In the last years, the Emergency Department (ED) has become an important source of admissions for hospitals. Since late 90s, the number of ED visits has been steadily increasing, and since Covid19 ...pandemic this trend has been much stronger. Accurate prediction of ED visits, even for moderate forecasting time-horizons, can definitively improve operational efficiency, quality of care, and patient outcomes in hospitals.
In this paper we propose two different interpretable approaches, based on Machine Learning algorithms, to accurately forecast hospital emergency visits. The proposed approaches involve a first step of data segmentation based on two different criteria, depending on the approach considered: first, a threshold-based strategy is adopted, where data is divided depending on the value of specific predictor variables. In a second approach, a cluster-based ensemble learning is proposed, in such a way that a clustering algorithm is applied to the training dataset, and ML models are then trained for each cluster.
The two proposed methodologies have been evaluated in real data from two hospital ED visits datasets in Spain. We have shown that the proposed approaches are able to obtain accurate ED visits forecasting, in short-term and also long-term prediction time-horizons up to one week, improving the efficiency of alternative prediction methods for this problem.
The proposed forecasting approaches have a strong emphasis on providing explainability to the problem. An analysis on which variables govern the problem and are pivotal for obtaining accurate predictions is finally carried out and included in the discussion of the paper.
•Forecasting of green mobility-related demand is approached for three problems.•Twelve Machine Learning and Deep Learning time series approaches are assessed.•Predictive variables are grouped into four sets whose relevance is studied.•A feature selection mechanism is incorporated to improve the prediction accuracy.•Excellent results in all the prediction problems approached are reported.
Up to 80% of patients surviving acute respiratory distress syndrome (ARDS) secondary to SARS-CoV-2 infection present persistent anomalies in pulmonary function after hospital discharge. There is a ...limited understanding of the mechanistic pathways linked to post-acute pulmonary sequelae.
To identify the molecular underpinnings associated with severe lung diffusion involvement in survivors of SARS-CoV-2-induced ARDS.
Survivors attended to a complete pulmonary evaluation 3 months after hospital discharge. RNA sequencing (RNA-seq) was performed using Illumina technology in whole-blood samples from 50 patients with moderate to severe diffusion impairment (DLCO<60%) and age- and sex-matched individuals with mild-normal lung function (DLCO≥60%). A transcriptomic signature for optimal classification was constructed using random forest. Transcriptomic data were analyzed for biological pathway enrichment, cellular deconvolution, cell/tissue-specific gene expression and candidate drugs.
RNA-seq identified 1357 differentially expressed transcripts. A model composed of 14 mRNAs allowed the optimal discrimination of survivors with severe diffusion impairment (AUC=0.979). Hallmarks of lung sequelae involved cell death signaling, cytoskeleton reorganization, cell growth and differentiation and the immune response. Resting natural killer (NK) cells were the most important immune cell subtype for the prediction of severe diffusion impairment. Components of the signature correlated with neutrophil, lymphocyte and monocyte counts. A variable expression profile of the transcripts was observed in lung cell subtypes and bodily tissues. One upregulated gene, TUBB4A, constitutes a target for FDA-approved drugs.
This work defines the transcriptional programme associated with post-acute pulmonary sequelae and provides novel insights for targeted interventions and biomarker development.
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•A distinct transcriptional program is associated with severe diffusion impairment.•Cell death and cytoskeletal architecture are implicated in pulmonary dysfunction.•TUBB4A emerges as a potential target to treat the respiratory functional sequelae.•A transcriptomic signature accurately identifies survivors with severe alterations.
