Efficacy and safety of self-made WenyangJianpi-qushi Decoction combined with mometasone furoate cream in the treatment of atopic dermatitis of spleen deficiency and dampness accumulation type.

Introduction: This work was to explore the efficacy and safety of self-made WenyangJianpi-qushi Decoction plus mometasone furoate cream in atopic dermatitis (AD) of spleen deficiency and dampness accumulation type. Material and method: 120 patients with this kind of atopic dermatitis were grouped: The Observation group (disease health education + basic treatment + mometasone furoate cream + self-made Decoction) and The Control group (disease health education + basic treatment + mometasone furoate cream), 60 cases in each group. The SCORAD score, serum IgE level, peripheral blood eosinophils, adverse events, recurrence rate, and total effective rate after treatment were observed.Result: Through treatment, SCORAD score of the observation group (29.96 ± 2.88) was lower as against controls (36.04 ± 3.12), p < 0.05. Through treatment, the peripheral blood eosinophil count in the observation group was (311.26 ± 50.19) 106/L, which was lower than (582.71 ± 54.75) 106/L in controls; the serum lgE of the observation group was (712.44 ± 93.32) IU/mL, which was lower than the controls (890.12 ± 81.25) IU/mL, p < 0.05. The Observation group (56/60, 93.33%) demonstrated superior total effective rate to the controls (34/60, 56.67%); The recurrence rate of the observation group was 4/60 (6.67%), which was lower than the controls 16/60 (26.67%), p < 0.05.Conclusion: Self-made WenyangJianpi-qushi Decoction plus mometasone furoate cream to treat atopic dermatitis of spleen deficiency and dampness accumulation type has significant efficacy and good safety.

Nanoplastics impair growth and nitrogen fixation of marine nitrogen-fixing cyanobacteria.

Nanoplastics pollution is a growing environmental problem worldwide. Recent research has demonstrated the toxic effects of nanoplastics on various marine organisms. However, the influences of nanoplastics on marine nitrogen-fixing cyanobacteria, a critical nitrogen source in the ocean, remained unknown. Here, we report that nanoplastics exposure significantly reduced growth, photosynthetic, and nitrogen fixation rates of Crocosphaera watsonii (a major marine nitrogen-fixing cyanobacterium). Transcriptomic analysis revealed that nanoplastics might harm C. watsonii via downregulation of photosynthetic pathways and DNA damage repair genes, while genes for respiration, cell damage, nitrogen limitation, and iron (and phosphorus) scavenging were upregulated. The number and size of starch grains and electron-dense vacuoles increased significantly after nanoplastics exposure, suggesting that C. watsonii allocated more resources to storage instead of growth under stress. We propose that nanoplastics can damage the cell (e.g., DNA, cell membrane, and membrane-bound transporters), inhibit nitrogen and carbon fixation, and hence lead to nutrient limitation and impaired growth. Our findings suggest the possibility that nanoplastics pollution could reduce the new nitrogen input and hence affect the productivity in the ocean. The impact of nanoplastics on marine nitrogen fixation and productivity should be considered when predicting the ecosystem response and biogeochemical cycling in the changing ocean.

Corrigendum: Infratentorial superficial siderosis: report of six cases and review of the literature.

[This corrects the article DOI: 10.3389/fnins.2024.1373358.].

Infratentorial superficial siderosis: report of six cases and review of the literature.

