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Transplant patients face an elevated risk of coronavirus disease 2019 (COVID-19) morbidity and mortality and commonly encounter renal dysfunction. Nirmatrelvir is primarily excreted through the kidneys. The dosage of nirmatrelvir/ritonavir (NR) needs to be adjusted according to the degree of renal function impairment. Nevertheless, NR is not recommended for patients with severe renal impairment (estimated glomerular filtration rate < 30 mL/min) due to a dearth of associated research. In this study, we focus on kidney transplant patients and document and analyze the experiences of using NR in individuals with severe kidney dysfunction. This was a retrospective multicenter study that included transplant recipients hospitalized for COVID-19 in five major tertiary hospitals in China from December 2022 to June 2023. The outcomes consisted of the disease progression rate by day 28, individual disease progression events, safety outcomes, information on adverse events (AEs), and the blood drug concentrations of immunosuppressants. Data were presented with descriptive statistics. All analyses were performed using SPSS version 22. In total, 40 patients were included in the analysis. Considering the potential interaction between drugs, all patients temporarily discontinued their immunosuppressants during the NR treatment. None of the 32 moderate patients experienced disease progression. However, among the eight patients with critical COVID-19, unfortunately, two of them died. During the medication period, four patients experienced a total of six AEs associated with NR. None of them experienced AEs with a maximum grade of ≥3. Blood drug concentrations of immunosuppressants were monitored in 22 of 40 patients, and the blood drug concentrations of immunosuppressants did not show a significant increase, but some patients experienced lower blood drug concentrations. Our findings supported the use of NR therapy for the treatment of COVID-19 in transplant patients with severe renal insufficiency. A modified dose of NR was well-tolerated.
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COVID-19 , Trasplante de Riñón , Insuficiencia Renal , Humanos , Receptores de Trasplantes , Ritonavir/efectos adversos , Tratamiento Farmacológico de COVID-19 , Riñón , Inmunosupresores/efectos adversos , Progresión de la Enfermedad , Antivirales/efectos adversosRESUMEN
BACKGROUND: To provide a preoperative prediction model for lymph node metastasis in pancreatic cancer patients and provide molecular information of key radiomic features. METHODS: Two cohorts comprising 151 and 54 pancreatic cancer patients were included in the analysis. Radiomic features from the tumor region of interests were extracted by using PyRadiomics software. We used a framework that incorporated 10 machine learning algorithms and generated 77 combinations to construct radiomics-based models for lymph node metastasis prediction. Weighted gene coexpression network analysis (WGCNA) was subsequently performed to determine the relationships between gene expression levels and radiomic features. Molecular pathways enrichment analysis was performed to uncover the underlying molecular features. RESULTS: Patients in the in-house cohort (mean age, 61.3 years ± 9.6 [SD]; 91 men [60%]) were separated into training (n = 105, 70%) and validation (n = 46, 30%) cohorts. A total of 1,239 features were extracted and subjected to machine learning algorithms. The 77 radiomic models showed moderate performance for predicting lymph node metastasis, and the combination of the StepGBM and Enet algorithms had the best performance in the training (AUC = 0.84, 95% CI = 0.77-0.91) and validation (AUC = 0.85, 95% CI = 0.73-0.98) cohorts. We determined that 15 features were core variables for lymph node metastasis. Proliferation-related processes may respond to the main molecular alterations underlying these features. CONCLUSIONS: Machine learning-based radiomics could predict the status of lymph node metastasis in pancreatic cancer, which is associated with proliferation-related alterations.
