This concept paper gives a narrative about intelligence from insects to the human brain, showing where evolution may have been influenced by the structures in these simpler organisms. The ideas also come from the author's own cognitive model, where a number of algorithms have been developed over time and the precursor structures should be codable to some level. Through developing and trying to implement the design, ideas like separating the data from the function have become architecturally appropriate and there have been several opportunities to make the system more orthogonal. Similarly for the human brain, neural structures may work in-sync with the neural functions, or may be slightly separate from them. Each section discusses one of the neural assemblies with a potential functional result, that cover ideas such as timing or scheduling, structural intelligence and neural binding. Another aspect of self-representation or expression is interesting and may help the brain to realise higher-level functionality based on these lower-level processes.

Intramammary infections (mastitis) of dairy cows, along with other periparturient diseases, have become problematic within the dairy industry as they lead to loss of milk production. The main objective of this study was to determine whether elevated somatic cell counts (SCC) in cows prior to drying off are related to the incidence of other periparturient diseases. Additionally, we de-termined whether milk composition and milk yield are affected by a high SCC prior to drying off. Somatic cell counts of milk samples were determined prior to dry off (n = 140) and were used to classify cows in the study as high (>200,000 cells/mL) or low (<200,000 cells/mL) SCC. The com-position of milk was analyzed before drying off and at 1 and 2 weeks after calving. The results showed that an elevated SCC before drying off was related to the incidence of ketosis. Cows with a high SCC at drying off also showed an increased likelihood of retained placenta, metritis, and lameness postpartum; however, it was not statistically significant. Milk lactose was lower in cows with high SCC, while protein content was lower after parturition. Milk production was lower for cows with pre-drying elevated SCC, particularly for cows with retained placenta, keto-sis, and mastitis. In conclusion, cows with pre-drying elevated SCC were more likely to develop disease after parturition and produce less milk and with lower lactose and protein content.

Introduction. Recent studies revealed that differentiation of valvular interstitial cell into myofibroblasts played an important role in pathological valve remodeling in rheumatic valvular disease. Objective. To investigate effects of atorvastatin, olmesartan, and resveratrol on Transforming Growth Factor β1-induced fibrosis. Methods. Valvular interstitial cell was isolated from 12-weeks male New Zealand rabbit (Oryctolagus cuniculus). Culture cells was divided into 4 groups, control group, group I (0.5 mg/mL Atorvastatin), group II (100 nmol/L Olmesartan), group III (50 μM/L Resveratrol) and group IV (combinations). All group were exposed to 100 nM Transforming Growth Factor β1 for 24 hours. Results. Immunochemical staining demonstrated that cells were completely differentiated into myofibroblasts with mean expression of α-smooth muscle actin 24522.64±4566.994. Atorvastatin, olmesartan, resveratrol, and its combination significantly reduced α-smooth muscle actin expression (6823±1735.3, 6942.7±2455.9, 14176.2±3343.3, 5051.8±1612.2 respectively (p<0.001). Conclusion. Our data showed atorvastatin, olmesartan, resveratrol, and its combination significantly reduce Transforming Growth Factor β1-induced valvular fibrosis.

Hypoxia, a condition of low oxygenation frequently found in triple-negative breast tumors (TNBC), promotes extracellular vesicle (EV) secretion and favors cell invasion, a complex process in which cell morphology is altered, dynamic focal adhesion spots are created, and ECM is re-modeled. Here, we investigated the invasive properties triggered by TNBC-derived hypoxic small EV (SEVh) in vitro in cells cultured under hypoxic and normoxic conditions, using pheno-typical and proteomic approaches. SEVh characterization demonstrated increased protein abundance and diversity over normoxic SEV (SEVn), with enrichment in pro-invasive pathways. In normoxic cells, SEVh promotes invasive behavior through pro-migratory morphology, in-vadopodia development, ECM degradation and matrix metalloprotease (MMP) secretion. Pro-teome profiling of normoxic cells exposed to SEVh determined enrichment in metabolic processes and cell cycle, modulating cell health to escape apoptotic pathways. In hypoxia, SEVh was re-sponsible for proteolytic and catabolic pathway inducement, interfering with integrin availabil-ity and gelatinase expression. Overall, our results demonstrate the importance of hypoxic signal-ing via SEV in tumors for the early establishment of metastasis.

The ATP synthase is a mitochondrial complex embedded in the inner mitochondrial membrane. The enzyme is under the double genetic control of the mitochondrial DNA (mtDNA) and nuclear DNA (nDNA). Fatal human diseases have been associated with defects in ATP synthase (Complex V) activity linked to mtDNA or nDNA pathogenetic variants in genes encoding structural subunits or assembly factors. Mitochondrial post-translational modifications of key amino acids, reduced/increased subunit expression, or protein to protein ATP synthase interaction, are also some of the mechanisms involved in the age-related disease pathway. All the major neurodegenerative diseases: Parkinson’s, Alzheimer’s and motor neuron diseases such as Amyotrophic Lateral Sclerosis highlight an impaired ATP generation in a mechanism involving the permeability transition pore that triggers a cellular homeostasis failure responsible for different forms of regulated cell death. In this review, we will explore ATP synthase assembly and function in physiological and pathological conditions by referring to the recent cryo-EM studies and by exploring human diseases models.

Research Highlights: This study identified the cell cycle genes in birch that likely play important roles during plant growth and development. This analysis provides a basis for understanding the regulatory mechanism of various cell cycles in Betula pendula. Background and Objectives: The cell cycle factors not only influence cell cycle progression together, but also regulate accretion, division and differentiation of cells, and then regulate growth and development of plant. In this study, we identified the putative cell cycle genes in B. pendula genome, based on the annotated cell cycle genes in A. thaliana. It could serve as a foundation for further functional studies. Materials and Methods: The transcript abundance was determined for all the cell cycle genes in xylem, root, leaf and flower tissues using RNA-seq technology. Results: We identified 59 cell cycle gene models in the genome of B. pendula, 17 highly expression genes among them. These genes were BpCDKA.1, BpCDKB1.1, BpCDKB2.1, BpCKS1.2, BpCYCB1.1, BpCYCB1.2, BpCYCB2.1, BpCYCD3.1, BpCYCD3.5, BpDEL1, BpDpa2, BpE2Fa, BpE2Fb, BpKRP1, BpKRP2, BpRb1 and BpWEE1. Conclusions: We identified 17 core cell cycle genes in the genome of birch by combining phylogenetic analysis and tissue specific expression data.

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.

Human Rhinovirus (HRV) is the most common cause of upper respiratory infections and exacerbations of asthma. In this work, we selected 14 peptides (6 from HRV A and 8 from HRV C) encompassing potential CD4 T cell epitopes. Peptides were selected for being highly conserved in HRV A and C serotypes and predicted to bind to multiple HLA II molecules. We found positive T cell recall responses by IFNγ-ELISPOT assays to 8 peptides, validating 7 of them (3 from HRV A and 4 from HRV C) as CD4 T cell epitopes through intracellular cytokine staining assays. Additionally, we verified their promiscuous binding to multiple HLA II molecules by quantitative binding assays. According to their experimental HLA II binding profile, the combination of all these 7 epitopes could be presented and recognized by > 95 % of the world population. We actually determined IFNγ responses to a pool encompassing these CD4 T cell epitopes by intracellular cytokine staining, finding positive responses in 29 out of 30 donors. The CD4 T cell epitopes identified in this study could be key to monitor HRV infections and to develop peptide-based vaccines against most HRV A and C serotypes.

Acute myeloid leukemia (AML) is a hematological cancer with poor outcomes due to a lack of efficacious targeted therapies. The Nuclear Factor of Activated T Cells (NFAT) family of transcription factors is well characterized as a regulator of the cell cycle and differentiation in the myeloid lineage. Recent evidence has demonstrated that NFAT family members may have roles in regulating AML leukemogenesis and resistance to targeted therapy in myeloid leukemias. Furthermore gene expression data from patient samples show that some NFATs are more highly expressed in poorly differentiated AML and after disease relapse, implying that the NFAT family may have roles in specific types of AML. This review outlines the evidence for the role of NFAT in healthy myeloid tissue and explores how NFAT might regulate AML pathogenesis, highlighting the potential to target specific NFAT proteins therapeutically in AML.

Track-structure Monte Carlo simulations are useful tools to evaluate initial DNA damage induced by irradiation. In the previous study, we have developed a Gean4-DNA-based application to estimate the cell surviving fraction of V79 cells after irradiation, bridging the gap between the initial DNA damage and the DNA-rejoining kinetics by means of the two-lesion kinetics (TLK) model. However, since the DNA repair performance depends on cell line, the same model parameters cannot be used for the different cell lines. Thus, we extended the Geant4-DNA application with an updated TLK model for the evaluation of DNA damage repair performance in HSGc-C5 carcinoma cells which are typically used for evaluating proton/carbon radiation treatment effects. For this evaluation, we also performed experimental measurements for cell surviving fractions and DNA-rejoining kinetics of the HSGc-C5s cells. Concerning fast- and slow-DNA rejoining, the TLK model parameters were adequately optimized with the simulated initial DNA damage. Using the optimized TLK model, the Geant4-DNA simulation is now able to predict cell survival and DNA-rejoining kinetics for HSGc-C5s cells.

It was the aim of this study to provide a more precise timeframe of development of the gonads and genital ducts in the equine fetus around the time of sexual differentiation. This included the identification and localisation of the primordial germ cell population. Equine fetuses between 45 and 60 days of gestation were evaluated using a combination of micro-computed tomography scanning, immunohistochemistry, and multiplex immunofluorescence. Fetal gonads increased in size by 23-fold from 45 to 60 days of gestation, paralleled by a greater increase in metanephros volume. Signs of mesonephros atrophy were detected during this time. Tubular structures of the fetal testes were present from day 50 onwards, whereas cell clusters dominated in the fetal ovary. The genital ducts were well-differentiated and presented a lumen in all samples. No sign of mesonephric or paramesonephric duct degeneration was detected. Expression of AMH was strong in the fetal testes but absent in ovaries. Irrespective of sex, primordial germ cells selectively expressed LIN28. Migration of primordial germ cells from the mesonephros to the gonad was detected at 45 days, but not at 60 days of development. Their number and distribution within the gonad were influenced (p&lt;0.05) by fetal sex. Most primordial germ cells (86.8 ± 3.2% in females and 84.6 ± 4.7% in males) were characterized as pluripotent according to co-localization with CD117. However, only a very small percentage of primordial germ cells was proliferating (7.5 ± 1.7% in females and 3.2 ± 1.2% in males) based on co-localization with Ki67. It can be concluded that gonadal sexual differentiation in the horse occurs asynchronously with regard to sex but already before 45 days of gestation.

A fundamental question in biology is how cell shapes are genetically encoded and enzymatically generated. Prevalent shapes among walled bacteria include spheres and rods. These shapes are chiefly determined by the peptidoglycan (PG) cell wall. Bacterial division results in two daughter cells, whose shapes are predetermined by the mother. This makes it difficult to explore the origin of cell shapes in healthy bacteria. In this review, we argue that the Gram-negative bacterium Myxococcus xanthus is an ideal model for understanding PG assembly and bacterial morphogenesis because it forms rods and spheres at different life stages. Rod-shaped vegetative cells of M. xanthus can thoroughly degrade their PG and form spherical spores. As these spores germinate, cells rebuild their PG and reestablish rod shape without preexisting templates. Such a unique sphere-to-rod transition provides a rare opportunity to visualize de novo PG assembly and rod-like morphogenesis in a well-established model organism.

When swine flu vaccines and circulating influenza A virus (IAV) strains are poorly matched, vaccine-induced antibodies may not protect from infection. Highly conserved T cell epitopes may, however, have a disease-mitigating effect. The degree of T cell epitope conservation among circulating strains and vaccine strains can vary, which may also explain differences in vaccine efficacy. Here, we evaluate a previously developed conserved T cell epitope-based vaccine and determine the persistence of T cell epitope conservation over time. We used a pair-wise homology score to define conservation between the vaccine’s swine leukocyte antigen (SLA) class I and II-restricted epitopes and T cell epitopes found in 1,272 swine IAV strains sequenced between 2013 and 2017. Twenty-four of the 48 total T cell epitopes included in the epitope-based vaccine were highly conserved and found in >1,000 circulating swine IAV strains over the five-year period. In contrast, commercial swine IAV vaccines developed in 2013 exhibited declining conservation with the circulating IAV strains over the same five-year period. Conserved T cell epitope vaccines may be useful adjunct for commercial swine flu vaccines and to improve protection against influenza when antibodies are not cross-reactive.

The aim of this work was to evaluate the influence of various food and beverages on the viability of probiotic bacteria during passing through artificial digestion. As a model food, solutions with various concentrations of alcohol, sugar, salt, protein and acid were prepared. Different types of real foods and beverages were used as well. Viability in presence of food matrices was tested on monocultures of Lactobacillus acidophilus CCM4833 and Bifidobacterium breve CCM7825T and on mixed commercial culture with 9 different strains of probiotic microorganisms( Lactobacillus, Bifidobacterium, Streptococcus). The concentration and viability of probiotic bacteria was tested by cultivation assay and flow cytometry. In model foods, the best growth of was determined in the presence of 10% albumin and 10% ethanol. Survival of the probiotics delivered in different food matrices through a simulated gastrointestinal tract was quantitatively different. As the best food environment for probiotics complex food matrices such as pasta with cream sauce, chocolate spread and homemade beef broth were selected, followed by mixed vegetables, potato salad, salted chips, fruits and yoghurt. Among beverages the best option was milk, followed by black tea, coffee and Coca Cola. Probiotic microorganisms are more viable when consumed with meals than with beverages only. In general, the highest viability of probiotic cells has been observed in presence of foods containing high concentration of sugar and fat or their suitable combination. The increase of cell viability observed in such foods during model digestion may further contribute to the positive effect of probiotics on human health.

