Macrophages as a source and target of GDF-15

(1) Background: The Gárdos channel (KCNN4) and Piezo1 are the best-known ion channels in the red blood cell (RBC) membrane. Nevertheless, the quantitative electrophysiological behavior of RBCs and its heterogeneity are still not completely understood.; (2) Methods: Here we use state-of-the-art biochemical methods to probe for the abundance of the channels in RBCs. Furthermore, we utilize automated patch-clamp, based on planar chips, to compare the activity of the two channels in reticulocytes and mature RBCs. Besides this characterization, we performed membrane potential measurements to demonstrate the effect of channel activity and interplay on the RBC properties.; (3) Results: Both, Gárdos channel and Piezo1, albeit their average copy number of activatable channels per cell is in the single digit range, can be detected by transcriptome analysis of reticulocytes. Proteomics analysis of RBCs could only detect Piezo1 but not the Gárdos channel. Furthermore, they can be reliably measured in the whole-cell configuration of the patch-clamp method. While for the Gárdos channel the activity is higher in reticulocytes compared to mature RBCs, for Piezo1 the tendency is the opposite. While the interplay between Piezo1 and Gárdos channel cannot be followed using the patch-clamp measurements, it could be proved based on membrane potential measurements in populations of intact RBCs.; (4) Conclusions: We discuss the Gárdos channel and Piezo1 abundance, interdependencies and interactions in the context of their proposed physiological and pathophysiological functions, which are the passing of small constrictions, e.g., in the spleen, and their active participation in blood clot formation and thrombosis.

Combined radiation with hemorrhage (combined injury, CI), exacerbates hematopoietic acute radiation syndrome and mortality compared to radiation alone (RI). We evaluated the effects of RI or CI on blood cell depletion as a biomarker to differentiate the two. Male CD2F1 mice were exposed to 8.75 Gy γ- radiation (60Co). Within 2 h of RI, animals were bled under anesthesia 0% (RI) or 20% (CI) of total blood volume. Blood samples were collected at 4-5 h and days 1, 2, 3, 7, and 15 after RI. CI decreased WBC at 4-5 h and continued to decrease them until day 3; counts then stayed at the nadir up to day 15. CI decreased neutrophils, lymphocytes, monocytes, eosinophils and basophils more than RI on day 1 or day 2. CI decreased RBCs, hemoglobin and hematocrit on days 7 and 15 compared to RI, whereas Hemorrhage alone returned to the baseline on days 7 and 15. RBCs depleted after CI faster than post RI. Hemorrhage alone increased platelet counts on days 2, 3, and 7, which returned to the baseline on day 15. Our data suggest that WBC depletion may be a biomarker within 2 days post-CI and RBC depletion after 3 days post-CI.

The elasticity of red blood cells (RBCs) is crucial for their ability to fulfill their role in the blood. Decreased RBC deformability is associated with various pathological conditions. This study explores the application of machine learning to predict the elasticity of RBCs using both image data and detailed physical measurements derived from simulations. We simulated RBC behavior in a microfluidic channel. The simulation results provided the basis for generating data on which we applied machine learning techniques. We analyzed the surface-area-to-volume ratio of RBCs as an indicator of elasticity, employing statistical methods to differentiate between healthy and diseased RBCs. The Kolmogorov–Smirnov test confirmed significant differences between healthy and diseased RBCs, though distinctions among different types of diseased RBCs were less clear. We used decision tree models, including random forests and gradient boosting, to classify RBC elasticity based on predictors derived from simulation data. The comparison of the results with our previous work on deep neural networks shows improved classification accuracy in some scenarios. The study highlights the potential of machine learning to automate and enhance the analysis of RBC elasticity, with implications for clinical diagnostics.

Background: The effect of velamentous cord insertion (VCI) on perinatal outcomes in twin pregnancies is unclear due to conflicting findings. This retrospective study aimed to examine VCI prevalence and related risk factors in twin pregnancies and its association with adverse perinatal outcomes. Methods: Women with twin pregnancies who delivered between January 2012 and December 2021 in a single tertiary hospital were included. The participants were divided into dichorionic (DC) and monochorionic diamniotic (MCDA) groups, and their maternal and fetal characteristics and VCI rates were compared. Logistic regression models were used to identify risk factors for VCI and VCI-related perinatal outcomes. Results: Among the 694 twin pregnancies included in this study, the VCI rate was significantly higher in MCDA than in DC twins. Body mass index and MCDA twins were significant risk factors for VCI, whereas assisted reproductive technology pregnancy was a significant protective factor against VCI. In DC twins, VCI did not affect perinatal outcomes. Conclusion: In MCDA twins, VCI was a significant risk factor for fetal growth restriction, twin-to-twin transfusion syndrome, and preterm birth at

Rheumatoid arthritis (RA) is a chronic autoimmune disease associated with a significantly increased risk of cardiovascular mortality, mainly attributed to accelerated atherosclerosis. Methods: Thirty-two women (aged more than 18 years) with RA, and 25 age-matched healthy women were included in this study. Biomarkers of inflammation, red blood cells (RBCs) redox balance, estrogen receptor alpha (ER-α) expression as well as ERK 1/2 phosphorylation content were evaluated in RA patients at baseline and six months after treatment with disease modifying anti‐rheumatic drugs (DMARDs). Results: For the first times we demonstrated that in RA patients: i) disease activity score (DAS-28) positively correlated with RBC ER-α expression, and negatively with total antioxidant capacity of plasma; ii) RBC ER-α expression positively correlated with systemic inflammatory biomarkers and oxidative stress parameters as well as ERK 1/2 phosphorylation; and iii) DMARDs treatments improved the clinical condition measured by DAS-28 score decrease, although the RBCs appeared to be more prone to pro-oxidant status associated to the expression of survival molecules. Conclusion: Our data strongly suggest that RBCs could also participate in vascular homeostasis through fine modulation of an intracellular signal linked to the ER-α.

Background/Objectives: Women with subclinical hypothyroidism (SCH) were reported to be at an increased perinatal risk. We aimed to investigate the relationship between SCH and perinatal outcomes in singleton pregnancies resulting from assisted reproduction technology (ART). Methods: We retrospectively examined the perinatal outcomes of ART singleton pregnancies in women who underwent thyroid function screening before conception and delivered at our hospital from January 2020 to July 2023. We defined SCH as thyroid-stimulating hormone (TSH) levels <2.5 mU/L and normal free T₄ levels. The patients were divided into three groups: normal thyroid function (group A), SCH without levothyroxine therapy (group B), and SCH with levothyroxine therapy (group C). The risks of preterm birth, preeclampsia, fetal growth restriction, manual placental removal, and blood loss at delivery were compared among the three groups. Results: Out of the 650 ART singleton deliveries, 581 were placed in group A, 34 in group B, and 35 in group C. The preterm birth rate at <34 weeks was significantly higher in group B and significantly lower in group C than in group A. The rate of preterm delivery at <34 weeks increased in correlation with TSH levels. Levothyroxine therapy was the significant preventive factor for preterm birth at <34 weeks. Conclusions: The preterm birth rate before 34 weeks was significantly higher in the SCH group. Levothyroxine therapy is a significant protective factor against preterm birth before 34 weeks. Universal screening for thyroid function and appropriate hormone therapy in pregnant women may help reduce perinatal risks, including preterm birth.

Hemangioblasts give rise to endothelial progenitor cells (EPCs), which also express the cell surface markers CD133 and C-kit. They may differentiate into the outgrowth endothelial cells (OECs) that control neovascularization in the developing embryo. Reduced levels of EPC in circulation have been linked to human cardiovascular disorders, according to numerous studies. Furthermore, preeclampsia and senescence have been linked to levels of EPCs produced from cord blood. Uncertainties surround how preeclampsia affects the way EPCs function. It is reasonable to speculate that preeclampsia may have an impact on the function of fetal EPCs during the in utero period; however, given the present literature's suggestion that maternal vasculopathies, including preeclampsia, damage fetal circulation. Additionally, the differentiation potential and general activity of EPCs may serve as an indicator of the health of the fetal vascular system since they promote neovascularization and repair during pregnancy. Thus, the purpose of this review is to compare, through assessment of their quantity, differentiation potency, angiogenic activity, and senescence, the angiogenic function of fetal EPCs obtained from cord blood for normal and pregnancy problems. This will shed light on the relationship between the angiogenic function of fetal EPCs and pregnancy complications, which could have an effect on the management of long-term health issues like metabolic and cardiovascular disorders in offspring with abnormal vasculature development.

Background Community infections of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have increased rapidly since the emergence of the Omicron strain. During the eighth and ninth pandemic waves—when movement restrictions in the community were eased—the all-case registration system was changed, and the actual status of infection became uncertain. Methods We conducted regular rapid antigen tests (R-RAT) once or twice a week to examine the actual state of coronavirus disease (COVID-19) diagnosis among healthcare employees. Results Overall, 320 (1.42/day) and 299 (1.76/day) employees were infected in the eighth and ninth pandemic waves. During both periods, 59/263 doctors (22.4%), 335/806 nurses (41.6%), 92/194 administrative employees (47.4%), and 129/218 clinical laboratory technicians (59.2%) were infected. In the eighth wave, 56 of 195 employees were infected through close contact; in the ninth wave, 26 of 62 employees were infected. No significant difference was observed in the number of vaccinations between infected and non-infected employees. The positivity rate of R-RAT was 0.41% and 0.45% in the eighth and ninth waves. R-RAT detected infection in 212 and 229 employees during the eighth and ninth waves, respectively; the ratio of R-RAT-detected positive employees to those who reported infection was significantly higher during the ninth wave (odds ratio: 1.67, 95% confidence interval: 1.17–2.37, p

Cerebral cavernous malformations (CCM) or familial cavernomatosis is a rare, autosomal dominant, inherited disease characterized by the presence of vascular malformations consisting of blood vessels with an abnormal structure in the form of clusters. Based on the altered gene (CCM1/Krit1, CCM2, CCM3) and its origin (spontaneous or familial), different types of this dis-ease can be found. In this work we have isolated and cultivated primary endothelial cells (ECs) from peripheral blood of a type 1 CCM patient. Differential functional and gene expression pro-file of these cells were analyzed and compared to primary ECs from a healthy donor. The muta-tion of the familial index case consisted of a heterozygous point mutation in the position +1 splicing consensus between exons 15 and 16, causing failure in RNA processing and in the final protein. Furthermore, gene expression analysis by quantitative PCR revealed a decreased ex-pression of genes involved in intercellular junction formation, angiogenesis, and vascular ho-meostasis. Cell biology analysis showed that CCM1 ECs were impaired in angiogenesis and cell migration. Taken together, the results obtained suggest that the alterations found in CCM1 ECs are already present in the heterozygous condition, suffering from vascular impairment and someway predisposed to vascular damage.

Clinically, knowing the number of red blood cells (RBCs) and white blood cells (WBCs) helps doctors to make the better decision on accurate diagnosis of numerous diseases. The manual cell counting is a very time-consuming and expensive process, and it depends on the experience of specialists. Therefore, a completely automatic method supporting cell counting is a viable solution for clinical laboratories. This paper proposes a novel blood cell counting procedure to address this challenge. The proposed method adopts SegNet - a deep learning semantic segmentation to simultaneously segment RBCs and WBCs. The global accuracy of the segmentation of WBCs, RBCs, and the background of peripheral blood smear images obtains 89% when segment WBCs and RBCs from the background of blood smear images. Moreover, an effective solution to separate grouped or overlapping cells and cell count is presented using Euclidean distance transform, local maxima, and connected component labeling. The counting result of the proposed procedure achieves an accuracy of 93.3% for red blood cell count using dataset 1 and 97.38% for white blood cell count using dataset 2.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a single stranded RNA virus which has resulted in the Coronavirus Disease 2019 (COVID-19) pandemic and has infected millions of people all over the world. SARS-CoV-2 has been mutating rapidly resulting in the emergence of multiple variants to escape the host immune system mainly by mutations in its receptor binding domain (RBD) of the spike protein. This rapid evolution of the SARS-CoV-2 posed a great challenge regarding the efficacy and effectiveness of the current SARS-CoV-2 vaccines. The RBD and full-length spike of SARS-CoV-2 is the main target of the neutralizing antibodies. Many SARS-CoV-2 variants are considered to have the potential to escape from the host immune system. In this study, the RBD of Alpha, Beta, Gamma, Kappa and Omicron and the full-length spike of BA.1, BA.2, BA.3, BA.4/5, BQ.1.1 and XBB.1.5 Omicron variants were used as coating antigens in Enzyme Linked Immuno-Sorbent Assay (ELISA) to check the neutralization capability of COVID-19 convalescent sera from patients of first wave of infection occurring in Wuhan. Our results show that the currently circulating Omicron BQ.1.1, XBB.1.5 and previous Omicron BA.1, BA.2 and BA.4/5 do not show significant reduction in neutralization, while Omicron BA.3 and previous variants Alpha, Beta, Gamma, Kappa, and Omicron showed a significantly reduced neutralization when compared to the wild-type Wuhan strain. These results indicate patients recovering from natural infection of early original Wuhan strain may have the potential to resist infection of current circulating variants and the vaccines using the prototype antigen may still working for newly emerged variants.

Circulating extracellular microvesicles (cEVs) are characterised by presenting surface antigens of parental cells. Since their biogenesis involves the translocation of phosphatidylserine (PS) from the inner to the outer-leaflet of the plasma membrane, exposed PS has been considered as a recognition hallmark of cEVs. However, not all cEVs externalise PS. In this study we have phenotypically and quantitatively characterised cEVs by flow cytometry with special attention to the proportions of PS in chronic heart failure patients (cHF; n=119) and reference non-HF group (n=21). PS─-cEVs were predominantly found in both groups. Parental markers showed differential pattern depending on PS exposure. Endothelium-derived and connexin 43-rich cEVs were mainly PS─-cEVs and significantly increased in cHF. On the contrary, platelet-derived cEVs were mostly PS+ and were increased in non-HF. We observed similar levels of PS+- and PS─-cEVs in non-HF subjects when analysing immune cell-derived EVs, but there was a subset-specific difference in cHF patients. Indeed, those cEVs carrying CD45+, CD29+, CD11b+ and CD15+ were mainly PS+-cEVs, while those carrying CD14+, CD3+ and CD56+ were mainly PS─-cEVs. In conclusion, endothelial and red blood cells are stressed in cHF patients as detected by a high shedding of cEVs. Despite PS+-cEVs and PS─-cEVs represent two distinct cEV populations, their release and potential function as both biomarkers and shuttles for cell communication seem unrelated to PS content.

