Pharmacokinetic Simulation and Area under the Curve Estimation of Drugs Subject to Enterohepatic Circulation.

Enterohepatic circulation (EHC) is a complex process where drugs undergo secretion and reabsorption from the intestinal lumen multiple times, resulting in pharmacokinetic profiles with multiple peaks. The impact of EHC on area under the curve (AUC) has been a topic of extensive debate, questioning the suitability of conventional AUC estimation methods. Moreover, a universal model for accurately estimating AUC in EHC scenarios is lacking. To address this gap, we conducted a simulation study evaluating five empirical models under various sampling strategies to assess their performance in AUC estimation. Our results identify the most suitable model for EHC scenarios and underscore the critical role of meal-based sampling strategies in accurate AUC estimation. Additionally, we demonstrate that while the trapezoidal method performs comparably to other models with a large number of samples, alternative models are essential when sample numbers are limited. These findings not only illuminate how EHC influences AUC but also pave the way for the application of empirical models in real-world drug studies.

Application of peripheral blood routine parameters in the diagnosis of influenza and Mycoplasma pneumoniae.

OBJECTIVES: Influenza and Mycoplasma pneumoniae infections often present concurrent and overlapping symptoms in clinical manifestations, making it crucial to accurately differentiate between the two in clinical practice. Therefore, this study aims to explore the potential of using peripheral blood routine parameters to effectively distinguish between influenza and Mycoplasma pneumoniae infections. METHODS: This study selected 209 influenza patients (IV group) and 214 Mycoplasma pneumoniae patients (MP group) from September 2023 to January 2024 at Nansha Division, the First Affiliated Hospital of Sun Yat-sen University. We conducted a routine blood-related index test on all research subjects to develop a diagnostic model. For normally distributed parameters, we used the T-test, and for non-normally distributed parameters, we used the Wilcoxon test. RESULTS: Based on an area under the curve (AUC) threshold of ≥ 0.7, we selected indices such as Lym# (lymphocyte count), Eos# (eosinophil percentage), Mon% (monocyte percentage), PLT (platelet count), HFC# (high fluorescent cell count), and PLR (platelet to lymphocyte ratio) to construct the model. Based on these indicators, we constructed a diagnostic algorithm named IV@MP using the random forest method. CONCLUSIONS: The diagnostic algorithm demonstrated excellent diagnostic performance and was validated in a new population, with an AUC of 0.845. In addition, we developed a web tool to facilitate the diagnosis of influenza and Mycoplasma pneumoniae infections. The results of this study provide an effective tool for clinical practice, enabling physicians to accurately diagnose and differentiate between influenza and Mycoplasma pneumoniae infection, thereby offering patients more precise treatment plans.

Characterizing Day 1 Area Under the Curve Following Vancomycin Loading Dose Administration in Adult Hospitalized Patients Using Non-Trapezoidal Linear Pharmacokinetic Equations: A Retrospective Observational Study.

INTRODUCTION: Methicillin-resistant Staphylococcus aureus (MRSA) infections are a serious threat to public health. Vancomycin (VAN) remains the primary treatment for these infections, and achieving the recommended area under the curve (AUC) target has been linked to improved clinical outcomes. The current VAN therapeutic monitoring guidelines recommend a loading dose (LD) of 20-35 mg/kg to rapidly attain targeted VAN exposures within 24 h of therapy. However, there is a paucity of data describing the impact of VAN LD on day 1 area under the curve (AUC0-24). This study aims to employ pharmacokinetic (PK) equations to calculate and describe the AUC0-24 following a VAN LD of 20 mg/kg. METHODS: This was a retrospective study of adult patients who were loaded with VAN 20 mg/kg, received ≥ 48 h of treatment, and had two consecutive serum VAN levels collected within 24 h. Linear, non-trapezoidal PK equations and two post-infusion VAN levels were used to calculate AUC0-24. Therapeutic AUC0-24 was defined as 400-600 mg/l*h. RESULTS: Among 123 included patients, the median age was 46 years (IQR 36, 62), 54% (67/123) of the patients had a body mass index (BMI) ≥ 30 kg/m2 and 27% (33/123) were admitted to the intensive care unit (ICU). Following a LD of 20 mg/kg, 50% (61/123) of the patients met the therapeutic AUC0-24, while 22% (27/123) of the patients were subtherapeutic, and 28% (35/123) were supratherapeutic. Compared with patients who achieved therapeutic AUC0-24, patients with subtherapeutic AUC0-24 were more likely to be younger (44 vs. 37 years old) and have a BMI ≥ 30 kg/m2 (67 vs. 52%). In contrast, patients with supratherapeutic AUC0-24 were more likely to be older (64 vs. 44 years old) and to have chronic kidney disease diagnosis (23 vs. 7%) when compared to patients who achieved a therapeutic AUC0-24. CONCLUSIONS: Only 50% of patients achieve the target AUC0-24 following a VAN 20 mg/kg LD, with younger, heavier patients underexposed and older patients with renal impairment overexposed, suggesting that different dosing strategies are needed for these populations.

