Miracle-dz/UniFAR-FTUs huggingface dataset:
Empathy Modulates the Activity of the Sensorimotor Mirror Neuron System during Pain Observation

Aim: The aim of this study is to analyze the brain activity patterns during the observation of painful expressions and to establish the relationship between this activity and the scores obtained on the Interpersonal Reactivity Index (IRI). Methods: The study included twenty healthy, right-handed subjects (10 women). We conducted a task-based and resting-state functional magnetic resonance imaging (fMRI) study. The task involved observing pictures displaying painful expressions. We performed a region of interest (ROI) analysis focusing on the core regions of the sensorimotor mirror neuron system (MNS). Resting-state fMRI was utilized to assess the functional connectivity of the sensorimotor MNS regions with the rest of the cortex using a seed-to-voxel approach. Additionally, we conducted a regression analysis to examine the relationship between brain activity and scores from the IRI subtests. Results: Observing painful expressions led to increased activity in specific regions of the frontal, temporal, and parietal lobes. The largest cluster of activation was observed in the left inferior parietal lobule (IPL). However, the ROI analysis did not reveal any significant activity in the remaining core regions of the sensorimotor MNS. The regression analysis demonstrated a positive correlation between brain activity during the observation of pain and the “empathic concern” subtest scores of the IRI in both the cingulate gyri and bilateral IPL. Finally, we identified a positive relationship between the “empathic concern” subtest of the IRI and the functional connectivity (FC) of bilateral IPLs with the bilateral prefrontal cortex and the right IFG. Conclusion: Observing expressions of pain triggers activation in the sensorimotor MNS, and this activation is influenced by the individual’s level of empathy.
POTENTIAL APPLICATIONS OF BIOACTIVE COMPONENTS FROM BROWN ALGAE

Recently, macroalgae has found extensive utilization within the domain of biotechnology. Based on their variety of bioactive components, species of class Phaeophyceae are involved in the food, cosmetic, and pharmaceutical industries. Studies have proved that these unique compounds show beneficial activities for human health. With peculiar properties, including antioxidant, antimicrobial, antiviral activities, and related functionalities, each compound holds potential value for human health. This review discusses the bioactive compounds of brown algae and the recent multiple applications of those components that make up algae’s potential in industrial companies. The review was conducted by searching and selecting references related to the content of interest with popular web search engines such as Google Scholar and PubMed.
Improving health literacy using the power of digital communications to achieve better health outcomes for patients and practitioners

Digital communication tools have demonstrated significant potential to improve health literacy which ultimately leads to better health outcomes. In this article, we examine the power of digital communication tools such as mobile health apps, telemedicine and online health information resources to promote health and digital literacy. We outline evidence that digital tools facilitate patient education, self-management and empowerment possibilities. In addition, digital technology is optimising the potential for improved clinical decision-making, treatment options and communication among providers. We also explore the challenges and limitations associated with digital health literacy, including issues related to access, reliability and privacy. We propose leveraging digital communication tools is key to optimising engagement to enhance health literacy across demographics leading to transformation of healthcare delivery and driving better outcomes for all.
Recovery of a Bryophyte Community on Hurricane Island, Maine

Recovery of a bryophyte community on an artifically denuded granite ledge was monitored for 4 years on Hurricane Island, Maine. Predominant bryophyte species were Dicranum polysetum, Polytrichum juniperinurn, Dicranum flagellare, Polytrichum piliferum, and Dicranum fuscescens. Site factors such as nutrient supply, moisture, and availability of reproductive material were considered in relation to bryophyte growth to assess the ability of a specific island plant community to recover from a major disturbance. Recovery of the bryophyte community was rapid, with 60 percent bryophyte coverage over a bare rock surface by the end of the study. There was a strong relationship between the amount of needlefall from a nearby spruce-fir stand and the percent area coverage of bryophyte species.
Identification of Luminal A breast cancer by using deep learning analysis based on multi-modal images

