Multi Task Consistency Guided Source-Free Test-Time Domain Adaptation Medical Image Segmentation

Source-free test-time adaptation for medical image segmentation aims to enhance the adaptability of segmentation models to diverse and previously unseen test sets of the target domain, which contributes to the generalizability and robustness of medical image segmentation models without access to the source domain. Ensuring consistency between target edges and paired inputs is crucial for test-time adaptation. To improve the performance of test-time domain adaptation, we propose a multi task consistency guided source-free test-time domain adaptation medical image segmentation method which ensures the consistency of the local boundary predictions and the global prototype representation. Specifically, we introduce a local boundary consistency constraint method that explores the relationship between tissue region segmentation and tissue boundary localization tasks. Additionally, we propose a global feature consistency constraint toto enhance the intra-class compactness. We conduct extensive experiments on the segmentation of benchmark fundus images. Compared to prediction directly by the source domain model, the segmentation Dice score is improved by 6.27\% and 0.96\% in RIM-ONE-r3 and Drishti GS datasets, respectively. Additionally, the results of experiments demonstrate that our proposed method outperforms existing competitive domain adaptation segmentation algorithms.Comment: 31 pages,7 figure

Comprehending the cuproptosis and cancer-immunity cycle network: delving into the immune landscape and its predictive role in breast cancer immunotherapy responses and clinical endpoints

BackgroundThe role of cuproptosis, a phenomenon associated with tumor metabolism and immunological identification, remains underexplored, particularly in relation to the cancer-immunity cycle (CIC) network. This study aims to rigorously examine the impact of the cuproptosis-CIC nexus on immune reactions and prognostic outcomes in patients with breast cancer (BC), striving to establish a comprehensive prognostic model.MethodsIn the study, we segregated data obtained from TCGA, GEO, and ICGC using CICs retrieved from the TIP database. We constructed a genetic prognostic framework using the LASSO-Cox model, followed by its validation through Cox proportional hazards regression. This framework’s validity was further confirmed with data from ICGC and GEO. Explorations of the tumor microenvironment were carried out through the application of ESTIMATE and CIBERSORT algorithms, as well as machine learning techniques, to identify potential treatment strategies. Single-cell sequencing methods were utilized to delineate the spatial distribution of key genes within the various cell types in the tumor milieu. To explore the critical role of the identified CICs, experiments were conducted focusing on cell survival and migration abilities.ResultsIn our research, we identified a set of 4 crucial cuproptosis-CICs that have a profound impact on patient longevity and their response to immunotherapy. By leveraging these identified CICs, we constructed a predictive model that efficiently estimates patient prognoses. Detailed analyses at the single-cell level showed that the significance of CICs. Experimental approaches, including CCK-8, Transwell, and wound healing assays, revealed that the protein HSPA9 restricts the growth and movement of breast cancer cells. Furthermore, our studies using immunofluorescence techniques demonstrated that suppressing HSPA9 leads to a notable increase in ceramide levels.ConclusionThis research outlines a network of cuproptosis-CICs and constructs a predictive nomogram. Our model holds great promise for healthcare professionals to personalize treatment approaches for individuals with breast cancer. The work provides insights into the complex relationship between the cuproptosis-CIC network and the cancer immune microenvironment, setting the stage for novel approaches to cancer immunotherapy. By focusing on the essential gene HSPA9 within the cancer-immunity cycle, this strategy has the potential to significantly improve the efficacy of treatments against breast cancer

A novel endophytic fungus strain of Cladosporium: its identification, genomic analysis, and effects on plant growth

IntroductionEndophytic microorganisms are bacteria or fungi that inhabit plant internal tissues contributing to various biological processes of plants. Some endophytic microbes can promote plant growth, which are known as plant growth-promoting endophytes (PGPEs). There has been an increasing interest in isolation and identification of PGPEs for sustainable production of crops. This study was undertaken to isolate PGPEs from roots of a halophytic species Sesuvium portulacastrum L. and elucidate potential mechanisms underlying the plant growth promoting effect.MethodsSurface-disinfected seeds of S. portulacastrum were germinated on an in vitro culture medium, and roots of some germinated seedlings were contaminated by bacteria and fungi. From the contamination, an endophytic fungus called BF-F (a fungal strain isolated from bacterial and fungal contamination) was isolated and identified. The genome of BF-F strain was sequenced, its genome structure and function were analyzed using various bioinformatics software. Additionally, the effect of BF-F on plant growth promotion were investigated by gene cluster analyses.ResultsBased on the sequence homology (99%) and phylogenetic analysis, BF-F is likely a new Cladosporium angulosum strain or possibly a new Cladosporium species that is most homologous to C. angulosum. The BF-F significantly promoted the growth of dicot S. portulacastrum and Arabidopsis as well as monocot rice. Whole genome analysis revealed that the BF-F genome has 29,444,740 bp in size with 6,426 annotated genes, including gene clusters associated with the tryptophan synthesis and metabolism pathway, sterol synthesis pathway, and nitrogen metabolism pathway. BF-F produced indole-3-acetic acid (IAA) and also induced the expression of plant N uptake related genes.DiscussionOur results suggest that BF-F is a novel strain of Cladosporium and has potential to be a microbial fertilizer for sustainable production of crop plants. The resulting genomic information will facilitate further investigation of its genetic evolution and its function, particularly mechanisms underlying plant growth promotion

