Abstract: China has a large number of patients with hypertension, and high blood pressure causes cardiac target organs, including changes in the size of the left atrial size.To explore the relevant factors of the atrial size related factors. Early controlling related risk factors may improve the prognosis of patients with hypertension.

The objective of this study was to evaluate the impact of diagnosis-related group(DRG) payments on hospitalization costs, length of stay(LOS), and in-hospital mortality in Nanjing. A quasinatural experiment was utilized. The intervention group consisted of patients enrolled in the Urban Employee Basic Medical Insurance and Urban and Rural Resident Basic Medical Insurance programs in Nanjing, while the other patients composed the comparison group. Interrupted time-series analysis and difference-in-differences combined with propensity score matching were employed in this study. The analysis was based on a case-level dataset from a tertiary hospital between January 2021 and December 2022. The introduction of the DRG payment caused a 13.5% decrease in hospitalization costs per admission for the intervention group compared with the comparison group. Furthermore, the intervention group exhibited a slight reduction in the LOS of 0.75 days in comparison to the comparison group. No significant changes were observed in care quality, as measured by in-hospital mortality. In conclusion, the DRG payment was effective in decreasing hospitalization costs and length of stay. No compelling evidence was identified in terms of the changes in in-hospital mortality. The evidence from China may also be valuable to other developing countries considering the adoption of DRG payments.

Complex media supplemented with a carbon source are commonly used in bioprocesses for recombinant protein production in E. coli. Optimizing these processes is challenging and requires precise understanding of cellular metabolism and nutrient requirements. Compared to a Design of Experiments approach that necessitates extensive experimentation, metabolic modeling using a genome scale metabolic model (GEM) offers a more predictive and systematic approach to guide process optimization by identifying specific metabolic bottlenecks. In addition, spent media analysis (SMA) can unravel the preferential utilization of different media components during the bioprocess. Here, we integrated the updated E. coli GEM with time course SMA data from a fed-batch process and performed dynamic flux balance analysis (dFBA) to identify metabolites that function as active nodes and are vital for cellular function. These are potential target supplements to boost cellular activity and in turn the recombinant protein productivity. Using an iterative approach of performing fermentation, SMA, and metabolic modeling, we optimized the bioprocess in just five experimental trials, resulting in a six-fold increase in protein productivity. The optimized feeding strategy involved yeast extract with amino acid supplementation (Ser, Thr, Asp, Glu) and increased oxygen transfer rates. This approach demonstrates significant promise for application in bioprocess optimization.

Context: Effective coordination between different functional contributors is fundamental for the success of collaboration-focused software development paradigms such as DevSecOps. However, the quantification of coordination in such environments has received limited attention. Objectives: We introduce a Multi-Class Socio-Technical Congruence metric MC-STC by extending the application of the widely studied Socio-Technical Congruence STC framework to address the above gap. Our metric enables assessing coordination in a setting where contributors with different functional roles or alignments collaborate. Using a large-scale exploratory case study, we evaluate MC-STC for two classes (i.e., 2C-STC) Methods: We calculated 2C-STC for 100 systematically selected projects from the TravisTorrent dataset, considering developers (dev) and security-focused developers (sf-dev) as the two types of contributors with different functional alignments (i.e. two classes). We hypothesised that the dev and sf-dev interaction would have a quantifiable impact on the Vulnerability Score (VS) of each project. Results: Our results show a moderate negative association between 2C-STC and VS, with the Spearman correlation reaching -0.427 (p = 0.00000624), indicating that higher levels of coordination between dev and sf-dev led to projects with a lower incidence of high-severity vulnerabilities. In addition, 2C-STC shows a stronger negative relationship with VS than STC, suggesting that it is the more sensitive indicator of this relationship. Conclusion: The specific instantiation of our proposed metric, 2C-STC, performs comparatively better than STC for measuring cross-functional coordination in our selected projects. However, further research is needed to explore its broader applicability.

