Miracle-dz/UniFAR-FTUs huggingface dataset:
Industrial Semi-Supervised Dynamic Soft-Sensor Modeling Approach Based on Deep Relevant Representation Learning

Soft sensors based on deep learning have been growing in industrial process applications, inferring hard-to-measure but crucial quality-related variables. However, applications may present strong non-linearity, dynamicity, and a lack of labeled data. To deal with the above-cited problems, the extraction of relevant features is becoming a field of interest in soft-sensing. A novel deep representative learning soft-sensor modeling approach is proposed based on stacked autoencoder (SAE), mutual information (MI), and long-short term memory (LSTM). SAE is trained layer by layer with MI evaluation performed between extracted features and targeted output to evaluate the relevance of learned representation in each layer. This approach highlights relevant information and eliminates irrelevant information from the current layer. Thus, deep output-related representative features are retrieved. In the supervised fine-tuning stage, an LSTM is coupled to the tail of the SAE to address system inherent dynamic behavior. Also, a k-fold cross-validation ensemble strategy is applied to enhance the soft-sensor reliability. Two real-world industrial non-linear processes are employed to evaluate the proposed method performance. The obtained results show improved prediction performance in comparison to other traditional and state-of-art methods. Compared to the other methods, the proposed model can generate more than 38.6% and 39.4% improvement of RMSE for the two analyzed industrial cases.
Differential Spatio-Temporal Regulation of T-Box Gene Expression by microRNAs during Cardiac Development

Cardiovascular development is a complex process that starts with the formation of symmetrically located precardiac mesodermal precursors soon after gastrulation and is completed with the formation of a four-chambered heart with distinct inlet and outlet connections. Multiple transcriptional inputs are required to provide adequate regional identity to the forming atrial and ventricular chambers as well as their flanking regions; i.e., inflow tract, atrioventricular canal, and outflow tract. In this context, regional chamber identity is widely governed by regional activation of distinct T-box family members. Over the last decade, novel layers of gene regulatory mechanisms have been discovered with the identification of non-coding RNAs. microRNAs represent the most well-studied subcategory among short non-coding RNAs. In this study, we sought to investigate the functional role of distinct microRNAs that are predicted to target T-box family members. Our data demonstrated a highly dynamic expression of distinct microRNAs and T-box family members during cardiogenesis, revealing a relatively large subset of complementary and similar microRNA–mRNA expression profiles. Over-expression analyses demonstrated that a given microRNA can distinctly regulate the same T-box family member in distinct cardiac regions and within distinct temporal frameworks, supporting the notion of indirect regulatory mechanisms, and dual luciferase assays on Tbx2, Tbx3 and Tbx5 3′ UTR further supported this notion. Overall, our data demonstrated a highly dynamic microRNA and T-box family members expression during cardiogenesis and supported the notion that such microRNAs indirectly regulate the T-box family members in a tissue- and time-dependent manner.
Off-Label Use of 0.19 mg Fluocinolone Acetonide Intravitreal Implant: A Systematic Review

Corticosteroids are used in a variety of ophthalmological diseases. One challenge faced by ophthalmologists is to deliver corticosteroids to the posterior segment of the eye with efficacy and safety. Sustained-release corticosteroid implants may be the answer to this problem. The 0.19 mg fluocinolone acetonide (FAc) implant (Iluvien®) releases FAc for 36 months, and it is approved for the treatment of diabetic macular edema (DME) and noninfectious uveitis. We decided to do a systematic review to acknowledge in which other diseases FAc implant is being used off-label. A literature search was performed in the following three electronic databases: PubMed, Scopus, and Web of Science (from January 1st, 2000, to September 20th, 2020), using the following query: (“Fluocinolone Acetonide” OR Iluvien®) AND (“eye” OR “ocular” OR “intravitreal). ” A total of 11 papers were included, and the use of FAc implant was analyzed in the following diseases: radiation-induced maculopathy (RM); paraneoplastic visual syndromes (melanoma-associated retinopathy (MAR) and cancer-associated retinopathy (CAR)); Sjogren's syndrome-related keratopathy; retinal vein occlusion (RVO); cystoid macular edema (CME); diabetic retinal neurodegeneration (DRN); and retinitis pigmentosa (RP). FAc implant may be a potential treatment for these diseases; however, the level of scientific evidence of the included studies in this review is limited. Further studies with larger cohorts and longer follow-ups are needed to validate this data.
The Mutational Landscape of Acute Myeloid Leukaemia Predicts Responses and Outcomes in Elderly Patients from the PETHEMA-FLUGAZA Phase 3 Clinical Trial

