HST-MRF: Heterogeneous Swin Transformer With Multi-Receptive Field for Medical Image Segmentation.

The Transformer has been successfully used in medical image segmentation due to its excellent long-range modeling capabilities. However, patch segmentation is necessary when building a Transformer class model. This process ignores the tissue structure features within patch, resulting in the loss of shallow representation information. In this study, we propose a Heterogeneous Swin Transformer with Multi-Receptive Field (HST-MRF) model that fuses patch information from different receptive fields to solve the problem of loss of feature information caused by patch segmentation. The heterogeneous Swin Transformer (HST) is the core module, which achieves the interaction of multi-receptive field patch information through heterogeneous attention and passes it to the next stage for progressive learning, thus complementing the patch structure information. We also designed a two-stage fusion module, multimodal bilinear pooling (MBP), to assist HST in further fusing multi-receptive field information and combining low-level and high-level semantic information for accurate localization of lesion regions. In addition, we developed adaptive patch embedding (APE) and soft channel attention (SCA) modules to retain more valuable information when acquiring patch embedding and filtering channel features, respectively, thereby improving model segmentation quality. We evaluated HST-MRF on multiple datasets for polyp, skin lesion and breast ultrasound segmentation tasks. Experimental results show that our proposed method outperforms state-of-the-art models and can achieve superior performance. Furthermore, we verified the effectiveness of each module and the benefits of multi-receptive field segmentation in reducing the loss of structural information through ablation experiments and qualitative analysis.

Causes and global, regional, and national burdens of traumatic brain injury from 1990 to 2019.

PURPOSE: Traumatic brain injury (TBI), currently a major global public health problem, imposes a significant economic burden on society and families. We aimed to quantify and predict the incidence and severity of TBI by analyzing its incidence, prevalence, and years lived with disability (YLDs). The epidemiological changes in TBI from 1990 to 2019 were described and updated to provide a reference for developing prevention, treatment, and incidence-reducing measures for TBI. METHODS: A secondary analysis was performed on the incidence, prevalence, and YLDs of TBI by sex, age group, and region (n = 21,204 countries and territories) between 1990 and 2019 using the Global Burden of Diseases, Injuries, and Risk Factors Study 2019. Proportions in the age-standardized incidence rate due to underlying causes of TBI and proportions of minor and moderate or severe TBI were also reported. RESULTS: In 2019, there were 27.16 million (95% uncertainty intervals (UI): 23.36 - 31.42) new cases of TBI worldwide, with age-standardized incidence and prevalence rates of 346 per 100,000 population (95% UI: 298-401) and 599 per 100,000 population (95% UI: 573-627), respectively. From 1990 to 2019, there were no significant trends in global age-standardized incidence (estimated annual percentage changes: -0.11%, 95% UI: -0.18% - -0.04%) or prevalence (estimated annual percentage changes: 0.01%, 95% UI: -0.04% - 0.06%). TBI caused 7.08 million (95% UI: 5.00 - 9.59) YLDs in 2019, with age-standardized rates of 86.5 per 100,000 population (95% UI: 61.1 - 117.2). In 2019, the countries with higher incidence rates were mainly distributed in Central Europe, Eastern Europe, and Australia. The 2019 global age-standardized incidence rate was higher in males than in females. The 2019 global incidence of moderate and severe TBI was 182.7 per 100,000 population, accounting for 52.8% of all TBI, with falls and road traffic injuries being the main causes in most regions. CONCLUSIONS: The incidence of moderate and severe TBI was slightly higher in 2019, and TBI still accounts for a significant portion of the global injury burden. The likelihood of moderate to severe TBI and the trend of major injury under each injury cause from 1990 to 2019 and the characteristics of injury mechanisms in each age group are presented, providing a basis for further research on injury causes in each age group and the future establishment of corresponding policies and protective measures.

Matrix stiffness regulates macrophage polarisation via the Piezo1-YAP signalling axis.

