DRUG RELEASE AND PHARMACOKINETIC PROPERTIES OF LIPOSOMAL DB-67

Sterically stabilized liposomes with saturated lipid as the major lipid component (DSPC:m-PEGDSPE were applied in DB-67 delivery. The drug retention in vitro and pharmacokinetic properties in vivo were investigated. Liposomal DB-67 was cleared faster from the circulation in the larger liposomes (~180 nm) than in the smaller ones (~120 nm), even though DB-67 was retained longer in smaller size liposomes in vitro. Liposomal DB-67 clearance was increased when cholesterol was present in the liposomal composition (40 mole %). It can be attributable to the faster drug release from cholesterol containing liposomes as compared to liposomes without cholesterol. Cholesterol free liposomes with smaller particle size (~120 nm) were chosen as the optimal formulation. In addition, high lipid doses led to the lower clearance of liposomal DB-67 because the liposomal carriers were retained in the circulation longer. Liposomes of larger particle size were taken up by the liver and spleen to a greater extent than the smaller ones. But cholesterol content and lipid dose did not alter the tissue uptake of liposomes. The area under the DB-67 plasma concentration-time curve (AUC) for liposomal DB-67 was 40-fold higher that for non-liposomal DB-67

A Brief Analysis of Translation Errors in Subtitle of the Movie The Wandering Earth

In recent years, film industry of China has developed rapidly. There have been a lot of high-quality movies which enter into the international market. Therefore, subtitle translation is so crucial to win more overseas audiences to effectively disseminate Chinese culture and display the soft power of China. This paper takes the Chinese and English subtitles of the Movie The Wandering Earth as the research object. It puts forward three categories of translation errors according to Nord’s theory and analyzes the examples of translation errors in the movie in order to provide references for movie subtitle translation.

Systematic Analysis of Impact of Sampling Regions and Storage Methods on Fecal Gut Microbiome and Metabolome Profiles.

The contribution of human gastrointestinal (GI) microbiota and metabolites to host health has recently become much clearer. However, many confounding factors can influence the accuracy of gut microbiome and metabolome studies, resulting in inconsistencies in published results. In this study, we systematically investigated the effects of fecal sampling regions and storage and retrieval conditions on gut microbiome and metabolite profiles from three healthy children. Our analysis indicated that compared to homogenized and snap-frozen samples (standard control [SC]), different sampling regions did not affect microbial community alpha diversity, while a total of 22 of 176 identified metabolites varied significantly across different sampling regions. In contrast, storage conditions significantly influenced the microbiome and metabolome. Short-term room temperature storage had a minimal effect on the microbiome and metabolome profiles. Sample storage in RNALater showed a significant level of variation in both microbiome and metabolome profiles, independent of the storage or retrieval conditions. The effect of RNALater on the metabolome was stronger than the effect on the microbiome, and individual variability between study participants outweighed the effect of RNALater on the microbiome. We conclude that homogenizing stool samples was critical for metabolomic analysis but not necessary for microbiome analysis. Short-term room temperature storage had a minimal effect on the microbiome and metabolome profiles and is recommended for short-term fecal sample storage. In addition, our study indicates that the use of RNALater as a storage medium of stool samples for microbial and metabolomic analyses is not recommended.IMPORTANCE The gastrointestinal microbiome and metabolome can provide a new angle to understand the development of health and disease. Stool samples are most frequently used for large-scale cohort studies. Standardized procedures for stool sample handling and storage can be a determining factor for performing microbiome or metabolome studies. In this study, we focused on the effects of stool sampling regions and stool sample storage conditions on variations in the gut microbiome composition and metabolome profile

Neural Activity Is Dynamically Modulated by Memory Load During the Maintenance of Spatial Objects

Visuospatial working memory (WM) is a fundamental but severely limited ability to temporarily remember selected stimuli. Several studies have investigated the underlying neural mechanisms of maintaining various visuospatial stimuli simultaneously (i.e., WM load, the number of representations that need to be maintained in WM). However, two confounding factors, namely verbal representation and encoding load (the number of items that need to be encoded into WM), have not been well controlled in previous studies. In this study, we developed a novel delayed-match-to-sample task (DMST) controlling for these two confounding factors and recorded scalp EEG signals during the task. We found that behavioral performance deteriorated severely as memory load increased. Neural activity was modulated by WM load in a dynamic manner. Specifically, higher memory load induced stronger amplitude in occipital and central channel-clusters during the early delay period, while the inverse trend was observed in central and frontal channel-clusters during late delay. In addition, the same inverse memory load effect, that was lower memory load induced stronger amplitude, was observed in occipital channel-cluster alpha power during late delay. Finally, significant correlations between neural activity and individual reaction time showed a role of late-delay central and frontal channel-cluster amplitude in predicting behavioral performance. Because the occipital cortex is important for visual information maintenance, the decrease in alpha oscillation was consistent with the cognitive role that is “gating by inhibition.” Together, our results from a well-controlled DMST suggest that WM load not exerted constant but dynamic effect on neural activity during maintenance of visuospatial objects