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Metástasis Linfática , Neoplasias Pancreáticas , Humanos , Neoplasias Pancreáticas/genética , Neoplasias Pancreáticas/patología , Neoplasias Pancreáticas/diagnóstico por imagen , Persona de Mediana Edad , Masculino , Metástasis Linfática/patología , Femenino , Genómica , Aprendizaje Automático , Anotación de Secuencia Molecular , Regulación Neoplásica de la Expresión Génica , Estudios de Cohortes , Anciano , Algoritmos , Redes Reguladoras de Genes , Curva ROC , Reproducibilidad de los Resultados , RadiómicaRESUMEN
The properties of polyethylene are highly dependent on the variety and quantity of substitutions. Generally, polyethylene can only be fully substituted with fluorine atoms, mainly e. g., polytetrafluoroethylene and nafion, because atomic radius of fluorine atom is small enough. The preparation of fully substituted polyethylene analogues (FSPEA) and their non-traditional intrinsic luminescence (NTIL) are attractive, especially for substitutions with relatively larger atomic radii than a fluorine atom. Here, Barbier polymerization-induced emission (PIE) is demonstrated as a universal method for the molecular design of NTIL type FSPEAs with intriguing aggregation-induced emission (AIE) behaviors. Through Barbier polymerization of diphenyldichloromethane and different peroxyesters in the presence of Mg in one pot, a series of FSPEAs, including polytriphenylethanol (PTPE), polydiphenylfurylethanol (PDPFE), polydiphenylthiophenylethanol (PDPTE) and polydiphenylnaphthylethanol (PDPNE) have been successfully prepared. Further potential applications for explosive detection, artificial light-harvesting system and white phosphor-converted light-emitting diode are investigated. Therefore, this work opens up a new approach for the molecular design of FSPEA with non-conjugated luminescence, which may cause inspirations to different research fields like polyolefin and luminescent materials.
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OBJECTIVE: This study aimed to develop and validate a quantitative index system for evaluating the data quality of Electronic Medical Records (EMR) in disease risk prediction using Machine Learning (ML). MATERIALS AND METHODS: The index system was developed in four steps: (1) a preliminary index system was outlined based on literature review; (2) we utilized the Delphi method to structure the indicators at all levels; (3) the weights of these indicators were determined using the Analytic Hierarchy Process (AHP) method; and (4) the developed index system was empirically validated using real-world EMR data in a ML-based disease risk prediction task. RESULTS: The synthesis of review findings and the expert consultations led to the formulation of a three-level index system with four first-level, 11 second-level, and 33 third-level indicators. The weights of these indicators were obtained through the AHP method. Results from the empirical analysis illustrated a positive relationship between the scores assigned by the proposed index system and the predictive performances of the datasets. DISCUSSION: The proposed index system for evaluating EMR data quality is grounded in extensive literature analysis and expert consultation. Moreover, the system's high reliability and suitability has been affirmed through empirical validation. CONCLUSION: The novel index system offers a robust framework for assessing the quality and suitability of EMR data in ML-based disease risk predictions. It can serve as a guide in building EMR databases, improving EMR data quality control, and generating reliable real-world evidence.
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Exactitud de los Datos , Registros Electrónicos de Salud , Aprendizaje Automático , Registros Electrónicos de Salud/normas , Humanos , Medición de Riesgo/normas , Técnica DelphiRESUMEN
Early quantification of multiplex biomarkers such as microRNAs (miRNAs) is critical during disease pathologic development and therapy. To tackle challenges of low abundance and multiplexing, we herein report a mass-encoded biosensing approach with duplex-specific nuclease (DSN) mediated signal amplification. Magnetic Fe3O4 cores are coated with small gold nanoparticles (AuNPs), which are applied to achieve facile DNA immobilization subsequent separation. This biosensor integrates multiple mass reporters corresponding to different targets (five miRNAs as examples). Due to the excellent resolution of mass spectrometry, these targets can be successfully distinguished in a single spectrum. Wide detection ranges from 10 fM to 1 nM are achieved, and the limits of detection are estimated to be 10 fM. High selectivity is promised due to the enzyme activity of DSN, and practical application in human serum samples performs satisfactorily. The number of targets to be tested can be further expanded by designing different specific mass tags in theory. Therefore, the proposed method can be utilized as an important and valuable tool to quantify multiplex miRNAs for disease screening as well as biomedical investigations.