Using Machine Learning to Evaluate the Value of Genetic Liabilities in the Classification of Hypertension within the UK Biobank.

Background and Objective: Hypertension increases the risk of cardiovascular diseases (CVD) such as stroke, heart attack, heart failure, and kidney disease, contributing to global disease burden and premature mortality. Previous studies have utilized statistical and machine learning techniques to develop hypertension prediction models. Only a few have included genetic liabilities and evaluated their predictive values. This study aimed to develop an effective hypertension classification model and investigate the potential influence of genetic liability for multiple risk factors linked to CVD on hypertension risk using the random forest and the neural network. Materials and Methods: The study involved 244,718 European participants, who were divided into training and testing sets. Genetic liabilities were constructed using genetic variants associated with CVD risk factors obtained from genome-wide association studies (GWAS). Various combinations of machine learning models before and after feature selection were tested to develop the best classification model. The models were evaluated using area under the curve (AUC), calibration, and net reclassification improvement in the testing set. Results: The models without genetic liabilities achieved AUCs of 0.70 and 0.72 using the random forest and the neural network methods, respectively. Adding genetic liabilities improved the AUC for the random forest but not for the neural network. The best classification model was achieved when feature selection and classification were performed using random forest (AUC = 0.71, Spiegelhalter z score = 0.10, p-value = 0.92, calibration slope = 0.99). This model included genetic liabilities for total cholesterol and low-density lipoprotein (LDL). Conclusions: The study highlighted that incorporating genetic liabilities for lipids in a machine learning model may provide incremental value for hypertension classification beyond baseline characteristics.

From data through discount rates to the area under the curve.

The rate of discounting future goods is a crucial factor in intertemporal trade-offs, upon which depends not only individual well-being but also that of our planet: How much privation now for a temperate future for our grandchildren? What is the best way to measure how the value of future goods decreases with its delay? The most accurate discount functions involve several covarying parameters, making interpretation equivocal. A universal and robust measure is the area under the discount curve, the AuC. The AuC of a hyperbolic discount function is a logarithmic function of the discount rate, k. The same integral also approximates the area under a hyperboloid function. A simple technique converts each datum into estimates of the discount rate, eliminating rogue data points in the process. These trimmed estimates are converted into areas and tested against data, where they succeed at predicting the AuC and its relation to log(k).

Nonparametric bootstrap methods for interval estimation of the area under the ROC curve with correlated diagnostic test data: application to whole-virus ELISA testing in swine.

Developing and evaluating novel diagnostic assays are crucial components of contemporary diagnostic research. The receiver operating characteristic (ROC) curve and the area under the ROC curve (AUC) are frequently used to evaluate diagnostic assays' performance. The variation in AUC estimation can be quantified nonparametrically using resampling methods, such as bootstrapping, and then used to construct interval estimation for the AUC. When multiple observations are observed from the same subject, which is very common in veterinary diagnostic tests evaluation experiments, a traditional bootstrap-based method can fail to provide valid interval estimations of AUC. In particular, the traditional method does not account for the correlation among data observations and could result in interval estimation that fails to cover the true AUC adequately at the desired confidence level. In this paper, we proposed two novel methods to calculate the confidence interval of the AUC for correlated diagnostic test data based on cluster bootstrapping and hierarchical bootstrapping, respectively. Our simulation studies showed that both proposed methods had adequate coverage probabilities which were higher than the existing traditional method when there were intra-subject correlations. We also discussed applying the proposed methods to evaluate a novel whole-virus ELISA (wv-ELISA) diagnostic assay in detecting porcine parainfluenza virus type-1 antibodies in swine serum.

Population pharmacokinetics of vancomycin in patients with diabetic foot infection: a comparison of five models.

