative transitions.The energy gap underwent a reduction of 0.43 eV,while the non-radiative transition was augmented,resulting in fluorescence quenching and achieving rapid detection of phosgene.Based on this,probe-loaded test strips were prepared.The color change under 365 nm illumination allowed visual discrimination of phosgene at concentrations below 20 μL/L.Furthermore,using a smartphone's built-in RGB application to measure the intensity of the blue(B)channel after the test strips were exposed to phosgene enabled both qualitative and quantitative detection.The detection range was 1.82-50 μL/L,with a limit of detection(LOD)of 1.814 μL/L.

Objective To propose a dynamic early warning model based on machine learning methods and validate its predi-ctive efficacy so as to achieve precise assessment and early warning of mortality risk in patients with traumatic hypothermia.Methods Firstly,a total of 480 patients who met inclusion criteria were retrospectively selected from the eICU database and randomly divided into training and test sets at an 8∶2 ratio.Secondly,physiological parameters were extracted from these patients,and five machine learning algorithms including XGBoost,AdaBoost,LightGBM,logistic regression(LR)and random forest(RF)were employed respectively to develop dynamic mortality risk warning models for traumatic hypothermia patients,utilizing a 1-hour observation window.Thirdly,receiver operating characteristic curves(ROC)were plotted using the test set data and the effects of different warning windows on the model performance were analyzed by calculating the AUC.Finally,the interpretability of the models was analyzed using the SHapley Additive exPlanations(SHAP)algorithm to elucidate the contribution of each feature to predictive performance.Results The optimal warning window for the dynamic warning model constructed using the eICU database was 12 hours,and in case of 12-hour warning window the logistic regression model achieved the highest AUC of 0.935 and showed optimal predictive performance.The results of the interpretability analysis by the SHAP algorithm showed that body temperature was the feature that had the greatest impact on the model results,and its reduction was positively correlated with the increased risk of death.Conclusion The machine learning-based dynamic warning model for mortality risk in traumatic hypothermia patients enables real-time dynamic risk assessment,providing robust support for clinicians to identify the patient's condition changes at an early stage and references for the adjustment of clinical treatment programs.[Chinese Medical Equipment Journal,2025,46(3):9-14]

Acetaminophen (APAP) is the primary cause of drug-induced acute liver failure. Ovarian tumor deubiquitinase 6A (OTUD6A), a recently discovered deubiquitinase of the OTU family, has been primarily studied in tumor contexts. However, its role in APAP-induced liver injury (AILI) remains unclear. Therefore, this study aimed to investigate the involvement of OTUD6A in the pathogenesis of AILI. Our findings demonstrated a substantial upregulation of OTUD6A in both the liver tissue and isolated hepatocytes of mice following APAP stimulation. OTUD6A knockout exacerbated APAP-induced inflammation, hepatocyte necrosis, and liver injury, whereas OTUD6A overexpression alleviated these pathologies. Mechanistically, OTUD6A directly interacted with the enhancer of zeste homolog 2 (EZH2) and selectively removed K48-linked polyubiquitin chains from EZH2, enhancing its stability. This resulted in increased protein levels of EZH2 and H3K27me3, as well as reduced endoplasmic reticulum (ER) stress and cell death in hepatocytes. Collectively, our research uncovers a novel role for OTUD6A in mitigating APAP-induced liver injury by promoting EZH2 stabilization.

Hepatocellular carcinoma (HCC) expresses abundant glycolytic enzymes and displays comprehensive glucose metabolism reprogramming. Aldolase A (ALDOA) plays a prominent role in glycolysis; however, little is known about its role in HCC development. In the present study, we aim to explore how ALDOA is involved in HCC proliferation. HCC proliferation was markedly suppressed both in vitro and in vivo following ALDOA knockout, which is consistent with ALDOA overexpression encouraging HCC proliferation. Mechanistically, ALDOA knockout partially limits the glycolytic flux in HCC cells. Meanwhile, ALDOA translocated to nuclei and directly interacted with c-Jun to facilitate its Thr93 phosphorylation by P21-activated protein kinase; ALDOA knockout markedly diminished c-Jun Thr93 phosphorylation and then dampened c-Jun transcription function. A crucial site Y364 mutation in ALDOA disrupted its interaction with c-Jun, and Y364S ALDOA expression failed to rescue cell proliferation in ALDOA deletion cells. In HCC patients, the expression level of ALDOA was correlated with the phosphorylation level of c-Jun (Thr93) and poor prognosis. Remarkably, hepatic ALDOA was significantly upregulated in the promotion and progression stages of diethylnitrosamine-induced HCC models, and the knockdown of A ldoa strikingly decreased HCC development in vivo. Our study demonstrated that ALDOA is a vital driver for HCC development by activating c-Jun-mediated oncogene transcription, opening additional avenues for anti-cancer therapies.