Single cell proteins are the dead dried cells of microorganisms or purified protein isolated from microorganism’s cell culture, used as a food supplement to humans’ food and animals feed. World suffer from malnutrition particularly developing countries, due to rapid increase in population, increased the demand for protein and nutrients requirement. Bacteria is potential microorganism for SCP production due to high protein content, fast generation time, bio-active secondary metabolites production and can grow on various substrates. Actinobacteria species and strain have capability to produce biological active compounds, produced about two-thirds of antibiotics available in the market, actively used as antibiotics, antiprotozoal, antifungal, antiviral, anticancer, anticholesterol, antihelminth and immunosuppressant. Actinomycetes can be used as probiotic as well as single cell protein that will deal with antibiotic as well as protein source.

Cancer is a leading cause of death worldwide. It is theorized that underlying genetic and epigenetic changes enable cells to proliferate out of control by escaping regulatory mechanisms. The progression of cancer is associated with increased cell proliferation, metabolic modifications, resistance to apoptosis, genetic instability, induction of angiogenesis and augmented migratory capability. Recent developments in DNA and RNA analysis have made it possible to study these genetic changes systematically. These advances have enabled us to possess a deeper knowledge of the signaling pathways and involved processes. In-depth studies of the pathways involved in carcinogenesis have led to the identification of pathways that may be targeted for therapeutic purposes. In this review, we provide an overview of the relevant mechanisms and pathways involved in the development and progression of cancer.

Cancer is a leading cause of death worldwide. It is theorized that underlying genetic and epigenetic changes enable cells to proliferate out of control by escaping regulatory mechanisms. The progression of cancer is associated with increased cell proliferation, metabolic modifications, resistance to apoptosis, genetic instability, induction of angiogenesis and augmented migratory capability. Recent developments in DNA and RNA analysis have made it possible to study these genetic changes systematically. These advances have enabled us to possess a deeper knowledge of the signaling pathways and involved processes. In-depth studies of the pathways involved in carcinogenesis have led to the identification of pathways that may be targeted for therapeutic purposes. In this review, we provide an overview of the relevant mechanisms and pathways involved in the development and progression of cancer.

Durability and performance of electrochemical energy converters such as fuel cells and electrolysers are not only dependent on the properties and the quality of the used materials. They strongly depend on operation conditions. Variations in external parameters, such as flow, pressure, temperature and, obviously, load can lead to significant local changes of current density, even local transients. The segmented cell technology was developed with the purpose to gain insight into local operation conditions in electrochemical cells, during operation. The operando measurement of the local current density and temperature distribution allows effective improvement of operation conditions, mitigation of potentially critical events and assessment of the performance of new materials. The segmented cell, which can replace a regular bipolar plate in the current state of the technology, can be used as monitoring tool and for targeted developments. This article gives an overview over the development and applications for proton exchange membrane fuel cell of this technology, such as water management or fault recognition. Recent advancements towards locally resolved monitoring of humidity and to current distributions in electrolysers are outlined.

Due to low working temperature, high energy density and low pollution, proton exchange fuel cells have been investigated under different operating conditions in different applications. Using platinum catalysts in methanol fuel cells leads to increasing the cost of this kind of fuel cell which is considered as a barrier to the commercialism of this technology. For this reason, a lot of efforts have been made to reduce the loading of the catalyst required on different supports. In this study, carbon black (CB) and carbon nanotubes (CNT) have been used as catalyst supports of the fuel cell as well as using the double-metal combination of platinum-ruthenium (PtRu) as anode electrode catalyst and platinum (Pt) as cathode electrode catalyst. The performance of these two types of electro-catalyst in the oxidation reaction of methanol has been compared based on electrochemical tests. Results showed that the carbon nanotubes increase the performance of the micro-fuel cell by 37% at maximum power density, compared to the carbon black. Based on thee-electrode tests of chronoamperometry and voltammetry, it was found that the oxidation onset potential of methanol for CNT has been around 20% less than CB, leading to the kinetic improvement of the oxidation reaction. The current density of methanol oxidation reaction increased up to 62% in CNT sample compared to CB supported one, therefore the active electrochemical surface area of the catalyst has been increased up to 90% by using CNT compared to CB which shows the significant rise of the electrocatalytic activity in CNT supported catalyst. Moreover, the resistance of the CNT supported sample to poisonous intermediate species has been found 3% more than CB supported one. According to the chronoamperometry test results, it was concluded that the performance and sustainability of the CNT electro-catalyst show remarkable improvement compared to CB electro-catalyst in the long term.

The cell’s capacity to integrate and respond to spatial information is a crucial feature of morphogenesis and development. The Planar Cell Polarity (PCP) pathway is a signaling mechanism, widely conserved across metazoans, providing spatial orientation along the plane of an epithelium in morphogenic processes ranging from insect wing patterning to mammalian cochleae. Although the core genes involved in the PCP pathway have been molecularly identified in the 1990s, the PCP signaling mechanism remains controversial. In this article I discuss the main players and previous models of PCP signaling reported in the literature, and propose a new model. According to it PCP is established through an homophobic signal by transmembrane protein Frizzled (Fz): 1) a Fz signal in one cell repeals Fz itself in the adjacent cell, thereby generating symmetry breaking; 2) the instructive PCP signal is conveyed through Fz interaction with atypical cadherin Flamingo (Fmi). More broadly, homophobic signaling may represent a novel mechanism for cell-cell signaling of spatial information through modulation of cell adhesion rather than canonical ligand-receptor binding.

This study proposes a new algorithm termed rain cell identification and tracking (RCIT) to identify and track rain cells from high resolution weather radar data. Previous algorithms have limitations when tracking non-consequent rain cells owing to their use of maximum correlation coefficient methods and their lack of an alternative way to handle the variation stages of rain cells during their life cycles. To address these deficiencies, various methods are implemented in the new algorithm. These include the particle image velocimetry (PIV) method for motion estimation and the rain cell matching rule to obtain the stage changes of rain cells. High resolution (5-min and 1-km) radar reflectivity data from three rainy days over the German federal state North Rhine Westphalia (NRW) are used to evaluate the proposed algorithm. The performance of the new algorithm is compared with a radar reflectivity map and verified by two object-oriented methods: structure–amplitude–location (SAL) and geometric index. The verification results suggest that the performance of the new algorithm is good. Application of the RCIT algorithm to the selected cases shows that the inner structure of rainfall events in the experimental region present extreme value distributions, with most rainfall events having a short duration with less intensity. The new algorithm can effectively capture the stage changes of rain cells during their life cycles. The proposed algorithm can serve as the basis for further hydro-meteorological applications such as spatial and temporal analysis of rainfall events and short-term flood forecasting.

The study was done to determine the effect of supplementing different forms of L-methionine (L-Met) and acetate on protein synthesis in immortalized bovine mammary epithelial cell line (MAC-T Cell): Control, L-Met, conjugated L-Met and acetate (CMA), and non-conjugated L-Met and Acetate (NMA). Protein synthesis mechanism was determined by omics method. NMA group had the highest protein content in the media and β-casein mRNA expression levels (P < 0.05). The number of upregulated and downregulated proteins observed were 77 and 62 in CMA group and 50 and 81 in NMA group from 448 proteins, respectively (P < 0.05). NMA and CMA treatments stimulated pathways related to protein and energy metabolism (P < 0.05). Metabolomic analysis also revealed CMA and NMA treatments resulted in increases of several metabolites (P < 0.05). In conclusion, NMA treatment increased protein concentration and expression level of β-casein mRNA in MAC-T cells compared to CMA.

The cell case temperature versus time profiles of a multistage fast charging technique (4C-1C-CV)/fast discharge (4C) in a 2.3 Ah cylindrical lithium-ion cell are analyzed using a 1D thermal model. Heat generation is dominated by the irreversible component associated to cell overpotential, although evidences of the reversible component are also observed, associated to the heat related to entropy from the electrode reactions. The final charging stages (i.e., 1C-CV) significantly reduce heat generation and cell temperature during charge, resulting in a thermally safe charging protocol. Cell heat capacity was determined from cell specific heats and cell materials thickness. The 1D model adjustment of the experimental data during the 2 min. resting period between discharge and charge allowed us to calculate both the time constant of the relaxation process and the cell thermal resistance. The obtained values of these thermal parameters used in the proposed model are almost equal to those found in the literature for the same cell model, which suggests that the proposed model is suitable for its implementation in thermal management systems.

Introduction Image Guided Superficial Radiation Therapy (IGSRT) is a novel technology which combines traditional superficial radiation therapy (SRT) with high resolution dermal ultrasound (HRDUS) to treat non-melanoma skin cancers (NMSC). Since development, IGSRT use has expanded dramatically in outpatient clinics. We review the IGSRT literature and state of the art operating principles in US dermatologic practices. Materials and Methods A literature search of electronic databases (Medline, Pubmed, Cochrane Library, Science Direct) combined with various authors’ published and unpublished documents, procedures and clinical experience with IGSRT were synthesized for this paper. Results Studies have demonstrated IGSRT consistently delivers high cure rates( >99%) with low complications for early stage (stage 0, I, or II) squamous cell and basal cell carcinomas. Control rates are statistically superior to non-image guided SRT and external beam radiation (XRT) as well as Mohs Micrographic Surgery(MMS). This improvement is attributed to in-vivo dermal tumor visualization via HRDUS and using an interdisciplinary approach to deliver care. IGSRT use in the dermatologic clinic for early stage NMSCs has become common practice and continues to expand. Conclusion While the safety and cosmetic benefits of SRT/XRT has been long documented, IGSRT represents a significant leap forward in efficacy (statistically significant) by adding in-vivo dermal tumor imaging. Results rival and appear on one study to surpass tumor control obtained with MMS. A contributing factor to the success may be the availability and use of an interdisciplinary team approach that includes dermatologists, radiation therapists, radiation oncologists and medical physicists. The high tumor control rates, minimal side effects, favorable cosmesis and ability to treat multiple lesions per session using IGSRT is establishing this modality as a standard first line therapy for early stage NMSCs in dermatology clinics. IGSRT may represent the most effective option for the non-surgical treatment of early stage NMSC to date.

This study aimed (1) to map the immunogenic epitopes (B and T cells) within the major BCoV structural proteins. These epitopes are believed to induce a robust im-mune response through the interaction with major histocompatibility complex (MHC class II) molecules (2) to design some novel BCoV multi-epitope-based vac-cines. To achieve these goals, we applied several integrated In-silico prediction computational tools to map these epitopes within the major BCoV structural pro-teins. The predicted epitopes were linked to some immunostimulants such as Toll-like receptors-2 (TLR2) and TLR-4. The tertiary structure of each epitope was modeled through the Alpha fold-2 colab machine learning tools. The stability and purity of each epitope were assessed using the Ramachandran plot and the Z Score values. Each multiepitope-based vaccine candidate conjugated with the Chlorotox-in B toxin as an adjuvant. We designed the vaccine constructs using various expres-sion vectors. We also predicted the affinity binding of these vaccines with the target protein using molecular docking. Our designed multiepitope vaccine candidates per each BCoV structural protein showed high antigenicity, immunogenicity, non-allergic, non-toxic, and high water solubility. Further studies are highly en-couraged to validate the efficacy of these novel BCoV vaccines in the natural host.

Fluorescent bioprobes are invaluable tools for visualizing live cells and deciphering complex biological processes by targeting intracellular biomarkers without disrupting cellular functions. In addition to protein-binding concepts, fluorescent probes utilize various mechanisms, including membrane, metabolism, and gating-oriented strategies. This study introduces a novel fluorescent mechanism distinct from existing ways. Here, we developed a B-cell selective probe, CDrB, with unique transport mechanisms. Through SLC-CRISPRa screening, we identified two transporters, SLCO1B3 and SLC25A41, by sorting out populations exhibiting higher and lower fluorescence intensities, respectively, demonstrating contrasting activities. We confirmed that SLCO1B3, with comparable expression levels in T and B cells, facilitates the transport of CDrB into cells, while SLC25A41, overexpressed in T lymphocytes, actively exports CDrB. The observation suggests that SLC25A41 plays a crucial role in discriminating between T and B lymphocytes. Furthermore, it reveals the potential for reversible localization of SLC25A41 to demonstrate its distinct activity. This study is the first report to unveil a novel strategy of SLC by exporting the probe. We anticipate that this research will open up new avenues for developing fluorescent probes.

Background: Renal cancers are among the top ten causes of cancer-specific mortality, of which the ccRCC subtype is responsible for most cases. The grading of ccRCC is important in determining tumour aggressiveness and clinical management. Objectives: The objectives of this research were to predict the WHO/ISUP grade of ccRCC pre-operatively and characterise the heterogeneity of tumour sub-regions using radiomics and ML models, including comparison with pre-operative biopsy-determined grading in a sub-group. Methods: Data were obtained from multiple institutions across two countries, including 391 patients with pathologically proven ccRCC. For analysis, the data were separated into four cohorts. Cohorts 1 and 2 included data from the respective institutions from the two countries, cohort 3 was the combined data from both cohort 1 and 2, and cohort 4 was a subset of cohort 1, for which both the biopsy and subsequent histology from resection (partial or total nephrectomy) were available. 3D image segmentation was carried out to derive a voxel of interest (VOI) mask. Radiomics features were then extracted from the contrast-enhanced images, and the data were normalised. The Pearson correlation coefficient and the XGBoost model were used to reduce the dimensionality of the features. Thereafter, 11 ML algorithms were implemented for the purpose of predicting the ccRCC grade and characterising the heterogeneity of sub-regions in the tumours. Results: For cohort 1, the 50% tumour core and 25% tumour periphery exhibited the best performance, with an average AUC of 77.9% and 78.6%, respectively. The 50% tumour core presented the highest performance in cohorts 2 and 3, with average AUC values of 87.6% and 76.9%, respectively. With the 25% periphery, cohort 4 showed AUC values of 95.0% and 80.0% for grade prediction when using internal and external validation, respectively, while biopsy histology had an AUC of 31.0% for the classification with the final grade of resection histology as a reference standard. The CatBoost classifier was the best for each of the four cohorts with an average AUC of 80.0%, 86.5%, 77.0% and 90.3% for cohorts 1, 2, 3 and 4 respectively. Conclusion: Radiomics signatures combined with ML have the potential to predict the WHO/ISUP grade of ccRCC with superior performance, when compared to pre-operative biopsy. Moreover, tumour sub-regions contain useful information that should be analysed independently when determining the tumour grade. Therefore, it is possible to distinguish the grade of ccRCC pre-operatively to improve patient care and management.

