bluuebunny/crossref_metadata_2025 huggingface dataset:
Biomarkers in Systemic Lupus Erythematosus along with Metabolic Syndrome
Authors: Corona-Meraz Fernanda Isadora , Vázquez-Del Mercado Mónica , Sandoval-García Flavio , Robles-De Anda Jesus-Aureliano , Tovar-Cuevas Alvaro-Jovanny , Rosales-Gómez Roberto-Carlos , Guzmán-Ornelas Milton-Omar , González-Inostroz Daniel , Peña-Nava Miguel , Martín-Márquez Beatriz-Teresita
Published: March 2024

Metabolic syndrome (MetS) is a group of physiological abnormalities characterized by obesity, insulin resistance (IR), and hypertriglyceridemia, which carry the risk of developing cardiovascular disease (CVD) and type 2 diabetes (T2D). Immune and metabolic alterations have been observed in MetS and are associated with autoimmune development. Systemic lupus erythematosus (SLE) is an autoimmune disease caused by a complex interaction of environmental, hormonal, and genetic factors and hyperactivation of immune cells. Patients with SLE have a high prevalence of MetS, in which elevated CVD is observed. Among the efforts of multidisciplinary healthcare teams to make an early diagnosis, a wide variety of factors have been considered and associated with the generation of biomarkers. This review aimed to elucidate some primary biomarkers and propose a set of assessments to improve the projection of the diagnosis and evolution of patients. These biomarkers include metabolic profiles, cytokines, cardiovascular tests, and microRNAs (miRs), which have been observed to be dysregulated in these patients and associated with outcomes.
Development of an Artificial Intelligence Diagnostic System Using Linked Color Imaging for Barrett’s Esophagus
Authors: Takeda Tsutomu , Asaoka Daisuke , Ueyama Hiroya , Abe Daiki , Suzuki Maiko , Inami Yoshihiro , Uemura Yasuko , Yamamoto Momoko , Iwano Tomoyo , Uchida Ryota , Utsunomiya Hisanori , Oki Shotaro , Suzuki Nobuyuki , Ikeda Atsushi , Akazawa Yoichi , Matsumoto Kohei , Ueda Kumiko , Hojo Mariko , Nojiri Shuko , Tada Tomohiro , Nagahara Akihito
Published: March 2024

Background: Barrett’s esophagus and esophageal adenocarcinoma cases are increasing as gastroesophageal reflux disease increases. Using artificial intelligence (AI) and linked color imaging (LCI), our aim was to establish a method of diagnosis for short-segment Barrett’s esophagus (SSBE). Methods: We retrospectively selected 624 consecutive patients in total at our hospital, treated between May 2017 and March 2020, who experienced an esophagogastroduodenoscopy with white light imaging (WLI) and LCI. Images were randomly chosen as data for learning from WLI: 542 (SSBE+/− 348/194) of 696 (SSBE+/− 444/252); and LCI: 643 (SSBE+/− 446/197) of 805 (SSBE+/− 543/262). Using a Vision Transformer (Vit-B/16-384) to diagnose SSBE, we established two AI systems for WLI and LCI. Finally, 126 WLI (SSBE+/− 77/49) and 137 LCI (SSBE+/− 81/56) images were used for verification purposes. The accuracy of six endoscopists in making diagnoses was compared to that of AI. Results: Study participants were 68.2 ± 12.3 years, M/F 330/294, SSBE+/− 409/215. The accuracy/sensitivity/specificity (%) of AI were 84.1/89.6/75.5 for WLI and 90.5/90.1/91.1/for LCI, and those of experts and trainees were 88.6/88.7/88.4, 85.7/87.0/83.7 for WLI and 93.4/92.6/94.6, 84.7/88.1/79.8 for LCI, respectively. Conclusions: Using AI to diagnose SSBE was similar in accuracy to using a specialist. Our finding may aid the diagnosis of SSBE in the clinic.
Role of Palliative Care in the Supportive Management of AL Amyloidosis—A Review
Authors: Habib Muhammad , Tiger Yun , Dima Danai , Schlögl Mathias , McDonald Alexandra , Mazzoni Sandra , Khouri Jack , Williams Louis , Anwer Faiz , Raza Shahzad
Published: March 2024