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Espectrometría de Masas , Técnicas de Amplificación de Ácido Nucleico , MicroARNs/química , Espectrometría de Masas/métodos , Técnicas de Amplificación de Ácido Nucleico/métodos , Ribonucleasas/metabolismo , Técnicas Biosensibles/métodos , Oro , Nanopartículas del MetalRESUMEN
BACKGROUND: The aim of this study was to investigate the effects of introducing the Enhanced Recovery After Surgery (ERAS) nursing model on postoperative delirium occurrence and rehabilitation quality in elderly patients with femoral neck fractures. METHODS: A total of 160 elderly patients with femoral neck fractures, who met the inclusion criteria and were admitted between March 2021 to March 2023, were divided into two groups: the traditional care group and the ERAS nursing model group. In addition to traditional care measures, the ERAS nursing model group received interventions based on the principles of the ERAS nursing model. The occurrence of delirium and sleep quality were observed at 24, 48, and 72 h postoperatively, as well as during the overall hospital stay. The duration of hospitalization, time to first mobilization, and post-discharge follow-up on quality of life were compared between the two groups. RESULTS: The ERAS nursing model group exhibited a significant difference in the occurrence of delirium at 48 and 72 h postoperatively, as well as during the overall hospital stay (P < 0.05). However, there was no significant difference in the occurrence of delirium at 24 h postoperatively (P > 0.05). The sleep quality of the two groups showed a statistically significant difference (P < 0.05). The ERAS nursing model group had shorter time to first mobilization, reduced hospitalization duration, and higher Harris and SF-36 scores during post-discharge follow-up, compared to the traditional care group (P < 0.05). CONCLUSIONS: The implementation of the ERAS nursing model in elderly patients with femoral neck fractures improved postoperative sleep quality, reduced delirium occurrence, shortened average hospitalization duration, and enhanced patients' quality of life.
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Delirio del Despertar , Fracturas del Cuello Femoral , Humanos , Anciano , Calidad de Vida , Cuidados Posteriores , Alta del Paciente , Fracturas del Cuello Femoral/cirugía , Tiempo de InternaciónRESUMEN
BACKGROUND: The growing number of patients visiting pediatric emergency departments could have a detrimental impact on the care provided to children who are triaged as needing urgent attention. Therefore, it has become essential to continuously monitor and analyze the admissions and waiting times of pediatric emergency patients. Despite the significant challenge posed by the shortage of pediatric medical resources in China's health care system, there have been few large-scale studies conducted to analyze visits to the pediatric emergency room. OBJECTIVE: This study seeks to examine the characteristics and admission patterns of patients in the pediatric emergency department using electronic medical record (EMR) data. Additionally, it aims to develop and assess machine learning models for predicting waiting times for pediatric emergency department visits. METHODS: This retrospective analysis involved patients who were admitted to the emergency department of Children's Hospital Capital Institute of Pediatrics from January 1, 2021, to December 31, 2021. Clinical data from these admissions were extracted from the electronic medical records, encompassing various variables of interest such as patient demographics, clinical diagnoses, and time stamps of clinical visits. These indicators were collected and compared. Furthermore, we developed and evaluated several computational models for predicting waiting times. RESULTS: In total, 183,024 eligible admissions from 127,368 pediatric patients were included. During the 12-month study period, pediatric emergency department visits were most frequent among children aged less than 5 years, accounting for 71.26% (130,423/183,024) of the total visits. Additionally, there was a higher proportion of male patients (104,147/183,024, 56.90%) compared with female patients (78,877/183,024, 43.10%). Fever (50,715/183,024, 27.71%), respiratory infection (43,269/183,024, 23.64%), celialgia (9560/183,024, 5.22%), and emesis (6898/183,024, 3.77%) were the leading causes of pediatric emergency room visits. The average daily number of admissions was 501.44, and 18.76% (34,339/183,204) of pediatric emergency department visits resulted in discharge without a prescription or further tests. The median waiting time from registration to seeing a doctor was 27.53 minutes. Prolonged waiting times were observed from April to July, coinciding with an increased number of arrivals, primarily for respiratory diseases. In terms of waiting time prediction, machine learning models, specifically random forest, LightGBM, and XGBoost, outperformed regression methods. On average, these models reduced the root-mean-square error by approximately 17.73% (8.951/50.481) and increased the R2 by approximately 29.33% (0.154/0.525). The SHAP method analysis highlighted that the features "wait.green" and "department" had the most significant influence on waiting times. CONCLUSIONS: This study offers a contemporary exploration of pediatric emergency room visits, revealing significant variations in admission rates across different periods and uncovering certain admission patterns. The machine learning models, particularly ensemble methods, delivered more dependable waiting time predictions. Patient volume awaiting consultation or treatment and the triage status emerged as crucial factors contributing to prolonged waiting times. Therefore, strategies such as patient diversion to alleviate congestion in emergency departments and optimizing triage systems to reduce average waiting times remain effective approaches to enhance the quality of pediatric health care services in China.
