Early megakaryocyte lineage-committed progenitors in adult mouse bone marrow.

Hematopoietic stem cells (HSCs) have been considered to progressively lose their self-renewal and differentiation potentials prior to the commitment to each blood lineage. However, recent studies have suggested that megakaryocyte progenitors (MkPs) are generated at the level of HSCs. In this study, we newly identified early megakaryocyte lineage-committed progenitors (MgPs) mainly in CD201-CD48- cells and CD48+ cells separated from the CD150+CD34-Kit+Sca-1+Lin- HSC population of the bone marrow in adult mice. Single-cell colony assay and single-cell transplantation showed that MgPs, unlike platelet-biased HSCs, had little repopulating potential in vivo, but formed larger megakaryocyte colonies in vitro (on average 8 megakaryocytes per colony) than did previously reported MkPs. Single-cell RNA sequencing supported that HSCs give rise to MkPs through MgPs along a Mk differentiation pathway. Single-cell reverse transcription polymerase chain reaction (RT-PCR) analysis showed that MgPs expressed Mk-related genes, but were transcriptionally heterogenous. Clonal culture of HSCs suggested that MgPs are not direct progeny of HSCs. We propose a differentiation model in which HSCs give rise to MgPs which then give rise to MkPs, supporting a classic model in which Mk-lineage commitment takes place at a late stage of differentiation.

Cu(II)-Loaded Polydopamine-Coated Urchin-like Titanate Microspheres as a High-Performance IMAC Adsorbent for Hemoglobin Separation.

Immobilized metal ion affinity chromatography (IMAC) adsorbents generally have excellent affinity for histidine-rich proteins. However, the leaching of metal ions from the adsorbent usually affects its adsorption performance, which greatly affects the reusable performance of the adsorbent, resulting in many limitations in practical applications. Herein, a novel IMAC adsorbent, i.e., Cu(II)-loaded polydopamine-coated urchin-like titanate microspheres (Cu-PDA-UTMS), was prepared via metal coordination to make Cu ions uniformly decorate polydopamine-coated titanate microspheres. The as-synthesized microspheres exhibit an urchin-like structure, providing more binding sites for hemoglobin. Cu-PDA-UTMS exhibit favorable selectivity for hemoglobin adsorption and have a desirable adsorption capacity towards hemoglobin up to 2704.6 mg g-1. Using 0.1% CTAB as eluent, the adsorbed hemoglobin was easily eluted with a recovery rate of 86.8%. In addition, Cu-PDA-UTMS shows good reusability up to six cycles. In the end, the adsorption properties by Cu-PDA-UTMS towards hemoglobin from human blood samples were analyzed by SDS-PAGE. The results showed that Cu-PDA-UTMS are a high-performance IMAC adsorbent for hemoglobin separation, which provides a new method for the effective separation and purification of hemoglobin from complex biological samples.

Evolution of olfactory receptor superfamily in bats based on high throughput molecular modelling.

The origin of flight and laryngeal echolocation in bats is likely to have been accompanied by evolutionary changes in other aspects of their sensory biology. Of all sensory modalities in bats, olfaction is perhaps the least well understood. Olfactory receptors (ORs) function in recognizing odour molecules, with crucial roles in evaluating food, as well as in processing social information. Here we compare OR repertoire sizes across taxa and apply a new pipeline that integrates comparative genome data with protein structure modelling and then we employ molecular docking techniques with small molecules to analyse OR functionality based on binding energies. Our results suggest a sharp contraction in odorant recognition of the functional OR repertoire during the origin of bats, consistent with a reduced dependence on olfaction. We also compared bat lineages with contrasting different ecological characteristics and found evidence of differences in OR gene expansion and contraction, and in the composition of ORs with different tuning breadths. The strongest binding energies of ORs in non-echolocating fruit-eating bats were seen to correspond to ester odorants, although we did not detect a quantitative advantage of functional OR repertoires in these bats compared with echolocating insectivorous species. Overall, our findings based on molecular modelling and computational docking suggest that bats have undergone olfactory evolution linked to dietary adaptation. Our results from extant and ancestral bats help to lay the groundwork for targeted experimental functional tests in the future.

