RESUMEN

Alcohol-related cognitive impairment (ARCI) is highly prevalent among patients with alcohol abuse and dependence. The pathophysiology of ARCI, pivotal for refined therapeutic approaches, is not fully elucidated, posing a risk of progression to severe neurological sequelae such as Korsakoff's syndrome (KS) and Alcohol-Related Dementia (ARD). This study ventures into the underlying mechanisms of chronic alcohol-induced neurotoxicity, notably glutamate excitotoxicity and cytoskeletal disruption, and explores the therapeutic potential of Memantine, a non-competitive antagonist of the N-methyl-d-aspartate (NMDA) receptor known for its neuroprotective effect against excitotoxicity. Our investigation centers on the efficacy of Memantine in mitigating chronic alcohol-induced cognitive and hippocampal damages in vivo. Male C57BL/6J mice were subjected to 30 % (v/v, 6.0 g/kg) ethanol via intragastric administration alongside Memantine co-treatment (10 mg/kg/day, intraperitoneally) for six weeks. The assessment involved Y maze, Morris water maze, and novel object recognition tests to evaluate spatial and recognition memory deficits. Histopathological evaluations of the hippocampus were conducted to examine the extent of alcohol-induced morphological changes and the potential protective effect of Memantine. The findings reveal that Memantine significantly improves chronic alcohol-compromised cognitive functions and mitigates hippocampal pathological changes, implicating a moderating effect on the disassembly of actin cytoskeleton and microtubules in the hippocampus, induced by chronic alcohol exposure. Our results underscore Memantine's capability to attenuate chronic alcohol-induced cognitive and hippocampal morphological harm may partly through regulating cytoskeleton dynamics, offering valuable insights into innovative therapeutic strategies for ARCI.

Asunto(s)

Disfunción Cognitiva , Modelos Animales de Enfermedad , Hipocampo , Memantina , Ratones Endogámicos C57BL , Animales , Memantina/farmacología , Masculino , Ratones , Hipocampo/efectos de los fármacos , Hipocampo/patología , Hipocampo/metabolismo , Disfunción Cognitiva/tratamiento farmacológico , Etanol/toxicidad , Etanol/administración & dosificación , Fármacos Neuroprotectores/farmacología , Fármacos Neuroprotectores/administración & dosificación , Alcoholismo/tratamiento farmacológico , Alcoholismo/patología , Alcoholismo/complicaciones , Aprendizaje por Laberinto/efectos de los fármacos , Antagonistas de Aminoácidos Excitadores/farmacología , Receptores de N-Metil-D-Aspartato/antagonistas & inhibidores , Receptores de N-Metil-D-Aspartato/metabolismo

RESUMEN

Importance: The effect of argatroban in patients with acute ischemic stroke (AIS) and early neurological deterioration (END) is unknown. Objective: To assess the efficacy of argatroban for END in AIS. Design, Setting, and Participants: This open-label, blinded-end point, randomized clinical trial was conducted from April 4, 2020, through July 31, 2022. The date of final follow-up was October 31, 2022. This was a multicenter trial. Eligible patients were adults with AIS who experienced END, which was defined as an increase of 2 or more points on the National Institutes of Health Stroke Scale within 48 hours from symptom onset. Patients who withdrew consent, experienced duplicate randomization, or were lost to follow-up were excluded from the study. Interventions: Patients were randomly assigned to the argatroban group and control group within 48 hours of symptom onset. Both groups received standard therapy based on guidelines, including oral mono or dual antiplatelet therapy. The argatroban group received intravenous argatroban for 7 days (continuous infusion at a dose of 60 mg per day for 2 days, followed by 20 mg per day for 5 days) in addition to standard therapy. Main Outcome and Measure: The primary end point was good functional outcome at 90 days, defined as a modified Rankin Scale score of 0 to 3. Results: A total of 628 patients (mean [SD] age, 65 [11.9] years; 400 male [63.7%]) were included in this study (argatroban group, 314 [50%] and control group, 314 [50%]). Of these, 18 withdrew consent, 1 had duplicate randomization, and 8 were lost to follow-up. A total of 601 patients with stroke were included in the intention-to-treat analysis. Finally, 564 patients were included in the per-protocol analysis as 6 participants in the argatroban group and 31 participants in the control group did not follow the complete protocol. The number of patients with good functional outcome at 90 days was 240 (80.5%) in the argatroban group and 222 (73.3%) in the control group (risk difference, 7.2%; 95% CI, 0.6%-14.0%; risk ratio, 1.10; 95% CI, 1.01-1.20; P = .04). The proportion of symptomatic intracranial hemorrhage was 3 of 317 (0.9%) in the argatroban group and 2 of 272 (0.7%) in the control group (P = .78). Conclusions and Relevance: Among patients with AIS with END, treatment with argatroban and antiplatelet therapy resulted in a better functional outcome at 90 days. This trial provided evidence to support the use of argatroban in reducing disability for patients with END. Trial Registration: ClinicalTrials.gov Identifier: NCT04275180.

