Model-based precision dosing and remedial dosing recommendations for delayed or missed doses of isoniazid in Chinese patients with tuberculosis.

AIMS: Isoniazid (INH) has been used as a first-line drug to treat tuberculosis (TB) for more than 50 years. However, large interindividual variability was found in its pharmacokinetics, and effects of nonadherence to INH treatment and corresponding remedy regime remain unclear. This study aimed to develop a population pharmacokinetic (PPK) model of INH in Chinese patients with TB to provide model-informed precision dosing and explore appropriate remedial dosing regimens for nonadherent patients. METHODS: In total, 1012 INH observations from 736 TB patients were included. A nonlinear mixed-effects modelling was used to analyse the PPK of INH. Using Monte Carlo simulations to determine optimal dosage regimens and design remedial dosing regimens. RESULTS: A 2-compartmental model, including first-order absorption and elimination with allometric scaling, was found to best describe the PK characteristics of INH. A mixture model was used to characterize dual rates of INH elimination. Estimates of apparent clearance in fast and slow eliminators were 28.0 and 11.2 L/h, respectively. The proportion of fast eliminators in the population was estimated to be 40.5%. Monte Carlo simulations determined optimal dosage regimens for slow and fast eliminators with different body weight. For remedial dosing regimens, the missed dose should be taken as soon as possible when the delay does not exceed 12 h, and an additional dose is not needed. delay for an INH dose exceeds 12 h, the patient only needs to take the next single dose normally. CONCLUSION: PPK modelling and simulation provide valid evidence on the precision dosing and remedial dosing regimen of INH.

Modulating tumour vascular normalisation using triptolide-loaded NGR-functionalized liposomes for enhanced cancer radiotherapy.

Radiotherapy is an effective therapy in tumour treatment. However, the characteristics of the tumour microenvironment, including hypoxia, low pH, and interstitial fluid pressure bring about radioresistance. To improve the anti-tumour effect of radiotherapy, it has been demonstrated that antiangiogenic therapy can be employed to repair the structural and functional defects of tumour angiogenic vessels, thereby preventing radioresistance or poor therapeutic drug delivery. In this study, we prepared triptolide (TP)-loaded Asn-Gly-Arg (NGR) peptide conjugated mPEG2000-DSPE-targeted liposomes (NGR-PEG-TP-LPs) to induce tumour blood vessel normalisation, to the end of increasing the sensitivity of tumour cells to radiotherapy. Further, to quantify the tumour vessel normalisation window, the structure and functionality of tumour blood vessels post NGR-PEG-TP-LPs treatment were evaluated. Thereafter, the anti-tumour effect of radiotherapy following these treatments was evaluated using HCT116 xenograft-bearing mouse models based on the tumour vessel normalisation period window. The results obtained showed that NGR-PEG-TP-LPs could modulate tumour vascular normalisation to increase the oxygen content of the tumour microenvironment and enhance the efficacy of radiotherapy. Further, liver and kidney toxicity tests indicated that NGR-PEG-TP-LPs are safe for application in cancer treatment.

[Estimation and Visualization of Nitrogen Content in Citrus Canopy Based on Two Band Vegetation Index (TBVI)].

Nitrogen is a necessary and important element for the growth and development of fruit orchards. Timely, accurate and nondestructive monitoring of nitrogen status in fruit orchards would help maintain the fruit quality and efficient production of the orchard, and mitigate the pollution of water resources caused by excessive nitrogen fertilization. This study investigated the capability of hyperspectral imagery for estimating and visualizing the nitrogen content in citrus canopy. Hyperspectral images were obtained for leaf samples in laboratory as well as for the whole canopy in the field with ImSpector V10E (Spectral Imaging Ltd., Oulu, Finland). The spectral datas for each leaf sample were represented by the average spectral data extracted from the selected region of interest (ROI) in the hyperspectral images with the aid of ENVI software. The nitrogen content in each leaf sample was measured by the Dumas combustion method with the rapid N cube (Elementar Analytical, Germany). Simple correlation analysis and the two band vegetation index (TBVI) were then used to develop the spectra data-based nitrogen content prediction models. Results obtained through the formula calculation indicated that the model with the two band vegetation index (TBVI) based on the wavelengths 811 and 856 nm achieved the optimal estimation of nitrogen content in citrus leaves (R2 = 0.607 1). Furthermore, the canopy image for the identified TBVI was calculated, and the nitrogen content of the canopy was visualized by incorporating the model into the TBVI image. The tender leaves, middle-aged leaves and elder leaves showed distinct nitrogen status from highto low-levels in the canopy image. The results suggested the potential of hyperspectral imagery for the nondestructive detection and diagnosis of nitrogen status in citrus canopy in real time. Different from previous studies focused on nitrogen content prediction at leaf level, this study succeeded in predicting and visualizing the nutrient content of fruit trees at canopy level. This would provide valuable information for the implementation of individual tree-based fertilization schemes in precision orchard management practices.