Case report: Bronchoscopic intervention for rare benign airway tumors: a report of 4 cases and literature review.

Due to their unique location, airway tumors have a significant impact on patient quality of life and survival. Current research has focused extensively on malignant airway tumors; however, benign airway tumors, especially rare ones, are less understood due to their low incidence. These tumors are often misdiagnosed and mistreated due to diagnostic challenges. Therefore, there is still a lack of consensus on the treatment of some rare benign airway tumors. Our center summarizes the diagnosis and treatment of four rare cases of benign airway stenosis in recent years, highlighting the bronchoscopic manifestations and therapeutic approaches to improve the understanding of these diseases.

Elevated Kallistatin promotes the occurrence and progression of non-alcoholic fatty liver disease.

Non-alcoholic fatty liver disease (NAFLD) is the most common chronic liver disease worldwide, and the development of non-alcoholic steatohepatitis (NASH) might cause irreversible hepatic damage. Hyperlipidemia (HLP) is the leading risk factor for NAFLD. This study aims to illuminate the causative contributor and potential mechanism of Kallistatin (KAL) mediating HLP to NAFLD. 221 healthy control and 253 HLP subjects, 62 healthy control and 44 NAFLD subjects were enrolled. The plasma KAL was significantly elevated in HLP subjects, especially in hypertriglyceridemia (HTG) subjects, and positively correlated with liver injury. Further, KAL levels of NAFLD patients were significantly up-regulated. KAL transgenic mice induced hepatic steatosis, inflammation, and fibrosis with time and accelerated inflammation development in high-fat diet (HFD) mice. In contrast, KAL knockout ameliorated steatosis and inflammation in high-fructose diet (HFruD) and methionine and choline-deficient (MCD) diet-induced NAFLD rats. Mechanistically, KAL induced hepatic steatosis and NASH by down-regulating adipose triglyceride lipase (ATGL) and comparative gene identification 58 (CGI-58) by LRP6/Gɑs/PKA/GSK3ß pathway through down-regulating peroxisome proliferator-activated receptor γ (PPARγ) and up-regulating kruppel-like factor four (KLF4), respectively. CGI-58 is bound to NF-κB p65 in the cytoplasm, and diminishing CGI-58 facilitated p65 nuclear translocation and TNFα induction. Meanwhile, hepatic CGI-58-overexpress reverses NASH in KAL transgenic mice. Further, free fatty acids up-regulated KAL against thyroid hormone in hepatocytes. Moreover, Fenofibrate, one triglyceride-lowering drug, could reverse hepatic steatosis by down-regulating KAL. These results demonstrate that elevated KAL plays a crucial role in the development of HLP to NAFLD and may be served as a potential preventive and therapeutic target.

Family intimacy and adaptability and non-suicidal self-injury: a mediation analysis.

BACKGROUND: Current research has been focusing on non-suicidal self-injury (NSSI) behaviors among adolescents with depression. Although family intimacy and adaptability are considered protective factors for NSSI, evidence supporting this relationship is lacking. OBJECTIVE: This study aims to examine the mechanisms operating in the relationship between family intimacy and adaptability and NSSI behaviors among adolescents. METHODS: A self-administered general demographic information questionnaire, the Behavioral Functional Assessment Scale for Non-Suicidal Self-Injury, the Family Intimacy and Adaptability Scale, the Connor-Davidson Resilience Scale, and the Self-Assessment of Depression Scale were distributed among adolescents with depression in three tertiary hospitals in Jiangsu Province. RESULTS: The relationship between family intimacy and adaptability and NSSI was assessed among 596 adolescents with depression. The results revealed the following: (1) Family intimacy and adaptability were negatively correlated with NSSI behavior. (2) Psychological resilience and depression levels acted as chain mediators in the relationship between family intimacy and adaptability and NSSI behavior. CONCLUSIONS: Enhancing psychological resilience, controlling depressive symptoms, and reducing depression severity among adolescents by improving their family intimacy and adaptability are conducive to preventing and mitigating their NSSI behaviors.

