Miracle-dz/UniFAR-FTUs huggingface dataset:
Cryoglobulinemic vasculitis and glomerulonephritis: concerns in clinical practice

Abstract Objective: Cryoglobulinemia often causes systemic vasculitis, thereby damaging to skin and internal organs including kidneys, even life-threatening. This review aimed to introduce the advances in understanding, detection, and treatment of this disease in recent years, with a particular concern to clinical practice. Data sources: All the data in this review were from the English or Chinese literature in the PubMed and China National Knowledge Infrastructure databases as of March 2019. Study selection: This review selected important original articles, meaningful reviews, and some reports on cryoglobulinemia published in recent years and in history, as well as the guidelines for treatment of underlying diseases which lead to cryoglobulinemia. Results: Diagnosis of cryoglobulinemia relies on serum cryoglobulin test, in which to ensure that the blood sample temperature is not less than 37°C in the entire pre-analysis phase is the key to avoid false negative results. Cryoglobulinemic vasculitis (Cryo Vas), including cryoglobulinemic glomerulonephritis (Cryo GN), usually occurs in types II and III mixed cryoglobulinemia, and can also be seen in type I cryoglobulinemia caused by monoclonal IgG3 or IgG1. Skin purpura, positive serum rheumatoid factor, and decreased serum levels of C4 and C3 are important clues for prompting types II and III Cryo Vas. Renal biopsy is an important means for diagnosis of Cryo GN, while membranous proliferative GN is the most common pathological type of Cryo GN. In recent years, great advances have been made in the treatment of Cryo Vas and its underlying diseases, and this review has briefly introduced these advances. Conclusions: Laboratory examinations of serum cryoglobulins urgently need standardization. The recent advances in the diagnosis and treatment of Cryo Vas and GN need to be popularized among the clinicians in related disciplines.
Effect of Porosity on Mechanical Properties of 3D Printed Polymers: Experiments and Micromechanical Modeling Based on X-ray Computed Tomography Analysis

Additive manufacturing (commonly known as 3D printing) is defined as a family of technologies that deposit and consolidate materials to create a 3D object as opposed to subtractive manufacturing methodologies. Fused deposition modeling (FDM), one of the most popular additive manufacturing techniques, has demonstrated extensive applications in various industries such as medical prosthetics, automotive, and aeronautics. As a thermal process, FDM may introduce internal voids and pores into the fabricated thermoplastics, giving rise to potential reduction on the mechanical properties. This paper aims to investigate the effects of the microscopic pores on the mechanical properties of material fabricated by the FDM process via experiments and micromechanical modeling. More specifically, the three-dimensional microscopic details of the internal pores, such as size, shape, density, and spatial location were quantitatively characterized by X-ray computed tomography (XCT) and, subsequently, experiments were conducted to characterize the mechanical properties of the material. Based on the microscopic details of the pores characterized by XCT, a micromechanical model was proposed to predict the mechanical properties of the material as a function of the porosity (ratio of total volume of the pores over total volume of the material). The prediction results of the mechanical properties were found to be in agreement with the experimental data as well as the existing works. The proposed micromechanical model allows the future designers to predict the elastic properties of the 3D printed material based on the porosity from XCT results. This provides a possibility of saving the experimental cost on destructive testing.
Mosquito feeding behavior and how it influences residual malaria transmission across Africa

