Network analysis of the comorbidity between post-traumatic stress, depression and anxiety symptoms among frontline healthcare workers during the COVID-19 pandemic.

Background: Coronavirus disease 2019 pandemic pointed out significant mental symptoms of frontline healthcare workers (HCWs). Objective: We aimed to estimate the prevalence and comorbidity of post-traumatic stress symptoms (PTSS), depression and anxiety symptoms in HCWs from Fangcang shelter hospitals during the pandemic. Design: Demographic information, post-traumatic stress disorder checklist for DSM-5 (PCL-5), Patient Health Questionnaire (PHQ-9) and Generalized Anxiety Disorder Questionnaire (GAD-7) were obtained online based on stratified random sampling design during April 2022, with 284 eligible responses. Method: Hierarchical regression analyses were applied to investigate independent variables associated with psychological status outcomes (PHQ-9, GAD-7 and PCL-5), and the network analyses were applied to explore the comorbidity using all items of PCL-5, PHQ-9 and GAD-7. Results: (1) 10.56%, 13.03% and 8.10% of HCWs reported PTSS, depression and anxiety symptoms. Fifty-three (18.66%) HCWs experienced at least one mental health disorder, among which 26.42-37.74% HCWs had comorbidity of two or three mental disorders; (2) several influence factors of mental health were identified, including medical professions, working hours, contacted patients (p < 0.05); (3) prominent bridge symptoms between PTSS and depression were sleep problems, suicide ideation, concentration difficulties and recklessness. Comorbidity between PTSS and anxiety was thought to mainly stem from negative affect, such as afraid, anxious, annoyed and worrying. Depressed mood and worry might be good targets during treatment of comorbidity of depression and anxiety. Conclusion: Our data suggest mild level of PTSS, depression and anxiety symptoms among HCWs during the pandemic and might give novel insights into assessment and intervention of comorbidity.

Green tea polyphenols inhibit TBBPA-induced lung injury via enhancing antioxidant capacity and modulating the NF-κB pathway in mice.

Tetrabromobisphenol A (TBBPA) is a global pollutant. When TBBPA is absorbed by the body through various routes, it can have a wide range of harmful effects on the body. Green tea polyphenols (GTPs) can act as antioxidants, resisting the toxic effects of TBBPA on animals. The effects and mechanisms of GTP and TBBPA on oxidative stress, inflammation and apoptosis in the mouse lung are unknown. Therefore, we established in vivo and in vitro models of TBBPA exposure and GTP antagonism using C57 mice and A549 cells and examined the expression of factors related to oxidative stress, autophagy, inflammation and apoptosis. The results of the study showed that the increase in reactive oxygen species (ROS) levels after TBBPA exposure decreased the expression of autophagy-related factors Beclin1, LC3-II, ATG3, ATG5, ATG7 and ATG12 and increased the expression of p62; oxidative stress inhibits autophagy levels. The increased expression of the pro-inflammatory factors IL-1ß, IL-6 and TNF-α decreased the expression of the anti-inflammatory factor IL-10 and activation of the NF-κB p65/TNF-α pathway. The increased expression of Bax, caspase-3, caspase-7 and caspase-9 and the decreased expression of Bcl-2 activate apoptosis-related pathways. The addition of GTP attenuated oxidative stress levels, restored autophagy inhibition and reduced the inflammation and apoptosis levels. Our results suggest that GTP can attenuate the toxic effects of TBBPA by modulating ROS, reducing oxidative stress levels, increasing autophagy and attenuating inflammation and apoptosis in mouse lung and A549 cells. These results provide fundamental information for exploring the antioxidant mechanism of GTP and further for studying the toxic effects of TBBPA.

High-fat diet disrupts the gut microbiome, leading to inflammation, damage to tight junctions, and apoptosis and necrosis in Nyctereutes procyonoides intestines.