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Registros Electrónicos de Salud , Listas de Espera , Humanos , Niño , Femenino , Masculino , Estudios Retrospectivos , Hospitalización , Alta del PacienteRESUMEN
Introduction: We explored the relationship and the predictive value of serum fibroblast growth factor 21 (FGF21) with all-cause mortality, major adverse cardiovascular events (MACEs) and pneumonia in hemodialysis (HD) patients.Methods: A total of 388 Chinese HD patients from two HD centers were finally enrolled in this prospective cohort study (registration number: ChiCTR 1900028249) between January 2018 and December 2018. Serum FGF21 was detected. Patients were followed up with a median period of 47 months to record the MACEs and pneumonia until death or 31 December 2022.Results: The incidence of all-cause mortality, MACEs and pneumonia in HD patients were 20.6%, 29.6%, and 34.8%, respectively. The optimal cutoffs for FGF21 to predict all-cause mortality, MACEs and pneumonia were 437.57 pg/mL, 216.99 pg/mL and 112.79 pg/mL. Multivariate Cox regression analyses showed that FGF21, as a categorical variable, was an independent predictor for all-cause mortality, MACEs and pneumonia (HR, 3.357, 95% CI, 2.128-5.295, p < 0.001; HR, 1.575, 95% CI, 1.046-2.371, p = 0.029; HR, 1.784; 95% CI, 1.124-2.830; p = 0.014, respectively). The survival nomogram, MACEs-free survival nomogram and pneumonia-free survival nomogram based on FGF21 constructed for individualized assessment of HD patients had a high C-index with 0.841, 0.706 and 0.734.Conclusion: Higher serum FGF21 is an independent predictor of all-cause mortality, MACEs and pneumonia in HD patients.
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Factores de Crecimiento de Fibroblastos , Diálisis Renal , Humanos , Factores de Crecimiento de Fibroblastos/sangre , Estudios Prospectivos , Diálisis Renal/efectos adversos , Pueblos del Este de AsiaRESUMEN
OBJECTIVES: To explore and establish a reliable and noninvasive ultrasound model for predicting the biological risk of gastrointestinal stromal tumors (GISTs). MATERIALS AND METHODS: We retrospectively reviewed 266 patients with pathologically-confirmed GISTs and 191 patients were included. Data on patient sex, age, tumor location, biological risk classification, internal echo, echo homogeneity, boundary, shape, blood flow signals, presence of necrotic cystic degeneration, long diameter, and short/long (S/L) diameter ratio were collected. All patients were divided into low-, moderate-, and high-risk groups according to the modified NIH classification criteria. All indicators were analyzed by univariate analysis. The indicators with inter-group differences were used to establish regression and decision tree models to predict the biological risk of GISTs. RESULTS: There were statistically significant differences in long diameter, S/L ratio, internal echo level, echo homogeneity, boundary, shape, necrotic cystic degeneration, and blood flow signals among the low-, moderate-, and high-risk groups (all p < .05). The logistic regression model based on the echo homogeneity, shape, necrotic cystic degeneration and blood flow signals had an accuracy rate of 76.96% for predicting the biological risk, which was higher than the 72.77% of the decision tree model (based on the long diameter, the location of tumor origin, echo homogeneity, shape, and internal echo) (p = .008). In the low-risk and high-risk groups, the predicting accuracy rates of the regression model reached 87.34 and 81.82%, respectively. CONCLUSIONS: Transabdominal ultrasound is highly valuable in predicting the biological risk of GISTs. The logistic regression model has greater predictive value than the decision tree model.
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Tumores del Estroma Gastrointestinal , Endosonografía , Tumores del Estroma Gastrointestinal/diagnóstico por imagen , Tumores del Estroma Gastrointestinal/patología , Humanos , Modelos Logísticos , Estudios Retrospectivos , UltrasonografíaRESUMEN
A serial jatrophane-type diterpenoids, comprised with three undescribed compounds kanesulones C-E (1-3) and four known ones (4-7), were obtained from the roots of Euphorbia kansui. The structures of compounds 1-3 were elucidated by detailed interpretation of their spectroscopic data, especially 2D-NMR and HR-ESI-MS, the absolute configuration of 1 was revealed by single crystal X-ray diffraction. These isolates were assayed for their multidrug resistance reversing activities on human breast adenocarcinoma cell line MCF-7/ADR. Compound 1 possessed potential as low toxic MDR modulator that could promote the efficacy of anticancer drug adriamycin ca. 85-fold at 5â µM, as 12â times stronger than the positive drug verapamil.