The antibodies targeting invasive proteins of Plasmodium falciparum (Pf) merozoites is a clever strategy against malaria parasite. The recent finding that Plasmodium merozoites surface enolase is a target for growth neutralizing antibodies has generated interest in identifying its re-ceptor (s) on erythrocytes. In the present study, several biochemical experiments were undertaken involving recombinant Pf enolase and antibody against it to search for its cognate receptor. The binding of rPfeno to erythrocytes was selectively sensitive to trypsin but resistant to neuramini-dase. Failure of yeast enolase binding to human red blood cells under similar conditions indicat-ed high specificity of parasite Pfeno. The mass spectrometric and immunological analyses of pro-teins obtained in pull downs and co-immunoprecipitation samples led to identification of band 3 as an interactor/receptor for Plasmodium enolase. Structural characterization of sequences of band 3 - rPfeno interacting regions revealed C-terminal exocytic regions of band 3 to be binding to Pfeno. Similarly, band 3 binding regions of rPfeno were also identified. Identification of receptor-ligand (band 3: Pfeno) pair paves the way for antimalarial anti-Pf enolase-based vaccine, anti-Pf enolase antibodies as drug and also for developing novel small molecule-based invasion inhibi-tory therapeutics including peptidomimetics that could disrupt the band 3: Pfeno protein-protein interactions.

Severe COVID-19 alters the biochemical and morphological characteristics of blood cells in a wide variety of ways. To date, however, the vast majority of research has been devoted to the study of leukocytes, while erythrocyte morphological changes have received significantly less attention. The purpose of this research was to identify erythrocyte types that were unique to COVID-19, compare the number of different poikilocyte types, and measure erythrocyte sizes to provide data on size dispersion. Red blood cells obtained from 6 control donors (800-2200 cells for each donor) and 5 COVID-19 patients (800-1900 cells for each patient) were examined using low voltage scanning electron microscopy. We did not discover any forms of poikilocytes that would be unique to COVID-19. Among COVID-19 patients, we observed an increase in the number of acanthocytes (p=0.01) and a decrease in the number of spherocytes (p=0.03). In addition, our research demonstrates that COVID-19 causes an increase in the median (p=0.004) and interquartile range (p=0.009) when assessing erythrocyte size.

Clustered regularly interspaced short palindromic repeats (CRISPR) based gene-editing has begun to transform the treatment landscape of genetic diseases. The history of the discovery of CRISPR/CRISPR-associated (Cas) proteins/single guide RNA (sgRNA)-based gene-editing since the first report of repetitive sequences of unknown significance in 1987 is fascinating, instructive, and inspiring for future advances. The recent approval of CRISPR-Cas9-based gene therapy to treat patients with severe sickle cell anemia and transfusion-dependent beta thalassemia has renewed hope for treating other hematologic diseases, including patients with germline predisposition to hematologic malignancies, who would benefit greatly from the development of CRISPR-based gene therapies. The purpose of this manuscript is three-fold: first, a chronological description of the history of CRISPR-Cas9-sgRNA-based gene editing; second, a brief description of the current state of clinical research in hematologic diseases, including selected applications in treating hematologic diseases with CRISPR-based gene therapy; and third, the current progress in gene therapies in inherited hematologic diseases and bone marrow failure syndromes, to hopefully stimulate efforts towards developing these therapies for patients with inherited bone marrow failure syndromes and other inherited conditions with germline predisposition to hematologic malignancies.

Blood image intensity has been used to detect erythrocyte sedimentation rate (ESR). However, it does not give an information on biophysical properties of blood sample under continuous ESR. In this study, three physical properties, including, τ₀, ESR_τ, and AI_I, are suggested to quantify mechanical variations of blood under continuous ESR. To demonstrate the proposed method, blood sample is loaded into a driving syringe. The blood flow rate is set in a periodic on–off pattern. Blood sample is then supplied into a capillary chip, and microscopic blood images are captured at specific intervals. Blood shear stress is quantified from the interface of blood stream in the coflowing channel. Both τ₀ and ESR_τ are then obtained by analyzing the blood shear stress. Simultaneously, the AI_I is evaluated by analyzing the image intensity of blood flow. According to the experimental results, the τ₀ exhibits consistent trends with respect to hematocrit as well as diluent. The ESR_τ and AI_I showed a reciprocal relationship each other. Three suggested properties represented substantial differences for suspended blood samples (i.e., hardened red blood cells, different concentration of dextran solution and fibrinogen). In conclusion, the present method can detect variations of blood sample under continuous ESR effectively.

Diabetes mellitus (DM) is the most common metabolic disease in humans, and its prevalence is increasing worldwide in parallel with the obesity pandemic. A lack of insulin or insulin resistance, and consequently hyperglycemia, leads to many systemic disorders, among which diabetic encephalopathy (DE) is a long-term complication of the central nervous system (CNS), characterized by cognitive impairment and motor dysfunctions. The role of oxidative stress and neuroinflammation in the pathomechanism of DE has been proven. Fractalkine (CX3CL1) has unique properties as an adhesion molecule and chemoattractant, and by acting on its only receptor, CX3CR1, it regulates the activity of microglia in physiological states and neuroinflammation. Depending on the clinical context, CX3CL1-CX3CR1 signaling may have neuroprotective effects by inhibiting the inflammatory process in microglia or, conversely, maintaining/intensifying inflammation and neurotoxicity. This review discusses the evidence supporting that the CX3CL1-CX3CR1 pair is neuroprotective and other evidence that it is neurotoxic. Interrupting the vicious cycle within neuron-microglia interactions may be a therapeutic goal in DE by limiting the inflammatory response.

Elizabethkingia anophelis is an opportunistic pathogen causing lifethreatening infections in humans, particularly in immunocompromised patients, neonates and elderly. Infections caused by this species are exceptionally challenging to treat due to its multiresistance to antimicrobials. We report a case of central line-associated bloodstream infection by E. anophelis in a 2.5-year-old girl with acute lymphoblastic leukemia successfully treated with a combination of piperacillin/tazobactam and amikacin. The literature was also reviewed on paediatric infections caused by E. anophelis. Accurate identification with MALDI-TOF, or using molecular techniques, is crucial because of varying susceptibilities among species. Early, accurate diagnosis and prompt effective treatment optimize outcomes.

Autoimmune hemolytic anemias (AIHAs) are conditions whereby a person produces an antibody to their own red blood cells (RBCs). These conditions can be primary with unknown cause or secondary, associated with diseases or infections. There are seven different categories of AIHA, warm-antibody AIHA (wAIHA); cold-antibody AIHA that includes cold agglutinin syndrome (CAS) and cold agglutin disease (CAD); mixed AIHA, also called combined cold and warm AIHA; paroxysmal cold hemoglobinuria (PCH) also termed Donath-Lansteiner test-positive AIHA; direct antiglobulin test-negative AIHA (DAT-neg AIHA); drug-induced immune hemolytic anemia (DIIHA); and passenger lymphocyte syndrome. This review will discuss each of these AIHAs and provide information on diagnosis and treatment.

This study aimed to investigate the potential of Cord Blood Stem Cell-derived exosome vesicles (CBSC-EVs) in regulating cancer growth and preventing cellular damage. The study aimed to examine the effects of CBSC-EVs on CHL1 cancer cells and healthy fibroblasts. The study results reveal that CBSC-EVs have an anti-cancer/antioxidant effect on CHL1 cancer cells without inducing any toxic effects on healthy lymphocytes. Further analysis of CBSC-EVs revealed the presence of seven miRNAs (noncoding RNA molecules), including three from the Let 7 family, two from the Let 5 family, and two novel miRNAs. The function of the novel miRNAs was the main focus of the study. To assess the efficacy of CBSC-EVs, CHL1 cells (a type of malignant melanoma cell line) and human fibroblasts were grouped into different treatments. One group of those cell lines were treated with CBSC-EVs, and in the second group, the cells were transfected with either miRNA inhibitor Novel 1 (miRNA IN1) plus CBSC-EVs or miRNA inhibitor Novel 2 (miRNA IN2) and CBSC-EVs to knock down those novel miRNAs in the CBSC-EVs. Therefore, by comparing these groups, the function of novel miRNAs is more understandable. In this study, the Comet assay was employed to evaluate cancer cells' DNA damage and CCK8 to measure cell viability. The findings revealed that CBSC-EVs caused an increase in DNA damage in CHL1 cells compared to cells without treatment (p

Human induced pluripotent stem cell (iPSC)-based model systems can be used to produce blood cells for the study of both hematologic and non-hematologic disorders. This commentary discusses recent advances that have utilized iPSC-derived red blood cells, megakaryocytes, myeloid cells, and lymphoid cells to model hematopoietic disorders. In addition, we review recent studies that have defined how microglial cells differentiated from iPSC-derived monocytes impact neurodegenerative disease. Related translational insights highlight the utility of iPSC models for studying pathologic anemia, bleeding, thrombosis, autoimmunity, immunodeficiency, blood cancers, and neurodegenerative disease such as Alzheimer’s.

Galectins are a family of beta-galactoside-binding proteins that are characterised by their carbohydrate recognition domain (CRD) and include galectin-1 and galectin-3. These galectins have been implicated in numerous diseases due to their pleiotropic nature, including cancer and fibrosis, with therapeutic inhibitors being clinically developed to block the CRD. One of the early methods developed to characterise these galectins was hemagglutination of red blood cells. Although insightful this approach has been hampered by a lack of sensitivity and accurate quantification of the agglutination observed. In this study we aimed to validate a more precise and quantitative method to enable further investigation of differences between galectins in respect to agglutination induction in different blood groups as well as characterisation of small molecule inhibitors. Quantification of hemagglutination was shown to be optimal using U-bottom plates imaged and analysed with FIJI ImageJ rather than flat bottom plates read for absorbance on an optical density plate reader. Galectin-3-induced red blood cell agglutination efficacy increased significantly from blood group O to A to B. However, for both the galectin-1 monomer and concatemer a more comparable effect was observed between blood group B and O but with more potent effects than in blood group A. Inhibition assays for both galectin-3 and galectin-1 induced-hemagglutination were able to demonstrate clear concentration-responses and expected selectivity profiles for a set of small molecule glycomimetics, confirming historical profiles obtained in biochemical binding and functional cellular assays.

The aim of our study was to describe our experience using a Spectra Optia® automated apheresis system in children with sickle cell disease (SCD). We used automated red blood cell exchange (RCE) to treat acute and chronic complications in 75 children with SCD who had a median age of 10 years [7-13]. We analysed 649 exchange sessions. Peripheral venous access was limited in a number of the children, thus requiring a femoral central double‐lumen venous catheter (CVC). We recommend the use of heparin locking, with 500 units in each lumen of a CVC. This method was well tolerated, with few complications during the procedures. For preoperative prevention, all of the patients had achieved a post-RCE HbS level of <30% since this is a mandatory condition imposed by the anaesthesiologist. With a post-RCE Hb level of approximately 10-11 g/dL, a blood exchange volume of ≥32 mL/kg, and an interval between each RCE procedure of ≤30 days, it was able to maintain the residual HbS level below 30%. Despite a target pre‐exchange HbS level of 47%, we did not encounter a single stroke recurrence. Erythrocytapheresis is useful and safe for children with SCD.

Acai (Euterpe oleracea Mart. Palmae, Arecaceae) is a palm plant native to the Brazilian Amazon. It contains many nutrients, such as polyphenols, iron, vitamin E, and unsaturated fatty acids, so in recent years, many of the antioxidant and anti-inflammatory effects of acai have been reported. However, the effects of acai on hematopoiesis have not been investigated yet. In the present study, we administered acai extract to mice and evaluated its hematopoietic effects. Acai treatment significantly increased the erythrocytes, hemoglobin, and hematocrit contents compared to controls for four days. We then examined the hematopoietic-related markers following a single injection. Acai administration significantly increased the levels of the hematopoietic-related hormone erythropoietin in blood compared to controls and also significantly upregulated the gene expression of Epo in the kidney. Furthermore, in the mice treated with acai extract, the kidneys were positively stained with the hypoxic probe pimonidazole in comparison to the controls. These results demonstrated that acai increases the number of blood cells through an increased erythropoietin expression via hypoxic action in the kidney. Acai can be expected to improve motility through hematopoiesis.

Attention mechanisms have become a fundamental component of deep learning, including the field of computer vision. The key idea behind attention in computer vision is to help the model focus on the relevant spatial regions of the input image, rather than treating all regions equally. The traditional approaches to attention mechanisms in computer vision often suffer from distribution inconsistencies in the attention maps, resulting in sharp transitions that negatively affect model’s focus and lead to poor generalization on complex shapes. The problem of spatial incoherence is particularly pronounced in the task of semantic segmentation, where accurate pixel-level predictions require a detailed understanding of the spatial relationships within the image. In this paper, we propose an attention mechanism called Smooth Attention designed for convolutional neural networks to address the problem of spatial inconsistency in attention maps through multidimensional spatial smoothing. We conduct a series of experiments to evaluate the effectiveness of the proposed mechanism and demonstrate its superior performance compared to traditional methods.

The study aimed to showcase how implementing a patient blood management (PBM) program effectively cut unnecessary red blood cell (RBC) transfusions in a New York City urban community teaching hospital. Analyzing seven years from 2013 to 2019, a retrospective review of RBC transfusions was conducted. Following PBM introduction, considerable improvements were observed annually. These included a drop in mean pretransfusion hemoglobin levels from 7.26g/dL (2013) to 6.58g/dL (2019), a 34% reduction in yearly RBC unit transfusions, and fewer units given to patients with pre-Hgb levels ≥7g/dL (1210 units in 2013 to 310 units in 2019). Furthermore, the study noted a decline in two-unit RBC orders when Hgb levels were ≥7g/dL from 65 orders in 2013 to merely 3 in 2019. The estimated total cost-savings attributed to the six-year PBM program duration after full implementation in 2014 amounted to $2.1 million US dollars. Overall, PBM implementation significantly decreased RBC transfusions and enhanced transfusion practices. The findings emphasize that successful PBM strategies don't always necessitate extensive resources or increased budgets but instead rely on the application of intuitive methods, as evidenced by this study.