Given the burgeoning Nyctereutes procyonoides breeding industry and its growing scale, it is imperative to investigate the impact of high-fat diets on the health of these animals. This study involved 30 male Nyctereutes procyonoides of comparable weights (3 kg ±0.5), randomly assigned to either a control group or a high-fat diet group (n = 15 each). The latter group was fed a mixture of lard and basal diet in a 2:5 ratio, establishing a high-fat diet model in Nyctereutes procyonoides. This diet induced diarrhea and histopathological changes in the Nyctereutes procyonoides. Analysis of the small intestine contents using 16S rRNA sequencing revealed a high-fat diet-induced disruption in the gut microbiota. Specifically, Escherichia-Shigella emerged as the biomarker in the high-fat diet group (P = 0.049), while Vagococcus was prevalent in the control group (P = 0.049), indicating a significant increase in harmful bacteria in the high-fat diet group. Furthermore, this disrupted gut flora correlated with inflammation and oxidative stress, as evidenced by marked increases in TNF-α (P < 0.01), IL-1ß (P < 0.05), and IL-6 (P < 0.05) levels, measured via q-PCR, Western blot, and oxidative stress assays. In addition, q-PCR analysis revealed significant upregulation of apoptosis and necrosis markers, including Bax, Caspase3, Caspase9, Caspase12, RIPK3, and RIPK1 (P < 0.01 to P < 0.001), and a concurrent downregulation of the anti-apoptotic gene Bcl-2 (P < 0.01) in the high-fat diet group, consistent with protein expression trends. These findings suggest that a high-fat diet alters the gut microbiome toward a more harmful bacterial composition, escalating inflammatory responses and intestinal tissue permeability, culminating in intestinal cell apoptosis and necrosis.IMPORTANCEThis study examines the impact of high-fat diets on Nyctereutes procyonoides. Our research established a Nyctereutes procyonoides model on a high-fat diet, revealing significant health impacts, such as diarrhea, histological anomalies, and alterations in the gut microbiota. These findings emphasize the importance of preventing health issues and promoting sustainable industry growth. They highlight the significant impact of diet on gut microbiota and overall animal health.

Polyethylene microplastics induced gut microbiota dysbiosis leading to liver injury via the TLR2/NF-κB/NLRP3 pathway in mice.

Microplastics (MPs) are ubiquitous environmental contaminants that have negative impacts on health and safety. The gut microbiota plays multiple roles as a newly discovered virtual metabolic organ. The objective of this study was to investigate the potential of MPs to cause liver injury by disrupting the balance of gut microbiota. The results indicated that exposure to MPs resulted in liver damage and disrupted the homeostasis of gut microbiota. MPs significantly reduced the liver organ coefficient, leading to liver cell injury and impaired function. Additionally, there was an increase in the expression of fibril-related proteins, which positively correlated with MPs concentration. Furthermore, MPs increased the relative abundances of Desulfovibrio, Clostridia, Enterorhabdus, Bacteroides, and Gemella while decreasing the abundance of Dubosoella. Different concentrations of MPs exhibited varying effects on specific bacterial groups, however, both concentrations resulted in an increase in pathogenic bacteria and a decrease in beneficial bacteria, as well as alterations in microbial structure. Moreover, MPs induced oxidative stress, inflammation, apoptosis and necrosis in liver cells. The study found that MPs disrupted gut microbiota homeostasis and activated TLR2/NF-κB/NLRP3 pathway in the liver, providing a new insight into the mechanism underlying MPs-induced liver injury. These findings serve as a warning regarding environmental pollution caused by MPs.

The impact of isolation on comorbidity of PTSD symptoms and depression: evidence from PTRP-5-6 in China.