The relationship between ostracism and negative risk-taking behavior: the role of ego depletion and physical exercise.

Background: As a major public health problem globally, negative risk-taking behavior of college students may be related to their ostracism experience, but the reason for this association is unclear. Based on the limited resource theory, combined with the integrative model of athletic performance, we tested a moderated mediation model in which ego depletion mediated the association between ostracism and risk-taking, and physical exercise moderated the mediation process to examine the mechanisms underlying the association between ostracism and negative risk-taking behavior. Methods: One thousand three hundred seven students (43% female) from four universities in China were recruited using cluster random sampling. The experience of being ostracized, ego depletion, physical exercise level, and negative risk-taking behavior were measured through an anonymous online questionnaire in "www.sojump.com." Results: After controlling for gender and grade in college, ostracism was positively related to negative risk-taking behavior; ego depletion mediated this relationship; and physical exercise level attenuated these direct and indirect relationships. Conclusion: The results highlight individual risk and protective factors associated with negative risk-taking behavior, and provide new perspectives on ways to prevent and reduce college students' negative risk-taking behavior.

Evolution and expression patterns of the neo-sex chromosomes of the crested ibis.

Bird sex chromosomes play a unique role in sex-determination, and affect the sexual morphology and behavior of bird species. Core waterbirds, a major clade of birds, share the common characteristics of being sexually monomorphic and having lower levels of inter-sexual conflict, yet their sex chromosome evolution remains poorly understood. Here, by we analyse of a chromosome-level assembly of a female crested ibis (Nipponia nippon), a typical core waterbird. We identify neo-sex chromosomes resulting from fusion of microchromosomes with ancient sex chromosomes. These fusion events likely occurred following the divergence of Threskiornithidae and Ardeidae. The neo-W chromosome of the crested ibis exhibits the characteristics of slow degradation, which is reflected in its retention of abundant gametologous genes. Neo-W chromosome genes display an apparent ovary-biased gene expression, which is largely driven by genes that are retained on the crested ibis W chromosome but lost in other bird species. These results provide new insights into the evolutionary history and expression patterns for the sex chromosomes of bird species.

The genome of the black-footed cat: Revealing a rich natural history and urgent conservation priorities for small felids.

Habitat degradation and loss of genetic diversity are common threats faced by almost all of today's wild cats. Big cats, such as tigers and lions, are of great concern and have received considerable conservation attention through policies and international actions. However, knowledge of and conservation actions for small wild cats are lagging considerably behind. The black-footed cat, Felis nigripes, one of the smallest felid species, is experiencing increasing threats with a rapid reduction in population size. However, there is a lack of genetic information to assist in developing effective conservation actions. A de novo assembly of a high-quality chromosome-level reference genome of the black-footed cat was made, and comparative genomics and population genomics analyses were carried out. These analyses revealed that the most significant genetic changes in the evolution of the black-footed cat are the rapid evolution of sensory and metabolic-related genes, reflecting genetic adaptations to its characteristic nocturnal hunting and a high metabolic rate. Genomes of the black-footed cat exhibit a high level of inbreeding, especially for signals of recent inbreeding events, which suggest that they may have experienced severe genetic isolation caused by habitat fragmentation. More importantly, inbreeding associated with two deleterious mutated genes may exacerbate the risk of amyloidosis, the dominant disease that causes mortality of about 70% of captive individuals. Our research provides comprehensive documentation of the evolutionary history of the black-footed cat and suggests that there is an urgent need to investigate genomic variations of small felids worldwide to support effective conservation actions.

Genomic evolution of island birds from the view of the Swinhoe's pheasant (Lophura swinhoii).