Purpose: This study aimed to compare individual pharmacokinetic (PK) parameters of vancomycin with predicted values from five population PK models in patients with diabetic foot infections (DFIs). Methods: Patients with a diagnosis of DFI and an estimated glomerular filtration rate (eGFR) ≥ 30 mL/min were included in the study. Individual PK data was carried on by collecting three vancomycin serum concentrations in a steady-state condition. Five published population-based nomograms were assumed to predict PK parameters. Optimal vancomycin exposure was considered as a trough level of 15-20 mg/L or the area under the curve over 24 h/minimum inhibitory concentration (AUC24/MIC) ≥ 400. Results: A total of 48 samples from 16 patients were analyzed. There was a statistically significant difference between the volume of distribution (Vd) obtained from population methods and the individual estimations (P ≤ 0.001 in Ambrose and Burton, P = 0.010 and 0.006 in Bauer and Burton revised models, respectively). AUC/MIC ≥ 400 was achieved in 68.7% of patients while 50% had a trough level of less than 15 mg/L. Conclusions: Vancomycin PK parameters, particularly individualized Vd, may not be predictable by population nomograms in patients with DFI and stable renal function. Moreover, the weak correlation between AUC24 values and trough concentrations underlines the starting practice of vancomycin AUC24-based monitoring and dosing in the clinical setting.

Intraperitoneally Administered Vancomycin in Patients with Peritoneal Dialysis-Associated Peritonitis: Population Pharmacokinetics and Dosing Implications.

Peritonitis is a limiting complication of peritoneal dialysis, which is treated by intraperitoneal administration of antibiotics. Various dosing strategies are recommended for intraperitoneally administered vancomycin, which leads to large differences in intraperitoneal vancomycin exposure. Based on data from therapeutic drug monitoring, we developed the first-ever population pharmacokinetic model for intraperitoneally administered vancomycin to evaluate intraperitoneal and plasma exposure after dosing schedules recommended by the International Society for Peritoneal Dialysis. According to our model, currently recommended dosing schedules lead to possible underdosing of a large proportion of patients. To prevent this, we suggest avoiding intermittent intraperitoneal vancomycin administration, and for the continuous dosing regimen, we suggest a loading dose of 20 mg/kg followed by maintenance doses of 50 mg/L in each dwell to improve the intraperitoneal exposure. Vancomycin plasma level measurement on the fifth day of treatment with subsequent dose adjustment would prevent it from reaching toxic levels in the few patients who are susceptible to overdose.

In Vitro-In Vivo Correlations (IVIVC) for Predicting the Clinical Performance of Metronidazole Topical Creams Intended for Local Action.

The safety and efficacy of a generic medicine can be confirmed by demonstrating bioequivalence (BE) between the generic product and its reference listed drug (RLD) by measuring drug concentrations in the blood following administration. However, for topical dermatological products that are not absorbed into the systemic circulation, clinical trials in patients are required. The objective of this investigation was to use an in vitro method to predict in vivo performance by correlating in vitro release testing (IVRT) data with tape stripping (TS) data following the application of metronidazole (MTZ) creams to the skin of healthy human participants. Whereas IVRT is generally used to characterize the release of a drug from topical products across a synthetic membrane into a suitable receptor medium, TS involves the sequential removal of layers of stratum corneum (SC) with an adhesive tape to determine the amount of the drug in the skin. The resulting IVRT and TS data were correlated using the IVRT parameter of the apparent release constant (ARC), which is the slope obtained from the release rate profile, with the TS parameter of the area under the curve (AUC) obtained from a plot of the amount of drug per tape strip vs. the relative SC depth. A rank order relationship for these parameters was established for the reference and test products. A graph of AUC vs. ARC was plotted to establish a Level C in vitro-in vivo correlation (IVIVC). Although the ARC for T1 was slightly lower than that for the reference, the rank order was essentially consistent. A linear relationship was observed between the AUCs and ARCs. The equation derived was used to predict the AUCs for all the tested products based on their respective ARCs. The predicted AUC values based on the observed ARCs were similar to the observed AUCs. The lower and upper limits for the in vitro and in vivo parameters for BE were computed based on regulatory acceptance criteria. In order to predict BE from the IVRT studies, the values of the ARC should be between 30.50 and 47.67 when comparing test and reference cream products containing MTZ.

Tutorial: statistical methods for the meta-analysis of diagnostic test accuracy studies.