Objectives: To investigate the etiology, clinical manifestations, imaging features, and treatment of patients with infratentorial superficial siderosis (iSS), enhance clinicians' comprehension of this rare disease, and conduct oral deferiprone intervention and subsequent monitoring. Methods: Six patients diagnosed with iSS based on magnetic resonance imaging (MRI) and susceptibility weighted imaging (SWI) were enrolled from 2021 to 2023 at the First Affiliated Hospital of Fujian Medical University. Their clinical datas were summarized, and the etiology and imaging characteristics were analyzed. Follow-up was conducted through telephone or outpatient visits. Results: Among the 6 patients, there were 3 males and 3 females. The onset age ranged from 35 to 71 years, with an average onset age of 53 years. The clinical symptoms mainly included acoustic disturbances (6/6), gait imbalance (6/6), dysolfactory (6/6), cognitive impairment (2/6), epilepsy (2/6), and pyramidal tract sign (2/6). Evidence of superficial siderosis was observed on MRI across the cortex, brainstem, cerebellum, and spinal cord in all patients. T2-space sequence MRI revealed two instances of dural tear. During the follow-up period ranging from 1 month to 3 years, three patients who received oral deferiprone treatment showed improvement, whereas the remaining three patients who declined deferiprone treatment demonstrated progression. Conclusion: The primary clinical manifestations of iSS include bilateral sensorineural hearing disturbances, progressive cerebellar ataxia, and spinal cord lesions. The key diagnostic criteria involve the presence of linear hypointensity on T2-WI in the surface region of the nervous system. Dural tear caused by various factors is considered to be the most common cause of iSS, and its treatment mainly involves surgical intervention for hemorrhagic primary diseases as well as pharmacotherapy with deferiprone.

Lightweight aerial image object detection algorithm based on improved YOLOv5s.

YOLOv5 is one of the most popular object detection algorithms, which is divided into multiple series according to the control of network depth and width. To realize the deployment of mobile devices or embedded devices, the paper proposes a lightweight aerial image object detection algorithm (LAI-YOLOv5s) based on the improvement of YOLOv5s with a relatively small amount of calculation and parameter and relatively fast reasoning speed. Firstly, to better detect small objects, the paper replaces the minimum detection head with the maximum detection head and proposes a new feature fusion method, DFM-CPFN(Deep Feature Map Cross Path Fusion Network), to enrich the semantic information of deep features. Secondly, the paper designs a new module based on VoVNet to improve the feature extraction ability of the backbone network. Finally, based on the idea of ShuffleNetV2, the paper makes the network more lightweight without affecting detection accuracy. Based on the VisDrone2019 dataset, the detection accuracy of LAI-YOLOv5s on the mAP@0.5 index is 8.3% higher than that of the original algorithm. Compared with other series of YOLOv5 and YOLOv3 algorithms, LAI-YOLOv5s has the advantages of low computational cost and high detection accuracy.

Hypoxia and warming take sides with small marine protists: An integrated laboratory and field study.

Hypoxia and ocean warming are two mounting global environmental threats influencing marine ecosystems. However, the interactive effects of rising temperature and depleted dissolved oxygen (DO) on marine protists remains unknown. Here, we conducted a series of laboratory experiments on four protozoa with distinct cell sizes to investigate the combined effects of temperature (19, 22, 25, 28, and 31 °C) and oxygen availability (hypoxia, 2 mg DO L-1 and normoxia, 7 mg DO L-1) on their physiological performances (i.e., growth, ingestion, and respiration rates). The hypoxia-induced inhibition in three physiological rates increased with the biovolume of the protists. As the larger surface area to volume (SA/V) quotients of smaller protists facilitate higher capabilities of oxygen absorption and utilization, the smaller protists suffered less inhibitions induced by hypoxia. Moreover, the hypoxia-induced inhibition in physiological rates was exacerbated by increasing temperature, which can be verified by the reductions in the temperature sensitivities (represented by the activation energy, E). These results suggest that hypoxia could lead to a shift of protistan community with enhanced domination of small protists, and warming could exacerbate such a trend. We further examined our laboratory results in the Pearl River Estuary, where extensive bottom hypoxia often occurs in summer. We found the mean protist biovolume in hypoxic waters was significantly lower than that at normal stations. Also, the mean protist biovolume decreased with declining DO concentration and rising temperature, indicating the interactive effect of temperature and oxygen availability. Collectively, we suggest that hypoxia could cause a higher proportion of small-sized cells in the marine protistan community, and the projected ocean warming could intensify the tendency, which could undermine the capacity of oceanic carbon sequestration.

SF-YOLOv5: A Lightweight Small Object Detection Algorithm Based on Improved Feature Fusion Mode.

