Lubricin-Inspired Nanozymes Reconstruct Cartilage Lubrication System with an "In-Out" Strategy.

Lubricin, secreted primarily by chondrocytes, plays a critical role in maintaining the function of the cartilage lubrication system. However, both external factors such as friction and internal factors like oxidative stress can disrupt this system, leading to osteoarthritis. Inspired by lubricin, a lubricating nanozyme, that is, Poly-2-acrylamide-2-methylpropanesulfonic acid sodium salt-grafted aminofullerene, is developed to restore the cartilage lubrication system using an "In-Out" strategy. The "Out" aspect involves reducing friction through a combination of hydration lubrication and ball-bearing lubrication. Simultaneously, the "In" aspect aims to mitigate oxidative stress by reducing free radical, increasing autophagy, and improving the mitochondrial respiratory chain. This results in reduced chondrocyte senescence and increased lubricin production, enhancing the natural lubrication ability of cartilage. Transcriptome sequencing and Western blot results demonstrate that it enhances the functionality of mitochondrial respiratory chain complexes I, III, and V, thereby improving mitochondrial function in chondrocytes. In vitro and in vivo experiments show that the lubricating nanozymes reduce cartilage wear, improve chondrocyte senescence, and mitigate oxidative stress damage, thereby mitigating the progression of osteoarthritis. These findings provide novel insights into treating diseases associated with oxidative stress and frictional damage, such as osteoarthritis, and set the stage for future research and development of therapeutic interventions.

Association between physical frailty and cortical structure in middle-aged and elderly people: a Mendelian randomization study.

Introduction: Physical weakness is associated with cortical structures, but the exact causes remain to be investigated. Therefore, we utilized Mendelian randomization (MR) analysis to uncover the underlying connection between frailty and cortical structures. Methods: The Genome-Wide Association Study (GWAS) on frailty pooled data from publicly available sources such as the UK Biobank and included five indicators of frailty: weakness, walking speed, weight loss, physical activity, and exhaustion. GWAS data on cerebral cortical structure were obtained from the ENIGMA consortium, and we assessed the causal relationship between hereditary frailty and cortical surface area (SA) or cortical thickness (TH). Inverse variance weighting (IVW) was used as the primary estimate, and heterogeneity and multidimensionality were monitored by MR-PRESSO to detect outliers. Additionally, MR-Egger, Cochran's Q test, and weighted median were employed. Results: At the aggregate level, there was no causal relationship between frailty and cortical thickness or surface area. At the regional level, frailty was associated with the thickness of the middle temporal lobe, parahippocampus, rostral middle frontal lobe, lower parietal lobe, anterior cingulate gyrus, upper temporal lobe, lateral orbital frontal cortex, pericardial surface area, rostral middle frontal lobe, upper temporal lobe, rostral anterior cingulate gyrus, lower parietal lobe, and upper parietal lobe. These results were nominally significant, and sensitivity analyses did not detect any multidirectionality or heterogeneity, suggesting that the results of our analyses are reliable. Discussion: The results of our analyses suggest a potential causal relationship between somatic weakness and multiple regions of cortical structure. However, the specific mechanisms of influence remain to be investigated. Preliminary results from our analysis suggest that the effects of physical frailty on cortical structures are influenced by various factors related to frailty exposure. This relationship has been documented, and it is therefore both feasible and meaningful to build on existing research to explore the clinical significance of the relationship.

Diagnostic Value of Nutritional Risk Index and Other Indices for Predicting Sarcopenia in the Middle-Aged and Elderly Population of China Without Cancer: A ROC Curve Analysis.

