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Curcumae Radix (CR) is a widely used traditional Chinese medicine with significant pharmaceutical importance, including enhancing blood circulation and addressing blood stasis. This study aims to establish an integrated and rapid quality assessment method for CR from various botanical origins, based on chemical components, antiplatelet aggregation effects, and Fourier transform near-infrared (FT-NIR) spectroscopy combined with multivariate algorithms. Firstly, ultra-performance liquid chromatography-photodiode array (UPLC-PDA) combined with chemometric analyses was used to examine variations in the chemical profiles of CR. Secondly, the activation effect on blood circulation of CR was assessed using an in vitro antiplatelet aggregation assay. The studies revealed significant variations in chemical profiles and antiplatelet aggregation effects among CR samples from different botanical origins, with constituents such as germacrone, ß-elemene, bisdemethoxycurcumin, demethoxycurcumin, and curcumin showing a positive correlation with antiplatelet aggregation biopotency. Thirdly, FT-NIR spectroscopy was integrated with various machine learning algorithms, including Artificial Neural Network (ANN), K-Nearest Neighbors (KNN), Logistic Regression (LR), Support Vector Machine (SVM), and Subspace K-Nearest Neighbors (Subspace KNN), to classify CR samples from four distinct sources. The result showed that FT-NIR combined with KNN and SVM classification algorithms after SNV and MSC preprocessing successfully distinguished CR samples from four plant sources with an accuracy of 100%. Finally, Quantitative models for active constituents and antiplatelet aggregation bioactivity were developed by optimizing the partial least squares (PLS) model with interval combination optimization (ICO) and competitive adaptive reweighted sampling (CARS) techniques. The CARS-PLS model achieved the best predictive performance across all five components. The coefficient of determination (R2p) and root mean square error (RMSEP) in the independent test sets were 0.9708 and 0.2098, 0.8744 and 0.2065, 0.9511 and 0.0034, 0.9803 and 0.0066, 0.9567 and 0.0172 for germacrone, ß-elemene, bisdemethoxycurcumin, demethoxycurcumin and curcumin, respectively. The ICO-PLS model demonstrated superior predictive capabilities for antiplatelet aggregation biotency, achieving an R2p of 0.9010, and an RMSEP of 0.5370. This study provides a valuable reference for the quality evaluation of CR in a more rapid and comprehensive manner.
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Curcuma , Inhibidores de Agregación Plaquetaria , Agregación Plaquetaria , Espectroscopía Infrarroja Corta , Curcuma/química , Espectroscopía Infrarroja Corta/métodos , Agregación Plaquetaria/efectos de los fármacos , Espectroscopía Infrarroja por Transformada de Fourier/métodos , Inhibidores de Agregación Plaquetaria/análisis , Inhibidores de Agregación Plaquetaria/química , Animales , Cromatografía Líquida de Alta Presión/métodos , Medicamentos Herbarios Chinos/química , Medicamentos Herbarios Chinos/análisis , Algoritmos , Extractos Vegetales/químicaRESUMEN
A ratiometric nanosensor was developed for detecting methyl orange (MO) based on down/up-conversion luminescence achieved by a triplet-triplet annihilation upconversion luminescence (TTA-UCL) system. The probe, utilizing sensitizer and annihilator fluorophores encapsulated in nanomicelles, demonstrated high sensitivity and selectivity for MO detection. The energy transfer from UCL to MO endowed the sensor with responsive capabilities. The unaffected triplet-triplet energy transfer process maintained the phosphorescence signal constant, serving as a reference to construct the ratiometric sensor along with the UCL signal. Additionally, a smartphone-assisted colorimetric detection method was also developed based on the ratiometric sensor, enabling rapid and convenient detection of MO without the need for a spectrometer. The performance of the nanosensor in real water samples confirmed its potential for practical environmental applications.