Macrophages play a pivotal role in the immunological cascade activated in response to biomedical implants, which predetermine acceptance or rejection of implants by the host via pro- and anti-inflammatory polarisation states. The role of chemical signals in macrophage polarisation is well-established, but how physical cues regulate macrophage function that may play a fundamental role in implant-bone interface, remains poorly understood. Here we find that bone marrow-derived macrophages (BMDM) cultured on polyacrylamide gels of varying stiffness exhibit different polarisation states. BMDM are 'primed' to a pro-inflammatory M1 phenotype on stiff substrates, while to an anti-inflammatory M2 phenotype on soft and medium stiffness substrates. It is further observed that matrix stiffening increases Piezo1 expression, as well as leads to subsequent activation of the mechanotransduction signalling effector YAP, thus favouring M1 polarisation whilst suppressing M2 polarisation. Moreover, upon treatment with YAP inhibitor, we successfully induce macrophage re-polarisation to the M2 state within the implant site microenvironment, which in turn promotes implant osseointegration. Collectively, our present study thus characterises the critical role of the Piezo1-YAP signalling axis in macrophage mechanosensing and stiffness-mediated macrophage polarisation and provides cues for the design of immuno-modulatory biomaterials that can regulate the macrophage phenotype.

Insight to the Catalytic Activity of Atomically Precise Ag4Ni2 Nanoclusters on Silicon Carbide for Nitroarene Reduction.

Atomically precise Ag4Ni2 nanoclusters with 2,4-dimethylbenzenethiol as the ligands were synthesized and characterized as a cocatalyst of SiC for the selective hydrogenation of nitroarenes to arylamine in the presence of NaBH4. The obtained Ag4Ni2/SiC samples exhibited extraordinary catalytic activity, and a self-accelerated catalytic process was observed with the reduction of nitrophenol to aminophenol as the model reaction. Experimental comparison between the Ag4Ni2/SiC samples before and after the catalysis showed that the transformation of Ag4Ni2 clusters to polydisperse Ag particles as well as amorphous NiOx on the surface of SiC in the catalysis was the key to their high activity. AIMD calculations revealed that the transformation of Ag4Ni2 was driven by the presence of multiple hydrides on the cluster, which induced the detachment of the thiol ligand of the nanoclusters.

Protein disulfide isomerase 1 is required for RodA assembling-based conidial hydrophobicity of Aspergillus fumigatus.

The hydrophobic layer of Aspergillus conidia, composed of RodA, plays a crucial role in conidia transfer and immune evasion. It self-assembles into hydrophobic rodlets through intramolecular disulfide bonds. However, the secretory process of RodA and its regulatory elements remain unknown. Since protein disulfide isomerase (PDI) is essential for the secretion of many disulfide-bonded proteins, we investigated whether PDI is also involved in RodA secretion and assembly. By gene knockout and phenotypic analysis, we found that Pdi1, one of the four PDI-related proteins of Aspergillus fumigatus, determines the hydrophobicity and integrity of the rodlet layer of the conidia. Preservation of the thioredoxin-active domain of Pdi1 was sufficient to maintain conidial hydrophobicity, suggesting that Pdi1 mediates RodA assembly through its disulfide isomerase activity. In the absence of Pdi1, the disulfide mismatch of RodA in conidia may prevent its delivery from the inner to the outer layer of the cell wall for rodlet assembly. This was demonstrated using a strain expressing a key cysteine-mutated RodA. The dormant conidia of the Pdi1-deficient strain (Δpdi) elicited an immune response, suggesting that the defective conidia surface in the absence of Pdi1 exposes internal immunogenic sources. In conclusion, Pdi1 ensures the correct folding of RodA in the inner layer of conidia, facilitating its secretion into the outer layer of the cell wall and allowing self-assembly of the hydrophobic layer. This study has identified a regulatory element for conidia rodlet assembly.IMPORTANCEAspergillus fumigatus is the major cause of invasive aspergillosis, which is mainly transmitted by the inhalation of conidia. The spread of conidia is largely dependent on their hydrophobicity, which is primarily attributed to the self-assembly of the hydrophobic protein RodA on the cell wall. However, the mechanisms underlying RodA secretion and transport to the outermost layer of the cell wall are still unclear. Our study identified a critical role for Pdi1, a fungal protein disulfide isomerase found in regulating RodA secretion and assembly. Inhibition of Pdi1 prevents the formation of correct S-S bonds in the inner RodA, creating a barrier to RodA delivery and resulting in a defective hydrophobic layer. Our findings provided insight into the formation of the conidial hydrophobic layer and suggested potential drug targets to inhibit A. fumigatus infections by limiting conidial dispersal and altering their immune inertia.

