Miracle-dz/UniFAR-FTUs huggingface dataset:
gH625-liposomes deliver PACAP through a dynamic in vitro model of the blood–brain barrier

The blood–brain barrier (BBB) selectively protects the central nervous system (CNS) from external insults, but its function can represent a limit for the passage of therapeutic molecules. Numerous in vitro models of the BBB have been realized in order to study the passage of drugs for neurodegenerative diseases, but these in vitro models are not very representative of the physiological conditions because of a limited supply of oxygen and nutrients due to static conditions. To avoid this phenomenon, we used a millifluidic bioreactor model that ensures a circulation of the medium and, therefore, of the nutrients, thanks to the continuous laminar flow. This dynamic model consists of a double-culture chamber separated by a membrane on which brain endothelial cells are cultured in order to evaluate the passage of the drug. Furthermore, in the lower chamber, SH-SY5Y were seeded as 3D spheroids to evaluate the drug passage through these cells. As nanodelivery system, we used liposomes functionalized with viral fusion peptide to evaluate the passage of a neuroprotective agent, pituitary adenylate cyclase-activating polypeptide (PACAP), through the dynamic in vitro model of the BBB. We showed that our nanodelivery system, made of functionalized liposomes and loaded with specific molecules, efficiently crosses the in vitro fluid-dynamic model of the BBB. Our findings represent an important step for further experimental investigations on PACAP administration as a therapeutic agent by an enhanced drug delivery system. Our results can improve the diffusion of good practice in neuroscience laboratories, helping to spread the 3R rules.
Human dendritic cell targeting peptide can be targeted to porcine dendritic cells to improve antigen capture efficiency to stimulate stronger immune response

Dendritic cells (DCs) play a key role in the natural recognition of pathogens and subsequent activation of adaptive immune responses due to their potent antigen-presenting ability. Dendritic cell-targeting peptide (DCpep) is strongly targeted to DCs, which often express antigens, to enhance the efficacy of vaccines. Our previous study showed that recombinant Lactobacillus expressing human DCpep could significantly induce stronger immune responses than recombinant Lactobacillus without DCpep, but the mechanism remains unclear. In this study, the mechanism by which DCpep enhances the immune response against recombinant Lactobacillus was explored. Fluorescence-labeled human DCpep was synthesized to evaluate the binding ability of human DCpep to porcine monocyte-derived dendritic cells (Mo-DCs) and DCs of the small intestine. The effects of Mo-DC function induced by recombinant Lactobacillus expressing human DCpep fused with the porcine epidemic diarrhea virus (PEDV) core neutralizing epitope (COE) antigen were also investigated. The results showed that human DCpep bind to porcine DCs, but not to porcine small intestinal epithelial cells. Human DCpep can also improve the capture efficiency of recombinant Lactobacillus by Mo-DCs, promote the maturation of dendritic cells, secrete more cytokines, and enhance the ability of porcine DCs to activate T-cell proliferation. Taken together, these results promote advanced understanding of the mechanism by which DCpep enhances immune responses. We found that some DCpeps are conserved between humans and pigs, which provides a theoretical basis for the development of a DC-targeted vaccine.
Human Impact Scale on the Preservation of Archaeological Sites from Mostiştea Valley (Romania)

Through time, both natural and cultural heritage have unfortunately been under threat due to multiple environmental and human-induced factors, which are likely to trigger various hazards such as soil erosion, landslides, or land collapse. The analysis of old cartographic material, aerial imagery, and satellite imagery has been used in multiple studies to observe and understand the changes that archaeological sites have undergone over the last centuries. These efforts are intended, among other things, to raise awareness of the threats affecting cultural heritage and prevent damages and preserve tangible evidence of the distant past. In this study, historical maps and satellite imagery were analyzed to observe how the landscape in the Mostiștea Valley (Romania) has been used over the last 230 years and how the land use has affected the cultural heritage. Land cover and land use (LCLU) changes in the Mostiștea Valley have occurred due to numerous natural and anthropic forces. These changes have resulted in the damage of tangible heritage in the area with varying degrees of intensity. The results of this study allow the quantification of the magnitude of these changes and their impact on different sites in the region.
An improved automated diatom detection method based on YOLOv5 framework and its preliminary study for taxonomy recognition in the forensic diatom test

The diatom test is a forensic technique that can provide supportive evidence in the diagnosis of drowning but requires the laborious observation and counting of diatoms using a microscopy with too much effort, and therefore it is promising to introduce artificial intelligence (AI) to make the test process automatic. In this article, we propose an artificial intelligence solution based on the YOLOv5 framework for the automatic detection and recognition of the diatom genera. To evaluate the performance of this AI solution in different scenarios, we collected five lab-grown diatom genera and samples of some organic tissues from drowning cases to investigate the potential upper/lower limits of the capability in detecting the diatoms and recognizing their genera. Based on the study of the article, a recall score of 0.95 together with the corresponding precision score of 0.9 were achieved on the samples of the five lab-grown diatom genera via cross-validation, and the accuracy of the evaluation in the cases of kidney and liver is above 0.85 based on the precision and recall scores, which demonstrate the effectiveness of the AI solution to be used in drowning forensic routine.
3D bioprinting of multi-layered segments of a vessel-like structure with ECM and novel derived bioink