Simple Summary Mutational profiling using a custom 43-gene next-generation sequencing panel revealed that patients with mutated DNMT3A or EZH2, or an increase in TET2 VAF and lower TP53 VAF showed a higher overall response. NRAS and TP53 variants were associated with shorter overall survival (OS), whereas only mutated BCOR was associated with a shorter relapse-free survival (RFS). Subgroup analyses of OS according to biological and genomic characteristics showed that patients with low–intermediate cytogenetic risk and mutated NRAS benefited from azacytidine therapy and patients with mutated TP53 showed a better RFS in the azacytidine arm. In conclusion, differential mutational profiling might anticipate the outcomes of first-line treatment choices (AZA or FLUGA) in older patients with AML. Abstract We sought to predict treatment responses and outcomes in older patients with newly diagnosed acute myeloid leukemia (AML) from our FLUGAZA phase III clinical trial (PETHEMA group) based on mutational status, comparing azacytidine (AZA) with fludarabine plus low-dose cytarabine (FLUGA). Mutational profiling using a custom 43-gene next-generation sequencing panel revealed differences in profiles between older and younger patients, and several prognostic markers that were useful in young patients were ineffective in older patients. We examined the associations between variables and overall responses at the end of the third cycle. Patients with mutated DNMT3A or EZH2 were shown to benefit from azacytidine in the treatment-adjusted subgroup analysis. An analysis of the associations with tumor burden using variant allele frequency (VAF) quantification showed that a higher overall response was associated with an increase in TET2 VAF (odds ratio (OR), 1.014; p = 0.030) and lower TP53 VAF (OR, 0.981; p = 0.003). In the treatment-adjusted multivariate survival analyses, only the NRAS (hazard ratio (HR), 1.9, p = 0.005) and TP53 (HR, 2.6, p = 9.8 × 10−7) variants were associated with shorter overall survival (OS), whereas only mutated BCOR (HR, 3.6, p = 0.0003) was associated with a shorter relapse-free survival (RFS). Subgroup analyses of OS according to biological and genomic characteristics showed that patients with low–intermediate cytogenetic risk (HR, 1.51, p = 0.045) and mutated NRAS (HR, 3.66, p = 0.047) benefited from azacytidine therapy. In the subgroup analyses, patients with mutated TP53 (HR, 4.71, p = 0.009) showed a better RFS in the azacytidine arm. In conclusion, differential mutational profiling might anticipate the outcomes of first-line treatment choices (AZA or FLUGA) in older patients with AML. The study is registered at ClinicalTrials.gov as NCT02319135.
Lactate Like Fluconazole Reduces Ergosterol Content in the Plasma Membrane and Synergistically Kills Candida albicans

Candida albicans is an opportunistic pathogen that induces vulvovaginal candidiasis (VVC), among other diseases. In the vaginal environment, the source of carbon for C. albicans can be either lactic acid or its dissociated form, lactate. It has been shown that lactate, similar to the popular antifungal drug fluconazole (FLC), reduces the expression of the ERG11 gene and hence the amount of ergosterol in the plasma membrane. The Cdr1 transporter that effluxes xenobiotics from C. albicans cells, including FLC, is delocalized from the plasma membrane to a vacuole under the influence of lactate. Despite the overexpression of the CDR1 gene and the increased activity of Cdr1p, C. albicans is fourfold more sensitive to FLC in the presence of lactate than when glucose is the source of carbon. We propose synergistic effects of lactate and FLC in that they block Cdr1 activity by delocalization due to changes in the ergosterol content of the plasma membrane.
Deep Learning Methods for Improving Pollen Monitoring

