Rapid Determination of Saponins in the Honey-Fried Processing of Rhizoma Cimicifugae by Near Infrared Diffuse Reflectance Spectroscopy.

ObjectiveA model of Near Infrared Diffuse Reflectance Spectroscopy (NIR-DRS) was established for the first time to determine the content of Shengmaxinside I in the honey-fried processing of Rhizoma Cimicifugae.MethodsShengmaxinside I content was determined by high-performance liquid chromatography (HPLC), and the data of the honey-fried processing of Rhizoma Cimicifugae samples from different batches of different origins by NIR-DRS were collected by TQ Analyst 8.0. Partial Least Squares (PLS) analysis was used to establish a near-infrared quantitative model.ResultsThe determination coefficient R² was 0.9878. The Cross-Validation Root Mean Square Error (RMSECV) was 0.0193%, validating the model with a validation set. The Root Mean Square Error of Prediction (RMSEP) was 0.1064%. The ratio of the standard deviation for the validation samples to the standard error of prediction (RPD) was 5.5130.ConclusionThis method is convenient and efficient, and the experimentally established model has good prediction ability, and can be used for the rapid determination of Shengmaxinside I content in the honey-fried processing of Rhizoma Cimicifugae

Learning to Adapt CLIP for Few-Shot Monocular Depth Estimation

Pre-trained Vision-Language Models (VLMs), such as CLIP, have shown enhanced performance across a range of tasks that involve the integration of visual and linguistic modalities. When CLIP is used for depth estimation tasks, the patches, divided from the input images, can be combined with a series of semantic descriptions of the depth information to obtain similarity results. The coarse estimation of depth is then achieved by weighting and summing the depth values, called depth bins, corresponding to the predefined semantic descriptions. The zero-shot approach circumvents the computational and time-intensive nature of traditional fully-supervised depth estimation methods. However, this method, utilizing fixed depth bins, may not effectively generalize as images from different scenes may exhibit distinct depth distributions. To address this challenge, we propose a few-shot-based method which learns to adapt the VLMs for monocular depth estimation to balance training costs and generalization capabilities. Specifically, it assigns different depth bins for different scenes, which can be selected by the model during inference. Additionally, we incorporate learnable prompts to preprocess the input text to convert the easily human-understood text into easily model-understood vectors and further enhance the performance. With only one image per scene for training, our extensive experiment results on the NYU V2 and KITTI dataset demonstrate that our method outperforms the previous state-of-the-art method by up to 10.6\% in terms of MARE.Comment: Accepted by WACV 202

Learning Procedure-aware Video Representation from Instructional Videos and Their Narrations

The abundance of instructional videos and their narrations over the Internet offers an exciting avenue for understanding procedural activities. In this work, we propose to learn video representation that encodes both action steps and their temporal ordering, based on a large-scale dataset of web instructional videos and their narrations, without using human annotations. Our method jointly learns a video representation to encode individual step concepts, and a deep probabilistic model to capture both temporal dependencies and immense individual variations in the step ordering. We empirically demonstrate that learning temporal ordering not only enables new capabilities for procedure reasoning, but also reinforces the recognition of individual steps. Our model significantly advances the state-of-the-art results on step classification (+2.8% / +3.3% on COIN / EPIC-Kitchens) and step forecasting (+7.4% on COIN). Moreover, our model attains promising results in zero-shot inference for step classification and forecasting, as well as in predicting diverse and plausible steps for incomplete procedures. Our code is available at https://github.com/facebookresearch/ProcedureVRL.Comment: Accepted to CVPR 202

Prevalence and risk factors of atopic dermatitis in Chinese children aged 1–7 years: a systematic review and meta analysis