OBJECTIVE: To assess the independent and combined effects of air pollutants, meteorological factors, and greenspace exposure on new tuberculosis (TB) cases. METHODS: TB case data from Shanghai (2013-2018) were obtained from the Shanghai Center for Disease Control and Prevention. Environmental data on air pollutants, meteorological variables, and greenspace exposure were obtained from the National Tibetan Plateau Data Center. We employed a distributed-lag nonlinear model to assess the effects of these environmental factors on TB cases. RESULTS: Increased TB risk was linked to PM _2.5, PM ₁₀, and rainfall, whereas NO ₂, SO ₂, and air pressure were associated with a reduced risk. Specifically, the strongest cumulative effects occurred at various lags: PM _2.5 ( RR = 1.166, 95% CI: 1.026-1.325) at 0-19 weeks; PM ₁₀ ( RR = 1.167, 95% CI: 1.028-1.324) at 0-18 weeks; NO ₂ ( RR = 0.968, 95% CI: 0.938-0.999) at 0-1 weeks; SO ₂ ( RR = 0.945, 95% CI: 0.894-0.999) at 0-2 weeks; air pressure ( RR = 0.604, 95% CI: 0.447-0.816) at 0-8 weeks; and rainfall ( RR = 1.404, 95% CI: 1.076-1.833) at 0-22 weeks. Green space exposure did not significantly impact TB cases. Additionally, low temperatures amplified the effect of PM _2.5 on TB. CONCLUSION Exposure to PM _2.5, PM ₁₀, and rainfall increased the risk of TB, highlighting the need to address air pollutants for the prevention of TB in Shanghai.
China/epidemiology* ; Humans ; Air Pollutants/analysis* ; Tuberculosis/epidemiology* ; Incidence ; Meteorological Concepts ; Particulate Matter/adverse effects* ; Environmental Exposure ; Male ; Female ; Adult ; Air Pollution ; Middle Aged

This study aims to explore the role and mechanism of CXC chemokine receptor 3 (CXCR3) in cisplatin-induced skeletal muscle atrophy. Wild-type mice were divided into two groups: cisplatin group and control group (treated by normal saline). The results showed that, compared to the control group, the expression levels of CXCR3 mRNA and protein were significantly up-regulated in the skeletal muscle of the cisplatin group, suggesting that CXCR3 may play an important role in the model of cisplatin-induced skeletal muscle atrophy. To further investigate its role and potential mechanisms, CXCR3 knockout mice and wild-type mice were treated with cisplatin to induce skeletal muscle atrophy. The results revealed that CXCR3 knockout not only failed to alleviate cisplatin-induced skeletal muscle atrophy, but also further reduced body weight, skeletal muscle mass, and muscle fiber cross-sectional area. Further analysis showed that, in the cisplatin-induced muscle atrophy model, CXCR3 knockout significantly up-regulated the expression levels of E3 ubiquitin ligases in skeletal muscle and down-regulated the expression levels of myogenic regulatory factors. To explore the molecular mechanism by which CXCR3 gene deletion exacerbated cisplatin-induced skeletal muscle atrophy, transcriptomic sequencing was performed on the atrophied skeletal muscles of wild-type and CXCR3 knockout mice. The results showed that, compared to wild-type mice, 14 genes were significantly up-regulated and 12 genes were significantly down-regulated in the skeletal muscle of CXCR3 knockout mice. Gene set enrichment analysis (GSEA) revealed a significant enrichment of genes related to fatty acid β-oxidation. Quantitative real-time PCR validation results were consistent with the transcriptomic sequencing results. These findings suggest that CXCR3 may counteract cisplatin-induced skeletal muscle atrophy by up-regulating E3 ubiquitin ligases, down-regulating myogenic regulatory factors, and enhancing the recruitment of fatty acid β-oxidation-related genes.
Animals ; Cisplatin/adverse effects* ; Muscular Atrophy/physiopathology* ; Mice ; Receptors, CXCR3/metabolism* ; Ubiquitin-Protein Ligases/metabolism* ; Mice, Knockout ; Oxidation-Reduction ; Fatty Acids/metabolism* ; Muscle, Skeletal/metabolism* ; Mice, Inbred C57BL ; Male