Asunto(s)

Arginina/análogos & derivados , Accidente Cerebrovascular Isquémico , Accidente Cerebrovascular , Sulfonamidas , Adulto , Humanos , Masculino , Anciano , Accidente Cerebrovascular Isquémico/tratamiento farmacológico , Accidente Cerebrovascular/complicaciones , Accidente Cerebrovascular/tratamiento farmacológico , Ácidos Pipecólicos/uso terapéutico , Ácidos Pipecólicos/efectos adversos , Anticoagulantes/uso terapéutico

RESUMEN

BACKGROUND: Semi-supervised learning has gained popularity in medical image segmentation due to its ability to reduce reliance on image annotation. A typical approach in semi-supervised learning is to select reliable predictions as pseudo-labels and eliminate unreliable predictions. Contrastive learning helps prevent the insufficient utilization of unreliable predictions, but neglecting the anatomical structure of medical images can lead to suboptimal optimization results. PURPOSE: We propose a novel approach for semi-supervised liver segmentation using contrastive learning, which leverages unlabeled data and enhances the suitability of contrastive learning for liver segmentation. METHOD AND MATERIALS: Contrastive learning helps prevent the inappropriate utilization of unreliable predictions, but neglecting the anatomical structure of medical images can lead to suboptimal optimization results. Therefore, we propose a semi-supervised contrastive learning method with local regions self-supervision (LRS2). On one side, we employ Shannon entropy to distinguish between reliable and unreliable predictions and reduce the dissimilarity between their representations within regional artificial units. Within each unit of the liver image, we strongly encourage unreliable predictions to acquire valuable information pertaining to the correct category by leveraging the representations of reliable predictions in their vicinity. On the other side, we introduce a dynamic reliability threshold based on the Shannon entropy of each prediction, gradually evaluating the confidence threshold of reliable predictions as predictive accuracy improves. After selecting reliable predictions, we sequentially apply erosion and dilation to refine them for better selection of qualified positive and negative samples. We evaluate our proposed method on abdominal CT images, including 131 images (train data: 77, validation data: 26, and testing data: 28) from 2017 ISBI Liver Tumors Segmentation Challenge. RESULTS: Our method obtains satisfactory performance in different proportion by exploiting the unreliable predictions. Compared with the result of VNet only under supervised settings (with 10, 30, 50, 70% and full labeled data), LRS2, respectively, brings an improvement of Dice coefficient by +6.11, +3.55, +4.43, and +2.25%, achieving Dice coefficients of 93.44, 93.31, 94.85, and 95.12%, respectively. CONCLUSION: In this study, we carefully select appropriate positive and negative samples from reliable regions, ensuring that anchor pixels within unreliable regions are correctly assigned to their respective categories. With a consideration of the anatomical structure present in CT images, we partition the image representations into regional units, enabling anchor pixels to capture more precise sample information. Extensive experiments confirm the effectiveness of our method.

