Miracle-dz/UniFAR-FTUs huggingface dataset:
R-TeaFor: Regularized Teacher-Forcing for Abstractive Summarization

Teacher-forcing is widely used in training sequence generation models to improve sampling efficiency and to stabilize training. However, teacher-forcing is vulnerable to the exposure bias problem. Previous works have attempted to address exposure bias by modifying the training data to simulate model-generated results. Nevertheless, they do not consider the pairwise relationship between the original training data and the modified ones, which provides more information during training. Hence, we propose Regularized Teacher-Forcing (R-TeaFor) to utilize this relationship for better regularization. Empirically, our experiments show that R-TeaFor outperforms previous summarization state-of-the-art models, and the results can be generalized to different pre-trained models.
Automatic Patient Note Assessment without Strong Supervision

Training of physicians requires significant practice writing patient notes that document the patient’s medical and health information and physician diagnostic reasoning. Assessment and feedback of the patient note requires experienced faculty, consumes significant amounts of time and delays feedback to learners. Grading patient notes is thus a tedious and expensive process for humans that could be improved with the addition of natural language processing. However, the large manual effort required to create labeled datasets increases the challenge, particularly when test cases change. Therefore, traditional supervised NLP methods relying on labelled datasets are impractical in such a low-resource scenario. In our work, we proposed an unsupervised framework as a simple baseline and a weakly supervised method utilizing transfer learning for automatic assessment of patient notes under a low-resource scenario. Experiments on our self-collected datasets show that our weakly-supervised methods could provide reliable assessment for patient notes with accuracy of 0.92.
The value of convolutional neural networks-based deep learning model in differential diagnosis of space-occupying brain diseases

Objectives It is still a challenge to differentiate space-occupying brain lesions such as tumefactive demyelinating lesions (TDLs), tumefactive primary angiitis of the central nervous system (TPACNS), primary central nervous system lymphoma (PCNSL), and brain gliomas. Convolutional neural networks (CNNs) have been used to analyze complex medical data and have proven transformative for image-based applications. It can quickly acquire diseases' radiographic features and correct doctors' diagnostic bias to improve diagnostic efficiency and accuracy. The study aimed to assess the value of CNN-based deep learning model in the differential diagnosis of space-occupying brain diseases on MRI. Methods We retrospectively analyzed clinical and MRI data from 480 patients with TDLs (n = 116), TPACNS (n = 64), PCNSL (n = 150), and brain gliomas (n = 150). The patients were randomly assigned to training (n = 240), testing (n = 73), calibration (n = 96), and validation (n = 71) groups. And a CNN-implemented deep learning model guided by clinical experts was developed to identify the contrast-enhanced T1-weighted sequence lesions of these four diseases. We utilized accuracy, sensitivity, specificity, and area under the curve (AUC) to evaluate the performance of the CNN model. The model's performance was then compared to the neuroradiologists' diagnosis. Results The CNN model had a total accuracy of 87% which was higher than senior neuroradiologists (74%), and the AUC of TDLs, PCNSL, TPACNS and gliomas were 0.92, 0.92, 0.89 and 0.88, respectively. Conclusion The CNN model can accurately identify specific radiographic features of TDLs, TPACNS, PCNSL, and gliomas. It has the potential to be an effective auxiliary diagnostic tool in the clinic, assisting inexperienced clinicians in reducing diagnostic bias and improving diagnostic efficiency.
Retinorecipient areas in the common marmoset (Callithrix jacchus): An image-forming and non-image forming circuitry

The mammalian retina captures a multitude of diverse features from the external environment and conveys them via the optic nerve to a myriad of retinorecipient nuclei. Understanding how retinal signals act in distinct brain functions is one of the most central and established goals of neuroscience. Using the common marmoset (Callithrix jacchus), a monkey from Northeastern Brazil, as an animal model for parsing how retinal innervation works in the brain, started decades ago due to their marmoset’s small bodies, rapid reproduction rate, and brain features. In the course of that research, a large amount of new and sophisticated neuroanatomical techniques was developed and employed to explain retinal connectivity. As a consequence, image and non-image-forming regions, functions, and pathways, as well as retinal cell types were described. Image-forming circuits give rise directly to vision, while the non-image-forming territories support circadian physiological processes, although part of their functional significance is uncertain. Here, we reviewed the current state of knowledge concerning retinal circuitry in marmosets from neuroanatomical investigations. We have also highlighted the aspects of marmoset retinal circuitry that remain obscure, in addition, to identify what further research is needed to better understand the connections and functions of retinorecipient structures.
Portable 3D-printed hand orthosis with spatial stiffness distribution personalized for assisting grasping in daily living