Light chain amyloidosis is a plasma–cell disorder with a poor prognosis. It is a progressive condition, causing worsening pain, disability, and life-limiting complications involving multiple organ systems. The medical regimen can be complex, including chemotherapy or immunotherapy for the disease itself, as well as treatment for pain, gastrointestinal and cardiorespiratory symptoms, and various secondary symptoms. Patients and their families must have a realistic awareness of the illness and of the goals and limitations of treatments in making informed decisions about medical therapy, supportive management, and end-of-life planning. Palliative care services can thus improve patients’ quality of life and may even reduce overall treatment costs. Light chain (AL) amyloidosis is a clonal plasma cell disorder characterized by the excessive secretion of light chains by an indolent plasma cell clone that gradually accumulates in vital organs as amyloid fibrils and leads to end-organ damage. With progressive disease, most patients develop diverse clinical symptoms and complications that negatively impact quality of life and increase mortality. Complications include cardiac problems including heart failure, hypotension, pleural effusions, renal involvement including nephrotic syndrome with peripheral edema, gastrointestinal symptoms leading to anorexia and cachexia, complex pain syndromes, and mood disorders. The prognosis of patients with advanced AL amyloidosis is dismal. With such a complex presentation, and high morbidity and mortality rates, there is a critical need for the establishment of a palliative care program in clinical management. This paper provides an evidence-based overview of the integration of palliative care in the clinical management of AL amyloidosis as a means of reducing ER visits, rehospitalizations, and in-hospital mortality. We also discuss potential future collaborative directions in various aspects of clinical care related to AL amyloidosis.
Improving Patient Outcomes in Abdominal Surgery
Authors: Brusasco Claudia , Cucciolini Giada , Barberis Andrea , Introini Carlo , Campodonico Fabio , Corradi Francesco
Published: March 2024

Post-operative acute kidney injury (PO-AKI) is a frequent complication described in 15% of non-cardiac surgeries, 30% of cardiac surgeries, and 52% of patients requiring intensive post-operative care [...]
Myocardial Expression of Pluripotency, Longevity, and Proinflammatory Genes in the Context of Hypercholesterolemia and Statin Treatment
Authors: Mylonas Konstantinos S. , Peroulis Michail , Kapetanakis Emmanouil I. , Kapelouzou Alkistis
Published: March 2024

Background: This study sought to assess the effect of statin therapy on myocardial inflammation in a White New Zealand rabbit model of atherogenesis. Methods: The mRNA expression levels of pro-inflammatory, pluripotency, and aging-related markers were quantified following a controlled feeding protocol and statin treatments. Results: Following high-cholesterol diet induction, we observed significant upregulation in the myocardial mRNA levels of MYD88, NF-κB, chemokines (CCL4, CCL20, and CCR2), IFN-γ, interleukins (IL-1β, IL-2, IL-4, IL-8, IL-10, and IL-18), and novel markers (klotho, KFL4, NANOG, and HIF1α). In contrast, HOXA5 expression was diminished following a hyperlipidemic diet. Both statin treatments significantly influenced the markers studied. Nevertheless, rosuvastatin administration resulted in a greater reduction in MYD88, NF-kB, chemokines (CCL4, CCL20, and CCR2), and interleukins IL-1β, IL-8, KLF4, NANOG, and HIF1α than fluvastatin. Fluvastatin, on the other hand, led to a stronger decrease in IL-4. Downregulation of IL-2 and IL-18 and upregulation of IFNβ and HOXA5 were comparable between the two statins. Notably, rosuvastatin had a stronger effect on the upregulation of klotho and IL-10. Conclusion: Overall, statin therapy significantly attenuated inflammatory, pluripotency, and klotho expression in myocardial tissue under atherogenic conditions. Our findings also highlight the differential efficacy of rosuvastatin over fluvastatin in curtailing proatherogenic inflammation, which could have profound implications for the clinical management of cardiovascular disease.
Pulmonary Hypertension and the Risk of 30-Day Postoperative Pulmonary Complications after Gastrointestinal Surgical or Endoscopic Procedures: A Retrospective Propensity Score-Weighted Cohort Analysis
Authors: Tatsuoka Yoshio , Carr Zyad J. , Jayakumar Sachidhanand , Lin Hung-Mo , He Zili , Farroukh Adham , Heerdt Paul
Published: March 2024