Interstitial lung disease (ILD) is an umbrella term representing a heterogeneous group of restrictive lung disorders with destructive abnormalities in the lung interstitium. The overlapping clinical onset of various ILD subtypes poses significant challenges in diagnosis and management of the disease. Various omics technologies have explored disease-specific molecular markers, crucial for understanding the complex pathophysiology underlying disease progression. Proteomics, a rapidly advancing high-throughput omics tool, captures dynamic protein changes within a biological system, depicting its actual functional state. This enables comprehensive proteome profiling, facilitating the identification of specific biomarkers and pathways, thereby enhancing diagnostic precision and paving the way for targeted therapeutic interventions. This review highlights recent proteomic discoveries in idiopathic pulmonary fibrosis, autoimmune ILDs, exposure-related ILDs, and sarcoidosis, including emerging therapeutic avenues. It summarizes dysregulated pathways and potential biomarkers crucial for differential diagnosis, prognosis, disease progression, and treatment responses. The pathogenesis of ILD involves complex interactions of complement activation, humoral immune responses, and extracellular matrix organization pathways, and the expression levels of these pathway mediators vary across ILD stages and subtypes. Further validation of these pathways and their mediators through multicentric, large-cohort studies across diverse geographical locations is needed to enhance disease understanding and develop ”true” clinical biomarkers.

Objective: Corticosteroid-resistant secondary immune thrombocytopenia (ITP) is a challenging condition in clinical practice. This study aimed to explore the clinical and immunological characteristics of corticosteroid-resistant secondary ITP associated with connective tissue diseases (CTD-ITP). Methods: We conducted a retrospective analysis of 201 CTD-ITP patients hospitalized between 2014 and 2022. Patients were categorized as corticosteroid-resistant or corticosteroid-sensitive, and their clinical, immunological, and demographic data were compared. Logistic regression analysis was employed to identify independent predictors of corticosteroid resistance. Results: Corticosteroid resistance was observed in 27.4% of patients. Compared with the sensitive group, the resistant group exhibited a higher percentage of CD3+T cell (71.38% versus 64.70%, p=0.004) and CD3+CD8+T cell (38.55% versus 28.95%, p=0.003), but a lower percentage of CD3−CD19+ B cell (13.70% versus 22.45%, p=0.001) in peripheral blood. No significant differences were found in demographics, clinical features, or autoantibody profiles. And the multivariable logistic regression analysis showed that percentage of CD3+CD8+T cells (OR=1.117, 95% CI: 1.014-1.350, p=0.031) was independent risk factors for corticosteroid resistance in CTD-ITP patients. Conclusion: This study highlights the role of CD3+CD8+T cells in corticosteroid resistance among CTD-ITP patients, suggesting that cellular immunity plays a key role in this resistance and providing potential biomarkers for personalized treatment strategies.

Current global changes are driving many species towards extinction, making the early detection of threatened species a priority for efficient conservation actions. However, the threat status of many species remains unknown because we lack primary data (e.g., population trends), and using ecological indicator traits such as range size is not always straightforward. Recently, the idea has emerged to link species’ current threat status to macroevolutionary indicators, e.g., rates of extinction, diversification or niche evolution. However, to fully utilise this approach, we need to understand the underlying assumptions and when they are valid; namely, in which cases macroevolutionary indicators can be used as proxies for extinction-promoting characteristics, such as small range size, narrow niche breadth or low evolutionary potential. Here, we assess current understanding of the assumptions underlying the relationship between macroevolutionary indices and contemporary extinction risk. We find that only past extinction rates can be reliable predictors of current extinction risk. Assumptions underlying relationships between current extinction risk and diversification and niche evolution rates were only supported in specific circumstances and should be tested on a case-by-case basis. When intermediate assumptions are validated, macroevolutionary indicators could be promising tools complementing trait-based approaches in identifying vulnerable species.