In the research of computer vision, a very challenging problem is the detection of small objects. The existing detection algorithms often focus on detecting full-scale objects, without making proprietary optimization for detecting small-size objects. For small objects dense scenes, not only the accuracy is low, but also there is a certain waste of computing resources. An improved detection algorithm was proposed for small objects based on YOLOv5. By reasonably clipping the feature map output of the large object detection layer, the computing resources required by the model were significantly reduced and the model becomes more lightweight. An improved feature fusion method (PB-FPN) for small object detection based on PANet and BiFPN was proposed, which effectively increased the detection ability for small object of the algorithm. By introducing the spatial pyramid pooling (SPP) in the backbone network into the feature fusion network and connecting with the model prediction head, the performance of the algorithm was effectively enhanced. The experiments demonstrated that the improved algorithm has very good results in detection accuracy and real-time ability. Compared with the classical YOLOv5, the mAP@0.5 and mAP@0.5:0.95 of SF-YOLOv5 were increased by 1.6% and 0.8%, respectively, the number of parameters of the network were reduced by 68.2%, computational resources (FLOPs) were reduced by 12.7%, and the inferring time of the mode was reduced by 6.9%.

A lightweight YOLOv3 algorithm used for safety helmet detection.

YOLOv3 is a popular and effective object detection algorithm. However, YOLOv3 has a complex network, and floating point operations (FLOPs) and parameter sizes are large. Based on this, the paper designs a new YOLOv3 network and proposes a lightweight object detection algorithm. First, two excellent networks, the Cross Stage Partial Network (CSPNet) and GhostNet, are integrated to design a more efficient residual network, CSP-Ghost-Resnet. Second, combining CSPNet and Darknet53, this paper designs a new backbone network, the ML-Darknet, to realize the gradient diversion of the backbone network. Finally, we design a lightweight multiscale feature extraction network, the PAN-CSP-Network. The newly designed network is named mini and lightweight YOLOv3 (ML-YOLOv3). Based on the helmet dataset, the FLPSs and parameter sizes of ML-YOLOv3 are only 29.7% and 29.4% of those of YOLOv3. Compared with YOLO5, ML-YOLOv3 also exhibits obvious advantages in calculation cost and detection effect.

Acceptance of seasonal influenza vaccination and associated factors among pregnant women in the context of COVID-19 pandemic in China: a multi-center cross-sectional study based on health belief model.

BACKGROUND: Seasonal influenza can circulate in parallel with coronavirus disease (COVID-19) in winter. In the context of COVID-19 pandemic, the risk of co-infection and the burden it poses on healthcare system calls for timely influenza vaccination among pregnant women, who are the priority population recommended for vaccination. We aimed to evaluate the acceptance of influenza vaccination and associated factors among pregnant women during COVID-19 pandemic, provide evidence to improve influenza vaccination among pregnant women, help reduce the risk of infection and alleviate the burden of healthcare system for co-infected patients. METHODS: We conducted a multi-center cross-sectional study among pregnant women in China. Sociodemographic characteristics, health status, knowledge on influenza, attitude towards vaccination, and health beliefs were collected. Locally weighted scatterplot smoothing regression analysis was used to evaluate the trends in the acceptance of influenza vaccine. Logistic regression was applied to identify factors associated with vaccination acceptance. RESULTS: The total acceptance rate was 76.5% (95%CI: 74.8-78.1%) among 2568 pregnant women enrolled. Only 8.3% of the participants had a history of seasonal influenza vaccination. In the logistic regression model, factors associated with the acceptance of influenza vaccine were western region, history of influenza vaccination, high knowledge of influenza infection and vaccination, high level of perceived susceptibility, perceived benefit, cues to action and low level of perceived barriers. Among 23.5% of the participants who had vaccine hesitancy, 48.0% of them were worried about side effect, 35.6% of them lacked confidence of vaccine safety. CONCLUSIONS: Our findings highlighted that tailored strategies and publicity for influenza vaccination in the context of COVID-19 pandemic are warranted to reduce pregnant women's concerns, improve their knowledge, expand vaccine uptake and alleviate pressure for healthcare system.

Acceptance of a COVID-19 vaccine and associated factors among pregnant women in China: a multi-center cross-sectional study based on health belief model.