[Development of prediction models for determining N content in citrus leaves based on hyperspectral imaging technology].

The present study presents prediction models for determining the N content in citrus leaves by using hyperspectral imaging technology combined with several chemometrics methods. The steps followed in this study are: hyperspectral image scanning, extracting average spectra curves, pretreatment of raw spectra data, extracting characteristic wavelengths with successive projection algorithm and developing prediction models for determining N content in citrus leaves. The authors obtained three optimal pretreatment methods through comparing eleven different pretreatment methods including Savitzky-Golay (SG) smoothing, standard normal variate (SNV), multiplicative scatter correction (MSC), first derivative (1-Der) and so on. These selected pretreatment methods are SG smoothing, detrending and SG smoothing-detrending. Based on these three pretreatment methods, the authros first extracted the characteristic wavelengths respectively with successive projection algorithm, and then used the spectral reflectance of the extracted characteristic wavelengths as input variables of partial least squares regression (PLS), multiple linear regression (MLR) and back propagation neural network (BPNN) modeling. Hence, the authors developed three prediction models with each pretreatment method, and obtained nine models in total. Among all the nine prediction models, the two models based on the methods of SG smoothing-detrending-SPA-BPNN (R(p): 0.8513, RMSEP: 0.1881) and detrending-SPABPNN (R(p): 0.8609, RMSEP: 0.1595) were found to have achieved the best prediction results. The final results show that using hyperspectra data to determine N content in citrus leaves is feasible. This would provide a theoretical basis for real-time and accurate monitoring of N content in citrus leaves as well as rational N fertilizer application during the plant's growth.

Analysis of growth dynamics in five different media and metabolic phenotypic characteristics of Piriformospora indica.

Piriformospora indica is an important endophytic fungus with broad potential for alleviating biotic and abiotic stress on host plants. This study monitored the growth dynamics of P. indica on five commonly used artificial media for microorganisms and analyzed its metabolic characteristics using Biolog Phenotype Microarray (PM) technology. The results showed that P. indica grew fastest on Potato Dextrose Agar (PDA), followed by Kidney Bean Agar (KBA), Alkyl Ester Agar (AEA), Oatmeal Agar (OA), and Luria-Bertani Agar (LB), and the most suitable medium for spore production was OA. Using Biolog PM1-10, 950 metabolic phenotypes of P. indica were obtained. P. indica could metabolize 87.89% of the tested carbon sources, 87.63% of the tested nitrogen sources, 96.61% of the tested phosphorus sources, and 100% of the tested sulfur sources. P. indica displayed 92 kinds of tested biosynthetic pathways, and it could grow under 92 kinds of tested osmotic pressures and 88 kinds of tested pH conditions. PM plates 1-2 revealed 43 efficient carbon sources, including M-Hydroxyphenyl acid, N-Acetyl-D-Glucosamine, Tyramine, Maltotrios, α-D-Glucosine, I-Erythritol, L-Valine, D-Melezitose, D-Tagatose, and Turanose. PM plates 3,6-8 indicated 170 efficient nitrogen sources, including Adenosine, Inosine Allantoin, D, L-Lactamide, Arg-Met, lle-Trp, Ala-Arg, Thr-Arg, Trp-Tyr, Val-Asn, Gly-Gly-D-Leu, Gly-Gly-Phe, and Leu-Leu-Leu. This study demonstrates that P. indica can metabolize a variety of substrates, such as carbon and nitrogen sources, and has a wide range of environmental adaptability. The growth dynamics on artificial culture media and metabolic phenotypes of P. indica can be used to investigate its biological characteristics, screen for more suitable growth and sporulation conditions, and elucidate the physiological mechanisms that enhance the stress resistance of host plants. This study provides a theoretical basis for its better application in agriculture.

