Complex Organ Research Articles

Artificial hearing systems based on functional cochlea models

Abstract The cochlea is one of the most complex organs in the human body, exhibiting a complex interplay of characteristics in acoustic, mechanical, electrical, and biological functions. Functional cochlea models are an essential platform for studying hearing mechanics and are crucial for developing next-generation auditory prostheses and artificial hearing systems for sensorineural hearing restoration. Recent advances in additive manufacturing, organ-on-a-chip models, drug delivery platforms, and artificial intelligence have provided valuable insights into how to manufacture artificial cochlea models that more accurately replicate the complex anatomy and physiology of the inner ear. This paper reviews recent advancements in the applications of advanced manufacturing techniques in reproducing the physical, biological, and intelligent functions of the cochlea. It also outlines the current challenges to developing mechanically, electrically, and anatomically accurate functional models of the inner ear. Finally, this review identifies the major requirements and outlook for impactful research in this field going forward. Through interdisciplinary collaboration and innovation, these functional cochlea models are poised to drive significant advancements in hearing treatments, and ultimately enhance the quality of life for individuals with hearing loss.

Parallel Simulations of the Sharp Wave-Ripples of the Hippocampus on Multicore CPUs and GPUs

The simulation of realistic systems plays a crucial role in modern sciences. Complex organs such as the brain can be described by mathematical models to reproduce biological behaviors. In the brain, the hippocampus is a critical region for memory and learning. In the literature, a model to reproduce the memory consolidation mechanism has been proposed. This model exhibits a high degree of biological realism, though it is accompanied by a significant increase in computational complexity. This paper proposes the development of parallel simulation targeting different devices, namely multicore CPUs and GPUs. The experiments highlighted that the biological realism is maintained, together with a significant decrease of the processing times. Finally, the conducted analysis highlights that the GPU is one of the most suitable technologies for this kind of simulation.

Cellular heterogeneity and dynamics of the human uterus in healthy premenopausal women

The human uterus is a complex and dynamic organ whose lining grows, remodels, and regenerates every menstrual cycle or upon tissue damage. Here, we applied single-cell RNA sequencing to profile more the 50,000 uterine cells from both the endometrium and myometrium of five healthy premenopausal individuals, and jointly analyzed the data with a previously published dataset from 15 subjects. The resulting normal uterus cell atlas contains more than 167K cells, representing the lymphatic endothelium, blood endothelium, stromal, ciliated epithelium, unciliated epithelium, and immune cell populations. Focused analyses within each major cell type and comparisons with subtype labels from prior studies allowed us to document supporting evidence, resolve naming conflicts, and propose a consensus annotation system of 39 subtypes. We release their gene expression centroids, differentially expressed genes, and messenger Ribonucleic Acid (mRNA) patterns of literature-based markers as a shared community resource. We identify multiple potential progenitor cells: compartment-wide progenitors for each major cell type and potential cross-lineage multipotent stromal progenitors that may replenish the epithelial, stromal, and endothelial compartments. Furthermore, many cell types and subtypes exhibit shifts in cell number and transcriptomes across different phases of the menstrual cycle. Finally, comparisons between premenopausal, postpartum, and postmenopausal samples revealed substantial alterations in tissue composition, particularly in the proportions of stromal, endothelial, and immune cells. The cell taxonomy and molecular markers we report here are expected to inform studies of both basic biology of uterine function and its disorders.

Pathophysiological Markers of Acute Respiratory Distress Syndrome Severity Are Correlated With Ventilation-Perfusion Mismatch Measured by Electrical Impedance Tomography.

