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OBJECTIVE: The risk category of gastric gastrointestinal stromal tumors (GISTs) are closely related to the surgical method, the scope of resection, and the need for preoperative chemotherapy. We aimed to develop and validate convolutional neural network (CNN) models based on preoperative venous-phase CT images to predict the risk category of gastric GISTs. METHOD: A total of 425 patients pathologically diagnosed with gastric GISTs at the authors' medical centers between January 2012 and July 2021 were split into a training set (154, 84, and 59 with very low/low, intermediate, and high-risk, respectively) and a validation set (67, 35, and 26, respectively). Three CNN models were constructed by obtaining the upper and lower 1, 4, and 7 layers of the maximum tumour mask slice based on venous-phase CT Images and models of CNN_layer3, CNN_layer9, and CNN_layer15 established, respectively. The area under the receiver operating characteristics curve (AUROC) and the Obuchowski index were calculated to compare the diagnostic performance of the CNN models. RESULTS: In the validation set, CNN_layer3, CNN_layer9, and CNN_layer15 had AUROCs of 0.89, 0.90, and 0.90, respectively, for low-risk gastric GISTs; 0.82, 0.83, and 0.83 for intermediate-risk gastric GISTs; and 0.86, 0.86, and 0.85 for high-risk gastric GISTs. In the validation dataset, CNN_layer3 (Obuchowski index, 0.871) provided similar performance than CNN_layer9 and CNN_layer15 (Obuchowski index, 0.875 and 0.873, respectively) in prediction of the gastric GIST risk category (All P >.05). CONCLUSIONS: The CNN based on preoperative venous-phase CT images showed good performance for predicting the risk category of gastric GISTs.
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Tumores do Estroma Gastrointestinal , Neoplasias Gástricas , Humanos , Tumores do Estroma Gastrointestinal/diagnóstico por imagem , Tumores do Estroma Gastrointestinal/cirurgia , Tomografia Computadorizada por Raios X/métodos , Neoplasias Gástricas/diagnóstico por imagem , Neoplasias Gástricas/cirurgia , Redes Neurais de Computação , Curva ROCRESUMO
Oxidative stress-induced ferroptosis of retinal pigment epithelium (RPE) cells contributes to retinal degenerative diseases. The antioxidant molecule hydrogen sulfide (H2S) regulates oxidative stress response, but its effect on the ferroptosis of RPE cells is unclear. In this study, sodium hydrosulfide (NaHS) was used as an exogenous H2S donor to intervene tert-butyl hydroperoxide (t-BHP)-induced ferroptosis of APRE-19 cells. We found that NaHS pretreatment attenuates t-BHP-induced oxidative stress and ferroptosis. Analysis of mRNA-sequencing coupled with FerrDb database identified nuclear factor erythroid-2-related factor 2 (NRF2) as a primary target for the cytoprotective role of H2S. NRF2 inhibitor ML385 reverses the effects of H2S on ferroptosis. Biochemical analysis revealed that H2S stabilizes NRF2. H2S decreases the interaction between NRF2 and KEAP1, but enhances the interaction between KEAP1 and p62. These results suggest that H2S activates the non-canonical NRF2-KEAP1 pathway. Further study demonstrated that H2S stimulates AMPK to interact and phosphorylate p62. Additionally, inhibiting AMPK or knocking down p62 blocks the effects of H2S. We speculate that targeting the non-canonical NRF2-KEAP1 pathway by H2S-based drug may benefit the treatment of retinal degenerative diseases.
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Ferroptose , Sulfeto de Hidrogênio , Proteína 1 Associada a ECH Semelhante a Kelch/genética , Proteína 1 Associada a ECH Semelhante a Kelch/metabolismo , Sulfeto de Hidrogênio/farmacologia , Sulfeto de Hidrogênio/metabolismo , Fator 2 Relacionado a NF-E2/genética , Fator 2 Relacionado a NF-E2/metabolismo , Proteínas Quinases Ativadas por AMP/metabolismo , Epitélio Pigmentado da Retina/metabolismo , Estresse Oxidativo , terc-Butil Hidroperóxido/farmacologia , Espécies Reativas de Oxigênio/metabolismoRESUMO
PURPOSE: To develop a deep learning-based cascaded HRNet model, in order to automatically measure X-ray imaging parameters of lumbar sagittal curvature and to evaluate its prediction performance. METHODS: A total of 3730 lumbar lateral digital radiography (DR) images were collected from picture archiving and communication system (PACS). Among them, 3150 images were randomly selected as the training dataset and validation dataset, and 580 images as the test dataset. The landmarks of the lumbar curve index (LCI), lumbar lordosis angle (LLA), sacral slope (SS), lumbar lordosis index (LLI), and the posterior edge tangent angle of the vertebral body (PTA) were identified and marked. The measured results of landmarks on the test dataset were compared with the mean values of manual measurement as the reference standard. Percentage of correct key-points (PCK), intra-class correlation coefficient (ICC), Pearson correlation coefficient (r), mean absolute error (MAE), mean square error (MSE), root-mean-square error (RMSE), and Bland-Altman plot were used to evaluate the performance of the cascade HRNet model. RESULTS: The PCK of the cascaded HRNet model was 97.9-100% in the 3 mm distance threshold. The mean differences between the reference standard and the predicted values for LCI, LLA, SS, LLI, and PTA were 0.43 mm, 0.99°, 1.11°, 0.01 mm, and 0.23°, respectively. There were strong correlation and consistency of the five parameters between the cascaded HRNet model and manual measurements (ICC = 0.989-0.999, R = 0.991-0.999, MAE = 0.63-1.65, MSE = 0.61-4.06, RMSE = 0.78-2.01). CONCLUSION: The cascaded HRNet model based on deep learning algorithm could accurately identify the sagittal curvature-related landmarks on lateral lumbar DR images and automatically measure the relevant parameters, which is of great significance in clinical application.
