Miracle-dz/UniFAR-FTUs huggingface dataset:
Review of Functional and Pharmacological Activities of Berries

Functional plant-based foods (such as fruits, vegetables, and berries) can improve health, have a preventive effect, and diminish the risk of different chronic diseases during in vivo and in vitro studies. Berries contain many phytochemicals, fibers, vitamins, and minerals. The primary phytochemicals in berry fruits are phenolic compounds including flavonoids (anthocyanins, flavonols, flavones, flavanols, flavanones, and isoflavonoids), tannins, and phenolic acids. Since berries have a high concentration of polyphenols, it is possible to use them for treating various diseases pharmacologically by acting on oxidative stress and inflammation, which are often the leading causes of diabetes, neurological, cardiovascular diseases, and cancer. This review examines commonly consumed berries: blackberries, blackcurrants, blueberries, cranberries, raspberries, black raspberries, and strawberries and their polyphenols as potential medicinal foods (due to the presence of pharmacologically active compounds) in the treatment of diabetes, cardiovascular problems, and other diseases. Moreover, much attention is paid to the bioavailability of active berry components. Hence, this comprehensive review shows that berries and their bioactive compounds possess medicinal properties and have therapeutic potential. Nevertheless, future clinical trials are required to study and improve the bioavailability of berries’ phenolic compounds and extend the evidence that the active compounds of berries can be used as medicinal foods against various diseases.
Adipose Tissue Immunomodulation and Treg/Th17 Imbalance in the Impaired Glucose Metabolism of Children with Obesity

In the last few decades, obesity has increased dramatically in pediatric patients. Obesity is a chronic disease correlated with systemic inflammation, characterized by the presence of CD4 and CD8 T cell infiltration and modified immune response, which contributes to the development of obesity related diseases and metabolic disorders, including impaired glucose metabolism. In particular, Treg and Th17 cells are dynamically balanced under healthy conditions, but imbalance occurs in inflammatory and pathological states, such as obesity. Some studies demonstrated that peripheral Treg and Th17 cells exhibit increased imbalance with worsening of glucose metabolic dysfunction, already in children with obesity. In this review, we considered the role of adipose tissue immunomodulation and the potential role played by Treg/T17 imbalance on the impaired glucose metabolism in pediatric obesity. In the patient care, immune monitoring could play an important role to define preventive strategies of pediatric metabolic disease treatments.
Automated prediction of final infarct volume in patients with large-vessel occlusion acute ischemic stroke.

OBJECTIVE In patients with large-vessel occlusion (LVO) acute ischemic stroke (AIS), determinations of infarct size play a key role in the identification of candidates for endovascular stroke therapy (EVT). An accurate, automated method to quantify infarct at the time of presentation using widely available imaging modalities would improve screening for EVT. Here, the authors aimed to compare the performance of three measures of infarct core at presentation, including an automated method using machine learning. METHODS Patients with LVO AIS who underwent successful EVT at four comprehensive stroke centers were identified. Patients were included if they underwent concurrent noncontrast head CT (NCHCT), CT angiography (CTA), and CT perfusion (CTP) with Rapid imaging at the time of presentation, and MRI 24 to 48 hours after reperfusion. NCHCT scans were analyzed using the Alberta Stroke Program Early CT Score (ASPECTS) graded by neuroradiology or neurology expert readers. CTA source images were analyzed using a previously described machine learning model named DeepSymNet (DSN). Final infarct volume (FIV) was determined from diffusion-weighted MRI sequences using manual segmentation. The primary outcome was the performance of the three infarct core measurements (NCHCT-ASPECTS, CTA with DSN, and CTP-Rapid) to predict FIV, which was measured using area under the receiver operating characteristic (ROC) curve (AUC) analysis. RESULTS Among 76 patients with LVO AIS who underwent EVT and met inclusion criteria, the median age was 67 years (IQR 54-76 years), 45% were female, and 37% were White. The median National Institutes of Health Stroke Scale score was 16 (IQR 12-22), and the median NCHCT-ASPECTS on presentation was 8 (IQR 7-8). The median time between when the patient was last known to be well and arrival was 156 minutes (IQR 73-303 minutes), and between NCHCT/CTA/CTP to groin puncture was 73 minutes (IQR 54-81 minutes). The AUC was obtained at three different cutoff points: 10 ml, 30 ml, and 50 ml FIV. At the 50-ml FIV cutoff, the AUC of ASPECTS was 0.74; of CTP core volume, 0.72; and of DSN, 0.82. Differences in AUCs for the three predictors were not significant for the three FIV cutoffs. CONCLUSIONS In a cohort of patients with LVO AIS in whom reperfusion was achieved, determinations of infarct core at presentation by NCHCT-ASPECTS and a machine learning model analyzing CTA source images were equivalent to CTP in predicting FIV. These findings have suggested that the information to accurately predict infarct core in patients with LVO AIS was present in conventional imaging modalities (NCHCT and CTA) and accessible by machine learning methods.
Persistent Spinal Pain Syndrome Type 2 (PSPS-T2), a Social Pain? Advocacy for a Social Gradient of Health Approach to Chronic Pain