3D-Bioprinting leads to the realization of tridimensional customized constructs to reproduce the biological structural complexity. The new technological challenge focuses on obtaining a 3D structure with several distinct layers to replicate the hierarchical organization of natural tissues. This work aims to reproduce large blood vessel substitutes compliant with the original tissue, combining the advantages of the 3D bioprinting, decellularization, and accounting for the presence of different cells. The decellularization process was performed on porcine aortas. Various decellularization protocols were tested and evaluated through DNA extraction, quantification, and amplification by PCR to define the adequate one. The decellularized extracellular matrix (dECM), lyophilized and solubilized, was combined with gelatin, alginate, and cells to obtain a novel bioink. Several solutions were tested, tuning the percentage of the components to obtain the adequate structural properties. The geometrical model of the large blood vessel constructs was designed with SolidWorks, and the construct slicing was done using the HeartWare software, which allowed generating the G-Code. The final constructs were 3D bioprinted with the Inkredible + using dual print heads. The composition of the bioink was tuned so that it could withstand the printing of a segment of a tubular construct up to 10 mm and reproduce the multicellular complexity. Among the several compositions tested, the suspension resulting from 8% w/v gelatin, 7% w/v alginate, and 3% w/v dECM, and cells successfully produced the designed structures. With this bioink, it was possible to print structures made up of 20 layers. The dimensions of the printed structures were consistent with the designed ones. We were able to avoid the double bioink overlap in the thickness, despite the increase in the number of layers during the printing process. The optimization of the parameters allowed the production of structures with a height of 20 layers corresponding to 9 mm. Theoretical and real structures were very close. The differences were 14% in height, 20% internal diameter, and 9% thickness. By tailoring the printing parameters and the amount of dECM, adequate mechanical properties could be met. In this study, we developed an innovative printable bioink able to finely reproduce the native complex structure of the large blood vessel.
Mechanical regulation of signal transduction in angiogenesis

Biophysical and biochemical cues work in concert to regulate angiogenesis. These cues guide angiogenesis during development and wound healing. Abnormal cues contribute to pathological angiogenesis during tumor progression. In this review, we summarize the known signaling pathways involved in mechanotransduction important to angiogenesis. We discuss how variation in the mechanical microenvironment, in terms of stiffness, ligand availability, and topography, can modulate the angiogenesis process. We also present an integrated view on how mechanical perturbations, such as stretching and fluid shearing, alter angiogenesis-related signal transduction acutely, leading to downstream gene expression. Tissue engineering-based approaches to study angiogenesis are reviewed too. Future directions to aid the efforts in unveiling the comprehensive picture of angiogenesis are proposed.
Electroacupuncture ameliorates peptic ulcer disease in association with gastroduodenal microbiota modulation in mice

Peptic ulcer disease (PUD) is a common disease and frequently encountered in the clinic. Accumulating evidence suggests that PUD is associated with the gastrointestinal microbiota. Electroacupuncture (EA) is an improved version of acupuncture, which can improve the clinical effect by increasing the stimulation and delivering appropriate electrical pulses to needles. This method has been widely used in the treatment of peptic ulcer disease. However, its effect on gastrointestinal microbiota remains unclear. Therefore, in the present study, the ameliorative effect of EA was evaluated on the gastroduodenal mucosa, and the regulatory effect of the gastroduodenal microbiota was assessed in PUD mice. A total of 48 male Kun Ming mice were randomly divided into the following groups: normal control group (NC), PUD model group (PUD), Shousanli group (LI10), and Zusanli group (ST36) (n=12). The mice in groups LI10 and ST36 were treated with EA at LI10 and ST36, respectively. This intervention was continued for 7 days. Subsequently, we evaluated the morphological changes in the gastric and duodenal mucosa, and specific indices were measured, including the contents of serum dopamine (DA), the trefoil factor (TFF), and the vasoactive intestinal peptide (VIP). In addition, the gastric and duodenal microbiota were assessed via 16S ribosomal DNA sequencing. The results indicated that EA at LI10 or ST36 significantly reduced the injury of the gastroduodenal mucosa in PUD mice. The gastric microbial community structure of the groups LI10 and ST36 was similar to that of the NC group following comparison with the microbial community structure of the PUD model group. Moreover, the abundance of Firmicutes in the stomach was decreased, whereas that of Bacteroidetes was increased, and the abundance of Firmicutes in the duodenum was decreased. Furthermore, the microbial diversity and richness of the gastric microbiota in group LI10 were also significantly increased, and the serum dopamine and trefoil factor levels in group ST36 were significantly increased. Therefore, it is suggested that EA ameliorating PUD is in association with improving the levels of DA and TFF and regulating the relative abundances of Firmicutes and Bacteroidetes in the gastric microbiota.
Transcriptomic analysis of CO2-treated strawberries (Fragaria vesca) with enhanced resistance to softening and oxidative stress at consumption