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Diterpenos , Euphorbia , Humanos , Euphorbia/química , Estructura Molecular , Diterpenos/farmacología , Diterpenos/química , Resistencia a Múltiples MedicamentosRESUMEN
BACKGROUND: The rapid spread of the COVID-19 pandemic in the United States has made people uncertain about their perceptions of the threat of COVID-19 and COVID-19 response measures. To mount an effective response to this epidemic, it is necessary to understand the public's perceptions, behaviors, and attitudes. OBJECTIVE: We aimed to test the hypothesis that people's perceptions of the threat of COVID-19 influence their attitudes and behaviors. METHODS: This study used an open dataset of web-based questionnaires about COVID-19. The questionnaires were provided by Nexoid United Kingdom. We selected the results of a questionnaire on COVID-19-related behaviors, attitudes, and perceptions among the US public. The questionnaire was conducted from March 29 to April 20, 2020. A total of 24,547 people who lived in the United States took part in the survey. RESULTS: In this study, the average self-assessed probability of contracting COVID-19 was 33.2%, and 49.9% (12,244/24,547) of the respondents thought that their chances of contracting COVID-19 were less than 30%. The self-assessed probability of contracting COVID-19 among women was 1.35 times that of males. A 5% increase in perceived infection risk was significantly associated with being 1.02 times (OR 1.02, 95% CI 1.02-1.02; P<.001) more likely to report having close contact with >10 people, and being 1.01 times (OR 1.01, 95% CI 1.01-1.01; P<.001) more likely to report that cohabitants disagreed with taking steps to reduce the risk of contracting COVID-19. However, there was no significant association between participants who lived with more than 5 cohabitants or less than 5 cohabitants (P=.85). Generally, participants who lived in states with 1001-10,000 COVID-19 cases, were aged 20-40 years, were obese, smoked, drank alcohol, never used drugs, and had no underlying medical conditions were more likely to be in close contact with >10 people. Most participants (21,017/24,547, 85.6%) agreed with washing their hands and maintaining social distancing, but only 20.2% (4958/24,547) of participants often wore masks. Additionally, male participants and participants aged <20 years typically disagreed with washing their hands, maintaining social distancing, and wearing masks. CONCLUSIONS: This survey is the first attempt to describe the determinants of the US public's perception of the threat of COVID-19 on a large scale. The self-assessed probability of contracting COVID-19 differed significantly based on the respondents' genders, states of residence, ages, body mass indices, smoking habits, alcohol consumption habits, drug use habits, underlying medical conditions, environments, and behaviors. These findings can be used as references by public health policy makers and health care workers who want to identify populations that need to be educated on COVID-19 prevention and health.
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COVID-19/epidemiología , Brotes de Enfermedades/prevención & control , Pandemias/prevención & control , Adulto , Estudios Transversales , Femenino , Humanos , Masculino , Percepción , SARS-CoV-2/aislamiento & purificación , Encuestas y Cuestionarios , Estados Unidos , Adulto JovenRESUMEN
BACKGROUND: The coronavirus disease (COVID-19), a pneumonia caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has shown its destructiveness with more than one million confirmed cases and dozens of thousands of death, which is highly contagious and still spreading globally. World-wide studies have been conducted aiming to understand the COVID-19 mechanism, transmission, clinical features, etc. A cross-language terminology of COVID-19 is essential for improving knowledge sharing and scientific discovery dissemination. METHODS: We developed a bilingual terminology of COVID-19 named COVID Term with mapping Chinese and English terms. The terminology was constructed as follows: (1) Classification schema design; (2) Concept representation model building; (3) Term source selection and term extraction; (4) Hierarchical structure construction; (5) Quality control (6) Web service. We built open access for the terminology, providing search, browse, and download services. RESULTS: The proposed COVID Term include 10 categories: disease, anatomic site, clinical manifestation, demographic and socioeconomic characteristics, living organism, qualifiers, psychological assistance, medical equipment, instruments and materials, epidemic prevention and control, diagnosis and treatment technique respectively. In total, COVID Terms covered 464 concepts with 724 Chinese terms and 887 English terms. All terms are openly available online (COVID Term URL: http://covidterm.imicams.ac.cn ). CONCLUSIONS: COVID Term is a bilingual terminology focused on COVID-19, the epidemic pneumonia with a high risk of infection around the world. It will provide updated bilingual terms of the disease to help health providers and medical professionals retrieve and exchange information and knowledge in multiple languages. COVID Term was released in machine-readable formats (e.g., XML and JSON), which would contribute to the information retrieval, machine translation and advanced intelligent techniques application.