Parkinson's disease (PD) is a common neurodegenerative disorder mainly related to mitochondrial dysfunction of dopaminergic neurons in the midbrain substantia nigra. This study aimed to investigate the effects of exercise preconditioning on motor deficits and mitochondrial function in a 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced PD mouse model. Eight-week-old male C57BL/6J mice were randomly divided into four groups: sedentary + saline (SS), sedentary + MPTP (SM), exercise + saline (ES), and exercise + MPTP (EM) groups. Mice in the ES and EM groups received 4 weeks of treadmill training, and then SM and EM groups were treated with MPTP for 5 days. Motor function was assessed by behavioral tests, and morphological and functional changes in dopaminergic neurons and mitochondria in the substantia nigra of the midbrain were evaluated using immunohistochemistry, Western blot, and transmission electron microscopy technology. The results showed that, compared with the SM group, the EM group exhibited significantly improved motor ability, up-regulated protein expression levels of tyrosine hydroxylase (TH) and dopamine transporter (DAT) in the midbrain, and down-regulated protein expression of α-synuclein (α-Syn) in the mitochondria of substantia nigra. Compared with the SM group, the EM group showed up-regulated protein expression levels of mitochondrial fusion proteins, including optical atrophy protein 1 (OPA1) and mitofusin 2 (MFN2), and biogenesis-related proteins, including peroxisome proliferator activated receptor gamma coactivator 1α (PGC-1α) and mitochondrial transcription factor A (TFAM), while the protein expression levels of dynamin-related protein 1 (DRP1) and mitochondrial fission protein 1 (FIS1) were significantly down-regulated. Compared with the SM group, the EM group showed significantly reduced damage to substantia nigra mitochondria, restored mitochondrial membrane potential and ATP production, and decreased levels of reactive oxygen species (ROS). These results suggest that 4-week treadmill pre-training can alleviate MPTP-induced motor impairments in PD mice by improving mitochondrial function, providing a theoretical basis for early exercise-based prevention of PD.
Animals ; Male ; Physical Conditioning, Animal/physiology* ; Mice ; Mice, Inbred C57BL ; Mitochondria/physiology* ; Dopaminergic Neurons ; MPTP Poisoning/physiopathology* ; Substantia Nigra ; Peroxisome Proliferator-Activated Receptor Gamma Coactivator 1-alpha ; 1-Methyl-4-phenyl-1,2,3,6-tetrahydropyridine

Hepatocellular carcinoma(HCC)expresses abundant glycolytic enzymes and displays comprehensive glucose metabolism reprogramming.Aldolase A(ALDOA)plays a prominent role in glycolysis;however,little is known about its role in HCC development.In the present study,we aim to explore how ALDOA is involved in HCC proliferation.HCC proliferation was markedly suppressed both in vitro and in vivo following ALDOA knockout,which is consistent with ALDOA overexpression encouraging HCC prolifera-tion.Mechanistically,ALDOA knockout partially limits the glycolytic flux in HCC cells.Meanwhile,ALDOA translocated to nuclei and directly interacted with c-Jun to facilitate its Thr93 phosphorylation by P21-activated protein kinase;ALDOA knockout markedly diminished c-Jun Thr93 phosphorylation and then dampened c-Jun transcription function.A crucial site Y364 mutation in ALDOA disrupted its interaction with c-Jun,and Y364S ALDOA expression failed to rescue cell proliferation in ALDOA deletion cells.In HCC patients,the expression level of ALDOA was correlated with the phosphorylation level of c-Jun(Thr93)and poor prognosis.Remarkably,hepatic ALDOA was significantly upregulated in the promotion and progression stages of diethylnitrosamine-induced HCC models,and the knockdown of Aldoa strikingly decreased HCC development in vivo.Our study demonstrated that ALDOA is a vital driver for HCC development by activating c-Jun-mediated oncogene transcription,opening additional avenues for anti-cancer therapies.