Association between admission temperature and mortality and major morbidity in preterm infants born at fewer than 33weeks\u27 gestation

Importance: Neonatal hypothermia has been associated with higher mortality and morbidity; therefore, thermal control following delivery is an essential part of neonatal care. Identifying the ideal body temperature in preterm neonates in the first few hours of lifemay be helpful to reduce the risk for adverse outcomes. Objectives: To examine the association between admission temperature and neonatal outcomes and estimate the admission temperature associated with lowest rates of adverse outcomes in preterm infants born at fewer than 33 weeks\u27 gestation.. Design, Setting, And Participants: Retrospective observational study at 29 neonatal intensive care units in the Canadian Neonatal Network. Participants included 9833 inborn infants born at fewer than 33 weeks\u27 gestation who were admitted between January 1, 2010, and December 31, 2012.. Exposure: Axillary or rectal body temperature recorded at admission.. Main Outcomes And Measures: The primary outcomewas a composite adverse outcome defined as mortality or any of the following: severe neurological injury, severe retinopathy of prematurity, necrotizing enterocolitis, bronchopulmonary dysplasia, or nosocomial infection. The relationships between admission temperature and the composite outcome as well as between admission temperature and the components of the composite outcome were evaluated using multivariable analyses.. Results: Admission temperatures of the 9833 neonates were distributed as follows: lower than 34.5°C (1%); 34.5°C to 34.9°C (1%); 35.0°C to 35.4°C (3%); 35.5°C to 35.9°C (7%); 36.0°C to 36.4°C (24%); 36.5°C to 36.9°C (38%); 37.0°C to 37.4°C (19%); 37.5°C to 37.9°C (5%); and 38.0°C or higher (2%). After adjustment for maternal and infant characteristics, the rates of the composite outcome, severe neurological injury, severe retinopathy of prematurity, necrotizing enterocolitis, bronchopulmonary dysplasia, and nosocomial infection had a U-shaped relationship with admission temperature (a \u3e 0 [P \u3c .05]). The admission temperature at which the rate of the composite outcome was lowest was 36.8°C (95%CI, 36.7°C-37.0°C). Rates of severe neurological injury, severe retinopathy of prematurity, necrotizing enterocolitis (95%CI, 36.3°C-36.7°C), bronchopulmonary dysplasia, and nosocomial infection (95%CI, 36.9°C-37.3°C) were lowest at admission temperatures ranging from 36.5°C to 37.2°C.. Conclusions And Relevance: The relationship between admission temperature and adverse neonatal outcomes was U-shaped. The lowest rates of adverse outcomes were associated with admission temperatures between 36.5°C and 37.2°C.

Construction of a cross-species cell landscape at single-cell level.

Individual cells are basic units of life. Despite extensive efforts to characterize the cellular heterogeneity of different organisms, cross-species comparisons of landscape dynamics have not been achieved. Here, we applied single-cell RNA sequencing (scRNA-seq) to map organism-level cell landscapes at multiple life stages for mice, zebrafish and Drosophila. By integrating the comprehensive dataset of > 2.6 million single cells, we constructed a cross-species cell landscape and identified signatures and common pathways that changed throughout the life span. We identified structural inflammation and mitochondrial dysfunction as the most common hallmarks of organism aging, and found that pharmacological activation of mitochondrial metabolism alleviated aging phenotypes in mice. The cross-species cell landscape with other published datasets were stored in an integrated online portal-Cell Landscape. Our work provides a valuable resource for studying lineage development, maturation and aging

The Influence of Seasonality on the Sustainability of Livelihoods of Households in Rural Tourism Destinations