Pulmonary ventilation/perfusion (V/Q) mismatch measured by electrical impedance tomography (EIT) is associated with the outcome of patients with the acute respiratory distress syndrome (ARDS), but the underlying pathophysiological mechanisms have not been fully elucidated. The present study aimed to verify the correlation between relevant pathophysiological markers of ARDS severity and V/Q mismatch. Prospective observational study. General ICU of a university-affiliated hospital. Deeply sedated intubated adult patients with ARDS under controlled mechanical ventilation. Measures of V/Q mismatch by EIT, respiratory mechanics, gas exchange, lung imaging, and plasma biomarkers. Unmatched V/Q units were assessed by EIT as the fraction of ventilated nonperfused plus perfused nonventilated lung units. At the same time, plasma biomarkers with proven prognostic and mechanistic significance for ARDS (carbonic anhydrase 9 [CA9], hypoxia-inducible factor 1 [HIF1], receptor for advanced glycation endproducts [RAGE], angiopoietin 2 [ANG2], gas exchange, respiratory mechanics, and quantitative chest CT scans were measured. Twenty-five intubated ARDS patients were included with median unmatched V/Q units of 37.1% (29.2-49.2%). Unmatched V/Q units were correlated with plasma levels of CA9 (rho = 0.47; p = 0.01), HIF1 (rho = 0.40; p = 0.05), RAGE (rho = 0.46; p = 0.02), and ANG2 (rho = 0.42; p = 0.03). Additionally, unmatched V/Q units correlated with plateau pressure (r = 0.38; p = 0.05) and with the number of quadrants involved on chest radiograph (r = 0.73; p < 0.01). Regional unmatched V/Q units were correlated with the corresponding fraction of poorly aerated lung tissue (r = 0.62; p = 0.01) and of lung tissue weight (rho: 0.51; p = 0.04) measured by CT scan. In ARDS patients, unmatched V/Q units are correlated with pathophysiological markers of lung epithelial and endothelial dysfunction, increased lung stress, and lung edema. Unmatched V/Q units could represent a comprehensive marker of ARDS severity, reflecting the complex organ pathophysiology and reinforcing their prognostic significance.

"Osteo-Organogenesis Niche" Hyaluronic Acid Engineered Materials Directing Re-Osteo-Organogenesis via Manipulating Macrophage CD44-MAPK/ERK-ETV1/5-MRC1 Axis.

The strategy of re-organogenesis provides an optimal framework for restoring complex organ structures and functions in adult damage. While the focus has often been on restoring organogenesis stem cells, there is limited investigations of reverting the environmental niche to support this approach. The guiding principle of "Nature selects the fittest to survive" drives the intricate dynamic changes in cellular events within the niche environment, especially through immune surveillance. The extracellular matrix (ECM) serves as the "self-associated molecular patterns" of the niche, containing extensive data on cell-niche reaction data and acting as the active tuner of immune surveillance. In this study, hyaluronic acid (HA) is identified as a unique component of the ECM in cranial osteo-organogenesis. Mechanistically, HA activates the Cluster of Differentiation 44 (CD44)-Mitogen-Activated Protein Kinase (MAPK)/Extracellular Signal-Regulated Kinase (ERK)-Ets Variant 1/5 (ETV1/5)- Mannose Receptor C-Type 1 (MRC1) axis in macrophages, establishing a distinct immune surveillance during osteo-organogenesis. Furthermore, HA is utilized as a novel engineered material for an "Osteo-organogenesis niche", restoring immune surveillance and synergistically regulating stem cells to achieve re-osteo-organogenesis in cranial defects of rats. Taken together, the study unveils a previously unknown strategy for leveraging re-organogenesis by utilizing "organogenesis niche" ECM engineered materials to manipulate immune surveillance, thereby comprehensively regulating stem cells and other tissue cells effectively for re-organogenesis.