Significance Malaria transmission persists even when mosquito control is used effectively. This “residual transmission” measures all forms of transmission that are beyond the reach of standard insecticidal nets and indoor residual spraying of insecticides when used optimally. The epidemiological importance of the time of day mosquitoes bite and how much this contributes to residual transmission is unclear. The scale of the problem must be understood to demonstrate the need for outdoor vector control tools. An additional 10.6 million clinical cases of malaria are predicted annually given the 10% higher level of outdoor biting observed here. Mosquito species and behavior data together with people’s resting and sleeping patterns are needed to fully measure indoor intervention efficacy and accurately quantify residual transmission. The antimalarial efficacy of the most important vector control interventions—long-lasting insecticidal nets (LLINs) and indoor residual spraying (IRS)—primarily protect against mosquitoes’ biting people when they are in bed and indoors. Mosquito bites taken outside of these times contribute to residual transmission which determines the maximum effectiveness of current malaria prevention. The likelihood mosquitoes feed outside the time of day when LLINs and IRS can protect people is poorly understood, and the proportion of bites received outdoors may be higher after prolonged vector control. A systematic review of mosquito and human behavior is used to quantify and estimate the public health impact of outdoor biting across Africa. On average 79% of bites by the major malaria vectors occur during the time when people are in bed. This estimate is substantially lower than previous predictions, with results suggesting a nearly 10% lower proportion of bites taken at the time when people are beneath LLINs since the year 2000. Across Africa, this higher outdoor transmission is predicted to result in an estimated 10.6 million additional malaria cases annually if universal LLIN and IRS coverage was achieved. Higher outdoor biting diminishes the cases of malaria averted by vector control. This reduction in LLIN effectiveness appears to be exacerbated in areas where mosquito populations are resistant to insecticides used in bed nets, but no association was found between physiological resistance and outdoor biting. Substantial spatial heterogeneity in mosquito biting behavior between communities could contribute to differences in effectiveness of malaria control across Africa.
A Novel Automated System Yields Reproducible Temporal Feeding Patterns in Laboratory Rodents

ABSTRACT Background The impact of temporal feeding patterns remains a major unanswered question in nutritional science. Progress has been hampered by the absence of a reliable method to impose temporal feeding in laboratory rodents, without the confounding influence of food-hoarding behavior. Objective The aim of this study was to develop and validate a reliable method for supplying crushed diets to laboratory rodents in consistent, relevant feeding patterns for prolonged periods. Methods We programmed our experimental feeding station to deliver a standard diet [StD; Atwater Fuel Energy (AFE) 13.9% fat] or high-fat diet (HFD; AFE 45% fat) during nocturnal grazing [providing 1/24th of the total daily food intake (tdF/I) of ad libitum–fed controls every 30 min] and meal-fed (3 × 1-h periods of ad libitum feeding) patterns in male rats (Sprague-Dawley: 4 wk old, 72–119 g) and mice [C57/Bl6J wild-type (WT): 6 mo old, 29–37 g], and ghrelin-null littermates (Ghr−/−; 27–34 g). Results Grazing yielded accurate, consistent feeding events in rats, with an approximately linear rise in nocturnal cumulative food intake [tdF/I (StD): 97.4 ± 1.5% accurate compared with manual measurement; R2 = 0.86; tdF/I (HFD): 99.0 ± 1.4% accurate; R2 = 0.86]. Meal-feeding produced 3 nocturnal meals of equal size and duration in StD-fed rats (tdF/I: 97.4 ± 0.9% accurate; R2 = 0.90), whereas the second meal size increased progressively in HFD-fed rats (44% higher on day 35 than on day 14; P < 0.01). Importantly, cumulative food intake in grazing and meal-fed rats was identical. Similar results were obtained in WT mice except that less restricted grazing induced hyperphagia (compared with meal-fed WT mice; P < 0.05 from day 1). This difference was abolished in Ghr−/− mice, with meal initiation delayed and meal duration enhanced. Neither pattern elevated corticosterone secretion in rats, but meal-feeding aligned ultradian pulses. Conclusions We have established a consistent, measurable, researcher-defined, stress-free method for imposing temporal feeding patterns in rats and mice. This approach will facilitate progress in understanding the physiologic impact of feeding patterns.
The Impact of a Community-Based Food Education Program on Nutrition-Related Knowledge in Middle-Aged and Older Patients with Type 2 Diabetes: Results of a Pilot Randomized Controlled Trial

