Identifying Barriers and Facilitators to Accessing Care for Historically Marginalized Communities Affected by Parkinson Disease: A Qualitative Study.

INTRODUCTION: Parkinson disease (PD) is the second most common neurodegenerative disease. Members of the Black Diaspora (MBD) and Hispanic/Latinx people are less likely to receive a timely diagnosis following the onset of symptoms and more likely to experience greater disease severity due to late diagnosis. Historically marginalized populations (i.e., MBD, Hispanic, and Latinx communities) are not accurately represented in research; this, along with many other barriers, compounds underreporting and lack of recognition of PD. It is important to understand barriers to early diagnosis and healthcare access for these historically marginalized populations from the community's perspective. METHODS: Our team conducted two focus groups to identify barriers and facilitators to PD healthcare-seeking behavior. We sought to identify which barriers are modifiable to ultimately improve engagement in neurological care for MBD and Hispanic individuals affected by PD. RESULTS: We enrolled 15 participants (13 female; African/African American/Black n = 10, Hispanic/Puerto Rican n = 3, other n = 2) for two focus groups. Discussions revealed sources of barriers to healthcare-seeking behavior in three main domains: legacy of racism in the United States, ancestral cultural environment, and healthcare system access. These sources influenced individuals' PD knowledge and familiarity. Additionally, participants expressed a desire to know more about PD and called for increased community-based programming for education and awareness. DISCUSSION: This paper uses a community-based participatory research approach to describe the experiences of MBD, Hispanic, and Latinx people in Manhattan and the surrounding areas in relation to possible sources of healthcare disparities and delayed PD diagnosis. These sources have broad implications and should be addressed through collaborative community programming.

An unexpected role of EasDaf: catalyzing the conversion of chanoclavine aldehyde to chanoclavine acid.

Ergot alkaloids (EAs) are a diverse group of indole alkaloids known for their complex structures, significant pharmacological effects, and toxicity to plants. The biosynthesis of these compounds begins with chanoclavine-I aldehyde (CC aldehyde, 2), an important intermediate produced by the enzyme EasDaf or its counterpart FgaDH from chanoclavine-I (CC, 1). However, how CC aldehyde 2 is converted to chanoclavine-I acid (CC acid, 3), first isolated from Ipomoea violacea several decades ago, is still unclear. In this study, we provide in vitro biochemical evidence showing that EasDaf not only converts CC 1 to CC aldehyde 2 but also directly transforms CC 1 into CC acid 3 through two sequential oxidations. Molecular docking and site-directed mutagenesis experiments confirmed the crucial role of two amino acids, Y166 and S153, within the active site, which suggests that Y166 acts as a general base for hydride transfer, while S153 facilitates proton transfer, thereby increasing the acidity of the reaction. KEY POINTS: • EAs possess complicated skeletons and are widely used in several clinical diseases • EasDaf belongs to the short-chain dehydrogenases/reductases (SDRs) and converted CC or CC aldehyde to CC acid • The catalytic mechanism of EasDaf for dehydrogenation was analyzed by molecular docking and site mutations.

Specific Knockdown of the NDUFS4 Gene Reveals Important Roles of Ferroptosis in UVB-induced Photoaging.

Ultraviolet (UV) irradiation significantly contributes to photoaging. Ferroptosis, an iron-dependent cell death mode recently identified, plays a key role in UVB-induced skin photoaging. This study examines the functions and regulatory mechanisms of ferroptosis in this regard. Characterized by increased intracellular iron and reactive oxygen species (ROS), ferroptosis is associated with mitochondrial function and structure. Through RNA sequencing, we identified NADH: ubiquinone oxidoreductase subunit S4 (NDUFS4), a gene implicated in UVB-mediated photoaging, and explored its role in ferroptosis by NDUFS4 knockdown. In vitro, inhibiting NDUFS4 reduced ferroptosis, decreased ROS and matrix metallopeptidase 1 levels, and increased collagen type I alpha 1 chain, glutathione peroxidase 4 (GPX4), ferritin heavy chain 1, and solute carrier family 7 member 11 levels, suggesting a reinforced ferroptosis protective mechanism. Additionally, NDUFS4 regulates ferroptosis via the mitogen-activated protein kinase (MAPK) pathway, with its knockdown reducing p38 and ERK phosphorylation and elevating GPX4 levels, enhancing ferroptosis resistance. Animal experiments supported these findings, demonstrating that Ferrostatin-1, a ferroptosis inhibitor, significantly mitigated UVB-induced skin photoaging and related protein expression. This study uncovers NDUFS4's novel role in regulating ferroptosis and provides new insights into ferroptosis-mediated UVB-induced skin photoaging.