Asunto(s)

Procesamiento de Imagen Asistido por Computador , Hígado , Aprendizaje Automático Supervisado , Hígado/diagnóstico por imagen , Procesamiento de Imagen Asistido por Computador/métodos , Humanos , Tomografía Computarizada por Rayos X

RESUMEN

Early accurate mammography screening and diagnosis can reduce the mortality of breast cancer. Although CNN-based breast cancer computer-aided diagnosis (CAD) systems have achieved significant results in recent years, precise diagnosis of lesions in mammogram remains a challenge due to low signal-to-noise ratio (SNR) and physiological characteristics. Many researchers achieved excellent performance in detecting mammographic images by inputting region of interest (ROI) annotations while ROI annotations require a great quantity of manual labor, time and resources. We propose a two-stage method that combines images preprocessing and model optimization to address the aforementioned challenges. Firstly, we propose the breast database preprocess (BDP) method to preprocess INbreast then we get INbreast†. The only label we need is benign or malignant label of one mammogram, not manual labeling such as ROI annotations. Secondly, we apply focal loss to ECA-Net50 which is an improved model based on ResNet50 with efficient channel attention (ECA) module. Our method can adaptively extract the key features of mammograms, meanwhile solving the problem of hard-to-classify samples and unbalanced categories. The AUC value of our method on INbreast† is 0.960, accuracy is 0.929, Recall is 0.928. The precision of our method on INbreast† is 0.883 which improved by 0.254 compared to ResNet50. In addition, we use Grad-CAM to visualize the effect of our model. The visualized heatmaps extracted by our method can focus more on lesion regions. Both numerical and visualized experiments demonstrate that our method achieves satisfactory performance.

Asunto(s)

Neoplasias de la Mama , Aprendizaje Automático , Humanos , Femenino , Mamografía/métodos , Redes Neurales de la Computación , Neoplasias de la Mama/diagnóstico por imagen , Neoplasias de la Mama/patología , Diagnóstico por Computador/métodos

RESUMEN

PURPOSE: It plays a significant role to accurately and automatically segment lesions from ultrasound (US) images in clinical application. Nevertheless, it is extremely challenging because distinct components of heterogeneous lesions are similar to background in US images. In our study, a transfer learning-based method is developed for full-automatic joint segmentation of nodular lesions. METHODS: Transfer learning is a widely used method to build high performing computer vision models. Our transfer learning model is a novel type of densely connected convolutional network (SDenseNet). Specifically, we pre-train SDenseNet based on ImageNet dataset. Then our SDenseNet is designed as a multi-channel model (denoted Mul-DenseNet) for automatically jointly segmenting lesions. As comparison, our SDenseNet using different transfer learning is applied to segmenting nodules, respectively. In our study, we find that more datasets for pre-training and multiple pre-training do not always work in segmentation of nodules, and the performance of transfer learning depends on a judicious choice of dataset and characteristics of targets. RESULTS: Experimental results illustrate a significant performance of the Mul-DenseNet compared to that of other methods in the study. Specially, for thyroid nodule segmentation, overlap metric (OM), dice ratio (DR), true-positive rate (TPR), false-positive rate (FPR) and modified Hausdorff distance (MHD) are [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text] and [Formula: see text] mm, respectively; for breast nodule segmentation, OM, DR, TPR, FPR and MHD are [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text] and [Formula: see text] mm, respectively. CONCLUSIONS: The experimental results illustrate our transfer learning models are very effective in segmentation of lesions, which also demonstrate that it is potential of our proposed Mul-DenseNet model in clinical applications. This model can reduce heavy workload of the physicians so that it can avoid misdiagnosis cases due to excessive fatigue. Moreover, it is easy and reproducible to detect lesions without medical expertise.

Asunto(s)

Mama , Nódulo Tiroideo , Humanos , Procesamiento de Imagen Asistido por Computador , Aprendizaje Automático , Ultrasonografía

RESUMEN

Fast calculation or simulation of the ablation zone induced by radiofrequency ablation (RFA) has a critical role in hepatic RFA planning and therapy. However, it remains challenging to approximate the ablation zone in real time, especially when more than one probe is involved in one ablation session. This paper presents a novel computational technique to calculate the 3D ablation zone of one probe RFA and two-probe switching RFA. The main idea is to get an approximate solution of the temperature distribution from a simplified Pennes bioheat equation, and further fit the solution to the coagulation measurements on ex vivo porcine liver. With a closed-form solution of temperature distribution, the calculation of the ablation zone is as simple as the commonly used ellipsoidal model, but it allows a more realistic prediction of combined ablation zones with different inter-probe spacing. The new approximation technique could potentially replace the original ellipsoidal model in the intervention planning step.