The purpose of this study was to evaluate the impact of a community-based food education program on nutrition-related knowledge in middle-aged and older patients with type 2 diabetes (T2D). Participants (n = 36; 65.9 ± 6.0 years old) were recruited in primary health care to a 9-month community-based lifestyle intervention program for patients with T2D and randomly assigned to an exercise program (control group; n = 16) or an exercise program plus a food education program (experimental group; n = 20). Nutrition-related knowledge was assessed through a modified version of the General Nutrition Knowledge Questionnaire. The increase in total nutrition-related knowledge score and sources of nutrients area score was significantly higher in the experimental group compared to the control group. No significant changes in nutrition-related knowledge were found between groups in dietary recommendations and diet-disease relationship areas, although improvements were observed. This community-based food education program, with the use of easy to implement strategies (short-duration lectures and dual-task problem solving activities during exercise), had a positive and encouraging impact on nutrition-related knowledge in middle-aged and older patients with T2D.
Rapid Solid-Liquid Dynamic Extraction (RSLDE): A Powerful and Greener Alternative to the Latest Solid-Liquid Extraction Techniques

Traditionally, solid-liquid extractions are performed using organic and/or inorganic liquids and their mixtures as extractant solvents in contact with an insoluble solid matrix (e.g., the Soxhlet method) or using sequential atmospheric pressure systems that require long procedures, such as maceration or percolation. The objective of this procedure is the extraction of any compounds that can be carried out from the inner solid material to the outlet, resulting in a solution containing colorants, bioactive compounds, odorous substances, etc. Over the years, in the extraction techniques sector, there have been many important changes from the points of view of production, quality, and human and environmental safety due to improvements in technology. In more recent times, the interest of the scientific community has been aimed at the study of sustainable processes for the valorization of extracts from vegetables and food by-products, through the use of non-conventional (innovative) technologies that represent a valid alternative to conventional methods, generally through saving time and energy and the formation of fewer by-products. Therefore, with the development of principles based on the prevention of pollution, on a lower risk for human health, and on a low environmental impact, new systems have been implemented to reduce extraction times and solvent consumption, to improve efficiency, and to increase the productivity of the extracts. From this point of view, rapid solid-liquid dynamic extraction (RSLDE), performed using the Naviglio extractor, compared to traditional applications, is a technique that is able to reduce extraction times, generally leads to higher yields, does not require heating of the system, allows one to extract the active ingredients, and avoids their degradation. This technique is based on a new solid-liquid extraction principle named Naviglio’s principle. In this review, after reviewing the latest extraction techniques, an overview of RSLDE applications in various research and production sectors over the past two decades is provided.
Strong muscles, weak heart: testosterone‐induced cardiomyopathy

Exogenous anabolic androgen steroid use is associated with adverse cardiovascular outcomes. A 53‐year‐old bodybuilder presented with 3 months of exertional dyspnoea. Physical examination showed tachycardia and pan‐systolic murmur; an echocardiogram showed a left ventricular ejection fraction (EF) of 15%. Evaluations included normal coronary angiogram, iron panel and thyroid studies, a negative viral panel (human immunodeficiency virus, Lyme disease, and hepatitis), and urine toxicology. He admitted to intramuscular anabolic steroid use; his testosterone level was 30 160.0 ng/dL (normal 280–1100 ng/dL). In addition to discontinuation of anabolic steroid use, he was treated with guideline‐directed heart failure medical therapy. Repeat echocardiogram at 6 months showed an EF of 54% and normalized testosterone level of 603.7 ng/dL. Anabolic steroid use is a rare, reversible cause of cardiomyopathy in young, otherwise healthy athletes; a high index of suspicion is required to prevent potentially fatal side effects.
Artificial Intelligence-Based Classification of Multiple Gastrointestinal Diseases Using Endoscopy Videos for Clinical Diagnosis