Evaluation of Biomechanical and Mental Workload During Human-Robot Collaborative Pollination Task.

OBJECTIVE: The purpose of this study is to identify the potential biomechanical and cognitive workload effects induced by human robot collaborative pollination task, how additional cues and reliability of the robot influence these effects and whether interacting with the robot influences the participant's anxiety and attitude towards robots. BACKGROUND: Human-Robot Collaboration (HRC) could be used to alleviate pollinator shortages and robot performance issues. However, the effects of HRC for this setting have not been investigated. METHODS: Sixteen participants were recruited. Four HRC modes, no cue, with cue, unreliable, and manual control were included. Three categories of dependent variables were measured: (1) spine kinematics (L5/S1, L1/T12, and T1/C7), (2) pupillary activation data, and (3) subjective measures such as perceived workload, robot-related anxiety, and negative attitudes towards robotics. RESULTS: HRC reduced anxiety towards the cobot, decreased joint angles and angular velocity for the L5/S1 and L1/T12 joints, and reduced pupil dilation, with the "with cue" mode producing the lowest values. However, unreliability was detrimental to these gains. In addition, HRC resulted in a higher flexion angle for the neck (i.e., T1/C7). CONCLUSION: HRC reduced the physical and mental workload during the simulated pollination task. Benefits of the additional cue were minimal compared to no cues. The increased joint angle in the neck and unreliability affecting lower and mid back joint angles and workload requires further investigation. APPLICATION: These findings could be used to inform design decisions for HRC frameworks for agricultural applications that are cognizant of the different effects induced by HRC.

Revealing Metabolic Dysregulation Induced by Polypropylene Nano- and Microplastics in Nile Tilapia via Noninvasive Probing Epidermal Mucus.

A noninvasive sampling technology was conceived, employing a disposable acupuncture needle in conjunction with high-resolution mass spectrometry (termed as noninvasive direct sampling extractive electrospray ionization mass spectrometry, NIDS-EESI-MS) to scrutinize the epidermal mucus of Nile tilapia for insights into the metabolic dysregulation induced by polypropylene nano- and microplastics. This analytical method initiates with the dispensing of an extraction solvent onto the needles coated with the mucus sample, almost simultaneously applying a high voltage to generate analyte ions. This innovative strategy obliterates the necessitation for laborious sample preparation, thereby simplifying the sampling process. Employing this technique facilitated the delineation of a plethora of metabolites, encompassing, but not confined to, amino acids, peptides, carbohydrates, ketones, fatty acids, and their derivatives. Follow-up pathway enrichment analysis exposed notable alterations within key metabolic pathways, including the biosynthesis of phenylalanine, tyrosine, and tryptophan, lysine degradation, as well as the biosynthesis and metabolism of valine, leucine, and isoleucine pathways in Nile tilapia, consequent to increased concentrations of polypropylene nanoplastics. These metabolic alterations portend potential implications such as immune suppression, among other deleterious outcomes. This trailblazing application of this methodology not only spares aquatic life from sacrifice but also inaugurates an ethical paradigm for conducting longitudinal studies on the same organisms, facilitating detailed investigations into the long-term effects of environmental pollutants. This technique enhances the ability to observe and understand the subtle yet significant impacts of such contaminants over time.

A whole-slide foundation model for digital pathology from real-world data.