Background: Vaccine hesitancy has been recognized as an urgent public health issue. We aimed to explore the acceptance of a COVID-19 vaccine and related factors among pregnant women, a vulnerable population for vaccine-preventable diseases.Methods: A multi-center cross-sectional study among pregnant women was conducted in five provinces of mainland China from November 13 to 27, 2020. We collected sociodemographic characteristics, attitude, knowledge, and health beliefs on COVID-19 vaccination. Locally weighted scatterplot smoothing regression analysis was used to assess the trends of vaccination acceptance. Multivariable logistic regression was performed to identify factors related to vaccination acceptance.Results: Among the 1392 pregnant women, the acceptance rate of a COVID-19 vaccine were 77.4% (95%CI 75.1-79.5%). In the multivariable regression model, the acceptance rate was associated with young age (aOR = 1.87, 95% CI: 1.20-2.93), western region (aOR = 2.73, 95% CI: 1.72-4.32), low level of education (aOR = 2.49, 95% CI: 1.13-5.51), late pregnancy (aOR = 1.49, 95% CI: 1.03-2.16), high knowledge score on COVID-19 (aOR = 1.05, 95% CI: 1.01-1.10), high level of perceived susceptibility (aOR = 2.18, 95% CI: 1.36-3.49), low level of perceived barriers (aOR = 4.76, 95% CI: 2.23-10.18), high level of perceived benefit (aOR = 2.18, 95% CI: 1.36-3.49), and high level of perceived cues to action (aOR = 15.70, 95% CI: 8.28-29.80).Conclusions: About one quarters of pregnant women have vaccine hesitancy. Our findings highlight that targeted and multipronged efforts are needed to build vaccine literacy and confidence to increase the acceptance of a COVID-19 vaccine during the COVID-19 pandemic, especially for vulnerable populations.

[Correlation between gut microbiota and liver biochemical indicators in patients with chronic hepatitis B].

Chronic hepatitis B (CHB) is a global epidemic disease caused by hepatitis B virus that can lead to hepatic failure, even liver cirrhosis and hepatocellular carcinoma. The occurrence and development of CHB are closely related to the changes in the gut microbiota communities. To explore the relationship between the structure of gut microbiota and liver biochemical indicators, 14 CHB patients (the CHB group) and 11 healthy people (the CN group) were randomly enrolled in this study. Our results demonstrate that CHB caused changes in the gut microbiota communities and biochemical indicators, such as alanine transaminase, total bilirubin and gamma glutamyl transferase. Furthermore, CHB induced imbalance of the gut microbiota. Prevotella, Blautia, Ruminococcus, Eubacterium eligens group, Bacteroides uniformis and Ruminococcus sp. 5_1_39BFAA were associated with the critical biochemical indicators and liver injury, suggesting a new approach to CHB treatment.

Image Stitching Based on Nonrigid Warping for Urban Scene.

Image stitching based on a global alignment model is widely used in computer vision. However, the resulting stitched image may look blurry or ghosted due to parallax. To solve this problem, we propose a parallax-tolerant image stitching method based on nonrigid warping in this paper. Given a group of putative feature correspondences between overlapping images, we first use a semiparametric function fitting, which introduces a motion coherence constraint to remove outliers. Then, the input images are warped according to a nonrigid warp model based on Gaussian radial basis functions. The nonrigid warping is a kind of elastic deformation that is flexible and smooth enough to eliminate moderate parallax errors. This leads to high-precision alignment in the overlapped region. For the nonoverlapping region, we use a rigid similarity model to reduce distortion. Through effective transition, the nonrigid warping of the overlapped region and the rigid warping of the nonoverlapping region can be used jointly. Our method can obtain more accurate local alignment while maintaining the overall shape of the image. Experimental results on several challenging data sets for urban scene show that the proposed approach is better than state-of-the-art approaches in both qualitative and quantitative indicators.

Detecting Matching Blunders of Multi-Source Remote Sensing Images via Graph Theory.