Various techniques using artificial intelligence (AI) have resulted in a significant contribution to field of medical image and video-based diagnoses, such as radiology, pathology, and endoscopy, including the classification of gastrointestinal (GI) diseases. Most previous studies on the classification of GI diseases use only spatial features, which demonstrate low performance in the classification of multiple GI diseases. Although there are a few previous studies using temporal features based on a three-dimensional convolutional neural network, only a specific part of the GI tract was involved with the limited number of classes. To overcome these problems, we propose a comprehensive AI-based framework for the classification of multiple GI diseases by using endoscopic videos, which can simultaneously extract both spatial and temporal features to achieve better classification performance. Two different residual networks and a long short-term memory model are integrated in a cascaded mode to extract spatial and temporal features, respectively. Experiments were conducted on a combined dataset consisting of one of the largest endoscopic videos with 52,471 frames. The results demonstrate the effectiveness of the proposed classification framework for multi-GI diseases. The experimental results of the proposed model (97.057% area under the curve) demonstrate superior performance over the state-of-the-art methods and indicate its potential for clinical applications.
Chimerical Dataset Creation Protocol Based on Doddington Zoo: A Biometric Application with Face, Eye, and ECG

Multimodal systems are a workaround to enhance the robustness and effectiveness of biometric systems. A proper multimodal dataset is of the utmost importance to build such systems. The literature presents some multimodal datasets, although, to the best of our knowledge, there are no previous studies combining face, iris/eye, and vital signals such as the Electrocardiogram (ECG). Moreover, there is no methodology to guide the construction and evaluation of a chimeric dataset. Taking that fact into account, we propose to create a chimeric dataset from three modalities in this work: ECG, eye, and face. Based on the Doddington Zoo criteria, we also propose a generic and systematic protocol imposing constraints for the creation of homogeneous chimeric individuals, which allow us to perform a fair and reproducible benchmark. Moreover, we have proposed a multimodal approach for these modalities based on state-of-the-art deep representations built by convolutional neural networks. We conduct the experiments in the open-world verification mode and on two different scenarios (intra-session and inter-session), using three modalities from two datasets: CYBHi (ECG) and FRGC (eye and face). Our multimodal approach achieves impressive decidability of 7.20 ± 0.18, yielding an almost perfect verification system (i.e., Equal Error Rate (EER) of 0.20% ± 0.06) on the intra-session scenario with unknown data. On the inter-session scenario, we achieve a decidability of 7.78 ± 0.78 and an EER of 0.06% ± 0.06. In summary, these figures represent a gain of over 28% in decidability and a reduction over 11% of the EER on the intra-session scenario for unknown data compared to the best-known unimodal approach. Besides, we achieve an improvement greater than 22% in decidability and an EER reduction over 6% in the inter-session scenario.
Cognitive, Emotional, and Behavioral Reactions to Snooping: The Role of Attachment Characteristics

Although snooping is common in romantic relationships, there has been limited research on reactions to being snooped by a romantic partner. This study was designed to examine the role of attachment style in cognitive, emotional, and behavioral reactions to partner snooping. Participants (n = 491) read one of four hypothetical scenarios that involved partner snooping through electronic or nonelectronic belongings and reported their reactions in an online study. Results showed that overall, an electronic snooping offense was associated with greater negative reactions, such as greater tendencies to attribute the partner and the self to the offense, and being less forgiving of the partner. Anxious attachment predicted greater positive emotional reactions to partner snooping, whereas avoidance predicted greater negative emotional reactions and being less forgiving of the partner. Finally, relationship status was a robust predictor of reactions such that being in a committed relationship was associated with lesser negative emotional reactions and greater positive emotional reactions to snooping, lesser tendencies to attribute the partner to the offense, and being more forgiving of the partner. Theoretical and practical implications of these findings were discussed.
Physiological Responses to Basic Tastes for Sensory Evaluation of Chocolate Using Biometric Techniques

Facial expressions are in reaction to basic tastes by the response to receptor stimulation. The objective of this study was to assess the autonomic nervous system responses to basic tastes in chocolates and to identify relationships between conscious and unconscious responses from participants. Panelists (n = 45) tasted five chocolates with either salt, citric acid, sugar, or monosodium glutamate, which generated four distinctive basic tastes plus bitter, using dark chocolate. An integrated camera system, coupled with the Bio-Sensory application, was used to capture infrared thermal images, videos, and sensory responses. Outputs were used to assess skin temperature (ST), facial expressions, and heart rate (HR) as physiological responses. Sensory responses and emotions elicited during the chocolate tasting were evaluated using the application. Results showed that the most liked was sweet chocolate (9.01), while the least liked was salty chocolate (3.61). There were significant differences for overall liking (p < 0.05) but none for HR (p = 0.75) and ST (p = 0.27). Sweet chocolate was inversely associated with angry, and salty chocolate positively associated with sad. Positive emotion-terms were associated with sweet samples and liking in self-reported responses. Findings of this study may be used to assess novel tastes of chocolate in the industry based on conscious and emotional responses more objectively.
Assessing micrometastases as a target for nanoparticles using 3D microscopy and machine learning