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OBJECTIVES: Develop and evaluate the performance of deep learning and linear regression cascade algorithms for automated assessment of the image layout and position of chest radiographs. METHODS: This retrospective study used 10 quantitative indices to capture subjective perceptions of radiologists regarding image layout and position of chest radiographs, including the chest edges, field of view (FOV), clavicles, rotation, scapulae, and symmetry. An automated assessment system was developed using a training dataset consisting of 1025 adult posterior-anterior chest radiographs. The evaluation steps included: (i) use of a CNN framework based on ResNet - 34 to obtain measurement parameters for quantitative indices and (ii) analysis of quantitative indices using a multiple linear regression model to obtain predicted scores for the layout and position of chest radiograph. In the testing dataset (n = 100), the performance of the automated system was evaluated using the intraclass correlation coefficient (ICC), Pearson correlation coefficient (r), mean absolute difference (MAD), and mean absolute percentage error (MAPE). RESULTS: The stepwise regression showed a statistically significant relationship between the 10 quantitative indices and subjective scores (p < 0.05). The deep learning model showed high accuracy in predicting the quantitative indices (ICC = 0.82 to 0.99, r = 0.69 to 0.99, MAD = 0.01 to 2.75). The automatic system provided assessments similar to the mean opinion scores of radiologists regarding image layout (MAPE = 3.05%) and position (MAPE = 5.72%). CONCLUSIONS: Ten quantitative indices correlated well with the subjective perceptions of radiologists regarding the image layout and position of chest radiographs. The automated system provided high performance in measuring quantitative indices and assessing image quality. KEY POINTS: ⢠Objective and reliable assessment for image quality of chest radiographs is important for improving image quality and diagnostic accuracy. ⢠Deep learning can be used for automated measurements of quantitative indices from chest radiographs. ⢠Linear regression can be used for interpretation-based quality assessment of chest radiographs.
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Aprendizado Profundo , Adulto , Humanos , Radiografia Torácica/métodos , Modelos Lineares , Estudos Retrospectivos , AlgoritmosRESUMO
BACKGROUND: The analysis of sagittal intervertebral rotational motion (SIRM) can provide important information for the evaluation of cervical diseases. Deep learning has been widely used in spinal parameter measurements, however, there are few investigations on spinal motion analysis. The purpose of this study is to develop a deep learning-based model for fully automated measurement of SIRM based on flexion-neutral-extension cervical lateral radiographs and to evaluate its applicability for the flexion-extension (F/E), flexion-neutral (F/N), and neutral-extension (N/E) motion analysis. METHODS: A total of 2796 flexion, neutral, and extension cervical lateral radiographs from 932 patients were analyzed. Radiographs from 100 patients were randomly selected as the test set, and those from the remaining 832 patients were used for training and validation. Landmarks were annotated for measuring SIRM at five segments from C2/3 to C6/7 on F/E, F/N, and N/E motion. High-Resolution Net (HRNet) was used as the main structure to train the landmark detection network. Landmark performance was assessed according to the percentage of correct key points (PCK) and mean of the percentage of correct key points (MPCK). Measurement performance was evaluated by intra-class correlation coefficient (ICC), Pearson correlation coefficient, mean absolute error (MAE), root mean square error (RMSE), and Bland-Altman plots. RESULTS: At a 2-mm distance threshold, the PCK for the model ranged from 94 to 100%. Compared with the reference standards, the model showed high accuracy for SIRM measurements for all segments on F/E and F/N motion. On N/E motion, the model provided reliable measurements from C3/4 to C6/7, but not C2/3. Compared with the radiologists' measurements, the model showed similar performance to the radiologists. CONCLUSIONS: The developed model can automatically measure SIRM on flexion-neutral-extension cervical lateral radiographs and showed comparable performance with radiologists. It may provide rapid, accurate, and comprehensive information for cervical motion analysis.