IntroductionAtopic dermatitis (AD) is a common, chronic, recurrent inflammatory skin disease. To date, no meta-analysis have been conducted on the prevalence and risk factors of AD in children aged 1–7 years in Mainland China.MethodsWe conducted a meta-analysis of the prevalence and risk factors of AD among children aged 1–7 years in China. Chinese and English publications were searched in Chinese and English databases on AD epidemiology published between 1999 and 2023. Two researchers independently screened the literature, extracted the data, and evaluated their quality. A meta-analysis was performed using a random-effects model (I2 > 50%) with 95% confidence intervals (CIs) for the forest plots. Data were processed using the RevMan 5.3.ResultsNineteen studies (data from 127,660 samples) met the inclusion criteria. The pooled prevalence of AD in Chinese children aged 1–7 years was 8%. Over the last decade, the prevalence of AD has increased. The prevalence of AD among children in southern China was higher than that in northern China and was the highest at the provincial level in Zhejiang, Shanxi, and Anhui. The prevalence of AD was dependent on the family history of allergy, passive smoking, households with pets, plush toys, and residential area.DiscussionThe prevalence of AD in children (age 1–7 years) in China has increased. Further studies are needed to monitor the prevalence of AD in Chinese children. Therefore, early prevention and screening should be performed for children with a family history of AD, and their living environment should be improved to reduce allergen stimulation, thus reducing the development of AD

Stratospheric PULSE–continental cold air outbreak coupling relationships: Interannual and interdecadal changes

Stratospheric processes and their role in weather and climate have attracted increasing interests. The correspondence between the occurrence of pulse-like, stronger stratospheric poleward warm airmass transport (PULSE) events and the continental-scale cold air outbreak (CAO) events in northern hemispheric winter is found to be unstable from year to year. This increases the difficulties in utilizing the more predictable stratospheric variability in the sub-seasonal forecasts of CAOs, which can cause cold hazards. Using the ERA5 reanalysis data covering 37 winters (November–March) in the period 1979–2015, this study categorizes the CAO events over mid-latitudes of Eurasia (CAO_EA) and those over North America (CAO_NA) into two groups: those coupled with and those decoupled with the PULSE events. The coupled CAOs are further categorized into events that are, respectively, lead-coupled and lag-coupled with PULSEs. The intensity and affected area of extremely cold temperatures tend to be larger during CAOs that are coupled with PULSEs, particularly during the CAO_NA events that are lag-coupled with PULSEs and the CAO_EA events that are lead-coupled with PULSEs. Remarkable interannual and interdecadal variations are observed in the percentage of CAOs that are coupled with PULSEs for each winter, which is an important reference for determining the window of opportunity for skillful sub-seasonal forecasts of CAO by using the stratospheric signals. At both interdecadal and interannual timescales, a warm phase of the El Niño–Southern Oscillation (ENSO) in winter is favorable for the higher lag-coupling rate of CAO_NA and the lead-coupling rate of CAO_EA, and vice versa. The ENSO signals related to the interdecadal changes of the CAO coupling rate in winter can be traced back to the previous winter, while an ENSO phase transition from the previous winter to the current winter is closely related to the interannual changes of the CAO coupling rate

A novel pathogenic species of genus Stenotrophomonas: Stenotrophomonas pigmentata sp. nov

IntroductionStenotrophomonas is a prominent genus owing to its dual nature. Species of this genus have many applications in industry and agriculture as plant growth-promoting rhizobacteria and microbial biological control agents, whereas species such as Stenotrophomonas maltophilia are considered one of the leading gram-negative multi-drug-resistant bacterial pathogens because of their high contribution to the increase in crude mortality and significant clinical challenge. Pathogenic Stenotrophomonas species and most clinical isolates belong to the Stenotrophomonas maltophilia complex (SMc). However, a strain highly homologous to S. terrae was isolated from a patient with pulmonary tuberculosis (TB), which aroused our interest, as S. terrae belongs to a relatively distant clade from SMc and there have been no human association reports.MethodsThe pathogenicity, immunological and biochemical characteristics of 610A2T were systematically evaluated.Results610A2T is a new species of genus Stenotrophomonas, which is named as Stenotrophomonas pigmentata sp. nov. for its obvious brown water-soluble pigment. 610A2T is pathogenic and caused significant weight loss, pulmonary congestion, and blood transmission in mice because it has multiple virulence factors, haemolysis, and strong biofilm formation abilities. In addition, the cytokine response induced by this strain was similar to that observed in patients with TB, and the strain was resistant to half of the anti-TB drugs.ConclusionsThe pathogenicity of 610A2T may not be weaker than that of S. maltophilia. Its isolation extended the opportunistic pathogenic species to all 3 major clades of the genus Stenotrophomonas, indicating that the clinical importance of species of Stenotrophomonas other than S. maltophilia and potential risks to biological safety associated with the use of Stenotrophomonas require more attention