Digital pathology poses unique computational challenges, as a standard gigapixel slide may comprise tens of thousands of image tiles1-3. Prior models have often resorted to subsampling a small portion of tiles for each slide, thus missing the important slide-level context4. Here we present Prov-GigaPath, a whole-slide pathology foundation model pretrained on 1.3 billion 256 × 256 pathology image tiles in 171,189 whole slides from Providence, a large US health network comprising 28 cancer centres. The slides originated from more than 30,000 patients covering 31 major tissue types. To pretrain Prov-GigaPath, we propose GigaPath, a novel vision transformer architecture for pretraining gigapixel pathology slides. To scale GigaPath for slide-level learning with tens of thousands of image tiles, GigaPath adapts the newly developed LongNet5 method to digital pathology. To evaluate Prov-GigaPath, we construct a digital pathology benchmark comprising 9 cancer subtyping tasks and 17 pathomics tasks, using both Providence and TCGA data6. With large-scale pretraining and ultra-large-context modelling, Prov-GigaPath attains state-of-the-art performance on 25 out of 26 tasks, with significant improvement over the second-best method on 18 tasks. We further demonstrate the potential of Prov-GigaPath on vision-language pretraining for pathology7,8 by incorporating the pathology reports. In sum, Prov-GigaPath is an open-weight foundation model that achieves state-of-the-art performance on various digital pathology tasks, demonstrating the importance of real-world data and whole-slide modelling.

Electroacupuncture stimulation modulates functional brain connectivity in the treatment of pediatric cerebral palsy: a case report.

Background: Pediatric cerebral palsy (CP) is a non-progressive brain injury syndrome characterized by central motor dysfunction and insufficient brain coordination ability. The etiology of CP is complex and often accompanied by diverse complications such as intellectual disability and language disorders, making clinical treatment difficult. Despite the availability of pharmacological interventions, rehabilitation programs, and spasticity relief surgery as treatment options for CP, their effectiveness is still constrained. Electroacupuncture (EA) stimulation has demonstrated great improvements in motor function, but its comprehensive, objective therapeutic effects on pediatric CP remain to be clarified. Methods: We present a case of a 5-year-old Chinese female child who was diagnosed with CP at the age of 4. The patient exhibited severe impairments in motor, language, social, and cognitive functions. We performed a 3-month period of EA rehabilitation, obtaining resting state functional magnetic resonance imaging (rs-fMRI) of the patient at 0 month, 3 months and 5 months since treatment started, then characterized brain functional connectivity patterns in each phase for comparison. Results: After a 12-month follow-up, notable advancements were observed in the patient's language and social symptoms. Changes of functional connectivity patterns confirmed this therapeutic effect and showed specific benefits for different recovery phase: starting from language functions then modulating social participation and other developmental behaviors. Conclusion: This is a pioneering report demonstrating the longitudinal effect of EA stimulation on functional brain connectivity in CP patients, suggesting EA an effective intervention for developmental disabilities (especially language and social dysfunctions) associated with pediatric CP.

Analysis of fungal diversity in the gut feces of wild takin (Budorcas taxicolor).

Introduction: The composition of the intestinal microbiome correlates significantly with an animal's health status. Hence, this indicator is highly important and sensitive for protecting endangered animals. However, data regarding the fungal diversity of the wild Budorcas taxicolor (takin) gut remain scarce. Therefore, this study analyzes the fungal diversity, community structure, and pathogen composition in the feces of wild B. taxicolor. Methods: To ensure comprehensive data analyses, we collected 82 fecal samples from five geographical sites. Amplicon sequencing of the internal transcribed spacer (ITS) rRNA was used to assess fecal core microbiota and potential pathogens to determine whether the microflora composition is related to geographical location or diet. We further validated the ITS rRNA sequencing results via amplicon metagenomic sequencing and culturing of fecal fungi. Results and discussion: The fungal diversity in the feces of wild Budorcas taxicolor primarily comprised three phyla (99.69%): Ascomycota (82.19%), Fungi_unclassified (10.37%), and Basidiomycota (7.13%). At the genus level, the predominant fungi included Thelebolus (30.93%), Functional_unclassified (15.35%), and Ascomycota_unclassified (10.37%). Within these genera, certain strains exhibit pathogenic properties, such as Thelebolus, Cryptococcus, Trichosporon, Candida, Zopfiella, and Podospora. Collectively, this study offers valuable information for evaluating the health status of B. taxicolor and formulating protective strategies.

Rapid quantitative authentication and analysis of camellia oil adulterated with edible oils by electronic nose and FTIR spectroscopy.