Clear cell renal cell carcinoma (ccRCC) is the most prevalent form of renal cancer and its treatment is hindered by resistance to targeted and immunotherapies and combinations ob both. We have reported that knockdown of the antisense noncoding mitochondrial RNAs (ASncmtRNAs) with chemically-modified antisense oligonucleotides induces proliferative arrest and apoptotic death in tumor cells from many human and mouse cancer types. These studies have been mostly performed in vitro and in vivo on commercially-available cancer cell lines and have shown that, in mouse models, tumor growth is stunted by the treatment. The present work was performed on cells derived from primary and metastatic ccRCC tumors. We established primary cultures fom primary and metastatic ccRCC tumors, which were subjected to knockdown of ASncmtRNAs in vitro and in vivo in an orthotopic xenograft model in NOD/SCID mice. We found that these primary ccRCC cells are affected in the same way as tumor cell lines and, in the orthotopic model, tumor growth was significantly reduced by the treatment. This study on patient-derived ccRCC tumor cells represents a model closer to actual patient ccRCC tumors and shows that knockdown of ASncmtRNAs poses a potential treatment option for these patients.

Standard Non-Melanoma Skin Cancer (NMSC) treatment involves surgery, recently combined with chemotherapy or immunotherapy in case of advanced tumors. Exosomes, integral to carcinogenesis, are found in NMSC, releasing mediators impacting tumor progression. Nevertheless, the precise intercellular signaling role of NMSC-derived exosomes remains unclear. This review aims to elucidate their potential role in NMSC diagnosis and treatment. A systematic review encompassed literature searches in electronic databases from inception to September 2023, based on certain inclusion and exclusion criteria, addressing NMSC-derived exosomes, their molecular cargo and their implications in the diagnosis, prognosis, and treatment of NMSC. Key components were identified. Extracellular vesicle (EV) proteins and RNA emerged as diagnostic biomarkers in EV-based liquid biopsy. Circular RNA CYP24A1, known for its molecular stability, holds promise as a diagnostic biomarker. Long noncoding RNAs (lincRNA-PICSAR) and Desmoglein 2 (DSg2) are linked to drug resistance, serving as prognostic biomarkers. EV mediators are actively investigated for their potential role as drug delivery agents. In conclusion, this systematic review showed that NMSC-derived EVs display promise as therapeutic targets and diagnostic biomarkers. Further research is imperative to fully comprehend exosome mechanisms and explore their potential in cancer diagnosis and treatment.

Small cell lung cancer (SCLC) and large cell neuroendocrine carcinoma (LCNEC) have recently been grouped as lung neuroendocrine carcinomas (NECs). Because these lung NECs are clinically malignant and their treatment strategies differ from those of non-SCLC, the quality of diagnosis has a significant prognostic impact. The diagnosis of LCNEC requires positive immunohistochemical staining with chromogranin A, synaptophysin, and CD56, along with morphological diagnosis, and insulinoma-associated protein 1 (INSM1) has been proposed as an additional marker but sometimes experience difficulty in making the diagnosis. We investigated Musashi-1 as a novel immunohistochemical marker in 42 patients with SCLCs and 44 with LCNECs who underwent lung resection between 1998 and 2020 at our institution. We found Musashi-1 expression in 41 (98%) of 42 SCLCs and 40 (90%) of 44 LCNECs. These findings were similar to CD56 expression and superior to synaptophysin, chromogranin A, and INSM1. Musashi-1 also tended to show more diffuse and intense staining, especially in LCNEC, with more cases staining &gt;10% than any other existing markers (Musashi-1, 77%; INSM1, 45%; chromogranin A, 34%; synaptophysin, 41%; and CD56, 66%). In conclusion, we identified Musashi-1 as a novel immunohistochemical staining marker to aid in the diagnosis of lung NEC.

One of the most common subgroups of cutaneous T-cell lymphomas is the that of primary cutaneous CD30 positive lymphoproliferative disorders. The group includes lymphomatoid papulosis (LyP) and primary cutaneous anaplastic large cell lymphoma (pcALCL), as well as some borderline cases. Recently, significant progress has been made in understanding the genetics and treatment of these disorders. This review article summarizes the clinical evidence supporting the current treatment options in these diseases. Recent years have seen the introduction of novel agents into clinical practice; most of these target CD30, such as anti-CD30 monoclonal antibodies and conjugated antibodies (brentuximab vedotin), bispecific antibodies and cellular therapies, particularly anti-CD30 CAR-T cells. This paper briefly reviews the biology of CD30 that makes it a good therapeutic target, and describes the anti-CD30 therapies that have emerged to date.

Tendons and ligaments injuries are frequent in sport horses and humans, representing a great therapeutic challenge. Tissue regeneration and function recovery are the paramount of tendon and ligament lesions management. Nowadays, several regenerative treatments are being developed, based on the use of stem cell and stem cell-based therapies. In the present study, the preparation of equine synovial membrane mesenchymal stem cells (eSM-MSCs) for clinical use - collection, transport, isolation, differentiation, characterization, and application is described. These cells are fibroblast-like and grow in clusters. They retain an osteogenic, chondrogenic and adipogenic differentiation potential. 16 clinical cases of tendonitis and desmitis, treated with allogenic eSM-MSCs and autologous serum are also presented, including their evaluation, treatment and follow-up. The use of autologous serum as a vehicle concern to a decreased immunogenic response after the administration of this combination and to its healing properties, due to the presence of growth factors and immunoglobulins. Most of the cases (14/16), healed in 30 days and presented a good outcome. Treatment of tendon and ligament lesions with the mixture of eSM-MSCs and autologous serum appears to be a promising clinical option for this category of lesions in equine patients.

The peril of a 3-dimensional, robust and sustained myocardial restoration by means of Tissue Engineering is that it still remains a largely experimental approach. Prolific protocols have been developed and tested in small and large animals, but as clinical cardiac surgeons, we have not come to the privilege of utilizing any of them in our clinical practice. The question arises: why? The heart is a unique organ, anatomically and functionally. It is not an easy target to replicate with current techniques, or even to support its viability and function. Currently available therapies fail to reverse the loss of functional cardiac tissue, the fundamental pathology remains unaddressed and a heart transplantation is an ultima ratio treatment option. Owing to equivocal results of cell-based therapies, several strategies have been pursued to overcome limitations of the current treatment options. Preclinical data as well as first-in-human studies conducted to date have provided important insights into the understanding of injection-based approaches for myocardial restoration. In the light of the available data, injectable biomaterials suitable for transcatheteter delivery appear to have the highest translational potential,. This article presents a current state-of-the-art in the field of hydrogel-based myocardial restoration therapy.

Cellular agriculture is defined as the production of agricultural products from cell cultures rather than from whole plants or animals. With growing interest in cellular agriculture as a means to address the public health, environmental, and animal welfare challenges of animal agriculture, the concept of producing seafood from fish cell- and tissue-cultures is emerging as a means to address similar challenges with industrial aquaculture systems and marine capture. Cell-based seafood - as opposed to animal-based seafood - can combine developments in biomedical engineering with modern aquaculture techniques. Biomedical engineering developments such as closed-system bioreactor production of land animal cells create a basis for large scale production of marine animal cells. Aquaculture techniques such as genetic modification and closed system aquaculture have achieved marked gains in production that can pave the way for innovations in cell-based seafood production. Here, we present the current state of innovation relevant to the development of cell-based seafood across multiple species as well as specific opportunities and challenges that exist for advancing this science. The authors find that the physiological properties of fish cell- and tissue- culture may be uniquely suited to cultivation in vitro. These physiological properties, including hypoxia tolerance, high buffering capacity, and low-temperature growth conditions, make marine cell culture an attractive opportunity for scale production of cell-based seafood; perhaps even more so than mammalian and avian cell cultures for cell-based meats. This, coupled with the unique capabilities of crustacean tissue-friendly scaffolding such as chitosan, a common seafood waste product and mushroom derivative, presents great promise for cell-based seafood production via bioreactor cultivation. To become fully realized, cell-based seafood research will require more understanding of fish muscle culture and cultivation; more investigation into serum-free media formulations optimized for fish cell culture; and bioreactor designs tuned to the needs of fish cells for large scale production.

The anode of a microbial fuel cell (MFC) was formed on a graphite electrode and immobilized Gluconobacter oxydans VKM-1280 bacterial cells. Immobilization was performed in chitosan, poly(vinyl alcohol) or N-vinylpyrrolidone-modified poly(vinyl alcohol). Ethanol was used as substrate. The anode was modified using multiwalled carbon nanotubes. The aim of the modification was to create a conductive network between cell lipid membranes, containing exposed PQQ-dependent alcoholdehydrogenases, and the electrode to facilitate electron transfer in the system. The bioelectrochemical characteristics of modified anodes at various cell/polymer ratios were assessed via current density, power density, polarization curves and impedance spectres. MFCs based on chitosan at a matrix/cell volume ratio of 5:1 produced maximal power characteristics of the system (8.3 μW/cm2) at a minimal resistance (1111 Ohm cm2). Modification of the anode by multiwalled carbon nanotubes led to a slight decrease of internal resistance (down to 1078 Ohm cm2) and to an increase of generated power density up to 10.6 μW/cm2. We explored the possibility of accumulating electric energy from an MFC on a 6,800-μF capacitor via a boost converter. Generated voltage was increased from 0.3 V up to 3.2 V. Accumulated energy was used to power a Clark-type biosensor and a bluetooth transmitter with three sensors, a miniature electric motor and a light-emitting diode.

Breast cancer treatment mostly revolved around radiation therapy and surgical interventions, these treatments doesn’t provide satisfactory relief to the patients and carry unmanageable side-effects. Nanomaterials show promising results in treating cancer cells and have many advantages such as high biocompatibility, bioavailability and effective therapeutic capabilities. Interestingly, fluorescent magnetic nanoparticles have been used in many biological and diagnostic applications, but there is no report of use of fluorescent magnetic submicronic polymer nanoparticles (FMSP-nanoparticles) in the treatment of human breast cancer cells. In the present study, we have tested the effect FMSP-nanoparticles on human breast cancer cells (MCF-7). We have tested different concentrations (1.25µg/1mL, 12.5µg/mL and 50µg/1mL) of FMSP-nanoparticles in MCF-7 cells and evaluated the nanoparticles response morphometrically. Our results revealed that FMSP-nanoparticles produced a concentration dependent effect on the cancer cells, dose of 1.25µg/mL produced no significant effect on the cancer cell morphology and cell death, whereas dosages of 12.5µg/mL and 50µg/mL respectively showed significant nuclear augmentation, disintegration, chromatic condensation followed by dose dependent cell death. Our results demonstrate FMSP-nanoparticles have ability to induce cell death in MCF-7 cells and may be considered as a potential anti-cancer agent for breast cancer treatments.

As the use of AI in medical imaging has increased, so has the need to explain a model’s results. Segmentation models are one technique used to produce explainable results. Due to larger size and sophistication, segmentation models which operate on 2D data can often produce better results than models operating on 3D data. In the real world, imaging is combined with clinical factors for diagnosis. To replicate this, multimodal models are used which combine image and text modalities. I propose a multimodal arrangement that converts 3D scans to 2D and uses a 2D segmentation model (DeepLabV3) to analyze the images. This is combined with clinical biomarkers to achieve a complete confidence score. Using the Medical Segmentation Decathlon Lung (MSDL) dataset and the LUng CAncer Screening dataset (LUCAS), I achieved a testing Dice coefficient of 0.91 on segmentation with a receiver operating characteristic (ROC), average precision (AP), and F-Score of 0.89, 0.91, and 0.85 respectively on the final multimodal results. This approach raises the F-score from the previously achieved value of 0.508 to 0.85, creating a new baseline of what is achievable with multimodal lung cancer diagnostics and possible methods to achieve these accuracies.

3D Printing /Additive manufacturing holds a promising future in healthcare as it aids in visualizing things and making 3D objects which is very important in different areas of medicine. The concept of one size fits all has failed the quality of care delivered by us in healthcare which demands customised needs for patient care to create 3D printed tissues, make personalized prosthetics, implants and physical models of the human body. The materials used for printing models and other healthcare devices for medical education, patient needs, and prototyping are increasing. The application of different materials for use in healthcare is not studied. New materials are also available for the various applications in healthcare industry. This experimental study was conducted to review the nine distinct 3D printing filament materials like PETG, PA, ABS, PLA, HIPS, PMMA, Ceramic, Carbon Fiber, and (PLA + Metal Composite) with the help of a 3D printed physical model of T-12 thoracic vertebrae using all the abovementioned materials. The evaluation of materials was based on diverse mechanical properties, applications across medical fields, performance metrics, costs, accuracy, and quality. The assessment This study also focuses on comparison of mechanical properties such as tensile strength, compressive strength of the abovementioned materials with human bone. The study also reviews the 3D printing process and explores its utilization in biomedical applications. The Insights about the application of various materials holds a promising future for development of newer materials for healthcare industry.