The osteoclastic activity in apical distal region of molar mesial roots affects orthodontic tooth movement and root resorption in rats.

The utilization of optimal orthodontic force is crucial to prevent undesirable side effects and ensure efficient tooth movement during orthodontic treatment. However, the sensitivity of existing detection techniques is not sufficient, and the criteria for evaluating optimal force have not been yet established. Here, by employing 3D finite element analysis methodology, we found that the apical distal region (A-D region) of mesial roots is particularly sensitive to orthodontic force in rats. Tartrate-resistant acidic phosphatase (TRAP)-positive osteoclasts began accumulating in the A-D region under the force of 40 grams (g), leading to alveolar bone resorption and tooth movement. When the force reached 80 g, TRAP-positive osteoclasts started appearing on the root surface in the A-D region. Additionally, micro-computed tomography revealed a significant root resorption at 80 g. Notably, the A-D region was identified as a major contributor to whole root resorption. It was determined that 40 g is the minimum effective force for tooth movement with minimal side effects according to the analysis of tooth movement, inclination, and hyalinization. These findings suggest that the A-D region with its changes on the root surface is an important consideration and sensitive indicator when evaluating orthodontic forces for a rat model. Collectively, our investigations into this region would aid in offering valuable implications for preventing and minimizing root resorption during patients' orthodontic treatment.

DBNet-SI: Dual branch network of shift window attention and inception structure for skin lesion segmentation.

The U-shaped convolutional neural network (CNN) has attained remarkable achievements in the segmentation of skin lesion. However, given the inherent locality of convolution, this architecture cannot capture long-range pixel dependencies and multiscale global contextual information effectively. Moreover, repeated convolutions and downsampling operations can readily result in the omission of intricate local fine-grained details. In this paper, we proposed a U-shaped network (DBNet-SI) equipped with a dual-branch module that combines shift window attention and inception structures. First, we proposed a dual-branch module that combines shift window attention and inception structures (MSI) to better capture multiscale global contextual information and long-range pixel dependencies. Specifically, we have devised a cross-branch bidirectional interaction module within the MSI module to enable information complementarity between the two branches in the channel and spatial dimensions. Therefore, MSI is capable of extracting distinguishing and comprehensive features to accurately identify the skin lesion boundaries. Second, we have devised a progressive feature enhancement and information compensation module (PFEIC), which progressively compensates for fine-grained features through reconstructed skip connections and integrated global context attention modules. The results of the experiment show the superior segmentation performance of DBNet-SI compared with other deep learning models for skin lesion segmentation in the ISIC2017 and ISIC2018 datasets. Ablation studies demonstrate that our model can effectively extract rich multiscale global contextual information and compensate for the loss of local details.

Immune-Enhancing Treatment among Acute Necrotizing Pancreatitis Patients with Metabolic Abnormalities: A Post Hoc Analysis of a Randomized Clinical Trial.

Background/Aims: : Metabolic syndrome is common in patients with acute pancreatitis and its components have been reported to be associated with infectious complications. In this post hoc analysis, we aimed to evaluate whether metabolic abnormalities impact the effect of immune-enhancing thymosin alpha-1 (Tα1) therapy in acute necrotizing pancreatitis (ANP) patients. Methods: : All data were obtained from the database for a multicenter randomized clinical trial that evaluated the efficacy of Tα1 in ANP patients. Patients who discontinued the Tα1 treatment prematurely were excluded. The primary outcome was 90-day infected pancreatic necrosis (IPN) after randomization. Three post hoc subgroups were defined based on the presence of hyperglycemia, hypertriglyceridemia, or both at the time of randomization. In each subgroup, the correlation between Tα1 and 90-day IPN was assessed using the Cox proportional-hazards regression model. Multivariable propensity-score methods were used to control potential bias. Results: : Overall, 502 participants were included in this post hoc analysis (248 received Tα1 treatment and 254 received matching placebo treatment). Among them, 271 (54.0%) had hyperglycemia, 371 (73.9%) had hypertriglyceridemia and 229 (45.6%) had both. Tα1 therapy was associated with reduced incidence of IPN among patients with hyperglycemia (18.8% vs 29.7%: hazard ratio, 0.80; 95% confidence interval, 0.37 to 0.97; p=0.03), but not in the other subgroups. Additional multivariate regression models using three propensity-score methods yielded similar results. Conclusions: : Among ANP patients with hyperglycemia, immune-enhancing Tα1 treatment was associated with a reduced risk of IPN (ClinicalTrials.gov, Registry number: NCT02473406).