Cortical, striatal, and thalamic populations self-organize into a functionally connected circuit with long-term memory properties

The human brain is a complex organ with an intricate neuronal connectivity and diverse functional regions. Neurological disorders often disrupt the delicate balance among these anatomical compartments, resulting in severe impairments. The available therapeutic options constitute an incomplete solution as many patients respond partially, highlighting the need for continued research into causes and treatments. Bottom-up approaches, like in vitro models, offer insights into brain functions as they recreate the in vivo microenvironment that allows studying how specific features affect physiological and pathological conditions. In this work, we engineered the cortical-striatal-thalamic (CST) circuit, involved in many brain functions such as action initiation and selection, using a three-compartment polymeric device. We characterized the emerging spontaneous electrophysiological activity by using Micro-Electrode Arrays (MEAs). Cortical neurons exhibited complex bursting activity, which influenced the entire circuit. Striatal and thalamic neurons displayed predominantly tonic firing when isolated, while interconnections with the cortex synchronized and organized their neuronal activity, highlighting the cortical pivotal role in bursting activity and information processing. The CST circuit demonstrated self-organization abilities and displayed high entropy values, indicative of dynamic richness and information encoding potential. Furthermore, we proved the CST’s involvement in learning and memory. Our CST model provides a platform for further exploration into brain circuitry and potential therapeutic interventions, underscoring the necessity of realistic in vitro models to fully understand neurological diseases' pathophysiology.

Influence of Microenvironmental Orchestration on Multicellular Lung Alveolar Organoid Development from Human Induced Pluripotent Stem Cells.

Induced pluripotent stem cells (iPSCs) have emerged as promising in vitro tools, providing a robust system for disease modelling and facilitating drug screening. Human iPSCs have been successfully differentiated into lung cells and three-dimensional lung spheroids or organoids. The lung is a multicellular complex organ that develops under the symphonic influence of the microenvironment. Here, we hypothesize that the generation of lung organoids in a controlled microenvironment (cmO) (oxygen and pressure) yields multicellular organoids with architectural complexity resembling the lung alveoli. iPSCs were differentiated into mature lung organoids following a stepwise protocol in an oxygen and pressure-controlled microenvironment. The organoids developed in the controlled microenvironment displayed complex alveolar architecture and stained for SFTPC, PDPN, and KRT5, indicating the presence of alveolar epithelial type II and type I cells, as well as basal cells. Moreover, gene and protein expression levels were also increased in the cmO. Furthermore, pathway analysis of proteomics revealed upregulation of lung development-specific pathways in the cmO compared to those growing in normal culture conditions. In summary, by using a controlled microenvironment, we established a complex multicellular lung organoid derived from iPSCs as a novel cellular model to study lung alveolar biology in both lung health and disease.

Current State and Challenges of Tissue and Organ Cryopreservation in Biobanking

Recent years have witnessed significant advancements in the cryopreservation of various tissues and cells, yet several challenges persist. This review evaluates the current state of cryopreservation, focusing on contemporary methods, notable achievements, and ongoing difficulties. Techniques such as slow freezing and vitrification have enabled the successful preservation of diverse biological materials, including embryos and ovarian tissue, marking substantial progress in reproductive medicine and regenerative therapies. These achievements highlight improved post-thaw survival and functionality of cryopreserved samples. However, there are remaining challenges such as ice crystal formation, which can lead to cell damage, and the cryopreservation of larger, more complex tissues and organs. This review also explores the role of cryoprotectants and the importance of optimizing both cooling and warming rates to enhance preservation outcomes. Future research priorities include developing new cryoprotective agents, elucidating the mechanisms of cryoinjury, and refining protocols for preserving complex tissues and organs. This comprehensive overview underscores the transformative potential of cryopreservation in biomedicine, while emphasizing the necessity for ongoing innovation to address existing challenges.