Xyleborus beetles, a diverse group of ambrosia beetles, present significant challenges to forestry and agriculture due to their damaging burrowing behavior and symbiotic relationships with fungi. This review synthesizes current knowledge on the biology, ecology, and management of Xyleborus. We explore the beetles' life cycle, reproductive strategies, habitat preferences, and feeding habits, emphasizing their ecological and economic impacts. Control and management strategies, including preventive measures, chemical and biological control, and integrated pest management (IPM), are critically evaluated. Recent advances in molecular genetics and behavioral studies offer insights into genetic diversity, population structure, and host selection mechanisms. Despite progress, managing Xyleborus effectively remains challenging. This review identifies future research needs and highlights innovative control methods, such as biopesticides and pheromone-based trapping systems.

Aiming at the problems of inaccurate segmentation of long object and information loss of small object in real-time semantic segmentation algorithm, this paper proposes a lightweight multi-branch real-time semantic segmentation network based on BiseNetV2. The new auxiliary branch makes full use of spatial details and context information to cover the long object in the field of view. Meanwhile, in order to ensure the inference speed of the model, the asymmetric convolution is used in each stage of the auxiliary branch to design a structure with low computational complexity. In the multi-branch fusion stage, the alignment and fusion module is designed to provide guidance information for deep and shallow feature mapping, so as to make up for the problem of feature misalignment in the fusion of information at different scales, and thus reduce the loss of small target information. In order to further improve the model’s awareness of key information, a global context module is designed to capture the most important features in the input data. The proposed network uses NVIDIA GeForce RTX 3080 Laptop GPU experiment, on the road street view data set Cityscapes and CamVid average occurring simultaneously ratio reached 77.1% and 78.4% respectively, with running speed of 127 frames/s respectively and 112 frames/s. The experimental results show that the proposed algorithm can achieve real-time segmentation and improve the accuracy significantly, showing good semantic segmentation performance

. Background: regular exercise elicits adaptive changes from several organs and physiological processes, including erythrocyte properties. Methods: in a group of 79 subjects (62 men and 17 women; mean age 31.37 +/- 10.19 years) who trained several times a week as they practiced amateur sports, we evaluated the elongation index, marker of erythrocyte deformability, the red blood cell distribution width (RDW), indicator of erythrocyte anisocytosis, hematocrit, hemoglobin and the main erythrocyte indices (MCV, MCH, MCHC) in basal conditions. Results: in comparison with a group of healthy not trained volunteers, the values of the elongation index, and not the RDW, are increased and this datum is accompanied by an increase of MCV and MCHC, likely related to an increased presence of circulating young erythrocytes in trained subjects. We also divided the same group according to the median of the VO2max, observing that the subgroup above the median shows both an increase in the elongation index values and a decrease in MCH and MCHC. Conclusions: in trained subjects there is no correlation between the values of elongation index and the RDW, while of particular interest and of a certain complexity seem the interrelations among elongation index, RDW and the main erythrocyte indices.

Open-vocabulary learning has recently gained prominence as a means to enable image segmentation for arbitrary categories based on textual descriptions. This advancement has extended the applicability of segmentation systems to a broader range of generally purpose scenarios. However, current methods often revolve around specialized architectures and parameters tailored to specific segmentation tasks, resulting in a fragmented landscape of segmentation models. In response to these challenges, we introduce OVAMTSeg, a versatile framework designed for Open-Vocabulary and Multitask Image Segmentation. OVAMTSeg harnesses adaptive prompt learning to empower the model to capture category-sensitive concepts, enhancing its robustness across diverse multi-task and scenario contexts. Text prompts are employed to effectively capture semantic and contextual features of the text, while cross-attention and cross-modal interactions enable the fusion of image and text features. Furthermore, a transformer-based decoder is incorporated for dense prediction. Extensive experimental results underscore the effectiveness of OVAMTSeg, showcasing its state-of-the-art performance and superior generalization capabilities across three segmentation tasks. Notable achievements include a 47.5 mIoU in referring expression segmentation, 51.6 mIoU on Pascal-VOC with four unseen classes, 46.6 mIoU on Pascal-Context in zero-shot segmentation, 65.9 mIoU on Pascal-5i, and 35.7 mIoU on COCO-20i datasets for one-shot segmentation.

Blood cell analysis is a crucial diagnostic process in medical practice. In particular, detecting white blood cells (WBCs) is essential for diagnosing of many diseases. The manual screening of blood films is a time-consuming and subjective process, which can lead to inconsistencies and errors. Therefore, automated detection of blood cells can improve the accuracy and efficiency of the screening process. In this study, an explainable Vision Transformer (ViT) model was proposed for the automatic detection of WBCs from blood films. The proposed model utilizes the self-attention mechanism to extract relevant features from the input images and leverages transfer learning by incorporating pre-trained model weights to improve its performance. The proposed model achieved a classification accuracy of 99.40% for five distinct types of WBCs and exhibited potential in reducing the time required for manual screening of blood films by pathologists. Upon examination of the misclassified test samples, it was observed that incorrect predictions were correlated with the presence or absence of granules in the cell samples. To validate this observation, the dataset was divided into two classes, namely Granulocytes and Agranulocytes, and a secondary training process was conducted. The resulting ViT model trained for binary classification achieved an accuracy of 99.70%, recall of 99.54%, precision of 99.32%, and F-1 score of 99.43% during the test phase. To ensure the reliability of the ViT model's multi-class classification of WBCs, the pixel areas that the model focuses on in its predictions are visualized through the Score-CAM algorithm.

Cardiotonic steroids (CTS) are a group of steroid compounds derived from certain plants and animals. CTS are selective inhibitors of Na,K-ATPase, so for a long time they were widely used for medical purposes to treat heart failure and some other diseases. However, over time, doctors gradually began to refuse this group of drugs due to their narrow therapeutic range and a number of serious side effects. However, in parallel with the rise and fall of interest in CTS as a drug, interest in them as a single class of high-affinity Na,K-ATPase inhibitors has only increased. Numerous data on the effect of CTS on signaling cascades and cell viability made impelling a search for a rationale for the existence of such a subtle biological regulator. A large number of studies devoted to the potential use of CTS in the treatment of neurodegenerative, oncological, immune and other diseases "revitalized" the already "written off" group of the drugs. If initially the role of exogenous (mainly plant origin) CTS was studied, then by the 90s of the XX century the study of the role of endogenous CTS and their regulatory effects became a popular trend in biology and physiology. The role of endogenous CTS was studied in details in the pathogenesis of cardiovascular diseases [1]. A large number of researchers have unanimously stated that endogenous CTS are very complex regulators of the development of pathological processes; however, the exact cause-and-effect relationship that would unambiguously explain the processes of synthesis, utilization, and the role of endogenous CTS has not yet been established. The effects of CTS in the frame of various regulatory schemes have been described, but the predominant number of studies was devoted to arterial hypertension, heart and renal failure, cancer [2–4], aging [5,6], and neuroinflammation. The effects of both endo- and exogenous CTS on blood cells and have been studied to a much lesser extent.

Background: Several kinds of research say that adjuvant blood glucose and blood pressure are usual, but an efficient solution for medical application count remains. This review analyzes the pandemic blood pressure and blood glucose to identify the publications which tell about the clinical practices and research gaps in systematic research.Methods: A study guides to identify the research of Blood Pressure (BP) and Blood Glucose. In order to analyze the recent innovations and research on BP and Blood glucose, the relevant publications and literature from journals were identified.Results: Co-morbidity of BP and Blood glucose is reported as very high. The commonness of blood pressure is thrice as high in type I diabetes patients and almost two times higher in type II diabetes patients when compared to others without Diabetes. The pervasiveness of getting depression is more in the female when compared with men. A detailed study about the linkage of BP and blood glucose tells that the relationship between them is not exactly clear.Limitations: Nearly all reviews providing the linkage of BP and blood glucose are with some limitations and they are not providing any clear conclusion.Conclusions: Present research tells that people having high blood glucose will have a greater chance of getting high blood pressure. More research is needed to state the linkage between BP, blood glucose, and the growth of diabetes mellitus issues and to provide support for managing Diabetes.

The expression of non-coding RNAs varies greatly depending on the cell type and physiological state. Changes in expression affect the regulatory properties of these molecules. We investigated RNA-seq data from sorted blood cells of healthy control donors and severe COVID-19 patients. Our aim was to display a distinguishable piRNA differential expression portrait for each type of cell and to study the behavior of piRNA in the blood cells of COVID-19 patients. Overall piRNA expression in sorted control cells (erythrocytes, monocytes, lymphocytes, eosinophils, basophils, neutrophils) differs depending on cell type. Four of the most abundant piRNA were expressed relatively equally in all cell types, they included piR-49145, piR-49144, piR-49143 and piR-33151. By reviewing piRNA expression in each group of sorted cells from severe COVID-19 patients we observed 3 upregulated and 10 downregulated piRNAs in erythrocytes. Monocytes were presented with a larger amount of statistically significant piRNA, 4 upregulated and 35 downregulated. In lymphocytes, all 19 piRNAs were upregulated.

Despite decades of conflict and political instability, drought has also severely affected Afghanistan’s rural population and agriculture sector. Agriculture is a primary livelihood source in the country, and recurring droughts have put cascading pressures on the agricultural economy and food security. Therefore, understanding the key drivers of all risk components through a comprehensive risk assessment is critical for proactive drought risk management. This study assesses agricultural drought risk from an integrated perspective, emphasizing the combined effects of drought hazard, exposure, and vulnerability. Multi-methods research was conducted, employing remote-sensing-based analysis covering a period from 2001 to 2023. We used the Vegetation Condition Index (VCI) to analyze the drought hazard for the agricultural system during the winter growing season. The vulnerability indicators and exposure levels of the agricultural system were determined through spatial analysis combined with a literature review and expert consultation. An adapted conceptual framework of the Intergovernmental Panel on Climate Change (IPCC) was utilized, which incorporates hazard, exposure, and vulnerability to define risk. The results revealed that droughts occur frequently and in changing patterns throughout the country. All provinces have experienced drought over the past two decades, albeit with varying severities and frequencies. Severe droughts were observed in 2001-2002, 2008, 2011, 2018, and consecutively in 2021-2022-2023. Drought vulnerability and exposure vary widely across the country, particularly in the northern, western, and southern provinces. The final calculated risk shows that most provinces in southern and southwestern zones face a high risk of recurrent droughts, further exacerbating agricultural challenges in these regions. Such analyses under a multimethod approach provide information on spatial patterns of drought risk and drivers of agricultural systems that can support decision-makers and policymakers in formulating strategies to reduce drought risk and adapt to the agricultural sector.

Glaucoma is one of the primary causes of blindness worldwide. Canal opening surgery, a type of minimally invasive glaucoma surgery (MIGS) applied in cases of mild to moderate glaucoma, has gained increasing popularity in recent years due to its efficacy in reducing intraocular pressure, its safety profile, the simplicity of its technique, and the reduced likelihood of compromised vision. Nevertheless, the existing body of histopathological studies remains insufficient for a comprehensive understanding of post-surgical wound healing. Consequently, debates persist among researchers regarding the mechanism through which Schlemm’s canal opening surgery reduces intraocular pressure, as well as the surgical techniques that may impact the outcomes and the factors influencing surgical success. As the history of MIGS is relatively short and lacks sufficient systemic reviews or meta-analysis evaluating the influence of individual factors, this review was conducted to illuminate disparities in the researchers’ opinions at the current stage of research.

Pulmonary Embolism (PE) is the obstruction of blood arteries in the lungs by a blood clot. The mortality risk for PE is approximately 30%. Detecting pulmonary embolism in the segmental arteries of the lung is more challenging than in the main arteries and is very prone to being missed. A computer-based approach was created in this work to automatically identify pulmonary embolism in the segmental arteries using computed tomography images. The system's infrastructure includes an enhanced Mask R-CNN deep neural network that has been trained with images containing PE. The network accurately identifies the location of the pulmonary embolism on the computed tomography picture and successfully extracts its borders. The investigation was conducted by generating a local dataset. The study's performance was evaluated using pulmonary embolisms identified manually by the expert radiologist. The sensitivity, specificity, accuracy, dice coefficient, and Jaccard index values for 2130 pictures were 96.4%, 93.5%, 96.1%, 0.96, and 0.90, respectively. The improved Mask R-CNN model has demonstrated superior performance when compared to the traditional Mask R-CNN and U-Net models. This high-performance technology is designed to identify pulmonary embolism and will aid professionals in assessing the size of the embolism.

Background: Acute pancreatitis is a common emergency. Morbidity control requires early detection of disease severity. METHODS: A total of 131 AP patients were analyzed retrospectively. Patients were divided into two groups mild AP (MAP: Ranson score <3) and severe AP (SAP: Ranson score ≥3), according to Ranson’s criteria. Demographic data, hospitalization duration, PNI, CRP, and RDW levels were compared. Any p-value below 0.05 (p<0.05) was accepted as statistically significant. RESULTS: Study included 67 (51.15%) males and 64 (48.85%) females. The age average was 59.74 (19-90) years. 95 (72.52%) patients had MAP, and 36 (27.48%) patients had SAP. Mean hospitalization time, PNI, and CRP differed significantly between the two groups (p=0.010, p<0.05, p<0.05, respectively). The RDW (p=0.380) level difference was insignificant. For SAP prediction; the sensitivity, specificity and cut-off value according to Ranson code cut-off point for PNI were determined as 80.0% (95% CI:54.8-85.8), %72.2 (95% CI:70.5-87.5) and ≤45.6 (gr/L) + (mm3), respectively, and 94.7% (95% CI:57.8-87.9), %75.0 (95% CI:88.1-98.3) and >105,1 mg/L, respectively for CRP. CONCLUSION: PNI and CRP values (but not RDW values) were compatible with the disease severity determined by the Ranson criteria.