Invasive pests have spread globally at an unprecedented scale, severely threatening biodiversity and resulting in significant economic losses, emerging as a global problem. In the process of spreading, pests establish new habitats, which depend on the joint effects of natural and human factors. However, research on the mechanisms by which human factors influence the global spread of Hyphantria cunea, a quarantine pest of international concern, is still lacking. Thus, this study developed a species distribution model to explore the role of human factors in predicting the global habitat suitability for Hyphantria cunea. We also emphasize that human activities and natural environmental changes have a significant impact on the distribution of invasive species such as Hyphantria cunea. Moreover, this research identifies areas of high suitability across continents and forecasts changes in the distribution patterns of Hyphantria cunea in the future. It offers crucial insights for developing more effective global quarantine strategies and pest management policies.

Environmental DNA (eDNA) analysis has become a popular conservation tool for detecting rare and elusive species. eDNA assays typically target mitochondrial DNA (mtDNA) due to its high copy number per cell and its ability to persist in the environment longer than nuclear DNA. Consequently, the development of eDNA assays has relied on mitochondrial reference sequences available in online databases, or in cases where such data are unavailable, de novo DNA extraction and sequencing of mtDNA. In this study, we designed eDNA primers for the critically endangered Bellinger River turtle (Myuchelys georgesi) using a bioinformatically assembled mitochondrial genome (mitogenome) derived from a reference genome. We confirmed the accuracy of this assembled mitogenome by comparing it to a Sanger-sequenced mitogenome of the same species, and no base pair mismatches were detected. Using the bioinformatically extracted mitogenome, we designed two 20 bp primers that target a 152-base-pair-long fragment of the cytochrome oxidase 1 (CO1) gene and a 186-base-pair-long fragment of the cytochrome B (CytB) gene. Both primers were successfully validated in silico, in vitro, and in situ.

Background: Freezing of gait (FoG) is a common and debilitating symptom in individuals with advanced Parkinson’s disease (PD), significantly increasing the risk of falls. Wearable devices have facilitated the detection of FoG and falls, but early prediction remains underexplored. This study investigates the use of multimodal sensor fusion and deep learning for the early prediction of FoG events in PD patients. Research Question: Can a multimodal sensor fusion deep learning model accurately predict FoG events well before time in Parkinson’s disease patients, and how robust is the model to noise and inter-subject variability? Methods: The proposed study utilized Inertial Measurement Unit (IMU), Electromyography (EMG), and Electroencephalography (EEG) signals from PD patients to develop and evaluate deep learning models. The CNN+LSTM architecture was employed and compared with other classifiers. Stratified ten-fold cross-validation was used to assess model accuracy. The robustness of IMU+EMG and IMU+EMG+EEG configurations to noise was tested, and inter-subject performance evaluation was conducted. Pre-FOG detection capabilities were also analyzed to emphasize the importance of temporal dynamics in the multimodal approach. Results: The CNN+LSTM model achieved a high accuracy of 94.45% in predicting FoG events. The IMU+EMG and IMU+EMG+EEG configurations demonstrated robust performance across inter-subject evaluations. The models showed resilience to noise, with the CNN+LSTM and IMU+EMG+EEG configurations maintaining high accuracy. Pre-FOG detection achieved 94.20% accuracy, highlighting the model’s effectiveness in capturing temporal dynamics. Significance: The CNN+LSTM model, particularly in the IMU+EMG+EEG configuration, proves to be a robust and accurate predictor of FoG events in PD patients. The study’s findings underscore the potential clinical impact of multimodal sensor fusion and deep learning in reducing false positives and negatives and enhancing precision, sensitivity, and specificity. These insights are crucial for deploying reliable FoG prediction systems in real-world settings and advancing PD management. Future research should explore additional sensor modalities, transferability to different PD cohorts, longitudinal data, and real-time deployment in clinical environments.