The Social Gradient of Health (SGH), or position in the social hierarchy, is one of the major determinants of health. It influences the development and evolution of many chronic diseases. Chronic pain dramatically affects individual and social condition. Its medico-economic impact is significant and worldwide. Failed Back Surgery Syndrome or Persistent Spinal Pain Syndrome type 2 (PSPS-T2) represents one of its most fascinating and disabling conditions. However, the influence of SGH on PSPS-T2 has been poorly explored. We designed a prospective multicentric study (PREDIBACK study) to assess the SGH prevalence, and to examine its association with medical and psychological variables, in PSPS-T2 patients. This study included 200 patients to determine the SGH association with pain (NPRS), Quality of life (EQ-5D-5L), kinesiophobia (FABQ-Work), catastrophism (CSQ), and functional capacity (ODI). Around 85.3% of PSPS-T2 patients in our study had low SGH. Low SGH patients had a higher FABQ-Work and CSQ-Catastrophizing score than high SGH patients (p < 0.05). High SGH patients have a higher ODI score than low SGH patients (p < 0.10). Our results suggest that SGH is a relevant factor to guide prevention, research, and ultimately intervention in PSPS-T2 patients and could be more widely transposed to chronic pain.
The Influence of Mitochondrial Dynamics and Function on Retinal Ganglion Cell Susceptibility in Optic Nerve Disease

The important roles of mitochondrial function and dysfunction in the process of neurodegeneration are widely acknowledged. Retinal ganglion cells (RGCs) appear to be a highly vulnerable neuronal cell type in the central nervous system with respect to mitochondrial dysfunction but the actual reasons for this are still incompletely understood. These cells have a unique circumstance where unmyelinated axons must bend nearly 90° to exit the eye and then cross a translaminar pressure gradient before becoming myelinated in the optic nerve. This region, the optic nerve head, contains some of the highest density of mitochondria present in these cells. Glaucoma represents a perfect storm of events occurring at this location, with a combination of changes in the translaminar pressure gradient and reassignment of the metabolic support functions of supporting glia, which appears to apply increased metabolic stress to the RGC axons leading to a failure of axonal transport mechanisms. However, RGCs themselves are also extremely sensitive to genetic mutations, particularly in genes affecting mitochondrial dynamics and mitochondrial clearance. These mutations, which systemically affect the mitochondria in every cell, often lead to an optic neuropathy as the sole pathologic defect in affected patients. This review summarizes knowledge of mitochondrial structure and function, the known energy demands of neurons in general, and places these in the context of normal and pathological characteristics of mitochondria attributed to RGCs.
Parenchymal Extinction Mimicking Hepatocellular Carcinoma in a Patient with Chronic Hepatitis B-Related Liver Cirrhosis

Parenchymal extinction is characterized by the irreversible loss of hepatocytes and their eventual replacement by fibrous tissue, along with the alteration of the sinusoidal architecture and the obstruction of the small portal and hepatic veins. In clinical practice, radiologic modalities are not sufficient for differentiating between parenchymal extinction and hepatocellular carcinoma in patients with advanced fibrosis or cirrhosis. Herein, we present a case of parenchymal extinction mimicking hepatocellular carcinoma in a patient with chronic hepatitis B-related liver cirrhosis.
Egocentric-View Fingertip Detection for Air Writing Based on Convolutional Neural Networks †