Antibacterial p-terphenyl and α­pyrone derivates isolated from the marine-derived actinomycete Nocardiopsis sp. HDN154086.

Assisted by OSMAC strategy, one new p-terphenyl and two new α­pyrone derivates, namely nocarterphenyl I (1) and nocardiopyrone D-E (2-3), were obtained and characterized from the marine sediment-derived actinomycete Nocardiopsis sp. HDN154086. The structures of these compounds were determined on the basis of MS, NMR spectroscopic data and single-crystal X-ray diffraction. Compound 1 with a rare 2,2'-bithiazole structure among natural products showed promising activity against five bacteria with MIC values ranging from 0.8 to 1.6 µM and 3 exhibited notable antibacterial activity against MRSA compared the positive control ciprofloxacin.

Structural connectivity from DTI to predict mild cognitive impairment in de novo Parkinson's disease.

BACKGROUND: Early detection of Parkinson's disease (PD) patients at high risk for mild cognitive impairment (MCI) can help with timely intervention. White matter structural connectivity is considered an early and sensitive indicator of neurodegenerative disease. OBJECTIVES: To investigate whether baseline white matter structural connectivity features from diffusion tensor imaging (DTI) of de novo PD patients can help predict PD-MCI conversion at an individual level using machine learning methods. METHODS: We included 90 de novo PD patients who underwent DTI and 3D T1-weighted imaging. Elastic net-based feature consensus ranking (ENFCR) was used with 1000 random training sets to select clinical and structural connectivity features. Linear discrimination analysis (LDA), support vector machine (SVM), K-nearest neighbor (KNN) and naïve Bayes (NB) classifiers were trained based on features selected more than 500 times. The area under the ROC curve (AUC), accuracy (ACC), sensitivity (SEN) and specificity (SPE) were used to evaluate model performance. RESULTS: A total of 57 PD patients were classified as PD-MCI nonconverters, and 33 PD patients were classified as PD-MCI converters. The models trained with clinical data showed moderate performance (AUC range: 0.62-0.68; ACC range: 0.63-0.77; SEN range: 0.45-0.66; SPE range: 0.64-0.84). Models trained with structural connectivity (AUC range, 0.81-0.84; ACC range, 0.75-0.86; SEN range, 0.77-0.91; SPE range, 0.71-0.88) performed similar to models that were trained with both clinical and structural connectivity data (AUC range, 0.81-0.85; ACC range, 0.74-0.85; SEN range, 0.79-0.91; SPE range, 0.70-0.89). CONCLUSIONS: Baseline white matter structural connectivity from DTI is helpful in predicting future MCI conversion in de novo PD patients.

A Dual-Attention Learning Network With Word and Sentence Embedding for Medical Visual Question Answering.

Research in medical visual question answering (MVQA) can contribute to the development of computer-aided diagnosis. MVQA is a task that aims to predict accurate and convincing answers based on given medical images and associated natural language questions. This task requires extracting medical knowledge-rich feature content and making fine-grained understandings of them. Therefore, constructing an effective feature extraction and understanding scheme are keys to modeling. Existing MVQA question extraction schemes mainly focus on word information, ignoring medical information in the text, such as medical concepts and domain-specific terms. Meanwhile, some visual and textual feature understanding schemes cannot effectively capture the correlation between regions and keywords for reasonable visual reasoning. In this study, a dual-attention learning network with word and sentence embedding (DALNet-WSE) is proposed. We design a module, transformer with sentence embedding (TSE), to extract a double embedding representation of questions containing keywords and medical information. A dual-attention learning (DAL) module consisting of self-attention and guided attention is proposed to model intensive intramodal and intermodal interactions. With multiple DAL modules (DALs), learning visual and textual co-attention can increase the granularity of understanding and improve visual reasoning. Experimental results on the ImageCLEF 2019 VQA-MED (VQA-MED 2019) and VQA-RAD datasets demonstrate that our proposed method outperforms previous state-of-the-art methods. According to the ablation studies and Grad-CAM maps, DALNet-WSE can extract rich textual information and has strong visual reasoning ability.