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COVID-19 , Epidemias , Humanos , Almacenamiento y Recuperación de la Información , Lenguaje , SARS-CoV-2RESUMEN
This study aimed to investigate the molecular mechanisms underlying the roles of metformin (MET) and Sorafenib (SOR) in the treatment of endometrial hyperplasia (EH) in polycystic ovary syndrome (PCOS). Effects of MET and SOR on the area of endometrium and myometrium were detected. Western blot analysis and immunohistochemistry assays were carried out to detect the levels of mammalian target of rapamycin complex 1 (mTORC1), mTORC2, LC3-II, P62, and Caspase-3 in rats and cultured cells. Furthermore, cell counting kit-8 assay and flow cytometry analysis was carried out to determine the apoptotic profiles of treated cells. MET and SOR could apparently decrease the areas of endometrium and myometrium in PCOS. MET notably enhanced the expression of LC3-II and Caspase-3 in PCOS while substantially reducing the level of mTORC1 and P62. Similarly, SOR also enhanced the expression of LC3-II and Caspase-3 in PCOS while substantially reducing the level of mTORC2 and P62. Treatment with MET and SOR significantly inhibited the proliferation of HCC-94 and HEC-1-A cells while promoting their apoptosis by upregulating the expression of Caspase-3. In cells treated with MET, the expression of mTORC1 and LC3-II was upregulated while the expression of P62 was downregulated. Similarly, in cells treated with SOR, the expression of mTORC2 and LC3-II was also upregulated while the expression of P62 was also downregulated. Furthermore, MET showed no effect on mTORC2 expression, while SOR showed no effect on mTORC1 expression. In this study, we suggested that MET and SOR alleviated the risk of EH in PCOS via the mTORC1/autophagy/apoptosis axis and mTORC2/autophagy/apoptosis axis, respectively.
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Apoptosis/efectos de los fármacos , Autofagia/efectos de los fármacos , Hiperplasia Endometrial/patología , Metformina/farmacología , Síndrome del Ovario Poliquístico/patología , Sorafenib/farmacología , Animales , Proteínas Reguladoras de la Apoptosis/efectos de los fármacos , Proteínas Reguladoras de la Apoptosis/metabolismo , Sinergismo Farmacológico , Hiperplasia Endometrial/metabolismo , Femenino , Síndrome del Ovario Poliquístico/metabolismo , Ratas , Ratas Sprague-DawleyRESUMEN
Factor VIII (FVIII) functions as a cofactor within the intrinsic pathway of blood coagulation in process of FX activation by FIXa, for which deficiency results in the bleeding disorder hemophilia A. The gene of FVIII contains 26 exons that code for a 19 amino acid signal peptide and a 2332 amino acid polypeptide with a domain structure designated A1-A2-B-A3-C1-C2, of which the A domains are homologous with each other, as are the C domains. It has been well-documented that both the domains are the necessary elements for FVIII activities. The B domain is highly glycosylated and has a variable sequence, even among FVIIIs from different species. The B domain plays versatile roles in FVIII lifespan except for coagulation activity, but the functional characteristics of its specific regions remain still obscure. A series of recombinant FVIIIs (rFVIIIs) with B domain truncated were constructed and transiently expressed in hepatocyte cells. Media and cell lysates were collected after 72 h for the analyses of FVIII biosynthesis, secretion, activity and stability in ex vivo plasma relative to the full length wild-type FVIII. Unexpectedly, various regions in B domain exhibited different contribution to these functionalities. The discovery might facilitate the bioengineered rFVIIIs and gene therapeutics.