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Aromatic amino acid oxidation products (AAAOPs) are newly discovered risk substances of thermal processes. Due to its significant polarity and trace level in food matrices, there are no efficient pre-treatment methods available to enrich AAAOPs. Herein, we proposed a magnetic cationic covalent organic framework (Fe3O4@EB-iCOF) as an adsorbent for dispersive magnetic solid-phase extraction (DMSPE). Benefiting from the unique charged characteristics of Fe3O4@EB-iCOF, AAAOPs can be enriched through electrostatic interaction and π-π interactions. Under the optimal DMSPE conditions, the combined HPLC-MS/MS method demonstrated good linearity (R2 ≥ 0.990) and a low detection limit (0.11-7.5 µg·kg-1) for AAAOPs. In addition, the method was applied to real sample and obtained satisfactory recoveries (86.8 % â¼ 109.9 %). Especially, we applied this method to the detection of AAAOPs in meat samples and conducted a preliminarily study on its formation rules, which provides a reliable basis for assessing potential dietary risks.
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Aminoácidos Aromáticos , Oxidación-Reducción , Extracción en Fase Sólida , Extracción en Fase Sólida/métodos , Aminoácidos Aromáticos/química , Aminoácidos Aromáticos/análisis , Aminoácidos Aromáticos/aislamiento & purificación , Espectrometría de Masas en Tándem , Estructuras Metalorgánicas/química , Calor , Contaminación de Alimentos/análisis , Cromatografía Líquida de Alta Presión , Animales , Adsorción , Carne/análisis , Alimentos ProcesadosRESUMEN
AIMS: This study aims to develop and validate an optimal model for predicting worsening heart failure (WHF). Multiple machine learning (ML) algorithms were compared, and the results were interpreted using SHapley Additive exPlanations (SHAP). A clinical risk calculation tool was subsequently developed based on these findings. METHODS AND RESULTS: This nested case-control study included 200 patients with chronic heart failure (CHF) from the China-Japan Friendship Hospital (September 2019 to December 2022). Sixty-five variables were collected, including basic information, physical and chemical examinations, and quality of life assessments. WHF occurrence within a 3-month follow-up was the outcome event. Variables were screened using LASSO regression, univariate analysis, and comparison of key variables in multiple ML models. Eighty per cent of the data was used for training and 20% for testing. The best models were identified by integrating nine ML algorithms and interpreted using SHAP, and to develop a final risk calculation tool. Among participants, 68 (34.0%) were female, with a mean age (standard deviation, SD) of 68.57 (12.80) years. During the follow-up, 60 participants (30%) developed WHF. N-terminal pro-brain natriuretic peptide (NT-proBNP), creatinine (Cr), uric acid (UA), haemoglobin (Hb), and emotional area score on the Minnesota Heart Failure Quality of Life Questionnaire were critical predictors of WHF occurrence. The random forest (RF) model was the best model to predict WHF with an area under the curve (AUC) (95% confidence interval, CI) of 0.842 (0.675-1.000), accuracy of 0.775, sensitivity of 0.900, specificity of 0.833, negative predictive value of 0.800, and positive predictive value of 0.600 for the test set. SHAP analysis highlighted NT-proBNP, UA, and Cr as significant predictors. An online risk predictor based on the RF model was developed for personalized WHF risk assessment. CONCLUSIONS: This study identifies NT-proBNP, Cr, UA, Hb, and emotional area scores as crucial predictors of WHF in CHF patients. Among the nine ML algorithms assessed, the RF model showed the highest predictive accuracy. SHAP analysis further emphasized NT-proBNP, UA, and Cr as the most significant predictors. An online risk prediction tool based on the RF model was subsequently developed to enhance early and personalized WHF risk assessment in clinical settings.