Road traffic mortality in Zunyi city, China: A 10 - year data analysis (2013-2022).

PURPOSE: The study aimed to examine the pattern of motorization and the mortality rate related to road traffic crashes in Zunyi (a city in northern Guizhou province of China) from 2013 to 2022, and to identify the epidemiological characteristics of these crashes with to provide insights that could help improve road safety. METHODS: Data were obtained from the Zunyi traffic management data platform, and the mortality rates were calculated. We deployed various analytical methods, including descriptive analysis, Chi-square test or Fisher's exact test of categorical variable, circular distribution map analysis, and Rayleigh test to characterize the traits of road traffic crashes in the region. RESULTS: During the 10-year study period, 7488 people died due to road traffic accidents, with males accounting for 70.4% and females 29.6% (χ2 = 101.97, p < 0.001). The mortality rate increased from 7.80 deaths per 100,000 people in 2013 to 10.70 deaths per 100,000 people in 2016, but then decreased to 9.54 deaths per 100,000 people in 2019. A notable finding was that the death rate per 10,000 vehicles declined from 16.09 deaths per 10,000 vehicles in 2013 to 5.48 deaths per 10,000 vehicles in 2022. The study also found that vulnerable road users represented nearly half (48.76%) of all accident fatalities, and unlicensed or inexperienced driving contributed significantly to the occurrence of road traffic accidents. CONCLUSION: Although the number of road traffic accidents in Zunyi has decreased, there are still some critical issues that need to be addressed, particularly for vulnerable road users and unlicensed drivers. Our results highlight the need of targeted interventions to address the specific risk factors of road traffic crashes, particularly those affecting vulnerable road users and drivers without sufficient experience or license.

Gene delivery to breast cancer by incorporated EpCAM targeted DARPins into AAV2.

OBJECTIVE: The aim of this study is to evaluate an AAV vector that can selectively target breast cancer cells and to investigate its specificity and anti-tumor effects on breast cancer cells both in vitro and in vivo, offering a new therapeutic approach for the treatment of EpCAM-positive breast cancer. METHODS: In this study, a modified AAV2 viral vector was used, in which EpCAM-specific DARPin EC1 was fused to the VP2 protein of AAV2, creating a viral vector that can target breast cancer cells. The targeting ability and anti-tumor effects of this viral vector were evaluated through in vitro and in vivo experiments. RESULTS: The experimental results showed that the AAV2MEC1 virus could specifically infect EpCAM-positive breast cancer cells and accurately deliver the suicide gene HSV-TK to tumor tissue in mice, significantly inhibiting tumor growth. Compared to the traditional AAV2 viral vector, the AAV2MEC1 virus exhibited reduced accumulation in liver tissue and had no impact on tumor growth. CONCLUSION: This study demonstrates that AAV2MEC1 is a gene delivery vector capable of targeting breast cancer cells and achieving selective targeting in mice. The findings offer a potential gene delivery system and strategies for gene therapy targeting EpCAM-positive breast cancer and other tumor types.

Pycnoporus sanguineus Polysaccharides as Reducing Agents: Self-Assembled Composite Nanoparticles for Integrative Diabetic Wound Therapy.

Purpose: Diabetic foot ulcers (DFU) are severe complications of diabetes, posing significant health and societal challenges. Elevated levels of reactive oxygen species (ROS) at the ulcer site hinder wound healing in most patients, while individuals with diabetes are also more susceptible to bacterial infections. This study aims to synthesize a comprehensive therapeutic material using polysaccharides from Pycnoporus sanguineus to promote DFU wound healing, reduce ROS levels, and minimize bacterial infections. Methods: Polysaccharides from P.sanguineus were employed as reducing and stabilizing agents to fabricate polysaccharide-based composite particles (PCPs) utilizing silver ions as templates. PCPs were characterized via UV-Vis, TEM, FTIR, XRD, and DLS. The antioxidant, antimicrobial, and cytotoxic properties of PCPs were assessed through in vitro and cellular experiments. The effects and mechanisms of PCPs on wound healing were evaluated using a diabetic ulcer mouse model. Results: PCPs exhibited spherical particles with an average size of 57.29±22.41 nm and effectively combined polysaccharides' antioxidant capacity with silver nanoparticles' antimicrobial function, showcasing synergistic therapeutic effects. In vitro and cellular experiments demonstrated that PCPs reduced cellular ROS levels by 54% at a concentration of 31.25 µg/mL and displayed potent antibacterial activity at 8 µg/mL. In vivo experiments revealed that PCPs enhanced the activities of superoxide dismutase (SOD) and catalase (CAT), promoting wound healing in DFUs and lowering the risk of bacterial infections. Conclusion: The synthesized PCPs offer a novel strategy for the comprehensive treatment of DFU. By integrating antioxidant and antimicrobial functions, PCPs effectively promote wound healing and alleviate patient suffering. The present study demonstrates a new strategy for the integrated treatment of diabetic wounds and expands the way for developing and applying the polysaccharide properties of P. sanguineus.