This tutorial shows how to perform a meta-analysis of diagnostic test accuracy studies (DTA) based on a 2 × 2 table available for each included primary study. First, univariate methods for meta-analysis of sensitivity and specificity are presented. Then the use of univariate logistic regression models with and without random effects for e.g. sensitivity is described. Diagnostic odds ratios (DOR) are then introduced to combine sensitivity and specificity into one single measure and to assess publication bias. Finally, bivariate random effects models using the exact binomial likelihood to describe within-study variability and a normal distribution to describe between-study variability are presented as the method of choice. Based on this model summary receiver operating characteristic (sROC) curves are constructed using a regression model logit-true positive rate (TPR) over logit-false positive rate (FPR). Also it is demonstrated how to perform the necessary calculations with the freely available software R. As an example a meta-analysis of DTA studies using Procalcitonin as a diagnostic marker for sepsis is presented.

Metadherin Promotes the Development of Bladder Cancer by Enhancing Cell Division.

Background: Bladder cancer (BLCA) is a malignant tumor occurring in bladder mucosa. Metadherin (MTDH) has been implicated in tumor progression; however, its molecular biological mechanisms in BLCA remain unclear. Materials and Methods: Cell functions were tested after BLCA cells were transfected by both short hairpin RNAs and small interfering RNAs to silence MTDH. Furthermore, in-house RNA sequencing (RNA-seq) was performed with T24 cells after the knockdown of MTDH. In addition, MTDH-related pathways were explored. Finally, MTDH mRNA and protein expression levels were examined using multiple detection methods in BLCA tissues. Results: MTDH knockdown could largely inhibit cell proliferation, viability, and migration and induce apoptosis of BLCA cells. In-house RNA-seq showed that MTDH knockdown led to extracellular matrix organization and cell division. The integrated analysis showed that the comprehensive expression of MTDH at the mRNA level was 0.47 and that at the protein level was 0.54, based on 11 platforms, including 1485 BLCA and 180 non-BLCA samples. Conclusions: MTDH promotes the growth of BLCA cells through the pathway of cell division. This study provides new directions and biomarkers for future treatment.

Analysis of Therapeutic Decisions for Infantile Hemangiomas: A Prospective Study Comparing the Hemangioma Severity Scale with the Infantile Hemangioma Referral Score.

BACKGROUND: In view of the high incidence of infantile hemangioma (IH) in infants and young children, a comprehensive and reasonable evaluation scale for referral is urgently needed. This study compared the influence of the Hemangioma Severity Scale (HSS) and the Infantile Hemangioma Referral Score (IHReS) on treatment decisions for infantile hemangioma patients. OBJECTIVE: We aimed to establish a reliable and effective evaluation method for referral. METHODS: This was a prospective study to determine whether treatment was needed for IH patients after evaluation with the HSS and IHReS. RESULTS: A total of 266 consecutive referred IH patients were evaluated for the risk of IH, and the treatment rate was 80.8%. The area under the curve (AUC) of the subject receiver operating characteristic curve (ROC) of treatment decision making after referral by the HSS was 0.703 (95% CI: 0.634-0.772), and after referral by the IHReS was 0.892 (95% CI: 0.824-0.960). LIMITATIONS: This was a single-center study. CONCLUSIONS: For decisions regarding the treatment of IH patients, the IHReS has a higher efficiency and sensitivity than the HSS. However, the specificity of the IHReS is lower than that of the HSS.

Metabolic Characteristics of Porcine LA-MRSA CC398 and CC9 Isolates from Germany and China via Biolog Phenotype MicroArrayTM.

Livestock-associated methicillin-resistant Staphylococcus aureus (LA-MRSA) is an important zoonotic pathogen, often multi-resistant to antimicrobial agents. Among swine, LA-MRSA of clonal complex (CC) 398 dominates in Europe, Australia and the Americas, while LA-MRSA-CC9 is the main epidemic lineage in Asia. Here, we comparatively investigated the metabolic properties of rare and widespread porcine LA-MRSA isolates from Germany and China using Biolog Phenotype MicroArray technology to evaluate if metabolic variations could have played a role in the development of two different epidemic LA-MRSA clones in swine. Overall, we were able to characterize the isolates' metabolic profiles and show their tolerance to varying environmental conditions. Sparse partial least squares discriminant analysis (sPLS-DA) supported the detection of the most informative substrates and/or conditions that revealed metabolic differences between the LA-MRSA lineages. The Chinese LA-MRSA-CC9 isolates displayed unique characteristics, such as a consistently delayed onset of cellular respiration, and increased, reduced or absent usage of several nutrients. These possibly unfavorable metabolic properties might promote the ongoing gradual replacement of the current epidemic LA-MRSA-CC9 clone in China with the emerging LA-MRSA-CC398 lineage through livestock trade and occupational exposure. Due to the enhanced pathogenicity of the LA-MRSA-CC398 clone, the public health risk posed by LA-MRSA from swine might increase further.