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Vértebras Cervicais , Aprendizado Profundo , Humanos , Vértebras Cervicais/diagnóstico por imagem , Radiografia , Amplitude de Movimento Articular , PescoçoRESUMO
BACKGROUND: Measurement of the posterior tibial slope (PTS) angle has important applications in total knee replacement surgery, high tibial osteotomy, and anterior cruciate ligament reconstruction. This study aimed to determine the mean PTS of knee joints in healthy Chinese adults, and provide data to guide knee surgery in China. METHODS: A retrospective analysis of 1257 (n = 1233, 50.4% male) plain X-ray films of participants aged 25-59 years was performed. The picture archiving and communication system was used for PTS measurement. The PTS was defined as the angle between the vertical line of the tangent of the anterior tibial cortex of the proximal tibia, and the tangent line of the tibial cortex. Two imaging physicians conducted the PTS measurements independently, and both the inter- and intraclass correlation coefficients (ICCs) were calculated. RESULTS: The mean PTS value was 7.68 ± 3.84° (range: 0-21°). The left PTS was significantly smaller in males than in females (7.22 ± 3.89 vs 8.05 ± 3.60; P = 0.005). Additionally, the PTS in participants aged 25-29 years was significantly larger than that in the other age groups (Left side: 8.64 ± 3.73 vs 6.92 ± 3.42, 7.42 ± 3.75, 7.53 ± 3.98; P < 0.001 and Right side: 8.68 ± 3.84 vs 7.48 ± 4.21, 7.13 ± 3.64, 7.66 ± 3.80; P = 0.004). There were no significant differences in PTS between the left and right sides. Two-way analysis of variance suggested that the differences in PTS between age groups were not affected by sex. The interobserver ICC was 0.91 (95% confidence interval [CI]: 0.85-0.94), and the intraobserver ICC was 0.90 (95% CI: 0.82-0.94). CONCLUSIONS: This study demonstrated that there were significant differences in PTS based on sex and age, highlighting the need to provide individualized treatment for knee surgery. It provided valuable information regarding the normal PTS values in Chinese adults and presented regionalised data to guide knee surgery.
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Reconstrução do Ligamento Cruzado Anterior , Artroplastia do Joelho , Adulto , Artroplastia do Joelho/métodos , Feminino , Humanos , Articulação do Joelho/diagnóstico por imagem , Articulação do Joelho/cirurgia , Masculino , Estudos Retrospectivos , Tíbia/diagnóstico por imagem , Tíbia/cirurgiaRESUMO
Advanced glycation end products (AGEs) are the compounds produced by non-enzymatic glycation of proteins, which are involved in diabetic-related complications. To investigate the potential anti-glycation activity of Myriocin (Myr), a fungal metabolite of Cordyceps, the effect of Myr on the formation of AGEs resulted from the glycation of bovine serum albumin (BSA) and the interaction between Myr and BSA were studied by multiple spectroscopic techniques and computational simulations. We found that Myr inhibited the formation of AGEs at the end stage of glycation reaction and exhibited strong anti-fibrillation activity. Spectroscopic analysis revealed that Myr quenched the fluorescence of BSA in a static process, with the possible formation of a complex (approximate molar ratio of 1:1). The binding between BSA and Myr mainly depended on van der Waals interaction, hydrophobic interactions and hydrogen bond. The synchronous fluorescence and UV-visible (UV-vis) spectra results indicated that the conformation of BSA altered in the presence of Myr. The fluorescent probe displacement experiments and molecular docking suggested that Myr primarily bound to binding site 1 (subdomain IIA) of BSA. These findings demonstrate that Myr is a potential anti-glycation agent and provide a theoretical basis for the further functional research of Myr in the prevention and treatment of AGEs-related diseases.
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Produtos Finais de Glicação Avançada , Soroalbumina Bovina , Soroalbumina Bovina/química , Simulação de Acoplamento Molecular , Produtos Finais de Glicação Avançada/metabolismo , Corantes Fluorescentes , Sítios de Ligação , Espectrometria de Fluorescência , Termodinâmica , Ligação Proteica , Espectrofotometria UltravioletaRESUMO
Myocardial 2',3'-cyclic nucleotide 3'-phosphodiesterase (CNPase) metabolizes a nucleoside 2',3'-cyclic phosphate to a nucleoside 2'-phosphate. Recently, the roles of CNPase in the pathophysiological processes of heart failure have emerged. The mitochondrial acylome subjected to SIRT3 regulation give us comprehensive understanding of acylation modifications to a vast array of protein targets, and the list of acetylated mitochondrial proteins is still growing. However, it remains elusive whether CNPase is subjected to the regulation of acetylation and deacetylation, and the effects of which on CNPase enzymatic activity are still unknown. In this study, the mitochondrial distribution of CNPase was identified by immunofluorescence and cytosol/mitochondria fractioning. The immunofluorescence staining pattern of CNPase and Sirt3 overlapped on the same focal plane. Moreover, Sirt3 associates directly with CNPase, and the CNPase enzymatic activity was subjected to Sirt3 activity. Then biochemical methods using acetic anhydride was employed to acetylate the CNPase proteins, the enzymatic activity of CNPase decreased. Furthermore, co-immunoprecipitation coupled mass spectrometry identifies K196, K379, K128 as the main acetylation sites. Molecular dynamic simulation shows that acetylation modification suppressed the CNPase enzymatic activity through decreasing the opening probability of the binding pocket and restricting substrate accessibility. Together with these findings, this study reveals a molecular mechanism underlying Sirt3 regulating CNPase enzymatic activity, and suggests that targeting CNPase's post-translational modifications represents a promising therapeutic strategy.