Even though seasonality is an important concern in tourism research, only a few scholars have focused on the seasonality of rural tourism. Therefore, this study examines seasonality in rural tourism destinations. We adopt a mixed research approach to explore the sustainable livelihoods of households in rural tourism destinations from a seasonality perspective, using the case of rural tourism destinations in Yulong River basin, Guangxi, China. First, in-depth interviews and grounded theory are used to construct a sustainable livelihood model for households in rural tourism destinations under the influence of seasonality. Second, the model is tested using the data envelopment analysis model and statistical analysis. We find that (1) psychological capital, a previously neglected livelihood capital, is an important component of rural households’ livelihood capital in rural tourism destinations under the influence of seasonality; (2) rural tourism does not significantly improve rural livelihoods due to seasonal influences; and (3) participating in tourism work in the off-season and combining it with other work practices are the main livelihood strategies of rural households to cope with seasonality; however, over-dispersing resources reduces the livelihood efficiency. This study’s findings will prove useful for policy formation by governments to deal with seasonality in rural tourism

The Influence of Seasonality on the Sustainability of Livelihoods of Households in Rural Tourism Destinations

Even though seasonality is an important concern in tourism research, only a few scholars have focused on the seasonality of rural tourism. Therefore, this study examines seasonality in rural tourism destinations. We adopt a mixed research approach to explore the sustainable livelihoods of households in rural tourism destinations from a seasonality perspective, using the case of rural tourism destinations in Yulong River basin, Guangxi, China. First, in-depth interviews and grounded theory are used to construct a sustainable livelihood model for households in rural tourism destinations under the influence of seasonality. Second, the model is tested using the data envelopment analysis model and statistical analysis. We find that (1) psychological capital, a previously neglected livelihood capital, is an important component of rural households’ livelihood capital in rural tourism destinations under the influence of seasonality; (2) rural tourism does not significantly improve rural livelihoods due to seasonal influences; and (3) participating in tourism work in the off-season and combining it with other work practices are the main livelihood strategies of rural households to cope with seasonality; however, over-dispersing resources reduces the livelihood efficiency. This study’s findings will prove useful for policy formation by governments to deal with seasonality in rural tourism

Rigid-Body Guidance Synthesis of Noncircular Gear-Five-Bar Mechanisms and Its Application in a Knee Joint Rehabilitation Device

At present, the research objects of rigid-body guidance synthesis are mostly limited to pure linkages, and there is little research on the combined mechanisms of gears or cams and linkages. In order to expand the research objects of rigid-body guidance and improve the kinematic mapping theory, this paper proposes a rigid-body guidance method of noncircular gear-five-bar combined mechanisms. A noncircular gear-five-bar mechanism can be regarded as a combination of a 2R (two revolute joints) open chain, a 3R (three revolute joints) open chain and a pair of noncircular gears. Firstly, the circle point curves and circle center point curves of the 2R and 3R open chains are obtained by using kinematic mapping, and they are formed into a double crank five-bar linkage. Secondly, the B-spline curve is used to fit the rotation angle relationship of the gear pair to obtain the pitch curves of noncircular gears. Finally, aiming at correcting patients’ abnormal gait, a noncircular gear-five-bar exoskeleton knee joint rehabilitation device is designed based on four task poses. The prototype is developed and the wear test is carried out. The test results verify the correctness of the rigid-body guidance synthesis method and the effectiveness of rehabilitation training

Rigid-Body Guidance Synthesis of Noncircular Gear-Five-Bar Mechanisms and Its Application in a Knee Joint Rehabilitation Device

At present, the research objects of rigid-body guidance synthesis are mostly limited to pure linkages, and there is little research on the combined mechanisms of gears or cams and linkages. In order to expand the research objects of rigid-body guidance and improve the kinematic mapping theory, this paper proposes a rigid-body guidance method of noncircular gear-five-bar combined mechanisms. A noncircular gear-five-bar mechanism can be regarded as a combination of a 2R (two revolute joints) open chain, a 3R (three revolute joints) open chain and a pair of noncircular gears. Firstly, the circle point curves and circle center point curves of the 2R and 3R open chains are obtained by using kinematic mapping, and they are formed into a double crank five-bar linkage. Secondly, the B-spline curve is used to fit the rotation angle relationship of the gear pair to obtain the pitch curves of noncircular gears. Finally, aiming at correcting patients’ abnormal gait, a noncircular gear-five-bar exoskeleton knee joint rehabilitation device is designed based on four task poses. The prototype is developed and the wear test is carried out. The test results verify the correctness of the rigid-body guidance synthesis method and the effectiveness of rehabilitation training