Purpose To evaluate the diagnostic performance of a deep learning model based on multi-modal images in identifying molecular subtype of breast cancer. Materials and methods A total of 158 breast cancer patients (170 lesions, median age, 50.8 ± 11.0 years), including 78 Luminal A subtype and 92 non-Luminal A subtype lesions, were retrospectively analyzed and divided into a training set (n = 100), test set (n = 45), and validation set (n = 25). Mammography (MG) and magnetic resonance imaging (MRI) images were used. Five single-mode models, i.e., MG, T2-weighted imaging (T2WI), diffusion weighting imaging (DWI), axial apparent dispersion coefficient (ADC), and dynamic contrast-enhanced MRI (DCE-MRI), were selected. The deep learning network ResNet50 was used as the basic feature extraction and classification network to construct the molecular subtype identification model. The receiver operating characteristic curve were used to evaluate the prediction efficiency of each model. Results The accuracy, sensitivity and specificity of a multi-modal tool for identifying Luminal A subtype were 0.711, 0.889, and 0.593, respectively, and the area under the curve (AUC) was 0.802 (95% CI, 0.657- 0.906); the accuracy, sensitivity, and AUC were higher than those of any single-modal model, but the specificity was slightly lower than that of DCE-MRI model. The AUC value of MG, T2WI, DWI, ADC, and DCE-MRI model was 0.593 (95%CI, 0.436-0.737), 0.700 (95%CI, 0.545-0.827), 0.564 (95%CI, 0.408-0.711), 0.679 (95%CI, 0.523-0.810), and 0.553 (95%CI, 0.398-0.702), respectively. Conclusion The combination of deep learning and multi-modal imaging is of great significance for diagnosing breast cancer subtypes and selecting personalized treatment plans for doctors.
Seasonal Variations in the Solar and Lunar Daily Geomagnetic Variations

Summary Seasonal variations of the solar, S, and lunar, L, daily geomagnetic variations are discussed in terms of the ratio of seasonal range to annual mean range, for data based on hourly mean values from 100 observatories for the interval 1957.5 to 1960.0. It is shown that, for all elements, the greatest and least values of the ratio occur at high latitudes for both S and L. The conflicting views of previous workers on the difference between seasonal variations of L and S are discussed in the light of the present results and those from longer series of data from a few observatories.
Vertical seismic wave gradiometry: Application at the San Andreas Fault Observatory at Depth

ABSTRACTWe have developed vertical seismic wave gradiometry (VSWG) to estimate velocity, impedance, and attenuation structure in the vicinity of boreholes using borehole array waveforms of check-shot explosions near the borehole head. We have extended wave gradiometry (WG) theory from a purely local relation of the wavefield and wavefield spatial gradient to one that incorporated the ray ansatz over the length of the borehole for a traveling wave in a vertically inhomogeneous medium. We checked the ray assumption against acoustic full-wave synthetic seismograms, and it was found to yield robust measures of the medium velocity. Anelastic attenuation and impedance structure trade off, but in cases of high anelastic attenuation, realistic bounds can be placed on the seismic impedance that effectively constrains the average attenuation. We have applied these methods to data collected at the San Andreas Fault Observatory at Depth borehole in central California in 2005, and we found that the WG velocity estimat.
Water use characteristics of black mangrove (Avicennia germinans) communities along an ecotone with marsh at a northern geographical limit