Current Micro-Computed Tomography (Micro-CT) protocols for microvasculature analysis often necessitate organ dissection and non-clearable contrast agents. We describe a non-destructive technique for achieving high-resolution images of the human coronary microvasculature. Formalin-fixed human hearts were cannulated using venogram catheters designed for balloon occlusion. Catheters were anchored at the aortic root. Hearts were placed in sealable, radiolucent containers filled with insulating polyurethane foam. Iodine potassium iodide (IKI, Lugol's solution;6.3% Potassium Iodide, 4.1% Iodide) was injected into the coronary arteries. Contrast distribution was monitored using a North Star Imaging X3000 Micro-CT scanner with low-radiation settings, followed by high-radiation scans (3600 rad, 60 kV, 900 mA). We successfully imaged two intact human hearts with chronic total coronary occlusions of the right coronary artery. The scans enabled detailed analysis of the vasa vasorum surrounding stenosed and occluded segments. After imaging, both hearts were cleared of iodine and excess polyurethane foam and then returned to their initial formalin-fixed state for indefinite storage. Conclusions: This method allows for the non-destructive, high-resolution micro-CT imaging of coronary microvasculature in intact human hearts, paving the way for 3D microvascular reconstruction in a macrovascular context.

The development of new turbomachinery designs requires numerous time-consuming and computationally intensive computational fluid dynamics (CFD) calculations. However, most of the generated high spatial resolution data remains unused at later development steps. That is also the case with automated optimization processes that use only a few integral values to determine objectives and constraints. Therefore the development of a data-driven AI model was initiated to ensure the potential of further use of the CFD data which is also used to train the AI model. The presented method subsequently provides a fast approximation of the 3D flow for new designs. In this paper, the structure of the developed AI model is presented and the approximation quality is analysed using a complex, state-of-the-art compressor test case. It is shown that the AI model can reproduce many characteristics of the 3D flow of new designs, and performance measures such as efficiency can be derived from these flow predictions. In addition, the complex test case revealed that greater design variation reduces the AI approximation quality which can lead to undesirable exploratory behaviour in an optimisation setup. Overall, the test case has shown promising results and has provided hints for further improvements of the AI model.

Fused deposition modeling (FDM) is a rather new technology in the production of personalized dosage forms. Melting and printing of polymer–active pharmaceutical ingredient (API) – mixtures can be used to produce oral dosage forms with different dosage as well as release behavior. This process is utilized to increase the bioavailability of pharmaceutically relevant active ingredients that are poorly soluble in physiological medium by transforming them into solid amorphous dispersions (ASD). Release from such ASDs is expected to be faster and higher compared to the raw materials and thus enhance bioavailability. Printing directly from powder while forming ASDs was realized. Different techniques to change release patterns as well as a non-destructive way for determination of API distribution were shown. By measuring the melt viscosities of mixtures printed a rheological model for the printer used is proposed.

The interconnection between the objectives of territorial development and the agro-ecological transition highlights the value of past knowledge in the sustainable management of resources and agro-ecological systems. However, retrospection in rural areas presents difficulties due to a lack of data. This paper contributes to the search for such knowledge from the past by developing an interactive methodology capable of combining heterogeneous sources of information and the activation of local collective memory. Its effectiveness is based on ensuring the interoperability of information and communication in an environment simultaneously shaped by geoinformatics and 3D geo-visualizations. This virtual environment fosters participation and interactivity, supported by representations of the paleo-landscape. Furthermore, synergies were achieved between information sources and their integration into local spatial systems. The application example involved identifying a rice field that existed from the 15th to the 19th century in Thessaly, Greece. It is an interesting case because the location and organization of cultivation in combination with its spatio-temporal coordination ensures the sustainable use of natural resources. It appears that the interplay between information and communication facilitates community participation and the activation of its collective memory as a source of information that enriches the search and local intelligence.

Accurate geometric modeling of blood vessels lumen given their 3D images is a basis for vessel quantification in support of cardiovascular diseases diagnosis, treatment and monitoring. Unlike other approaches, which assume circular or elliptical vessel cross-section, the proposed method employs parametric B-splines combined with the image formation system equations to accurately localize the highly curved lumen boundaries. No image segmentation is involved which might reduce the localization accuracy in effect of spatial discretization. It is shown that the model parameters can be reliably identified by a feedforward neural network which, driven by the cross-section images, predicts the parameter values many times faster than a reference least-squares (LS) model fitting algorithm. Two example applications: modeling the lower extremities artery-vein complexes visualized in steady-state contrast-enhanced magnetic resonance images (MRI) and the coronary arteries pictured in computed tomography angiograms (CTA), are presented and discussed to demonstrate the method potential. Besides application to medical diagnosis, blood-flow simulation and vessel-phantom design, it can serve as a tool for automated annotation of image datasets required to train machine-learning algorithms.

This study aims at relating the microstructural arrangement, in particular the symmetry materialised by filament sequencing in fused filament fabrication process on mechanical behaviour of printed polyamide. Dogbone structures are printed using various printing temperatures, which are combined with part orientation and raster angle that represent the in-plane and out-of-plane symmetrical arrangement of filament. Mechanical testing is conducted on both as-received filaments and printed structures to derive the effect of filament arrangement symmetry and process-generated defects on mechanical loss. In addition, microstructural analysis using scanning electron microscopy is used to share more light on the filament arrangement and their consequence on deformation mechanisms with respect to the printing conditions. The results show that 3D printed polyamide-based material exhibit remarkable tensile performance with strain stiffening behaviour and large elongation at break thanks to particular filament layout. Among the considered printing conditions, the part orientation is found to have the largest influence on tensile behaviour, which modulates the behaviour from complete restoration of the filament performance to mechanical loss.

The issue of equipment layout in multi-floor satellites consists of two primary parts: allocating the equipment to the satellite's layers and placing the equipment in each layer individually. In reviewing the past literature in this field, firstly, the issue of assigning equipment to layers is observed in a few articles and next in the layout part, the non-overlapping constraint has always been a challenge, particularly for components that do not have a circular cross-section. In addition to presenting a heuristic method for allocating equipment to different layers of the satellite, this article presents a robust flexible programming model (RFPM) for the placement of equipment at different layers, taking into account the inherent flexibility of the equipment in placement and the subject of uncertainty. This model is based on the existing uncertainty between the distances of cuboid equipment which has not been addressed in any of the previous research, and by comparing its outputs with cases from past studies, it demonstrates a significantly higher efficiency in placing the equipment and meeting the limit of non-overlapping constraints between the equipment. Finally, it would be possible to reduce the design time in the conceptual and preparatory stages, as well as the satellite's overall size, while still satisfying other constraints like stability and thermal limitations, moments of inertia and centre of gravity.

Cycle times at workstations in offsite construction factories fluctuate widely due to various influencing factors. Consequently, relying on average rates, such as length per unit of time, for estimating cycle times proves to be inaccurate, often leading to significant deviations between production schedules and actual operations. To address this issue, this study proposes an estimation system that leverages machine-learning-based prediction, statistical methods, 3D simulation, and computer vision to predict cycle times at the workstation level. Testing of the system on a semi-automated wood-wall framing workstation in a panelized construction factory shows that it reduces the mean absolute error and sum of errors by approximately 36% and 68%, respectively, compared to the fixed rate method. The results also highlight the efficacy of using computer vision data for training machine-learning models for cycle time estimation, the importance of identifying and understanding the factors influencing cycle times, and the impact of random delays on the accuracy of cycle time estimation systems.

Abstract: The widespread and popular use of TADs for orthodontic anchoring has become a daily routine in clinical orthodontic treatment. However, as there have been many accidents over the past decade, safety action is needed to help reduce these accidents. We have advocated using the surgical guide and developed a procedure that can benefit patients and orthodontists. The first part of this paper is about the rationale for making the surgical guide for various implant placements that were observed. Due to their anatomical structure, some placements may require particular attention, which is focused on and discussed in length. The second part deals with fabricating the surgical guide in the laboratory procedure. The data from the intraoral SLT acquisition was extracted, and with the DICOM data from CBCT and in a 3-Shapes software, the guidance was designed. The detailed and step-by-step laboratory procedure, CAD/CAM, and 3D printers to make the surgical guide for TADs are explained. The procedure is performed in an easy-to-understand manner to make using the surgical guide possible for the daily practice of orthodontics (Pubmed).

Maxillofacial defects, arising from trauma, oncological disease or congenital differences, detrimentally affect everyday life. Prosthetic repair offers the aesthetic and functional reconstruction with the help of materials mimicking natural tissues, among which polymers take unprecedented role. The three-dimensional (3D) printing techniques based on the computer-aided design, where polymers are essential, provide a rapid and cost-effective workflow protocol to perfectly restore patient-specific anatomy for prosthetics. This review discusses the main 3D printing approaches to maxillofacial prostheses fabrication: extrusion and lithography, which are radically preferable to the traditional methods. The main assessment criteria, affording the polymer implementation in 3D printing of prostheses, as well as the characteristics of the key advanced polymers, are considered. The success of the prosthesis is shown to be largely dependent on the retention system, predominantly using polymers in the form of adhesives and osseointegrated implants as a support for the prosthesis. The approaches and technological prospects are also discussed in the context of specific aesthetic restoration on the example of the nasal, auricle and ocular prostheses. 3D printing techniques determine the development of personalized approaches to improve aesthetic and functional effect of prosthetics in patients with maxillofacial defects.

With a view to sustainable development and circular economy, this work focused on the possibility to valorize a secondary waste stream of recycled carbon fiber (rCF) to produce a 3D printing usable material with PA6,6 polymer matrix. The reinforcing fibers implemented in the present research are the result of a double recovery action: starting with pyrolysis from which long fibers are obtained, used to produce non-woven fabrics and, subsequently, fiber agglomerate wastes obtained from this last process are ground in a ball mill. The effect of a different amount of reinforcement at 5% and 10% by weight on the mechanical properties of 3D printed thermoplastic composites was investigated. Although the recycled fraction was successfully integrated in the production of filaments for 3D printing and therefore in the production of specimens via Fused Deposition Modeling technique, the results showed that fibers did not improve the mechanical properties as expected, due to an unsuitable average size distribution and the presence of a predominant dusty fraction ascribed to the non-optimized ball milling process. PA6,6 + 10 wt.% rCF composites exhibited a tensile strength of 59.53 MPa and a tensile modulus of 2.24 GPa, which correspond to an improvement in mechanical behavior of 21 5 % and 5 21 % compared to the neat PA6,6 specimens, respectively. The printed composite specimens loaded with the lowest content of rCF provided the greatest improvement in strength (+ 9% over the neat sample). Then, a prediction of the “optimum” critical length of carbon fibers was proposed that could be used for future optimizations of the recycled fiber processing.

Building Information Modelling (BIM) has gained significant relevance in civil engineering, particularly in the infrastructure sector. It offers the potential to increase efficiencies, optimize processes, and enhance sustainability throughout infrastructure projects’ life cycles. BIM consolidates information about asset components into a single model, enabling real-time updates, cost reduction, and improved consistency. Digital twins serve as valuable extensions of BIM in infrastructure, playing a crucial role during operation. By capturing real-time data from sensors and IoT devices, digital twins enabls continuous monitoring, proactive maintenance, efficient energy management, and informed decision-making for optimized operational efficiency. Advancements in 3D point cloud technologies, such as 3D laser scanning, have expanded BIM’s application in operation and maintenance. These technologies rapidly capture accurate and detailed three-dimensional information, prompting the exploration of automated alternatives to manual point cloud modeling. This paper demonstrates the application of supervised machine learning, specifically support vector machines, for analyzing and segmenting 3D point clouds, a crucial step in 3D modeling. Various approaches for semantic segmentation are introduced, investigated, and evaluated using diverse data sets. The results highlight the effectiveness of supervised machine learning techniques in achieving accurate segmentation of 3D point clouds.

Natural rocks are highly heterogeneous due to various geological processes that constantly alter their properties. The accumulation, deposition, and cementation of mineral and organic particles continuously modify the spatial characteristics of rock properties. Property variability or anisotropy is commonly observed in most rock types and influences strength, transport, and thermal conductivity behavior. This unpredictability presents a significant challenge for laboratory testing. Binder-jet additive manufacturing (3D printing) has emerged as a valuable technology for characterizing rock properties in geoscience and engineering. This study proposes a methodology to evaluate the variability and repeatability of mechanical properties of 3D-printed sandstones during binder-jet additive manufacturing. The mechanical properties were analyzed statistically for samples located in various parts of the 3D printer build volume. The results showed that the 3D-printed sandstones exhibited significant variations in their strength and stiffness properties when measured from samples produced within the same build volume during binder-jet additive manufacturing. The Uniaxial Compressive Strength (UCS) varied from 23 to 38 MPa, with an average value of 29 MPa. The Young's modulus, on the other hand, ranged from 1.5 to 4.05 GPa, with an average value of 2.33 GPa. The variability of the mechanical properties, quantified by the standard deviation, decreased when the entire population of 3D-printed sandstones was divided into smaller samples situated at different elevations of the build platform.