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Pseudorabies virus is a swine alpha-herpesvirus. We demonstrated that alpha-herpesvirus infection downregulates HSF1, a master transcription factor in the heat shock response. The serine/threonine protein kinase activity of late viral protein UL13 is indispensable for HSF1 depletion and phosphorylation, and UL13 does not degrade HSF1 posttranslationally but inhibits the HSF1 mRNA level. Importantly, UL13 increased HSF1 activity even though it reduced HSF1 mRNA. Furthermore, viral replication markedly decreased in the HSF1 knockout cell line or in the presence of an HSF1-specific inhibitor. Interestingly, HSF1 knockout accelerated the activation of NF-κB and p38MAPK. The K96 loci of UL13 are important to induce high levels of IL-6, TNF-α, and IL-ß cytokines while playing a crucial role in promoting mild interstitial pneumonia, liver necrosis, and severe inflammatory cell infiltration in the footpad. Thus, UL13 steers the heat shock response to promote viral replication and the inflammatory response. IMPORTANCE: PRV is a ubiquitous pathogen that infects a variety of mammals, such as pigs, ruminants, carnivores, and rodents as well as human beings, causing enormous economic losses in the swine industry. Here, we employed PRV as a model to determine the relationship between α-herpesvirus and the inflammatory response. Overall, our findings indicated that PRV infection inhibits the level of HSF1 mRNA via the serine/threonine protein kinase activity of UL13. Additionally, we discovered that HSF1 was involved in NF-κB activation upon PRV infection. PRV UL13 orchestrates the level of HSF1 mRNA, HSF1 protein phosphorylation, and priming of the inflammatory response. Our study reveals a novel mechanism employed by UL13 serine/threonine protein kinase activity to promote the inflammatory response, providing novel clues for therapy against alpha-herpesvirus infection.
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PURPOSE: More than 80% of patients with moderate to severe obstructive sleep apnea (OSA) are still not diagnosed timely. The prediction model based on random forest (RF) algorithm was established by using heart rate variability (HRV), clinical and demographic features so as to screen for the patients with high risk of moderate and severe obstructive sleep apnea. METHODS: The sleep monitoring data of 798 patients were randomly divided into training set (n = 558) and test set (n = 240) in 7:3 proportion. Grid search was applied to determine the best parameters of the RF model. 10-fold cross validation was utilized to evaluate the predictive performance of the RF model, which was then compared to the performance of the Logistic regression model. RESULTS: Among the 798 patients, 638 were males and 160 were females, with the average age of 43.51 years old and the mean body mass index (BMI) of 25.92 kg/m2. The sensitivity, specificity, accuracy, F1 score and the area under receiver operating characteristic curve for RF model and Logistic regression model were 94.68% vs. 73.94%; 73.08% vs. 86.54%; 90.00% vs. 76.67%; 0.94 vs. 0.83 and 0.83 vs. 0.80 respectively. CONCLUSIONS: The RF prediction model can effectively distinguish patients with moderate to severe OSA, which is expected to carry out in a large-scale population in order to screening for high-risk patients, and helps to evaluate the effect of OSA treatment continuously.
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Malignant melanoma is a rare malignant tumor that can occur in many parts of the body. Primary vaginal malignant melanoma (PVMM) in women accounts for only 3%-7% of all malignant melanomas. PVMM is extremely rare, aggressive, and has a poor prognosis. We report a case of primary vaginal malignant melanoma in order to improve our understanding of the disease.
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Achieving the clinically staged treatment of osteosarcoma-associated bone defects encounters the multiple challenges of promptly removing postoperative residual tumor cells and bacterial infection, followed by bone reconstruction. Herein, a core/shell hydrogel with multiple-effect combination is designed to first exert antitumor and antibacterial activities and then promote osteogenesis. Specifically, doxorubicin (DOX) is loaded by magnesium-iron-based layered double hydroxide (LDH) to prepare LDOX, which is introduced into a thermo-sensitive hydrogel to serve as an outer shell of the core/shell hydrogel, meanwhile, LDH-contained liquid crystal hydrogel, abbreviated as LCgel-L, is served as an inner core. At the early stage of treatment, the dissociation of the outer shell triggered by moderate hyperthermia led to the thermo-sensitive release of LDOX, which can be targeted for the release of DOX within tumor cells, thereby promptly removing postoperative residual tumor cells based on the synergistic effect of photothermal therapy (PTT) and DOX, and postoperative bacterial infection can also be effectively prevented by PTT simultaneously. More importantly, the dissociation of the outer shell prompted the full exposure of the inner core, which will exert osteogenic activity based on the synergy of liquid crystal hydrogel as well as LDH-induced mild hyperthermia and ion effects, thereby enabling "temporal regulation" treatment of osteosarcoma-associated bone defects. This study provides a valuable insight for the development of osteosarcoma-associated bone repair materials.