This research investigated real-time fingertip detection in frames captured from the increasingly popular wearable device, smart glasses. The egocentric-view fingertip detection and character recognition can be used to create a novel way of inputting texts. We first employed Unity3D to build a synthetic dataset with pointing gestures from the first-person perspective. The obvious benefits of using synthetic data are that they eliminate the need for time-consuming and error-prone manual labeling and they provide a large and high-quality dataset for a wide range of purposes. Following that, a modified Mask Regional Convolutional Neural Network (Mask R-CNN) is proposed, consisting of a region-based CNN for finger detection and a three-layer CNN for fingertip location. The process can be completed in 25 ms per frame for 640×480 RGB images, with an average error of 8.3 pixels. The speed is high enough to enable real-time “air-writing”, where users are able to write characters in the air to input texts or commands while wearing smart glasses. The characters can be recognized by a ResNet-based CNN from the fingertip trajectories. Experimental results demonstrate the feasibility of this novel methodology.
Chemotherapeutic Regimens and Chemotherapy-Free Intervals Influence the Survival of Patients with Recurrent Advanced Epithelial Ovarian Carcinoma: A Retrospective Population-Based Study

We aimed to evaluate factors influencing the outcomes of patients with platinum-sensitive recurrent epithelial ovarian carcinoma (EOC). Patients with advanced-stage EOC, who received debulking surgery and adjuvant chemotherapy for recurrence, were obtained from the National Health Insurance Research database of Taiwan between 2000 and 2013. A total of 1038 patients with recurrent advanced-stage EOC were recruited. The platinum + paclitaxel (PT) group had the best five-year overall survival (OS) compared with the other three groups (p < 0.001). The hazard ratios (HRs) of five-year OS for the platinum + liposomal doxorubicin (PD), topotecan (TOP), and pegylated liposomal doxorubicin (PLD) groups were 1.21 (p = 0.07), 1.35 (p = 0.016), and 1.80 (p < 0.001), respectively, compared with the PT group. The PT group also had lower hazard ratios of five-year OS for patients with platinum therapy-free interval (TFIp) between 6 and 12 months compared with the other three groups (p < 0.0001). However, the HRs of five-year OS did not differ between the PT and PD groups in patients with TFIp >12 months. Patients with TFIp >12 months had lower HRs of five-year OS compared with those with TFIp of 6–12 months, regardless of whether they were treated with platinum-based (p = 0.001) or non-platinum-based (p = 0.003) regimens. Chemotherapeutic regimens and TFIp influenced the outcomes of patients with recurrent EOC. For patients with TFIp of 6–12 months, the PT regimen is the first choice based on their best overall survival result. For patients with TFIp >12 months, either platinum-based or non-platinum regimens could be used because of their similar excellent overall survival.
Tactile Interaction Sensor with Millimeter Sensing Acuity

In this article we report on a 3 × 3 mm tactile interaction sensor that is able to simultaneously detect pressure level, pressure distribution, and shear force direction. The sensor consists of multiple mechanical switches under a conducting diaphragm. An external stimulus is measured by the deflection of the diaphragm and the arrangement of mechanical switches, resulting in low noise, high reliability, and high uniformity. Our sensor is able to detect tactile forces as small as ~50 mgf along with the direction of the shear force. It also distinguishes whether there is a normal pressure during slip motion. We also succeed in detecting the contact shape and the contact motion, demonstrating potential applications in robotics and remote input interfaces. Since our sensor has a simple structure and its function depends only on sensor dimensions, not on an active sensing material, in comparison with previous tactile sensors, our sensor shows high uniformity and reliability for an array-type integration.
Poorly Differentiated and Anaplastic Thyroid Cancer: Insights into Genomics, Microenvironment and New Drugs