BACKGROUND: The Omicron pandemic struck Shanghai, China, resulting in impairments of both physical and psychological health on those patients who were confirmed and transferred to the Fangcang shelters. The way of isolation led to high risk of posttraumatic stress symptoms (PTSS) and depressive symptoms among the patients in Fangcang shelters. We aim to estimate the prevalence and comorbidity of PTSS and depressive symptoms in patients from China's Fangcang shelters during the epidemic. METHODS: Demographic information questionnaire, the posttraumatic stress disorder checklist for DSM-5 (PCL-5), and Patient Health Questionnaire (PHQ-9) were used in the study. The data were collected online via mobile phones during 10th April to 20th April, 2022, as part of our Psychological Trauma Recover Project-5-6 (PTRP-5-6), a longitudinal study focusing on individuals who have experienced trauma. RESULTS: A total of 336 subjects were included in the analysis. The results revealed (1) the prevalence of depressive symptoms, and PTSS were 30.1% (cut-off = 10) and 6% (cut-off = 33); (2) Multiple logistic regression showed that female (OR = 3.04, p < 0.05), suffering from dyspnea (OR = 5.83, p < 0.05) or gastrointestinal symptoms (OR = 6.38, p < 0.05) were risk factors for PTSS; higher education level (OR = 3.27, p < 0.05) and suffering from dizziness or headache (OR = 2.46, p < 0.05) were risk factors for depressive symptoms; (3)Respectively, 85% of the patients who reported PTSS also experienced depressive symptoms, 16.8% of the patients who reported depressive symptoms presented PTSS. CONCLUSION: In the context of COVID-19, the comorbidity rate of PTSS and depressive symptoms among patients in Fangcang shelters increased with the severity of depressive symptoms.

HSH-UNet: Hybrid selective high order interactive U-shaped model for automated skin lesion segmentation.

The use of computer-assisted clinical dermatologists to diagnose skin diseases is an important aid. And computer-assisted techniques mainly use deep neural networks. Recently, the proposal of higher-order spatial interaction operations in deep neural networks has attracted a lot of attention. It has the advantages of both convolution and transformers, and additionally has the advantages of efficient, extensible and translation-equivariant. However, the selection of the interaction order in higher-order interaction operations requires tedious manual selection of a suitable interaction order. In this paper, a hybrid selective higher-order interaction U-shaped model HSH-UNet is proposed to solve the problem that requires manual selection of the order. Specifically, we design a hybrid selective high-order interaction module HSHB embedded in the U-shaped model. The HSHB adaptively selects the appropriate order for the interaction operation channel-by-channel under the computationally obtained guiding features. The hybrid order interaction also solves the problem of fixed order of interaction at each level. We performed extensive experiments on three public skin lesion datasets and our own dataset to validate the effectiveness of our proposed method. The ablation experiments demonstrate the effectiveness of our hybrid selective higher order interaction module. The comparison with state-of-the-art methods also demonstrates the superiority of our proposed HSH-UNet performance. The code is available at https://github.com/wurenkai/HSH-UNet.

Optical coherence tomography image despeckling based on tensor singular value decomposition and fractional edge detection.

Optical coherence tomography (OCT) imaging is a technique that is frequently used to diagnose medical conditions. However, coherent noise, sometimes referred to as speckle noise, can dramatically reduce the quality of OCT images, which has an adverse effect on how OCT images are used. In order to enhance the quality of OCT images, a speckle noise reduction technique is developed, and this method is modelled as a low-rank tensor approximation issue. The grouped 3D tensors are first transformed into the transform domain using tensor singular value decomposition (t-SVD). Then, to cut down on speckle noise, transform coefficients are thresholded. Finally, the inverse transform can be used to produce images with speckle suppression. To further enhance the despeckling results, a feature-guided thresholding approach based on fractional edge detection and an adaptive backward projection technique are also presented. Experimental results indicate that the presented algorithm outperforms several comparison methods in relation to speckle suppression, objective metrics, and edge preservation.

Zinc deficiency causes oxidative stress, endoplasmic reticulum stress, apoptosis and inflammation in hepatocytes in grass carp.