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OBJECTIVE: The E3 ubiquitin ligase is well recognized as a significant contributor to glioblastoma (GBM) progression and has promise as a prospective therapeutic target. This study explores the contribution of E3 ubiquitin ligase RNF122 in the GBM progression and the related molecular mechanisms. METHODS: RNF122 expression levels were evaluated using qRT-PCR, WB, and IHC, while functional assays besides animal experiments were used to assess RNF122's effect on GBM progression. We also tested the RNF122 impact on JAK2/STAT3/c-Myc signaling using WB. RESULTS: RNF122 was upregulated in GBM and correlated to the advanced stage and poor clinical outcomes, representing an independent prognostic factor. Based on functional assays, RNF122 promotes GBM growth and cell cycle, which was validated further in subsequent analyses by JAK2/STAT3/c-Myc pathway activation. Moreover, JAK2/STAT3 signaling pathway inhibitor WP1066 can weaken the effect of overexpression RNF122 on promoting GBM progression. CONCLUSION: Our results revealed that RNF122 caused an aggressive phenotype to GBM and was a poor prognosticator; thus, targeting RNF122 may be effectual in GBM treatment.
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Neoplasias Encefálicas , Glioblastoma , Janus Quinasa 2 , Proteínas Proto-Oncogénicas c-myc , Factor de Transcripción STAT3 , Transducción de Señal , Ubiquitina-Proteína Ligasas , Humanos , Glioblastoma/metabolismo , Glioblastoma/patología , Janus Quinasa 2/metabolismo , Factor de Transcripción STAT3/metabolismo , Ubiquitina-Proteína Ligasas/metabolismo , Ubiquitina-Proteína Ligasas/genética , Proteínas Proto-Oncogénicas c-myc/metabolismo , Proteínas Proto-Oncogénicas c-myc/genética , Transducción de Señal/fisiología , Transducción de Señal/efectos de los fármacos , Masculino , Neoplasias Encefálicas/metabolismo , Neoplasias Encefálicas/patología , Neoplasias Encefálicas/genética , Femenino , Animales , Línea Celular Tumoral , Ratones Desnudos , Persona de Mediana Edad , Ratones , Proliferación Celular/efectos de los fármacos , Proliferación Celular/fisiología , Ratones Endogámicos BALB C , Péptidos y Proteínas de Señalización IntracelularRESUMEN
AIMS: Narrative nursing (NN) is a crucial component of modern medical humanistic care. It involves utilising storytelling as a means to guide nurses in devising future interventions for patients, and help patients in reconstructing positive psychological defences. The willingness of clinical nurses to engage in narrative nursing holds significant implications for both effective communication and the overall quality of care. However, there is limited knowledge regarding clinical nurses' willingness to engage in narrative nursing. This study aims to investigate the participation willingness of Chinese nurses, identify its predictors and explore its corresponding reasons. DESIGN: A cross-sectional study. METHODS: Clinical nurses were enrolled in Hunan province, Central South, China, and a convenience sampling strategy was used. A structured questionnaire was distributed to clinical nurses by an online survey platform. Information on sociodemographic characteristics, willingness and possible influencing factors (experience, ability, perceptions on narrative nursing) was collected. Binary logistic regression was conducted to identify the predictors of willingness to participate in narrative nursing. RESULTS: A total of 2310 nurses were recruited, of which 2092 nurses completed the questionnaire (response rate: 90.6%). One thousand seven hundred and thirty-four nurses (82.9%) were willing to participate in NN, and 358 (17.1%) were not. Binary logistic regression analysis identified nine predictors of participants' willingness to participate, including working departments, professional title, working position, experience of received mobilisation and training of NN, understanding of related knowledge, NCS level, affirmation of NN and positive attitude towards clinical application (all p values < 0.05). These indicators explained 17.1% of the variances in the dependent variable (p < 0.001). CONCLUSION: A high proportion of nurses in Hunan province were willing to practice in clinic using NN. Willingness to participate may be increased by a focus on nurses with low professional titles, no administrative position and working in specialised departments, such as emergency departments, infectious departments, critical care units and operating theatres. IMPACT: The study identified a high proportion of nurses in Hunan Province who were willing to use NN. However, the figure was slightly lower than expected. Influencing factors were analysed to give insights for managers to develop more effective NN outreach programs. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution.