Camellia oil, recognized as a high-quality edible oil endorsed by the Food and Agriculture Organization, is confronted with authenticity issues arising from fraudulent adulteration practices. These practices not only pose health risks but also lead to economic losses. This study proposes a novel machine learning framework, referred to as a transformer encoder backbone with a support vector machine regressor (TES), coupled with an electronic nose (E-nose), for detecting varying adulteration levels in camellia oil. Experimental results indicate that the proposed TES model exhibits the best performance in identifying the adulterated concentration of camellia oi, compared with five other machine learning models (the support vector machine, random forest, XGBoost, K-nearest neighbors, and backpropagation neural network). The results obtained by E-nose detection are verified by complementary Fourier transform infrared (FTIR) spectroscopy analysis for identifying functional groups, ensuring accuracy and providing a comprehensive assessment of the types of adulterants. The proposed TES model combined with E-nose offers a rapid, effective, and practical tool for detecting camellia oil adulteration. This technique not only safeguards consumer health and economic interests but also promotes the application of E-nose in market supervision.

Impact of Booster Vaccination Interval on SARS-CoV-2 Infection, Hospitalization, and Death.

OBJECTIVES: We investigated how booster interval affects the risks of SARS-CoV-2 infection and Covid-19-related hospitalization and death in different age groups. METHODS: We collected data on booster receipts and Covid-19 outcomes between September 22, 2021 and February 9, 2023 for 5,769,205 North Carolina residents ≥12 years of age who had completed their primary vaccination series. We related Covid-19 outcomes to baseline characteristics and booster doses through Cox regression models. RESULTS: For adults ≥65 years of age, boosting every 9 months was associated with proportionate reductions (compared with no boosting) of 18.9% (95% CI, 18.5 to 19.4) in the cumulative frequency of infection, 37.8% (95% CI, 35.3 to 40.3) in the cumulative risk of hospitalization or death, and 40.9% (95% CI, 37.2 to 44.7) in the cumulative risk of death at two years after completion of primary vaccination. The reductions were lower by boosting every 12 months and higher by boosting every 6 months. The reductions were smaller for individuals 12-64 years of age. CONCLUSION: Boosting at a shorter interval was associated with a greater reduction in Covid-19 outcomes, especially hospitalization and death. Frequent boosting conferred greater benefits for individuals aged ≥65 than for individuals aged 12-64.

A preliminary study on calcifying nanoparticles in dental plaque: Isolation, characterization, and potential mineralization mechanism.

OBJECTIVES: Calcifying nanoparticles (CNPs), referred to as nanobacteria (NB), are recognized to be associated with ectopic calcification. This study aims to isolate and culture CNPs from the dental plaque of patients with periodontal disease and investigate their possible role in unravelling the aetiology of periodontal disease. MATERIAL AND METHODS: Supragingival and subgingival plaques were sampled from 30 periodontitis patients for CNPs isolation and culture. Alkaline phosphatase (ALP) content changes were tracked over time. Positive samples underwent thorough morphological identification via hematoxylin and eosin (HE) staining, Alizarin red S (ARS), and transmission electron microscopy (TEM). The chemical composition of CNPs analysis involved calcium (Ca) and phosphorus (P) content determination, Fourier transform infrared spectroscopy (FTIR), and X-ray diffraction (XRD). RESULTS: The subgingival plaque dental group exhibited a higher CNPs isolation rate at 36.67% (11/30) compared to the supragingival dental plaque group at 66.67% (20/30). ALP activity varied among the positive, negative and control groups. Morphological observation characterized the CNPs as round, oval, and ellipsoid particles with Ca deposits. Chemical analysis revealed the Ca/P ratio was 0.6753. Hydroxyl, methyl, carbonate, phosphate, hydrogen phosphate, and dihydrogen phosphate were detected by FTIR; the main chemical components detected by XRD were hydroxyapatite and tricalcium phosphate. CONCLUSION: CNPs were found in periodontitis-related dental plaque and exhibited the potential to develop calcified structures resembling dental calculus. However, the potential involvement of ALP in CNPs formation requires deeper exploration, as does the precise nature of its role and the interrelation with periodontitis demand a further comprehensive investigation.

CircPIAS1 promotes hepatocellular carcinoma progression by inhibiting ferroptosis via the miR-455-3p/NUPR1/FTH1 axis.