Axis "microbiota – gut – eye": a review

Every organ in the human body has its own microbiota, and the eye, a complex multi-component organ, is no exception. Due to the limitations of traditional methods, detailed study of the ocular microbiome began only in 2010 as part of the Eye Microbiome Project, when advances in research methods made it possible to obtain detailed data, although there had been debate previously about whether microorganisms were even able to attach to the ocular surface due to the layers of the tear film, which have antibacterial properties. The cornea, conjunctiva, lacrimal glands and tear film, meibomian glands and microbiome form the microenvironment of the ocular surface, interacting together and resisting irritants, allergens and pathogens. Homeostasis of the ocular microbiota is critical for maintaining the health of the visual organ. Most microorganisms are found on the cornea and conjunctiva, and modern research methods, including 16S rRNA sequencing, have allowed us to establish the "core" of the ocular surface microbiota, identifying the most common types: Staphylococcus, Corynebacterium, Propionibacterium, and Streptococcus, although the exact composition of the “core” remains debatable. Many factors can influence the composition of the microbiome, including age, contact lens wear, ophthalmic medications, and antibiotics. Like the microbiome of many other organs, the ocular surface microbiome is influenced by the gut microbiome: this relationship has been called the "microbiota – gut – eye" axis. Within the "gut – eye" axis, healthy gut microbiota produce short-chain fatty acids, indoles, polyamines, and other substances that have a beneficial effect on the immune system and retinal health. The state of dysbiosis leads to disruption of homeostasis, and the increasing inflammatory reaction can contribute to damage to the optic nerve and progression of eye disease. Some ophthalmologic diseases, such as diabetic retinopathy, age-related macular degradation, choroidal neovascularization, uveitis, primary open-angle glaucoma, Sjogren's syndrome, dry eye syndrome are associated with dysbiosis of the intestinal microbial composition. Correction of intestinal dysbiosis using various methods can lead to a decrease in the risk of eye diseases, although additional research is needed to discover new methods for treating ophthalmologic pathologies along the "microbiota – gut – eye" axis.

Pathologic findings of the placenta and clinical implications - recommendations for placental examination.

The placenta is a unique and complex organ that combines the circulatory systems of two or more individuals within a single dynamic organ with a set, short lifespan. A diverse spectrum of disorders, including infections as well as metabolic, genetic, circulatory, and maturation defects, may affect its function. Pathology investigation of the placenta is key for identifying several pathogenic processes in both the mother and the foetus. Aberrant placentation, maternal and foetal vascular compromise, infection, inflammatory immunologic conditions, and disorders of maturation are elements of newly proposed classification schemes. The clinical impact of placental examination consists of diagnosing maternal and foetal disease, identifying the potential for recurrence, correlating clinical pathological findings with distinct morphologic features, and identifying the aetiology responsible for growth restriction or foetal death. Gestational trophoblastic disease occurs more frequently in the first trimester; however, in very rare cases, it can affect the term or third-trimester placenta. The application of reproducible nomenclature is expected to facilitate progress in the diagnosis and treatment of obstetric and foetal disorders with placental manifestation. Therefore, this review aims to facilitate communication between obstetricians, neonatologists, and pathologists involved in this diagnostic process.

Distinct cellular and junctional dynamics independently regulate the rotation and elongation of the embryonic gut in Drosophila.

Complex organ structures are formed with high reproducibility. To achieve such intricate morphologies, the responsible epithelium undergoes multiple simultaneous shape changes, such as elongation and folding. However, these changes have typically been assessed separately. In this study, we revealed how distinct shape changes are controlled during internal organ morphogenesis. The Drosophila embryonic hindgut undergoes left-right asymmetric rotation and anteroposterior elongation in a tissue-autonomous manner driven by cell sliding and convergent extension, respectively, in the hindgut epithelia. However, the regulation of these processes remains unclear. Through genetic analysis and live imaging, we demonstrated that cell sliding and convergent extension are independently regulated by Myosin1D and E-cadherin, and Par-3, respectively, whereas both require MyosinII activity. Using a mathematical model, we demonstrated that independently regulated cellular dynamics can simultaneously cause shape changes in a single mechanical system using anisotropic edge contraction. Our findings indicate that distinct cellular dynamics sharing a common apparatus can be independently and simultaneously controlled to form complex organ shapes. This suggests that such a mechanism may be a general strategy during complex tissue morphogenesis.