Significance Successful delivery of therapeutic agents to metastatic tumors is critical for controlling their growth and improving cancer patient survival. It is challenging to design drug carriers that target metastases because of the limitations of current techniques for analyzing drug carrier interactions with metastatic tumors. We overcome this problem by developing a new imaging and image analysis workflow that enables us to track nanoparticle delivery, penetration, and distribution within micrometastases. More importantly, we can predict the delivery of nanoparticles to the micrometastases based on their physiology using a machine learning algorithm. This allows us to predict the micrometastases pathophysiology that can be targeted more effectively. Metastasis of solid tumors is a key determinant of cancer patient survival. Targeting micrometastases using nanoparticles could offer a way to stop metastatic tumor growth before it causes excessive patient morbidity. However, nanoparticle delivery to micrometastases is difficult to investigate because micrometastases are small in size and lie deep within tissues. Here, we developed an imaging and image analysis workflow to analyze nanoparticle–cell interactions in metastatic tumors. This technique combines tissue clearing and 3D microscopy with machine learning-based image analysis to assess the physiology of micrometastases with single-cell resolution and quantify the delivery of nanoparticles within them. We show that nanoparticles access a higher proportion of cells in micrometastases (50% nanoparticle-positive cells) compared with primary tumors (17% nanoparticle-positive cells) because they reside close to blood vessels and require a small diffusion distance to reach all tumor cells. Furthermore, the high-throughput nature of our image analysis workflow allowed us to profile the physiology and nanoparticle delivery of 1,301 micrometastases. This enabled us to use machine learning-based modeling to predict nanoparticle delivery to individual micrometastases based on their physiology. Our imaging method allows researchers to measure nanoparticle delivery to micrometastases and highlights an opportunity to target micrometastases with nanoparticles. The development of models to predict nanoparticle delivery based on micrometastasis physiology could enable personalized treatments based on the specific physiology of a patient’s micrometastases.
Brexpiprazole, a Serotonin-Dopamine Activity Modulator, Can Sensitize Glioma Stem Cells to Osimertinib, a Third-Generation EGFR-TKI, via Survivin Reduction

Glioblastoma is a primary brain tumor associated with a poor prognosis due to its high chemoresistance capacity. Cancer stem cells (CSCs) are one of the mechanisms of chemoresistance. Although therapy targeting CSCs is promising, strategies targeting CSCs remain unsuccessful. Abnormal activation of epidermal growth factor receptors (EGFRs) due to amplification, mutation, or both of the EGFR gene is common in glioblastomas. However, glioblastomas are resistant to EGFR tyrosine kinase inhibitors (EGFR-TKIs), and overcoming resistance is essential. Brexpiprazole is a new, safe serotonin-dopamine activity modulator used for schizophrenia and depression that was recently reported to have anti-CSC activity and function as a chemosensitizer. Here, we examined its chemosensitization effects on osimertinib, a third-generation EGFR-TKI with an excellent safety profile, in glioma stem cells (GSCs), which are CSCs of glioblastoma. Brexpiprazole treatment sensitized GSCs to osimertinib and reduced the expression of survivin, an antiapoptotic factor, and the pharmacological and genetic inhibition of survivin mimicked the effects of brexpiprazole. Moreover, co-treatment of brexpiprazole and osimertinib suppressed tumor growth more efficiently than either drug alone without notable toxicity in vivo. This suggests that the combination of brexpiprazole and osimertinib is a potential therapeutic strategy for glioblastoma by chemosensitizing GSCs through the downregulation of survivin expression.