Light Detection and Ranging (LiDAR) technology, a cutting-edge advancement in mobile applications, presents a myriad of compelling use cases, including enhancing low-light photography, capturing and sharing 3D images of fascinating objects, and elevating the overall augmented reality (AR) experience. However, its widespread adoption has been hindered by the prohibitive costs and substantial power consumption associated with its implementation. To surmount these obstacles, this paper proposes a low-power, low-cost, SPAD-based system-on-chip (SoC) which packages the microlens arrays (MLA) and incorporates with a light-weight RGB-guided sparse depth imaging completion neural network for 3D LiDAR imaging. The proposed SoC integrates an 8x8 Single-Photon Avalanche Detectors (SPADs) macro pixel array with time-to-digital converters (TDC) and charge pump, fabricated using a 180nm bipolar-CMOS-DMOS (BCD) process. A random MLA-based homogenizing diffuser efficiently transforms Gaussian beams into flat-topped beams with a 45° field of view (FOV), enabling flash projection at the transmitter. To further enhance resolution and broaden application possibilities, a lightweight neural network employing RGB-guided sparse depth complementation is proposed, enabling a substantial expansion of image resolution from 8x8 to quarter video graphics array level (QVGA; 256x256). Experimental results demonstrate the effectiveness and stability of the hardware encompassing the SoC and optical system, as well as the lightweight features and accuracy of the algorithmic neural network. This integrated state-of-the-art hardware-software solution offers a promising and inspiring foundation for developing consumer-level 3D imaging applications.

This paper proposes an algorithm for transmitting and reconstructing the estimated point cloud using temporally estimating a dynamic point cloud sequence. When a non-rigid 3D point cloud sequence (PCS) is input, the sequence is divided into groups of point cloud frames (PCF), and a key PCF is selected. After the 3D skeleton is predicted through 3D pose estimation, the motion of the skeleton is estimated by analyzing the joints and bones of the 3D skeleton. For the deformation of the non-rigid human PC, the 3D PC model is transformed into a mesh model, and the key PCF is rigged using the 3D skeleton. After deforming the key PCF into the target PCF utilizing the motion vector of the estimated skeleton, the residual PC between the motion compensation PCF and the target PCF is generated. If there is a key PCF, the motion vector of the target PCF, and a residual PC, the target PCF can be reconstructed. Just as compression is performed using pixel correlation between frames in a 2D video, this paper compresses 3D PCF by estimating the non-rigid 3D motion of a 3D object in a 3D PC. The proposed algorithm can be regarded as an extension of the 2D motion estimation of a rigid local region in a 2D plane to the 3D motion estimation of a non-rigid object (human) in 3D space. Experimental results show that the proposed method can successfully compress 3D PC sequences. If it is used together with a PC compression technique such as MPEG PCC (point cloud compression) in the future, a system with high compression efficiency may be configured.

Supramolecular structures are of great interest due to their applicability in various scientific and industrial fields. These fields of scientific action include promising applications i biomedical areas, in sensing, and in conductive and electrical phases. The sensible definition of supramolecular molecules is being set by investigators, who, because of the different sensitivities of their methods and observational timescales, may have different views as to what constitute these supramolecular structures. Besides, diverse polymers can be found to offer unique avenues for multifunctional systems with properties in medicine industrial applications. Aspects of this review provide different conceptual strategies to address molecular design, properties, and potential applications of self-assembly materials and the use of metal coordination as a feasible and useful strategy for constructing complex supramolecular structures. In this order of appreciations and ideas order, it is that this review report involves classic topics such as hydrogels that range from their relationship with drug delivery systems, to metallo-supramolecular materials, through applications in ophthalmic systems, in applications that require adhesiveness and electrically conductive hydrogels. This review also addresses systems that are largely based on hydrogel chemistry and the enormous opportunities to design very specific structures for applications that demand enormous specificity.

Methacrylated silk (Sil-MA) is a chemically modified silk fibroin specifically designed to be crosslinkable under UV light. This allows the structuring of this material throught additive manufacturing techniques and then to easily prototype patient specific construct. In this study we used Sil-MA to produce single layer crosslinked structures that can be withdrawal and ejected recovering their shape after rehydration. A complete chemical and physical characterization of the material has been conducted. Additionally, we tested the material biocompatibility according to the International Standard Organization protocols (ISO 10993) ensuring the possibility to use it in future trials. The material was also tested to verify its ability to support the osteogenesis. Two different additive manufacturing techniques have been tested (a Digital Light Processing (DLP) UV projector and a pneumatic extrusion technique) to develop Sil-MA grid. Finally, we provide a proof-of-concept that the printed Sil-MA structures are injectable.

Lesion studies are crucial in establishing brain-behavior relationships, and accurately segmenting the lesion represents the first step in achieving this. Manual lesion segmentation is the gold standard for chronic strokes. However, it is labor-intensive, subject to bias, and limits sample size. Therefore, our objective is to develop an automatic segmentation algorithm for chronic stroke lesions on T1-weighted MR images. Methods: To train our model, we utilized an open-source dataset: ATLAS v2.0 (Anatomical Tracings of Lesions After Stroke). We partitioned the dataset of 655 T1 images with manual segmentation labels into five subsets and performed a 5-fold cross-validation to avoid overfitting of the model. We used a deep neural network (DNN) architecture for model training. Results: To evaluate the model performance, we used three metrics that pertain to diverse aspects of volumetric segmentation including shape, location, and size. The Dice similarity coefficient (DSC) compares the spatial overlap between manual and machine segmentation. The average DSC was 0.65 (0.61- 0.67; 95% bootstrapped CI). Average symmetric surface distance (ASSD) measures contour distances between the two segmentations. ASSD between manual and automatic segmentation was 12mm. Finally, we compared the total lesion volumes and the Pearson correlation coefficient (ρ) between the manual and automatically segmented lesion volumes, which was 0.97(p-value &lt; 0.001). Conclusions: We present the first automated segmentation model trained on a large multicentric dataset. This model will enable automated on-demand processing of MRI scans and quantitative chronic stroke lesion assessment.

As Automated Driving Systems (ADS) technology gets assimilated into the market, the driver’s obligation will be changed to a supervisory role. A key point to consider is the driver’s engagement in the secondary task to maintain the driver/user in the control loop. The paper’s objective is to monitor driver engagement with a game and identify any impacts the task has on hazard recognition. We designed a driving simulation using Unity3D and incorporated three tasks: No-task, AR-Video, and AR-Game tasks. The driver engaged in an AR object interception game while monitoring the road for threatening road scenarios. From the results, there was less than 1 second difference between the means of gaming task (mean = 2.55s, std = 0.1002s) to no-task (mean = 2.55s, std = 0.1002s). Game scoring followed three profiles/phases: learning, saturation, and decline profile. From the profiles, it is possible to quantify/infer drivers’ engagement with the game task. The paper proposes alternative monitoring that has utility, i.e., entertaining the user. Further experiments AR-Game focusing on real-world car environment will be performed to confirm the performance following the recommendations derived from the current test.

During the night between 9 and 10 September 2017, multiple flash floods associated to a heavy-precipitation event affected the town of Livorno, located in Tuscany, Italy. Accumulated precipitation exceeding 200 mm in two hours, associated with a return period higher than 200 years, caused all the largest streams of the Livorno municipality to flood several areas of the town. We used the limited-area Weather Research and Forecasting (WRF) model, in a convection-permitting setup, to reconstruct the extreme event leading to the flash floods. We evaluated possible forecasting improvements emerging from the assimilation of local ground stations and X- and S-band radar data into the WRF, using the configuration operational at the meteorological center of Tuscany region (LaMMA) at the time of the event. Simulations were verified against weather station observations, through an innovative method aimed at disentangling the positioning and intensity errors of precipitation forecasts. By providing more accurate descriptions of the low-level flow and a better assessment of the atmospheric water vapour, the results demonstrate that assimilating radar data improved the quantitative precipitation forecasts.

Accurate forecasts of ocean waves energy can not only reduce costs for investment but it is also essential for management and operation of electrical power. This paper presents an innovative approach based on the Long Short Term Memory (LSTM) to predict the power generation of an economical wave energy converter named “Searaser”. The data for analyzing is provided by collecting the experimental data from another study and the exerted data from numerical simulation of searaser. The simulation is done with Flow-3D software which has high capability in analyzing the fluid solid interactions. The lack of relation between wind speed and output power in previous studies needs to be investigated in this field. Therefore, in this study the wind speed and output power are related with a LSTM method. Moreover, it can be inferred that the LSTM Network is able to predict power in terms of height more accurately and faster than the numerical solution in a field of predicting. The network output figures show a great agreement and the root mean square is 0.49 in the mean value related to the accuracy of LSTM method. Furthermore, the mathematical relation between the generated power and wave height was introduced by curve fitting of the power function to the result of LSTM method.

The small satellite market continues to grow year after year. A compound annual growth rate of 17% is estimated during the period between 2020 and 2025. Low-cost satellites can send a vast amount of images to be post-processed at the ground to improve the quality and extract detailed information. In this domain lies the resolution enhancement task, where a low-resolution image is converted to a higher resolution automatically. Deep learning approaches to Super-Resolution (SR) reached the state-of-the-art in multiple benchmarks; however, most of them were studied in a single-frame fashion. With satellite imagery, multi-frame images can be obtained at different conditions giving the possibility to add more information per image and improve the final analysis. In this context, we developed and applied to the PROBA-V dataset of multi-frame satellite images a model that recently topped the European Space Agency’s Multi-frame Super Resolution (MFSR) competition. The model is based on proven methods that worked on 2D images tweaked to work on 3D: the Wide Activation Super Resolution (WDSR) family. We show that with a simple 3D CNN residual architecture with WDSR blocks and a frame permutation technique as data augmentation better scores can be achieved than with more complex models. Moreover, the model requires few hardware resources, both for training and evaluation, so it can be applied directly from a personal laptop.

The extrusion-based additive manufacturing is a popular fabrication method, which has attracted the attention of various industries due to its simplicity, cheapness, ability to produce complex geometric shapes, and high production speed. One of the effective parameters in this process is the feed of filament that is presented in the production G-code. The feed of filament is calculated according to the layer height, the extrusion width and the length of printing path. All the required motion paths and filling patterns created by commercial software are a set of straight lines or circular arcs that are placed next to each other at a fixed distance. In special curved paths, the distance of adjacent ones is not equal at different points, and due to the weakness of common commercial software, it is not possible to create curved paths for proper printing. Therefore, making a special computer code that can be used to create various functions of curved paths is investigated in this research, and also the feed of filament parameter is studied in detail. Next, by introducing a correction technique, the feed of filament is changed during the curved path to distribute the polymer material uniformly. Finally, composite samples (which have variable stiffness) consisting of curved fibers are produced with the proposed method, and the high quality of printed samples confirm the suggested code and technique.

Emerging pollutants as pharmaceuticals have been focusing international attention for few decades. Ciprofloxacin (CIP) is a common drug widely found in effluents from hospitals, industrial and different wastewater treatment plants, as well as rivers. In this work, the lab-scale 3D-BER system was established, and more than 90% of the antibiotic CIP removal from the Low C/N wastewater. Best results were obtained with current intensity, and different C/N ratio significantly improve the removal of CIP and nitrates, when the ideal conditions were; C/N = 1.5-3.5, pH =7.0-7.5, and I = 60 mA. The highest removal efficiency of CIP = 94.20 %, NO3--N= 95.53 % and total nitrogen (TN) = 84.27 %, respectively. In this novel system, the autotrophic-heterotrophic denitrifying bacteria played vital role for the removal of CIP and enhanced denitrification process. Thus, autotrophic denitrifying bacteria uses CO2 and H2 as carbon sources to reduce nitrates to N2. This system has the assortment and prosperous community revealed at the current intensity of 60 mA, and the analysis of bacterial community structure in effluent samples fluctuates under different condition of C/N ratios. According to the results of LC-MS/MS analysis, the intermediate products were proposed after efficient biodegradation of CIP. Microbial community on biodegrading was mostly found at phylum, and class level was dominantly responsible for the NO3--N and biodegradation of CIP. This work can provide some new insights towards the biodegradation of CIP and the efficient removal of nitrates from low C/N wastewater treatment by the novel 3D-BER system.

The integration of 3D city models with Building Information Models (BIM), abbreviated as GeoBIM, facilitates improved data support to several applications, e.g. 3D map updates, building permits issuing, detailed city analysis, infrastructure design, context-based building design, to name a few. To solve the integration, several issues need to be tackled and solved, i.e. harmonization of features, interoperability, format conversions, integration of procedures. The GeoBIM benchmark 2019, funded by ISPRS and EuroSDR, evaluated the state of implementation of tools addressing some of those issues. In particular, in the part of the benchmark described in this paper, the application of georeferencing to Industry Foundation Classes (IFC) models and making consistent conversions between 3D city models and BIM are investigated, considering the OGC CityGML and buildingSMART IFC as reference standards. In the benchmark, sample datasets in the two reference standards were provided. External volunteers were asked to describe and test georeferencing procedures for IFC models and conversion tools between CityGML and IFC. From the analysis of the delivered answers and processed datasets, it was possible to notice that while there are tools and procedures available to support georeferencing and data conversion, comprehensive definition of the requirements, clear rules to perform such two tasks, as well as solid technological solutions implementing them, are still lacking in functionalities. Those specific issues can be a sensible starting point for planning the next GeoBIM integration agendas.

Interest in drone solutions in forestry applications is growing. Using drones, datasets can be captured flexibly and at high spatial and temporal resolutions when needed. In forestry applications, fundamental tasks include the detection of individual trees, tree species classification, bio-mass estimation, etc. Deep Neural Networks (DNN) have shown superior results when comparing with conventional machine learning methods such as Multi-Layer Perceptron (MLP) in cases of huge input data. The objective of this research was to investigate 3D convolutional neural networks (3D-CNN) to classify three major tree species in a boreal forest: pine, spruce, and birch. The proposed 3D-CNN models were employed to classify tree species in a test site in Finland. The classifiers were trained with a dataset of 3039 manually labelled trees. Then the accuracies were assessed by employing independent datasets of 803 records. To find the most efficient set of feature combination, we compare the performances of 3D-CNN models trained with hyperspectral (HS) channels, RGB channels, and canopy height model (CHM), separately and combined. It is demonstrated that the proposed 3D-CNN model with RGB and HS layers produces the highest classification accuracy. The producer accuracy of the best 3D-CNN classifier on the test dataset were 99.6%, 94.8%, and 97.4% for pines, spruces, and birches, respectively. The best 3D-CNN classifier produced ~5% better classification accuracy than the MLP with all layers. Our results suggest that the proposed method provides excellent classification results with acceptable performance metrics for HS datasets. Our results show that pine class was detectable in most layers. Spruce was most detectable in RGB data, while birch was most detectable in the HS layers. Furthermore, the RGB datasets provide acceptable results for many low-accuracy applications.