Asunto(s)

Ablación por Catéter/métodos , Conductividad Térmica , Animales , Coagulación Sanguínea , Simulación por Computador , Hígado/fisiología , Hígado/cirugía , Porcinos , Factores de Tiempo

RESUMEN

BACKGROUND: Indoleamine 2,3-dioxygenase 1 (IDO1) is a critical regulator of T cell function, contributing to immune tolerance. Upregulation of IDO1 has been found in many cancer types; however, the regulatory mechanisms and clinical significance of IDO1 in colon cancer are still unclear. Here, we investigated the role of dysregulated microRNA (miRNA) targeting IDO1 in the colon cancer microenvironment. METHODS: We elucidated IDO1 function by performing cell-based assays and establishing transplanted tumor models in BALB/c mice and BALB/c nude mice. We evaluated IDO1 protein expression by immunohistochemistry (IHC) in a tissue microarray (TMA) and analyzed IDO1 mRNA expression with The Cancer Genome Atlas (TCGA). We screened miRNAs targeting IDO1 by using a dual luciferase reporter assay. We tested the function of microRNA-448 (miR-448) by using western blotting (WB) and fluorescence-activated cell sorting (FACS). RESULTS: We demonstrated that stable IDO1 overexpression enhanced xenograft tumor growth in BALB/c mice but not in BALB/c nude mice. We also revealed the involvement of posttranscriptional regulation of IDO1 in colon cancer by observing IDO1 protein levels and mRNA levels. Furthermore, ectopic expression of miRNA mimics suggested that miR-448 could significantly downregulate IDO1 protein expression. Notably, we proved that miR-448 suppressed the apoptosis of CD8+ T cells by suppressing IDO1 enzyme function. CONCLUSION: Our findings indicated that IDO1 suppressed the CD8+ T cell response in colon cancer. miR-448, as a tumor-suppressive miRNA, enhanced the CD8+ T cell response by inhibiting IDO1 expression. The results provide a theoretical basis for the development of new immunotherapy for the treatment of colon cancer.

Asunto(s)

Linfocitos T CD8-positivos/inmunología , Neoplasias del Colon/inmunología , Indolamina-Pirrol 2,3,-Dioxigenasa/inmunología , MicroARNs/inmunología , Animales , Linfocitos T CD8-positivos/metabolismo , Línea Celular Tumoral , Movimiento Celular/fisiología , Neoplasias del Colon/genética , Neoplasias del Colon/metabolismo , Neoplasias del Colon/patología , Células HCT116 , Células HT29 , Xenoinjertos , Humanos , Indolamina-Pirrol 2,3,-Dioxigenasa/antagonistas & inhibidores , Indolamina-Pirrol 2,3,-Dioxigenasa/genética , Indolamina-Pirrol 2,3,-Dioxigenasa/metabolismo , Masculino , Ratones , Ratones Endogámicos BALB C , Ratones Desnudos , MicroARNs/genética , MicroARNs/metabolismo , ARN Mensajero/biosíntesis , ARN Mensajero/genética , Transfección

RESUMEN

A reliable liquid chromatography/tandem mass (LC-MS/MS) method was developed for quantitation of 3', 4'-dimethoxy flavonol-3-ß-d-glucopyranoside (DF3G) in rat plasma using pantoprazole as the internal standard. An Agilent C18 column (100 mm × 3 mm, 3.5 µm) was performed for chromatographic separation with the mobile phase composed of methanol-water (containing formic acid) at a flow rate of 0.4 mL/min. A triple-quadrupole mass spectrometry equipped with an electrospray ionization (ESI) source in positive ion mode was applied to quantitative analysis by multiple reacting monitoring (MRM). The MRM precursor-product ion transition of DF3G and Pantoprazole (IS) were m/z 461.1 → 299.2 and 383.9 → 200.2, respectively. Calibration curves were recovered in a concentration range of 1-500 ng/mL for plasma with a limit of lower quantification (LLOQ) of 1 ng/mL. The intra-day and inter-day precision were not >10%. The accuracy of DF3G ranged from -10% to 0.53% in quality control (QC) samples at three concentrations. DF3G was not degraded during the analysis and the storage period. All the data were validated in accordance with the FDA bioanalytical method validation guideline. The LC-MS/MS method was successfully employed in the pharmacokinetic study of the DF3G after oral administration and intravenous injection in rats.