Background: Emerging evidence suggests that systemic inflammatory and nutritional biomarkers, along with derived indices, could serve as predictors for sarcopenia in cancer population. This study aimed to compare these predictors, focusing on the nutritional risk index (NRI) and evaluate its diagnostic value, for sarcopenic patients without cancer. Methods: This cross-sectional retrospective study included 1674 participants. Sarcopenia is defined by skeletal muscle mass index (SMI). Laboratory data reflected the values of systemic inflammatory and nutritional biomarkers, from which the derived indices were calculated. Multiple logistic regression analysis, ROC curve analysis, and the Youden index were utilized to assess the association between these markers and sarcopenia and determine the cutoff value for predicting sarcopenia. Results: Among all participants (1110 men and 564 women, mean age 61.97 ± 9.83 years), 398 individuals were diagnosed with sarcopenia, indicating a prevalence of 23.78% in China's middle-aged and elderly population without cancer. Logistic regression analysis revealed significant associations between all biomarkers and derived indices with sarcopenia. Following adjustment for potential confounders, lower NRI values were significantly associated with a higher incidence of sarcopenia. For sarcopenia diagnosis, the area under the curve (AUC) for NRI was 0.769 ([95% CI, 0.742, 0.796], P < 0.001), with a cutoff value of 106.016, sensitivity of 75.6% and specificity of 66.1%. NRI demonstrated greater predictive advantage for sarcopenia incidence in men compared to women. Conclusion: A lower NRI value was associated with a higher prevalence of sarcopenia. NRI shows promise for early, rapid, and effective sarcopenia screening, particularly in China's middle-aged and elderly male population without cancer.

Association between environmental phthalates exposure and gut microbiota and metabolome in dementia with Lewy bodies.

BACKGROUND: Emerging evidence has shown the potential involvement of phthalates (PAEs) exposure in the development of dementia with Lewy bodies (DLB). Metabolomics can reflect endogenous metabolites variation in the progress of disease after chemicals exposure. However, little is known about the association between PAEs, gut microbiota and metabolome in DLB. OBJECTIVE: We aim to explore the intricate relationship among urinary PAEs metabolites (mPAEs), dysbiosis of gut bacteria, and metabolite profiles in DLB. METHODS: A total of 43 DLB patients and 45 normal subjects were included in this study. Liquid chromatography was used to analyze the levels of mPAEs in the urine of the two populations. High-throughput sequencing and liquid chromatography-mass spectrometry were used to analyze gut microbiota and the profile of gut metabolome, respectively. The fecal microbiota transplantation (FMT) experiment was performed to verify the potential role of mPAEs on gut dysbiosis contribute to aggravating cognitive dysfunction in α-synuclein tg DLB/PD mice. RESULTS: The DLB patients had higher DEHP metabolites (MEOHP, MEHHP and MEHP), MMP and MnBP, lower MBP and MBzP than the control group and different microbiota. A significantly higher abundance of Ruminococcus gnavus and lower Prevotella copri, Prevotella stercorea and Bifidobacterium were observed in DLB. Higher 3 DEHP metabolites, MMP, MnBP and lower MBP and MBzP were significantly negatively associated with Prevotella copri, Prevotella stercorea and Bifidobacterium. Additionally, using metabolomics, we found that altered bile acids, short-chain fatty acids and amino acids metabolism are linked to these mPAEs. We further found that FMT of fecal microbiota from highest DEHP metabolites donors significantly impaired cognitive function in the germ-free DLB/PD mice. CONCLUSION: Our study suggested that PAEs exposure may alter the microbiota-gut-brain axis and providing novel insights into the interactions among environmental perturbations and microbiome-host in pathogenesis of DLB.

Protocatechuic acid enhanced the selective degradation of sulfonamide antibiotics in Fe(III)/peracetic acid process under actually neutral pH conditions.

The practical application of the Fe-catalyzed peracetic acid (PAA) processes is seriously restricted due to the need for narrow pH working range and poor anti-interference capacity. This study demonstrates that protocatechuic acid (PCA), a natural and eco-environmental phenolic acid, significantly enhanced the removal of sulfonamide antibiotics in Fe(III)/PAA process under actually neutral pH conditions (6.0-8.0) by complexing Fe(III). With sulfamethoxazole (SMX) as the model contaminant, the pseudo-first-order rate constant of SMX elimination in PCA/Fe(III)/PAA process was 63.5 times higher than that in Fe(III)/PAA process at pH 7.0, surpassing most of the previously reported strategies-enhanced Fe-catalyzed PAA processes (i.e., picolinic acid and hydroxylamine etc.). Excluding the primary contribution of reactive species commonly found in Fe-catalyzed PAA processes (e.g., •OH, R-O•, Fe(IV)/Fe(V) and 1O2) to SMX removal, the Fe(III)-peroxy complex intermediate (CH3C(O)OO-Fe(III)-PCA) was proposed as the primary reactive species in PCA/Fe(III)/PAA process. DFT theoretical calculations indicate that CH3C(O)OO-Fe(III)-PCA exhibited stronger oxidation potential than CH3C(O)OO-Fe(III), thereby enhancing SMX removal. Four potential removal pathways of SMX were proposed and the toxicity of reaction solution decreased with the removal of SMX. Furthermore, PCA/Fe(III)/PAA process exhibited strong anti-interference capacity to common natural anions (HCO3-, Cl-and NO3-) and humic acid. More importantly, the PCA/Fe(III)/PAA process demonstrated high efficiency for SMX elimination in actual samples, even at a trace Fe(III) dosage (i.e., 5 µM). Overall, this study provided a highly-efficient and eco-environmental strategy to remove sulfonamide antibiotics in Fe(III)/PAA process under actually neutral pH conditions and to strengthen its anti-interference capacity, underscoring its potential application in water treatment.