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2',3'-Nucleotídeo Cíclico Fosfodiesterases/metabolismo , Sirtuínas/metabolismo , Acilação , Animais , Células Cultivadas , Ratos , Especificidade por SubstratoRESUMO
Liver fibrosis is an increasing health problem worldwide, for which no effective antifibrosis drugs are available. Although the involvement of aerobic glycolysis in hepatic stellate cell (HSC) activation has been reported, the role of pyruvate kinase M2 (PKM2) in liver fibrogenesis still remains unknown. We examined PKM2 expression and location in liver tissues and primary hepatic cells. The in vitro and in vivo effects of a PKM2 antagonist (shikonin) and its allosteric agent (TEPP-46) on liver fibrosis were investigated in HSCs and liver fibrosis mouse model. Chromatin immunoprecipitation sequencing and immunoprecipitation were performed to identify the relevant molecular mechanisms. PKM2 expression was significantly up-regulated in both mouse and human fibrotic livers compared with normal livers, and mainly detected in activated, rather than quiescent, HSCs. PKM2 knockdown markedly inhibited the activation and proliferation of HSCs in vitro. Interestingly, the PKM2 dimer, rather than the tetramer, induced HSC activation. PKM2 tetramerization induced by TEPP-46 effectively inhibited HSC activation, reduced aerobic glycolysis, and decreased MYC and CCND1 expression via regulating histone H3K9 acetylation in activated HSCs. TEPP-46 and shikonin dramatically attenuated liver fibrosis in vivo. Our findings demonstrate a nonmetabolic role of PKM2 in liver fibrosis. PKM2 tetramerization or suppression could prevent HSC activation and protects against liver fibrosis.
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Células Estreladas do Fígado/enzimologia , Cirrose Hepática/enzimologia , Multimerização Proteica , Piruvato Quinase/metabolismo , Acetilação , Animais , Ciclina D1/metabolismo , Feminino , Células Estreladas do Fígado/patologia , Histonas/metabolismo , Humanos , Cirrose Hepática/patologia , Masculino , Camundongos , Compostos Orgânicos/farmacologia , Proteínas Proto-Oncogênicas c-myc/metabolismo , Piridazinas , PirróisRESUMO
OBJECTIVES: To study the effect of ultrashort wave combined with loxoprofen sodium on serum inflammatory factors in patients with acute gouty arthritis. METHODS: Records of patients with acute gouty arthritis who were treated in The Fourth Hospital of Changsha from May 2018 to September 2020, were reviewed. Of them, 77 cases were selected and divided into two groups based on the received treatment. The control group (n=39) was treated with loxoprofen sodium, and the treatment group (n=38) was treated with an ultrashort wave combined with loxoprofen sodium, for 10 continuous days. The clinical efficacy of the treatment in two groups was analyzed. RESULTS: After treatment, the quality of life of patients in both groups was improved (P < 0.05), but there was no significant difference in the degree of improvement between the two groups (P > 0.05). After treatment, the VAS score of the treatment group was lower than that of the control group (P < 0.05), the improvement of symptoms and signs of the treatment group was better than that of the control group (P < 0.05). Serum CRP and ESR levels in the treatment group were lower than those in the control group (P < 0.05), and the serum IL-1 ß, IL-8, TNF-a and MMP-3 levels of the treatment group were lower than those of the control group (P < 0.05). The total effective rate of the treatment group (94.87%) was higher than that of the control group (87.18%), the difference was statistically significant (P < 0.05). No adverse reactions occurred in all patients during the treatment. CONCLUSION: An ultrashort wave combined with loxoprofen sodium in the treatment of acute gouty arthritis can reduce the inflammatory reaction, improve the degree of joint pain and swelling, improve the curative effect, and do not increase the adverse reactions. The results may be related to the regulation of IL-1 ß, IL-8, TNF-a and MMP-3.
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Protective effect of protodioscin or methyl protodioscin against inflammation had been reported in various inflammation diseases. This study aimed to investigate the effect of protodioscin against Complete Freund's adjuvant (CFA)-induced arthritis rats. Rats randomly divided into model groups were injected with CFA, companied with different dose of protodioscin (50, 100, and 200 mg/kg body weight). The histology, changes in biochemical parameters and inflammatory cytokines expression were detected for anti-inflammation effect evaluation of protodioscin. CFA treatment induced arthritic rats with swelling paw, ankle inflammation, and area of lymphocyte infiltration, upregulated inflammatory cytokines (IL-1ß, TNF-α, cyclo-oxygenase 2, and IL-6 as well as prostaglandin E2), articular elastase, myeloperoxidase, lipid peroxidase and nitrite oxide levels, downregulated glutathione, catalase, and superoxide dismutase. In contrast, protodioscin ameliorated all the changes induced by CFA in rats, suggesting the anti-inflammatory effect of protodioscin. We concluded that protodioscin administration into CFA-induced arthritis rats protected against CFA-induced oxidative stress, neutrophil infiltration, and inflammation, suggesting the anti-inflammatory effect and the therapeutic potential of protodioscin for arthritis.