BACKGROUND: The role of circRNAs in hepatocellular carcinoma (HCC) progression remains unclear. CircPIAS1 (circBase ID: hsa_circ_0007088) was identified as overexpressed in HCC cases through bioinformatics analysis. This study aimed to investigate the oncogenic properties and mechanisms of circPIAS1 in HCC development. METHODS: Functional analyses were conducted to assess circPIAS1's impact on HCC cell proliferation, migration, and ferroptosis. Xenograft mouse models were employed to evaluate circPIAS1's effects on tumor growth and pulmonary metastasis in vivo. Bioinformatics analysis, RNA immunoprecipitation, and luciferase reporter assays were utilized to elucidate the molecular pathways influenced by circPIAS1. Additional techniques, including RNA pulldown, fluorescence in situ hybridization (FISH), chromatin immunoprecipitation (ChIP), qPCR, and western blotting, were used to further explore the underlying mechanisms. RESULTS: CircPIAS1 expression was elevated in HCC tissues and cells. Silencing circPIAS1 suppressed HCC cell proliferation and migration both in vitro and in vivo. Mechanically, circPIAS1 overexpression inhibited ferroptosis by competitively binding to miR-455-3p, leading to upregulation of Nuclear Protein 1 (NUPR1). Furthermore, NUPR1 promoted FTH1 transcription, enhancing iron storage in HCC cells and conferring resistance to ferroptosis. Treatment with ZZW-115, an NUPR1 inhibitor, reversed the tumor-promoting effects of circPIAS1 and sensitized HCC cells to lenvatinib. CONCLUSION: This study highlights the critical role of circPIAS1 in HCC progression through modulation of ferroptosis. Targeting the circPIAS1/miR-455-3p/NUPR1/FTH1 regulatory axis may represent a promising therapeutic strategy for HCC.

Endodontic Microsurgery Outcomes over 10 Years and Associated Prognostic Factors: A Retrospective Cohort Study.

INTRODUCTION: This retrospective cohort study aimed to evaluate long-term healing outcomes (10-17.5 years) after contemporary endodontic microsurgery (EMS) and identify the associated prognostic factors. METHODS: Clinical and radiographic data of an EMS cohort (2006-2013) from the electronic database of the dental hospital were reviewed retrospectively by 2 independent examiners to determine their survival and healing outcomes, and potential prognostic factors were analyzed by Cox proportional hazards regression and logistic regression (α = 0.05). RESULTS: Through strict inclusion and exclusion criteria and 721 EMS-treated teeth in the cohort, 309 (42.9%) were included (male = 35.0%; female = 65.0%; age = 45.83 ± 15.53 years) with a mean final follow-up of 152.26 ± 26.37 months (range, 120-211 months; median = 148 months). Clinical and radiographic assessments found an 80.5% 10-year survival rate with 63.4% of success. Collectively, tooth type, tooth mobility, preoperative lesion size, clinical crown-to-root ratio, and crown restorations at follow-up were significantly associated with long-term success and survival over 10 years. CONCLUSIONS: The preoperative status and condition of the tooth including its alveolar bone support and adequate full-crown restorations may be relevant prognostic determinants of success and survival after EMS over time.

Prior knowledge-guided multilevel graph neural network for tumor risk prediction and interpretation via multi-omics data integration.

The interrelation and complementary nature of multi-omics data can provide valuable insights into the intricate molecular mechanisms underlying diseases. However, challenges such as limited sample size, high data dimensionality and differences in omics modalities pose significant obstacles to fully harnessing the potential of these data. The prior knowledge such as gene regulatory network and pathway information harbors useful gene-gene interaction and gene functional module information. To effectively integrate multi-omics data and make full use of the prior knowledge, here, we propose a Multilevel-graph neural network (GNN): a hierarchically designed deep learning algorithm that sequentially leverages multi-omics data, gene regulatory networks and pathway information to extract features and enhance accuracy in predicting survival risk. Our method achieved better accuracy compared with existing methods. Furthermore, key factors nonlinearly associated with the tumor pathogenesis are prioritized by employing two interpretation algorithms (i.e. GNN-Explainer and IGscore) for neural networks, at gene and pathway level, respectively. The top genes and pathways exhibit strong associations with disease in survival analyses, many of which such as SEC61G and CYP27B1 are previously reported in the literature.