A lack of the trace element zinc (Zn) in freshwater environments causes slow growth and malnutrition and affects the normal biological functions of organisms. In this study, a Zn deficiency model of grass carp hepatocytes was established with TPEN. Acetylcysteine (NAC) was used as an inhibitor. TPEN was added to L8824 cell culture medium, and LDH, AST, ALT, and AKP activities were enhanced in a Zn-deficient environment, leading to abnormal hepatopancreas function. Fluorescence microscopy showed an increase in ROS levels, and antioxidant enzyme activity assays revealed that SOD, CAT, GSH-PX, and T-AOC activities were decreased, indicating oxidative stress caused by Zn deficiency. The RT‒PCR results showed that the mRNA expression of GRP78, PERK, EIF2α, ATF4, and Chop was increased due to the addition of TPEN. Calcium kits showed increased Ca2+ levels. The RT‒PCR results showed that the mRNA expression levels of Caspase-12, Caspase-9, Caspase-3, and PARP apoptotic were increased due to the addition of TPEN. RT‒PCR and ELISA showed that the expression levels of interleukin-1ß (IL-1ß), interleukin-8 (IL-8), tumour necrosis factor (TNF-α), and inducible nitric oxide synthase (iNOS) were increased. This led to the conclusion that Zn deficiency in the freshwater environment caused inflammation and apoptosis in hepatocytes in grass carp. For the first time, apoptosis caused by endoplasmic reticulum stress in grass carp hepatocytes due to Zn deficiency was studied in the context of Ca2+. The present study provided some insight into the adverse effects of Zn deficiency in freshwater environments on fish.

Speckle attenuation for optical coherence tomography images using the generalized low rank approximations of matrices.

A frequently used technology in medical diagnosis is optical coherence tomography (OCT). However, coherent noise, also known as speckle noise, has the potential to severely reduce the quality of OCT images, which would be detrimental to the use of OCT images for disease diagnosis. In this paper, a despeckling method is proposed to effectively reduce the speckle noise in OCT images using the generalized low rank approximations of matrices (GLRAM). Specifically, the Manhattan distance (MD)-based block matching method is first used to find nonlocal similar blocks for the reference one. The left and right projection matrices shared by these image blocks are then found using the GLRAM approach, and an adaptive method based on asymptotic matrix reconstruction is proposed to determine how many eigenvectors are present in the left and right projection matrices. Finally, all the reconstructed image blocks are aggregated to create the despeckled OCT image. In addition, an edge-guided adaptive back-projection strategy is used to improve the despeckling performance of the proposed method. Experiments with synthetic and real OCT images show that the presented method performs well in both objective measurements and visual evaluation.

Polyethylene microplastics trigger cell apoptosis and inflammation via inducing oxidative stress and activation of the NLRP3 inflammasome in carp gills.

Microplastics cause varying degrees of damage to aquatic organisms. Exposure to microplastics contaminated water, the gills are among the first tissues, after the skin, to be affected by microplastics. As an essential immune organ, prolonged stimulation by microplastics disrupts immune function not only in the gills but throughout the body, yet the underlying mechanisms remain elusive. A model of gill injury from exposure to polyethylene (PE) microplastics was developed in this study. H&E staining revealed that polyethylene microplastics caused gill inflammation, vascular remodeling, and mucous cell proliferation. An increase in collagen indicates severe tissue damage. Additional analysis showed that polyethylene microplastics profoundly exacerbated oxidative stress in the gills. TUNEL assay demonstrated cell apoptosis induced by polyethylene microplastic. The mRNA levels were subsequently quantified using RT-PCR. The results showed that polyethylene microplastics increased the expression of the nuclear factor-κB (NF-κB) pathway (NF-κB p65, IKKα, IKKß) and apoptosis biomarkers (p53, caspase-3, caspase-9, and Bax). Nucleotide-binding oligomerization domain-like receptor protein 3 (NLRP3) inflammasomes, which is an influential component of innate immunity, were overactive. What's more, the pro-inflammatory factors (TNF-α, IFN-γ, IL-2, IL-6, IL-8, IL-1ß) that induce immune disorder also increased significantly, while the anti-inflammatory factors (IL-4, IL-10) decreased significantly. These results suggested that oxidative stress acted as an activation signal of apoptosis triggered by the NF-κB pathway and activating the NLRP3 inflammasome to promote inflammatory immune responses. The present study provided a different target for the prevention of toxin-induced gill injury under polyethylene microplastics.