Latamoxef-induced severe thrombocytopenia during the treatment of pulmonary infection: A case report.

BACKGROUND: Latamoxef shows excellent antibacterial activity against anaerobic bacteria such as Bacteroides fragilis. Reports of thrombocytopenic toxicity of latamoxef are limited. This report presents a case of severe thrombocytopenia possibly induced by latamoxef, an infrequent adverse drug reaction in a young patient with tuberculosis and Crohn's disease in China. CASE SUMMARY: We reported a case of severe thrombocytopenia induced by latamoxef in a 28-year-old man with tuberculosis and Crohn's disease. On admission, the patient presented with a cough productive of bloody sputum, a chest computed tomogram suggested scattered mottled, high-density shadows in both lungs. Laboratory tests indicated a platelet count of 140000/µL. Considered a pulmonary bacterial infection, the patient received anti-infection therapy with latamoxef (dose: 2.0 g) intravenously Q12h. On the 9th day of treatment, the platelet count decreased to 44000/µL. On the 12th day, scattered purpura and ecchymosis appeared on the patient's limbs and trunk, and the platelet count decreased to 9000/µL after latamoxef treatment for 15 d. Three days after discontinuation of latamoxef, the platelet count recovered to 157000/µL, and the area of scattered purpura and ecchymosis on the limbs and trunk decreased. The platelet counts remained in the normal range, and no thrombocytopenia was found at follow-up 15 mo after discharge. CONCLUSION: For patients treated with latamoxef, platelet counts should be carefully followed, and caregivers should be vigilant for the appearance of scattered ecchymosis.

Precision Cardio-Oncology: Use of Mechanistic Pharmacokinetic and Pharmacodynamic Modeling to Predict Cardiotoxicities of Anti-Cancer Drugs.

The cardiotoxicity of anti-cancer drugs presents as a challenge to both clinicians and patients. Significant advances in cancer treatments have improved patient survival rates, but have also led to the chronic effects of anti-cancer therapies becoming more prominent. Additionally, it is difficult to clinically predict the occurrence of cardiovascular toxicities given that they can be transient or irreversible, with large between-subject variabilities. Further, cardiotoxicities present a range of different symptoms and pathophysiological mechanisms. These notwithstanding, mechanistic pharmacokinetic (PK) and pharmacodynamic (PD) modeling offers an important approach to predict cardiotoxicities and offering precise cardio-oncological care. Efforts have been made to integrate the structures of physiological and pharmacological networks into PK-PD modeling to the end of predicting cardiotoxicities based on clinical evaluation as well as individual variabilities, such as protein expression, and physiological changes under different disease states. Thus, this review aims to report recent progress in the use of PK-PD modeling to predict cardiovascular toxicities, as well as its application in anti-cancer therapies.

Two new lankacidin-related metabolites from Streptomyces sp. HS-NF-1178.

Two new lankacidin-related metabolites, 2,18-seco-lankacidinol A (1), 2,18-seco-lankacidinol B (2) and a known compound, lankacidinol (3), were isolated from the fermentation broth of Streptomyces sp. HS-NF-1178. Their structures were determined on the basis of spectroscopic analysis, including 1D and 2D NMR techniques as well as ESI-MS and comparison with data from the literature. These two new compounds, especially compound 1, exhibited potent antitumor activity.

Rapamycin-ameliorated diabetic symptoms involved in increasing adiponectin expression in diabetic mice on a high-fat diet.

Recent studies showed that rapamycin improved diabetic complications. Here, we investigated the metabolic effects of rapamycin in type 2 diabetes model (T2DM) mice. Mice were treated with a daily intraperitoneal injection of rapamycin at 2 mg/kg or vehicle only for 3 weeks and were maintained on a high-fat diet. The treated diabetic mice exhibited decreased body weight, blood glucose levels, and fat mass. FGF21 expression was suppressed in C57B/L6 mice, but adiponectin expression increased both in FGF21 KO and C57B/L6 mice. These results suggest that rapamycin may alleviate FGF21 resistance in mice on a high-fat diet. The reduction of adipose tissue mass of the diabetic mice may be due to the increased adiponectin.

A new tetrahydrobenzofuranone metabolite from Streptomyces sp. HS-NF-853.

A new tetrahydrobenzofuranone derivative, strefuranone A (1), was isolated from Streptomyces sp. HS-NF-853. The structure of the compound was elucidated on the basis of MS and extensive NMR analysis.