Anti-inflammatory Steroids from the South China Sea Sponge Spongia officinalis.

One new highly degraded steroid, namely 21-nor-4-ene-chaxine A (1) furnishing a 5/6/5-tricyclic, along with one known related analogue (2), were isolated from the South China Sea sponge Spongia officinalis. Their structures including absolute configurations were established by extensive spectroscopic data analysis, TDDFT-ECD calculation, and comparison with the spectral data previously reported in the literature. Compound 1 represent the new member of incisterols family with a highly degradation in ring B. In vitro bioassays revealed compound 2 exhibited significant anti-microglial inflammatory effect on lipopolysaccharide (LPS)-induced inflammation in BV-2 microglial cells.

Prevalence of nonalcoholic fatty liver disease and liver cirrhosis in Chinese adults with type 2 diabetes mellitus.

BACKGROUND: Nonalcoholic fatty liver disease (NAFLD) and liver cirrhosis are significant clinical concerns, especially among individuals with type 2 diabetes mellitus (T2DM). However, in China, there is a paucity of reliable evidence detailing the characteristics of NAFLD and liver cirrhosis in T2DM. Furthermore, the relationship between blood glucose levels and NAFLD prevalence remains unclear. METHODS: Data from the Shanghai Suburban Adult Cohort and Biobank were analyzed, including 6621 participants with T2DM. NAFLD was diagnosed by ultrasonography and liver cirrhosis was performed according to the health information systems. Logistic regression and restricted cubic spline analysis were used to explore the potential risk factors for NAFLD and liver cirrhosis. RESULTS: The prevalence of NAFLD was 59.36%, and liver cirrhosis was 1.43% among T2DM patients. In these patients, factors like age, being female, marital status, and obesity significantly increased the risk of NAFLD. Specifically, obesity had a strong positive association with NAFLD (odds ratio [OR] = 4.70, 95% confidence interval [CI]: 4.13-5.34). The higher glycated hemoglobin (HbA1c) quartile was associated with a heightened NAFLD risk compared to the lowest quartile (all p < .001). The HbA1c-NAFLD relationship displayed a linear that mimicked an inverted L-shaped pattern. A significant positive association existed between HbA1c levels and NAFLD for HbA1c <8.00% (OR = 1.59, 95% CI: 1.44-1.75), but this was not observed for HbA1c >8.00% (OR = 1.03, 95% CI: 0.92-1.15). CONCLUSION: Systematic screening for NAFLD is essential in T2DM patients, especially with poor glucose control and obesity in female.

Genus Shewanella: A Potential Intestinal Colonizer Associated With Post-Operative Surgical Site Infections in Coastal Regions.

Background: This study aims to elucidate the clinical characteristics of Shewanella-related surgical site infections (SSIs) and assess the risk of mortality in patients by establishing a predictive model. Patients and Methods: A retrospective analysis of medical history and laboratory data of Shewanella-related SSI patients over the past decade was conducted via the electronic medical record (EMR) system. A predictive model for mortality risk in Shewanella-related SSI patients was established using plasma interleukin-6 (IL-6) levels combined with the Howell-PIRO scoring system. Results: Over the past 10 years, 45 strains of Shewanella were isolated from specimens such as bile, drainage fluid, and whole blood in patients with digestive tract SSIs. Among them, 21 of 45 (46.67%) patients underwent malignant tumor resection of the digestive system, 14 of 45 (31.11%) underwent endoscopic retrograde cholangiopancreatography (ERCP) common bile duct exploration or the stone removal, and seven of 45 (15.56%) were trauma repair patients with fractures and abdominal injuries. Among the 45 Shewanella-related SSI patients, 10 died within 30 days of infection, six cases involved infections with more than two other types of bacteria. The combined use of IL-6 and Howell-PIRO scores for mortality risk assessment yielded an receiver operating characteristic (ROC) curve with an area under the curve (AUC) of 0.9350, a positive predictive value of 92.71%, a negative predictive value of 94.58%, a diagnostic sensitivity of 95.35%, and a diagnostic specificity of 92.14%-all higher than the model using IL-6 or Howell-PIRO scores alone. Conclusions: We found that residents in coastal areas faced an increased risk of Shewanella-related SSI. Moreover, the higher the number of concurrent microbial infections occurring alongside Shewanella-related SSI, the greater the mortality rate among patients. The combined application of plasma IL-6 levels and the Howell-PIRO scoring system is beneficial for assessing patient mortality risk and guiding timely and proactive clinical interventions.