Modified electroconvulsive therapy (MECT) is an effective treatment for mood and psychiatric disorders and provides rapid and significant improvements in severe symptoms of several mental health conditions. The basis and molecular mechanisms underlying the therapeutic effects of MECT are poorly understood. We attempted to compare the urinary proteome of each depressive patient before and after electroconvulsive therapy. 54 urinary proteomes from 9 patients were analyzed, including before and after MECT. Due to the heterogeneity of depression disorder, comparing the urine proteome of each person before and after treatment was used. Common differential protein and biological process were thought to contribute most to the changes caused by MECT. The common biological processes enriched by differential proteins through GO analysis with most patients mainly included cell adhesion (9/9 patients), immune response (7/9), axon guidance (7/9), and oxidation stress (7/9). Moreover, the common biological pathways identified by Ingenuity Pathway Analysis software showed that acute phase response signaling (7/9 patients), NRF2-mediated oxidative stress response (7/9), synaptogenesis signaling pathway (5/9), and ephrin B signaling (5/9) were all upregulated among each patient and were involved in promoting synaptic plasticity and neuroplasticity. Common biological processes and pathways top distributed in urine were reported about resulting in increased excitatory synaptic activity, which were related to the mechanism of MECT in the treatment of mental illnesses. In addition, the common differential proteins CSPG4, CBG, APP, NCAM1, and ARSA were suspected to be related to memory loss, memory damage, and memory formation, which might be the effects of MECT.

With the aging population and labor shortage, the proportion of labor costs in the production costs of tomato harvesting is increasing, making the research and development of tomato harvesting robots urgent. This paper develops a cherry tomato harvesting robot, consisting of a mobile chassis, lifting platform, robotic arm, end effector, depth camera, and control system, to achieve automated walking navigation, harvesting, and basket loading. This paper outlines the system design and harvesting scenario of the tomato harvesting robot, details the design and implementation of the robot’s chassis and walking route planning, end effector design, tomato recognition and positioning, robotic arm motion planning, and control system. Furthermore, the architecture and control flow of the software system are elaborated. Finally, field tests validate the robot’s performance and harvesting success rate. Tests show that the overall accuracy and recall rates of the visual recognition model for tomato bunches are 85.04% and 88.71%, respectively, and for the stalks are 82.72% and 81.51%, respectively, with a harvesting success rate of 70.77%. These efforts provide beneficial exploration for the future commercial application of cherry tomato harvesting robots.

： The secure gripping of soft grippers remains a difficult challenge to address. To solve this challenge, the Single-axis deformation (SD) soft grippers were designed that were inspired by the blooming behavior of petunias. Four SD finger structures were designed by analyzing the anatomical structure of petunia petals. The stress concentration resulting from the deformation of the fingers with different structures was analyzed using numerical methods under the same deformation load conditions. In order to prove the SD soft grippers have a improving ability of secure gripping, The dexterity, gripping capacity, and radial load-bearing capacity of the SD soft grippers were tested through experiments. The experimental results shown that the opening and closing range of the SD soft gripper is 18mm-144mm, the maximum gripping load is 39.4N, and the radial bending angle is only 2.76 when the radial load is 24N.

The precision of cancer immunotherapy is critically dependent on accurately characterizing the tumor immune microenvironment (TIME), which represents a complex interplay of cellular components, cytokines, and metabolic factors. Traditional diagnostic methods have been limited in resolving the dynamic molecular interactions within the TIME at a microscale level. This review focuses on recent advancements in microscale measurements for identifying novel immune-oncology biomarkers and therapeutic targets within the TIME, emphasizing the importance of high-fidelity data on tumor immune infiltrates and the significance of longitudinal high-dimensional analysis for predicting treatment responses. Furthermore, the review discusses the impact of cancer metabolic reprogramming on the TIME and the potential of new biomarkers for predicting responses to immunotherapy. The role of nanotechnology in enhancing the detection of immune checkpoints and the development of AI-based sensors for real-time data analysis and predictive modeling is also explored, highlighting the potential of these advanced technologies to revolutionize the field of cancer immunotherapy.

A low-cost high-responsivity design of Si/SiGe Heterojunction Bipolar Phototransistor (HPT) built in an industrial 55nm-BiCMOS technology is integrated in a cascode configuration with a bipolar bipolar transistor (HBT) to be used for microwave-photonic communication receivers. Performances of both the cascode pair and the single Heterojunction Bipolar Phototransistor are compared. At high-frequency, the cascode circuit has better performances than the single HPT stage. At 850-nm wavelength, the pair can reach a low-frequency responsivity a low-frequency responsivity of 3.24 A/W and a bandwidth of 0.69 GHz when coupling losses are corrected.