Mangroves are expanding into warm temperate‐zone salt marsh communities in several locations globally. Although scientists have discovered that expansion might have modest effects on ecosystem functioning, water use characteristics have not been assessed relative to this transition. We measured early growing season sapflow (Js) and leaf transpiration (Tr) in Avicennia germinans at a latitudinal limit along the northern Gulf of Mexico (Louisiana, United States) under both flooded and drained states and used these data to scale vegetation water use responses in comparison with Spartina alterniflora. We discovered strong convergence when using either Js or Tr for determining individual tree water use, indicating tight connection between transpiration and xylem water movement in small Avicennia trees. When Tr data were combined with leaf area indices for the region with the use of three separate approaches, we determined that Avicennia stands use approximately 1·0–1·3 mm d–1 less water than Spartina marsh. Differences were only significant with the use of two of the three approaches, but are suggestive of net conservation of water as Avicennia expands into Spartina marshes at this location. Average Js for Avicennia trees was not influenced by flooding, but maximum Js was greater when sites were flooded. Avicennia and Spartina closest to open water (shoreline) used more water than interior locations of the same assemblages by an average of 1·3 mm d−1. Lower water use by Avicennia may indicate a greater overall resilience to drought relative to Spartina, such that aperiodic drought may interact with warmer winter temperatures to facilitate expansion of Avicennia in some years. Published 2012. This article is a U.S. Government work and is in the public domain in the USA.
Ultrasound-Guided vs. Fluoroscopy-Guided Interventions for Back Pain Management: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

The objective of this study was to compare the outcomes of the ultrasound- and fluoroscopy-guided techniques in the management of back pain. Using PubMed, Scopus, and the Cochrane Library, we searched randomized controlled trials (RCTs) published before May 2023, which reported relevant data on the topic. The effectiveness of the ultrasound-guided (US-guided) and fluoroscopy-guided (FL-guided) approaches for back pain management was compared in terms of postoperative pain intensity, postoperative functional outcomes, and postoperative complications. Subgroup analyses were conducted for different postoperative periods. Eight studies were included in the analysis. There was no significant difference in post-procedural pain relief at one week, two weeks, one month, two months, and three months between the US-guided and FL-guided interventions for back pain management (SMD with 95% CI is −0.01 [−0.11, 0.10]), p = 0.91, I2 = 0%). In terms of the postoperative functional outcomes assessed by the “Oswestry Disability Index” (ODI) functionality score, the model tends to favor the FL-guided injections over the US-guided injections (SMD with 95% CI: 0.13 [−0.00, 0.25], p = 0.05, I2 = 0). Finally, the US-guided and FL-guided injections did not show significantly different results in terms of postoperative complications (RR with 95% CI is 0.99 [0.49, 1.99], p = 0.97, I2 = 0). The subgroup analysis also did not demonstrate differences between the US-guided and FL-guided techniques in the following outcomes: vasovagal reaction, transient headache, and facial flushing. There was no significant difference between the US-guided and FL-guided injections for treating back pain in terms of postoperative pain intensity and complications. Still, the model tends to favor the FL-guided injections over the US-guided injections in terms of functionality.
Perseid: A Secondary Indexing Mechanism for LSM-based Storage Systems

LSM-based storage systems are widely used for superior write performance on block devices. However, they currently fail to efficiently support secondary indexing, since a secondary index query operation usually needs to retrieve multiple small values, which scatter in multiple LSM components. In this work, we revisit secondary indexing in LSM-based storage systems with byte-addressable persistent memory (PM). Existing PM-based indexes are not directly competent for efficient secondary indexing. We propose Perseid, an efficient PM-based secondary indexing mechanism for LSM-based storage systems, which takes into account both characteristics of PM and secondary indexing. Perseid consists of (1) a specifically designed secondary index structure that achieves high-performance insertion and query, (2) a lightweight hybrid PM-DRAM and hash-based validation approach to filter out obsolete values with subtle overhead, and (3) two adapted optimizations on primary table searching issued from secondary indexes to accelerate non-index-only queries. Our evaluation shows that Perseid outperforms existing PM-based indexes by 3-7 × and achieves about two orders of magnitude performance of state-of-the-art LSM-based secondary indexing techniques even if on PM instead of disks.
Presencia del icnogénero Iguanodontipus en el Cretácico Inferior de la provincia de Teruel (España) Presence of the ichnogenus Iguanodontipus in the Lower Cretaceous of the Teruel province (Spain)