Catalytic Hydrogenation of Nitroarenes over Ag33 Nanoclusters: The Ligand Effect.

Using ligand-protected metallic nanoclusters with atomic precision as catalysts and elucidating its ligand effect in the catalysis are the prerequisites to deepen the structure-catalysis relationship of nanoclusters at the molecular level. Herein, a series of Ag33 nanoclusters protected with different thiolate ligands (2-phenylethanethiol, 4-chlorobenzyl mercaptan, and 4-methoxybenzyl mercaptan as precursors) were synthesized and used as heterogeneous catalysts for the conversion of nitroarenes to arylamine with NaBH4 as reductant. The obtained nanoclusters exhibited ligand-dependent catalytic activity, with benzyl thiolate ligands distinctly superior to the phenethyl thiolate ligands. DFT calculations revealed that the ligand regulated catalytic activity of the nanoclusters was ascribed to the H-π and π-π interactions between the ligands and the substrates, owing to the presence of phenyl rings in these structures. This work highlighted the importance of the ligands on the metallic nanoclusters in catalysis and provides a strategy to regulate the catalytic activity by utilizing weak interactions between the catalysts and the substrates.

A nanowire-assembled Co3S4/Cu2S@carbon binary metal sulfide hybrid as a sodium-ion battery anode displaying high capacity and recoverable rate-performance.

A binary metal sulfide hybrid consisting of nanowire-assembled and polypyrrole-coated Co3S4/Cu2S spheres after nitrogen-doped carbon coating (Co3S4/Cu2S@NC) is developed as an anode, which displays a capacity exceeding 412.3 mA h g-1 after 550 cycles under 1.0 A g-1. Recoverable rate-performance and good temperature tolerance under 50 °C and -10 °C are achievable; a full cell delivers 339.5 mA h g-1, indicating promising potential for applications in various conditions.

The Roles of Periodontal Bacteria in Atherosclerosis.

Atherosclerosis (AS) is an inflammatory vascular disease that constitutes a major underlying cause of cardiovascular diseases (CVD) and stroke. Infection is a contributing risk factor for AS. Epidemiological evidence has implicated individuals afflicted by periodontitis displaying an increased susceptibility to AS and CVD. This review concisely outlines several prevalent periodontal pathogens identified within atherosclerotic plaques, including Porphyromonas gingivalis, Aggregatibacter actinomycetemcomitans, and Fusobacterium nucleatum. We review the existing epidemiological evidence elucidating the association between these pathogens and AS-related diseases, and the diverse mechanisms for which these pathogens may engage in AS, such as endothelial barrier disruption, immune system activation, facilitation of monocyte adhesion and aggregation, and promotion of foam cell formation, all of which contribute to the progression and destabilization of atherosclerotic plaques. Notably, the intricate interplay among bacteria underscores the complex impact of periodontitis on AS. In conclusion, advancing our understanding of the relationship between periodontal pathogens and AS will undoubtedly offer invaluable insights and potential therapeutic avenues for the prevention and management of AS.

Analysis of emerging trends and hot spots in respiratory biomechanics from 2003 to 2022 based on CiteSpace.