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Processing of sensory stimuli triggers changes in brain electrical activity characterized by increases in the centroparietal Late Positive Potential (LPP) and larger posterior alpha frequency desynchronization. Additionally, it has been showed that visual inspection parameters change during the presentation of emotional high arousing stimuli, suggesting orienting and attention allocation, in accordance with recent approaches suggesting that the processing of emotional stimuli requires attentional resources. Interestingly, indicators of visual scanning have been few used to determine engagement in tasks used as distractors during the processing of emotional images. This work aimed to analyze the effects of the attentional competence between the performance of a cognitive task and the processing of an emotionally arousing picture using EEG and Eye Tracking. Results showed that the superimposition of a cognitive task in a very reduced space of the visual field (1,2%) had an early attractor effect causing a reduction in the LPP amplitude, suggesting that the allocation of attentional resources is necessary for the processing of arousing images. Unexpectedly, the background image exploration was reassumed after participants responded to the task, particularly the unpleasant pictures. This effect can be attributed to the intrinsic significance of the emotional images.

Understanding the mechanism underlying the formation of bimodal raindrop size distribution (RDSD) requires quantification of the cloud microphysical and dynamic behavior of precipitation particles within the precipitation system. Although the microphysical equilibrium state associated with collision-coalescence and breakup is considered the main mechanism for the formation of bimodal RDSD, the importance of dynamical advection effects associated with the influence of background wind fields has also been pointed out in recent years. Here, we investigated the formation of bimodal RDSD by quantifying the microphysical and dynamical processes that cause RDSD variability in a two-dimensional idealized simulation with an explicit representation of RDSD using a spectral-bin cloud microphysics scheme. Within the simulated precipitation system, bimodal RDSDs formed by horizontal and vertical advection and collision-coalescence breakups were present in similar proportions. The coalescence breakup-type bimodal RDSD appeared when the updrafts in the background field were strong. In contrast, the vertical advection-type bimodal RDSD was formed when the particles at the secondary peak selectively fell out by size sorting. Furthermore, the horizontal advection type of the bimodal RDSD was formed under the influence of particle size sorting associated with horizontal wind. The bimodal RDSD formed by these processes can be classified according to the particle size of the secondary peak. This study proposes a novel comprehensive picture of the bimodal RDSD formation mechanism caused by different microphysical and dynamical processes.

Raindrop size distribution (DSD) is fundamental for understanding precipitation processes. This study utilized a two-dimensional simulation with bin cloud microphysics parameterizations to investigate the spatiotemporal variability of DSDs owing to the influence of mesoscale circulation associated with the precipitation system. The simulated multicellular convection went through developing, mature, and dissipating stages, with updraft weakening and rainfall area expanding through these stages. The width of the DSD narrowed as rainfall weakened. In addition, a significant bimodal DSD was observed during the dissipating stage. Furthermore, we investigated the spatial distribution of the number density of raindrops corresponding to the maximum, local minimum, and local maximum of the significant bimodal DSD in the dissipating stage. According to the results, the raindrops constituting the maximum, local minimum, and local maximum followed different advection processes. This size-dependent advection effect may have contributed to the bimodal DSD formation.

Kali B. Middleby1, Lucas A. Cernusak1­, Martin F. Breed2, Darren M. Crayn3,4, Susan G.W. Laurance1, Noel Preece1,5,6, Penny van Oosterzee1,5,6, Jayden Engert1, and Alexander W. Cheesman11 Centre for Tropical Environmental Sustainability Science, James Cook University Nguma-Bada Campus, McGregor Road, Smithfield, QLD, Australia2 College of Science and Engineering, Flinders University, Bedford Park, SA, Australia3 Australian Tropical Herbarium, James Cook University Nguma-Bada Campus, McGregor Road, Smithfield, QLD, Australia4 ARC Centre of Excellence for Indigenous and Environmental Histories and Futures, James Cook University Nguma-Bada Campus, McGregor Road, Smithfield, QLD, Australia5 Biome 5 Pty Ltd., Atherton, QLD, Australia6Research Institute for the Environment and Livelihoods, Charles Darwin University, Darwin, NT 0909, Australia