A cross-sectional study of tongue disorders among dental outpatients

PurposeThe tongue is a complex organ that can provide insight into oral and systemic conditions. A variety of disorders, such as geographic tongue, hairy tongue, fissured tongue, macroglossia, microglossia, and others, can be observed. The objective of this cross-sectional study, conducted on a cohort of dental patients, was to examine the prevalence of tongue disorders and their relationship with factors such as demographic data, oral hygiene practices, history of systemic diseases, and bad habits. MethodThe tongues of 772 dental outpatients, comprising 355 males and 417 females, were examined in detail, and the factors associated with tongue disorders were noted. ResultsThe prevalence of tongue disorders was 32.6%. The remaining tongue disorders were as follows: fissured tongue (12.1%), macroglossia (7.1%), geographic tongue (3.4%), hairy tongue (3.6%), coated tongue (3.4%), median rhomboid glossitis (0.5%), ankyloglossia (0.4%), glossitis (0.4%), and microglossia (0.1%). The most prevalent tongue disorder observed in the study cohort was fissured tongue, while both bifid tongue and idiopathic burning tongue syndrome were absent. The prevalence of macroglossia, fissured tongue, and hairy tongue was significantly higher in males than in females (p<0.05, p< 0.05, p < 0.05, p < 0.005, respectively). A statistically significant difference was observed in the frequency of macroglossia, furred tongue, hairy tongue, and glossitis between age groups. ConclusionThe findings of this study identified the most common tongue disorders and their relationship with factors such as systemic history, demographic factors, oral hygiene care, bad habits, and systemic diseases. The significance of tongue appearance in providing insight into the systemic and oral condition of the patient has once again been demonstrated.

Reinforcement learning-based anatomical maps for pancreas subregion and duct segmentation.

The pancreas is a complex abdominal organ with many anatomical variations, and therefore automated pancreas segmentation from medical images is a challengingapplication. In this paper, we present a framework for segmenting individual pancreatic subregions and the pancreatic duct from three-dimensional (3D) computed tomography (CT) images. A multiagent reinforcement learning (RL) network was used to detect landmarks of the head, neck, body, and tail of the pancreas, and landmarks along the pancreatic duct in a selected target CT image. Using the landmark detection results, an atlas of pancreases was nonrigidly registered to the target image, resulting in anatomical probability maps for the pancreatic subregions and duct. The probability maps were augmented with multilabel 3D U-Net architectures to obtain the final segmentationresults. To evaluate the performance of our proposed framework, we computed the Dice similarity coefficient (DSC) between the predicted and ground truth manual segmentations on a database of 82 CT images with manually segmented pancreatic subregions and 37 CT images with manually segmented pancreatic ducts. For the four pancreatic subregions, the mean DSC improved from 0.38, 0.44, and 0.39 with standard 3D U-Net, Attention U-Net, and shifted windowing (Swin) U-Net architectures, to 0.51, 0.47, and 0.49, respectively, when utilizing the proposed RL-based framework. For the pancreatic duct, the RL-based framework achieved a mean DSC of 0.70, significantly outperforming the standard approaches and existing methods on different datasets. The resulting accuracy of the proposed RL-based segmentation framework demonstrates an improvement against segmentation with standard U-Netarchitectures.

Research progress on single-cell expression quantitative trait loci.

Expression quantitative trait loci (eQTL) represent genetic variants that regulate gene expression levels. eQTL analysis has become a crucial method for identifying the functional roles of disease-associated genetic variants in the post-genome-wide association study (GWAS) era, yielding numerous significant discoveries. Traditional eQTL analysis relies on whole-genome sequencing combined with bulk RNA-seq, which obscures gene expression differences between cells and thus fails to identify cell type- or state-dependent eQTL. This limitation makes it challenging to elucidate the roles of disease-associated genetic variants under specific conditions. In recent years, with the development and widespread application of single-cell RNA sequencing (scRNA-seq) technology, scRNA-seq-based eQTL (sc-eQTL) research has emerged as a focal point. The advantage of this approach lies in its ability to leverage the resolution and granularity of single-cell sequencing to uncover eQTL that are dependent on cell type, cell state, and cellular dynamics. This significantly enhances our ability to analyze genetic variants associated with gene expression. Consequently, it holds substantial significance for advancing our understanding of the formation of complex organs and the mechanisms underlying disease onset, progression, intervention, and treatment. This review comprehensively examines the recent advancements in sc-eQTL studies, focusing on their development, experimental design strategies, modeling approaches, and current challenges. The aim is to offer researchers novel perspectives for identifying disease-associated loci and elucidating gene regulatory mechanisms.