Simple Summary In the last decades, many researchers produced promising data concerning genetics and tumor microenvironment of poorly differentiated thyroid cancer (PDTC) and anaplastic thyroid cancer (ATC). They are trying to tear the veil covering these orphan cancers, suggesting new therapeutic weapons as single or combined therapies. Abstract PDTC and ATC present median overall survival of 6 years and 6 months, respectively. In spite of their rarity, patients with PDTC and ATC represent a significant clinical problem, because of their poor survival and the substantial inefficacy of classical therapies. We reviewed the newest findings about genetic features of PDTC and ATC, from mutations occurring in DNA to alterations in RNA. Therefore, we describe their tumor microenvironments (both immune and not-immune) and the interactions between tumor and neighboring cells. Finally, we recapitulate how this upcoming evidence are changing the treatment of PDTC and ATC.
Integrating Electrocardiography and Vectorcardiography in the Differential Diagnosis of Wide Complex Tachycardia in a Patient with Left Ventricular Noncompaction: A Case Report and Brief Literature Review

A 69-year-old woman with a history of hypertension and obesity, hospitalized with atypical chest pain, was diagnosed with left ventricular noncompaction. In-hospital monitoring of the cardiac rhythm revealed multiple episodes of atrial tachycardia and one episode of wide complex tachycardia (WCT) with left bundle branch block-like morphology and a right superior QRS axis. The electrocardiographic criteria were suggestive of a supraventricular origin of the WCT. Given the importance of reaching the correct diagnosis when dealing with a WCT, we tried to further define the pattern of ventricular activation using vectorcardiography (VCG). We analyzed the QRS loops during WCT in comparison to a sinus beat, a narrow complex tachycardia beat, and a premature ventricular contraction. The fast initial activation seen in the efferent limb of the QRS loop during the WCT was thought to be reflective of the fast initial activation via the conduction system seen in SVT with aberrancy, which was our final diagnosis for the WCT episode. This case illustrates a novel use of vectorcardiography as an additional diagnostic tool in the differential diagnosis of WCT.
TRPV1 Blocker HCRG21 Suppresses TNF-α Production and Prevents the Development of Edema and Hypersensitivity in Carrageenan-Induced Acute Local Inflammation

Currently the TRPV1 (transient receptor potential vanilloid type 1) channel is considered to be one of the main targets for pro-inflammatory mediators including TNF-α. Similarly, the inhibition of TRPV1 activity in the peripheral nervous system affects pro-inflammatory mediator production and enhances analgesia in total. In this study, the analgesic and anti-inflammatory effects of HCRG21, the first peptide blocker of TRPV1, were demonstrated in a mice model of carrageenan-induced paw edema. HCRG21 in doses of 0.1 and 1 mg/kg inhibited edema formation compared to the control, demonstrated complete edema disappearance in 24 h in a dose of 1 mg/kg, and effectively reduced the productionof TNF-α in both doses examined. ELISA analysis of blood taken 24 h after carrageenan administration showed a dramatic cytokine value decrease to 25 pg/mL by HCRG21 versus 100 pg/mL in the negative control group, which was less than the TNF-α level in the intact group (40 pg/mL). The HCRG21 demonstrated potent analgesic effects on the models of mechanical and thermal hyperalgesia in carrageenan-induced paw edema. The HCRG21 relief effect was comparable to that of indomethacin taken orally in a dose of 5 mg/kg, but was superior to this nonsteroidal anti-inflammatory drug (NSAID) in duration (which lasted 24 h) in the mechanical sensitivity experiment. The results confirm the existence of a close relationship between TRPV1 activity and TNF-α production once again, and prove the superior pharmacological potential of TRPV1 blockers and the HCRG21 peptide in particular.
Optimizing the microscopic agglutination test (MAT) panel for the diagnosis of Leptospirosis in a low resource, hyper-endemic setting with varied microgeographic variation in reactivity

The microscopic agglutination test (MAT) is the standard serological reference test for the diagnosis of leptospirosis, despite being a technically demanding and laborious procedure. The use of a locally optimised MAT panel is considered essential for proper performance and interpretation of results. This paper describes the procedure of selecting such an optimised panel for Sri Lanka, a country hyper-endemic for leptospirosis. MAT was performed using 24 strains on 1132 serum samples collected from patients presenting with acute undifferentiated fever. Of 24 strains, 15 were selected as the optimised panel, while only 11% of serum samples showed positivity. A geographical variation in predominantly reactive serovars was observed, whereas reactivity was low with the saprophytic strain Patoc. Testing with paired sera yielded a higher sensitivity but provided only a retrospective diagnosis. Serological tests based on ELISA with complementary molecular diagnosis using PCR are a feasible and robust alternative approach to diagnose leptospirosis in countries having a higher burden of the disease.
Beverage Intake and the Risk of Gestational Diabetes Mellitus: The SECOST