Assessment of an online calculator's vancomycin dosing and exposure appropriateness in persons who inject drugs with methicillin-resistant Staphylococcus aureus bloodstream infections.

WHAT IS KNOWN AND OBJECTIVE: While the gold standard for calculating AUC involves two steady-state concentrations, online calculators can empirically estimate AUC and other pharmacokinetic (PK) parameters. In patients with potentially altered PK, such as persons who inject drugs (PWID), the reliability of these predictions is unclear. Our objectives were to characterize the PK of vancomycin in PWID with methicillin-resistant Staphylococcus aureus (MRSA) bloodstream infections (BSI) and to assess the impact of these PK parameters on dosing regimens when compared to regimens generated by an online calculator. METHODS: This descriptive pilot study included a retrospective chart review of 48 inpatient PWID with MRSA BSI from 30 April 2018 through 31 August 2020. Demographic and clinical data along with vancomycin dosing and serum concentrations were collected. Patient-specific PK parameters were used to calculate the AUC of each empiric regimen compared with the originally predicted AUC. RESULTS AND DISCUSSION: The study population had a median volume of distribution of 0.74 L/kg, clearance of 0.081 L/kg/h, elimination rate constant of 0.110/h and half-life of 6.3 h. The online calculator empirically predicted 6 subtherapeutic and 42 appropriate AUC values with its recommended empiric dosing regimens. Using the actual patient-specific PK parameters, the empiric vancomycin regimens actually resulted in 21 (43.75%) underexposures, 24 (50%) appropriate exposures and 3 (6.25%) overexposures. WHAT IS NEW AND CONCLUSIONS: In PWID, empiric vancomycin dosing strategies suggested by an online calculator frequently resulted in lower-than-predicted vancomycin exposures. These findings suggest that PWID with MRSA BSI may require higher and/or more frequent vancomycin doses than those empirically recommended by the population-based methods of an online calculator.

Systems biomarker characteristics of circulating alkaline phosphatase activities for 48 types of human diseases.

BACKGROUND: Most human diseases are accompanied by systems changes. Systems biomarkers should reflect such changes. The phosphorylation and dephosphorylation of biomolecules maintain human homeostasis. However, the systems biomarker characteristics of circulating alkaline phosphatase, a routine blood test conducted for many human diseases, have never been investigated. METHOD: This study retrieved the circulating alkaline phosphatase (ALP) activities from patients with 48 clinically confirmed diseases and healthy individuals from the database of our hospital during the past five years. A detailed analysis of the statistical characteristics of ALP was conducted, including quantiles, receiving operator curve (ROC), and principal component analysis. RESULTS: Among the 48 diseases, 45 had increased, and three had decreased median levels of ALP activities compared to the healthy control. Preeclampsia, hepatic encephalopathy, pancreatic cancer, and liver cancer had the highest median values, whereas nephrotic syndrome, lupus erythematosus, and nephritis had decreased median values compared to the healthy control. Further, area under curve (AUC) values were ranged between 0.61 and 0.87 for 19 diseases, and the ALP activities were the best systems biomarker for preeclampsia (AUC 0.87), hepatic encephalopathy (AUC 0.87), liver cancer (AUC 0.81), and pancreatic cancer (AUC 0.81). CONCLUSIONS: Alkaline phosphatase was a decent systems biomarker for 19 different types of human diseases. Understanding the molecular mechanisms of over-up-and-down-regulation of ALP activities might be the key to understanding the whole-body systems' reactions during specific disease progression.

Effects of Acute Resistance Exercise with and without Whole-Body Electromyostimulation and Endurance Exercise on the Postprandial Glucose Regulation in Patients with Type 2 Diabetes Mellitus: A Randomized Crossover Study.