Background: Pulmonary hypertension (PH) patients are at higher risk of postoperative complications. We analyzed the association of PH with 30-day postoperative pulmonary complications (PPCs). Methods: A single-center propensity score overlap weighting (OW) retrospective cohort study was conducted on 164 patients with a mean pulmonary artery pressure (mPAP) of >20 mmHg within 24 months of undergoing elective inpatient abdominal surgery or endoscopic procedures under general anesthesia and a control cohort (N = 1981). The primary outcome was PPCs, and the secondary outcomes were PPC sub-composites, namely respiratory failure (RF), pneumonia (PNA), aspiration pneumonia/pneumonitis (ASP), pulmonary embolism (PE), length of stay (LOS), and 30-day mortality. Results: PPCs were higher in the PH cohort (29.9% vs. 11.2%, p < 0.001). When sub-composites were analyzed, higher rates of RF (19.3% vs. 6.6%, p < 0.001) and PNA (11.2% vs. 5.7%, p = 0.01) were observed. After OW, PH was still associated with greater PPCs (RR 1.66, 95% CI (1.05–2.71), p = 0.036) and increased LOS (median 8.0 days vs. 4.9 days) but not 30-day mortality. Sub-cohort analysis showed no difference in PPCs between pre- and post-capillary PH patients. Conclusions: After covariate balancing, PH was associated with a higher risk for PPCs and prolonged LOS. This elevated PPC risk should be considered during preoperative risk assessment.
Pediatric Benign Paroxysmal Positional Vertigo: Degree of Nystagmus and Concurrent Dizziness Differs from Adult BPPV
Authors: An Jun Beom , Kim Jisu , Park Seok Hyun , Yoon Joonsung , Choo Oak Sung , Park Su-Kyoung , Chang Jiwon
Published: March 2024

Background: Benign paroxysmal positional vertigo (BPPV) is characterized by brief, intense episodes of vertigo triggered by abrupt changes in head position. It is generally accepted as being most common in adults, while it is regarded as rare in children. It is necessary to compare the disease between pediatric and adult patients for a better understanding of the disease’s characteristics and its natural history. This study aimed to identify the clinical characteristics of BPPV in children and compare them with those of adult BPPV patients. Methods: All children ≤ 18 years old who were diagnosed with BPPV were selected by searching the electronic database of our hospital. Clinical features were identified by medical record review. For adult patients, we collected data from patients > 19 years of age. Results: A total of 30 pediatric (13.65 ± 4.15 years old) and 264 adult patients (60.86 ± 13.74 years old) were included in the study. Among pediatric patients, the lateral canals were involved in 80% and the posterior canals in 16.67%. In adult patients, the lateral and posterior canals were involved similarly (p = 0.007). The degree of nystagmus in pediatric patients was 6.82 ± 12.09, while in adults it was 15.58 ± 20.90 (p < 0.001). The concurrent dizziness disorder was higher in the pediatric group and recurrence was higher in the adult group. In the regression analysis, it was found that adult patients had a stronger nystagmus with a value of 6.206 deg/sec, and the risk of concurrent dizziness disorder was found to be 5.413 times higher in the pediatric group (p < 0.05). Conclusions: BPPV occurs in pediatric patients with lower prevalence, but it cannot be overlooked. In the pediatric group, a relatively high proportion of patients demonstrated lateral canal involvement, weaker nystagmus, and additional dizziness disorder.
Sex Differences in Cognitive Reflection: A Meta-Analysis
Authors: Otero Inmaculada , Martínez Alexandra , Cuadrado Dámaris , Lado Mario , Moscoso Silvia , Salgado Jesús F.
Published: March 2024

The current study presents a meta-analytic review of the differences between men and women in cognitive reflection (CR). The study also explores whether the type of CR test (i.e., numerical tests and verbal tests) moderates the relationship between CR and sex. The results showed that men score higher than women on CR, although the magnitude of these differences was small. We also found out that the type of CR test moderates the sex differences in CR, especially in the numerical tests. In addition, the results showed that the length of numerical tests (i.e., number of items) does not affect the differences between men and women in CR. Finally, the implications of these results are discussed, and future research is suggested.
Psychometric Modeling to Identify Examinees’ Strategy Differences during Testing
Authors: Hauenstein Clifford E. , Embretson Susan E. , Kim Eunbee
Published: March 2024