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Factor VIII/metabolismo , Hepatocitos/metabolismo , Línea Celular , Exones , Factor VIII/química , Factor VIII/genética , Humanos , Mutación , Dominios Proteicos , Proteínas Recombinantes/química , Proteínas Recombinantes/genética , Proteínas Recombinantes/metabolismoRESUMEN
An amendment to this paper has been published and can be accessed via the original article.
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1. We aimed to establish a population pharmacokinetic (PK) model of tacrolimus and identify clinical covariates, especially the genetic polymorphisms of CYP3A5, ABCB1 and POR*28 that affected the PK to prevent fluctuation in the trough concentration of tacrolimus during the early period after renal transplantation. 2. Tacrolimus trough concentration, clinical data and CYP3A5/ABCB1/POR28 genotypes were retrospectively collected from 234 kidney transplant recipients during the first month post-transplantation. The population PK model was built using the non-linear mixed effects modeling software NONMEM. Dosing simulation was performed based on the final model. 3. A one-compartment model with first-order absorption and elimination was used to characterize the PK of tacrolimus. Among the genotypes, only CYP3A5 genotype was confirmed to have clinical significance. The final model describing CL/F (l/h) was as follows: 23.3 × ( HCT / 0.309 ) - 0.445 × [ ( 0.897 , i f POD > 10 ) o r ( 1 , i f POD ≤ 10 ) ] × ( 0.657 , i f CYP 3 A 5 * 3 / * 3 genotype ) . The inter-individual variability in CL/F was 21.9%. Monte Carlo simulation based on the final model was carried out to determine the optimal dosage regimen. 4. CYP3A5 genotype, post-operative day and hematocrit were confirmed as critical PK factors of tacrolimus. The model could be used to accurately predict individual PK parameters of tacrolimus and provide valuable insights into the dosage optimization.
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Citocromo P-450 CYP3A/genética , Inmunosupresores/farmacocinética , Tacrolimus/farmacocinética , Subfamilia B de Transportador de Casetes de Unión a ATP/genética , Humanos , Trasplante de Riñón , Polimorfismo de Nucleótido SimpleRESUMEN
BACKGROUND: The increasing global cancer incidence corresponds to serious health impact in countries worldwide. Knowledge-powered health system in different languages would enhance clinicians' healthcare practice, patients' health management and public health literacy. High-quality corpus containing cancer information is the necessary foundation of cancer education. Massive non-structural information resources exist in clinical narratives, electronic health records (EHR) etc. They can only be used for training AI models after being transformed into structured corpus. However, the scarcity of multilingual cancer corpus limits the intelligent processing, such as machine translation in medical scenarios. Thus, we created the cancer specific cross-lingual corpus and open it to the public for academic use. METHODS: Aiming to build an English-Chinese cancer parallel corpus, we developed a workflow of seven steps including data retrieval, data parsing, data processing, corpus implementation, assessment verification, corpus release, and application. We applied the workflow to a cross-lingual, comprehensive and authoritative cancer information resource, PDQ (Physician Data Query). We constructed, validated and released the parallel corpus named as ECCParaCorp, made it openly accessible online. RESULTS: The proposed English-Chinese Cancer Parallel Corpus (ECCParaCorp) consists of 6685 aligned text pairs in Xml, Excel, Csv format, containing 5190 sentence pairs, 1083 phrase pairs and 412 word pairs, which involved information of 6 cancers including breast cancer, liver cancer, lung cancer, esophageal cancer, colorectal cancer, and stomach cancer, and 3 cancer themes containing cancer prevention, screening, and treatment. All data in the parallel corpus are online, available for users to browse and download ( http://www.phoc.org.cn/ECCParaCorp/ ). CONCLUSIONS: ECCParaCorp is a parallel corpus focused on cancer in a cross-lingual form, which is openly accessible. It would make up the imbalance of scarce multilingual corpus resources, bridge the gap between human readable information and machine understanding data resources, and would contribute to intelligent technology application as a preparatory data foundation e.g. cancer-related machine translation, cancer system development towards medical education, and disease-oriented knowledge extraction.