Introduction: With the global prevalence of coronavirus disease 2019 (COVID-19), an increasing number of people are experiencing respiratory discomfort. Respiratory biomechanics can monitor breathing patterns and respiratory movements and it is easier to prevent, diagnose, treat or rehabilitate. However, there is still a lack of global knowledge structure in the field of respiratory biomechanics. With the help of CiteSpace software, we aim to help researchers identify potential collaborators and collaborating institutions, hotspots and research frontiers in respiratory biomechanics. Methods: Articles on respiratory biomechanics from 2003 to 2022 were retrieved from the Web of Science Core Collection by using a specific strategy, resulting a total of 2,850 publications. We used CiteSpace 6.1.R6 to analyze the year of publication, journal/journals cited, country, institution, author/authors cited, references, keywords and research trends. Co-citation maps were created to visually observe research hot spots and knowledge structures. Results and discussion: The number of annual publications gradually increased over the past 20 years. Medical Physics published the most articles and had the most citations in this study. The United States was the most influential country, with the highest number and centrality of publications. The most productive and influential institution was Harvard University in the United States. Keall PJ was the most productive author and MCCLELLAND JR was the most cited authors The article by Keall PJ (2006) article (cocitation counts: 55) and the article by McClelland JR (2013) were the most representative and symbolic references, with the highest cocitation number and centrality, respectively. The top keywords were "radiotherapy", "volume", and "ventilation". The top Frontier keywords were "organ motion," "deep inspiration," and "deep learning". The keywords were clustered to form seven labels. Currently, the main area of research in respiratory biomechanics is respiratory motion related to imaging techniques. Future research may focus on respiratory assistance techniques and respiratory detection techniques. At the same time, in the future, we will pay attention to personalized medicine and precision medicine, so that people can monitor their health status anytime and anywhere.

Cytosol Peroxiredoxin and Cell Surface Catalase Differentially Respond to H2O2 Stress in Aspergillus nidulans.

Both catalase and peroxiredoxin show high activities of H2O2 decomposition and coexist in the same organism; however, their division of labor in defense against H2O2 is unclear. We focused on the major peroxiredoxin (PrxA) and catalase (CatB) in Aspergillus nidulans at different growth stages to discriminate their antioxidant roles. The dormant conidia lacking PrxA showed sensitivity to high concentrations of H2O2 (>100 mM), revealing that PrxA is one of the important antioxidants in dormant conidia. Once the conidia began to swell and germinate, or further develop to young hyphae (9 h to old age), PrxA-deficient cells (ΔprxA) did not survive on plates containing H2O2 concentrations higher than 1 mM, indicating that PrxA is an indispensable antioxidant in the early growth stage. During these early growth stages, absence of CatB did not affect fungal resistance to either high (>1 mM) or low (<1 mM) concentrations of H2O2. In the mature hyphae stage (24 h to old age), however, CatB fulfills the major antioxidant function, especially against high doses of H2O2. PrxA is constitutively expressed throughout the lifespan, whereas CatB levels are low in the early growth stage of the cells developing from swelling conidia to early growth hyphae, providing a molecular basis for their different contributions to H2O2 resistance in different growth stages. Further enzyme activity and cellular localization analysis indicated that CatB needs to be secreted to be functionalized, and this process is confined to the growth stage of mature hyphae. Our results revealed differences in effectiveness and timelines of two primary anti-H2O2 enzymes in fungus.

All-Climate Long-Life and Fast-Charging Sodium-Ion Battery using Co3 S4 @NiS2 Heterostructures Encapsulated in Carbon Matrix as Anode.

Sodium-ion (Na-ion) battery is one of the research focuses because of high theoretical capacity and low cost. However, seeking for ideal anodes remains a big challenge. Here, a Co3 S4 @NiS2 /C synthesized by in situ growing NiS2 on CoS spheres then converting to Co3 S4 @NiS2 heterostructures encapsulated by carbon matrix, is developed as a promising anode. Co3 S4 @NiS2 /C as anode displays a high capacity of 654.1 mAh g-1 after 100 cycles. Even over 2000 cycles at a high rate of 10 A g-1 , capacity exceeds 143.2 mAh g-1 . Heterostructures between Co3 S4 and NiS2 improve electron transfer as verified by density functional theory (DFT) calculations. In addition, when cycling at a high temperature of 50 °C, the Co3 S4 @NiS2 /C anode displays 525.2 mAh g-1 , while it remains 340 mAh g-1 at -15 °C, indicating all-climate potential for using under different temperatures.