Hand Hygiene Education Components Among First-Year Nursing Students: A Cluster Randomized Clinical Trial.

Importance: Few studies have directly and objectively measured the individual and combined effects of multifaceted hand hygiene education programs. Objective: To evaluate the individual and combined immediate effects of an instructional video and hand scan images on handwashing quality, decontamination, and knowledge improvement. Design, Setting, and Participants: This cluster randomized clinical trial was conducted in June to July 2023 among first-year nursing students at a university in Hong Kong. The study used an intention-to-treat analysis. Intervention: Hand hygiene education sessions featuring an instructional video, hand scan images, or both. Main Outcomes and Measures: The primary outcome was the change in residue from fluorescent lotion remaining on participants' hands after handwashing before and after the intervention. The secondary outcomes included handwashing quality and knowledge of hand hygiene. Results: A total of 270 of 280 students (mean [SD] age, 19 [1] years; 182 [67.4%] female) participated in the trial (96.4% participation rate). Participants were randomized to a control group (66 participants), hand scan image group (68 participants), instructional video group (67 participants), and hand scan image with instructional video group (69 participants). All intervention groups had greater reductions in residue after the intervention compared with the control group, although none reached statistical significance (hand scan image group: 3.9 [95% CI, 2.0-5.8] percentage points; instructional video group: 4.8 [95% CI, 2.9-6.7] percentage points; hand scan image with instructional video: 3.5 [95% CI, 1.6-5.4] percentage points; control group: 3.2 [95% CI, 1.3-5.2] percentage points). The instructional video group showed a significant improvement in their handwashing performance, with a higher percentage of participants correctly performing all 7 steps compared with the control group (22.4% [95% CI, 13.1% to 31.6%] vs 1.5% [-7.9% to 10.9%]; P < .001). Hand scan images revealed that wrists, fingertips, and finger webs were the most commonly ignored areas in handwashing. Conclusions and Relevance: In this cluster randomized clinical trial of an education program for hand hygiene, a handwashing instructional video and hand scan images did not enhance the level of decontamination. The intervention group had improved handwashing techniques compared with the control group, a secondary outcome. Trial Registration: ClinicalTrials.gov Identifier: NCT05872581.

Potential factors affecting the success rate of indirect pulp therapy in primary molars with deep caries: a retrospective study.

Indirect pulp therapy (IPT) is a common conservative treatment for deep dental caries. However, the potential risk factors for the prognosis of IPT have not been well studied. This study retrospectively investigated the success rate of IPT in treating primary molars with deep caries and the factors potentially affecting the two-year success rate. A total of 303 primary molars in 202 children (106 boys and 96 girls) were included in this study. These primary molars were identified as having deep caries by clinical and radiographic examinations and were treated with IPT. The factors potentially affecting the IPT success rate were analyzed after two years of follow-up. The results indicated that the two-year IPT success rate was 86% (262/303). The success rate of primary molars with and without stainless steel crowns was 96% (120/125) and 80% (142/178), respectively. Primary molars treated with stainless steel crowns showed a significantly lower risk of failure (hazard ratio (HR) = 0.18, 95% confidence interval (CI): (0.10, 0.34), p = 0.01). There were no significant differences in other factors, including gender (male vs. female), age (preschool vs. school age), cooperation level (Frankl 2 vs. 3 or 4 scales), arch type (maxillary vs. mandibular), tooth type (first vs. second primary molar), or pulp capping material (calcium hydroxide vs. glass ionomer cement). IPT is an effective, conservative treatment modality for primary molars with deep caries. Stainless steel crowns could significantly improve the IPT success rate.