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Objective To investigate the current status of physical activity and depressive symptoms among middle-aged and older adults in Chengdu,Sichuan and explore the relationship between physical activity and depressive symptoms. Methods Multi-stage proportional stratified random sampling was employed to select middle-aged and older adults aged ≥45 years as the participants,and face-to-face interviews were carried out to collect data.Logistic regression was adopted to explore the relationship between physical activity and depressive symptoms in middle-aged and older adults.The trend test was performed for the relationship between different levels of physical activity and depressive symptoms.The subgroup analysis and the test for multiplicative interactions were conducted for the relationship between physical activity and depressive symptoms. Results A total of 4376 middle-aged and older adults were included.Among them,14.58% (638/4376),25.98% (1137/4376),and 27.83% (1218/4376) had depressive symptoms,failed to reach the guideline-recommended standards of physical activity,and were at low levels of physical activity,respectively.There was a negative association between reaching guideline-recommended physical activity standard and depressive symptoms in middle-aged and older adults (OR=0.713,95%CI=0.589-0.861,P<0.001).In addition,moderate levels (OR=0.714,95%CI=0.586-0.871,P=0.001) and high levels of physical activity (OR=0.705,95%CI=0.548-0.906,P=0.006) had negative associations with the presence of depressive symptoms.The trend test revealed that the negative association between physical activity and depressive symptoms in middle-aged and older adults enhanced as the level of physical activity increased (Pfor trend=0.001).The subgroup analysis and the test for multiplicative interactions revealed that neither reaching guideline-recommended physical activity standards or not nor the physical activity level had an interaction with each of the subgroups (all Pfor interaction>0.05). Conclusion The current status of depressive symptoms among middle-aged and older adults in Chengdu,Sichuan needs to be ameliorated.A negative association existed between reaching the guideline-recommended physical activity standard and presence of depressive symptoms,and the negative association enhanced as the physical activity level elevated.
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Depresión , Humanos , Depresión/epidemiología , Depresión/psicología , Anciano , China/epidemiología , Persona de Mediana Edad , Masculino , Femenino , Ejercicio Físico , Actividad Motora , Anciano de 80 o más AñosRESUMEN
This study utilized data from 140,294 prostate cancer cases from the Surveillance, Epidemiology, and End Results (SEER) database. Here, 10 different machine learning algorithms were applied to develop treatment options for predicting patients with prostate cancer, differentiating between surgical and non-surgical treatments. The performances of the algorithms were measured using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, positive predictive value, negative predictive value. The Shapley Additive Explanations (SHAP) method was employed to investigate the key factors influencing the prediction process. Survival analysis methods were used to compare the survival rates of different treatment options. The CatBoost model yielded the best results (AUC = 0.939, sensitivity = 0.877, accuracy = 0.877). SHAP interpreters revealed that the T stage, cancer stage, age, cores positive percentage, prostate-specific antigen, and Gleason score were the most critical factors in predicting treatment options. The study found that surgery significantly improved survival rates, with patients undergoing surgery experiencing a 20.36% increase in 10-year survival rates compared with those receiving non-surgical treatments. Among surgical options, radical prostatectomy had the highest 10-year survival rate at 89.2%. This study successfully developed a predictive model to guide treatment decisions for prostate cancer. Moreover, the model enhanced the transparency of the decision-making process, providing clinicians with a reference for formulating personalized treatment plans.
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The evolutionary dynamics of cancer, characterized by its profound heterogeneity, demand sophisticated tools for a holistic understanding. This review delves into tumor phylogenetics, an essential approach bridging evolutionary biology with oncology, offering unparalleled insights into cancer's evolutionary trajectory. We provide an overview of the workflow, encompassing study design, data acquisition, and phylogeny reconstruction. Notably, the integration of diverse data sets emerges as a transformative step, enhancing the depth and breadth of evolutionary insights. With this integrated perspective, tumor phylogenetics stands poised to redefine our understanding of cancer evolution and influence therapeutic strategies.