Aptitude test scores are typically interpreted similarly for examinees with the same overall score. However, research has found evidence of examinee differences in strategies, as well as in the continued application of appropriate procedures during testing. Such differences can impact the correlates of test scores, making similar interpretations for equivalent scores questionable. This study presents some item response theory (IRT) models that are relevant to identifying examinee differences in strategies and understanding of test-taking procedures. First, mixture IRT models that identify latent classes of examinees with different patterns of item responses are considered; these models have long been available but unfortunately are not routinely applied. Strategy differences between the classes can then be studied separately by modeling the response patterns with cognitive complexity variables within each class. Secondly, novel psychometric approaches that leverage response time information (in particular, response time residuals) in order to identify both inter and intraindividual variability in response processes are considered. In doing so, a general method for evaluating threats to validity is proposed. The utility of the approach, in terms of providing more interpretable performance estimates and improving the administration of psychological measurement instruments, is then demonstrated with an empirical example.
Geochemical Factors as a Tool for Distinguishing Geogenic from Anthropogenic Sources of Potentially Toxic Elements in the Soil
Authors: Brenko Tomislav , Ružičić Stanko , Radonić Niko , Puljko Martina , Cvetković Marko
Published: March 2024

Potentially toxic element (PTE) contamination of soils and their sources remains one of key global environmental concerns. Agricultural soil in Kalinovac, Podravina region, Croatia is the subject of this study. The main aims include determining the concentration and distribution of PTEs in the soil, differentiation between possible geogenic and anthropogenic sources, and determining the correlation between the analysed PTEs and soil parameters. To achieve these objectives, geochemical analyses of the soil in the study area were carried out. Spatial distribution of the individual PTE contents, enrichment factors (EF), contamination factors (CF), and geoaccumulation index (Igeo) were created using GIS tools. In addition, statistical data processing was carried out, including the calculation of the correlation matrix, hierarchical cluster analysis (HCA), and factor analysis. The obtained results show that certain elements such as lead, chromium, copper, and cadmium were predominantly of anthropogenic origin in the study area, while others tended to have more geogenic origin. By applying different methods used in this study, it is possible to distinguish between geogenic and anthropogenic sources of PTEs in soils of this type.
From Galls to Cecidological Herbaria: The Role of Gall Collections in Modern Life Sciences
Authors: Mandrioli Mauro , Tonetti Luca , Beltrame Tiziana , Canadelli Elena
Published: March 2024

Galls (also known as cecidia) have been studied by botanists, zoologists and microbiologists over the last century. Indeed, galls can be induced by different animals, bacteria, viruses and fungi, so that their presence simultaneously attested the presence of specific host plants and gall-inducing species. Consequently, gall collections, also known as cecidological herbaria or cecidological collections, can be interesting to study biodiversity changes over time. This review describes the main cecidological collections currently available in different European museums in order to stimulate their future study. The present analysis suggests that well-organized and preserved cecidological collections have great potential to guide research in taxonomy and systematics. Furthermore, this review aims to encourage future research on the conservation and digitisation standards of gall specimens in order to make cecidological data more accessible to researchers.
Genetic Potential of Newly Developed Maize Hybrids under Different Water-Availability Conditions in an Arid Environment
Authors: Sedhom Youstina S. A. , Rabie Hassan A. , Awaad Hassan A. , Alomran Maryam M. , ALshamrani Salha M. , Mansour Elsayed , Ali Mohamed M. A.
Published: March 2024

Drought is a crucial environmental stress that tremendously impacts maize production, particularly under abrupt climate changes. Consequently, breeding drought-tolerant and high-yielding maize hybrids has become decisive in sustaining its production and ensuring global food security under the global fast-growing population. The present study aimed to explore drought tolerance and agronomic performance of newly developed maize inbred lines and their hybrids. Ten newly developed maize inbred lines were crossed with two high-yielding testers using a line × tester mating design. The developed twenty hybrids alongside two high-yielding commercial hybrids were evaluated under water-deficit (5411 m3/ha) and well-watered (7990 m3/ha) conditions in dry summer climate conditions. Highly significant variations were detected among the evaluated hybrids for all studied agronomic traits under well-watered and water-deficit conditions. The inbred lines L10 and L6 were particularly notable, demonstrating the most significant negative general combining ability (GCA) effects for earliness, which is crucial for stress avoidance in both environmental settings. Inbred lines L11, L7, L6, and L1 also showed the highest positive and most significant GCA effects for key yield traits, indicating their potential as parents in breeding programs. The crosses L-10×T-1 and L-6×T-2 were outstanding for their heterotic effects on earliness in days to tasseling and silking. Similarly, the crosses L-4×T-2 and L-1×T-1 excelled in plant and ear heights under both irrigation regimes. The hybrids L-1×T-2 and L-7×T-1 demonstrated superior heterosis for chlorophyll content, number of rows per ear, and overall grain yield. Additionally, hybrids L-11×T-1 and L-11×T-2 exhibited remarkable heterotic effects for the number of grains per row, number of rows per ear, 100-kernel weight, and grain yield, highlighting their potential in breeding for productivity. Based on drought tolerance indices and cluster analysis, the cross combinations L-11×T-1, L-11×T-2, L-7×T-1, and L-1×T-2 were classified as the most drought-tolerant crosses. The principal component analysis highlighted traits such as days to tasseling, days to silking, chlorophyll content, plant height, ear height, number of grains per row, number of rows per ear, and 100-kernel weight can be taken as selection criteria for improving grain yield in maize breeding programs under limited water conditions. Based on the summarized results, the identified genetic materials could be considered promising under both conditions and hold potential for future breeding programs.
Explainable Deep Learning: A Visual Analytics Approach with Transition Matrices
Authors: Radiuk Pavlo , Barmak Olexander , Manziuk Eduard , Krak Iurii
Published: March 2024