Liver metastasis in colorectal cancer is the major cause of cancer-related deaths. To identify and characterize proteins associated with colon cancer metastasis, we have compared the conditioned ...serum-free medium of highly metastatic KM12SM colorectal cancer cells with the parental, poorly metastatic KM12C cells using quantitative stable isotope labeling by amino acids in cell culture (SILAC) analyses on a linear ion trap-Orbitrap Velos mass spectrometer. In total, 1337 proteins were simultaneously identified in SILAC forward and reverse experiments. For quantification, 1098 proteins were selected in both experiments, with 155 proteins showing >1.5-fold change. About 52% of these proteins were secreted directly or using alternative secretion pathways. GDF15, S100A8/A9, and SERPINI1 showed capacity to discriminate cancer serum samples from healthy controls using ELISAs. In silico analyses of deregulated proteins in the secretome of metastatic cells showed a major abundance of proteins involved in cell adhesion, migration, and invasion. To characterize the tumorigenic and metastatic properties of some top up- and down-regulated proteins, we used siRNA silencing and antibody blocking. Knockdown expression of NEO1, SERPINI1, and PODXL showed a significant effect on cellular adhesion. Silencing or blocking experiments with SOSTDC1, CTSS, EFNA3, CD137L/TNFSF9, ZG16B, and Midkine caused a significant decrease in migration and invasion of highly metastatic cells. In addition, silencing of SOSTDC1, EFNA3, and CD137L/TNFSF9 reduced liver colonization capacity of KM12SM cells. Finally, the panel of six proteins involved in invasion showed association with poor prognosis and overall survival after dataset analysis of gene alterations. In summary, we have defined a collection of proteins that are relevant for understanding the mechanisms underlying adhesion, migration, invasion, and metastasis in colorectal cancer.
Signet‐ring cells are morphologically defined by the presence of a large intracytoplasmic vacuole that compresses and displaces the nucleus to the periphery. In most cases, these cells are associated ...with adenocarcinomas of various locations, and with non‐epithelial neoplasms. To date, less than 20 cases of squamous cell carcinoma with signet‐ring morphology have been described, mainly located on the skin. We present the case of a 73‐year‐old male with pleural effusion and a left lower lobe mass. The cytological study of the pleural effusion allowed the diagnosis of metastasis of squamous cell carcinoma, signet‐ring cell variant. The treatment of lung cancer in advanced stages requires a precise diagnosis that allows the best therapy to be offered to the patient, depending on the clinical stage and the positivity of the biomarkers, among others. Our patient died 18 months after the initial diagnosis.
The influence of particle size in both the structure and thermochromic behavior of 4H-SrMnO3 related perovskite is described. Microsized SrMnO3 suffers a structural transition from hexagonal ...(P63/mmc) to orthorhombic (C2221) symmetry at temperature close to 340 K. The orthorhombic distortion is due to the tilting of the corner-sharing Mn2O9 units building the 4H structural type. When temperature decreases, the distortion becomes sharper reaching its maximal degree at ∼125 K. These structural changes promote the modification of the electronic structure of orthorhombic SrMnO3 phase originating the observed color change. nano-SrMnO3 adopts the ideal 4H hexagonal structure at room temperature, the orthorhombic distortion being only detected at temperature below 170 K. A decrease in the orthorhombic distortion degree, compared to that observed in the microsample, may be the reason why a color change is not observed at low temperature (77 K).
We performed a study of congenital toxoplasmosis of the first and third gestation periods in mice, and determined its effects on the embryos/fetuses, the placentae and the maternal organs. We ...infected pregnant BALB/c mice by i.v. injection of 2.5‐–10.0 × 106 tachyzoites of the ME49 T. gondii strain and euthanized them 72 h later. The tissues were analyzed by histopathology, immunohistochemistry and parasite-specific qPCR. Infections with the lowest dose induced remarkably different changes in the two thirds: a) all doses diminished the number of products/litter, the lowest dose only by 14%; but most embryos still visible were degenerated in the case of the first period, while the fetuses of the last third were perfectly preserved; b) the transmission rate in the first third was relatively high, but with a very low parasite burden; c) with the lowest dose, strong vascular changes (congestion, thrombosis and hemorrhage) predominated in the placentas of the first period, while they were absent in the last third; d) necrosis caused by T. gondii to maternal organs was much stronger during the last gestation period than in the first. Our results suggest that the vascular alterations at the placenta of the first third of pregnancy prevent embryo from large parasite burden, but provoke its death by starvation. In the last gestation period, there was poor control of parasite dissemination to the placenta and the fetus, but there was greater capacity of the product to defend itself from T. gondii.