Generalizable Re-Identification from Videos with Cycle Association

In this paper, we are interested in learning a generalizable person re-identification (re-ID) representation from unlabeled videos. Compared with 1) the popular unsupervised re-ID setting where the training and test sets are typically under the same domain, and 2) the popular domain generalization (DG) re-ID setting where the training samples are labeled, our novel scenario combines their key challenges: the training samples are unlabeled, and collected form various domains which do no align with the test domain. In other words, we aim to learn a representation in an unsupervised manner and directly use the learned representation for re-ID in novel domains. To fulfill this goal, we make two main contributions: First, we propose Cycle Association (CycAs), a scalable self-supervised learning method for re-ID with low training complexity; and second, we construct a large-scale unlabeled re-ID dataset named LMP-video, tailored for the proposed method. Specifically, CycAs learns re-ID features by enforcing cycle consistency of instance association between temporally successive video frame pairs, and the training cost is merely linear to the data size, making large-scale training possible. On the other hand, the LMP-video dataset is extremely large, containing 50 million unlabeled person images cropped from over 10K Youtube videos, therefore is sufficient to serve as fertile soil for self-supervised learning. Trained on LMP-video, we show that CycAs learns good generalization towards novel domains. The achieved results sometimes even outperform supervised domain generalizable models. Remarkably, CycAs achieves 82.2% Rank-1 on Market-1501 and 49.0% Rank-1 on MSMT17 with zero human annotation, surpassing state-of-the-art supervised DG re-ID methods. Moreover, we also demonstrate the superiority of CycAs under the canonical unsupervised re-ID and the pretrain-and-finetune scenarios

Pharmacokinetics and bioequivalence evaluation of acamprosate calcium tablets in healthy Chinese volunteers

AbstractBackgroundFew pharmacokinetic data of acamprosate were available in Chinese population and no medication is approved for alcohol dependence in China.Purpose1. Investigate the pharmacokinetic properties of acamprosate calcium in healthy Chinese male volunteers on single- and multiple-dose administration. 2. Compare the bioequivalence of two formulations of acamprosate calcium tablets both under fasting and fed conditions.MethodsThis open-label, randomized study included 3 stages. In each stage, a 2-way crossover bioequivalence study was conducted to study the pharmacokinetic properties and bioequivalence of acamprosate calcium tablets on multiple dosing after standardized meals, single dosing under fasting conditions and fed conditions, respectively. The washout period between each treatment in a stage and between each stage was 1week. Plasma acamprosate calcium was quantified by a validated liquid chromatography-tandem mass spectrometry (LC-MS/MS) method. Tolerability was evaluated by monitoring adverse events, physical examinations, 12-lead ECG, and laboratory tests.ResultsTotally, 36 male subjects were enrolled in the study and all of them completed the whole 3 study stages. Main pharmacokinetic parameters of test and reference formulations were as follows: multiple dosing, Tmax 9.94±6.59 and 9.47±5.47h, Cmax 435.74±348.10 and 346.54±155.66ng·mL−1, AUC0-t 8600.52±5264.77 and 9315.10±6820.03ng·mL−1·h, AUC0–∞ 8845.38±5838.18 and 9669.24±7326.53ng·mL−1·h, t1/2 10.06±8.83 and 9.87±10.35h; single dosing under fasting conditions, Tmax 7.29±4.87 and 6.57±1.85h, Cmax 247.85±110.05 and 244.64±132.43ng·mL−1, AUC0-t 3385.41±1418.92 and 3496.24±1767.29ng·mL−1·h, AUC0–∞ 3781.53±1556.96 and 3829.56±1981.25ng·mL−1·h, t1/2 13.07±17.24 and 10.26±7.78h; single dosing under fed conditions, Tmax 17.72±9.42 and 19.50±9.84h, Cmax 183.90±74.52 and 168.14±60.67ng·mL−1, AUC0-t 3181.71±1368.24 and 3575.11±1416.39ng·mL−1·h, AUC0–∞3442.39±2002.53 and 3624.44±1418.12ng·mL−1·h, t1/2 8.76±12.28 and 6.67±4.84h, respectively. In all three stages, 90% CIs for the test/reference ratio of AUC0–t and AUC0–∞ were located within 80%–125%, 90% CI for Cmax was within 70%–143%.ConclusionsSimilar pharmacokinetic results of acamprosate calcium tablets in healthy Chinese volunteers were found as those in Caucasic population. In all three stages, the two formulations met the regulatory criteria for bioequivalence.Chictr.org identifier: ChiCTR-TTRCC-14004853

Improve Deep Forest with Learnable Layerwise Augmentation Policy Schedule

As a modern ensemble technique, Deep Forest (DF) employs a cascading structure to construct deep models, providing stronger representational power compared to traditional decision forests. However, its greedy multi-layer learning procedure is prone to overfitting, limiting model effectiveness and generalizability. This paper presents an optimized Deep Forest, featuring learnable, layerwise data augmentation policy schedules. Specifically, We introduce the Cut Mix for Tabular data (CMT) augmentation technique to mitigate overfitting and develop a population-based search algorithm to tailor augmentation intensity for each layer. Additionally, we propose to incorporate outputs from intermediate layers into a checkpoint ensemble for more stable performance. Experimental results show that our method sets new state-of-the-art (SOTA) benchmarks in various tabular classification tasks, outperforming shallow tree ensembles, deep forests, deep neural network, and AutoML competitors. The learned policies also transfer effectively to Deep Forest variants, underscoring its potential for enhancing non-differentiable deep learning modules in tabular signal processing