A construction strategy for conservative adaptive Kriging surrogate model with application in the optimal design of contaminated groundwater extraction-treatment.

When the simulation-optimization model to optimize the groundwater extraction-treatment schemes is used, the construction of a surrogate model for the numerical simulation model has become an effective means to overcome the large calculation load of repeatedly calling the numerical model. However, there are still some problems in using the surrogate model, such as large training sample size, low accuracy, and poor optimization results. In this paper, a conservative adaptive Kriging surrogate model (CAKSM) was proposed by coupling the Kriging surrogate model, optimal solution adaptive sampling method (OSAS), and conservative prediction idea. Firstly, an initial Kriging surrogate model (IKSM) was built for the numerical simulation model of groundwater flow and solute transport. Then, the IKSM was coupled with the optimization model to construct the adaptive Kriging surrogate model (AKSM) by using OSAS. A safety margin was added to the AKSM to build the CAKSM. Finally, the simulation-optimization models based on IKSM, AKSM, and CAKSM were solved by the genetic algorithm, respectively. The results showed that the IKSM could well substitute for the simulation model. The AKSM significantly improved the approximation degree between the surrogate model and the simulation model at the optimal solution by supplementing a small number of new samples. CAKSM could effectively constrain the pollutant mass concentrations within the controlled value, improving the reliability of the optimization scheme. The optimal extraction wells based on different surrogate models were all well 5, well 6, and well 9. They were concentrated in the middle and lower reaches of the contaminated plume's central axis. The sequence for the remediation effects by different surrogate models from high to low was as follows: CAKSM, AKSM, and IKSM. The risk rate of the optimal remediation scheme from the hydraulic conductivity random fields was as high as 12.12%, and the risks were mainly located upstream of the pollution plume's central axis.

Novel small-insertion mutation in the LIPH gene in a patient with autosomal recessive woolly hair/hypotrichosis.

Autosomal recessive woolly hair/hypotrichosis (ARWH/H) is a rare form of congenital alopecia, which can be caused by mutations in lipase H (LIPH), lysophosphatidic acid receptor 6 (LPAR6/P2RY5) or keratin 25 (KRT25) genes. We present a 32-year-old woman with typical clinical features of ARWH. Hair microscopy was performed to observe differences between the patient's hair and a normal sample. Next-generation sequencing was used to detect pathogenic mutations. Sanger sequencing was used to further confirm the mutations. Abnormal hair appearance was found by hair microscopy. A novel frame-shift mutation (NM_139248: c.686delinsGTAGAACCCAACCTGGCT: p.Asp229fs37X) and a reported mutation (NM_139248: exon6:c.T736A: p.C246S) in LIPH were identified in the patient. All reported mutations related to ARWH of various races were reviewed. Our study provides further evidence of the similarity of ARWH between the Chinese and Japanese population. A novel small-insertion mutation also expands the LIPH mutation spectrum.

Comparative Study of Traditional Ablative CO2 Laser-Assisted Topical Antifungal with only Topical Antifungal for Treating Onychomycosis: A Multicenter Study.