One of the greatest threats to wild strawberries (Fragaria vesca Mara des Bois) after harvest is the highly perishability at ambient temperature. Breeders have successfully met the quality demands of consumers, but the prevention of waste after harvest in fleshy fruits is still pending. Most of the waste is due to the accelerated progress of senescence-like process after harvest linked to a rapid loss of water and firmness at ambient temperature. The storage life of strawberries increases at low temperature, but their quality is limited by the loss of cell structure. The application of high CO2 concentrations increased firmness during cold storage. However, the key genes related to resistance to softening and cell wall disassembly following transference from cold storage at 20°C remain unclear. Therefore, we performed RNA-seq analysis, constructing a weighted gene co-expression network analysis (WGCNA) to identify which molecular determinants play a role in cell wall integrity, using strawberries with contrasting storage conditions, CO2-cold stored (CCS), air-cold stored (ACS), non-cold stored (NCS) kept at ambient temperature, and intact fruit at harvest (AH). The hub genes associated with the cell wall structural architecture of firmer CO2-treated strawberries revealed xyloglucans stabilization attributed mainly to a down-regulation of Csl E1, XTH 15, Exp-like B1 and the maintenance of expression levels of nucleotide sugars transferases such as GMP and FUT as well as improved lamella integrity linked to a down-regulation of RG-lyase, PL-like and PME. The preservation of cell wall elasticity together with the up-regulation of LEA, EXPA4, and MATE, required to maintain cell turgor, is the mechanisms controlled by high CO2. In stressed air-cold stored strawberries, in addition to an acute softening, there is a preferential transcript accumulation of genes involved in lignin and raffinose pathways. Non-cold stored strawberries kept at 20°C after harvest are characterized by an enrichment in genes mainly involved in oxidative stress and up-expression of genes involved in jasmonate biosynthesis. The present results on transcriptomic analysis of CO2-treated strawberries with enhanced resistance to softening and oxidative stress at consumption will help to improve breeding strategies of both wild and cultivated strawberries.
Deep learning-based gas-phase chemical kinetics kernel emulator: Application in a global air quality simulation case

The global atmospheric chemical transport model has become a key technology for air quality forecast and management. However, precise and rapid air quality simulations and forecast are frequently limited by the model’s computational performance. The gas-phase chemistry module is the most time-consuming module in air quality models because its traditional solution method is dynamically stiff. To reduce the solving time of the gas phase chemical module, we built an emulator based on a deep residual neural network emulator (NN) for Carbon Bond Mechanism Z (CBM-Z) mechanism implemented in Global Nested Air Quality Prediction Modeling System. A global high resolution cross-life multi-species dataset was built and trained to evaluate multi-species concentration changes at a single time step of CBM-Z. The results showed that the emulator could accelerate to approximately 300–750 times while maintaining an accuracy similar to that of CBM-Z module (the average correlation coefficient squared was 0.97) at the global scale. This deep learning-based emulator could adequately represent the stiff kinetics of CBM-Z, which involves 47 species and 132 reactions. The emulated ozone (O3), nitrogen oxides (NOx), and hydroxyl radical (OH) were consistent with those of the original CBM-Z module in different global regions, heights, and time. Our results suggest that data-driven emulations have great potential in the construction of hybrid models with process-based air quality models, particularly at larger scales.
Exploring pathological signatures for predicting the recurrence of early-stage hepatocellular carcinoma based on deep learning