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Multilingüismo , Neoplasias , Humanos , Almacenamiento y Recuperación de la Información , Lenguaje , Unified Medical Language SystemRESUMEN
This study proposes an image segmentation method based on bottleneck detection and watershed algorithm to solve the problem of overlapping cervical cell image. First, we use polygon approximation to get all feature points on the cell contour and then use bottleneck detection and ellipse fitting to obtain the correct split point pairs. Therefore, the approximate range of the overlapping region was determined. The watershed algorithm was used to obtain the internal boundary information for the gradient image of the region. Finally, the segmentation results of the overlapped cells were obtained by superimposing with the outer contour. The experimental results show that this algorithm can segment the contour of a single cell from the overlapping cervical cell images with good accuracy and integrity. The segmentation result is close to that of doctors' manual marking, and the segmentation result is better than other existing algorithms.
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Algoritmos , Cuello del Útero/citología , Procesamiento de Imagen Asistido por Computador , Femenino , HumanosRESUMEN
High-mobility group box-1 (HMGB-1) acts as a pro-inflammatory cytokine contributing to the occurrence of many central inflammatory and infectious disorders. Brain mast cells (MCs) are the first responders to peripheral inflammatory stimulation because of their rapid response to external stimuli coupled with their release of preformed and newly synthesized reactive chemicals. Little is known about the involvement of brain MCs in the pro-inflammatory effects of HMGB-1 on the central nervous system (CNS). Thus, we investigated the activation process of MCs by HMGB-1 and explored whether this process is involved in the pro-inflammatory effects of HMGB-1 on the CNS. In this study, we used P815 cells to study the activating role of HMGB-1 on MCs and to explore its potential mechanism in vitro. In an in vivo study, adult male Sprague-Dawley rats received i.c.v. injection of sterile saline or cromoglycate (stabilizer of MCs) 30 min prior to i.p. injection of HMGB-1. Increased levels of tumor necrosis factor and IL-1ß were observed in the P815 cells, as well as in the rats' brains, after HMGB-1 treatment. Pretreatment with the receptor of advanced glycation endproducts (RAGE)-siRNA inhibited the HMGB-1-induced inflammatory process in the P815 cells. Activation of the RAGE/nuclear factor-κB (NF-κB) pathway was observed in both the P815 cells and rats' brains. In addition, HMGB-1 induced the accumulation of brain MCs in the hippocampal CA1 region, and the blood-brain barrier was disrupted. Pretreatment with cromoglycate, a stabilizer of MCs, mitigated these HMGB-1-induced pro-inflammatory processes in rats. These findings indicate that brain MCs are involved in the pro-inflammatory effect of HMGB-1 on the CNS, probably via activating the RAGE/NF-κB pathway.
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Encéfalo/inmunología , Proteína HMGB1/inmunología , Mastocitos/inmunología , Transducción de Señal/inmunología , Animales , Encéfalo/metabolismo , Proteína HMGB1/metabolismo , Masculino , Mastocitos/metabolismo , Ratones , FN-kappa B/inmunología , FN-kappa B/metabolismo , Ratas , Ratas Sprague-Dawley , Receptor para Productos Finales de Glicación Avanzada/inmunología , Receptor para Productos Finales de Glicación Avanzada/metabolismoRESUMEN
A novel chiral derivatization reagent, the N-[1-oxo-5-(triphenylphosphonium)pentyl]- (R)-1,3-thiazolidinyl-4-N-hydroxysuccinimide ester bromide salt (OTPTHE), was developed for the separation and selective detection of chiral DL-amino acids by RP-HPLC analysis. The OTPTHE reacted with DL-amino acids at 60°C maintained for 30 minutes in the presence of 100 mM borate buffer (pH 9.5). The separability of the diastereomeric derivatives was evaluated in terms of the resolution value (Rs) using 13 kinds of DL-amino acids, which were completely separated by reversed-phase chromatography using C18 column at 254 nm. The Rs of the DL-amino acids varied from 1.62 to 2.51. As for the application of the DL-amino acids, the determination of DL-Ser in the human plasma of healthy volunteers was performed based on our developed method. It was shown that linear calibrations were available with high coefficients of correlation (r2 > 0.9997). The limit of detection (S/N = 3) of the DL-Ser enantiomers was 5.0 pmol; the relative standard deviations of the intraday and interday variations were below 4.56%; the accuracy ranged between 95.40%-110.06% and 95.45%-109.80%, respectively; the mean recoveries (%) of the DL-Ser spiked in the human plasma were 99.49%-103.74%. The amounts of DL-Ser in the human plasma of healthy volunteers were determined.