Until now, the presence of iguanodontoids in the Lower Cretaceous of the Teruel province has been restricted to fossil bones and teeth. New tracks have been found in the Areniscas de Camarillas Formation (lower Barremian) in Cabra de Mora and El Castellar (both villages located in Teruel province, Maestrazgo basin, Penagolosa Sub-basin). These new tracks are assigned to the ichnogenus Iguanodontipus, and their presence helps to complete the record of this kind of tracks in the Iberian Peninsula. Moreover, these tracks show that iguanodontoids were part of these fluvial continental ecosystems of this stratigraphic unit. It is quite remarkable the size of these ornithopods illustrated by track CPT-4399, measuring 50 cm of both length and width. This footprint has been preserved as convex epirelief.
Evaluation of Dietary and Alcohol Drinking Patterns in Patients with Excess Body Weight in a Spanish Cohort: Impact on Cardiometabolic Risk Factors

Unhealthy dietary habits and sedentarism coexist with a rising incidence of excess weight and associated comorbidities. We aimed to analyze the dietary and drinking patterns of patients with excess weight, their main characteristics, plausible gender differences and impact on cardiometabolic risk factors, with a particular focus on the potential contribution of beer consumption. Data from 200 consecutive volunteers (38 ± 12 years; 72% females) living with overweight or class I obesity attending the obesity unit to lose weight were studied. Food frequency questionnaires and 24 h recalls were used. Reduced-rank regression (RRR) analysis was applied to identify dietary patterns (DPs). Anthropometry, total and visceral fat, indirect calorimetry, physical activity level, comorbidities and circulating cardiometabolic risk factors were assessed. Study participants showed high waist circumference, adiposity, insulin resistance, dyslipidemia, pro-inflammatory adipokines and low anti-inflammatory factors like adiponectin and interleukin-4. A low-fiber, high-fat, energy-dense DP was observed. BMI showed a statistically significant (p < 0.05) correlation with energy density (r = 0.80) as well as percentage of energy derived from fat (r = 0.61). Excess weight was associated with a DP low in vegetables, legumes and whole grains at the same time as being high in sweets, sugar-sweetened beverages, fat spreads, and processed meats. RRR analysis identified a DP characterized by high energy density and saturated fat exhibiting negative loadings (>−0.30) for green leafy vegetables, legumes, and fruits at the same time as showing positive factor loadings (>0.30) for processed foods, fat spreads, sugar-sweetened beverages, and sweets. Interestingly, for both women and men, wine represented globally the main source of total alcohol intake (p < 0.05) as compared to beer and distillates. Beer consumption cannot be blamed as the main culprit of excess weight. Capturing the DP provides more clinically relevant and useful information. The focus on consumption of single nutrients does not resemble real-world intake behaviors.
Individualization of Duration of Dual Antiplatelet Therapy after Coronary Stenting: A Comprehensive, Evidence-Based Review

Dual antiplatelet therapy (DAPT), comprising aspirin and a P2Y12 receptor inhibitor, is the cornerstone of post-percutaneous coronary intervention treatment to prevent stent thrombosis and reduce the risk of adverse cardiovascular events. The selection of an optimal DAPT regimen, considering the interplay of various antiplatelet agents, patient profiles, and procedural characteristics, remains an evolving challenge. Traditionally, a standard duration of 12 months has been recommended for DAPT in most patients. While contemporary guidelines provide general frameworks, DAPT modulation with longer or shorter treatment courses followed by aspirin or P2Y12 inhibitor monotherapy are evolving towards an individualized strategy to optimize the balance between efficacy and safety. This review comprehensively examines the current landscape of DAPT strategies after coronary stenting, with a focus on emerging evidence for treatment individualization.
Assessment of the effects of prepartum anti-inflammatory therapies on type 1/type 2 immunity ratio using a rapid blood test