Background Postoperative recurrence impedes the curability of early-stage hepatocellular carcinoma (E-HCC). We aimed to establish a novel recurrence-related pathological prognosticator with artificial intelligence, and investigate the relationship between pathological features and the local immunological microenvironment. Methods A total of 576 whole-slide images (WSIs) were collected from 547 patients with E-HCC in the Zhongshan cohort, which was randomly divided into a training cohort and a validation cohort. The external validation cohort comprised 147 Tumor Node Metastasis (TNM) stage I patients from The Cancer Genome Atlas (TCGA) database. Six types of HCC tissues were identified by a weakly supervised convolutional neural network. A recurrence-related histological score (HS) was constructed and validated. The correlation between immune microenvironment and HS was evaluated through extensive immunohistochemical data. Results The overall classification accuracy of HCC tissues was 94.17%. The C-indexes of HS in the training, validation and TCGA cohorts were 0.804, 0.739 and 0.708, respectively. Multivariate analysis showed that the HS (HR= 4.05, 95% CI: 3.40-4.84) was an independent predictor for recurrence-free survival. Patients in HS high-risk group had elevated preoperative alpha-fetoprotein levels, poorer tumor differentiation and a higher proportion of microvascular invasion. The immunohistochemistry data linked the HS to local immune cell infiltration. HS was positively correlated with the expression level of peritumoral CD14+ cells (p= 0.013), and negatively with the intratumoral CD8+ cells (p< 0.001). Conclusions The study established a novel histological score that predicted short-term and long-term recurrence for E-HCCs using deep learning, which could facilitate clinical decision making in recurrence prediction and management.
Investigating the differences between females perceive same-gender and heterogender sex robots regarding adoption and intentions

The market for sex robots is on the rise with the development of human–computer interaction. However, most sex robots on the market are presented as male-friendly products. This issue may limit and hinder females' adoption and utilization of sex robots. This paper was to take females as the research subjects exploring and verifying several concerns based on previous theories and to conduct primary research and quantitative method to investigate: (i) how females differently perceive same-gender and heterogender sex robots; (ii) their attitudes and the knowledge or definition of sex robots; and (iii) their intention of adopting heterogender robots. This study confirmed several previous theories and provided new findings and insights. Females are more likely to feel threatened by the presence of same-gender sex robots. Their negative attitudes are related to the way that sex robots exist. They are jealous of same-gender sex robots; nevertheless, this should not be attributed to their negative perception of sex robots since they also have positive perceptions and intentions to adopt a sex robot. They define sex robots more as sexual products than as engaging in the prostitution industry.
Using network pharmacology to explore the mechanism of Danggui-Shaoyao-San in the treatment of diabetic kidney disease

Danggui-Shaoyao-San (DSS) is one of traditional Chinese medicine, which recently was found to play a protective role in diabetic kidney disease (DKD). However, the pharmacological mechanisms of DSS remain obscure. This study would explore the molecular mechanisms and bioactive ingredients of DSS in the treatment of DKD through network pharmacology. The potential target genes of DKD were obtained through OMIM database, the DigSee database and the DisGeNET database. DSS-related targets were acquired from the BATMAN-TCM database and the STITCH database. The common targets of DSS and DKD were selected for analysis in the STRING database, and the results were imported into Cytoscape to construct a protein-protein interaction network. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enrichment analysis and Gene Ontology (GO) enrichment analysis were carried out to further explore the mechanisms of DSS in treating DKD. Molecular docking was conducted to identify the potential interactions between the compounds and the hub genes. Finally, 162 therapeutic targets of DKD and 550 target genes of DSS were obtained from our screening process. Among this, 28 common targets were considered potential therapeutic targets of DSS for treating DKD. Hub signaling pathways including HIF-1 signaling pathway, TNF signaling pathway, AMPK signaling pathway, mTOR signaling pathway, and PI3K-Akt signaling pathway may be involved in the treatment of DKD using DSS. Furthermore, TNF and PPARG, and poricoic acid C and stigmasterol were identified as hub genes and main active components in this network, respectively. In this study, DSS appears to treat DKD by multi-targets and multi-pathways such as inflammatory, oxidative stress, autophagy and fibrosis, which provided a novel perspective for further research of DSS for the treatment of DKD.
Multiple Pickering emulsions stabilized by the same particles with different extent of hydrophobization in situ

Multiple emulsions are widely used in pharmaceuticals, foods, and cosmetics. However, those stabilized by surfactants with different HLB values are generally unstable due to the diffusion of the surfactants between inner and outer interfaces. Here, we report that multiple W/O/W emulsions can be prepared by using the same particles in combination with a surfactant of different concentrations. The less surface-active raw CaCO3 nanoparticles can be hydrophobized to surface-active in situ by adsorption of the anionic surfactant SDS, and the wettability of the particles can be controlled to be suitable for stabilizing both O/W and W/O Pickering emulsions by adjusting the surfactant concentration. With toluene as oil phase, the CaCO3 particles at 1.0 wt% tend to stabilize a W/O emulsion in the presence of 3 mm SDS in an aqueous solution, which can then be further dispersed in an aqueous phase with 1.0 wt% CaCO3 and SDS below 1 mm to form a W/O/W multiple emulsion. The effects of the ratio of W/O emulsion to the outer water phase and the preparation methods on stabilization of multiple emulsions were examined. With a ratio smaller than 3:1 and by gentle magnetic stirring, the multiple emulsions obtained can stay stable for at least a month without coalescence. This simple method not only ensures stabilization of multiple emulsions but also avoids complicated synthesis of colloid particles with different wettability.