We propose a novel unsupervised semantic segmentation method for fast and accurate flood area detection utilizing color images acquired from Unmanned Aerial Vehicles (UAVs). To the best of our knowledge, this is the first fully unsupervised method for flood area segmentation in color images captured by UAVs, without the need of pre-disaster images. The proposed framework addresses the problem of flood segmentation based on parameter-free calculated masks and unsupervised image analysis techniques. First, a fully unsupervised algorithm gradually excludes areas classified as non-flood utilizing calculated masks over each component of the LAB colorspace, as well an RGB vegetation index and the detected edges of the original image. Unsupervised image analysis techniques, such as distance transform, are then applied, producing a probability map for the location of flooded areas. Finally, flood detection is obtained by applying the hysteresis thresholding segmentation. The proposed method is tested and compared with variations, and other supervised methods in two public datasets, consisting of 953 color images in total, yielding high-performance results, with 87.4% and 80.9% overall accuracy and F1-Score, respectively. The results and computational efficiency of the proposed method show that it is suitable for on board data execution and decision-making during UAVs flight.

Interaction between multiple phases especially liquid-gas is one of the most common phenomena in industrial systems. Computer Vision enables modern systems to derive an automated and robust image-processing technique to address this issue. However, diverse experimental conditions still make it a challenging task to overcome. In Deep Learning, instance segmentation has created a niche in various computer vision applications as it aims to provide different instance IDs to objects belonging to the same class. In this paper, we propose a novel approach employing the YOLO (You Look Only Once) an end-to-end deep learning architecture for the detection and segmentation of bubbles in fluid flows. YOLOv5 offers significant improvements in both speed and accuracy compared to its predecessors like YOLOv3. Therefore, we train the YOLOv5 network on a dataset consisting of annotated images representing instances of bubbles across varied fluid flow environments. This paper provides both qualitative and quantitative evaluation of three YOLOv5 networks (small, medium, and extra-large) in detecting and segmenting bubbles with high accuracy and efficiency. Based on the metrics all three YOLOv5 models achieved high precision above 0.98 for bounding box detection and 0.97 for segmentation mask, and high recall value greater than 0.97 for box and 0.96 for mask quality was achieved. The achieved results indicate that the models accurately localize bubbles within the image frame, and distinguish bubble pixels from the background. Also, mean average precision (mAP50-95) consistently exceeds 0.84 across all models for the bounding box and 0.73 for the segmentation mask. The ascertained results emphasize the potential of YOLOv5 architecture as a powerful tool for automated bubble analysis in real-world applications. Our research contributes to advancing the field of deep neural networks in fluid systems and provides a fresh approach for future developments in automated bubble analysis.

tRNA-derived fragments function as markers additionally to playing the role key of signalling molecules in a number of disorders.  It is known that the repertoire of these molecules differs greatly in different cell types and varies depending on the physiological condition. The aim of our research was to compare the pattern of tRF expression in the main blood cell types and to determine how the composition of these molecules changes during COVID-19-induced cytokine storm. Erythrocytes, monocytes, lymphocytes, neutrophils, basophils, and eosinophils from control donors and patients with severe COVID-19 were obtained by fluorescence sorting. We extracted RNA from FACS sorted cells and performed NGS of short RNAs. The composition of tRNA-derived fragments was analysed applying a semi-custom bioinformatic pipeline. In this study, we assessed the length and type distribution of TRFs and reported the 150 most prevalent TRF sequences across all cell types. Additionally we demonstrate a significant (p<0.05, fold change>16) change in the pattern of tRFs in erythrocytes (21 downregulated, 12 upregulated), monocytes (53 downregulated, 38 upregulated) and lymphocytes (49 upregulated) in patients with severe COVID-19. Thus, different blood cell types exhibit a significant variety of TRFs and react to cytokine storm by dramatically changing their differential expression patterns. We suppose that the observed phenomenon occurs due to the regulation of nucleotide modifications and alterations in activity of various Rnases.

The segmentation of abnormal regions is vital in smart manufacturing. However, the existing segmentation system for detecting sauce-packet leakage on intelligent sensors encounters an issue of imaging blurring caused by uneven illumination. This issue adversely affects segmentation performance, thereby impeding the rapid production of industrial assembly lines. To alleviate this issue, we propose the two-stage Illumination-aware Sauce-packet Leakage Segmentation (ISLS) method for intelligent sensors. The ISLS comprises two main stages: Illumination-aware region enhancement and leakage region segmentation. In the first stage, YOLO-Fastestv2 is employed to capture the Region of Interest (ROI), which reduces redundancy computations. Additionally, we propose an image enhancement to relieve the impact of uneven illumination, enhancing the texture details of ROI. In the second stage, we propose a novel feature extraction network. Specifically, we propose the Multi-scale Feature Fusion Module (MFFM) and the Sequential Self-Attention Mechanism (SSAM) to capture discriminative representations of leakage. The multi-level features are fused by MFFM with a small number of parameters, which capture leakage semantics at different scales. The SSAM realizes the enhancement of valid features and the suppression of invalid features by adaptive weighting of spatial and channel dimensions. Furthermore, we generated a self-built dataset of sauce-packets, including 606 images with various leakage areas. Comprehensive experiments demonstrate that our ISLS method shows better results than several state-of-the-art methods, with additional performance analyses deployed on intelligent sensors to affirm the effectiveness of our proposed method. Our code is available at https://github.com/LSJ5106/SauceDetect.

Glycosidic linkage analysis was conducted on the unfractionated polysaccharides in the alcohol-insoluble residues (AIRs) prepared from six red seaweeds (Gracilariopsis sp., Prionitis sp., Mastocarpus papillatus, Callophyllis sp., Mazzaella splendens, and Palmaria palmata) using GC-MS/FID analysis of partially methylated alditol acetates (PMAAs). The cell walls of P. palmata primarily contained mixed-linkage xylans and small amounts of sulfated galactans and cellulose. In contrast, the unfractionated polysaccharides of the other five species were rich in galactans displaying diverse 3,6-anhydro-galactose and galactose linkages with varied sulfation patterns. Different levels of cellulose were also observed. This glycosidic linkage method offers advantages for cellulose analysis over traditional monosaccharide analysis that is known for underrepresenting glucose in crystalline cellulose. Relative linkage compositions calculated from GC-MS and GC-FID measurements showed that anhydro sugar linkages generated more response in the latter detection method. This improved linkage workflow presents a useful tool for studying polysaccharide structural variations across red seaweed species. Furthermore, for the first time, relative linkage compositions from GC-MS and GC-FID measurements, along with normalized FID and total ion current (TIC) chromatograms without peak assignments, were analyzed using principal component analysis (PCA) as a proof-of-concept demonstration of the technique's potential to differentiate various red seaweed species.

The effect of Alzheimer's disease (AD) medications on CD4+ T cells homing has not been thoroughly investigated. Alzheimer's disturbs the life of at least five million persons in the USA. CD4+ T cells could both exacerbate and reduce AD symptoms. Regulating CD4+ T cells homing to the leaky blood-brain barrier (BBB) constitutes a new hope for enhancing AD prognosis. Alzheimer's drugs such as Donepezil (Aricept), Rivastigmine (Exelon), Galantamine (Razadyne) and memantine are known to play an important part in regulating the neurotransmitters mechanisms. However, little is known about the effect of these drugs on CD4+ T cells homing. In this review, we focus on current and new drugs that could modulate CD4+ T cells interactions with the BBB in AD.

Far-red fluorescent reporter genes can be used for tracking cells non-invasively in vivo using fluorescence imaging. Here, we investigate the effectiveness of the far-red fluorescent protein, E2-Crimson (E2C), for tracking mouse embryonic cells (mESCs) in vivo following subcutaneous administration into mice. Using a knock-in strategy, we introduced E2C into the Rosa26 locus of an E14-Bra-GFP mESC line, and after confirming that the E2C had no obvious effect on the phenotype of the mESCs, we injected them into mice and imaged them over 9 days. The results showed that fluorescence intensity was weak, and cells could only be detected when injected at high densities. Furthermore, intensity peaked on day 4 and then started to decrease, despite the fact that tumour volume continued to increase beyond day 4. Histopathological analysis showed that although E2C fluorescence could barely be detected in vivo at day 9, analysis of frozen sections indicated that all mESCs within the tumours continued to express E2C. We hypothesise that the decrease in fluorescence intensity in vivo was probably due to the fact that the mESC tumours became more vascular with time, thus leading to increased absorbance of E2C fluorescence by haemoglobin. We conclude that the E2C reporter has limited use for tracking cells in vivo, at least when introduced as a single copy into the Rosa26 locus.

Innovative strategies to control malaria are urgently needed. Exploring the interplay between the Plasmodium sp. parasites and host red blood cells (RBC) offers opportunities for novel antimalarial interventions. Pyruvate kinase deficiency (PKD), characterized by heightened 2,3-diphosphoglycerate (2,3-DPG) concentration, has been associated with protection against malaria. Elevated 2,3-DPG levels, a specific mammalian metabolite, may hinder glycolysis, prompting us to hypothesize its potential contribution to PKD-mediated protection. We investigated the impact of the extracellular supplementation of 2,3-DPG on the Plasmodium falciparum intraerythrocytic developmental cycle in vitro. Results showed an inhibition of parasite growth, resulting from significantly less progeny from 2,3-DPG-treated parasites. We analyzed differential gene expression and the transcriptomic profile of P. falciparum trophozoites, from in vitro cultures submitted or not submitted to the action of 2,3-DPG, using Nanopore Sequencing Technology. The presence of 2,3-DPG in the culture medium was associated to a significant differential expression of 71 genes, mostly associated to GO terms nucleic acid binding, transcription, or monoatomic anion channel. Further, several genes related to the cell cycle control were downregulated in treated parasites. These findings suggest that the presence of this RBC-specific glycolytic metabolite impact the expression of genes transcribed during the parasite trophozoite stage and the number of merozoites released from individual schizonts, which supports the potential role of 2,3-DPG in the mechanism of protection against malaria by PKD.

The increase in the rate and prevalence of diseases associated with the localized and general loss of bone mass calls for an investigation into therapeutic alternatives that largely involve the de-velopment of new biomaterials and cell therapy, converting tissue bioengineering into a prom-ising option. An experimental model of a critical mandibular lesion in rats has been used to study bone re-generation by treating the ostectomy with the biomaterials Evolution® and Gen-Os® (OsteoBiol®, Italy) combined, or not, with dental pulp stem cells (DP-MSC). The results obtained through the Micro-CT and histological study reveal the almost complete re-covery of the lesion in the group with DP-MSC. These results are supported by increases in endoglin, TGF-β, protocollagen I, parathormone, and calcitonin, generating an environment of bone generation and development when combining Evolution® and Gen-Os® (OsteoBiol®, Italy) with DP-MSC. These promising results confirm the transcendental role of DP-MSC in combina-tion with osteogenic biomaterials for bone regeneration, and warrant further studies, including its assessment in clinical trials.

In the last two decades many detailed full transcriptomic studies on complex biological samples have been published and included in large gene expression repositories. These studies primarily provide bulk expression signal for each sample, including multiple cell-types mixed within the global signal. The cellular heterogeneity in these mixtures does not allow the activity of specific genes in specific cell types to be identified. Therefore, inferring relative cellular composition is a very powerful tool to achieve a more accurate molecular profiling of complex biological samples. In recent decades, computational techniques have been developed to solve this problem by applying cell deconvolution methods, designed to decompose cell mixtures into their cellular components and calculate the relative proportions of these elements. Some of them, only calculate the cell proportions (supervised methods), while other deconvolution algorithms can also identify the gene signatures specific for each cell type (unsupervised methods). In these work, five deconvolution methods (CIBERSORT, FARDEEP, DECONICA, LINSEED and ABIS) were implemented and used to analyze blood and immune cells, and also cancer cells, in complex mixture samples (using three bulk expression datasets). Our study provides three analytical tools (corrplots, cell-signature plots and bar-mixture plots) that allow a thorough comparative analysis of the cell mixture data. The work indicates that CIBERSORT is a robust method optimized for the identification of immune cell-types, but not as efficient in the identification of cancer cells. We also observed that LINSEED is a very powerful unsupervised method that provides precise and specific gene signatures for each of the five main immune cell-types analyzed: neutrophils and monocytes (in the myeloid lineage), B-cells, NK cells and T-cells (in the lymphoid lineage).

Separation and interpretation of rebellious Circulating Tumor Cells (CTCs) originating from the primary tumor or cancer tissue plays a significant role in diagnostics, cancer progression analyses, suitable medicine exploration, and treatment proficiency examination. Cancer metastasis occurs when CTCs spread throughout the body and invade healthy tissues, leading to new tumors in that area. Although a dramatic rate of deaths begins from spreading CTCs around the body, valuable measures have been made to control their development. However, the first step is separating these harmful cells from the bloodstream and investigating their features. Having examined the characteristics of CTCs as cancer’s main strength, researchers can introduce complementary treatments that can affect cancerous cells without damaging the healthy cells. Therefore, according to their unique characteristics, numerous techniques have been established for continuous and fast separation and sorting of CTCs. Nevertheless, few separators enjoy the efficient performance and appropriate accuracy and can be produced in mass numbers due to the available fabrication equipment. Microfabrication advancements enable separators to combine the advantages of active and passive methods in a small-scale platform for probing individual cells and separation purposes. Reduction in reagents, sample volume, analysis time, and less harmfulness to patients are some of the motivations that encourage researchers to employ microfluidic instruments for CTCs separation from other blood cells over the last two decades. However, microfabrication limitations mean effective separators, and the diagnostic option they provide, are not readily available. Addressing these limitations requires optimizing the design and fabrication of separators such that they are reduced in their size and fabrication cost, while also maintaining high-throughput separating capability. The emergence of the Lab-On-a-Chip (LOC) and then Lab-On-a-CD (LOCD) technologies, having more inherent benefits than conventional microfluidic devices, has created new opportunities and become increasingly widespread in recent years. Evidence suggests that employing single methodologies or integrating approaches without sufficient understanding of potential outcomes is unlikely to result in successful diagnostic results. This paper contributes an extensive review of several separation systems, including fundamental theories and experimental details, and describes detailed operating principles and device performance.