This paper presents the systematic development and performance characterization of a non-proprietary 3D-printable ultra-high-performance fiber-reinforced concrete (UHPFRC) for digital construction. Several fresh and hardened properties of the developed 3D-printable UHPFRC matrix (without fiber) and composite (with 2% volume fraction of steel fibers) were evaluated and compared to that of conventionally mold-cast UHPFRC. Additionally, the effects of testing direction on the compressive and flexural strengths of the printed UHPFRC were investigated. The fresh properties of the UHPFRC developed in this study satisfied the criteria for extrudability, buildability, and shape-retention-ability, which are relevant for ensuring printability. The printed UHPFRC exhibited superior flexural performance to the mold-cast UHPFRC due to alignment of the short fibers in the printing direction. The high compressive and flexural strengths, along with the deflection-hardening behavior, of the developed UHPFRC can enable the production of thin 3D-printed components with significant reduction or complete elimination of conventional steel bars.

The diffusion coefficients of ions are measured in a microchip filled with a cationic charged 3D hydrogel in order to study the effect of cationic charged 3D hydrogel on the diffusivity of ions. In this study, poly-diallyl-dimethyl-ammoniumchloride (poly-DADMAC) is used to produce a 3D hydrogel. Four different fluorophores are used in the 3D hydrogel rhodamine 6G, rhodamine-BSA, fluorescein isothio-cyanate (FITC) and FITC-BSA. The rhodamine 6G and rhodamine-BSA are positively charged (cations), while fluorescein isothio-cyanate (FITC) and FITC-BSA are negatively charged (anions). Two widely used techniques which are short time diffusivity measurement technique and long time diffusivity measurement techniques are used to measure the diffusion coefficients. For the short time measurement, Fluorescence recovery after photo-bleaching (FRAP) is used by a 3D confocal microscope. For the long time measurement, fluorescence images are taken for 11 days to observe a pure diffusivity without any convective movement. As a result, the diffusivity of the cations was found to be lower than that of the anions in the cationic charged hydrogel.

Abstract: The promise of regenerative medicine and tissue engineering is founded on the ability to regenerate diseased or damaged tissues and organs into functional tissues and organs or the creation of new tissues and organs altogether. In theory, all damaged and diseased tissues and organs can be regenerated or created using different configurations and combinations of extracellular matrix, cells and inductive biomolecules. Currently, regenerative medicine and tissue engineering can allow the improvement of patients’ quality of life through availing novel treatment options. Tissues and organs have a specific ECM, with specific proteins and factors released by cells residing within the local microenvironment. The coupling of regenerative medicine and tissue engineering field with 3D printing is revolutionizing the treatment of patients in a huge way. 3D bioprinting allows the proper placement of cells and ECMs, allowing the recapitulation of native microenvironments of tissues and organs. 3D bioprinting utilizes different bioinks made up of different formulations of ECM/biomaterials, biomolecules and even cells. The choice of the bioink used during 3D bioprinting is very important as properties such as printability, compatibility and physical strength influence the final construct printed. The extracellular matrix (ECM) provides both physical and mechanical microenvironment needed by cells to survive and proliferate. Decellularized ECM bioink contains biochemical cues from the original native ECM and also the right proportions of ECM proteins. Different techniques and characterization methods are used to derive bioinks from several tissues and organs and to evaluate their quality. This review discusses the uses of decellularized ECM bioinks and argues that they represent the most biomimetic bioinks available. In addition, we briefly discuss some polymer-based bioinks utilized in 3D bioprinting.

The parts obtained by FFF technology are anisotropic in any direction; while the whole part constitutes out of layers, each of the layers include one or more perimeters of shell and the infill with density from 0 to 100%. Mechanical performance of FFF parts depends on its shape, orientation, constitution and 3D printing parameters. A classification for shapes of parts obtained by FFF and stressed during its operation is provided. For the most questionable class (parts with interrupted shell critically stressed on interlayer boundaries) a representative sample and testing apparatus is developed. Different approaches to the sample shape modification were applied and tested. The part shape optimization resulted in increment of the force, required to fracture the part from 483 to 1096 N.

Designing motion representations for the problem of 3D human action recognition from skeleton sequences is an important yet challenging task. An effective representation should be robust to noise, invariant to viewpoint changes and result in a good performance with low-computational demand. Two main challenges in this task include how to efficiently represent spatio-temporal patterns of skeletal movements and how to learn their discriminative features for classification task. This paper presents a novel skeleton-based representation and a deep learning framework for 3D action recognition using RGB-D sensors. We propose to build an action map called SPMF (Skeleton Posture-Motion Feature), which is a compact image representation built from skeleton poses and their motions. An Adaptive Histogram Equalization (AHE) algorithm is then applied on the SPMF to enhance their local patterns and form an enhanced action map, namely Enhanced-SPMF. For learning and classification tasks, we exploit Deep Convolutional Neural Networks based on the DenseNet architecture to learn directly an end-to-end mapping between input skeleton sequences and their action labels via the Enhanced-SPMFs. The proposed method is evaluated on four challenging benchmark datasets, including both individual actions, interactions, multiview and large-scale datasets. The experimental results demonstrate that the proposed method outperforms previous state-of-the-art approaches on all benchmark tasks, whilst requiring low computational time for training and inference.

This paper presents the latest developments in microCT, both globally and locally, for supporting the additive manufacturing industry. There are a number of recently developed capabilities which are especially relevant to the non-destructive quality inspection of additive manufactured parts; and also for advanced process optimization. These new capabilities are all locally available but not yet utilized to their full potential, most likely due to a lack of knowledge of these capabilities. The aim of this paper is therefore to fill this gap and provide an overview of these latest capabilities, showcasing numerous local examples.

Most of the phase change materials (PCMs) have been limited to use as functional additions or sealed in containers, and extra auxiliary equipment or supporting matrix is needed. The emergence of 3D printing technique has dramatically advanced the developments of materials and simplified production processes. This study focuses on a novel strategy to model thermal energy storage crystalline gels with three-dimensional architecture directly from liquid resin without supporting materials through light-induced polymerization 3D printing technique. A mask-projection stereolithography printer was used to measure the 3D printing test, and the printable characters of crystalline thermal energy storage P(SA-DMAA) gels with different molar ratios were evaluated. For the P(SA-DMMA) gels with small fraction of SA, the 3D fabrication was realized with higher printing precision both on mili- and micro-meter scales. As a comparison of 3D printed samples, P(SA-DMAA) gels made by other two methods, post-UV curing treatment after 3D printing and UV curing using conventional mold, were prepared. The 3D printed P(SA-DMAA) gels shown high crystallinity. Post–UV curing treatment was beneficial to full curing of 3D printed gels, but did not lead to the further improvement of crystal structure to get higher crystallinity. The P(SA-DMAA) crystalline gel having the highest energy storage enthalpy that reached 69.6 J·g⁻¹ was developed. Its good thermoregulation property in the temperature range from 25 to 40 °C was proved. The P(SA-DMAA) gels are feasible for practical applications as one kind of 3D printing material with thermal energy storage and thermoregulation functionality.

Selective laser melting (SLM) is one of the widely used techniques in metallic additive manufacturing, in which high-density laser powder is utilized to selectively melting layers of powders to create geometrically complex parts. Temperature distribution and molten pool geometry directly determine the balling effect, and concentrated balling phenomenon significantly deteriorates surface integrity and mechanical properties of the part. Finite element models have been developed to predict temperature distribution and molten pool geometry, but they were computationally expensive. In this paper, the three-dimensional temperature distributions are predicted by analytical models using point moving heat source and semi-ellipsoidal moving source respectively. The molten pool dimensions under various process conditions are obtained from the three-dimensional temperature predictions and experimentally validated. Ti-6Al-4V alloy is chosen for the investigation. Good agreements between the predictions and the measurements are observed. The presented models are also suitable for other metallic materials in the SLM process.

The planar cell polarity (PCP) of epithelial ciliated cells is essential for effective mucociliary clearance (MCC) in the sinonasal mucosa. We hypothesize that MCC coordination is impaired in nasal polyp (NP) mucosae due to suppressed expression of a series of CPLANE (ciliogenesis and planar cell polarity effector) complex proteins in chronic rhinosinusitis (CRS) patients. To inves-tigate this hypothesis, we subjected sinonasal mucosal samples to live video recording to measure mucociliary transport velocity (MCTV) and scanning electron microscopy to evaluate surface morphology. The expression and distribution of a panel of PCP proteins, e.g. WDPCP and FUZ, were investigated in relation to inflammatory cytokine levels and clinical features. The mean MCTV of NP mucosae was significantly lower than that of the inferior turbinate mucosae. The CRS group with NPs (CRSwNP group) (n=28) showed increased expression of IL-13 and CCL26 mRNA compared to CRS patients without NPs (n=25) and controls (n=30). WDPCP and FUZ mRNA levels were significantly decreased in NP mucosae compared to ethmoid sinus mucosae in CRSwNP patients. WDPCP protein distribution was reduced in the cytoplasmic region of ciliated cells in CRSwNP patients. We conclude that suppression of WDPCP in ciliated cells is responsible for the impaired MCC of nasal polyps with type-2 inflammation. This mechanism might explain the decreased clearance and the potential for worsening symptoms of CRSwNP.

Renal cell carcinoma (RCC) accounts for approximately 90-95% of all kidney cancers in adults, with the clear cell RCC (ccRCC) the most frequently identified subtype. RCC is known for its responsiveness to immunotherapy, making it an area of significant research interest. Immune checkpoint (IC) molecules, which regulate immune surveillance, are established therapeutic targets in RCC. The aim of this study was to analyze the influence of polymorphisms in genes HVEM and CD160 on susceptibility to ccRCC and patient overall survival (OS) with over a ten-year period of observation. We genotyped three HVEM single nucleotide polymorphisms (SNPs): rs1886730, rs2234167, and rs8725, and two CD160 SNPs: rs744877 and rs2231375, in 238 ccRCC patients and 521 controls. Our findings indicated that heterozygosity within rs2231375 and/or rs2234167 increases ccRCC risk. Furthermore, in women, heterozygosity within additional HVEM SNPs, rs8725 and rs1886730, is associated with an increased ccRCC risk. The presence of a minor allele for rs1886730, rs2234167, rs8725, and rs2231375 was also correlated with certain clinical features of the disease. Moreover, the rs1886730 SNP was found to be associated with patients' OS. In conclusion, our study highlights an association between HVEM and CD160 polymorphisms and the risk of developing ccRCC as well as patient’s OS.

Human adipose stem cell-derived extracellular vesicles (hASC-EVs) are key mediators of paracrine signaling with promising therapeutic applications. Although hASC-EVs are derived from human cells and are less immunogenic, their immunogenicity cannot be completely excluded. Here, we evaluate the immune responses of ICR and C57BL/6 mice to high doses of hASC-EVs for 10 days after injection. Lymphocyte subpopulations are analyzed using flow cytometry at 0.5, 1, 3 and 24 h post injection. In the spleen and blood of C57BL/6 mice, neutrophils sharply increased at 0.5 h and decreased at 3 h following hASC-EV treatment. We observe increased proportions of monocytes, macrophages, and natural killer cells at 3 h but returned to similar level of vehicle control at 24 h post injection in the spleen and blood of ICR mice. Although the in vivo experiments reveal different immune responses to hASC-EV treatment in C57BL/6 and ICR strains, no major changes occur in human peripheral blood mononuclear cell composition after applying hASC-EVs in vitro. In conclusion, unlike those in mice, immune responses to hASC-EVs in humans are not detectable, indicating a minimal risk of fatal side-effects from hASC-EV-based therapies.

Pericytes are increasingly recognized as being important in the control of blood-brain barrier permeability and vascular flow. Research on this important cell type has been hindered by widespread confusion regarding the phenotypic identity and nomenclature of pericytes and other perivascular cell types. In addition, pericyte heterogeneity and mouse-human species differences have contributed to confusion. Herein we summarize our present knowledge on the identification of pericytes and pericyte subsets in humans, primarily focusing on recent findings in humans and nonhuman primates. Precise identification and definition of pericytes and pericyte subsets in humans may help us to better understand pericyte biology and develop new therapeutic approaches specifically targeting disease-associated pericyte subsets.

Publically available (own) transcriptomic data were re-analyzed to quantify the alteration of functional pathways in the thyroid cancer, establish the gene hierarchy, identify potential gene targets and predict the effects of their manipulation. The expression data were generated from one case of papillary thyroid carcinoma (PTC) and from genetically manipulated BCPAP (papillary) and 8505C (anaplastic) human thyroid cancer cell lines. The study used the genomic fabric perspective that considers the transcriptome as a multi-dimensional mathematical object based on the three independent characteristics that can be derived for each gene from the expression data. We found remarkable remodeling of the thyroid hormone synthesis, cell cycle, oxidative phosphorylation and apoptosis pathways. Serine peptidase inhibitor, Kunitz type, 2 (SPINT2) was identified as the Gene Master Regulator of the investigated PTC. The substantial increase of the expression synergism of SPINT2 with apoptosis genes in the cancer nodule with respect to the surrounding normal tissue (NOR) suggests that its experimental overexpression may force the PTC cells into apoptosis with negligible effect on the NOR cells. The predictive value of the expression coordination for the expression regulation was validated with data from 8505C and BCPAP cells before and after lentiviral transfection with DDX19B.