Key Clinical Message:Masson’s tumor is a rare condition that can mimic malignancy, particularly when located in atypical regions. This case emphasizes the importance of considering this diagnosis in unusual anatomical locations and highlights the critical role of histopathological evaluation in achieving an accurate diagnosis. Prompt identification and surgical management can lead to favorable outcomes, even in rare presentations.Introduction:Masson’s tumor, also known as intravascular papillary endothelial hyperplasia (IPEH), is a benign non-neoplastic lesion, first described in 1923 under the name of “vegetant intravascular hemangioendothelioma” [1]. Initially believed to be an atypical proliferation of papillary endothelial cells, it was reclassified as a reactive process in 1932 by Henschen. This tumor is rare, and accounts for 2% of benign and malignant vascular tumors of the skin and subcutaneous tissues [2].This case highlights a Masson tumor, a vascular tumor arising in the lower extremities, a region where such tumors are less commonly observed compared to their typical occurrence in the head and neck area.Case History/ExaminationA 49-year-old male hairdresser presented to an outpatient clinic in Beirut, Lebanon, with a chief complaint of a lesion on the right posterior lower extremity, which was present for the past 3 years. The lesion had grown recently, over the last 6 months and was not painful to touch. The patient’s occupation required prolonged periods of standing.On examination, a large, soft, well-demarcated subcutaneous nodule measuring approximately 4 x 4 cm in size was noted at the site (fig1). The lesion was non-tender to palpation. The patient had no significant past medical history, surgical history, or reported allergies. Family history included pilar cysts in the patient’s mother and brother.MethodsDifferential DiagnosisThe patient presented with a subcutaneous nodule with a benign clinical appearance, suggestive of a common soft tissue lesion such as a lipoma. No additional symptoms or concerning features, such as rapid growth, pain, or skin changes, were observed. Based on the clinical presentation, the differential diagnosis primarily included lipoma, epidermoid cyst, or a benign vascular lesion.InvestigationsDue to financial limitations, advanced imaging or biopsy was not performed prior to excision. The clinical evaluation supported the decision to proceed with direct surgical excision under the working assumption of a lipoma.Post-excision, the gross examination revealed a well-demarcated vascular nodule, located superficial to the subcutaneous tissue, comprising three lobules encapsulated within fibrous bands. Histologic examination of the excised tissue revealed a dilated vessel within the superficial subcutaneous tissue, showing intravascular proliferation of reactive endothelial cells. The endothelial cells formed numerous papillary structures lined by a single layer of plump endothelial cells. The lesion was enclosed within a fibrous pseudo capsule, supporting the diagnosis of a benign vascular tumor.TreatmentThe nodule was excised in its entirety during the initial surgical procedure. Complete surgical excision was achieved, as confirmed by histopathology, with no evidence of residual lesion or malignancy.Conclusion and results:Figures 2 and 3 show the histological results. The surgical approach and prognosis were explained to the patient. Informed consent was obtained for the use of his photos and clinical information in this case report.Following complete surgical excision, the patient experienced an uneventful recovery with no signs of recurrence at follow-up. Dermatologists and surgeons should maintain a high index of suspicion for IPEH when evaluating vascular tumors to optimize patient outcomes.Intravascular papillary endothelial hyperplasia (IPEH) is a rare but benign vascular lesion that poses diagnostic challenges, particularly in the clinical and pre-operative settings. Accurate diagnosis relies heavily on histopathological evaluation, as clinical presentations often mimic other soft tissue lesions. This case underscores the importance of considering IPEH in the differential diagnosis of vascular tumors to ensure timely and appropriate management.Discussion:This tumor has several names, including Masson’s hemangioma, Masson intravascular hemangio-endothelioma, intravascular papillary endothelial hyperplasia (IPEH), and reactive papillary endothelial hyperplasia [3].The precise etiopathogenesis remains unclear, though it is widely regarded as a reactive process believed to result from growth factors production, leading to excessive endothelial cell proliferation [4]. In fact, research employing northern blot and immunoblotting revealed a significant increase in the expression of fibroblast growth factor beta, suggesting its secretion by the endothelial cells through an autocrine mechanism. The condition is thought to arise from an aberrant resolution of a thrombosis, unfolding through several stages [5].It typically manifests as a firm or soft, reddish-blue color nodule over the head and neck and upper extremities [6]. Occurrences on the lower extremities, such as in our case, are rare. Generally, it is asymptomatic, slow-growing and is not associated with any pulsation. The sonographic features of subcutaneous IPEH are not specific; however, consideration of the diagnosis is warranted when encountering a soft tissue mass showing a vascular pattern. This entity has a slight predilection for adult females, and IPEH can also manifest in children [7].Diagnosis mainly relies on histology since imaging such as MRI or US cannot differentiate it from other vascular lesions. Histologically, it is characterized by the presence of papillary structures lined by a single layer of endothelial cells. There will be absence of pleomorphism, mitosis or necrosis. It has been classified into three main types. The first type is the pure form, where the endothelial proliferation occurs from veins and less commonly artery without any vascular abnormalities. The second type arises from a pre-existing vascular abnormalities such as an aneurysm [5], arteriovenous malformations, hemangiomas and pyogenic granulomatosis. The third and least common type arises from an extravascular hematoma.These tumors stain positive for CD31 and CD34 [8]. Staining positivity for factor VIII, type 4 collagen and SMA and MSA varies and is not as consistent.Clinically, IPEH can mimic a variety of conditions, both benign and malignant such as pyogenic granuloma and Kaposi’s sarcoma. Moreover, it should be distinguished from malignant angiosarcoma, a differentiation typically achieved through histology and immunohistochemical staining. The primary characteristic of IPEH is its intravascular development, in contrast to angiosarcoma, which rarely remains confined within the vascular lumen. Also, CD105 is a useful immunohistochemical stain, as angiosarcoma would stain positive while IPEH doesn’t [8].Since IPEH can be mistaken for angiosarcoma and other malignant tumors, surgical excision is the treatment of choice. Since these tumors rarely occur de novo within extravascular hematomas, meticulous surgical techniques should be utilized during resection to prevent any spillage of the aneurysm-associated thrombus, given the theoretical risk of extravascular recurrence. Other alternative options include observation or using sclerosing agents such as sodium tetradecyl sulfate [9]. Chemotherapy or radiotherapy may be considered for cases of recurrence following incomplete excision, as well as for multiple intracranial lesions or suspected lesions[10].Ethical Statement:the patient in this manuscript has given written informed consent for participation in the study and the use of their de-identified, anonymized, aggregated data and their case details (including photographs) for publication.Author ContributionMariana El Hawa (1st author): Conceptualization and study design, data analysis, manuscript drafting, and critical revision.Serena Saade: Critical review of histopathological findings and drafting specific sections of the manuscript.William Abou Shahla: literature review and drafting specific sections of the manuscript.Dana Saade: Critical review of the whole manuscript and contribution to the discussion section.References:1. Masson, P., Hemangioendotheliome vegetant intravasculaire. Bull.Soc.Anat.Paris, 1923. 93 : p. 517-523.2. Fasina, O., A. Adeoye, and E. Akang, Orbital intravascular papillary endothelial hyperplasia in a Nigerian child: a case report and review of the literature. J Med Case Rep, 2012. 6 : p. 300.3. Benantar, L., et al., Peri-orbital Masson’s tumor: a case report and literature review. Pan Afr Med J, 2022. 42 : p. 147.4. Sasso, S.E., et al., Masson’s tumor (intravascular papillary endothelial hyperplasia). An Bras Dermatol, 2019. 94 (5): p. 620-621.5. Chapman, S.C., et al., Masson tumor (intravascular papillary endothelial hyperplasia) arising in a superficial temporal artery aneurysm. J Vasc Surg Cases Innov Tech, 2019. 5 (3): p. 388-391.6. Kim, O.H., et al., Subcutaneous intravascular papillary endothelial hyperplasia: ultrasound features and pathological correlation. Skeletal Radiol, 2016. 45 (2): p. 227-33.7. Huang, W.P., et al., Intravascular papillary endothelial hyperplasia of the spleen in a child: a case report. BMC Med Imaging, 2022.22 (1): p. 207.8. Akdur, N.C., et al., Intravascular papillary endothelial hyperplasia: histomorphological and immunohistochemical features. Diagn Pathol, 2013. 8 : p. 167.9. De Maria, L., et al., Sclerotherapy for Venous Malformations of Head and Neck: Systematic Review and Meta-Analysis. Neurointervention, 2020. 15 (1): p. 4-17.10. Dryden, S.C., et al.,Intravascular Papillary Endothelial Hyperplasia of the Orbit: A Case of Masson’s Tumor. Cureus, 2019. 11 (12): p. e6266.