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Anti-Inflamatórios/farmacologia , Artrite Experimental/tratamento farmacológico , Diosgenina/análogos & derivados , Edema/tratamento farmacológico , Regulação da Expressão Gênica/efeitos dos fármacos , Saponinas/farmacologia , Animais , Apoptose/efeitos dos fármacos , Artrite Experimental/induzido quimicamente , Artrite Experimental/genética , Artrite Experimental/patologia , Catalase/genética , Catalase/metabolismo , Ciclo-Oxigenase 2/genética , Ciclo-Oxigenase 2/metabolismo , Dinoprostona/metabolismo , Diosgenina/farmacologia , Relação Dose-Resposta a Droga , Edema/induzido quimicamente , Edema/genética , Edema/patologia , Adjuvante de Freund/administração & dosagem , Glutationa/metabolismo , Membro Posterior , Interleucina-1beta/genética , Interleucina-1beta/metabolismo , Interleucina-6/genética , Interleucina-6/metabolismo , Masculino , Óxido Nítrico/metabolismo , Estresse Oxidativo , Elastase Pancreática/genética , Elastase Pancreática/metabolismo , Peroxidase/genética , Peroxidase/metabolismo , Ratos , Ratos Sprague-Dawley , Transdução de Sinais , Superóxido Dismutase/genética , Superóxido Dismutase/metabolismo , Fator de Necrose Tumoral alfa/genética , Fator de Necrose Tumoral alfa/metabolismoRESUMO
It is now accepted that white matter abnormalities play an important role in demyelinating diseases and a wide range of psychiatric disorders. Experimental demyelination (especially induced by cuprizone) has been investigated extensively. However, details regarding demyelination and ultrastructural changes of myelinated fibers have not been previously reported. Therefore, we determined the extent of demyelination using quantitative stereology. Mice exposed to cuprizone in the current study showed abnormal anxiety-like behavior without impaired spatial learning or memory. The myelinated fibers in whole corpus callosum of mice exposed to cuprizone showed extensive myelin deficiencies and occasional axonal injuries. The total length of the myelinated fibers in whole corpus callosum of mice exposed to cuprizone was significantly decreased by 45% compared with control mice. The loss of myelinated fibers was mainly due to the marked loss of the fibers with a diameter of 0.4 to 0.8 µm. The g-ratio of the myelinated fibers in the corpus callosum of mice exposed to cuprizone (0.69 ± 0.02) was significantly decreased compared with control mice (0.76 ± 0.02). These results might help us to further understand the role of white matter abnormalities in demyelinating diseases or a wide range of psychiatric disorders. © 2016 Wiley Periodicals, Inc.
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Corpo Caloso/patologia , Corpo Caloso/ultraestrutura , Doenças Desmielinizantes/induzido quimicamente , Doenças Desmielinizantes/patologia , Animais , Quelantes/toxicidade , Corpo Caloso/efeitos dos fármacos , Cuprizona/toxicidade , Modelos Animais de Doenças , Comportamento Exploratório/efeitos dos fármacos , Masculino , Aprendizagem em Labirinto/efeitos dos fármacos , Camundongos , Camundongos Endogâmicos C57BL , Microscopia Eletrônica de Transmissão , Proteína Básica da Mielina/metabolismo , Fibras Nervosas Mielinizadas/patologia , Fibras Nervosas Mielinizadas/ultraestrutura , Teste de Desempenho do Rota-RodRESUMO
Background and aim: Dapagliflozin inhibits the sodium-glucose cotransporter protein 2 (SGLT-2), while sotagliflozin, belonging to a new class of dual-acting SGLT-1/SGLT-2 inhibitors, has garnered considerable attention due to its efficacy and safety. Both Dapagliflozin and sotagliflozin play a significant role in treating worsening heart failure in diabetes/nondiabetes patients with heart failure. Therefore, this article was to analyze and compare the cost per outcome of both drugs in preventing one event in patients diagnosed with diabetes-related heart failure. Method: The Cost Needed to Treat (CNT) was employed to calculate the cost of preventing one event, and the Number Needed to Treat (NNT) represents the anticipated number of patients requiring the intervention treatment to prevent a single adverse event, or the anticipated number of patients needing multiple treatments to achieve a beneficial outcome. The efficacy and safety data were obtained from the results of two published clinical trials, DAPA-HF and SOLOIST-WHF. Due to the temporal difference in the drugs' releases, we temporarily analyzed the price of dapagliflozin to calculate the price of sotagliflozin within the same timeframe. The secondary analyses aimed to assess the stability of the CNT study and minimize differences between the results of the RCT control and trial groups, employing one-way sensitivity analyses. Result: The final results revealed an annualized Number Needed to Treat (aNNT) of 4 (95% CI 3-7) for preventing one event with sotagliflozin, as opposed to 23 (95% CI 16-55) for dapagliflozin. We calculated dapagliflozin's cost per prevented event (CNT) to be $109,043 (95% CI $75,856-$260,755). The price of sotagliflozin was set below $27,260, providing a favorable advantage. Sensitivity analysis suggests that sotagliflozin may hold a cost advantage. Conclusion: In this study, sotagliflozin was observed to exhibit a price advantage over dapagliflozin in preventing one events, cardiovascular mortality, or all-cause mortality in patients with diabetes.