BACKGROUND: Long hyperglycemic episodes trigger complications in type 2 diabetes mellitus (T2DM) patients. Postprandial glucose excursions can be reduced by acute physical activity. However, it is not yet clear which type of exercise has the best effect on postprandial glucose levels. METHODS: Six T2DM patients participated in three 20-min moderate-intensity exercise sessions after breakfast in a randomized order: resistance exercise with whole-body electromyostimulation (WB-EMS), resistance exercise without electromyostimulation (RES) and cycling endurance exercise (END). A continuous glucose monitoring system recorded glucose dynamics. RESULTS: Postprandially-increased glucose levels decreased in all cases. Time to baseline (initial value prior to meal intake) was quite similar for WB-EMS, RES and END. Neither glucose area under the curve (AUC), nor time in range from the start of the experiment to its end (8 h later) differed significantly. A Friedman analysis of variance, however, revealed an overall significant difference for AUC in the post-exercise recovery phase (END seems to have superior effects, but post-hoc tests failed statistical significance). CONCLUSIONS: There are no notable differences between the effects of the different types of exercise on glucose levels, especially when comparing values over a longer period of time.

Performance of Scoring Systems in Predicting Clinical Outcomes in Patients with Bacteremia of Listeria monocytogenes: A 9-Year Hospital-Based Study.

BACKGROUND: Listeria monocytogenes (LM) is a facultative anaerobe, Gram-positive bacillus which is widely distributed in nature, and can be separated from soil, water, and rotten vegetables. Immunocompetent people are less likely to suffer from LM infection or may only show gastrointestinal symptoms. However, immunocompromised elderly people, pregnant women, and newborns may develop life-threatening invasive infections. The mortality rate of LM infection is as high as 25-30%. The aim of this study is to investigate clinical scores of patients with bacteremia of LM confirmed by one or more blood cultures. We analyzed their demographics and laboratory findings in relation to their clinical outcomes. MATERIALS AND METHODS: This was a hospital-based retrospective study on patients with bacteremia of LM. Data were collected from the electronic clinical database of Taichung Veterans General Hospital between January 2012 and December 2020. Bacteremia of LM was confirmed by at least one blood culture. Demographics, clinical characteristics, and laboratory data were collected for analysis. A variety of clinical scoring systems were used to predict the clinical outcome. RESULTS: A total of 39 patients had confirmed bacteremia of LM. Among them, 1 neonatal patient was excluded. The remaining 38 patients were studied. They included 16 males (42.1%) and 22 females (57.9%), with a mean age of 59.9 ± 19.6 years. Their hospital stay averaged 23.3 ± 20.9 days. The in-hospital mortality rate was 36.8%. Mortality in Emergency Department Sepsis (MEDS) Score was 6.6 ± 4.0 for survivors and 12.4 ± 4.4 for non-survivors (P < 0.001). The National Early Warning Score (NEWS) was 3.9 ± 2.8 for survivors and 7.8 ± 3.1 for non-survivors (P = 0.001). Regarding the prediction of mortality risk, the AUC of ROC was 0.829 for MEDS and 0.815 for NEWS. CONCLUSIONS: MEDS and NEWS were both good predictors of the clinical outcome in LM bacteremic patients. In those with higher scores of MEDS (≥10) and NEWS (≥8), we recommended an early goal-directed therapy and appropriate antibiotic treatment as early as possible to reduce mortality. Further large-scale studies are required to gain a deeper understanding of this disease and to ensure patient safety.

Diabetes mellitus and postoperative blood glucose value help predict posthepatectomy liver failure in patients with hepatocellular carcinoma.