Image segmentation and classification still represent an active area of research since no universal solution can be identified. Established segmentation algorithms like thresholding are problem specific, treat well the easy cases and mostly relied on single parameter i.e intensity. Machine learning approaches offer alternatives where predefined features are combined into different classifiers. On the other hand, the outcome of machine learning is only as good as the underlying feature space. Differential geometry can substantially improve the outcome of machine learning since it can enrich the underlying feature space with new geometrical objects, called invariants. In this way, the geometrical features form a high-dimensional feature space for each pixel, where original objects can be resolved. Alternatives based on the geometry of the image scale-invariant interest points have been exploited successfully in the field of computer vision. Here, we integrate geometrical feature extraction based on signal processing, machine learning, and input relying on domain knowledge. The approach is exemplified on the ISBI 2012 image segmentation challenge data set. As a second application, we demonstrate powerful image classification functionality based on the same principles, which was applied to the HeLa and HEp-2 data sets. Obtained results demonstrate that feature space enrichment properly balanced with feature selection functionality can achieve performance comparable to deep learning approaches.

Microscopic image segmentation (MIS) plays a pivotal role in various fields such as medical imaging and biology. With the advent of deep learning (DL), numerous methods have emerged for automating and improving the accuracy of this crucial image analysis task. This systematic literature review (SLR) aims to provide an exhaustive overview of the state-of-the-art DL methods employed for the segmentation of microscopic images. In this review, we analyze a diverse array of studies published in the last five years, highlighting their contributions, methodologies, datasets, and performance evaluations. We explore the evolution of DL techniques and their adaptation to specific segmentation challenges, from cell and nucleus segmentation to tissue analysis. This paper, through the integration of existing knowledge, provides valuable perspectives for researchers involved in the field of microscopic image segmentation.

Acute myeloid leukemia (AML) is a malignant disease of the blood and bone marrow that is characterized by uncontrolled clonal proliferation of abnormal myeloid progenitor cells. Nucleophosmin 1 (NPM1) gene mutations are the most common genetic abnormality in AML, detectable in blast cells from about one third of adults with AML. AML NPM1mut is recognized as a separate entity in the World Health Organization (WHO) classification of AML. Clinical and survival data suggest that patients with this form of AML often have a more favorable prognosis, which may be due to the immunogenicity created by the mutations in the NPM1 protein. Consequently, AML with NPM1mut can be considered an immunogenic subtype of AML. However, the underlying mechanisms of this immunogenicity and associated favorable survival outcomes need to be further investigated. Immune checkpoint molecules, such as the programmed cell death-1 (PD-1) protein and its ligand, PD-L1, play important roles in leukemogenesis through their maintenance of an immunosuppressive tumor microenvironment. Preclinical trials have shown that the use of PD-1/PD-L1 (PDx) checkpoint inhibitors in solid tumors and lymphoma work best in novel therapy combinations. Patients with NPM1mut AML may be better suited to immunogenic strategies that are based on the inhibition of the immune checkpoint pathway of PDx than patients without this mutation, suggesting the genetic landscape of patients may also inform best practice for the use of PDx inhibitors.

The task of weakly supervised point cloud semantic segmentation has received widespread attention and also has been widely used in autonomous driving, robotics, and modern industries. Due to the high dimensionality and large volume of point cloud data, many technical difficulties appeal to weakly supervised semantic processing, especially segmentation. However, weakly-supervised schemes usually provide only partial labelling information of the underlying point cloud data and thus need to effectively extract local features, geometric information, and contextual relationships only using these limited labelled data for supervised learning. To improve weakly-supervised semantic segmentation, we propose a novel segmentation network through the boundary-based feature aggregation based on a K-NN algorithm with down-sampling operation, and also introduce the smoothness loss and Siamese loss for effective segmentation. The experiments on public datasets demonstrate that our presented segmentation method exceeds most of the existing fully supervised and weakly-supervised methods in terms of mIoU. Specifically, our network has high segmentation accuracy on the labels of objects with similar geometrical structures, such as ceiling, wall, floor, chair and table, reaching 91.2%, 98.8%, 83.3%, 75.3% and 80.2%, respectively. Extensive experiments also illustrate its robustness, effectiveness, and generalization of the proposed weakly supervised segmentation network.

Rapid isolation of white blood cells (WBCs) from whole blood is an essential part of any WBC examination platform. However, most conventional cell separation techniques are labor-intensive and low throughput, require large volumes of samples, need extensive cell manipulation, and have low purity. To address these challenges, we report the design and fabrication of a passive, label-free microfluidic device with a unique U-shaped cross-section to separate WBCs from whole blood using hydrodynamic forces that exist in a microchannel with curvilinear geometry. It is shown that the spiral microchannel with a U-shaped cross-section concentrates larger blood cells (e.g., WBCs) in the inner cross-section of the microchannel by moving smaller blood cells (e.g., red blood cells (RBCs) and platelets) to the outer microchannel section and preventing them from returning to the inner microchannel section. Therefore, it overcomes the major limitation of a rectangular cross-section where secondary Dean vortices constantly enforce particles throughout the entire cross-section and decrease its isolation efficiency. Under optimal settings, more than 95% of WBCs can be isolated from whole blood under high-throughput (6 ml/min), high-purity (88%), and high-capacity (180 ml of sample in 1 hour) conditions. High efficiency, fast processing time, and non-invasive WBC isolation from large blood samples without centrifugation, RBC lysis, cell biomarkers, and chemical pre-treatments make this method an ideal choice for downstream cell study platforms.

Medical image segmentation is a critical step in various healthcare applications, aiding in diagnosis, treatment planning, and disease monitoring. In this study, we investigate the efficacy of a segmentation approach based on the 2D wavelet transform. Leveraging a dataset comprising 10 diverse medical images, we evaluate the performance of our segmentation method using three key metrics: accuracy, precision, and recall. Our findings demonstrate that the proposed approach enhances segmentation accuracy, offering promising results compared to existing methods. By harnessing the multi-resolution feature extraction capabilities of the 2D wavelet transform, our method achieves improved delineation of medical image structures, paving the way for more accurate and efficient healthcare interventions.

Depth-sensing technology has led to broad applications of inexpensive depth cameras that can capture human motion and scenes in 3D space. Background subtraction algorithms can be improved by fusing color and depth cues, thereby allowing many issues encountered in classical color segmentation to be solved. In this paper, we propose a new fusion method that combines depth and color information for foreground segmentation based on an advanced color-based algorithm. First, a background model and a depth model are developed. Then, based on these models, we propose a new updating strategy that can eliminate ghosting and black shadows almost completely. Extensive experiments have been performed to compare the proposed algorithm with other, conventional RGB-D algorithms. The experimental results suggest that our method extracts foregrounds with higher effectiveness and efficiency.

In this study, novel biomarkers in Blood Mononuclear Cells (PBMCs) of Hepatocellular Carcinoma (HCC) patients were identified through microarray data analysis. The problem that prompted the study was the lack of reliable biomarkers for early diagnosis and monitoring of HCC. The purpose of this study was to discover potential biomarkers in PBMCs of HCC patients that can be used for early diagnosis and monitoring of the disease. The main hypothesis was that there are genes that are overexpressed in PBMC of HCC patients compared to healthy individuals. The results showed that genes HBB, WBP2, HBA2, and HBA1 were overexpressed in PBMCs of HCC patients. Additionally, nine genes were found to be upregulated in HCC patients and had a relation between KEGG pathways of RA, suggesting a link between the two diseases. These genes are TLR4, IL1B, CXCL5, IL11, HLA-DQA1, HLA-DRA, LBT, ATP6V1B2 and ATP6V1C1. The Gene ontology analysis revealed biological processes used in the process of how these genes play a role in development of HCC. In conclusion, this study identified potential biomarkers in PBMC of HCC patients that can aid in early diagnosis and monitoring of the disease. The findings of this study have important implications for improving the clinical management of HCC patients.

Glaucoma, a global leading cause of blindness, necessitates accurate segmentation of the optic disc (OD) and optic cup (OC) for effective screening. However, existing segmentation methods based on convolutional neural networks (CNNs) suffer from high computational complexity and long inference times. In this paper, we propose an end-to-end segmentation method for the OD and OC using a lightweight MobileNetv3 as the feature extraction network. Our approach incorporates boundary branches and an adversarial learning network to achieve multi-label segmentation of the OD and OC. We evaluate the proposed method on three publicly available datasets: Drishti-GS, RIM-ONE-r3, and REFUGE. The experimental results demonstrate segmentation accuracies of 0.974/0.900, 0.966/0.875, and 0.962/0.880 for the OD and OC on the respective datasets, while significantly reducing inference time.

Tsallis entropy has been widely used in image thresholding because of its non-extensive properties. The non-extensive parameter q contained in this entropy plays an important role in various adaptive algorithms and has been successfully applied in bi-level image thresholding. In this paper, the relationships between parameter q and pixels’ long-range correlations have been further studied within multi-threshold image segmentation. It is found that the pixels’ correlations are remarkable and stable for images generated by a known physical principle, such as infrared images and medical CT images. And the corresponding non-extensive parameter q can be evaluated by using self-adaptive Tsallis entropy algorithm. The results of this algorithm are compared with those of Shannon entropy algorithm and the original Tsallis entropy algorithm, in terms of quantitative image quality evaluation metrics PSNR (Peak Signal-to-Noise Ratio) and SSIM (Structural Similarity). Furthermore, we observed that for image series with the same background, the q values determined by the adaptive algorithm are consistently kept in a narrow range. Therefore, similar or identical scenes during imaging would produce similar strength of long-range correlations, which provides potential applications for unsupervised image processing.

Per- and polyfluoroalkyl substances (PFASs) are a group of fluorinated, organic, man-made chemicals; they do not occur naturally in the environment. This study aimed to determine the profile and content of PFASs in volunteers’ blood plasma and urine after fermented red beetroot juice consumption and correlated it with the blood parameters. During 42 days, 24 healthy volunteers intake 200 mL/60 kg of body weight fermented red beetroot juice. PFASs were analyzed using micro-HPLC-MS/MS method. Five perfluoroalkyl substances were found in human body fluids. After juice consumption, PFASs, due to the consumption of food contaminated with them, was discovered that for perfluorocarboxylic acids, a downward trend was observed, while for perfluoroalkane sulfonates, their plasma content showed a statistically significant upward trend. Analysis of the hematology parameters indicated that the intake the fermented red beetroot juice showed a significant decrease in mean corpuscular volume (MCV), platelets concentration, mean platelet volume (MPV), platelet large cell ratio (P-LCR) at the significance level p < 0.01, and he-matocrit (p < 0.05). On the other hand, the dietary intervention also indicated a significant (p < 0.01) increase corpuscular/ cellular hemoglobin concentration (MCHC). In the case of blood biochemi-stry, no significant change in blood samples after intake the fermented beetroot juice was observed. However, a decreasing tendency of total cholesterol and low-density lipoprotein concentration (LDL-C) were observed. Based on the presented results, there is a need to analyze and monitor health-promoting food regarding undesirable substances and their impact on consumer health.

The blood-brain barrier (BBB) acts as a structural and functional barrier for brain homeostasis. This review highlights the pathological contribution of BBB dysfunction to neuroimmunological diseases, including multiple sclerosis (MS), neuromyelitis optica spectrum disorder (NMOSD), myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD), autoimmune encephalitis (AE) and paraneoplastic neurological syndrome (PNS). The transmigration of massive lymphocytes across the BBB caused by the activation of cell adhesion molecules is involved in the early phase of MS, and dysfunction of the cortical BBB is associated with the atrophy of gray matter in the late phase of MS. In the onset of NMOSD, increased permeability of the BBB causes the entry of circulating AQP4 autoantibodies into the central nervous system (CNS). Recent reports have shown the importance of glucose-regulated protein (GRP) autoantibodies as BBB-reactive autoantibodies in NMOSD, inducing antibody-mediated BBB dysfunction. BBB breakdown has also been observed in MOGAD, NPSLE, and AE with anti-NMDAR antibodies. Our recent report demonstrated the presence of GRP78 autoantibodies in patients with MOGAD and the molecular mechanism responsible for GRP78 autoantibody-mediated BBB impairment. Disruption of the BBB may explain the symptoms in the brain and cerebellum in the development of PNS, as it induces the entry of pathogenic autoantibodies or lymphocytes into the CNS by autoimmunity against tumors in the periphery. GRP78 autoantibodies were detected in paraneoplastic cerebellar degeneration and Lambert-Eaton myasthenic syndrome and were associated with cerebellar ataxia with anti-P/Q type voltage-gated calcium channel antibodies. This review reports that therapies affecting the BBB that are currently available for disease-modifying therapies for neuroimmunological diseases have the potential to prevent BBB damage.

A single paragraph of about 200 words maximum. For research articles, abstracts should give a pertinent overview of the work. We strongly encourage authors to use the following style of structured abstracts, but without headings: (1) Background: Place the question addressed in a broad context and highlight the purpose of the study; (2) Methods: briefly describe the main methods or treatments applied; (3) Results: summarize the article’s main findings; (4) Conclusions: indicate the main conclusions or interpretations. The abstract should be an objective representation of the article and it must not contain results that are not presented and substantiated in the main text and should not exaggerate the main conclusions.

Mobile health technologies enable continuous, quantitative assessment of mobility and gait in real-world environments, facilitating early diagnosis of gait disorders, disease progression monitoring, and prediction of adverse events like falls. Traditionally, mobile gait assessment predominantly relied on body-fixed sensors positioned at the feet or lower trunk. Here, we investigate the potential of an algorithm utilizing an ear-worn motion sensor for spatiotemporal segmentation of gait patterns. We collected 3D acceleration profiles from the ear-worn sensor during varied walking speeds in 53 healthy adults. Temporal convolutional networks were trained to detect stepping sequences and predict spatial relations between steps. The resulting algorithm, mEar, accurately detects initial and final ground contacts (F1 score of 99% and 91%, respectively). It enables determination of temporal and spatial gait cycle characteristics (among others stride time and stride length) with good to excellent validity at a precision sufficient to monitor clinically relevant changes in walking speed, stride-to-stride variability, and side asymmetry. This study highlights the ear as a viable site for monitoring gait and proposes its potential integration with in-ear vital sign monitoring. Such integration offers a practical approach to comprehensive health monitoring and telemedical applications, by integrating multiple sensors in a single anatomical location.