GMAlignNet: multi-scale lightweight brain tumor image segmentation with enhanced semantic information consistency.

Although the U-shaped architecture, represented by UNet, has become a major network model for brain tumor segmentation, the repeated convolution and sampling operations can easily lead to the loss of crucial information. Additionally, directly fusing features from different levels without distinction can easily result in feature misalignment, affecting segmentation accuracy. On the other hand, traditional convolutional blocks used for feature extraction cannot capture the abundant multi-scale information present in brain tumor images. This paper proposes a multi-scale feature-aligned segmentation model called GMAlignNet that fully utilizes Ghost convolution to solve these problems. Ghost hierarchical decoupled fusion unit and Ghost hierarchical decoupled unit are used instead of standard convolutions in the encoding and decoding paths. This transformation replaces the holistic learning of volume structures by traditional convolutional blocks with multi-level learning on a specific view, facilitating the acquisition of abundant multi-scale contextual information through low-cost operations. Furthermore, a feature alignment unit is proposed that can utilize semantic information flow to guide the recovery of upsampled features. It performs pixel-level semantic information correction on misaligned features due to feature fusion. The proposed method is also employed to optimize three classic networks, namely DMFNet, HDCNet, and 3D UNet, demonstrating its effectiveness in automatic brain tumor segmentation. The proposed network model was applied to the BraTS 2018 dataset, and the results indicate that the proposed GMAlignNet achieved Dice coefficients of 81.65%, 90.07%, and 85.16% for enhancing tumor, whole tumor, and tumor core segmentation, respectively. Moreover, with only 0.29 M parameters and 26.88G FLOPs, it demonstrates better potential in terms of computational efficiency and possesses the advantages of lightweight. Extensive experiments on the BraTS 2018, BraTS 2019, and BraTS 2020 datasets suggest that the proposed model exhibits better potential in handling edge details and contour recognition.

In Situ Electrochemical Atomic Force Microscopy: From Interfaces to Interphases.

The electrochemical interface formed between an electrode and an electrolyte significantly affects the rate and mechanism of the electrode reaction through its structure and properties, which vary across the interface. The scope of the interface has been expanded, along with the development of energy electrochemistry, where a solid-electrolyte interphase may form on the electrode and the active materials change properties near the surface region. Developing a comprehensive understanding of electrochemical interfaces and interphases necessitates three-dimensional spatial resolution characterization. Atomic force microscopy (AFM) offers advantages of imaging and long-range force measurements. Here we assess the capabilities of AFM by comparing the force curves of different regimes and various imaging modes for in situ characterizing of electrochemical interfaces and interphases. Selected examples of progress on work related to the structures and processes of electrode surfaces, electrical double layers, and lithium battery systems are subsequently illustrated. Finally, this review provides perspectives on the future development of electrochemical AFM.

In Vivo Imaging MicroRNA with Bright Fluorescent RNA Aptamer Through Target-Mediated Entropy-Driven Toehold Exchange.

MicroRNAs (miRNAs) play vital roles in biological activities, but their in vivo imaging is still challenging due to the low abundance and the lack of efficient fluorescent tools. RNA aptamers with high affinity and low background emerge for bioimaging yet suffering from low brightness. We introduce a rational design based on target-mediated entropy-driven toehold exchange (EDTE) to induce the release of RNA aptamer and subsequently light up corresponding fluorophore, which achieves selective imaging of miRNAs with good stability in both living cells and tumor-bearing mouse. Through tailoring recognition unit of the EDTE probes, highly sensitive imaging of different miRNAs including miRNA-125b and miRNA-21 is achieved, confirming its universal bioimaging applications. In comparison with the reported "one-to-one" model, the EDTE strategy shows a remarkable 4.6-time improvement in signal/noise ratio for intracellular imaging of the same miRNA. Particularly, it realizes sensitive imaging of miRNA in vivo, providing a promising tool in investigating functions and interactions of disease-associated miRNAs.