At present more than 9 million people die of cancer every year. Simple and broad-spectrum drugs are still an urgent need for cancer patients. Recently, we proposed a new hypothesis that intracellular osmotic pressure (IOP) is the driving force of cell division, and abnormal tumor proliferation is the result of uncontrolled IOP in cells. On the one hand, aneuploidy and abnormal function of Na⁺/K⁺ pump lead to a faster rise of IOP in tumor cell than normal cells, on the other hand, abnormality of cytoskeleton assembly leads to the decrease of tolerance limit of cell membrane (TLCM) of tumor cells for resisting IOP. This hypothesis predicts: 1)Tumor cells were more intolerant to hypotonic stress than normal cells. 2) Maligancies may be sellectively killed by a suddenn increase of IOP and combined with decrease of the TLCM of tumors. Na⁺/K⁺ pump inhibitors can promotely increase the IOP of tumor cells and cytoskeleton inhibitors can dramatically lower the TLCM of tumor cells. Therefore, Na⁺/K⁺ pump and cytoskeleton inhibitors may have a synergetic effect to kill tumor cells. 3) Molecules regulating cell osmolality may be new targets for cancer treatment.

BACKGROUND: Treatment failure in primary as well as metastatic cancer patients, caused by chemo and radio resistance, has truncated the research for the applicability of personalized medicine. The use of stem cells and cancer stem cells in such a treatment approach will be reviewed in this study. RESULTS: CRC stem cells prove to be a promising asset for CRC treatment optimization both by serving as biomarkers for the current therapy modalities by means of treatment personalization and patient/tumor stratification, as well as in the development of targeted therapies, selective for the stem cell population. Similar conclusions are drawn, regarding mesenchymal stromal cells and their effect in CRC therapy; while resident stromal cells of tumor microenvironment seem to promote the tumorigenic and metastatic processes in addition to conferring to the chemo- and radio resistance, under certain conditions they are able to improve the treatment outcome of CRC chemotherapy, e.g. by targeted enzyme/prodrug treatment of CRC cells. CONCLUSION: This review, truncates the dynamic potential of cancer stem cells and other stem cell types in CRC treatment personalization as well as, in the improvement of current treatment approaches opting to a higher therapeutic rate, improved prognosis, survival and quality of life for CRC patients.

Intracellular aggregates of the alpha-synuclein protein result in cell loss and dysfunction in Parkinson’s disease and atypical parkinsonism, such as multiple system atrophy and dementia with Lewy bodies. Each of these neurodegenerative conditions, known collectively as alpha-synucleinopathies, may be characterized by a different suite of molecular triggers that initiate pathogenesis. The mechanisms whereby alpha-synuclein aggregates in turn mediate cytotoxicity also remain to be fully elucidated. However, recent studies have implicated the cell-to-cell spread of alpha-synuclein as the major mode of disease propagation between brain regions during disease progression. Here, we review the current evidence for different modes of alpha-synuclein cellular release, movement and uptake, including exocytosis, exosomes, tunnelling nanotubes, glymphatic flow and endocytosis. A more detailed understanding of the major modes by which alpha-synuclein pathology spreads throughout the brain may provide new targets for therapies that halt the progression of disease.

One in 12 babies is born with a rare genetic disease. Sadly, most cases are undetected until later age, missing time for early treatment and opportunity to prevent complications. Humanity has entered a new era where Big Data collected by governments, including 2D and 3D facial scans, are available. Many rare genetic diseases can be identified by artificial intelligence (AI) analysis of the facial photo. Phenotyping AI utilizations facilitate comprehensive and accurate genetic evaluations. AI processing of this Big Data to identify rare genetic diseases could bring unimaginable benefits to healthcare, although this would be a questionable step in terms of citizen privacy and could lead to future "Orwellian" ramifications with government abuse. Going forward, a balance must be found between protecting the privacy of citizens and the enticing use of AI for their health risks and cost savings through prevention. The unimaginable potential of AI early diagnostics from facial photos also raises various ethical and legal concerns. This paper presents concept, protentional methods and legal and other limitations within EU legal framework in contrast with potential benefits. This paper is focused on AI utilization to early diagnostic of rare genetic diseases. Shift of paradigm in the screening for rare genetic diseases in population with AI face analysis is expected to have a significant impact. The potential of AI algorithms utilizations similar to face2gene app in general population or systematically on Big governmental datasets recording facial traits changes in time can have significant impact on public health but at the same time give raise to profound concern as violation of one’s privacy.

Stem cells can be used to treat diabetic mellitus and complications. ω3-docosahexaenoic acid (DHA) derived lipid mediators are inflammation-resolving and protective. This study found novel DHA-derived 7S,14R-dihydroxy-4Z,8E,10Z,12E,16Z,19Z-docosahexaenoic acid (7S,14R-diHDHA), a maresin-1 stereoisomer biosynthesized by leukocytes and related enzymes. Moreover, 7S,14R-diHDHA can enhance mesenchymal stem cell (MSC) functions in the amelioration of diabetic mellitus and retinal pericyte loss in diabetic db/db mice. MSCs treated with 7S,14R-diHDHA were delivered into db/db mice i.v. every 5 days for 35 days. Blood glucose levels in diabetic mice were lowered by 7S,14R-diHDHA-treated MSCs compared to control and untreated MSC groups, accompanied by improved glucose tolerance and higher blood insulin levels. 7S,14R-diHDHA-treated MSCs increased insulin+ β-cell ratio and decreased glucogan+ α-cell ratio in islets, as well as reduced macrophages in pancreas. 7S,14R-diHDHA induced MSC functions in promoting MIN6 β-cell viability and insulin secretion. 7S,14R-diHDHA induced MSC paracrine functions by increasing the generation of hepatocyte growth factor and vascular endothelial growth factor. Furthermore, 7S,14R-diHDHA enhanced MSC functions to ameliorate diabetes-caused pericyte loss in diabetic retinopathy by increasing their density in retina in db/db mice. Our findings provide a novel strategy for improving therapy for diabetes and diabetic retinopathy using 7S,14R-diHDHA-primed MSCs.

Deep Learning (DL) has made significant advances in computer vision with the advent of Vision Transformers (ViT). Unlike Convolutional Neural Networks (CNNs), ViTs use self-attention to extract both local and global features from image data, and then use residual connections to feed these features directly into a fully networked multilayer perceptron head. In hospitals, hematologists prepare peripheral blood smears (PBSs) and read them under a medical microscope to detect abnormalities in blood counts such as leukemia. However, this task is time-consuming and prone to human error. This study investigates the transfer learning process of Google ViT and ImageNet CNNs to automate the reading of PBSs. The study used two online PBS datasets, PBC and BCCD, and transferred them into balanced datasets to investigate the influence of data amount and noise immunity on both neural networks. The PBC results show that Google ViT is an excellent DL neural solution for data scarcity. The BCCD results show that Google ViT is superior to ImageNet CNNs in dealing with unclean, noisy image data because it is able to extract both global and local features and use residual connections, despite the additional time and computational overhead.

Background: Lung cancer remains the leading cause of cancer-related mortality globally, predo-minantly affecting older individuals. Despite the increasing use of immune checkpoint inhibitors (ICIs) like nivolumab in non-small cell lung cancer (NSCLC), the efficacy and safety in elderly pa-tients, particularly those aged 65 and above, remain underexplored due to their underrepresenta-tion in clinical trials. Methods: This retrospective study analyzed data from 60 elderly patients (≥65 years) with metastatic NSCLC who received nivolumab as second-line or later therapy between January 2020 and May 2023. Results: The median age was 67 years, with a predominance of males (78%). Nivolumab was administered for a median of 8 cycles, with 33.3% of patients recei-ving 15 or more cycles. The median OS was 23 months, and the 1-, 3-, and 5-year survival rates were 93.3%, 54.1%, and 18.6%, respectively. Multivariate analysis identified adenocarcinoma histology, fewer than 15 cycles of nivolumab, and non-response to prior therapies as independent predictors of poor OS. Nivolumab treatment was generally well-tolerated, with 45% of patients experiencing at least grade 1 toxicity. Conclusion: Nivolumab is effective and well-tolerated in elderly patients with metastatic NSCLC, providing survival benefits comparable to those observed in younger populations. The number of treatment cycles and initial response to therapy are key determinants of survival, underscoring the importance of continued treatment in this age group.

Background: Ubiquitination is an important post-transcriptional modification crucial for maintaining cell homeostasis. As a deubiquitination enzyme, ubiquitin-specific protease 1 (USP1) is associated with tumor progression; however, its role in bladder cancer is unknown. This study was aimed to analyze USP1 expression and study its roles in bladder cancer. Methods: The web server GEPIA was used to analyze the USP1 expression. To explore USP1 function in bladder cancer, we constructed USP1-knockout cell lines in UMUC3 cells. A FLAG-USP1 (WT USP1) plasmid and a plasmid FLAG-USP1 C90S (catalytic-inactive mutant) used to overexpress USP1 in T24 cells. CCK8, colony formation, and transwell assays were used to assess cell viability, proliferation and migration. RNA sequencing (RNA-seq) and dual-luciferase reporter assays were performed to screen the pathway. Coimmunoprecipitation and immunofluorescence were used to explore the interaction between USP1 and c-MYC. Xenograft mouse model was used to study the role of USP1 in bladder cancer. Results: USP1 expression is upregulated in human bladder cancer cells and correlated with poor patient prognosis. USP1 overexpression promoted cell proliferation, clone formation, and migration; this was attenuated by genetic ablation of USP1. Furthermore, we observed that USP1- deficiency inhibited tumor formation in vivo. Mechanistically, the c-MYC pathway was remarkably activated compared with the other pathways. Furthermore, USP1 could directly interact with c-MYC. and increase c-MYC stability depending on the catalytic activity of USP1. Conclusions: Our results suggest that high expression of USP1 promotes bladder cancer progression by stabilizing c-MYC; hence, USP1 it may serve as a novel therapeutic target for treating bladder cancer.

Silver nanoparticles (AgNPs) have arisen as promising specialists in malignant growth treatment, especially in further developing radiotherapy results. In vitro examinations feature AgNPs' capacity to increment radiosensitivity in disease cell lines, prompting uplifted cell demise and decreased clonogenic endurance. Outstandingly, AgNPs display insignificant poisonousness to ordinary cells, recommending potential for specific focusing of disease cells during radiotherapy. The blend of AgNPs with cisplatin shows huge cytotoxicity and oxidative pressure, particularly in tumoral cells, underscoring the requirement for additional investigation of this therapeutic methodology. AgNPs likewise show guarantee in prompting oxidative pressure in pancreatic disease cells, recommending an expected application in pancreatic malignant growth treatment. In co-openness situations, AgNPs, when joined with cadmium, prompt metabolic variation, showing compromised cell safeguard systems. Moreover, AgNPs display potential in tweaking ABC carrier action, offering a procedure to defeat multidrug obstruction in disease cells. While featuring the significant capability of AgNPs in disease treatment, the rundown highlights the need for continuous exploration to clarify their components, well-being profiles, and clinical applications. Combining AgNPs with radiotherapy presents a promising road, tending to limits in ordinary disease therapies and underlining their multifunctionality in forming the eventual fate of malignant growth therapeutics.

Dendritic cells (DCs) are known as major antigen-presenting cells, and lymph nodes (LNs) play an important role in the DC-mediated immune response. This study focused on infiltration of CD1a-positive DCs (CD1a-DCs) in regional LNs in 70 cases of gallbladder cancer (GBC). The results showed that LNs infiltration by CD1a-DCs was associated with unfavorable clinical outcomes in patients with GBC in univariate analyses, but all cases categorized as CD1a-DCs high group at regional LNs had nodal metastasis. Therefore, LNs infiltration by CD1a-DCs was not an independent prognostic factor identified by multivariate analyses. The subgroup analyses in cases with LN metastasis group (n = 32), significant impact of CD1a-DCs infiltration into metastatic LNs was not observed. In contrast, CD1a-DCs infiltration into primary tumor had a significant impact on surgical outcomes. As the results of previous reports that focused on CD1a-DCs infiltration in regional LNs of other organs were varied, the role and significance of CD1a-DCs infiltration in regional LNs may be different according to the tumor histology or primary site. Accumulation of further studies is needed to clarify the role and significance of CD1a-DCs infiltration into regional LNs of solid cancers.

This paper deals with the formulation of a Cobot kinematic model by developing both the direct and inverse kinematics and choosing the noa transformation matrix for defining the end-effector position and orientation with respect to the base frame. These algorithms have been validated via software in Matlab environment and by means of suitable experimental tests, which have been carried out by using a UR5e Cobot. Moreover, a specific industrial application regarding the robotized assembling of a multi-cylinder IC engine, has been designed in terms of layout and corresponding automatic cycle that is intended as a sequence of the robot elementary actions. In particular, the proposed robotized cell is composed by the UR5e Cobot along with its controller and a suitable electropneumatic circuit that includes a PLC with its user interface, which are both governed by means of a specific electronic board and a switch control box. The IC engine in scale of 1:5 and specific parts of the end-effector, which takes the role of vacuum gripper and torque limiting screwdriver, have been designed and manufactured by using a 3D printer.