A facilitative transport system exists on the blood brain barrier (BBB) that has been tacitly assumed to be a path for glutamate entry to brain. But glutamate is a non-essential amino acid whose brain content is much greater than plasma, and studies in vivo show that glutamate does not enter brain in material quantities except in those small regions with fenestrated capillaries (circumventricular organs). The situation became understandable when luminal (blood facing) and abluminal (brain facing) membranes were isolated and studied separately. Facilitative transport of glutamate and glutamine exist only on the luminal membranes whereas Na+-dependent transport systems for glutamate, glutamine and some other amino acids are present only on the abluminal membrane. The Na+-dependent cotransporters of the abluminal membrane are in a position to actively transport amino acids from the extracellular fluid (ECF) into the endothelial cells of the BBB. These powerful secondary active transporters couple the energy of the Na+-gradient to move glutamate and glutamine into the ECF whereupon glutamate can exit to blood on the luminal facilitative glutamate transporter. Glutamine may also exit brain on a separate facilitative transport system that exists on the luminal membranes or glutamine can be hydrolyzed to glutamate within the BBB thereby releasing ammonia that is freely diffusible. The γ-glutamyl participate cycle participates indirectly by producing oxoproline (pyroglutamate) that stimulates almost all secondary active transporters yet discovered in the abluminal membranes of the BBB.

With the rapid developments that have been made in computer vision and computer technology, semantic segmentation of high-resolution images has emerged as a mainstream and challenging task. The, segmentation of water areas remains a complex task due to the similar features between water areas or between water areas and other land objects. Meanwhile, since coastlines and riverbanks are typically presented in irregular shapes, it is difficult to obtain the categories of pixels at boundaries. This paper proposed the use of a Water-Land Boundary Attention Network (WLBANet) to improve the accuracy of pixels at boundaries between water and land. This network also reinforced the performance of contextual information extraction into distinguishing between water areas and other land objects. To prove the validity of this proposed network, WLBANet was performed on the Water Land Dataset (WLD), which is also by this paper, and which contains water areas and other land objects categories. The results demonstrates that the proposed method has significant effectiveness.

Large datasets play a crucial role in the progression of surgical robotics, facilitating advancements in the fields of surgical task recognition and automation. Moreover, public datasets enable the comparative analysis of various algorithms and methodologies, thereby assessing their effectiveness and performance. The ROSMA (Robotics Surgical Maneuvers) dataset provides 206 trials of common surgical training tasks performed with the da Vinci Research Kit (dVRK). In this work, we extend ROSMA dataset with two annotated subsets: ROSMAT24, which contains bounding box annotations for instrument detection, and ROSMAG40, which contains high and low level gesture annotations. We propose an annotation method that provides independent labels for the right-handed tool and the left-handed tool. For instrument identification, we validate our proposal with a YOLOv4 model in two experimental scenarios. We demonstrate the generalization capabilities of the network to detect instruments in unseen scenarios. For gesture segmentation, we propose two label categories: high-level annotations that describe gestures at a maneuvers level, and low-level annotations that describe gestures at a fine-grain level. To validate this proposal, we have designed a recurrent neural network based on a bidirectional long-short term memory layer. We present results for four cross-validation experimental setups, reaching up to a 77.35% mAP.

Lymphocyte collection by apheresis for CAR-T production usually does not include mobilized blood using Granulocyte Colony Stimulating Factor (G-CSF) due to the widespread knowledge that it causes a decrease in the number and functionality of lymphocytes. However, it is used for stem cell transplant, which is a common treatment for hematological malignancies. The growing demand for CAR therapies (CAR-T and NK-CAR), both in research and clinic, makes necessary to evaluate whether mobilized PBSC products may be potential candidates for use in such therapies. This review collects recent work that experimentally verifies the role and functionality of T and NK lymphocytes, and the generation of CAR-T, from apheresis after G-CSF mobilization. As discussed, T cells do not vary significantly in their phenotype, the ratio of CD4+ and CD8+ remains constant and the different sub-populations remain stable. In addition, its expansion and proliferation rate are invariant regardless mobilization with G-CSF, as well as the secretion of proinflammatory cytokines and the cytotoxic ability. Therefore, cells mobilized before apheresis are postulated as a new alternative source of T cells for adoptive therapies that will serve to alleviate high demand, increase availability, and take advantage of the substantial number of existing cryopreserved products.

Porcine circovirus type 2 (PCV2) is a small non-enveloped DNA virus that causes swine immunosuppression by inducing apoptosis in lymphocytes. The ORF3 protein plays a major role in PCV2-induced apoptosis in porcine kidney cells, but there is little information regarding this protein in PCV2-infected lymphocytes. In this study, hybridoma screening and epitope mapping were determined by using an indirect ELISA. The mAb 7D3 against ORF3 peptide (residues 35–65) of PCV2 were generated in this study. In vivo situation, the mAb 7D3 recognized ORF3 protein existed in PCV2-infected apoptotic porcine PBMCs. It is noteworthy that thimerosal interfered with the binding of mAb 7D3 to epitope and it was diminished by adding cysteine. Additionally, thimerosal interacting with cysteine-containing peptide was demonstrated by the PTI assay. Furthermore, thimerosal specifically interacted with the antigen-binding sites of mAb 7D3. This study suggested that thimerosal blockade the occlusion of the antigen-binding sites of mAb 7D3 to bind ORF3 peptide (residues 35–65) via thimerosal interacting with cysteine residues which should be located within the antigen-binding sites of mAb 7D3. Overall, the mAb 7D3 has been characterized and it will be a valuables tool in future studies of ORF3 function and the wider mechanism of cell apoptosis caused by PCV2 infection. Similarly, these techniques will be useful for applications in detecting thimerosal too.

In the era of massive construction, damaged and aging infrastructure are becoming more common. Defects, such as cracking, spalling, etc., are main types of structural damage that widely occur. Hence, ensuring the safe operation existing infrastructure through health monitoring has emerged as an important challenge facing structural engineers. In recent years, intelligent approaches, such as data driven machine and deep learning crack detection, gradually dominate over traditional methods. Among them, the semantic segmentation using deep learning models is a process of characterization of accurate location and portrait of cracks using pixel level classification. Most available studies rely on single model knowledge to perform this task. However, it is well-known that the single model might suffer from low variance and low ability to generalize in case of data alteration. By leveraging the ensemble deep learning philosophy, a novel corporative semantic segmentation of concrete cracks method called Co-CrackSegment is proposed. Firstly, five models, namely the U-net, SegNet, DeepCrack19, DeepLabV3-ResNet50, and DeepLabV3-ResNet101 are trained to serve as core models for the ensemble model Co-CrackSegment. To build the ensemble model Co-CrackSegment, a new iterative approach based on the best evaluation metrics, namely the dice score, IoU, pixel accuracy, precision, and recall metrics is developed. Results show that the Co-CrackSegment exhibits a prominent performance compared to core models and weighted average ensemble by means of the considered best statistical metrics.

BACKGROUND Detecting total cholesterol in dried blood spots could aid in identifying individuals with a high likelihood of familial hypercholesterolemia and could be used as a screening measure. This study aims to assess the diagnostic accuracy of dried blood spots on Whatman 903 paper cards using a manual enzymatic technique. METHODS A total of 394 samples collected as serum and dried blood spots were compared. Cholesterol was determined in serum using the automated reference method, while cholesterol on paper was measured using a manual enzymatic method. Within- and between-day diagnostic variability were analyzed. The correlation between both methods was assessed using Passing-Bablok regression and Bland-Altman plot. Internal validation of our correlation formula was performed on 149 samples, along with external validation of the formula proposed by Corso et al. RESULTS The within- and between-day coefficient of variation was found to be lower than 10.14% and 14.09%, respectively. Method comparison yielded an area under the curve of 0.976, with a standard error of 0.009. Passing-Bablok regression indicated a precision of 0.803 and an accuracy of 0.96. Internal validation precision was measured at 0.716. Regarding internal validation, calculated cholesterol with our regression line did not differ from serum cholesterol analysis, while significant differences were observed in calculated cholesterol levels using the external formula. CONCLUSIONS Total cholesterol analysis in dot blood spots demonstrates high precision and reproducibility. This method reliably enables the incorporation of this biological marker into neonatal screening for familial hypercholesterolemia detection.

Cells respond to a myriad of stressors by senescing, acquiring stable growth arrest, morphologic and metabolic changes, and a senescence-associated-secretory-phenotype (SASP). The heterogeneity of senescent cells (SnCs) and their SASP is vast, yet poorly characterized. SnCs have diverse roles in health and disease and are therapeutically targetable, making characterization of SnCs and harmonization of their nomenclature a priority. The Cellular Senescence Network (SenNet), a NIH Common Fund initiative, will leverage emerging single cell and spatial-omics to identify and map SnCs in numerous organs across the lifespan of humans and mice. A common coordinate framework will integrate the data, using validated, standardized methods, creating public 4-dimensional SnC atlases. Key SenNet deliverables include development of innovative tools/technologies to detect SnCs, biomarker discovery, common annotations to describe SnCs and extensive public data sets. The goal is to comprehensively understand and map SnCs for diagnostic and therapeutic purposes to improve human health.

Three different populations of sulfated polysaccharides can be found in the cell wall of the red alga Botryocladia occidentalis. In a previous work, the structures of the two more sulfated polysaccharides were revised. In this work, NMR-based structural analysis was performed on the least sulfated polysaccharide and its chemically modified derivatives. Results have revealed the presence of both 4-linked α- and 3-linked β-galactose units having the following chemical features: more than half of the total galactose units are not sulfated, the α-units occur primarily as 3,6-anhydro-galactose units either 2-O-methylated or 2-O-sulfated, and the β-galactose units can be 4-O-sulfated or 2,4-O-disulfated. SPR-based results indicated weaker binding of the least sulfated galactan to thrombin, factor Xa, and antithrombin, but stronger binding to heparin cofactor II than unfractionated heparin. This report together with our previous publication completes the structural characterization of the three polysaccharides found in the cell wall of the red alga B. occidentalis and correlates the impact of their composing chemical groups with the levels of interaction with the blood co-factors.

Pregnancy in women with Sickle Cell Disease (SCD) is a high-risk situation, especially during the third trimester of gestation and in the post-partum period, due to chronic hypoxia and vaso-occlusive phenomena occurring in the maternal-fetal microcirculation: as a result, unfavorable outcomes, such as intra-uterine growth restriction, prematurity or fetal loss are more frequent in SCD pregnancies. Therefore, there is a consensus on the need for a strict and multidisciplinary follow-up within specialized structures. Transfusion support remains the mainstay of treatment of SCD pregnancies, although most appropriate modalities are still controversial: the benefit of prophylactic management, either by simple transfusions or by automated Red Blood Cell Exchange (aRBCX), is not unanimously recognized. We illustrate the cases of three SCD pregnant patients who underwent aRBCX procedures at our institution in different clinical scenarios. Moreover, we carried out a careful literature revision to investigate the management of pregnancy in SCD, particularly regarding the practice of aRBCX. Our experience and current literature support using aRBCX in pregnancy as a feasible and safe procedure provided that specialized equipment and an experienced apheresis team are available. However, further research in this high-risk population, with appropriately powered prospective trials, will be desirable to refine indications and timing of aRBCX and confirm this approach's advantages on other transfusion modalities.

Background: The prevalence of atopic dermatitis in domestic animals is one of the problems of modern veterinary. Treating with standard techniques using chemotherapeutic agents not always leads to a positive result of therapy; moreover, many drugs produce adverse side effects. Methods: Low level laser therapy, in particular, intravenous laser blood illumination (ILBI) has a pronounced and long-lasting impact on the immune system of animals. The combined technique including ILBI-635 (635 nm, 2 mW, 5 min) and LUVBI^® (365 nm, 2 mW, 3 min) every other day provides a positive change in clinical status of cats with allergic dermatitis after the 3rd-4th treatment session. Results: The increased level of erythrocytes and hemoglobin was identified in the course of treatment, and it indirectly indicates increased blood transport activity, which improves trophic provision and microcirculation. A double reduction of leukocytes and a significant decrease of neutrophil cells indicate the immunomodulatory effect of LILI (low-intensity laser illumination). The increase in the percentage of lymphocytes and the decrease of eosinophils and monocytes against the background of basophil concentrations deviations within physiological concentration result in the reduction of inflammatory mediators expression that induce itching. The reduction of total IgE concentration 32 times against control on the 7th day of treatment correlates with the decrease in the quantitative content of peripheral blood eosinophils, indicating the decrease in severity of an allergic process. Conclusion: LLLT is recommended against the background of standard drug therapy to achieve quick clinical outcome together with a long-lasting prolonged effect.

(1) Background: Myelodysplastic syndromes (MDS) are a group of diseases that affect the morphology and function of neutrophils. Rapid diagnosis of MDS is crucial for the initiation of treatment that can vastly improve disease outcome. (2) methods: In this work, we present a new approach for detecting morphological differences between neutrophils isolated from blood samples of high risk MDS patients and that for patients and blood bank donors (BBDs). First, using fluorescent flow cytometry CD66b positive cells were stained with 2′,7′-dichlorofluorescin diacetate (DCF) and Hoechst. Secondly, we imaged the cells using interferometric phase microscopy (IPM) without utilizing cell staining. (3) Results: flow cytometry results show MDS patients present different dispersion patterns compared to BBDs. BBDs present two distinct subpopulations (one of these are the H cells constituting 16% for neutrophils) whereas MDS patients present only 4% of this subpopulation. IPM results are consistent with this pattern: ~20% of BBDs neutrophils were characterized as H cells and whereas MDS patients present only ~4% of these cells. (5) Conclusion- IPM can be utilized for diagnosis of complex hematological pathologies such as MDS.