The risk of pollen-induced allergies can be determined and predicted based on data derived from pollen monitoring. Hirst-type samplers are sensors that allow airborne pollen grains to be detected and their number to be determined. Airborne pollen grains are deposited on adhesive-coated tape, and slides are then prepared, which require further analysis by specialized personnel. Deep learning can be used to recognize pollen taxa based on microscopic images. This paper presents a method for recognizing a taxon based on microscopic images of pollen grains, allowing the pollen monitoring process to be automated. In this research, a deep CNN (convolutional neural network) model was built from scratch. Publicly available deep neural network models, pre-trained on image data (not including microscopic pictures), were also used. The results show that even a simple deep learning model produces quite good results when the classification of pollen grain taxa is performed directly from the images. The best deep learning model achieved 97.88% accuracy in the difficult task of recognizing three types of pollen grains (birch, alder, and hazel) with similar structures. The derived models can be used to build a system to support pollen monitoring experts in their work.
Distance Education During COVID-19 Pandemic: A College of Pharmacy Experience

Purpose This study aimed at describing the experience of academic staff and students with distance education, during the COVID-19 pandemic, at a college of pharmacy in Saudi Arabia. Methods This study used a mixed-method approach. The first phase implemented a survey that targeted both academic staff and students to evaluate their experiences with distance education during the COVID-19 pandemic. Then, a focus group discussion was conducted to explore, in-depth, their experience. The survey consisted of five domains as follows: readiness for the shift to distance education during the full and partial lockdown, perception towards distance education, barriers against distance education, and the acquisitions due to distance education. A five-point Likert scale was used to assess participants’ responses to the different domains (mean score ± standard deviation). Results Seventy-eight percent of the academic staff and 65% of the students responded to the survey. Participants’ views were positive for readiness for the shift to distance education during the full lockdown (3.89±0.42 for academic staff and 3.82±0.50 for students) with almost similar evaluation for the readiness during the blended learning period (3.91±0.44 for staff and 3.83±0.59 for students). The findings showed a generally positive perception towards distance education (3.59± 0.67 for academic staff and 3.47±0.64 for students). The acquisitions due to distance education were also positive (3.95±0.72 for academic staff and 3.78±0.77 for students). Nonetheless, some barriers that affected distance education were raised with an overall neutral view from both academic staff (3.31±0.72) and students (3.31±0.64), with different responses for the individual items. Qualitative findings from the focus group discussions explored the strengths, weaknesses, opportunities, and challenges, with emphasis on the areas for improvement. Conclusion Although the shift for distance education was out of a sudden, participants showed overall positive views about their experience with distance education and highlighted areas for improvement.
PCL/Andiroba Oil (Carapa guianensis Aubl.) Hybrid Film for Wound Healing Applications

Developing a biomimetic material to wound care is an emerging need for the healing process. Poly (ε-caprolactone) (PCL) is a polymer with the necessary dressing’s requirements often used in medicine. Their surface, physic-chemical and biological properties can be modified by adding bioactive compounds, such as andiroba seed oil (Carapa guianensis). This Amazonian natural plant has medicinal and pharmacological properties. For this purpose, PCL polymeric films incorporated with andiroba oil were investigated. The synthesis of hybrids materials was carried out in the solvent casting method. Thermal properties were evaluated using thermogravimetric analysis (TGA/DTGA) and differential scanning calorimetry (DSC). The solvent type on the surface and hydrophilicity of samples was studied using a scanning electron microscope (SEM). Additionally, contact angle measurements, functional groups analysis, fluid absorption capacity, and cell viability were performed. The results demonstrated the influences of andiroba oil under the morphology and thermal properties of the polymeric matrix; the hydrophilicity of the hybrid film obtained by acetic acid was reduced by 13%; the porosity decreased as the concentration of oil increased, but its higher thermal stability. The L929 cell line’s proliferation was observed in all materials, and it presented nontoxic nature. It was demonstrated the ability of PCL hybrid film as a matrix for cell growth. Then, the materials were proved potential candidates for biomedical applications.
Changes in the Brain Activity and Visual Performance of Patients with Strabismus and Amblyopia after a Compete Cycle of Light Therapy