Meibomian glands segmentation in infrared images with limited annotation.

AIM: To investigate a pioneering framework for the segmentation of meibomian glands (MGs), using limited annotations to reduce the workload on ophthalmologists and enhance the efficiency of clinical diagnosis. METHODS: Totally 203 infrared meibomian images from 138 patients with dry eye disease, accompanied by corresponding annotations, were gathered for the study. A rectified scribble-supervised gland segmentation (RSSGS) model, incorporating temporal ensemble prediction, uncertainty estimation, and a transformation equivariance constraint, was introduced to address constraints imposed by limited supervision information inherent in scribble annotations. The viability and efficacy of the proposed model were assessed based on accuracy, intersection over union (IoU), and dice coefficient. RESULTS: Using manual labels as the gold standard, RSSGS demonstrated outcomes with an accuracy of 93.54%, a dice coefficient of 78.02%, and an IoU of 64.18%. Notably, these performance metrics exceed the current weakly supervised state-of-the-art methods by 0.76%, 2.06%, and 2.69%, respectively. Furthermore, despite achieving a substantial 80% reduction in annotation costs, it only lags behind fully annotated methods by 0.72%, 1.51%, and 2.04%. CONCLUSION: An innovative automatic segmentation model is developed for MGs in infrared eyelid images, using scribble annotation for training. This model maintains an exceptionally high level of segmentation accuracy while substantially reducing training costs. It holds substantial utility for calculating clinical parameters, thereby greatly enhancing the diagnostic efficiency of ophthalmologists in evaluating meibomian gland dysfunction.

CeO2 nanocages with tetra-enzyme mimetic activities for dual-channel ratiometric colorimetric detection of microcystins-LR.

BACKGROUND: Microcystin-leucine-arginine (MC-LR) produced by various cyanobacteria during harmful algal bloom poses serious threats to drinking water safety and human health. Conventional chromatography-based detection methods require expensive instruments and complicated sample pretreatment, limiting their application for on-site detection. Colorimetric aptasensors are simple and rapid, and are amenable to fast detection. However, they provide only one output signal, resulting in poor sensitivity and accuracy. Dual-channel ratiometric colorimetric method based on the peroxidase-like activity of nanozyme can achieve self-calibration by recording two reverse signals, providing significantly enhanced sensitivity and accuracy. RESULTS: CeO2 nanocages (CeO2 NCs) with tetra-enzyme mimetic activities (oxidase-, peroxidase-, catalase- and superoxide dismutase-like activities) were facilely synthesized using zeolitic imidazolate framework-67 (ZIF-67) as sacrificial template. The peroxidase-like activity of CeO2 NCs can be regulated by DNA, and it showed opposite response to two chromogenic substrates (2,2'-azino-bis-(3-ethylbenzthiazoline-6-sulfonic acid) (ABTS) and 3,3',5,5'-tetramethylbenzidine (TMB)), which was mainly attributed to the changed affinity. On the basis of MC-LR aptamer-tunable peroxidase-like activity of CeO2 NCs in TMB and ABTS channel, a dual-channel ratiometric colorimetric aptasensor was constructed for detection of MC-LR. Compared with conventional single-signal colorimetric assays, the proposed method showed lower limit of detection (0.66 pg mL-1) and significantly enhanced sensitivity. Moreover, the practicability of the ratiometric colorimetric assay was demonstrated by detecting MC-LR in real water samples, and satisfactory recoveries (94.9-101.9 %) and low relative standard deviations (1.6-6.3 %) were obtained. SIGNIFICANCE: This work presents a nanozyme-based ratiometric colorimetric aptasensor for MC-LR detection by recording the reverse responses of two chromogenic reactions. Benefiting from the self-calibration function, the method can achieve higher sensitivity and accuracy. The short detection time and practical application in real water samples show great potential for environmental monitoring.

Unsupervised lung CT image registration via stochastic decomposition of deformation fields.