Given the importance of menstrual blood in the pathogenesis of endometriosis and the multifunctional roles of menstrual mesenchymal stem cells (MenSCs) in regenerative medicine, this issue has gained prominence in the scientific community. Moreover, recent reviews highlight how robust the integrated assessment of omics data is for endometriosis. To our knowledge, no study has applied the multi-omics approaches to endometriosis MenSCs. It is a case-control study at a university-affiliated hospital. MenSCs transcriptome and proteome data were obtained by RNA-seq and UHPLC-MS/MS detection. Among the differentially expressed proteins and genes, we emphasize ATF3, ID1, ID3, FOSB, SNAI1, NR4A1, EGR1, LAMC3, and ZFP36 genes and MT2A, TYMP, COL1A1, COL6A2, and NID2 proteins that were already reported in the endometriosis. Our functional enrichment analysis reveals integrated modulating signaling pathways such as epithelial-mesenchymal transition (↑) and PI3K signaling via AKT to mTORC1 (↓in proteome), mTORC1 signaling, TGF beta signaling, TNFA signaling via NFkB, and response to hypoxia via HIF1A targets (↑in transcriptome). Our findings highlight primary changes in the endometriosis MenSCs, suggesting that the chronic inflammatory endometrial microenvironment can modulate these cells, providing opportunities for endometriosis etiopathogenesis. Moreover, they identify challenges for future research leveraging knowledge for regenerative and precision medicine in endometriosis.

Plant phenotype plays an important role in crop breeding and planting. Leaf phenotype is an important part of plant phenotype. In order to analyze the leaf phenotype, the target leaf is required to be segmented from the complex background image. In this paper, an automatic soybean leaf segmentation method based on object detection and interactive segmentation models is proposed. Firstly, the Libra R-CNN object detection algorithm is used to detect all soybean leaves in the image. Then, based on the idea that the target soybean leaf is located in the center of the image and the area is large, the detection bounding box of the target leaf is selected. In order not to destroy the segmentation result, the bounding box is optimized to completely enclose the whole leaf. Finally, according to the optimized bounding box, the prior channels of foreground and background are constructed using Gaussian model. The two channels together with the original image are as the input of the interactive object segmentation with inside-outside guidance model to segment the target soybean leaf. A large number of qualitative and quantitative experimental results show that the method has high segmentation accuracy and strong generalization capacity.

Natural killer (NK) cell therapy is one of the most promising treatments for Glioblastoma Multiforme (GBM). However, this emerging technology is limited by the availability of sufficient numbers of fully functional cells. Here, we investigated the efficacy of NK cells that were expanded and treated by interleukin-2 (IL-2) and heat shock protein70 (HSP70), both in vitro and in vivo. Proliferation and cytotoxicity assays were used to assess the functionality of NK cells in vitro, after which treated and naïve NK cells were administrated intra-cranially and systemically to compare the potential antitumor activities in our in vivo rat GBM models. In vitro assays provided strong evidence of NK cell efficacy against C6 tumor cells. In vivo tracking of NK cells showed efficient homing around and within the tumor site. Furthermore, significant amelioration of the tumor in rats treated with HSP70/Il-2 treated NK cells as compared to those subjected to non-treated NK cells, as confirmed by MRI, proved the efficacy of adoptive NK cell therapy. Moreover, results obtained with systemic injection confirmed migration of activated NK cells over the blood brain barrier and subsequent targeting of GBM tumor cells. Our data suggest that administration of HSP70/Il-2 treated NK cells may be a promising therapeutic approach to be considered in the treatment of GBM.

This article presents a succinct overview of the progress, obstacles, and uses of semantic segmentation and instance segmentation within the forestry domain. The objective of this review is to conduct a critical analysis of the current literature pertaining to segmentation techniques and provide a methodical summary of their impact on forestry-related activities, including but not limited to tree species classification, forest inventory, and ecological monitoring such as retrieval of dominant tree species. Through the process of synthesizing pivotal discoveries from multiple studies, this comprehensive analysis provides valuable perspectives on the present status of research and highlights prospective areas for further exploration. The primary topics addressed encompass the approach employed for executing the examination, the fundamental discoveries associated with semantic segmentation and instance segmentation in the domain of forestry, and the ramifications of these discoveries for the discipline. The results indicate that the utilization of semantic segmentation methods has been efficacious in the field of forestry for the precise identification of tree species. Such methods also aid in tracking of deforested regions over the course of time by separating other land-use classes from forested regions. Additionally, the employment of instance segmentation techniques exhibits potential in the demarcation of individual trees. Instance segmentation offers promising results due to deep learning models based on forest point clouds. However, several challenges persist in the successful implementation of semantic segmentation methods such as the presence of occlusions, overlapping branches, and intricate structures hampers the accurate segmentation of trees. Additionally, instance segmentation approaches that utilize models are mostly trained by using laser scanning data based on forest types which are typically trained on specific laser scanning data and forest types that create limitations in generalization from high to low resolution point clouds. Due to this reason, the existing approaches often struggle with handling these complex structures, leading to the need for manual methods for extracting measurements from forest point clouds. The review culminates by underscoring the necessity for additional research to tackle current obstacles and augment the precision and relevance of segmentation methodologies in the field of forestry. In general, the present article provides a significant reference for scholars and professionals who are interested in utilizing segmentation techniques in the field of forestry.

Background: The prevalence of human T-lymphotropic virus type-1 (HTLV-1) infection is higher in women, and sexual intercourse has been described as an important route of male-to-female transmission. The present study aimed to quantify HTLV-1 proviral load (PVL) in vaginal fluid, and to investigate correlations with PVL in peripheral blood mononuclear cells (PBMC). Methods: HTLV-1-infected women were consecutively recruited at a multidisciplinary center for HTLV patients in Salvador-Brazil. All women underwent gynecological examinations to obtain cervicovaginal fluid and venipuncture for blood collection. PVL, as measured by real-time quantitative polymerase chain reaction (RT-qPCR), was expressed as the number of copies of HTLV-1/106 cells in blood and vaginal fluid samples. Light microscopy was used to assess cervicovaginal cytopathology and vaginal microbiota. Results: In the 56 included women (43 asymptomatic carriers and 13 diagnosed with HTLV-associated myelopathy/tropical spastic paraparesis-HAM/TSP), mean age was 35.9 (SD±7.2) years. PVL was higher in PBMCs [median: 23,264 copies/106 cells (IQR: 7,420 - 64,371)] than in vaginal fluid [451.9 copies/106 cells (IQR: 0 - 2,672)] (p<0.0001). PVL in PBMCs was observed to correlate directly with PVL in vaginal fluid (R=0.32, p=0.01). PVL was undetectable in vaginal fluid samples from 20 women (35.7%), most of whom were asymptomatic (19/20). Cytopathologic analyses revealed no differences between women with detectable or undetectable PVL. Conclusion: HTLV-1 proviral load is detectable in vaginal fluid and correlates directly with proviral load in peripheral blood. This finding suggests that sexual transmission of HTLV-1 from female to male may occur and vertical transmission, particularly in the context of vaginal delivery.

Background: Older adults with bipolar disorder (OABD) are individuals aged 50 years and older with bipolar disorder (BD). People with BD may have fewer coping strategies or resilience. A long course of the disease, such as in OABD, could impact the development of resilience strategies, but this remains under-researched in OABD. Therefore, this study aims to assess resilience levels within the OABD and explore associated factors, hypothesizing that resilience could improve psychosocial functioning, wellbeing and quality of life of OABD patients. Methods: This study sampled 33 OABD patients from the OABD cohort at the Bipolar and Depressive Disorders Unit of Hospital Clinic of Barcelona. This was an observational, descriptive and cross-sectional study. Demographic and clinical variables as well as psychosocial functioning, resilience and cognitive reserve were analyzed. Resilience was measured using the CD-RISC-10. Non-parametric tests were used for statistical analysis. Results: The average CD-RISC-10 score was 25.67 points (SD 7.87). Resilience negatively correlated with the total number of episodes (p = 0.034), depressive episodes (p = 0.001), and the FAST (p < 0.001). Participants with normal resilience had a lower FAST (p = 0.046), a higher CRASH (p = 0.026), and more EOBD (p = 0.037) compared to those with low resilience. Conclusions: OABD individuals may exhibit lower resilience levels which correlate with more psychiatric episodes, particularly the number of depressions and worse psychosocial functioning and cognitive reserve. Better understanding and characterization of resilience could aid in early identification of patients requiring additional support to foster resilience and enhance OABD management.

Marine invertebrates are model organisms in several areas of biological sciences, being a source of massive biological information. Although, the scientific relevance of marine invertebrates, the research with them can be limited for their tissue characteristics and troubles for the replication of physical and chemical properties of seawater. Thence, the main goal of this laboratory workflow is to provide a useful methodological approach to reduce the experimental limitations during the study of marine invertebrates. The present study describes experimental methodologies for the collection, transport, and maintenance of sessile tunicates. Also, an approach to observe and characterize, a diverse population of blood cells in marine invertebrates, by several cytological stains and electron microscopy. Lastly, suggestions and protocols to extract quality RNA from samples with high concentrations of salts, pigments, secondary metabolites, and polysaccharides. This methodological approach can be easily adapted to other marine invertebrates, moreover uses low-cost reagents and widely available laboratory equipment. Making possible the study of different types of marine animals in diverse locations.

In the last decade, the application of non-Saccharomyces yeasts in oenology as a natural tool to obtain wine diversification and higher quality has aroused great interest. In this work, three M. pulcherrima strains, isolated from vineyard, were characterized through the evaluation of their main technological properties, antimicrobial activity and specific enzymatic activities (β-glucosidase, β-lyase, polygalacturonase and protease). The M. pulcherrima strains did not produce any inhibition against S. cerevisiae, while they were able to exert an antimicrobial action against some unwanted bacteria and yeasts frequently present in grape must and potentially causing alteration of wines. After this preliminary screening, M. pulcherrima AS3C1 has been selected to be used in the winemaking of red grape Vitis vinifera cv. Aglianico on a pilot scale. The effect of sequential inoculation of M. pulcherrima AS3C1 with a commercial strain of Saccharomyces cerevisiae was verified using for comparison a single inoculum with S. cerevisiae and a spontaneous fermentation. Our results showed a higher concentration of anthocyanins and catechins in wines obtained by sequential inoculation of M. pulcherrima AS3C1 and S. cerevisiae. On the basis of the data obtained, M. pulcherrima AS3C1 possesses an enzymatic profile and some oenological properties that could contribute positively to the definition of the chemical composition of wines, suggesting its possible use for red winemaking processes.

This research introduces a pioneering solution to the challenges posed by gastrointestinal tract (GI) cancer in radiation therapy, focusing on the imperative task of precise organ segmentation for minimizing radiation-induced damage. GI imaging has historically used manual demarcation, which is laborious and uncomfortable for patients. We address this by introducing the ResECA-U-Net deep learning model, a novel combination of the UNet and ResNet34 architectures. Furthermore, we further augment its functionality by incorporating the Efficient Channel Attention (ECA-Net) methodology. By utilizing data from the UW-Madison Carbone Cancer Centre, we carefully investigate several image processing techniques designed to capture critical local characteristics. With its foundation in computer vision concepts, the ResECA-U-Net model is excellent at extracting fine details from GI images. Sophisticated metrics such as intersection over union (IoU) and the dice coefficient are used to evaluate performance. Our study's outcomes demonstrate the effectiveness of the suggested method, yielding an impressive 96.27% Dice coefficient and 91.48% IoU. These results highlight the significant contribution that our strategy has made to the advancement of cancer therapy. Beyond its scientific merits, this work has the potential to significantly enhance cancer patients' quality of life and provide better long-term outcomes. Our work is a significant step towards automating and optimizing the segmentation process, which can potentially change how GI cancer is treated completely.

Pulmonary arteriovenous malformations (PAVMs) are vascular anomalies resulting in abnormal connection between pulmonary arteries and veins. In 80% of cases, PAVMs are present from birth, but clinical manifestations are rarely seen in childhood. These congenital malformations are typically associated with Hereditary Hemorrhagic Telangiectasia (HHT), a rare disease that affects 1 in 5,000/8,000 individuals. HHT disease is frequently caused by mutations in genes involved in the TGF-β pathway. However, approximately 15% of patients do not have a genetic diagnosis and, among the genetically diagnosed, more than 33% do not meet the Curaçao Criteria. This makes clinical diagnosis even more challenging in the pediatric age group. Here, we introduce an 8 years old patient bearing a severe phenotype of multiple diffuse PAVMs caused by an unknown mutation which ended in lung transplantation. Phenotypically, the case of study follows a molecular pattern HHT-like. Therefore, molecular biology and cellular functional analysis has been performed in primary endothelial cells (ECs) isolated from the explanted lung. The findings revealed a loss of functionality in lung endothelial tissue and a stimulation of endothelial to mesenchymal transition. Understanding the molecular basis of this transition could potentially offer new therapeutic strategies to delay lung transplantation in severe cases.

Diagnosing skin lesions can be a challenging task. Dermatologic lesions are hard to differentiate especially for an untrained eye. However, carefully analyzing every aspect of the lesion can help clinicians reach an accurate diagnosis. If diagnosed correctly with the naked eye, many lesions can be treated without the need for further histopathology or investigations. Those aspects include morphology, color, distribution, configuration and arrangement, texture and consistency, and any evolutions or changes within the lesion. Clinicians must also contextualize those lesions into the patient’s history and overall systemic symptoms and signs. Risk factors should be taken into consideration and whether there are evolutionary changes in the lesions. Clinicians should also look for patterns as they might be the key to diagnosis. If definitive diagnosis is still not reached, biopsy, dermatoscopy, cultures, skin scrapings, patch testing, blood tests, and imaging studies may be necessary for confirmation. Integrating these methods with clinical judgment and patient history significantly enhances the accuracy of diagnosis in dermatology. Treatment for dermatologic lesions varies depending on the underlying cause.

Umbilical cord-derived mesenchymal stem cells (UC-MSCs) are reported to have features intermediate between fetal and adult mesenchymal cells. Hence, UC-MSCs were cocultured with chondrocytes and Schwann cells to induce differentiation because of their flexible differentiation potential. US-MSCs were obtained from umbilical cords and cells at second passage were used in the experiments. Atelocollagen sponge was used as the scaffold for coculture; a horizontal, interactive coculture plate with a 0.6-μm pore size filter was placed between the connected vessels. US-MSCs were cocultured separately with chondrocytes and Schwann cells and culture alone served as a control. Five weeks after induction of differentiation, each specimen was evaluated histologically. In specimens cocultured with chondrocytes and the controls, cartilage tissues were detected using hematoxylin-eosin and toluidine blue staining. Cells positive for S100 protein were detected in the specimens cocultured with Schwann cells, but not in the controls. UC-MSCs were easily induced to differentiate into chondrocytes and neural cells by coculture. This indicates that continuously-shared humoral factors were effective in inducing differentiation of UC-MSCs. Coculture appears to be a potential technique for tissue regeneration using MSCs.