Large radiometric and geometric distortion in multi-source images leads to fewer matching points with high matching blunder ratios, and global geometric relationship models between multi-sensor images are inexplicit. Thus, traditional matching blunder detection methods cannot work effectively. To address this problem, we propose two matching blunder detection methods based on graph theory. The proposed methods can build statistically significant clusters in the case of few matching points with high matching blunder ratios, and use local geometric similarity constraints to detect matching blunders when the global geometric relationship is not explicit. The first method (named the complete graph-based method) uses clusters constructed by matched triangles in complete graphs to encode the local geometric similarity of images, and it can detect matching blunders effectively without considering the global geometric relationship. The second method uses the triangular irregular network (TIN) graph to approximate a complete graph to reduce to computational complexity of the first method. We name this the TIN graph-based method. Experiments show that the two graph-based methods outperform the classical random sample consensus (RANSAC)-based method in recognition rate, false rate, number of remaining matching point pairs, dispersion, positional accuracy in simulated and real data (image pairs from Gaofen1, near infrared ray of Gaofen1, Gaofen2, panchromatic Landsat, Ziyuan3, Jilin1and unmanned aerial vehicle). Notably, in most cases, the mean false rates of RANSAC, the complete graph-based method and the TIN graph-based method in simulated data experiments are 0.50, 0.26 and 0.14, respectively. In addition, the mean positional accuracy (RMSE measured in units of pixels) of the three methods is 2.6, 1.4 and 1.5 in real data experiments, respectively. Furthermore, when matching blunder ratio is no higher than 50%, the computation time of the TIN graph-based method is nearly equal to that of the RANSAC-based method, and roughly 2 to 40 times less than that of the complete graph-based method.

Significance of the thrombo-inflammatory status-based novel prognostic score as a useful predictor for in-hospital mortality of patients with type B acute aortic dissection.

BACKGROUND: Inflammation and thrombosis are associated with development and progression of acute aortic dissection (AAD). The aim of this study was to assess the prognostic significance of Simplified Thrombo-Inflammatory Prognostic Score (sTIPS), in patients with early phase type B AAD. METHODS: We retrospectively reviewed 491 patients with type B AAD between November 2012 and September 2015. sTIPS was calculated from the white blood cell count (WBC) and mean platelet volume to platelet count (MPV/PC) ratio, at the time of admission. Patients with both, WBC > 10 (109/L) and MPV/PC ratio > 7.5 (102fL/109L-1) were assigned a score of 2, while patients with high levels of either one or none of the above markers, were assigned scores of 1 and 0 respectively. Multivariable Cox regression analyses were used to investigate the associations between the score and hospital survival. RESULTS: Of the 491 type B AAD patients included in this analysis, 24 patients (4.9%) died during hospitalization. Kaplan-Meier analysis revealed that the cumulative mortality was significantly higher in patients with higher sTIPS (P = 0.001). Multivariable Cox regression analysis further indicated that higher sTIPS was a strong predictor of in-hospital mortality after eliminating all confounding factors (sTIPS 2: hazard ratio 4.704, 95%; confidence interval [CI] 1.184-18.685; P = 0.028; sTIPS 1: hazard ratio 1.918, 95%; CI 1.134-3.537; P = 0.045). CONCLUSIONS: sTIPS at admission was a useful tool for stratifying the risk in type B AAD patients, for outcomes such as in-hospital mortality in the early phase.

Hypoalbuminemia predicts clinical outcome in patients with type B acute aortic dissection after endovascular therapy.

BACKGROUND: Few studies have reported that serum albumin (SA) levels on admission were associated with increased risk of long-term outcomes in patients with type B acute aortic dissection (AAD). The aim of this study was to investigate the effect of admission levels of SA on survival among patients with type B AAD undergoing endovascular therapy (EVT). METHODS: A total of 131 patients with type B AAD undergoing EVT were retrospectively enrolled and followed up for 2.1years. They were divided into hypoalbuminemia and nonhypoalbuminemia groups. We analyzed the incidence of inhospital complications and long-term mortality. Kaplan-Meier curves and multivariable Cox regression analyses were used to investigate the associations between SA levels and survival. RESULTS: Among 131 type B AAD patients, hypoalbuminemia was detected in 61 (46.6%) at admission. Compared to those without hypoalbuminemia, patients with hypoalbuminemia did not have higher inhospital complications; however, Kaplan-Meier analysis showed that they did have a significantly lower survival rate (73.8% vs 92.5%; log-rank χ(2)=9.8; P=.002). Multivariable Cox regression analysis further revealed that hypoalbuminemia was an independent predictor of long-term mortality among patients with type B AAD (hazard ratio, 4.28; 95% confidence interval, 1.36-13.47; P=.013), over 2.1years. CONCLUSIONS: Hypoalbuminemia is common in type B AAD patients and is independently associated with increased risk of long-term death. Renal dysfunction may be the main pathophysiological mechanism underlying hypoalbuminemia in patients with type B AAD.