We address the problem of lung CT image registration, which underpins various diagnoses and treatments for lung diseases. The main crux of the problem is the large deformation that the lungs undergo during respiration. This physiological process imposes several challenges from a learning point of view. In this paper, we propose a novel training scheme, called stochastic decomposition, which enables deep networks to effectively learn such a difficult deformation field during lung CT image registration. The key idea is to stochastically decompose the deformation field, and supervise the registration by synthetic data that have the corresponding appearance discrepancy. The stochastic decomposition allows for revealing all possible decompositions of the deformation field. At the learning level, these decompositions can be seen as a prior to reduce the ill-posedness of the registration yielding to boost the performance. We demonstrate the effectiveness of our framework on Lung CT data. We show, through extensive numerical and visual results, that our technique outperforms existing methods.

A murine model of post-acute neurological sequelae following SARS-CoV-2 variant infection.

Viral variant is one known risk factor associated with post-acute sequelae of COVID-19 (PASC), yet the pathogenesis is largely unknown. Here, we studied SARS-CoV-2 Delta variant-induced PASC in K18-hACE2 mice. The virus replicated productively, induced robust inflammatory responses in lung and brain tissues, and caused weight loss and mortality during the acute infection. Longitudinal behavior studies in surviving mice up to 4 months post-acute infection revealed persistent abnormalities in neuropsychiatric state and motor behaviors, while reflex and sensory functions recovered over time. In the brain, no detectable viral RNA and minimal residential immune cell activation was observed in the surviving mice post-acute infection. Transcriptome analysis revealed persistent activation of immune pathways, including humoral responses, complement, and phagocytosis, and gene expression levels associated with ataxia telangiectasia, impaired cognitive function and memory recall, and neuronal dysfunction and degeneration. Furthermore, surviving mice maintained potent systemic T helper 1 prone cellular immune responses and strong sera neutralizing antibodies against Delta and Omicron variants months post-acute infection. Overall, our findings suggest that infection in K18-hACE2 mice recapitulates the persistent clinical symptoms reported in long-COVID patients and provides new insights into the role of systemic and brain residential immune factors in PASC pathogenesis.

[Characteristics of caries-related oral microorganisms in early childhood caries].

PURPOSE: To study the structural characteristics of oral microorganisms in children with caries by 16S rRNA high-throughput sequencing technology. METHODS: Thirty healthy children aged 3-5 years were enrolled as subjects. According to the index of dmfs, they were divided into caries-free (CF) group (15) and early childhood caries (ECC) group(15). To compare the differences in bacterial community structure, samples of saliva and dental plaque were collected, and high-throughput sequencing was conducted using the Illumina Miseq sequencing platform. Bioinformatics analysis was used to analyze the difference of microbial community structure and diversity with SPSS 23.0 software package. RESULTS: Microbial diversity in ECC group was significantly lower than CF group. At phylum level, Actinobateria was more abundant in saliva samples of ECC group, while Firmicutes was more abundant in plaque samples of CF group. At genus level, the abundance of Lautropia of CF group was higher in saliva samples while Cardiobacterium, Gemella and Granulicatella were abundant in plaque samples. The abundance of Rothia of ECC group was higher in saliva samples and Corynebacterium was abundant of ECC group in plaque samples. CONCLUSIONS: There are significant differences in the species and composition of microbial community in saliva and plaque of children with or without caries. Specific microorganisms are related to the occurrence of ECC, and screening specific microorganisms is helpful for early prediction and prevention of ECC.

Use of serum KL-6 and chest radiographic severity grade to predict 28-day mortality in COVID-19 patients with pneumonia: a retrospective cohort study.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has had a global social and economic impact. An easy assessment procedure to handily identify the mortality risk of inpatients is urgently needed in clinical practice. Therefore, the aim of this study was to develop a simple nomogram model to categorize patients who might have a poor short-term outcome. METHODS: A retrospective cohort study of 189 COVID-19 patients was performed at Shanghai Ren Ji Hospital from December 12, 2022 to February 28, 2023. Chest radiography and biomarkers, including KL-6 were assessed. Risk factors of 28-day mortality were selected by a Cox regression model. A nomogram was developed based on selected variables by SMOTE strategy. The predictive performance of the derived nomogram was evaluated by calibration curve. RESULTS: In total, 173 patients were enrolled in this study. The 28-day mortality event occurred in 41 inpatients (23.7%). Serum KL-6 and radiological severity grade (RSG) were selected as the final risk factors. A nomogram model was developed based on KL-6 and RSG. The calibration curve suggested that the nomogram model might have potential clinical value. The AUCs for serum KL-6, RSG, and the combined score in the development group and validation group were 0.885 (95% CI: 0.804-0.952), 0.818 (95% CI: 0.711-0.899), 0.868 (95% CI: 0.776-0.942) and 0.932 (95% CI: 0.862-0.997), respectively. CONCLUSIONS: Our results suggested that the nomogram based on KL-6 and RSG might be a potential method for evaluating 28-day mortality in COVID-19 patients. A high combined score might indicate a poor outcome in COVID-19 patients with pneumonia.