Island endemic birds account for the majority of extinct vertebrates in the past few centuries. To date, the evolutionary characteristics of island endemic bird's is poorly known. In this research, we de novo assembled a high-quality chromosome-level reference genome for the Swinhoe's pheasant, which is a typical endemic island bird. Results of collinearity tests suggest rapid ancient chromosome rearrangement that may have contributed to the initial species radiation within Phasianidae, and a role for the insertions of CR1 transposable elements in rearranging chromosomes in Phasianidae. During the evolution of the Swinhoe's pheasant, natural selection positively selected genes involved in fecundity and body size functions, at both the species and population levels, which reflect genetic variation associated with island adaptation. We further tested for variation in population genomic traits between the Swinhoe's pheasant and its phylogenetically closely related mainland relative the silver pheasant, and found higher levels of genetic drift and inbreeding in the Swinhoe's pheasant genome. Divergent demographic histories of insular and mainland bird species during the last glacial period may reflect the differing impact of insular and continental climates on the evolution of species. Our research interprets the natural history and population genetic characteristics of the insular endemic bird the Swinhoe's pheasant, at a genome-wide scale, provides a broader perspective on insular speciation, and adaptive evolution and contributes to the genetic conservation of island endemic birds.

A Transformer-Based Knowledge Distillation Network for Cortical Cataract Grading.

Cortical cataract, a common type of cataract, is particularly difficult to be diagnosed automatically due to the complex features of the lesions. Recently, many methods based on edge detection or deep learning were proposed for automatic cataract grading. However, these methods suffer a large performance drop in cortical cataract grading due to the more complex cortical opacities and uncertain data. In this paper, we propose a novel Transformer-based Knowledge Distillation Network, called TKD-Net, for cortical cataract grading. To tackle the complex opacity problem, we first devise a zone decomposition strategy to extract more refined features and introduce special sub-scores to consider critical factors of clinical cortical opacity assessment (location, area, density) for comprehensive quantification. Next, we develop a multi-modal mix-attention Transformer to efficiently fuse sub-scores and image modality for complex feature learning. However, obtaining the sub-score modality is a challenge in the clinic, which could cause the modality missing problem instead. To simultaneously alleviate the issues of modality missing and uncertain data, we further design a Transformer-based knowledge distillation method, which uses a teacher model with perfect data to guide a student model with modality-missing and uncertain data. We conduct extensive experiments on a dataset of commonly-used slit-lamp images annotated by the LOCS III grading system to demonstrate that our TKD-Net outperforms state-of-the-art methods, as well as the effectiveness of its key components. Codes are available at https://github.com/wjh892521292/Cataract_TKD-Net.

Disrupted topological organization of the default mode network in mild cognitive impairment with subsyndromal depression: A graph theoretical analysis.

AIMS: Subsyndromal depression (SSD) is common in mild cognitive impairment (MCI). However, the neural mechanisms underlying MCI with SSD (MCID) are unclear. The default mode network (DMN) is associated with cognitive processes and depressive symptoms. Therefore, we aimed to explore the topological organization of the DMN in patients with MCID. METHODS: Forty-two MCID patients, 34 MCI patients without SSD (MCIND), and 36 matched healthy controls (HCs) were enrolled. The resting-state functional connectivity of the DMN of the participants was analyzed using a graph theoretical approach. Correlation analyses of network topological metrics, depressive symptoms, and cognitive function were conducted. Moreover, support vector machine (SVM) models were constructed based on topological metrics to distinguish MCID from MCIND. Finally, we used 10 repeats of 5-fold cross-validation for performance verification. RESULTS: We found that the global efficiency and nodal efficiency of the left anterior medial prefrontal cortex (aMPFC) of the MCID group were significantly lower than the MCIND group. Moreover, small-worldness and global efficiency were negatively correlated with depressive symptoms in MCID, and the nodal efficiency of the left lateral temporal cortex and left aMPFC was positively correlated with cognitive function in MCID. In cross-validation, the SVM model had an accuracy of 0.83 [95% CI 0.79-0.87], a sensitivity of 0.88 [95% CI 0.86-0.90], a specificity of 0.75 [95% CI 0.72-0.78] and an area under the curve of 0.88 [95% CI 0.85-0.91]. CONCLUSIONS: The coexistence of MCI and SSD was associated with the greatest disrupted topological organization of the DMN. The network topological metrics could identify MCID and serve as biomarkers of different clinical phenotypic presentations of MCI.