The non-transparency of artificial intelligence (AI) systems, particularly in deep learning (DL), poses significant challenges to their comprehensibility and trustworthiness. This study aims to enhance the explainability of DL models through visual analytics (VA) and human-in-the-loop (HITL) principles, making these systems more transparent and understandable to end users. In this work, we propose a novel approach that utilizes a transition matrix to interpret results from DL models through more comprehensible machine learning (ML) models. The methodology involves constructing a transition matrix between the feature spaces of DL and ML models as formal and mental models, respectively, improving the explainability for classification tasks. We validated our approach with computational experiments on the MNIST, FNC-1, and Iris datasets using a qualitative and quantitative comparison criterion, that is, how different the results obtained by our approach are from the ground truth of the training and testing samples. The proposed approach significantly enhanced model clarity and understanding in the MNIST dataset, with SSIM and PSNR values of 0.697 and 17.94, respectively, showcasing high-fidelity reconstructions. Moreover, achieving an F1m score of 77.76% and a weighted accuracy of 89.38%, our approach proved its effectiveness in stance detection with the FNC-1 dataset, complemented by its ability to explain key textual nuances. For the Iris dataset, the separating hyperplane constructed based on the proposed approach allowed for enhancing classification accuracy. Overall, using VA, HITL principles, and a transition matrix, our approach significantly improves the explainability of DL models without compromising their performance, marking a step forward in developing more transparent and trustworthy AI systems.
Microstructure and Wear Resistance of Grx-Ti-BN Composite Coating on TC4 by Argon Arc Cladding
Authors: Li Qindong , Meng Junsheng , Ding Hao , Hou Yilin , Li Sijie , Hao Chenfan , Shi Xiaoping
Published: March 2024

The TC4 (Ti-6Al-4V) alloy has problems such as low material hardness, poor wear resistance, and abnormal sensitivity to adhesive wear and fretting wear. In this study, we used graphene-reinforced Ti/BN composite coatings prepared on the surface of the TC4 alloy by argon arc cladding technology. We explored the optimal content of graphene to improve its hardness and wear resistance. The physical phases and microstructures of the coatings were analyzed using an X-ray diffractometer, metallurgical microscope, and scanning electron microscope. Microhardness and wear properties of the cladding coating were measured by a Vickers hardness tester and a universal friction and wear tester. The incorporation of graphene resulted in a transformation of the reinforcing phase in the coating from TiN to Ti(N, C). The C element in the molten pool was substituted with the N element in an unending solid solution, resulting in the formation of Ti(N, C) through intermittent nucleation. As the amount of graphene in the molten pool increases, the concentration of carbon (C) also increases. This leads to the continuous growth of Ti(N, C) particles, resulting in a coarser coating structure and a decrease in coating performance. When the graphene content is 5 wt.%, the microstructure refinement of the coating is the most obvious, the microhardness is 900 HV0.2, which is 3 times higher than that of the matrix, and the wear rate is 4.9 × 10−5 mm3/(N·m), which is 4.9 times higher than that of the matrix. The wear mechanism of the coating is primarily abrasive wear with some slight adhesive wear.
The Bacterial and Fungal Compositions in the Rhizosphere of Asarum heterotropoides Fr. Schmidt var. mandshuricum (Maxim.) Kitag. in a Typical Planting Region
Authors: Wang Fuqi , Zhao Zilu , Han Yangyang , Li Shiying , Bi Xinhua , Ren Shumeng , Pan Yingni , Wang Dongmei , Liu Xiaoqiu
Published: March 2024