Evolution of the Human Brain and the Myth of its Ten-Percent Use

The human brain is a complex organ that controls nearly every function of the human body. As science believes, humans evolved from apes but over time, humans achieved domain specification and maturation in the nervous system due to which they gained sensory, language, and other social cognition functions, called higher-level cognitive functions. Neurogenesis, or brain development, is an organized process that starts from the early weeks of pregnancy to early childhood. During development, brain parts connect to each other directly and indirectly to process information. As the brain is a mysterious organ so many theories and myths are linked to its development and its use. A widespread misconception, a claim, is that most people use only about 10 % of their potential brain power. But there is no room for this myth because we have now mapped almost every region of the brain. Furthermore, PET scans and fMRI clearly show that almost all parts of the brain are connected to each other and all parts are functionally active. And if the parts of the brain are unnecessary and unused, then they must be removed or disappear, according to the rule of the theory of evolution. Now it is the time to put the myth to rest even though it has survived for a whole century.

Cross‐Institutional Prediction System for Estimating Patient‐Specific Organ Dose from Chest CT Scans without Segmenting Internal Organs

This study aims to establish and validate a cross‐institutional prediction system for estimating patient‐specific organ doses from chest CT scans. By collaborating across multiple institutions, the study seeks to develop models that allow rapid online estimation of organ doses, eliminating the need for complex organ segmentation. Researchers delineate skin outlines from chest CT images obtained from two different institutions. Radiomics features are extracted from the chest CT data and skin contours. Organ doses are computed using Monte Carlo simulations as reference organ doses. Single‐ and cross‐institutional support vector regression (SVR) models are trained with radiomics features to predict organ doses from chest CT scans. Model performance is assessed using metrics like maean absolute percentage error (MAPE) and R‐squared (R2). For chest organs (lungs, heart, spinal cord, trachea, and esophagus), single‐institutional SVR models achieve MAPE values ranging from 4.72% to 15.31% and R2 values from 0.73 to 0.93. Cross‐institutional models have MAPE values in the range of 2.16–7.49% and R2 values from 0.84 to 0.99. SVR models trained with radiomics features from skin outlines can reliably estimate organ doses from chest CT scans. The proposed method is applicable across different institutions, and cross‐institutional models enhance predictive accuracy, generality, and robustness.

Lipids and adipocytes involvement in tumor progression with a focus on obesity and diet.

The adipose tissue is a complex organ that can play endocrine, metabolic, and immune regulatory roles in cancer. In particular, adipocytes provide metabolic substrates for cancer cell proliferation and produce signaling molecules that can stimulate cell adhesion, migration, invasion, angiogenesis, and inflammation. Cancer cells, in turn, can reprogram adipocytes towards a more inflammatory state, resulting in a vicious cycle that fuels tumor growth and evolution. These mechanisms are enhanced in obesity, which is associated with the risk of developing certain tumors. Diet, an exogenous source of lipids with pro- or anti-inflammatory functions, has also been connected to cancer risk. This review analyzes how adipocytes and lipids are involved in tumor development and progression, focusing on the relationship between obesity and cancer. In addition, we discuss how diets with varying lipid intakes can affect the disease outcomes. Finally, we introduce novel metabolism-targeted treatments and adipocyte-based therapies in oncology.

The InterVision Framework: An Enhanced Fine-Tuning Deep Learning Strategy for Auto-Segmentation in Head and Neck.