[Effect of electroacupuncture of "Neiguan" (PC 6) on heart rate and plasma catecholamine contents in ventricular tachycardia rats].

OBJECTIVE: To observe the effect of electroacupuncture (EA) of "Neiguan" (PC 6) on heart rate (HR) and plasma catecholamine (CA) levels in ventricular tachycardia (VT) rats. METHODS: A total of 50 SD rats were randomly divided into normal control, sham-operation (sham), model, EA-PC 6 and EA-LU 7 groups, with 10 cases in each. VT model was established by intravenous injection of cesium chloride (CsCl) via femoral vein. Electrocardiogram (ECG) was recorded. EA (2 Hz/15 Hz, 1 mA) was separately applied to bilateral "Neiguan" (PC 6) and "Lieque" (LU 7) for 5 minutes, followed by collecting blood samples for detecting plasma norepinephrine (NE) and epinephrine (E) levels with fluorometric method. RESULTS: In comparison with normal control group, plasma NE and E contents in model group increased apparently (P < 0.01). Compared with model group, HR and plasma NE and E contents of EA-PC 6 group reduced significantly (P < 0.01), while those of EA-LU 7 had no apparent change (P > 0.05). CONCLUSION: EA of "Neiguan" (PC 6) can downregulate heart rate and plasma CA level in VT rats, which may contribute to its effect in relieving tachycardia.

[Effect of benzene on sperm DNA].

OBJECTIVE: To assess the effect of benzene on sperm DNA. METHODS: Twenty-seven workers exposed to benzene for over two years were included in the experiment group and 35 unexposed ones were chosen as controls. Damage by benzene on sperm DNA was detected by modified single cell gel electrophoresis (SCGE). RESULTS: The benzene concentration in the air of the workplace of the exposed workers was (86.49 +/- 2.83) mg/m3, twice that of the national maximum allowance (40 mg/cm3). Urinary, trans-muconic acid in the exposed group was (1.40 +/- 0.62) mg/L (n = 27), significantly higher than that of the controls [(0.82) +/- 0.16) mg/L, n = 35]. After SCGE, the percentage of head DNA in the exposed group [(70.18% +/- 7.36%, n = 13 ] was significantly lower than that of the controls (90.62% +/- 2.94%, n = 16), P < 0.001. CONCLUSION: Higher concentration of benzene could cause damage to the sperm DNA of the workers exposed to it.

[Detection of numerical aberrations of chromosomes 7 and 8 in sperms of workers exposed to benzene series by two-color fluorescence in situ hybridization].

OBJECTIVE: To investigate the frequency of numerical aberrations for chromosomes 7 and 8 in the sperms of workers exposed to benzene series. METHODS: Numerical aberrations in the sperms of workers were detected by two-color fluorescence in situ hybridization with biotin labeled chromosome 7 probe (D7Z1) and digoxingenin labeled chromosome 8 probe (D8Z1). RESULTS: The time-weight average air concentration (TWA) of benzene in the workshop was 42.29 mg/m(3), which was significantly higher than that of the national maximum allowable concentration [6 mg/m(3)]. The concentration of urinary trans,trans-muconic acid(ttMA) in the exposed group was also higher than that of the control group. In all, 155721 sperm nuclei from 15 workers in the exposed group and 123771 sperm nuclei from 12 individuals in the control group were examined. The results showed that the frequency of diploidy sperms and the frequencies of disomic sperm for chromosomes 7 and 8 in the exposed group (0.129%, 0.170%, 0.078%) were significantly higher than those of the control group (0.055%, 0.053%, 0.033%), respectively. The frequencies of nullisomic sperm for chromosomes 7 and 8 in the exposed group (0.165%, 0.088%) were also significantly increased, compared with those of the control group (0.056%, 0.029%). A statistically significant difference in the frequency of overall numerical chromosome aberrations was seen between the exposed group (0.745%) and the control group (0.289%). CONCLUSION: The results suggested that higher concentration of benzene may induce higher frequencies of numerical aberrations in the sperms of workers exposed to benzene series.