Graphical Abstract Summary During the transition period, cows experience systemic inflammatory processes necessary for physiological events related to calving; however, an exacerbated inflammatory response could increase the risk of developing diseases and poor performance. Postpartum anti-inflammatory treatments have been proposed as an alternative to modulating this inflammatory response. Moreover, prepartum anti-inflammatory strategies have not been investigated yet. The objective of this study was to assess the effects of prepartum administration of anti-inflammatory therapies on type 1/type 2 immunity ratio using a rapid blood test (D2Dx immunity test) and identify correlations between the rapid blood test scores and daily milk yield in Holstein dairy cows. Cows treated with acetylsalicylic acid and meloxicam had higher type 1/type 2 immunity ratios around calving compared with placebo animals. These results suggest that prepartum anti-inflammatory therapies may cause an increased shift in type 1 immunity around calving, which may be associated with stronger immunity.
Mammoth Bilateral Ovarian Serous Cyst Adenomas in a Postmenopausal Woman: A Rare Case Report

Serous cyst adenomas account for about 40% of all ovarian tumors and most commonly are diagnosed in middle-aged women. The aim of this publication is to present an extremely rare case of mammoth bilateral cyst adenomas in a postmenopausal woman, occupying the pelvis and the most of abdominal cavity. A 67-year-old obese woman was presented to our emergency department with abdominal pain. Ultrasound and computed tomography of the abdomen verified two huge cystic masses. Exploration of the abdominal cavity by laparotomy established two intact giant cystic masses with ovarian origin. The cysts were removed by bilateral salpingo-oophorectomy and hysterectomy was performed. Histological examination revealed that both cystic masses were ovarian serous cyst adenomas. The woman was discharged with an uneventful recovery. We present a case of the largest gigantic bilateral ovarian cyst adenomas in the oldest woman ever reported.
Transcriptome and miRNAs Profiles Reveal Regulatory Network and Key Regulators of Secondary Xylem Formation in “84K” Poplar

Secondary xylem produced by stem secondary growth is the main source of tree biomass and possesses great economic and ecological value in papermaking, construction, biofuels, and the global carbon cycle. The secondary xylem formation is a complex developmental process, and the underlying regulatory networks and potential mechanisms are still under exploration. In this study, using hybrid poplar (Populus alba × Populus glandulosa clone 84K) as a model system, we first ascertained three representative stages of stem secondary growth and then investigated the regulatory network of secondary xylem formation by joint analysis of transcriptome and miRNAs. Notably, 7507 differentially expressed genes (DEGs) and 55 differentially expressed miRNAs (DEMs) were identified from stage 1 without initiating secondary growth to stage 2 with just initiating secondary growth, which was much more than those identified from stage 2 to stage 3 with obvious secondary growth. DEGs encoding transcription factors and lignin biosynthetic enzymes and those associated with plant hormones were found to participate in the secondary xylem formation. MiRNA-target analysis revealed that a total of 85 DEMs were predicted to have 2948 putative targets. Among them, PagmiR396d-PagGRFs, PagmiR395c-PagGA2ox1/PagLHW/PagSULTR2/PagPolyubiquitin 1, PagmiR482d-PagLAC4, PagmiR167e-PagbHLH62, and PagmiR167f/g/h-PagbHLH110 modules were involved in the regulating cambial activity and its differentiation into secondary xylem, cell expansion, secondary cell wall deposition, and programmed cell death. Our results give new insights into the regulatory network and mechanism of secondary xylem formation.
Carbonate reservoir characterization with lithofacies clustering and porosity prediction

One of the objectives in reservoir characterization is to quantitatively or semi-quantitatively map the spatial distribution of its heterogeneity and related properties. With the availability of 3D seismic data, artificial neural networks are capable of discovering the nonlinear relationship between seismic attributes and reservoir parameters. For a target carbonate reservoir, we adopt a two-stage approach to conduct characterization. First, we use an unsupervised neural network, the self-organizing map method, to classify the reservoir lithofacies. Then we apply a supervised neural network, the back-propagation algorithm, to quantitatively predict the porosity of the carbonate reservoir. Based on porosity maps at different time levels, we interpret the target reservoir vertically related to three depositional phases corresponding to, respectively, a lowstand system tract before sea water immersion, a highstand system tract when water covers organic deposits and a transition zone for the sea level falling. The highstand system is the most prospective zone, given the organic content deposited during this stage. The transition zone is also another prospective feature in the carbonate depositional system due to local build-ups.