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To investigate the dispersion process of the underground toxic gas carbon monoxide (CO) into the refuge chamber during a mine disaster and enhance the survival rate of trapped miners, a simplified model of an underground refuge chamber and the main roadway was constructed. The impact of temperature and pressurized air volume on CO dispersion into the refuge chamber has been examined through both analog experiments and numerical simulations, and the reliability of the simulation results was verified. The results indicate that CO dispersion into the refuge chamber through the top of the protective isolation door occurs when the temperature in the refuge chamber is lower than that of the toxic gas. When the temperature of the toxic gas is higher, it tends to enter the refuge chamber through the bottom of the protective isolation door. The evolution of CO concentration in the transition chamber can be divided toxic survival chamber can be categorized into a sudden decline stage and a stable stage. And a flexible isolation door designed to control the entry of toxic gases into the refuge chamber was implemented, and its impact on CO dispersion has been compared and analyzed. When the temperature of the main roadway is 50 °C and the temperature of the refuge chamber is 20 °C, the required pressurized air volume to maintain the CO concentration within the safe threshold (24 ppm) is reduced to 69.6% of that needed without the isolation door, thereby significantly reducing the infiltration of harmful gases from the main roadway into the refuge chamber.
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Background: Research has demonstrated that radiomics models are capable of forecasting the characteristics of lung cancer. Nevertheless, due to radiomics' poor interpretability, its applicability in clinical settings remains restricted. This investigation sought to verify the correlation between radiomics features (RFs) and the biological behavior of clinical stage IA adenocarcinomas. Methods: A retrospective analysis was conducted on patients diagnosed with clinical stage IA lung adenocarcinoma who underwent resection between May 2005 and December 2018. Detailed radiomics examination of the primary tumor was carried out utilizing preoperative computed tomography (CT) images. Subsequently, patients were grouped based on their RFs using consensus clustering, enabling comparison of tumor biological characteristics among the clusters. Survival disparities among the clusters were evaluated through Kaplan-Meier and Cox analyses. Results: A consensus cluster analysis was performed on 669 patients [median age, 58 years; interquartile range (IQR), 50-64 years, 257 males, 412 females], and three distinct clusters were identified. Cluster 2 was associated with radiological solid adenocarcinoma [119 of 324 (36.7%), P<0.001], larger tumors with median tumor size of 2.1 cm with IQR of 1.7 to 2.5 cm (P<0.001), central tumor [91 of 324 (28.1%), P=0.002], pleural invasion [87 of 324 (26.9%), P<0.001], occult lymph node metastasis (ONM) [106 of 324 (32.7%), P<0.001], and a higher frequency of metastasis or recurrence [62 of 324 (19.1%), P<0.001]. The frequency of histological grade 3 was the highest in Cluster 3 [8 of 34 (23.5%), P<0.001]. Cluster 1 was associated with pure ground glass nodules (pGGNs) [184 of 310 (59.4%), P<0.001], smaller tumors with median tumor size of 1.1 cm with IQR of 0.8 to 1.4 cm (P<0.001), no pleural invasion [276 of 310 (89.0%), P<0.001], histological grade 1 [114 of 248 (46.0%), P<0.001], ONM negative [292 of 310 (94.2%), P<0.001], and a lower rate of metastasis or recurrence [298 of 310 (96.1%), P<0.001]. Conclusions: Differences in tumor biological behavior were detected among consensus clusters based on the RFs of clinical stage IA adenocarcinoma.
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Background: Hirschsprung's disease (HSCR) is a complex congenital neurodevelopmental disorder affecting colons caused by both genetic and environmental factors. Although several genes have been identified as contributing factors in HSCR, the pathogenesis is still largely unclear, especially for the low prevalent long-segment HSCR (L-HSCR). Gap junction protein alpha 8 (GJA8) is involved in several physiological processes and has been implicated in several diseases. However, the relationship between GJA8 single nucleotide polymorphism (SNP) rs17160783 and HSCR in the southern Chinese population remains unknown. The study aimed to explore the association of genetic variants in GJA8 and HSCR susceptibility in southern Chinese. Methods: SNP rs17160783 A>G in GJA8 was genotyped by TaqMan SNP Genotyping Assay in all samples, which included 1,329 HSCR children (cases) and 1,473 healthy children (controls). Odds ratio (OR) and 95% confidence interval (CI) were used to evaluate the association of GJA8 polymorphisms with HSCR susceptibility. The GTEx database and transcription factor binding site (TFBS) prediction were used to analyze the potential regulatory function of rs17160783. Results: Genetic association analysis illustrated that rs17160783 could increase the risk of L-HSCR (Padj=0.04, ORadj =1.48, 95% CI: 1.02-2.14). We also found that GJA8 expression was increased in HSCR and neurodevelopmentally impaired animal models. External epigenetic data revealed that GJA8 rs17160783 may have the potential to regulate the expression of the GJA8, possibly by altering the binding of transcription factors for GJA8, and consequently impacting the PI3K-Akt signaling pathway during the enteric nervous system (ENS) development. Conclusions: Our results suggested that rs17160783 might play a regulatory role in GJA8 expression and increase the susceptibility of L-HSCR in children from southern China.