Polygonal Approximation Learning for Convex Object Segmentation in Biomedical Images with Bounding Box Supervision.

As a common and critical medical image analysis task, deep learning based biomedical image segmentation is hindered by the dependence on costly fine-grained annotations. To alleviate this data dependence, in this paper, a novel approach, called Polygonal Approximation Learning (PAL), is proposed for convex object instance segmentation with only bounding-box supervision. The key idea behind PAL is that the detection model for convex objects already contains the necessary information for segmenting them since their convex hulls, which can be generated approximately by the intersection of bounding boxes, are equivalent to the masks representing the objects. To extract the essential information from the detection model, a repeated detection approach is employed on biomedical images where various rotation angles are applied and a dice loss with the projection of the rotated detection results is utilized as a supervised signal in training our segmentation model. In biomedical imaging tasks involving convex objects, such as nuclei instance segmentation, PAL outperforms the known models (e.g., BoxInst) that rely solely on box supervision. Furthermore, PAL achieves comparable performance with mask-supervised models including Mask R-CNN and Cascade Mask R-CNN. Interestingly, PAL also demonstrates remarkable performance on non-convex object instance segmentation tasks, for example, surgical instrument and organ instance segmentation. Our code is available at https://github.com/shenmishajing/PAL.

Prospective assessment of breast lesions AI classification model based on ultrasound dynamic videos and ACR BI-RADS characteristics.

Introduction: AI-assisted ultrasound diagnosis is considered a fast and accurate new method that can reduce the subjective and experience-dependent nature of handheld ultrasound. In order to meet clinical diagnostic needs better, we first proposed a breast lesions AI classification model based on ultrasound dynamic videos and ACR BI-RADS characteristics (hereafter, Auto BI-RADS). In this study, we prospectively verify its performance. Methods: In this study, the model development was based on retrospective data including 480 ultrasound dynamic videos equivalent to 18122 static images of pathologically proven breast lesions from 420 patients. A total of 292 breast lesions ultrasound dynamic videos from the internal and external hospital were prospectively tested by Auto BI-RADS. The performance of Auto BI-RADS was compared with both experienced and junior radiologists using the DeLong method, Kappa test, and McNemar test. Results: The Auto BI-RADS achieved an accuracy, sensitivity, and specificity of 0.87, 0.93, and 0.81, respectively. The consistency of the BI-RADS category between Auto BI-RADS and the experienced group (Kappa:0.82) was higher than that of the juniors (Kappa:0.60). The consistency rates between Auto BI-RADS and the experienced group were higher than those between Auto BI-RADS and the junior group for shape (93% vs. 80%; P = .01), orientation (90% vs. 84%; P = .02), margin (84% vs. 71%; P = .01), echo pattern (69% vs. 56%; P = .001) and posterior features (76% vs. 71%; P = .0046), While the difference of calcification was not significantly different. Discussion: In this study, we aimed to prospectively verify a novel AI tool based on ultrasound dynamic videos and ACR BI-RADS characteristics. The prospective assessment suggested that the AI tool not only meets the clinical needs better but also reaches the diagnostic efficiency of experienced radiologists.

Characterization and genomic analysis of a novel bacteriophage BUCT_49532 lysing Klebsiella pneumoniae.

Bacteriophages are a type of virus widely distributed in nature that demonstrates a remarkable aptitude for selectively recognizing and infecting bacteria. In particular, Klebsiella pneumoniae is acknowledged as a clinical pathogen responsible for nosocomial infections and frequently develops multidrug resistance. Considering the increasing prevalence of antibiotic-resistant bacteria, bacteriophages have emerged as a compelling alternative therapeutic approach. In this study, a novel phage named BUCT_49532 was isolated from sewage using K. pneumoniae K1119 as the host. Electron microscopy revealed that BUCT_49532 belongs to the Caudoviricetes class. Further analysis through whole genome sequencing demonstrated that BUCT_49532 is a Jedunavirus comprised of linear double-stranded DNA with a length of 49,532 bp. Comparative genomics analysis based on average nucleotide identity (ANI) values revealed that BUCT_49532 should be identified as a novel species. Characterized by a good safety profile, high environmental stability, and strong lytic performance, phage BUCT_49532 presents an interesting case for consideration. Although its host range is relatively narrow, its application potential can be expanded by utilizing phage cocktails, making it a promising candidate for biocontrol approaches.