ObjectiveAs the central hub of the classical visual pathway, the primary visual cortex not only encodes and processes visual information but also establishes dense neural circuit connections with higher-order cognitive brain regions. Numerous studies have shown that 40 Hz flicker stimulation can induce γ oscillations in the brain and significantly improve learning and cognitive impairments in patients with neurodegenerative diseases. Moreover, flickering light phenomena naturally occur in daily environments. Given that the primary visual cortex serves as the brain’s first cortical hub for receiving visual input, it is essential to comprehensively understand how non-invasive light flicker stimulation modulates its information processing mechanisms. This study systematically investigates the effects of non-invasive light flicker stimulation at different frequencies on the functional properties of neurons in the primary visual cortex of adult mice, aiming to uncover how such stimulation modulates this region and, consequently, affects overall brain function. MethodsThree groups of adult mice (approximately 12 weeks old) were exposed to light flicker stimulation at frequencies of 20 Hz, 40 Hz, and 60 Hz, respectively, for a duration of two months. A control group was exposed to the same light intensity without flickering. Following the stimulation period, in vivo multi-channel electrophysiological recordings were conducted. During these recordings, anesthetized mice were presented with various types of moving sinusoidal light gratings to assess the effects of different flicker frequencies on the functional properties of neurons in the primary visual cortex. ResultsThe experimental results demonstrate that two months of light flicker stimulation at 20 Hz, 40 Hz, and 60 Hz enhances the orientation tuning capabilities of neurons in the primary visual cortex. Specifically, 40 Hz and 60 Hz stimulation improved contrast sensitivity, whereas 20 Hz had no significant effect. Further analysis revealed that all three frequencies reduced neuronal response variability (as measured by the Fano factor), increased the signal-to-noise ratio, and decreased noise correlation (r_sc) between neurons. ConclusionNon-invasive light flicker stimulation enhances orientation tuning (e.g., orientation bias index) and contrast sensitivity (e.g., contrast threshold and C₅₀) in neurons of the primary visual cortex. This enhancement is likely due to improved information processing efficiency, characterized by reduced neuronal variability and increased signal-to-noise ratio. These findings suggest that the primary visual cortex can achieve precise and efficient information encoding in complex lighting environments by selectively adapting to different flicker frequencies and optimizing receptive field properties. This study provides new experimental evidence on how various types of light flicker influence visual perception and offers insights into the mechanisms through which specific frequencies enhance brain function.

Objective To propose a dynamic early warning model based on machine learning methods and validate its predi-ctive efficacy so as to achieve precise assessment and early warning of mortality risk in patients with traumatic hypothermia.Methods Firstly,a total of 480 patients who met inclusion criteria were retrospectively selected from the eICU database and randomly divided into training and test sets at an 8∶2 ratio.Secondly,physiological parameters were extracted from these patients,and five machine learning algorithms including XGBoost,AdaBoost,LightGBM,logistic regression(LR)and random forest(RF)were employed respectively to develop dynamic mortality risk warning models for traumatic hypothermia patients,utilizing a 1-hour observation window.Thirdly,receiver operating characteristic curves(ROC)were plotted using the test set data and the effects of different warning windows on the model performance were analyzed by calculating the AUC.Finally,the interpretability of the models was analyzed using the SHapley Additive exPlanations(SHAP)algorithm to elucidate the contribution of each feature to predictive performance.Results The optimal warning window for the dynamic warning model constructed using the eICU database was 12 hours,and in case of 12-hour warning window the logistic regression model achieved the highest AUC of 0.935 and showed optimal predictive performance.The results of the interpretability analysis by the SHAP algorithm showed that body temperature was the feature that had the greatest impact on the model results,and its reduction was positively correlated with the increased risk of death.Conclusion The machine learning-based dynamic warning model for mortality risk in traumatic hypothermia patients enables real-time dynamic risk assessment,providing robust support for clinicians to identify the patient's condition changes at an early stage and references for the adjustment of clinical treatment programs.[Chinese Medical Equipment Journal,2025,46(3):9-14]