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Rationale: Neovascular ocular diseases (NODs) represent the leading cause of visual impairment globally. Despite significant advances in anti-angiogenic therapies targeting vascular endothelial growth factor (VEGF), persistent challenges remain prevalent. As a proof-of-concept study, we herein demonstrate the effectiveness of targeted degradation of VEGF with bispecific aptamer-based lysosome-targeting chimeras (referred to as VED-LYTACs). Methods: VED-LYTACs were constructed with three distinct modules: a mannose-6-phosphate receptor (M6PR)-binding motif containing an M6PR aptamer, a VEGF-binding module with an aptamer targeting VEGF, and a linker essential for bridging and stabilizing the two-aptamer structure. The degradation efficiency of VED-LYTACs via the autophagy-lysosome system was examined using an enzyme-linked immunosorbent assay (ELISA) and immunofluorescence staining. Subsequently, the anti-angiogenic effects of VED-LYTACs were evaluated using in vitro wound healing assay, tube formation assay, three-dimensional sprouting assay, and ex vivo aortic ring sprouting assay. Finally, the potential therapeutic effects of VED-LYTACs on pathological retinal neovascularization and vascular leakage were tested by employing mouse models of NODs. Results: The engineered VED-LYTACs promote the interaction between M6PR and VEGF, consequently facilitating the translocation and degradation of VEGF through the lysosome. Our data show that treatment with VED-LYTACs significantly suppresses VEGF-induced angiogenic activities both in vitro and ex vivo. In addition, intravitreal injection of VED-LYTACs remarkably ameliorates abnormal vascular proliferation and leakage in mouse models of NODs. Conclusion: Our findings present a novel strategy for targeting VEGF degradation with an aptamer-based LYTAC system, effectively ameliorating pathological retinal angiogenesis. These results suggest that VED-LYTACs have potential as therapeutic agents for managing NODs.
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Aptámeros de Nucleótidos , Lisosomas , Neovascularización Retiniana , Factor A de Crecimiento Endotelial Vascular , Animales , Aptámeros de Nucleótidos/farmacología , Factor A de Crecimiento Endotelial Vascular/metabolismo , Ratones , Neovascularización Retiniana/tratamiento farmacológico , Neovascularización Retiniana/metabolismo , Humanos , Lisosomas/metabolismo , Lisosomas/efectos de los fármacos , Células Endoteliales de la Vena Umbilical Humana , Ratones Endogámicos C57BL , Modelos Animales de Enfermedad , Inhibidores de la Angiogénesis/farmacología , AngiogénesisRESUMEN
The filamentous fungus Magnaporthe oryzae is widely recognized as a notorious plant pathogen responsible for causing rice blasts. With rapid advancements in molecular biology technologies, numerous regulatory mechanisms have been thoroughly investigated. However, most recent studies have predominantly focused on infection-related pathways or host defence mechanisms, which may be insufficient for developing novel structure-based prevention strategies. A substantial body of literature has utilized cryo-electron microscopy and X-ray diffraction to explore the relationships between functional components, shedding light on the identification of potential drug targets. Owing to the complexity of protein extraction and stochastic nature of crystallization, obtaining high-quality structures remains a significant challenge for the scientific community. Emerging computational tools such as AlphaFold for structural prediction, docking for interaction analysis, and molecular dynamics simulations to replicate in vivo conditions provide novel avenues for overcoming these challenges. In this review, we aim to consolidate the structural biological advancements in M. oryzae, drawing upon mature experimental experiences from other species such as Saccharomyces cerevisiae and mammals. We aim to explore the potential of protein construction to address the invasion and proliferation of M. oryzae, with the goal of identifying new drug targets and designing small-molecule compounds to manage this disease.