Recent advancements in nanotechnology have led to the development of multifunctional iron oxide nanoparticles, presenting new opportunities in cancer therapy. This study aimed to synthesize and evaluate citric acid-coated/ folic acid conjugated nanoparticles loaded with doxorubi-cin and investigate their efficacy in experimental tumor models. For synthesis, controlled co-precipitation method was employed to produce highly dispersive, multifunctional nanofluids with a narrow size distribution of iron oxide nanoparticles. Nanoparticles were characterized using Dynamic Light Scattering (DLS) and Electrophoretic Light Scattering (ELS) for size distribution and zeta potential, X-ray Diffraction (XRD) and Transmission Electron Microscopy (TEM) for structure and morphology, Vibrating Sample Magnetometry (VSM) for magnetic properties, and UV-Visible (UV-Vis) and Fourier-Transform Infra-red (FTIR) spectroscopy for modification confirmation. In vitro experiments employed RM1 (prostate cancer) and MEC1 (Chronic lymphocytic leukemia) cell lines to assess cytotoxicity and drug delivery efficiency. Fluorescence microscopy confirmed the intracellular delivery of doxorubicin by these nanoparticles, highlighting their potential for targeted therapy. As a result, nanoparticles conjugated with folic acid showed reduced efficacy over time. This study underscores the critical role of nanoparticle modifications in optimizing therapeutic outcomes. Future research should focus on further refining nanoparticle formulations and long-term effects in vivo, for development of effective and safe agents for targeted cancer treatment.

The mechanistic Target of Rapamycin Complex 1 (mTORC1) regulates ribosome biogenesis and the transcription of ribosomal genes. Its inactivation impacts protein synthesis necessary for transport of cell adhesion molecule. In Dictyostelium discoideum, the activity of mechanistic Target of Rapamycin Complex 2 (mTORC2) is crucial for cAMP synthesis and relay, processes that depend on heterotrimeric G-proteins and Ras GTPases. Mutants lacking rip3 or lst-8 genes exhibit impaired adenyl cyclase activation and cAMP signaling, resulting in deficient expression of the cell adhesion protein CsaA. Despite this, rip3^- cells, which have impaired mTORC2, upregulate Cad-1 expression, a cell adhesion protein regulated by Ras-GTPases, to compensate for the loss of CsaA. lst-8^- cells, which have both mTORC1 and mTORC2 inactivated, show reduced nutrient sensing, premature CsaA expression and solitary cell behavior. These cells also show defective transport of adhesion proteins to the cell surface, impeding aggregation. Similar defects are observed with caffeine treatment, suggesting both mTORC1 and mTORC2 inhibition. This study highlights the interplay between mTORC1 and mTORC2 in regulating cell adhesion and aggregation through cAMP signaling and protein synthesis pathways in Dictyostelium.

Equine laminitis is a debilitating condition characterized by the breakdown of the dermal–epidermal junction, resulting in severe lameness and pain, often requiring euthanasia. This study aimed to establish an in vitro model of laminitis using a continuous keratinocyte cell line exposed to anoxia-reoxygenation and activated neutrophil supernatant. A significant decrease in keratinocytes metabolism was noted during the reoxygenation period, indicative of cellular stress. Adding muscle-derived mesenchymal stem/stroma cells during reoxygenation demonstrated a protective effect, restoring keratinocytes metabolic activity. Moreover, incubation of keratinocytes with activated neutrophil supernatant or myeloperoxidase alone induced increased keratinocyte myeloperoxidase activity, which was modulated by stem cells. These findings underscore the potential of muscle-derived mesenchymal stem/stroma cells in mitigating inflammation and restoring keratinocyte metabolism, offering insights for future cell therapy research in laminitis treatment.

Vegetative desiccation tolerance has evolved within the genus Craterostigma and Lindernia. A centre of endemism and diversification for these plants appears to occur in ancient tropical montane rainforests of east Africa in Kenya and Tanzania. Lindernia subracemosa, a desiccation-sensitive relative of C. plantagineum, occurs in these rainforests and experiences adequate rainfall and thus does not require desiccation tolerance. However, sharing this inselberg habitat, another species Lindernia brevidens does retain vegetative desiccation tolerance and is also related to the resurrection plant C. plantagineum found in South Africa. Leaf material was collected from all three species at different stages of hydration: fully hydrated, half-dry (ca. 45% relative water content), and fully desiccated. Cell wall monosaccharide datasets were collected from all three species. Comprehensive microarray polymer profiling (CoMPP) was performed using ca. 27 plant cell wall specific antibody and carbohydrate binding module probes. Global datasets do not show significant differences between the selected species suggesting that cell wall modifications in response to vegetative desiccation involve subtle cell wall remodelling not reflected by compositional analysis and that the plants and their walls are constitutively protected against desiccation.

The objective of this paper was to study the expression pattern of the GLOD4 gene in the testis and its regulatory effect on testicular cells. Currently, the regulated mechanism through are unclear. Here, we explored how GLOD4 functions in goat leydig cells to enhance our understanding of spermatogenesis and improve reproduction in breeding rams. In this study, we demonstrated that the localization of GLOD4 in testicular cells using immunohistochemistry and subcellular localization analyses. Subsequently, we analyzed the GLOD4 expression pattern in 4 age-based groups (0, 6, 12, and 18 months old) using real-time quantitative polymerase chain reaction (qRT‒PCR) and protein blotting. Finally, we performed GLOD4 gene silencing and overexpression studies in testicular cells from goats and explored the effects of GLOD4 on cell proliferation, the cell cycle, steroid hormone secretion and the expression of candidate testosterone hormone-regulated genes. GLOD4 was mainly expressed in testicular leydig cells, and the subcellular localization results showed that the GLOD4 protein was mainly localized in the cytoplasm and nucleus. Silencing of GLOD4 significantly suppressed the mRNA expression levels of the testosterone secretion-related genes CYP11A1, 3β-HSD and CYP17A1 and the mRNA expression levels of cell-cycle related genes CDK6, PCNA, and Cyclin E. Moreover, the cell cycle was blocked at the G2/M phase after GLOD4 silencing, which significantly suppressed testosterone secretion. In contrast, GLOD4 overexpression significantly increased the mRNA expression levels of the testosterone secretion-related genes CYP11A1, 3β-HSD, and CYP17A1 and increased the expression of the cell-cycle related genes CDK6, PCNA, and Cyclin E. Moreover, GLOD4 overexpression promoted the cell cycle from G0/G1 phases to enter the S phase and G2/M phases,promoted the secretion of testosterone. Taken together, our experimental results indicate that GLOD4 may affect the development of cells in Qianbei Ma goats of different ages by influencing the cell cycle, Proliferation and testosterone hormone synthesis. These findings enhance our understanding of the functions of GLOD4 in the cells of goats.

Cutaneous T-cell lymphomas (CTCLs) are a heterogeneous group of T-cell lymphomas characterised by high relapse rates and no curative treatments unless the allogeneic stem cell transplantation. The main complication in the management of this kind of malignancy is the variability that characterises the genetic and clinical features among the CTCL subtypes. JAK/STAT, MAPK/ERK, PI3K/Akt, and NF-kB are those signalling pathways that are found altered in CTCL and that are responsible for promoting both T-cell malignancy and the pro-tumorigenic microenvironment. Thus, targeting key players of these pathways can be an advantageous therapeutic option for CTCL. In this review, we aim to summarise the different approaches that precisely inhibit the kinases of each cited signalling. JAK inhibitors seem to be the most promising kinase inhibitors for CTCL. However, adverse events have been reported especially in patients with immunosuppression or an underlying autoimmune disease. More studies are needed, especially clinical trials, to investigate the benefits of these drugs for the treatment of cutaneous T-cell lymphomas.

Pathogenic adenovirus (Ad) infections are widespread but typically mild and transient, except in the immunocompromised. As vectors for gene therapy, vaccine and oncology applications, Ad based platforms offer advantages including ease of genetic manipulation, scale of production and well established safety profiles, making them attractive tools for therapeutic development. However, the immune system often poses a significant challenge that may need to be overcome for adenovirus based therapies to be truly efficacious. Both pre-existing anti-Ad immunity in the population as well as the rapid development of an immune response against engineered adenoviral vectors can have detrimental effects upon the downstream impact of an adenovirus-based therapeutic. This review focusses on the different challenges posed, including pre-existing natural immunity and anti-vector immunity induced by a therapeutic, both in context of the innate and adaptive immune responses. We summarize different approaches developed with the aim of tackling these problems, as well as their outcomes and potential future applications.

Amitriptyline is a tricyclic antidepressant commonly used for depressive disorders and pre-scribed off-label for several neurological conditions like neuropathic pain, migraine and anxiety. Amitriptyline potentiates the monoaminergic transmission by blocking the reuptake of norepi-nephrine and serotonin. However, antidepressants also act on additional targets that contribute to either therapeutic or adverse effects and may suggest new indications for their repurposing. Furthermore, since depression is often a co-morbidity in patients with chronic conditions (i.e. cancer, neurodegenerative diseases) the use of antidepressants interfering with pathways in-volved in cell homeostasis may affect the progression and outcome of these pathologies. Here we investigate the effects of amitriptyline on proliferation and autophagy in human SH-SY5Y neuroblastoma cells. Dose and time-dependent upregulation of the autophagy markers LC3II and autophagy receptor p62, with accumulation of LAMP1 positive compartments, were observed in SH-SY5Y cells exposed to amitriptyline. Alteration of autophagy was accompanied by reduced cell viability and decreased clonogenic capacity, without a significant induction of apoptosis. Decrease viability and clonogenic activity were still observed in autophagy deficient Atg5 -/- MEF and following pre-treatment of SH-SY5Y culture with the autophagy inhibitor chloroquine suggesting that the amitriptyline’s effects on cell proliferation were not caused by the modulation of autophagy. Our findings demonstrate that amitriptyline acts on pathways that are crucial for cell and tissue homeostasis and pose the basis for further studies on the potential application of these effects and the consequences during long-term antidepressant treatment.

Fine dust causes various disorders, including cardiovascular, neurological, renal, reproductive, motor, systemic, respiratory, and cancerous diseases. Therefore, it is necessary to study functional materials to prevent these problems. In this study we used various methods, including quantitative PCR, flow cytometry, ELISA, and Alizarin O staining, to study the beneficial effects of erucic acid against fine dust. Erucic acid and erucic acid-induced exosomes (EIE) strongly suppress the attenuation of osteocytic differentiation and inflammation induced by fine dust. Erucic acid effectively suppresses inflammation in fibroblasts exposed to fine dust. Notably, despite exposure to fine dust, EIE promoted osteocytic differentiation in adipose-derived stem cells (ASC) and osteogenesis in macrophages, in addition to phagocytosis. Dramatic upregulation of RunX2 and BMP7 by EIE indicates that it is a strong activator of osteocytic differentiation in ASC and protects them from the effects of fine dust. Moreover, EIE induces immune activity and acts as an osteogenic trigger for macrophages. Therefore, this study suggests the potential use of erucic acid and erucic acid-induced exosomes (EIE) as biomaterials to prevent environment-borne diseases.

This study explores the use of remote ultrasound vibration to enhance welding strength. It examines the effects of 20 kHz, and 40 kHz High Power Ultrasound Transducers (HPUT) in contact and contactless modes during ultrasonic assistance laser welding. Employing shear tests and microscopy for assessment, the research evaluates ultrasound's impact on welding strength and identifies the optimal transducer. Theoretical and numerical analyses investigate vibration transmission into the welding area, particularly examining the vibration distribution and cavitation initiation within the molten pool area. Results indicate that ultrasound-assisted welding increases pull test performance, including the resistance force and strain, and improves microscopic structural integrity. Numerical simulations suggest that narrow-band vibration intensifies pressure in specific welding zones. Contactless ultrasound application also shows enhanced welding quality, offering a promising alternative to current methods. This work contributes to electric car technology by suggesting improvements in welding techniques for power battery systems.

Neurodegenerative diseases that include Alzheimer's disease (AD), amyotrophic lateral sclerosis (ALS), Parkinson's disease (PD), Huntington's disease (HD), and multiple sclerosis (MS), arise due to numerous causes like protein accumulation and autoimmunity, characterized by neurologic depletion which lead to incapacity in normal physiological function such as thinking and movement in these patients. Glial cells perform a critical role in protective neuronal function; in the case of neuroinflammation, glial cell dysfunction can promote the development of neurodegenerative diseases. MiRNA participates in gene regulation and plays a vital role in many biological processes in the body; in the central nervous system (CNS), it can play an essential part in neural maturation and differentiation. In neurodegenerative diseases, miRNA dysregulation occurs, enhancing the development of these diseases. In this review, we discuss neurodegenerative diseases (Alzheimer's disease (AD), Parkinson's disease (PD), amyotrophic lateral sclerosis (ALS), and multiple sclerosis (MS)) and how miRNA is preserved as a diagnostic biomarker or therapeutic agent in these disorders. Finally, we highlighted miRNA as therapy.

The mechanisms underlying the establishment of asymmetric structures during development remain elusive. The wing of Drosophila is asymmetric along the Anterior-Posterior (AP) axis, despite that its growth signals that drive its growth are presumably symmetric. Here, we investigated the contribution of cell recruitment, a process that drives wing fate differentiation in Drosophila, to the asymmetric shape and pattern of the adult wing. Genetic impairment of cell recruitment results in a significant reduction in adult wing asymmetry, primarily affecting the region between longitudinal vein 5 and the wing margin (L5-M). Morphometric analysis reveals that the lack of cell recruitment results in a more symmetric wing with respect to the AP, suggesting a contribution of cell recruitment to the establishment of asymmetry in the adult wing. A close examination of the expression of the wing selector gene vestigial (vg) in wing disc does not support this hypothesis. However, the circularity of the Vg pattern significantly increase in recruitment-impaired wing disc, suggesting that while the decrease of the L5-M region in the adult wing may not be attributed to cell recruitment, it could contribute to the overall asymmetry of the adult wing. We conclude that cell recruitment, a widespread mechanism that participates in growth and patterning of several developing systems, could drive, at least partially, the asymmetric shape of the Drosophila wing.