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•Pathological events in maternal organs, placentas and offspring vary between the first and third gestation periods•Toxoplasma gondii causes vascular alterations at the placenta along gestation•The death of the first third embryos was related to signs of starvation and not to parasite induced necrosis
In this paper the performance of different Machine Learning and Deep Learning approaches is evaluated in problems related to green mobility in big cities. Specifically, the forecasting of bike ...sharing demand in Madrid and Barcelona (Spain) is approached, for different prediction time-horizons, and also a problem of cable car demand forecasting in Madrid city. An important number of predictive variables are considered, which are grouped into four different sets (categorical/calendrical, persistence-based, meteorological and, as a novelty of the paper, information about analogue past instances), whose relevance is studied for all cases. A feature selection mechanism is also incorporated in order to improve the prediction accuracy of the proposed algorithms. A total of 12 different multivariate regression techniques are implemented, covering from Machine Learning methods to time-series Deep Learning approaches. Excellent results in all the prediction problems approached are reported. Finally, the consequences of obtaining accurate prediction in these three problem of green mobility in big cities are discussed. In addition, it is studied how the results could be exported to other similar cases in more general urban mobility studies. Novelties of the work include: (1) Addressing the forecast problem of passenger flow on a cable car using ML and DL multivariate techniques; (2) using the demand of analogous past instances as an additional feature to solve the demand prediction problems; and (3) the extraction of global conclusions about feature relevance when addressing a demand forecasting problem in green mobility.
Toxoplasma gondii has at least 318 genotypes distributed worldwide, and tropical regions usually have greater genetic diversity. Campeche is a state located in the southeastern region of México and ...has favourable climate conditions for the replication and dissemination of this protozoan, similar to those in South American countries where broad genetic diversity has been described. Thus, in this study, 4 T. gondii isolates were obtained from tissues of stray dogs and free-range chickens in Campeche, México, and were genotyped by Mn-PCR-RFLP with 10 typing markers (SAG1, altSAG2, SAG3, BTUB, GRA6, c22-8, c29-2, L358, PK1 and Apico) and 5 virulence markers (CS3, ROP16, ROP17, ROP18 and ROP5) to provide new information about the distribution and virulence prediction of T. gondii genotypes. Two isolates of T. gondii genotype #116 and 2 of genotype #38 were obtained from stray dogs and chickens, respectively. The parasite load found in these species was between <50 and more than 35 000 tachyzoites per mg of tissue. Virulence marker genotyping revealed a recombinant 1&3 ROP5 RFLP pattern in 2 ToxoDB #116 isolates with no prediction of virulence in a murine model, while in the 2 ToxoDB #38 isolates, the ROP18/ROP5 combination predicted high virulence. Considering all the typed markers, there is a predominance of type I and III alleles, as constantly reported for the isolates characterized in various regions of México. It is crucial to determine their phenotype to corroborate the genetic virulence profile of the T. gondii isolates obtained in this study.
Extracellular vesicles (EVs) are evaginations of the cytoplasmic membrane, containing nucleic acids, proteins, lipids, enzymes, and toxins. EVs participate in various bacterial physiological ...processes.
interacts and communicates with the host skin.
EVs may have an essential role in this communication mechanism, modulating the immunological environment. This work aimed to evaluate if
EVs can modulate cytokine production by keratinocytes in vitro and in vivo using the imiquimod-induced psoriasis murine model.
EVs were obtained from a commensal strain (ATC12228EVs) and a clinical isolated strain (983EVs). EVs from both origins induced IL-6 expression in HaCaT keratinocyte cultures; nevertheless, 983EVs promoted a higher expression of the pro-inflammatory cytokines VEGF-A, LL37, IL-8, and IL-17F than ATCC12228EVs. Moreover, in vivo imiquimod-induced psoriatic skin treated with ATCC12228EVs reduced the characteristic psoriatic skin features, such as acanthosis and cellular infiltrate, as well as VEGF-A, IL-6, KC, IL-23, IL-17F, IL-36γ, and IL-36R expression in a more efficient manner than 983EVs; however, in contrast, Foxp3 expression did not significantly change, and IL-36 receptor antagonist (IL-36Ra) was found to be increased. Our findings showed a distinctive immunological profile induction that is dependent on the clinical or commensal EV origin in a mice model of skin-like psoriasis. Characteristically, proteomics analysis showed differences in the EVs protein content, dependent on origin of the isolated EVs. Specifically, in ATCC12228EVs, we found the proteins glutamate dehydrogenase, ornithine carbamoyltransferase, arginine deiminase, carbamate kinase, catalase, superoxide dismutase, phenol-soluble β1/β2 modulin, and polyglycerol phosphate α-glucosyltransferase, which could be involved in the reduction of lesions in the murine imiquimod-induced psoriasis skin. Our results show that the commensal ATCC12228EVs have a greater protective/attenuating effect on the murine imiquimod-induced psoriasis by inducing IL-36Ra expression in comparison with EVs from a clinical isolate of
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