Stroke survivors having limited finger coordination require an active hand orthosis to assist them with grasping tasks for daily activities. The orthosis should be portable for constant use; however, portability imposes constraints on the number, size, and weight of the actuators, which increase the difficulty of the design process. Therefore, a tradeoff exists between portability and the assistive force. In this study, a personalized spatial stiffness distribution design is presented for a portable and strengthful hand orthosis. The spatial stiffness distribution of the orthosis was optimized based on measurements of individual hand parameters to satisfy the functional requirements of achieving sufficient grip aperture in the pre-grasping phase and minimal assistive force in the grasping phase. Ten stroke survivors were recruited to evaluate the system. Sufficient grip aperture and high grip strength-to-weight ratio were achieved by the orthosis via a single motor. Moreover, the orthosis significantly restored the range of motion and improved the performance of daily activities. The proposed spatial stiffness distribution can suggest a design solution to make strengthful hand orthoses with reduced weight.
Editorial: New developments in the intention-behavior gap for physical activity – recent trends, controversies, and a critical outlook

COPYRIGHT © 2023 Englert, Rebar, Rhodes and Pfe er. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. Editorial: New developments in the intention-behavior gap for physical activity – recent trends, controversies, and a critical outlook
Chemo-immunotherapy for metastatic non-squamous NSCLC in a patient with HIV infection: A case report

Activity and safety data of chemo-immunotherapy for patients with metastatic NSCLC and known HIV infection are still limited, since HIV-positive patients were generally excluded from clinical trials. Here we report the case of a metastatic NSCLC patient with HIV infection and undetectable viral load treated with first-line chemo-immunotherapy (pembrolizumab, carboplatin and pemetrexed), achieving a meaningful and durable objective response, with no treatment-related adverse events and no HIV-related complications. This report suggests that NSCLC patients with virologically controlled HIV infection can be safely treated with chemo-immunotherapy and should not be excluded from this treatment based on their viral infection only.
Classification of the lower energy levels of highly ionized transition elements

230 newly classified spectral lines emitted from higly ionized elements and belonging to the sodium, magnesium, aluminium, silicon, phosphorus, sulphur and chlorine isoelectronic sequences are reported as a result of observations of laser-produced plasmas formed from elements in the period between chlorine and iron. The transitions studied occur between low-lying energy levels and are of importance both to the study of forbidden lines of astrophysical interest and to the identification of iron emission lines in solar spectra. The observation of the Fe XIII 3s23p2 3P-3s3p3 3S multiplet provides the most direct confirmation of the identity of the solar forbidden lines at 10 746.8 AA and 10 797.95 AA. Revised wavelengths of emission lines in the scandium spectrum between 320 AA and 800 AA are listed.
Editorial: Health-related quality of life in health care

COPYRIGHT © 2023 Kharroubi and Elbarazi. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. Editorial: Health-related quality of life in health care
Combination of Aspergillus niger MJ1 with Pseudomonas stutzeri DSM4166 or mutant Pseudomonas fluorescens CHA0-nif improved crop quality, soil properties, and microbial communities in barrier soil

Soil salinization and acidification seriously damage soil health and restricts the sustainable development of planting. Excessive application of chemical fertilizer and other reasons will lead to soil acidification and salinization. This study focus on acid and salinized soil, investigated the effect of phosphate-solubilizing bacteria, Aspergillus niger MJ1 combined with nitrogen-fixing bacteria Pseudomonas stutzeri DSM4166 or mutant Pseudomonas fluorescens CHA0-nif on crop quality, soil physicochemical properties, and microbial communities. A total of 5 treatments were set: regular fertilization (T1), regular fertilization with MJ1 and DSM4166 (T2), regular fertilization with MJ1 and CHA0-nif (T3), 30%-reducing fertilization with MJ1 and DSM4166 (T4), and 30%-reducing fertilization with MJ1 and CHA0-nif (T5). It was found that the soil properties (OM, HN, TN, AP, AK, and SS) and crop quality of cucumber (yield production, protein, and vitamin C) and lettuce (yield production, vitamin C, nitrate, soluble protein, and crude fiber) showed a significant response to the inoculated strains. The combination of MJ1 with DSM4166 or CHA0-nif influenced the diversity and richness of bacterial community in the lettuce-grown soil. The organismal system-, cellular process-, and metabolism-correlated bacteria and saprophytic fungi were enriched, which were speculated to mediate the response to inoculated strains. pH, OM, HN, and TN were identified to be the major factors correlated with the soil microbial community. The inoculation of MJ1 with DSM4166 and CHA0-nif could meet the requirement of lettuce and cucumber growth after reducing fertilization in acid and salinized soil, which provides a novel candidate for the eco-friendly technique to meet the carbon-neutral topic.
Analysis of bulk RNA-seq data from sepsis patients reveals sepsis-associated lncRNAs and targeted cell death-related genes contributing to immune microenvironment regulation