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Gemcitabine is considered the standard first-line chemotherapeutic agent for patients with intrahepatic cholangiocarcinoma (ICC). However, its therapeutic efficacy is hampered by the development of chemoresistance. Pyruvate kinase M2 (PKM2), a crucial mediator of the final step in glycolysis, has been implicated in the origination and advancement of diverse malignancies. Its expression is increased in many tumor types and this may correlate with increased drug sensitivity. However, the specific effect of PKM2 on the gemcitabine sensitivity in ICC remains to be elucidated. In this research, we aimed to elucidate the role and functional significance of PKM2 in ICC, as well as the heightened susceptibility of ICC cells to gemcitabine by targeting PKM2 and the underlying molecular mechanisms. Immunohistochemical and immunofluorescence analyses revealed elevated expression of PKM2 in both tumor cells and macrophages in human ICC tissues. Reducing PKM2 levels significantly restrained the proliferation of tumor cells, impeded cell cycle advance, induced programmed cell death, and suppressed metastasis. In addition, knockdown or pharmacological inhibition of PKM2 could enhance the response of ICC cells to gemcitabine in vitro. Interestingly, conditioned medium co-culture system suggested that conditioned medium from M2 macrophages increased gemcitabine sensitivity of ICC cells. However, silencing PKM2 or pharmacological inhibition of PKM2 in M2 macrophages did not ameliorate the gemcitabine resistance mediated by M2 macrophages derived conditioned medium. Mechanistically, downregulation of PKM2 repressed the expression of ß-catenin and its downstream transcriptional targets, thereby hindering the propagation of ß-catenin signaling cascade. Finally, the results of the subcutaneous xenograft experiment in nude mice provided compelling evidence of a synergistic interaction between PKM2-IN-1 and gemcitabine in vivo. In summary, we reported that PKM2 may function as an advantageous target for increasing the sensitivity of ICC to gemcitabine treatment. Targeting PKM2 improves the gemcitabine sensitivity of ICC cells via inhibiting ß-catenin signaling pathway.
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Neoplasias dos Ductos Biliares , Colangiocarcinoma , Animais , Camundongos , Humanos , Gencitabina , beta Catenina/metabolismo , Camundongos Nus , Meios de Cultivo Condicionados , Linhagem Celular Tumoral , Transdução de Sinais , Colangiocarcinoma/metabolismo , Ductos Biliares Intra-Hepáticos/metabolismo , Ductos Biliares Intra-Hepáticos/patologia , Neoplasias dos Ductos Biliares/tratamento farmacológico , Neoplasias dos Ductos Biliares/metabolismo , Neoplasias dos Ductos Biliares/patologia , Proliferação de CélulasRESUMO
Cerebral ischemic stroke is a serious disease with high mortality and disability rates. However, few neuroprotective drugs have been used for ischemic stroke in the clinic. Two main reasons may be responsible for this failure: difficulty in penetrating the blood-brain barrier (BBB) and easily inactivated in the blood circulation. Ferroptosis, a lipid oxidation-related cell death, plays significant roles in cerebral ischemia-reperfusion injury. We utilized RVG29, a peptide derived from Rabies virus glycoprotein, to obtain BBB-targeted lipid nanoparticles (T-LNPs) in order to investigate whether T-LNPs improved the neuroprotective effects of Ferrostatin-1 (Fer1, an inhibitor of ferroptosis) against cerebral ischemic damage. T-LNPs significantly increased BBB penetration following oxygen/glucose deprivation exposure in an in vitro BBB model and enhanced the fluorescence distribution in brain tissues at 6 h post-administration in a cerebral ischemic murine model. Moreover, T-LNPs encapsulated Fer1 (T-LNPs-Fer1) significantly enhanced the inhibitory effects of Fer1 on ferroptosis by maintaining the homeostasis of NADPH oxidase 4 (NOX4) and glutathione peroxidase 4 (GPX4) signals in neuronal cells after cerebral ischemia. T-LNPs-Fer1 significantly suppressed oxidative stress [heme oxygenase-1 expression and malondialdehyde (the product of lipid ROS reaction)] in neurons and alleviated ischemia-induced neuronal cell death, compared to Fer1 alone without encapsulation. Furthermore, T-LNPs-Fer1 significantly reduced cerebral infarction and improved behavior functions compared to Fer1-treated cerebral ischemic mice after 45-min ischemia/24-h reperfusion. These findings showed that the T-LNPs helped Fer1 penetrate the BBB and improved the neuroprotection of Fer1 against cerebral ischemic damage in experimental stroke, providing a feasible translational strategy for the development of clinical drugs for the treatment of ischemic stroke.