BACKGROUND: Many complications after hepatectomy can lead to perioperative death, among which posthepatectomy liver failure (PHLF) is the leading one. Existing studies suggest that one of the most important risk factors for PHLF is cirrhosis. Hepatitis B virus (HBV) infection is an important factor in the occurrence of cirrhosis, and the exact relationship between HBV infection and PHLF is not obvious. Diabetes mellitus and postoperative blood glucose are closely associated with liver regeneration, but its exact relationship with PHLF remains unclear. METHODS: We collected clinical indicators from 920 adult patients treated at the Liver Surgery and Transplantation Center of West China Hospital of Sichuan University from April 2009 and April 2019. We conducted a univariate analysis find out the risk factors of PHLF, follow by a multivariate analysis to ascertain the independent risk factors. Receiver operating characteristic (ROC) curves were plotted to evaluate the predictive efficiency of each risk factor. RESULTS: Following hepatectomy, 205 (22.2%) of patients were diagnosed with PHLF. Several variables were confirmed to related with PHLF significantly: diabetes [P<0.01, odds ratio (OR) =10.845, 95% confidence interval (CI): 5.450-21.579], HBV (P<0.01, OR =0.345, 95% CI: 0.187-0.635), blood glucose on the first postoperative day (post-BG1) (P=0.027, OR =1.059, 95% CI: 1.006-1.115), blood glucose on the third postoperative day (post-BG3) (P=0.021, OR =1.085, 95% CI: 1.012-1.162), blood glucose on the fifth postoperative day (post-BG5) (P=0.014, OR =1.119, 95% CI: 1.023-1.225), postoperative total bilirubin (post-TB) (P<0.01, OR =1.160, 95% CI: 1.133-1.187), and liver cirrhosis (P<0.01, OR =0.982, 95% CI: 0.561-1.717) identified to be independent risk factors of PHLF. CONCLUSIONS: Diabetes, HBV, post-BG1, post-BG3, and post-BG5 are related to the development of PHLF, and diabetes and post-BG can be used as predictors of the development of PHLF in patients with hepatocellular carcinoma (HCC).

The utilization of hydroxychloroquine to reduce the main signs and symptoms of COVID-19 patients, a cross-sectional study.

Hydroxychloroquine (HCQ) and chloroquine were found to have positive results in some non-randomized clinical trials with more benefit in decreasing the viral load of COVID-19. HCQ is a lysosomotropic and lipophilic drug that can penetrate cell membranes, and accumulates in the acidic lysosomes. The high concentration of alkaline HCQ increases the pH in lysosomes from the normal levels of 4.7-4.8 to 6 which leads to inhibition of lysosomes functions and thus, prevents the entry of coronavirus into cells. OBJECTIVES: The main aim of this study is to find out the appropriateness of using HCQ in asymptomatic/mildly symptomatic COVID-19 positive patients in an attempt to reduce the development of signs and symptoms of COVID-19 and severe disease. METHODOLOGY: Randomized selection, open-label trial to evaluate the efficacy of HCQ for patients presenting with asymptomatic COVID-19 upon diagnosis. Cases that met the inclusion criteria were divided into two arms [102 subjects to take HCQ (a loading dose of 400 mg twice daily given orally, followed by a maintenance dose of 200 mg twice daily for 4 days), and 100 subjects were used as a control group]. A follow-up for all the participants on daily basis for 14 days for any signs and symptoms (fever, cough, and shortness of breath). The main variables are action profile (represented by Area under the curve (AUC) for fever, cough, and shortness of breath statistically analyzed to differentiate between the two groups. RESULTS: Data in this study showed that HCQ was effective in reducing body temperature from the first day to the fifth day; this positive effect was significant with (p < 0.001) compared with subjects who didn't receive HCQ. While there was no significant effect on cough or Shortness of breath. CONCLUSION: The recommendation of this study is to utilize HCQ to all subjects with asymptomatic COVID-19 infection providing that these subjects are within the inclusion criteria of this study. There was no adverse drug reaction observed for HCQ on daily follow-up.

Modelling and Differential Quantification of Electric Cell-Substrate Impedance Sensing Growth Curves.

Measurement of cell surface coverage has become a common technique for the assessment of growth behavior of cells. As an indirect measurement method, this can be accomplished by monitoring changes in electrode impedance, which constitutes the basis of electric cell-substrate impedance sensing (ECIS). ECIS typically yields growth curves where impedance is plotted against time, and changes in single cell growth behavior or cell proliferation can be displayed without significantly impacting cell physiology. To provide better comparability of ECIS curves in different experimental settings, we developed a large toolset of R scripts for their transformation and quantification. They allow importing growth curves generated by ECIS systems, edit, transform, graph and analyze them while delivering quantitative data extracted from reference points on the curve. Quantification is implemented through three different curve fit algorithms (smoothing spline, logistic model, segmented regression). From the obtained models, curve reference points such as the first derivative maximum, segmentation knots and area under the curve are then extracted. The scripts were tested for general applicability in real-life cell culture experiments on partly anonymized cell lines, a calibration setup with a cell dilution series of impedance versus seeded cell number and finally IPEC-J2 cells treated with 1% and 5% ethanol.