Background Sepsis is a life-threatening organ dysfunction syndrome that leads to the massive death of immune cells. Long non-coding RNAs (lncRNAs) have been reported to exert key regulatory roles in cells. However, it is unclear how lncRNAs regulate the survival of immune cells in the occurrence and development of sepsis. Methods In this study, we used blood whole transcriptome sequencing data (RNA-seq) from normal controls (Hlty) and patients with uncomplicated infection (Inf1 P), sepsis (Seps P), and septic shock (Shock P), to investigate the fraction changes of immune cell types, expression pattern of cell death-related genes, as well as differentially expressed lncRNAs. Association network among these factors was constructed to screen out essential immune cell types, lncRNAs and their potential targets. Finally, the expression of lncRNAs and cell death genes in sepsis patients were validated by qRT-PCR. Results In this study, we found fifteen immune cell types showed significant fraction difference between Hlty and three patient groups. The expression pattern of cell death-related genes was also dysregulated in Hlty compared with patient groups. Co-expression network analysis identified a key turquoise module that was associated with the fraction changes of immune cells. We then identified differentially expressed lncRNAs and their potential targets that were tightly associated with the immune cell dysregulation in sepsis. Seven lncRNAs, including LINC00861, LINC01278, RARA-AS1, RP11-156P1.3, RP11-264B17.3, RP11-284N8.3 and XLOC_011309, as well as their co-expressed cell death genes, were finally identified, and we validated two lncRNAs (LINC00861 and LINC01278) and four mRNA targets using qRT-PCR in sepsis samples. Conclusion The global analysis of cell death-related genes in the occurrence and development of sepsis was carried out for the first time, and its expression regulation mode was displayed. The expression pattern of sepsis-associated lncRNAs were analyzed and identified, and the lncRNAs were significantly related to the change of immune cell proportion. We highlight the important roles of lncRNAs and their potential targets in the regulation of immune cell fraction changes during sepsis progression. The identified lncRNAs and their target genes may become new biomarkers and therapeutic targets of sepsis.
Manipulation of ferroelectric vortex domains in hexagonal manganites

The modification of ferroelectric vortex domain patterns in hexagonal manganites (here exemplified by YMnO3 and HoMnO3) owing to chemical treatment, thermal annealing, and local electric-field poling is investigated by piezoresponse force microscopy. Chemical treatment transfers the domain pattern into a topographical pattern by domain selective etching. Thermal annealing alters the domain pattern without any sign of temperature memory effects. Local electric fields affect the domain structure with possible signs of electric memory effects. These observations are important for future investigations of the microscopic mechanisms and macroscopic parameters defining the formation of ferroelectric domains in this unusual multiferroic.
Effects of chemotherapy and immunotherapy on microbial diversity in TME and engineered bacterial-mediated tumor therapy

Tumor microbiota is a group of microorganisms located in tumor tissues with rich diversity that can promote tumorigenesis and development, and different types of tumors have different tumor microbiotas, which has important implications for tumor research, detection, and clinical treatment. In this review, we examine the diversity of the tumor microbiota, discuss the impact of chemotherapy and immunotherapy on tumor microbiota diversity, and summarize recent advances in the use of genetically engineered bacteria for the treatment of tumors. In addition, we propose key questions that need to be further addressed by the tumor microbiota.
Fuzzy Risk Graph Model for Determining Safety Integrity Level

The risk graph is one of the most popular methods used to determine the safety integrity level for safety instrumented functions. However, conventional risk graph as described in the IEC 61508 standard is subjective and suffers from an interpretation problem of risk parameters. Thus, it can lead to inconsistent outcomes that may result in conservative SIL's. To overcome this difficulty, a modified risk graph using fuzzy rule-based system is proposed. This novel version of risk graph uses fuzzy scales to assess risk parameters, and calibration may be made by varying risk parameter values. Furthermore, the outcomes which are numerical values of risk reduction factor (the inverse of the probability of failure on demand) can be compared directly with those given by quantitative and semiquantitative methods such as fault tree analysis (FTA), quantitative risk assessment (QRA), and layers of protection analysis (LOPA).
Effects of the addition of leucine on flavor and quality of sausage fermented by Lactobacillus fermentum YZU-06 and Staphylococcus saprophyticus CGMCC 3475

