热疗对肿瘤免疫微环境中免疫细胞及免疫相关细胞因子的影响

随着对肿瘤热疗和肿瘤免疫微环境(TIME)的深入研究,近年来热疗对TIME的作用越来越受到学者们的重视。本文就目前国内外研究进展,对热疗与TIME中几类主要免疫细胞和免疫相关细胞因子的影响及作用机制作一综述。全面而透彻的了解热疗对TIME的调控作用,有助于为肿瘤治疗提供新的思路和方法。     

Family Caregivers' Subjective Caregiving Burden,Quality of Life,and Depressive Symptoms Are Associated With Terminally Ill Cancer Patients' Distinct Patterns of Conjoint Symptom Distress and Functional Impairment in Their Last Six Months of Life

Context

Family caregivers constitute a critical component of the end-of-life care system with considerable cost to themselves. However, the joint association of terminally ill cancer patients' symptom distress and functional impairment with caregivers' subjective caregiving burden, quality of life (QOL), and depressive symptoms remains unknown.

Learning to Discretize: Solving 1D Scalar Conservation Laws via Deep Reinforcement Learning

Conservation laws are considered to be fundamental laws of nature. It has broad applications in many fields, including physics, chemistry, biology, geology, and engineering. Solving the differential equations associated with conservation laws is a major branch in computational mathematics. The recent success of machine learning, especially deep learning in areas such as computer vision and natural language processing, has attracted a lot of attention from the community of computational mathematics and inspired many intriguing works in combining machine learning with traditional methods. In this paper, we are the first to view numerical PDE solvers as an MDP and to use (deep) RL to learn new solvers. As proof of concept, we focus on 1-dimensional scalar conservation laws. We deploy the machinery of deep reinforcement learning to train a policy network that can decide on how the numerical solutions should be approximated in a sequential and spatial-temporal adaptive manner. We will show that the problem of solving conservation laws can be naturally viewed as a sequential decision-making process, and the numerical schemes learned in such a way can easily enforce long-term accuracy. Furthermore, the learned policy network is carefully designed to determine a good local discrete approximation based on the current state of the solution, which essentially makes the proposed method a meta-learning approach. In other words, the proposed method is capable of learning how to discretize for a given situation mimicking human experts. Finally, we will provide details on how the policy network is trained, how well it performs compared with some state-of-the-art numerical solvers such as WENO schemes, and supervised learning based approach L3D and PINN, and how well it generalizes.     

Correction of frequency and phase variations induced by eddy currents in localized spectroscopy with multiple echo times.

As a consequence of the time-varying magnetic field induced by eddy currents, frequency drifting occurs when the sampling window of localized spectroscopy continuously shifts. The frequency drifting and the concomitant phase variations can severely affect spectroscopy results when data are acquired with multiple echo times (TEs), such as in the measurement of glutamate (Glu) concentration using the TE-averaged method. Specifically, the averaged spectra are further broadened and distorted in the presence of residual eddy currents, and editing of the coupled spins of Glu C4 protons is affected, resulting in errors in the measured relative intensity ratio. Postacquisition correction using unsuppressed water as reference can effectively minimize this detrimental effect, as manifested by the significantly enhanced signal intensity. Also, it is demonstrated that the methyl signals of creatine (Cr) at 3.0 ppm and choline (Cho) at 3.2 ppm can be used as internal references in finding frequency and phase disparities between different TEs.     

166Ho-DOTMP radiation-absorbed dose estimation for skeletal targeted radiotherapy.

166Ho-1,4,7,10-tetraazacyclododecane-1,4,7,10-tetramethylene-phosphonate (DOTMP) is a tetraphosphonate molecule radiolabeled with 166Ho that localizes to bone surfaces. This study evaluated pharmacokinetics and radiation-absorbed dose to all organs from this beta-emitting radiopharmaceutical. METHODS: After two 1.1-GBq administrations of 166Ho-DOTMP, data from whole-body counting using a gamma-camera or uptake probe were assessed for reproducibility of whole-body retention in 12 patients with multiple myeloma. The radiation-absorbed dose to normal organs was estimated using MIRD methodology, applying residence times and S values for 166Ho. Marrow dose was estimated from measured activity retained after 18 h. The activity to deliver a therapeutic dose of 25 Gy to the marrow was determined. Methods based on region-of-interest (ROI) and whole-body clearance were evaluated to estimate kidney activity, because the radiotracer is rapidly excreted in the urine. The dose to the surface of the bladder wall was estimated using a dynamic bladder model. RESULTS: In clinical practice, gamma-camera methods were more reliable than uptake probe-based methods for whole-body counting. The intrapatient variability of dose calculations was less than 10% between the 2 tracer studies. Skeletal uptake of 166Ho-DOTMP varied from 19% to 39% (mean, 28%). The activity of 166Ho prescribed for therapy ranged from 38 to 67 GBq (1,030-1,810 mCi). After high-dose therapy, the estimates of absorbed dose to the kidney varied from 1.6 to 4 Gy using the whole-body clearance-based method and from 8.3 to 17.3 Gy using the ROI-based method. Bladder dose ranged from 10 to 20 Gy, bone surface dose ranged from 39 to 57 Gy, and doses to other organs were less than 2 Gy for all patients. Repetitive administration had no impact on tracer biodistribution, pharmacokinetics, or organ dose. CONCLUSION: Pharmacokinetics analysis validated gamma-camera whole-body counting of 166Ho as an appropriate approach to assess clearance and to estimate radiation-absorbed dose to normal organs except the kidneys. Quantitative gamma-camera imaging is difficult and requires scatter subtraction because of the multiple energy emissions of 166Ho. Kidney dose estimates were approximately 5-fold higher when the ROI-based method was used rather than the clearance-based model, and neither appeared reliable. In future clinical trials with 166Ho-DOTMP, we recommend that dose estimation based on the methods described here be used for all organs except the kidneys. Assumptions for the kidney dose require further evaluation.     

中草药灌肠液＋西医药治疗慢性结肠炎66例体会

目的 探讨中西医结合治疗慢性结肠炎的体会。方法 对采用中草药灌肠液E＋西医药治疗66例慢性结肠炎的临床观察进行分析。结果66例患者中，有效率达96％左右。结论 慢性结肠炎是我国的常见病及多发病，采用中草药＋西医药治疗，效果好，药价低廉，操作简便，值得推广，应予重视。