The contribution and impact of beverage intake to total nutrient and energy intake may be substantial. Given the link between lifestyle, diet, and the risk of pregnancy complications, this study investigated the association between the quantity and types of beverages with gestational diabetes mellitus (GDM) risk. The study included 452 women from the Seremban Cohort Study (SECOST). The mean energy by beverage intake was 273 ± 23.83 kcal/day (pre-pregnancy), 349 ± 69.46 kcal/day (first trimester) and 361 ± 64.24 kcal/day (second trimester). Women significantly increased intake of maternal milks and malted drinks, but significantly reduced the intake of carbonated drinks and other drinks from before until the second trimester of pregnancy. For chocolate drinks, carbonated drinks, and soy milk, women increased intake from pre-conception to the first trimester, but reduced their intake from the first to the second trimester. While higher intake of cultured-milk drinks was associated with an increased risk of GDM, higher fruit juice intake was associated with a lower risk of GDM. However, these associations were only observed for intake prior to pregnancy and during the first trimester. Further research is needed to corroborate these findings and investigate the contributions of different beverages to overall diet quality as well as adverse health outcomes during pregnancy.
Integrative Analysis of Next-Generation Sequencing for Next-Generation Cancer Research toward Artificial Intelligence

Simple Summary In recent years both research areas of next-generation sequencing and artificial intelligence have grown remarkably. Their intersection simultaneously gave rise to a panacea of different algorithms and applications. This article delineates tailored machine learning and systems biology approaches and combinations thereof that tackle the various challenges that arise in the face of big data. Moreover, it provides an overview of the numerous applications of artificial intelligence aiding the analysis and interpretation of next-generation sequencing data. Abstract The rapid improvement of next-generation sequencing (NGS) technologies and their application in large-scale cohorts in cancer research led to common challenges of big data. It opened a new research area incorporating systems biology and machine learning. As large-scale NGS data accumulated, sophisticated data analysis methods became indispensable. In addition, NGS data have been integrated with systems biology to build better predictive models to determine the characteristics of tumors and tumor subtypes. Therefore, various machine learning algorithms were introduced to identify underlying biological mechanisms. In this work, we review novel technologies developed for NGS data analysis, and we describe how these computational methodologies integrate systems biology and omics data. Subsequently, we discuss how deep neural networks outperform other approaches, the potential of graph neural networks (GNN) in systems biology, and the limitations in NGS biomedical research. To reflect on the various challenges and corresponding computational solutions, we will discuss the following three topics: (i) molecular characteristics, (ii) tumor heterogeneity, and (iii) drug discovery. We conclude that machine learning and network-based approaches can add valuable insights and build highly accurate models. However, a well-informed choice of learning algorithm and biological network information is crucial for the success of each specific research question.
A Conceptual Framework for Integrating Cellular Protein Folding, Misfolding and Aggregation

How proteins properly fold and maintain solubility at the risk of misfolding and aggregation in the cellular environments still remains largely unknown. Aggregation has been traditionally treated as a consequence of protein folding (or misfolding). Notably, however, aggregation can be generally inhibited by affecting the intermolecular interactions leading to aggregation, independently of protein folding and conformation. We here point out that rigorous distinction between protein folding and aggregation as two independent processes is necessary to reconcile and underlie all observations regarding the combined cellular protein folding and aggregation. So far, the direct attractive interactions (e.g., hydrophobic interactions) between cellular macromolecules including chaperones and interacting polypeptides have been widely believed to mainly stabilize polypeptides against aggregation. However, the intermolecular repulsions by large excluded volume and surface charges of cellular macromolecules can play a key role in stabilizing their physically connected polypeptides against aggregation, irrespective of the connection types and induced conformational changes, underlying the generic intrinsic chaperone activity of cellular macromolecules. Such rigorous distinction and intermolecular repulsive force-driven aggregation inhibition by cellular macromolecules could give new insights into understanding the complex cellular protein landscapes that remain uncharted.