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Barreira Hematoencefálica , Cicloexilaminas , Nanopartículas , Fármacos Neuroprotetores , Fenilenodiaminas , Animais , Camundongos , Barreira Hematoencefálica/efeitos dos fármacos , Barreira Hematoencefálica/metabolismo , Barreira Hematoencefálica/patologia , Fármacos Neuroprotetores/farmacologia , Nanopartículas/administração & dosagem , Masculino , Cicloexilaminas/farmacologia , Fenilenodiaminas/farmacologia , Fenilenodiaminas/uso terapêutico , AVC Isquêmico/tratamento farmacológico , AVC Isquêmico/patologia , Isquemia Encefálica/tratamento farmacológico , Isquemia Encefálica/patologia , Isquemia Encefálica/metabolismo , Camundongos Endogâmicos C57BL , Modelos Animais de Doenças , Ferroptose/efeitos dos fármacos , Glicoproteínas , Lipossomos , Fragmentos de Peptídeos , Proteínas ViraisRESUMO
Background: Lumbar spine disorders are one of the common causes of low back pain (LBP). Objective and reliable measurement of anatomical parameters of the lumbar spine is essential in the clinical diagnosis and evaluation of lumbar disorders. However, manual measurements are time-consuming and laborious, with poor consistency and repeatability. Here, we aim to develop and evaluate an automatic measurement model for measuring the anatomical parameters of the vertebral body and intervertebral disc based on lateral lumbar radiographs and deep learning (DL). Methods: A model based on DL was developed with a dataset consisting of 1,318 lateral lumbar radiographs for the prediction of anatomical parameters, including vertebral body heights (VBH), intervertebral disc heights (IDH), and intervertebral disc angles (IDA). The mean of the values obtained by 3 radiologists was used as a reference standard. Statistical analysis was performed in terms of standard deviation (SD), mean absolute error (MAE), Percentage of correct keypoints (PCK), intraclass correlation coefficient (ICC), regression analysis, and Bland-Altman plot to evaluate the performance of the model compared with the reference standard. Results: The percentage of intra-observer landmark distance within the 3 mm threshold was 96%. The percentage of inter-observer landmark distance within the 3 mm threshold was 94% (R1 and R2), 92% (R1 and R3), and 93% (R2 and R3), respectively. The PCK of the model within the 3 mm distance threshold was 94-99%. The model-predicted values were 30.22±3.01 mm, 10.40±3.91 mm, and 10.63°±4.74° for VBH, IDH, and IDA, respectively. There were good correlation and consistency in anatomical parameters of the lumbar vertebral body and disc between the model and the reference standard in most cases (R2=0.89-0.95, ICC =0.93-0.98, MAE =0.61-1.15, and SD =0.89-1.64). Conclusions: The newly proposed model based on a DL algorithm can accurately measure various anatomical parameters on lateral lumbar radiographs. This could provide an accurate and efficient measurement tool for the quantitative evaluation of spinal disorders.
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Psoriasis, a chronic inflammatory skin disease induced by various factors, including genetic factors, immune factors, environmental factors, and psychological factors, is characterized by thickening of the epidermis, excessive proliferation of keratinocytes, abnormal differentiation, and an excessive inflammatory response. Traditional treatments for psoriasis still face challenges because of limited curative effects, notable side effects, and a tendency for recurrence. In contrast, topical therapy provides a favorable option for psoriasis treatment because of its noninvasive and self-administered method. In this study, gentiopicrin (Gen) is encapsulated in the liposomes to form a nanodrug, and then chitosan is covered on the nanodrug to assemble the nanodrug delivery system (CS@Gen), which is used as a topical agent for treating psoriasis. Then M5 (a mixture of five pro-inflammatory cytokines, i.e., IL-17A, IL-22, IL-1α, oncostatin M, and TNF-α)-induced HacaT cells and imiquimod-induced psoriasis mouse models are established, whose results show that CS@Gen induces apoptosis and inhibits the proliferation and cell migration of psoriasis keratinocytes. Additionally, the application of CS@Gen cream can significantly reduce epidermal thickness, diminish skin scaling, and improve other related mechanisms in mice affected by psoriasis. Meanwhile, the prepared CS@Gen can significantly reduce the expression levels of IL-17a, Cxcl2, S100a, Mki67, and other related inflammatory factors, resulting in indirectly inhibiting the inflammation of keratinocytes. In summary, the present study provides an ideal loading for an anti-inflammatory and immunomodulatory drug delivery system for the treatment of psoriasis.