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Proteínas Fúngicas , Oryza , Enfermedades de las Plantas , Oryza/microbiología , Enfermedades de las Plantas/microbiología , Proteínas Fúngicas/química , Proteínas Fúngicas/genética , Proteínas Fúngicas/metabolismo , Ascomicetos/genética , Ascomicetos/patogenicidad , Ascomicetos/química , Microscopía por CrioelectrónRESUMEN
Background: Targeted therapy with neoadjuvant chemotherapy for patients with human epidermal growth factor receptor 2 (HER2)-positive breast cancer has increased the rates of pathological complete response (pCR) and breast preservation surgery and improved the overall disease-free survival rate. This study aimed to determine whether tumor enhancement and shrinkage patterns in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) can predict the efficacy of targeted therapy in patients with HER2-positive breast cancer and differentiate pCR from non-pCR. Methods: The data of 64 patients with HER2-positive breast cancer who received targeted therapy prior to surgery were retrospectively collected. All patients had complete postoperative pathological data. The pretreatment evaluation of the tumor enhancement pattern and the shrinkage pattern after two treatment cycles were assessed. The difference in the enhancement and shrinkage patterns between the pCR and non-pCR groups was evaluated via the χ2 test. Logistic regression analysis was used to assess the value of enhancement and shrinkage patterns for predicting pCR in patients with HER2-positive breast cancer. Results: There were statistically significant differences in tumor size, estrogen receptor (ER) status, lymph node metastasis, enhancement pattern, and shrinkage pattern between the pCR and non-pCR cases. Patients with a tumor size ≤20 mm were likely to achieve pCR. ER status, lymph node metastasis, and enhancement and shrinkage patterns each had good precision for predicting pCR, and the combination of enhancement and shrinkage patterns had the highest prediction accuracy. Multivariate logistic regression analysis indicated that only enhancement pattern had a significant predictive value. Conclusions: Among patients with HER2-positive breast cancer, those with tumor size ≤20 mm, ER-negative status, no lymph node metastases, and mass enhancement and concentric shrinkage patterns are more likely to achieve pCR. Mass enhancement combined with concentric shrinkage had the highest accuracy in predicting pCR, indicating that preoperative imaging may be useful for guiding clinical decisions regarding targeted treatments.
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BACKGROUD: Supernatants from various cytological samples, including body cavity effusion, sputum, bronchoalveolar lavage fluid (BALF), and needle aspiration, have been validated for detecting genetic alterations using cell-free DNA (cfDNA) in patients with non-small cell lung cancer (NSCLC). However, the sensitivity of fusion variations detection remains challenging. The protection of cell-free RNA (cfRNA) is critical for resolving the issue. METHODS: A protective solution (PS) was applied for preserving cfRNA in cytological supernatant (CS), and the quality of protected cfRNA was assessed by cycle threshold (CT) values from reverse transcription quantitative polymerase chain reaction (RT-qPCR). Furthermore, we collected an additional set of malignant cytological and matched tumor samples from 84 NSCLC patients, cfDNA & cfRNA extraction and double detection for driver gene mutations was validated using the multi-gene mutations detection by RT-qPCR. RESULTS: Under the optimal protection system, 91.0% (101/111) of cfRNA were protected effectively. Among the 84 NSCLC patient samples, seven cytological samples failed the tests. In comparison with tumor samples, the overall sensitivity and specificity of detecting driver genes of supernatant cfDNA and cfRNA were 93.8% (74/77) and 100% (77/77), respectively. Notably, when focusing exclusively on patients with fusion gene changes, both sensitivity and specificity reached 100% (11/11) for EML4-ALK, ROS1, RET fusions, and MET ex14 skipping. CONCLUSION: These findings suggest that cfDNA & cfRNA extraction and double detection strategy recommended in this study improve the accuracy of driver genes mutations test, especially for RNA-based assay.