Laser-targeted weeding methods further enhance the sustainable development of green agriculture, with one key technology being the improvement of weed localization accuracy. Here, we propose an improved YOLOv8 instance segmentation based on bidirectional feature fusion and deformable convolution (BFFDC-YOLOv8-seg) to address the challenges of insufficient weed localization accuracy in complex environments with resource-limited laser weeding devices. Initially, by training on extensive datasets of plant images, the most appropriate model scale and training weights are determined, facilitating the development of a lightweight network. Subsequently, the introduction of the Bidirectional Feature Pyramid Network (BiFPN) during feature fusion effectively prevents the omission of weeds. Lastly, the use of Dynamic Snake Convolution (DSConv) to replace some convolutional kernels enhances flexibility, benefiting the segmentation of weeds with elongated stems and irregular edges. Experimental results indicate that the BFFDC-YOLOv8-seg model achieves a 4.9% increase in precision, an 8.1% increase in recall rate, and a 2.8% increase in mAP50 value to 98.8% on a vegetable weed dataset compared to the original model. It also shows improved mAP50 over other typical segmentation models such as Mask R-CNN, YOLOv5-seg, and YOLOv7-seg by 10.8%, 13.4%, and 1.8%, respectively. Furthermore, the model achieves a detection speed of 24.8 FPS on the Jetson Orin nano standalone device, with a model size of 6.8MB that balances between size and accuracy. The model meets the requirements for real-time precise weed segmentation, suitable for complex vegetable field environments and resource-limited laser weeding devices.

Dried blood spot (DBS) testing on confetti is one of the most common methods used to collect and extract DNA from field samples for molecular epidemiology of malaria studies. Here, we investigated whether ethanol or other solutions used to clean scissors are a source of sample contamination. DBS were prepared from 3 drops of blood from two Plasmodium falciparum cultures spotted on confetti, and 3 solutions (water, ethanol and DNase) were used to clean scissors between spots during DNA extraction. For each cleaning solution, two blank confetti were used as negative controls. Samples were analyzed by PCR-based genotyping of merozoite surface proteins 1 & 2 (msp-1 and msp-2), and P. falciparum chloroquine resistance transporter (Pfcrt). A total of 15 samples were analyzed. Based on msp-1 and msp-2 amplification, P. falciparum was detected on blank confetti when scissors were washed with ethanol. Based on Pfcrt amplification, DNA of P. falciparum was detected on blank confetti when scissors were cleaned with ethanol or water. No P. falciparum genes were detected on blank confetti when scissors were cleaned with DNase. Scissors cleaned with DNase prevented cross-contamination between samples during processing of dried blood spots, whereas ethanol (which is commonly used) fails to avert cross-contamination.

Proprotein convertase subtilisin/kexin type 9 (PCSK9) is the key regulator of low-density lipoprotein cholesterol (LDL-C) plasma levels. We previously observed that treatment of dyslipidemic subjects with nutraceutical combination containing red yeast rice (monacolin K 3.3 mg), Berberis aristata cortex extract (Berberine 531.25 mg) and Morus alba leaves extract (1-deoxynojirimycin 4 mg) (LopiGLIK®) did not alter the plasma PCSK9 levels. Thus, the aim of the present study was to investigate the effect of these three components on PCSK9 expression in HepG2 cell line in relationship to their effects on LDL-C cellular uptake. HepG2 cell line were incubated with Berberis aristata cortex extract (BCE), red yeast rice (RYR) and Morus alba leaves extract (MLE) alone or in combination for 24 h. RYR (50 µg/mL) increased PCSK9 protein expression (WB and ELISA assays), PCSK9 mRNA and its promoter activity. BCE (40 µg/mL) reduced PCSK9 expression, mRNA levels and promoter activity. MLE determined a concentration-dependent inhibition of PCSK9 at mRNA and protein levels, with a maximal reduction at 1 mg/mL; no significant changes in PCSK9 promoter activity were found. MLE also downregulates the expression of fatty acid synthase and HMG-CoA reductase mRNA levels. The combination of RYR, BCE and MLE reduced PCSK9 at mRNA, protein, and promoter activity. Finally, this combination induced the LDL receptor and LDL-C uptake by HepG2 cells. In conclusion, the positive effect of MLE on PCSK9 supports the rational of using this nutraceutical combination to control hyperlipidemic conditions.

Tinnitus is a common phantom auditory percept, believed to be related to plastic changes in the brain due to hearing loss. However, tinnitus can also occur in absence of any clinical hearing loss. Then, since there is no hearing loss, the mechanisms that drive plastic changes remain largely enigmatic. Previous studies showed subtle differences in sound-evoked brain activity associated with tinnitus in subjects with tinnitus and otherwise, normal hearing, but the results are not consistent across studies. Here, we aim to investigate those differences using monaural rather than binaural stimuli. Sound-evoked responses were measured using functional magnetic resonance imaging (MRI) in participants with and without tinnitus. All participants had clinically normal audiograms. The stimuli were pure tones with frequencies between 353 and 8000 Hz, presented monaurally. A Principal Component Analysis (PCA) of the response in the auditory cortex revealed no difference in tonotopic organization, which confirmed earlier studies. A GLM analysis showed hyperactivity in the lateral areas of the bilateral auditory cortex. Consistent with the tonotopic map, this hyperactivity mainly occurred in response to low stimulus frequencies. This may be related to hyperacusis, which was associated with tinnitus found in the parahippocampus. This may reflect an interference between tinnitus and spatial orientation.

Objective: To investigate the effects and mechanisms of different concentrations of CCCP on mitophagy in human peripheral blood regulatory T cells. Methods: Tregs were isolated, identified and then grouped, treating with CCCP at a concentration of 2.5 μM, 5 μM, 10 μM, 20 μM and 40 μM for 24h in an incubator. Flow cytometry detected the reactive oxygen species (ROS), mitochondrial membrane potential (MMP), mitochondrial quality, and fluorescence microscopy observed the co-localization of mitochondria and lysosomes in each group. Results: The purity of CD4⁺CD25⁺Tregs was (93.36 ± 1.87) %. With the increase of CCCP concentration, the level of ROS gradually increased, while the MMP decreased gradually. About the mitochondria and lysosome fusion, the fluorescence intensity of orange (yellow) was the highest when the concentration of CCCP was in the range of 5-10 μM while decreased with the CCCP concentration continually increasing. The mitochondrial quality decreased with the increase of CCCP concentration. However, there was no significant difference between groups C, D and E. The mitochondrial quality of groups F and G were significantly lower than that of group E. Conclusions: With the concentration of CCCP gradually increased, the level of ROS in Treg cells increased, and MMP decreased, which promoted the mitophagy, mitochondrial quality maintains homeostasis; When ROS accumulated, and MMP decreased significantly, the mitophagy was inhibited, and the mitochondrial quality was significantly decreased.

Glucose is a simple sugar molecule. The sugar molecule is chemically symbolised as C6H12O6. This means that the glucose molecule contains 6 carbon atoms (C), 12 hydrogen atoms (H) and 6 oxygen atoms (O). In human blood, the molecule glucose circulates as blood sugar. Normally after eating or drinking, our body breaks down the sugars in food and uses them to obtain energy for our cells. To do this, our pancreas produces insulin. Insulin "pulls" sugar from the blood and puts it into the cells for use. If someone has diabetes, their pancreas can't produce enough insulin. As a result, the level of glucose in the blood rises. This can lead one to many potential complications, including blindness, disease, nerve damage, amputation, stroke, heart attack and damage to blood vessels etc. In this study, a non-invasive method for monitoring blood glucose has been developed and is therefore easily usable. The device developed can measure the glucose level continuously and eliminates the disadvantages of the invasive system. Near-IR sensors (optical sensors) were used to estimate the concentration of glucose in the blood; these sensors have a wavelength of 940 nm. The sensor is placed on the tip of the finger and the output of the optical sensor is then connected to the microcontroller at the analogue input. Another sensor used, but only to provide more medical information was the heartbeat sensor. After processing and regression analysis, the glucose level is predicted, and data is sent via the Bluetooth network to a developed APP. The results of the implemented device were compared with available invasive methods. The study consists of a hardware platform inserted into an armband and then a small black parallelepiped-shaped box in which the optical sensors are inserted. The hardware consists of a microcontroller, a Near-IR optical sensor, a heartbeat sensor and a Bluetooth module.

2-(Morpholin-4-yl)-4,5-bis(2’’,2’’,2’’-trinitroethoxy)-1,3,5-triazine having QSAR-predicted anti-tumor activity was tested for the cytotoxicity using MTT and LDH cell viability tests. The experiments were conducted using human fibroblasts, peripheral blood mononuclear cells and breast cancer cells and allowed to identify effective cytotoxic concentration ant therapeutic range of this compound. The data obtained suggest the feasibility of the further studies of the test compound as a potential anti-cancer agent.

Vitronectin is a glycoprotein, present in plasma and extracellular matrix, implicated in cell migration. The high amount of vitronectin found in neuroblastoma biopsies was associated with poor prognosis. However, there are almost no studies of vitronectin levels in neuroblastoma cell culture media nor in plasma of neuroblastoma patients. Vitronectin concentration in culture media of four neuroblastoma cell lines grown in monolayer and in 3D-models, and in plasma of 114 neuroblastoma patients, was quantified using ELISA. Three of the neuroblastoma cell lines secreted vitronectin to culture media when cultured in monolayer and 3D-models. Vitronectin release was higher by neuroblastoma cells cultured in 3D-models than in monolayer, and was still great when cells grown in 3D-scaffolds with cross-linked vitronectin. Vitronectin secretion occurred independently of cell numbers in cultures. Its concentration in plasma of neuroblastoma patients ranged between 52.4 and 870µg/mL (median, 218µg/mL). A ROC curve was used to establish a cutoff of 361µg/mL, above which patients over 18-months-old had worse prognosis (p=0.0018). Vitronectin could be considered a new plasma prognostic biomarker in neuroblastoma, and warrants confirmation in collaborative studies. Drugs inhibiting vitronectin interaction with cells and/or extracellular matrix could represent a significant improvement in survival for neuroblastoma patients.

Keywords: gut microbiota; small intestinal bacteria overgrowth; SIBO; diet, dysbiosis; microbial ecology.

Hyperspectral imaging, a rapidly evolving technique, furnishes exhaustive information on Earth's surface reflectance over an extensive spectrum of wavelengths. We have developed a more precise method for analyzing spectral data by meticulously selecting plant leaf pixels and employing a relative reference approach. This enhanced technique correlates camera pixel values with light intensity, bypassing the need for complex equations and thereby providing clearer insights into vegetation vitality. The findings of this study not only enhance the precision of hyperspectral imaging but also bolster our capability for ecological monitoring and understanding environmental health. A novel algorithm based on the red-edge slope was established to classify images, exploiting the spectral reflectance data gleaned from the hyperspectral Liquid Crystal Tunable Filter (LCTF) camera. Compared with conventional SVM and K-means algorithms, our novel algorithm demonstrated commendable performance, achieving an overall accuracy of 90% with a Kappa Coefficient of 0.86. This comparison highlights the novel algorithm's relative strength and potential for large-scale satellite and drone imagery analysis applications. The advancements facilitated by this research are instrumental in ecological assessments, conservation efforts, and resource management strategies, signaling a leap forward in the era of environmental monitoring and analysis.

Background: Monocyte-derived dendritic cells (mo-DCs) play a vital role in the innate immune response by activating Th17 cells, which in turn release the pro-inflammatory cytokine IL-17. We hypothesised that following repetitive mechanical strain, tenocytes activate monocyte-derived dendritic cells, which in turn, drive the pathogenesis of tendinopathy. Aim: The aim of the study was to determine if monocyte-derived dendritic cells are upregulated in a human tendinopathy model. Method: Torn supraspinatus tendon and matched intact subscapularis tendon samples were collected from 7 patients undergoing arthroscopic shoulder surgery. Healthy control samples of subscapularis tendon were collected from 5 patients undergoing arthroscopic stabilization surgery. Tendon biopsy samples were evaluated immunohistochemically by quantifying the presence of monocyte-derived dendritic cells (CD11C and CD206). Results: Tendinopathic tendon samples exhibited significantly greater (2-3-fold) monocyte-derived dendritic cell expression when compared with healthy control tissue (P &lt; .05). Conclusion: This study provides evidence for a monocyte-derived dendritic cell upregulation in early-stage human tendinopathy.

Cancer treatment with specific chemotherapeutic agents has been well documented to have an adverse impact on female fertility leading to premature ovarian failure (POF). The objective of this study was to investigate if chemotherapeutic induced POF can be reversed with an infusion of autologous nucleated peripheral blood cells (PBMC). To reach our goal, mice were treated with a single intraperitoneal injections of busulfan and cyclophosphamide to induce POF. This was followed by transfusion of PBMC. The ovarian morphology and functional parameters were monitored by radioimmunoassay, real-time PCR, immunofluorescence and immunohistochemistry analysis. Our study showed that chemotherapy (CTX) protracted estrous cycle period and repressed E2 production. CTX decreased the expressions of steroidogenesis markers- CYP-17 synthesis, StAR and Connexin-43 protein expression from the ovarian follicles. We also observed reduced numbers and sizes of the primordial and primary follicles in CTX-treated mice compared to untreated controls (P < 0.05). When both CTX and untreated –control groups were stimulated with gonadotrophin, the control group produced ten times more ova than the CTX group. Finally, the treatment of premature ovarian failure induced by CTX with autologous PBMC transfusion resulted in over-expression and a statistically significant increase in several stem cell markers and restoration of fertility. Infusion with PBMC in CTX further decreased the estrous cycle length by 2.5 times (P < 0.01). We found that transfusion of autologous PBMC to mice with chemotherapy induced POF was very effective at restoring fertility. These results are similar to other studies using bone marrow derived mesenchymal stem cells.