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Neem leaves have long been used in traditional medicine for promoting longevity. However, the precise mechanisms underlying their anti-aging effects remain elusive. In this study, we investigated the impact of neem leaf extract (NLE) extracted from a 50% ethanol solution on the chronological lifespan of Saccharomyces cerevisiae, revealing an extension in lifespan, heightened oxidative stress resistance, and a reduction in reactive oxygen species. To discern the active compounds in NLE, LC/MS and the GNPS platform were employed. The majority of identified active compounds were found to be flavonoids. Subsequently, compound-target pharmacological networks were constructed using the STP and STITCH platforms for both S. cerevisiae and Homo sapiens. GOMF and KEGG enrichment analyses of the predicted targets revealed that "oxidoreductase activity" was among the top enriched terms in both yeast and human cells. These suggested a potential regulation of oxidative stress response (OSR) by NLE. RNA-seq analysis of NLE-treated yeast corroborated the anti-oxidative effect, with "oxidoreductase activity" and "oxidation-reduction process" ranking high in enriched GO terms. Notably, CTT1, encoding catalase, emerged as the most significantly up-regulated gene within the "oxidoreductase activity" cluster. In a ctt1 null mutant, the enhanced oxidative stress resistance and extended lifespan induced by NLE were nullified. For human cells, NLE pretreatment demonstrated a decrease in reactive oxygen species levels and senescence-associated ß-galactosidase activity in HeLa cells, indicative of anti-aging and anti-oxidative effects. This study unveils the anti-aging and anti-oxidative properties of NLE while delving into their mechanisms, providing novel insights for pharmacological interventions in aging using phytochemicals.
Assuntos
Antioxidantes , Estresse Oxidativo , Extratos Vegetais , Folhas de Planta , Espécies Reativas de Oxigênio , Saccharomyces cerevisiae , Humanos , Saccharomyces cerevisiae/efeitos dos fármacos , Folhas de Planta/química , Extratos Vegetais/farmacologia , Antioxidantes/farmacologia , Estresse Oxidativo/efeitos dos fármacos , Espécies Reativas de Oxigênio/metabolismo , Envelhecimento/efeitos dos fármacos , Flavonoides/farmacologiaRESUMO
Background: Morphological parameters of the lumbar spine are valuable in assessing lumbar spine diseases. However, manual measurement of lumbar morphological parameters is time-consuming. Deep learning has automatic quantitative and qualitative analysis capabilities. To develop a deep learning-based model for the automatic quantitative measurement of morphological parameters from anteroposterior digital radiographs of the lumbar spine and to evaluate its performance. Methods: This study used 1,368 anteroposterior digital radiographs of the lumbar spine to train a deep learning model to measure the quantitative morphological indicators, including L1 to L5 vertebral body height (VBH) and L1-L2 to L4-L5 intervertebral disc height (IDH). The means of the manual measurements by three radiologists were used as the reference standard. The parameters predicted by the model were analyzed against the manual measurements using paired t-tests. Percentage of correct key points (PCK), intra-class correlation coefficient (ICC), Pearson correlation coefficient (r), mean absolute error (MAE), root mean square error (RMSE), and Bland-Altman plots were performed to assess the performance of the model. Results: Within the 3-mm distance threshold, the model had a PCK range of 99.77-99.46% for the L1 to L4 vertebrae and 77.37% for the L5 vertebrae. Except for VBH-L5 and IDH_L3-L4, IDH_L4-L5 (P<0.05), the estimated values of the model in the remaining parameters were not statistically significant compared with the reference standard (P>0.05). Except for VBH-L5 and IDH_L4-L5, the model showed good correlation and consistency with the reference standard (ICC =0.84-0.96, r=0.85-0.97, MAE =0.5-0.66, RMSE =0.66-0.95). The model outperformed other models (EfficientDet + Unet, EfficientDet + DarkPose, HRNet, and Unet) in predicting landmarks within a distance threshold of 1.5 to 5 mm. Conclusions: The model developed in this study can automatically measure the morphological parameters of the L1 to L4 vertebrae from anteroposterior digital radiographs of the lumbar spine. Its performance is close to the level of radiologists.
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PURPOSE: To assess the performance of radiomics-based analysis of contrast-enhanced computerized tomography (CE-CT) images for distinguishing GS from gastric GIST. METHODS: Forty-nine patients with GS and two hundred fifty-three with GIST were enrolled in this retrospective study. CT features were evaluated by two associate chief radiologists. Radiomics features were extracted from portal venous phase images using Pyradiomics software. A non-radiomics dataset (combination of clinical characteristics and radiologist-determined CT features) and a radiomics dataset were used to build stepwise logistic regression and least absolute shrinkage and selection operator (LASSO) logistic regression models, respectively. Model performance was evaluated according to sensitivity, specificity, accuracy, and receiver operating characteristic (ROC) curve, and Delong's test was applied to compare the area under the curve (AUC) between different models. RESULTS: A total of 1223 radiomics features were extracted from portal venous phase images. After reducing dimensions by calculating Pearson correlation coefficients (PCCs), 20 radiomics features, 20 clinical characteristics + CT features were used to build the models, respectively. The AUC values for the models using radiomics features and those using clinical features were more than 0.900 for both the training and validation groups. There were no significant differences in predictive performance between the radiomic and clinical data models according to Delong's test. CONCLUSION: A radiomics-based model applied to CE-CT images showed comparable predictive performance to senior physicians in the differentiation of GS from GIST.