Methyl-branched aldehydes, especially 3-methylbutanal, have been reported to be perceived either as a malty or as a nutty/chocolate-like aroma and were considered an important flavor contributor in fermented meat products. Decomposition of leucine (Leu) by branched-chain amino acid transaminase (BACT) is a crucial step in the metabolism of Leu to 3-methylbutanal. This study was conducted to explore the effects of mixed-starter culture (Lactobacillus fermentum YZU-06 and Staphylococcus saprophyticus CGMCC 3475) and addition of Leu (0, 1, and 3 mM) on the flavor and quality of fermented sausages. The pH, water activity, texture profile analysis, color, counts of lactic acid bacteria (LAB) and staphylococci, peptide, and flavor compounds were detected during fermentation. The results showed that the starter culture group increased hardness, elasticity, the counts of LAB and staphylococci, peptide content, volatile flavor compounds, as well as the sensorial scores of sausage, while decreasing pH, aw, and L* and b* values compared with the non-inoculation group. The mixed starter of adding with 3 mM Leu enhanced the content of 3-methylbutanal and overall flavor of fermented sausages. It is applicable to directionally produce methyl-branched aldehydes and improve the overall quality of fermented sausage by the addition of Leu and using starter of L. fermentum YZU-06 and S. saprophyticus CGMCC 3475.
Biomarkers (mRNAs and non-coding RNAs) for the diagnosis and prognosis of rheumatoid arthritis

In recent years, diagnostic and therapeutic approaches for rheumatoid arthritis (RA) have continued to improve. However, in the advanced stages of the disease, patients are unable to achieve long-term clinical remission and often suffer from systemic multi-organ damage and severe complications. Patients with RA usually have no overt clinical manifestations in the early stages, and by the time a definitive diagnosis is made, the disease is already at an advanced stage. RA is diagnosed clinically and with laboratory tests, including the blood markers C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR) and the autoantibodies rheumatoid factor (RF) and anticitrullinated protein antibodies (ACPA). However, the presence of RF and ACPA autoantibodies is associated with aggravated disease, joint damage, and increased mortality, and these autoantibodies have low specificity and sensitivity. The etiology of RA is unknown, with the pathogenesis involving multiple factors and clinical heterogeneity. The early diagnosis, subtype classification, and prognosis of RA remain challenging, and studies to develop minimally invasive or non-invasive biomarkers in the form of biofluid biopsies are becoming more common. Non-coding RNA (ncRNA) molecules are composed of long non-coding RNAs, small nucleolar RNAs, microRNAs, and circular RNAs, which play an essential role in disease onset and progression and can be used in the early diagnosis and prognosis of RA. In this review of the diagnostic and prognostic approaches to RA disease, we provide an overview of the current knowledge on the subject, focusing on recent advances in mRNA–ncRNA as diagnostic and prognostic biomarkers from the biofluid to the tissue level.
Application of diffusion tensor imaging technology in glaucoma diagnosis

Glaucoma is the first major category of irreversible blinding eye illnesses worldwide. Its leading cause is the death of retinal ganglion cells and their axons, which results in the loss of vision. Research indicates that glaucoma affects the optic nerve and the whole visual pathway. It also reveals that degenerative lesions caused by glaucoma can be found outside the visual pathway. Diffusion tensor imaging (DTI) is a magnetic resonance imaging (MRI) technique that can investigate the complete visual system, including alterations in the optic nerve, optic chiasm, optic tract, lateral geniculate nuclear, and optic radiation. In order to provide a more solid foundation for the degenerative characteristics of glaucoma, this paper will discuss the standard diagnostic techniques for glaucoma through a review of the literature, describe the use of DTI technology in glaucoma in humans and animal models, and introduce these techniques. With the advancement of DTI technology and its coupling with artificial intelligence, DTI represents a potential future for MRI technology in glaucoma research.
High quality factor dielectric multilayer structures fabricated by rf-sputtering

Rare earth activated 1-D photonic crystals were fabricated by rf-sputtering technique. The cavity is constituted by an Er3+-doped SiO2 active layer inserted between two Bragg reflectors consisting of ten pairs of SiO2/TiO2 layers. SEM microscopy is employed to put in evidence the quality of the sample, the homogeneities of the layers thicknes and the good adhesion. NIR transmittance and variable angle reflectance spectra confirm that the presence of a stop-band from 1500 nm to 2000 nm with a cavity resonance centered at 1749 nm at 0° with a quality factor Q is about 890. The influence of the cavity on the 4I13/2 → 4I15/2 emission band of Er3+ ion is also demonstrated.