Asunto(s)

Cromatografía Líquida de Alta Presión/métodos , Flavonoles/sangre , Glucósidos/sangre , Espectrometría de Masas en Tándem/métodos , Animales , Proteínas Sanguíneas , Femenino , Flavonoles/química , Flavonoles/farmacocinética , Glucósidos/química , Glucósidos/farmacocinética , Límite de Detección , Masculino , Ratas , Reproducibilidad de los Resultados , Sensibilidad y Especificidad

RESUMEN

Reduced-gliotoxin is a small molecule derived from the secondary metabolites of marine fungi; compared to other gliotoxin analogues, it exhibits potent anticancer effects. However, the molecular basis of the death of colorectal cancer (CRC) cells induced by reduced-gliotoxin is unclear. Thus, the aim of this study was to investigate the potency of reduced-gliotoxin against CRC cells and to elucidate the underlying mechanisms. Cell morphology, flow cytometric analysis and western bolt analysis were performed to examine the functions and mechanisms of cell death induced by reduced-gliotoxin. Our findings demonstrated that reduced-gliotoxin triggered rapid cell detachment and induced anoikis in CRC cells. Mechanistically, our data indicated that the anoikis induced by reduced-gliotoxin was associated with the disruption of integrin-associated cell detachment and multiple signaling pathways. Furthermore, reduced-gliotoxin induced the excessive production of reactive oxygen species (ROS) and the disruption of mitochondrial membrane potential (MMP), resulting in the activation of both endogenous and exogenous apoptotic pathways and eventually, in the apoptosis of CRC cells. The blockage of ROS generation with N-acetylcysteine (NAC) attenuated the anoikis induced by reduced-gliotoxin. Taken together, these results suggest that reduced-gliotoxin may prove to be a potential candidate in the treatment of CRC.

Asunto(s)

Anoicis/efectos de los fármacos , Antineoplásicos/farmacología , Neoplasias Colorrectales/tratamiento farmacológico , Gliotoxina/farmacología , Especies Reactivas de Oxígeno/metabolismo , Acetilcisteína/farmacología , Antineoplásicos/química , Antineoplásicos/uso terapéutico , Neoplasias Colorrectales/patología , Gliotoxina/química , Gliotoxina/uso terapéutico , Células HCT116 , Células HT29 , Humanos , Potencial de la Membrana Mitocondrial/efectos de los fármacos , Mitocondrias/efectos de los fármacos , Mitocondrias/fisiología , Transducción de Señal/efectos de los fármacos

RESUMEN

PEAK1 is upregulated in multiple human malignancies and has been associated with tumor invasion and metastasis, but little is known about the role of PEAK1 in colorectal cancer (CRC) progression. We investigated the expression pattern, function and regulatory mechanisms of PEAK1 in CRC. Here, we found that PEAK1 is overexpressed in CRC tissues and that high PEAK1 expression predicts poor survival in colon cancer but not rectal cancer. Functionally, silencing PEAK1 inhibits cell proliferation, migration, and invasion in vitro and inhibits the growth of tumor xenografts in nude mice. Mechanistic studies revealed that PEAK1 is induced by epidermal growth factor receptor (EGFR) signaling and that PEAK1 is required for KRas-induced CRC cell growth and metastasis. Furthermore, we demonstrated that miR-181d directly targets PEAK1. Ectopic expression of miR-181d reduces the expression of PEAK1 and inhibits the growth and metastasis of CRC cells in vitro. Clinically, miR-181d is downregulated in CRC samples, and low miR-181d is correlated with poor patient survival. Our study demonstrates the importance of PEAK1 in CRC progression and suggests a potential mechanism by which increasing PEAK1 expression in CRC might be the result of EGFR/KRas signal activation and consequent miR-181d repression.