Colorimetric immunoassay of carcinoembryonic antigen based on the glucose oxidase/MnO2 nanosheet cascade reaction with self-supplying oxygen.

The detection of carcinoembryonic antigen (CEA) has profound implications in cancer diagnostics and therapeutic monitoring. In this work, we developed a colorimetric immunoassay for the detection of CEA. This assay involves the utilization of zinc(II)-based coordination polymers (ZnCPs) as a host for integrating glucose oxidase (GOx) and anti-carcinoembryonic antigen antibody (anti-CEA), which results in the formation of a detection antibody (anti-CEA/GOx@ZnCPs). The adaptable inclusion properties of ZnCPs enable the preservation of the original catalytic behavior of GOx and antigen capture ability of anti-CEA. Consequently, the anti-CEA/GOx@ZnCPs can act as a detection antibody to facilitate the development of an immunoassay. The combination of anti-CEA/GOx@ZnCPs in the immunoassay triggers a cascade reaction involving GOx and MnO2 nanosheets, leading to the generation of an amplified colorimetric signal through self-supplying oxygen. This colorimetric immunoassay exhibits a linear response ranging from 2 to 180 ng mL-1 CEA and has a detection limit of 50 pg mL-1. The practicality of this colorimetric immunoassay in biological matrices was demonstrated by the successful determination of CEA in serum samples with good recovery and precision. We believe that this study will pave the way to rationally design multifunctional CP-based composites for a wide range of applications in bioanalysis.

The liver microenvironment orchestrates FGL1-mediated immune escape and progression of metastatic colorectal cancer.

Colorectal cancer (CRC) patients with liver metastases usually obtain less benefit from immunotherapy, and the underlying mechanisms remain understudied. Here, we identify that fibrinogen-like protein 1 (FGL1), secreted from cancer cells and hepatocytes, facilitates the progression of CRC in an intraportal injection model by reducing the infiltration of T cells. Mechanistically, tumor-associated macrophages (TAMs) activate NF-ĸB by secreting TNFα/IL-1ß in the liver microenvironment and transcriptionally upregulate OTU deubiquitinase 1 (OTUD1) expression, which enhances FGL1 stability via deubiquitination. Disrupting the TAM-OTUD1-FGL1 axis inhibits metastatic tumor progression and synergizes with immune checkpoint blockade (ICB) therapy. Clinically, high plasma FGL1 levels predict poor outcomes and reduced ICB therapy benefits. Benzethonium chloride, an FDA-approved antiseptics, curbs FGL1 secretion, thereby inhibiting liver metastatic tumor growth. Overall, this study uncovers the critical roles and posttranslational regulatory mechanism of FGL1 in promoting metastatic tumor progression, highlighting the TAM-OTUD1-FGL1 axis as a potential target for cancer immunotherapy.

How genomic insights into the evolutionary history of clouded leopards inform their conservation.

Clouded leopards (Neofelis spp.), a morphologically and ecologically distinct lineage of big cats, are severely threatened by habitat loss and fragmentation, targeted hunting, and other human activities. The long-held poor understanding of their genetics and evolution has undermined the effectiveness of conservation actions. Here, we report a comprehensive investigation of the whole genomes, population genetics, and adaptive evolution of Neofelis. Our results indicate the genus Neofelis arose during the Pleistocene, coinciding with glacial-induced climate changes to the distributions of savannas and rainforests, and signatures of natural selection associated with genes functioning in tooth, pigmentation, and tail development, associated with clouded leopards' unique adaptations. Our study highlights high-altitude adaptation as the main factor driving nontaxonomic population differentiation in Neofelis nebulosa. Population declines and inbreeding have led to reduced genetic diversity and the accumulation of deleterious variation that likely affect reproduction of clouded leopards, highlighting the urgent need for effective conservation efforts.