Leaf nutrient traits of planted forests demonstrate a heightened sensitivity to environmental changes compared to natural forests

Leaf nutrient content (nitrogen, phosphorus) and their stoichiometric ratio (N/P) as key functional traits can reflect plant survival strategies and predict ecosystem productivity responses to environmental changes. Previous research on leaf nutrient traits has primarily focused on the species level with limited spatial scale, making it challenging to quantify the variability and influencing factors of forest leaf nutrient traits on a macro scale. This study, based on field surveys and literature collected from 2005 to 2020 on 384 planted forests and 541 natural forests in China, investigates the differences in leaf nutrient traits between forest types (planted forests, natural forests) and their driving factors. Results show that leaf nutrient traits (leaf nitrogen content (LN), leaf phosphorus content (LP), and leaf N/P ratio) of planted forests are significantly higher than those of natural forests (P< 0.05). The impact of climatic and soil factors on the variability of leaf nutrient traits in planted forests is greater than that in natural forests. With increasing forest age, natural forests significantly increase in leaf nitrogen and phosphorus content, with a significant decrease in N/P ratio (P< 0.05). Climatic factors are key environmental factors dominating the spatial variability of leaf nutrient traits. They not only directly affect leaf nutrient traits of planted and natural forest communities but also indirectly through regulation of soil nutrients and stand factors, with their direct effects being more significant than their indirect effects

Efficacy of PBTZ169 and pretomanid against Mycobacterium avium, Mycobacterium abscessus, Mycobacterium chelonae, and Mycobacterium fortuitum in BALB/c mice models

ObjectivesWe aimed to evaluate the activity of PBTZ169 and pretomanid against non-tuberculous mycobacteriosis (NTM) in vitro and in vivo.MethodsThe minimum inhibitory concentrations (MICs) of 11 antibiotics, against slow-growing mycobacteria (SGMs) and rapid-growing mycobacteria (RGMs) were tested using the microplate alamarBlue assay. The in vivo activities of bedaquiline, clofazimine, moxifloxacin, rifabutin, PBTZ169 and pretomanid against four common NTMs were assessed in murine models.ResultsPBTZ169 and pretomanid had MICs of >32 μg/mL against most NTM reference and clinical strains. However, PBTZ169 was bactericidal against Mycobacterium abscessus (3.33 and 1.49 log10 CFU reductions in the lungs and spleen, respectively) and Mycobacterium chelonae (2.29 and 2.24 CFU reductions in the lungs and spleen, respectively) in mice, and bacteriostatic against Mycobacterium avium and Mycobacterium fortuitum. Pretomanid dramatically decreased the CFU counts of M. abscessus (3.12 and 2.30 log10 CFU reductions in the lungs and spleen, respectively), whereas it showed moderate inhibition of M. chelonae and M. fortuitum. Bedaquiline, clofazimine, and moxifloxacin showed good activities against four NTMs in vitro and in vivo. Rifabutin did not inhibit M. avium and M. abscessus in mice.ConclusionPBTZ169 appears to be a candidate for treating four common NTM infections. Pretomanid was more active against M. abscessus, M. chelonae and M. fortuitum than against M. avium