Design, synthesis, and evaluation of novel quindoline derivatives with fork-shaped side chains as RNA G-quadruplex stabilizers for repressing oncogene NRAS translation.

NRAS mutation is the second most common oncogenic factor in cutaneous melanoma. Inhibiting NRAS translation by stabilizing the G-quadruplex (G4) structure with small molecules seems to be a potential strategy for cancer therapy due to the NRAS protein's lack of a druggable pocket. To enhance the effects of previously reported G4 stabilizers quindoline derivatives, we designed and synthesized a novel series of quindoline derivatives with fork-shaped side chains by introducing (alkylamino)alkoxy side chains. Panels of experimental results showed that introducing a fork-shaped (alkylamino)alkoxy side chain could enhance the stabilizing abilities of the ligands against NRAS RNA G-quadruplexes and their anti-melanoma activities. One of them, 10b, exhibited good antitumor activity in the NRAS-mutant melanoma xenograft mouse model, showing the therapeutic potential of this kind of compounds.

Dual-space high-frequency learning for transformer-based MRI super-resolution.

BACKGROUND AND OBJECTIVE: Magnetic resonance imaging (MRI) can provide rich and detailed high-contrast information of soft tissues, while the scanning of MRI is time-consuming. To accelerate MR imaging, a variety of Transformer-based single image super-resolution methods are proposed in recent years, achieving promising results thanks to their superior capability of capturing long-range dependencies. Nevertheless, most existing works prioritize the design of transformer attention blocks to capture global information. The local high-frequency details, which are pivotal to faithful MRI restoration, are unfortunately neglected. METHODS: In this work, we propose a high-frequency enhanced learning scheme to effectively improve the awareness of high frequency information in current Transformer-based MRI single image super-resolution methods. Specifically, we present two entirely plug-and-play modules designed to equip Transformer-based networks with the ability to recover high-frequency details from dual spaces: 1) in the feature space, we design a high-frequency block (Hi-Fe block) paralleled with Transformer-based attention layers to extract rich high-frequency features; while 2) in the image intensity space, we tailor a high-frequency amplification module (HFA) to further refine the high-frequency details. By fully exploiting the merits of the two modules, our framework can recover abundant and diverse high-frequency information, rendering faithful MRI super-resolved results with fine details. RESULTS: We integrated our modules with six Transformer-based models and conducted experiments across three datasets. The results indicate that our plug-and-play modules can enhance the super-resolution performance of all foundational models to varying degrees, surpassing the capabilities of existing state-of-the-art single image super-resolution networks. CONCLUSION: Comprehensive comparison of super-resolution images and high-frequency maps from various methods, clearly demonstrating that our module possesses the capability to restore high-frequency information, showing huge potential in clinical practice for accelerated MRI reconstruction.

Projection domain decomposition denoising algorithm based on low rank and similarity-based regularization.

BACKGROUND: Projection Domain Decomposition (PDD) is a dual energy reconstruction method which implements the decomposition process before image reconstruction. The advantage of PDD is that it can alleviate beam hardening artifacts and metal artifacts effectively as energy spectra estimation is considered in PDD. However, noise amplification occurs during the decomposition process, which significantly impacts the accuracy of effective atomic number and electron density. Therefore, effective noise reduction techniques are required in PDD. OBJECTIVE: This study aims to develop a new algorithm capable of minimizing noise while simultaneously preserving edges and fine details. METHODS: In this study, a denoising algorithm based on low rank and similarity-based regularization (LRSBR) is presented. This algorithm incorporates the low-rank characteristic of tensors into similarity-based regularization (SBR) framework. This method effectively addresses the issue of instability in edge pixels within the SBR algorithm and enhances the structural consistency of dual-energy images. RESULTS: A series of simulation and practical experiments were conducted on a dual-layer dual-energy CT system. Experiments demonstrate that the proposed method outperforms exiting noise removal methods in Peak Signal-to-noise Ratio (PSNR), Root Mean Square Error (RMSE), and Structural Similarity (SSIM). Meanwhile, there has been a notable enhancement in the visual quality of CT images. CONCLUSIONS: The proposed algorithm has a significantly improved noise reduction compared to other competing approach in dual-energy CT. Meanwhile, the LRSBR method exhibits outstanding performance in preserving edges and fine structures, making it practical for PDD applications.