This research assesses the brain activity and visual performance at baseline and after light therapy (LTH), of seventeen patients with strabismus and amblyopia (SA), and eleven healthy controls (HCs) from Querétaro, México. Quantitative electroencephalogram analysis (qEEG) was used to record the brain activity, and clinical metrics such as the visual acuity, angle of deviation, phoria state, stereopsis, and visual fields determined the visual performance. Results showed a constant higher alpha-wave frequency for HCs. Low voltages remained negative for HCs and positive for SA patients across stimulation. After LTH, high voltage increased in SA patients, and decreased in HCs. A second spectral peak, (theta-wave), was exclusively recorded in SA patients, at baseline and after LTH. Positive Spearman correlations for alpha-wave frequency, low and high voltages were only seen in SA patients. Synchronized brain activity was recorded in all SA patients stimulated with filters transmitting light in the blue but not in the red spectrum. Enhancement in the visual performance of SA patients was found, whereas deterioration of the phoria state and a decrease in the amount of stereopsis was seen in HCs. To conclude, only a suffering brain and a visual pathway which needs to be enabled can benefit from LTH.
Synthetic Biology towards Improved Flavonoid Pharmacokinetics

Flavonoids are a structurally diverse class of natural products that have been found to have a range of beneficial activities in humans. However, the clinical utilisation of these molecules has been limited due to their low solubility, chemical stability, bioavailability and extensive intestinal metabolism in vivo. Recently, the view has been formed that site-specific modification of flavonoids by methylation and/or glycosylation, processes that occur in plants endogenously, can be used to improve and adapt their biophysical and pharmacokinetic properties. The traditional source of flavonoids and their modified forms is from plants and is limited due to the low amounts present in biomass, intrinsic to the nature of secondary metabolite biosynthesis. Access to greater amounts of flavonoids, and understanding of the impact of modifications, requires a rethink in terms of production, more specifically towards the adoption of plant biosynthetic pathways into ex planta synthesis approaches. Advances in synthetic biology and metabolic engineering, aided by protein engineering and machine learning methods, offer attractive and exciting avenues for ex planta flavonoid synthesis. This review seeks to explore the applications of synthetic biology towards the ex planta biosynthesis of flavonoids, and how the natural plant methylation and glycosylation pathways can be harnessed to produce modified flavonoids with more favourable biophysical and pharmacokinetic properties for clinical use. It is envisaged that the development of viable alternative production systems for the synthesis of flavonoids and their methylated and glycosylated forms will help facilitate their greater clinical application.
A Comprehensive Machine Learning Framework for the Exact Prediction of the Age of Onset in Familial and Sporadic Alzheimer’s Disease

Machine learning (ML) algorithms are widely used to develop predictive frameworks. Accurate prediction of Alzheimer’s disease (AD) age of onset (ADAOO) is crucial to investigate potential treatments, follow-up, and therapeutic interventions. Although genetic and non-genetic factors affecting ADAOO were elucidated by other research groups and ours, the comprehensive and sequential application of ML to provide an exact estimation of the actual ADAOO, instead of a high-confidence-interval ADAOO that may fall, remains to be explored. Here, we assessed the performance of ML algorithms for predicting ADAOO using two AD cohorts with early-onset familial AD and with late-onset sporadic AD, combining genetic and demographic variables. Performance of ML algorithms was assessed using the root mean squared error (RMSE), the R-squared (R2), and the mean absolute error (MAE) with a 10-fold cross-validation procedure. For predicting ADAOO in familial AD, boosting-based ML algorithms performed the best. In the sporadic cohort, boosting-based ML algorithms performed best in the training data set, while regularization methods best performed for unseen data. ML algorithms represent a feasible alternative to accurately predict ADAOO with little human intervention. Future studies may include predicting the speed of cognitive decline in our cohorts using ML.
Sustained Release of Bone Morphogenetic Protein-2 through Alginate Microbeads Enhances Bone Regeneration in Rabbit Tibial Metaphyseal Defect Model