BACKGROUND: The predominance of onychomycosis has been increasing recently. New medications and treatment modalities are being researched for better saturation of the antifungal agents through the nail plate topically because of the low resilience of some patients for the oral antifungal agents. Treatment of onychomycosis, mainly moderate to severe, can be very challenging, expensive, and time consuming. OBJECTIVE: The objective of this clinical trial is to compare the efficacy and safety of a manually operated ablative CO2 laser combined with a topical antifungal agent in patients with onychomycosis. STUDY DESIGN: We conducted an open-label controlled prospective study of 160 eligible patients randomized into control and treatment groups with a 1:1 allocation in the department of dermatology in five different hospitals in Shanghai. It was a 6-month study where both groups were treated with a topical antifungal agent, with the treatment group also receiving ablation by the traditional CO2 laser once a month for the first 3 months. RESULTS: The clinical efficacy and mycological cure rate were significantly higher (p < 0.001) for the treatment group. Three (3.75%) patients from the control group and 18 (25%) patients from the treatment group achieved complete nail clearance along with negative potassium hydroxide and negative culture (primary endpoint) results at 24 weeks. Mycological clearance with at least moderate nail clearance (secondary endpoint) for the treatment group was also significantly higher (p < 0.001) for the laser treatment group. The laser treatment was mildly painful but tolerable by the patients. No drug interactions for both groups were encountered. CONCLUSIONS: The ablative CO2 laser is a primitive yet effective modality to be considered for the delivery of topical antifungal agents for the management of mild-to-severe onychomycosis. The laser has good tolerance in patients and is a common equipment found in most dermatology units even those without the latest medical technology.

Weighted Schatten p-norm minimization for 3D magnetic resonance images denoising.

Magnetic resonance (MR) imaging plays an important role in clinical diagnosis and scientific research. A clean MR image can better provide patient's information to doctors or researchers for further treatment. However, in real life, MR images are inevitably corrupted by annoying Rician noise in the process of imaging. Aiming at the Rician noise of 3D MR images, a framework is proposed to suppress noise by low-rank matrix approximation (LRMA) with weighted Schatten p-norm minimization regularization (WSNMD-3D). The proposed method not only considers the importance of different rank components, but can also approximate the true rank of the latent low-rank matrix. This approach first groups similar non-local cubic patches extracted from the noisy 3D MR image into a matrix whose columns are vectorized patches. The above matrix can be modeled as a low-rank matrix approximate model. Then weighted Schatten p-norm minimization (WSNM) is applied to the model, which shrinks different rank components with different treatments. Finally, the denoised 3D MR image is acquired by aggregating all denoised patches with weighted averaging. Experimental results on synthetic and real 3D MR data show that the proposed method obtains better results than state-of-the-art methods, both visually and quantitatively.

Speckle noise reduction of multi-frame optical coherence tomography data using multi-linear principal component analysis.

Optical coherence tomography (OCT) is an important interferometric diagnostic technique extensively applied in medical sciences. However, OCT images inevitably suffer from speckle noise, which reduces the accuracy of the diagnosis of ocular diseases. To deal with this problem, a speckle noise reduction method based on multi-linear principal component analysis (MPCA) is presented to denoise multi-frame OCT data. To well preserve local image features, nonlocal similar 3D blocks extracted from the data are first grouped using k-means++ clustering method. MPCA transform is then performed on each group and the transform coefficients are shrunk to remove speckle noise. Finally, the filtered OCT volume is obtained by inverse MPCA transform and aggregation. Experimental results show that the proposed method outperforms other compared approaches in terms of both speckle noise reduction and fine detail preservation.

Speckle attenuation by adaptive singular value shrinking with generalized likelihood matching in optical coherence tomography.

As a high-resolution imaging mode of biological tissues and materials, optical coherence tomography (OCT) is widely used in medical diagnosis and analysis. However, OCT images are often degraded by annoying speckle noise inherent in its imaging process. Employing the bilateral sparse representation an adaptive singular value shrinking method is proposed for its highly sparse approximation of image data. Adopting the generalized likelihood ratio as similarity criterion for block matching and an adaptive feature-oriented backward projection strategy, the proposed algorithm can restore better underlying layered structures and details of the OCT image with effective speckle attenuation. The experimental results demonstrate that the proposed algorithm achieves a state-of-the-art despeckling performance in terms of both quantitative measurement and visual interpretation.