Kallistatin Deficiency Induces the Oxidative Stress-Related Epithelial-Mesenchymal Transition of Retinal Pigment Epithelial Cells: A Novel Protagonist in Age-Related Macular Degeneration.

Purpose: Retinal pigment epithelium (RPE) dysfunction induced by oxidative stress-related epithelial-mesenchymal transition (EMT) of RPE is the primary underlying mechanism of age-related macular degeneration (AMD). Kallistatin (KAL) is a secreted protein with an antioxidative stress effect. However, the relationship between KAL and EMT in RPE has not been determined. Therefore we aimed to explore the impact and mechanism of KAL in oxidative stress-induced EMT of RPE. Methods: Sodium iodate (SI) was injected intraperitoneally to construct the AMD rat model and investigate the changes in RPE morphology and KAL expression. KAL knockout rats and KAL transgenic mice were used to explain the effects of KAL on EMT and oxidative stress. In addition, Snail overexpressed adenovirus and si-RNA transfected ARPE19 cells to verify the involvement of Snail in mediating KAL-suppressed EMT of RPE. Results: AMD rats induced by SI expressed less KAL in the retina, and KAL knockout rats showed RPE dysfunction spontaneously where EMT and reactive oxygen species (ROS) production increased in RPE. In contrast, KAL overexpression attenuated EMT and ROS levels in RPE, even in TGF-ß treatment. Mechanistically, Snail reversed the beneficial effect of KAL on EMT and ROS reduction. Moreover, KAL ameliorated SI-induced AMD-like pathological changes. Conclusions: Our findings demonstrated that KAL inhibits oxidative stress-induced EMT by downregulating the transcription factor Snail. Herein, KAL knockout rats may be an appropriate animal model for observing spontaneous RPE dysfunction for AMD-like retinopathy, and KAL may represent a novel therapeutic target for treating dry AMD.

Attractive deep morphology-aware active contour network for vertebral body contour extraction with extensions to heterogeneous and semi-supervised scenarios.

Automatic vertebral body contour extraction (AVBCE) from heterogeneous spinal MRI is indispensable for the comprehensive diagnosis and treatment of spinal diseases. However, AVBCE is challenging due to data heterogeneity, image characteristics complexity, and vertebral body morphology variations, which may cause morphology errors in semantic segmentation. Deep active contour-based (deep ACM-based) methods provide a promising complement for tackling morphology errors by directly parameterizing the contour coordinates. Extending the target contours' capture range and providing morphology-aware parameter maps are crucial for deep ACM-based methods. For this purpose, we propose a novel Attractive Deep Morphology-aware actIve contouR nEtwork (ADMIRE) that embeds an elaborated contour attraction term (CAT) and a comprehensive contour quality (CCQ) loss into the deep ACM-based framework. The CAT adaptively extends the target contours' capture range by designing an all-to-all force field to enable the target contours' energy to contribute to farther locations. Furthermore, the CCQ loss is carefully designed to generate morphology-aware active contour parameters by simultaneously supervising the contour shape, tension, and smoothness. These designs, in cooperation with the deep ACM-based framework, enable robustness to data heterogeneity, image characteristics complexity, and target contour morphology variations. Furthermore, the deep ACM-based ADMIRE is able to cooperate well with semi-supervised strategies such as mean teacher, which enables its function in semi-supervised scenarios. ADMIRE is trained and evaluated on four challenging datasets, including three spinal datasets with more than 1000 heterogeneous images and more than 10000 vertebrae bodies, as well as a cardiac dataset with both normal and pathological cases. Results show ADMIRE achieves state-of-the-art performance on all datasets, which proves ADMIRE's accuracy, robustness, and generalization ability.