The Arctic tundra biome is undergoing rapid shrub expansion (“shrubification”) in response to anthropogenic climate change. During the previous ~2.6 million years, glacial cycles caused substantial shifts in Arctic vegetation, leading to changes in species’ distributions, abundance, and connectivity, which have left lasting impacts on the genetic structure of modern populations. Examining how shrubs responded to past climate change using genetic data can inform the ecological and evolutionary consequences of shrub expansion today. Here we test scenarios of Quaternary population history of dwarf birch species (Betula nana L. and Betula Glandulosa Michx.) using SNP markers obtained from RAD sequencing and approximate Bayesian computation. We compare the timings of population events with ice sheet reconstructions and other paleoenvironmental information to untangle the impacts of alternating cold and warm periods on the phylogeography of dwarf birch. Our best supported model suggested that the species diverged in the Mid-Pleistocene Transition as glaciations intensified, and ice sheets expanded. We found support for a complex history of inter- and intraspecific divergences and gene flow, with secondary contact occurring during periods of both expanding and retreating ice sheets. Our spatiotemporal analysis suggests that the modern genetic structure of dwarf birch was shaped by transitions in climate between glacials and interglacials, with ice sheets acting alternatively as a barrier or an enabler of population mixing. Tundra shrubs may have had more nuanced responses to past climatic changes than phylogeographic analyses have often suggested, with implications for future eco-evolutionary responses to anthropogenic climate change.