Bone morphogenetic protein-2 (BMP-2) is widely used to enhance bone regeneration. However, because of its short half-life and rapid disappearance, large amounts of BMP-2 are needed, leading to unintended side effects. In this study, BMP-2-encapsulated alginate microbeads (AM) were used to enhance bone regeneration. Enzyme-linked immunosorbent assay confirmed the sustained release of BMP-2 from AM. Vascular endothelial growth factor (VEGF)-adsorbing aptamer-conjugated hydroxyapatite (Apt-HA) was used for osteoconduction and dual delivery of VEGF and BMP-2. For in vivo bone regeneration evaluation, the grafts (1) Apt-HA + phosphate-buffered saline (PBS), (2) Apt-HA + AM without BMP-2, (3) Apt-HA + BMP-2, and (4) Apt-HA + AM encapsulated with BMP-2 were implanted into rabbit tibial metaphyseal defects. After four weeks, micro-computed tomography (CT), histological, and histomorphometric analyses were performed to evaluate bone regeneration. The Apt-HA + AM with BMP-2 group revealed a significantly higher new bone volume and bone volume/total volume (BV/TV) in both cortical and trabecular bone than the others. Furthermore, as evaluated by histomorphometric analysis, BMP-2 AM exhibited a significantly higher bone formation area than the others, indicating that AM could be used to efficiently deliver BMP-2 through sustained release. Moreover, the combined application of BMP-2-encapsulated Apt-HA + AM may effectively promote bone regeneration.
Retrospective Evaluation of Septic Subtendinous Calcaneal Bursitis in 29 Cattle

Simple Summary Infections of the subtendinous calcaneal bursa (SCB) in cattle are mainly caused by pressure sores and directly penetrating wounds. We describe the clinical, ultrasonographic and radiographic findings and outcomes in cattle diagnosed with this condition, including postoperative complications and postoperative survival times. Medical records of 29 cattle with a mean age of 4.1 years were reviewed. Twelve animals (41.4%) showed septic inflammation of the SCB only (group 1) and 17 cattle (58.6%) had a concurrent bone infection at the calcaneal tuber (group 2). Eleven cattle (37.9%) were euthanized after diagnosis due to poor prognosis. Eighteen (62.1%) patients underwent surgical treatment and 15 cattle attained full recovery with a median cumulative postoperative survival time of 23.0 months. Surgically treated patients of group 1 had a success rate of 100%, compared with 70% in group 2. Group 2 cattle with septic inflammation of the SCB and concurrent bone infection had more postoperative complications and tended to have shorter postoperative survival times. In conclusion, cattle exclusively suffering from septic SCB and treated by surgery had a good prognosis. Abstract Septic subtendinous calcaneal bursitis in cattle commonly results from hock lesions, and less commonly from penetrating wounds. The goal of this retrospective study was to describe clinical and diagnostic imaging findings, outcomes, postoperative complications and postoperative survival times (SURV-T) in cattle with this condition. Clinical data from 29 cattle with a mean age of 4.1 years were included. Twelve (41.4%) cattle were assigned to group 1 (septic bursitis only) and 17 (58.6%) to group 2 (septic bursitis, concurrent bone infection at the calcaneal tuber (CT) and lesions of the superficial digital flexor tendon. Eleven cattle (37.9%) with comorbidities were euthanized after diagnosis due to poor prognosis. Surgical treatment was performed in 18 (62.1%) patients of which 15 showed full recovery and a median cumulative SURV-T of 23.0 months. The success rate of surgically treated patients was 100% (8/8) in group 1 and 70% (7/10) in group 2. There was no statistically significant association (p > 0.05) between the duration of septic bursitis and concurrent bone infection at the CT with occurrence of postoperative complications and SURV-T. However, there was a clear trend favoring more postoperative complications and shorter SURV-T in cattle with concurrent CT bone infection. In conclusion, cattle with septic subtendinous calcaneal bursitis exclusively have a good prognosis, provided adequate surgical treatment is performed.