Small RNA SmsR1 modulates acidogenicity and cariogenic virulence by affecting protein acetylation in Streptococcus mutans.

Post-transcriptional regulation by small RNAs and post-translational modifications (PTM) such as lysine acetylation play fundamental roles in physiological circuits, offering rapid responses to environmental signals with low energy consumption. Yet, the interplay between these regulatory systems remains underexplored. Here, we unveil the cross-talk between sRNAs and lysine acetylation in Streptococcus mutans, a primary cariogenic pathogen known for its potent acidogenic virulence. Through systematic overexpression of sRNAs in S. mutans, we identified sRNA SmsR1 as a critical player in modulating acidogenicity, a key cariogenic virulence feature in S. mutans. Furthermore, combined with the analysis of predicted target mRNA and transcriptome results, potential target genes were identified and experimentally verified. A direct interaction between SmsR1 and 5'-UTR region of pdhC gene was determined by in vitro binding assays. Importantly, we found that overexpression of SmsR1 reduced the expression of pdhC mRNA and increased the intracellular concentration of acetyl-CoA, resulting in global changes in protein acetylation levels. This was verified by acetyl-proteomics in S. mutans, along with an increase in acetylation level and decreased activity of LDH. Our study unravels a novel regulatory paradigm where sRNA bridges post-transcriptional regulation with post-translational modification, underscoring bacterial adeptness in fine-tuning responses to environmental stress.

STADNet: Spatial-Temporal Attention-Guided Dual-Path Network for cardiac cine MRI super-resolution.

Cardiac cine magnetic resonance imaging (MRI) is a commonly used clinical tool for evaluating cardiac function and morphology. However, its diagnostic accuracy may be compromised by the low spatial resolution. Current methods for cine MRI super-resolution reconstruction still have limitations. They typically rely on 3D convolutional neural networks or recurrent neural networks, which may not effectively capture long-range or non-local features due to their limited receptive fields. Optical flow estimators are also commonly used to align neighboring frames, which may cause information loss and inaccurate motion estimation. Additionally, pre-warping strategies may involve interpolation, leading to potential loss of texture details and complicated anatomical structures. To overcome these challenges, we propose a novel Spatial-Temporal Attention-Guided Dual-Path Network (STADNet) for cardiac cine MRI super-resolution. We utilize transformers to model long-range dependencies in cardiac cine MR images and design a cross-frame attention module in the location-aware spatial path, which enhances the spatial details of the current frame by using complementary information from neighboring frames. We also introduce a recurrent flow-enhanced attention module in the motion-aware temporal path that exploits the correlation between cine MRI frames and extracts the motion information of the heart. Experimental results demonstrate that STADNet outperforms SOTA approaches and has significant potential for clinical practice.

Structure modification of anoplin for fighting resistant bacteria.

The emergence of bacterial resistance has posed a significant challenge to clinical antimicrobial treatment, rendering commonly used antibiotics ineffective. The development of novel antimicrobial agents and strategies is imperative for the treatment of resistant bacterial infections. Antimicrobial peptides (AMPs) are considered a promising class of antimicrobial agents due to their low propensity for resistance and broad-spectrum activity. Anoplin is a small linear α-helical natural antimicrobial peptide that was isolated from the venom of the solitary wasp Anplius samariensis. It exhibits rich biological activity, particularly broad-spectrum antimicrobial activity and low hemolytic activity. Over the past three decades, more than 40 research publications on anoplin have been made available online. This review focuses on the advancements of anoplin in antimicrobial research, encompassing its sources, characterization, antimicrobial activity, influencing factors and structural modifications. The aim is to provide assistances for the development of new antimicrobial agents that can combat bacterial resistance.