As the impacts of global climate change and human activities intensify, monitoring and assessing ecological environmental quality (EEQ) is crucial for sustainable development. This study takes the Northern Slope Economic Belt of the Tianshan Mountains (NSEB of the Tianshan Mountains) as an example, using Landsat satellite imagery data from 1996 to 2023. Based on the Google Earth Engine (GEE) platform, we constructed a Remote Sensing Ecological Index (RSEI) to evaluate the spatiotemporal characteristics of ecological environment evolution in this region. Through Principal Component Analysis (PCA), we integrated four key RSEI: greenness, humidity, dryness, and heat, to reveal the main driving factors of EEQ changes. The research results indicate that: 1) From 1996 to 2023, the overall EEQ in the study area showed a deteriorating trend. However, the EEQ in places such as Tacheng City and Shuanghe City, Xinjiang Uygur Autonomous Region, China, has improved year by year, while the EEQ in Hoboksar Mongol Autonomous County and Alashankou City, Xinjiang Uygur Autonomous Region, China, has deteriorated annually. 2)The degradation of the EEQ in the NSEB of the Tianshan Mountains is greater than the improvement, with degraded areas accounting for 50.93% and improved areas accounting for 3.05%. In the future, the EEQ in most regions is expected to show an improving trend, covering 42.27% of the total area. 3)The analysis of the driving factors of the EEQ using geographic detectors indicates that both human and natural factors significantly impact EEQ, with land use change having the greatest influence.

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