Adaptive radiotherapy (ART) workflows are increasingly adopted to achieve dose escalation and tissue sparing under dynamic anatomical conditions. However, recontouring and time constraints hinder the implementation of real-time ART workflows. Various auto-segmentation methods, including deformable image registration, atlas-based segmentation, and deep learning-based segmentation (DLS), have been developed to address these challenges. Despite the potential of DLS methods, clinical implementation remains difficult due to the need for large, high-quality datasets to ensure model generalizability. This study introduces an InterVision framework for segmentation. The InterVision framework can interpolate or create intermediate visuals between existing images to generate specific patient characteristics. The InterVision model is trained in two steps: (1) generating a general model using the dataset, and (2) tuning the general model using the dataset generated from the InterVision framework. The InterVision framework generates intermediate images between existing patient image slides using deformable vectors, effectively capturing unique patient characteristics. By creating a more comprehensive dataset that reflects these individual characteristics, the InterVision model demonstrates the ability to produce more accurate contours compared to general models. Models are evaluated using the volumetric dice similarity coefficient (VDSC) and the Hausdorff distance 95% (HD95%) for 18 structures in 20 test patients. As a result, the Dice score was 0.81 ± 0.05 for the general model, 0.82 ± 0.04 for the general fine-tuning model, and 0.85 ± 0.03 for the InterVision model. The Hausdorff distance was 3.06 ± 1.13 for the general model, 2.81 ± 0.77 for the general fine-tuning model, and 2.52 ± 0.50 for the InterVision model. The InterVision model showed the best performance compared to the general model. The InterVision framework presents a versatile approach adaptable to various tasks where prior information is accessible, such as in ART settings. This capability is particularly valuable for accurately predicting complex organs and targets that pose challenges for traditional deep learning algorithms.

Kupffer Cells and Hepatocytes: A Key Relation in the Context of Canine Leishmaniasis.

Human zoonotic visceral leishmaniasis (ZVL) and canine leishmaniasis (CanL) constitute a major public and veterinary health concern and are both caused by the infection with the protozoan parasite Leishmania infantum. One of the main target organs in CanL is the liver. This complex organ, composed of various highly specialized cell types, has garnered significant attention from the scientific community as a crucial player in innate immune functions. In the context of CanL, liver infection by parasites and the host immune response generated strongly influence the disease outcome. Thus, taking advantage of a co-culture system involving canine hepatocytes and L. infantum-infected autologous Kupffer cells (KCs), allowing cell-to-cell interaction, the current report aims to shed light on the hepatocyte-KCs immune interaction. The co-culture of infected KCs with hepatocytes revealed a vital role of these cells in the activation of a local immune response against L. infantum parasites. Although KCs alone can be immunologically silenced by L. infantum infection, the cell-to-cell interaction with hepatocytes in co-culture can lead to local immune activation. In co-culture it was observed gene expression increased the number of innate immune receptors, specifically cell membrane TLR2 and cytoplasmatic NOD1 along with high TNF-α generation. Altogether, these results suggest that the immune response generated in co-culture could induce the recruitment of other circulating cells to contain and contribute to the resolution of the infection in the liver. This work also enhances our understanding of the liver as a vital organ in innate immunity within the context of CanL.

Optical Transmission in Single-Layer Brain Tissues under Different Optical Source Types: Modelling and Simulation.

The human brain is a complex organ controlling daily activity. Present technique models have mostly focused on multi-layer brain tissues, which lack understanding of the propagation characteristics of various single brain tissues. To better understand the influence of different optical source types on individual brain tissues, we constructed single-layer brain models and simulated optical propagation using the Monte Carlo method. Based on the optical simulation results, sixteen optical source types had different optical energy distributions, and the distribution in cerebrospinal fluid had obvious characteristics. Five brain tissues (scalp, skull, cerebrospinal fluid, gray matter, and blood vessel) had the same set of the first three optical source types with maximum depth, while white matter had a different set of the first three optical source types with maximum depth. Each brain tissue had different optical source types with the maximum and minimum full width at half maximum. The study on single-layer brain tissues under different optical source types lays the foundation for constructing complex brain models with multiple tissue layers. It provides a theoretical reference for optimizing the selection of optical source devices for brain imaging.