Asunto(s)

Neoplasias Colorrectales/enzimología , MicroARNs/metabolismo , Proteínas Tirosina Quinasas/metabolismo , Proteínas Proto-Oncogénicas p21(ras)/metabolismo , Animales , Células CACO-2 , Movimiento Celular , Proliferación Celular , Neoplasias Colorrectales/genética , Neoplasias Colorrectales/mortalidad , Neoplasias Colorrectales/patología , Receptores ErbB/genética , Receptores ErbB/metabolismo , Femenino , Regulación Enzimológica de la Expresión Génica , Regulación Neoplásica de la Expresión Génica , Células HCT116 , Células HT29 , Humanos , Masculino , Ratones Desnudos , MicroARNs/genética , Persona de Mediana Edad , Invasividad Neoplásica , Proteínas Tirosina Quinasas/genética , Proteínas Proto-Oncogénicas p21(ras)/genética , Transducción de Señal

RESUMEN

5-fluorouracil (5-FU)-based chemotherapy is the main chemotherapeutic approach for colorectal cancer (CRC) treatment. Because chemoresistance occurs frequently and significantly limits CRC therapies, a novel agent is needed. Pseudolaric acid B (PAB), a small molecule derived from the Chinese medicinal herb ''Tujinpi'', exhibits strong cytotoxic effects on a variety of cancers. However, the detailed mechanisms by which PAB inhibits CRC cell growth and its potential role in overcoming 5-FU resistance have not been well studied. In this study, we showed that PAB significantly inhibited the viability of various CRC cell lines but induced minor cytotoxicity in normal cells. Both the in vitro and in vivo results showed that PAB induced proliferation inhibition, mitotic arrest and subsequently caspase-dependent apoptosis in both 5-FU-sensitive and -resistant CRC cells. Moreover, PAB was shown to interfere with CRC cell mitotic spindle apparatus and activate the spindle assembly checkpoint. Finally, CDK1 activity was involved in PAB-induced mitotic arrest and apoptosis in CRC cells. Taken together, these data reveal that PAB induces CRC cell mitotic arrest followed by apoptosis and overcomes 5-FU resistance in vitro and in vivo, suggesting that PAB may be a potential agent for CRC treatment, particularly for 5-FU-resistant CRC.

Asunto(s)

Antimetabolitos Antineoplásicos/farmacología , Antineoplásicos Fitogénicos/farmacología , Apoptosis/efectos de los fármacos , Neoplasias Colorrectales/tratamiento farmacológico , Diterpenos/farmacología , Resistencia a Antineoplásicos , Fluorouracilo/farmacología , Mitosis/efectos de los fármacos , Animales , Proteína Quinasa CDC2 , Caspasas/metabolismo , Proliferación Celular/efectos de los fármacos , Neoplasias Colorrectales/metabolismo , Neoplasias Colorrectales/patología , Quinasas Ciclina-Dependientes/metabolismo , Relación Dosis-Respuesta a Droga , Células HCT116 , Células HT29 , Humanos , Puntos de Control de la Fase M del Ciclo Celular/efectos de los fármacos , Ratones , Ratones Endogámicos BALB C , Ratones Desnudos , Transducción de Señal/efectos de los fármacos , Huso Acromático/efectos de los fármacos , Huso Acromático/metabolismo , Huso Acromático/patología , Factores de Tiempo , Carga Tumoral/efectos de los fármacos , Ensayos Antitumor por Modelo de Xenoinjerto

RESUMEN

A method incorporating double-wavelength ultra high performance liquid chromatography with quadrupole time-of-flight mass spectrometry was developed for the investigation of the chemical fingerprint of Ganmaoling granule. The chromatographic separations were performed on an ACQUITY UPLC HSS C18 column (2.1 × 50 mm, 1.8 µm) at 30°C using gradient elution with water/formic acid (1%) and acetonitrile at a flow rate of 0.4 mL/min. A total of 11 chemical constituents of Ganmaoling granule were identified from their molecular weight, UV spectra, tandem mass spectrometry data, and retention behavior by comparing the results with those of the reference standards or literature. And 25 peaks were selected as the common peaks for fingerprint analysis to evaluate the similarities among 25 batches of Ganmaoling granule. The results of principal component analysis and orthogonal projection to latent structures discriminant analysis showed that the important chemical markers that could distinguish the different batches were revealed as 4,5-di-O-caffeoylquinic acid, 3,5-di-O-caffeoylquinic acid, and 4-O-caffeoylquinic acid. This is the first report of the ultra high performance liquid chromatography chemical fingerprint and component identification of Ganmaoling granule, which could lay a foundation for further studies of Ganmaoling granule.

Asunto(s)

Cromatografía Líquida de Alta Presión/métodos , Medicamentos Herbarios Chinos/química , Espectrometría de Masas/métodos , Estándares de Referencia