Asarum is a traditional Chinese medicinal plant, and its dried roots are commonly used as medicinal materials. Research into the traits of the bacteria and fungus in the Asarum rhizosphere and how they relate to the potency of medicinal plants is important. During four cropping years and collecting months, we used ITS rRNA gene amplicon and sequencing to assess the population, diversity, and predominant kinds of bacteria and fungus in the rhizosphere of Asarum. HPLC was used to determine the three bioactive ingredients, namely asarinin, aristolochic acid I, and volatile oil. The mainly secondary metabolites of Asarum, relationships between microbial communities, soil physicochemical parameters, and possible influences on microbial communities owing to various cropping years and collecting months were all statistically examined. The cropping years and collecting months affected the abundance and diversity of rhizosphere bacteria and fungi, but the cropping year had a significant impact on the structures and compositions of the bacterial communities. The rhizosphere microorganisms were influenced by both the soil physicochemical properties and enzyme activities. Additionally, this study revealed that Trichoderma was positively correlated with the three bioactive ingredients of Asarum, while Tausonia showed entirely opposite results. Gibberella and Leptosphaeria demonstrated a significantly negative correlation with asarinin and violate oil, but they were weakly correlated with the aristolochic acid I content. This study revealed variations in the Asarum rhizosphere microorganism population, diversity, and dominant types across four cropping years and collecting months. The relationship between Asarum secondary metabolites, the soil physicochemical properties, enzyme activities, and rhizosphere microorganisms was discussed. Our results will guide the exploration of the soil characteristics and rhizosphere microorganisms’ structures by regulating the microbial community to enhance Asarum quality.
Correction: Nukulkit et al. Eight Indole Alkaloids from the Roots of Maerua siamensis and Their Nitric Oxide Inhibitory Effects. Molecules 2022, 27, 7558
Authors: Nukulkit Sasiwimon , Jantimaporn Angkana , Poldorn Preeyaporn , Khongkow Mattaka , Rungrotmongkol Thanyada , Chang Hsun-Shuo , Suttisri Rutt , Chansriniyom Chaisak
Published: March 2024

After a proofreading check, some experimental data were inconsistent with the supplementary information in the original publication [...]
Bioaccessibility of Phenolic Compounds, Resistant Starch, and Dietary Fibers from Australian Green Banana during In Vitro Digestion and Colonic Fermentation
Authors: Bashmil Yasmeen M. , Dunshea Frank R. , Appels Rudi , Suleria Hafiz A. R.
Published: March 2024

Green bananas contain a substantial amount of resistant starch (RS), dietary fiber (DF), and phytochemicals, which exhibit potent antioxidant capabilities, primarily attributable to the abundance of polyphenols. The objective of this study was to assess the variations in the contents and bioaccessibility of RS, DF, and phenolic compounds in three types of Australian green bananas (Cavendish “Musa acuminata”, Ladyfinger “Musa paradisiaca L.”, and Ducasse “Musa balbisiana”), along with their antioxidant capacities, and the production of short-chain fatty acids (SCFAs) following in vitro simulated gastrointestinal digestion and colonic fermentation. The studied cultivars exhibited significant levels of RS, with Ladyfinger showing the greatest (49%). However, Ducasse bananas had the greatest DF concentration (38.73%). Greater TPC levels for Ladyfinger (2.32 mg GAE/g), as well as TFC and TTC (0.06 mg QE/g and 3.2 mg CE/g, respectively) in Cavendish, together with strong antioxidant capacities (DPPH, 0.89 mg TE/g in Cavendish), have been detected after both intestinal phase and colonic fermentation at 12 and 24 h. The bioaccessibility of most phenolic compounds from bananas was high after gastric and small intestinal digestion. Nevertheless, a significant proportion of kaempferol (31% in Cavendish) remained detectable in the residue after colonic fermentation. The greatest production of SCFAs in all banana cultivars was observed after 24 h of fermentation, except valeric acid, which exhibited the greatest output after 12 h of fermentation. In conclusion, the consumption of whole green bananas may have an advantageous effect on bowel health and offer antioxidant characteristics.
Silencing RNA-Mediated Knockdown of IFITM3 Enhances Senecavirus A Replication
Authors: Aftab Shamiq , Nelson Eric , Hildreth Michael , Wang Xiuqing
Published: March 2024

Senecavirus A (SVA) is a non-enveloped, positive sense, single-stranded RNA virus that causes vesicular diseases in pigs. Interferon-induced transmembrane 3 (IFITM3) is an interferon-stimulated gene (ISG) that exhibits broad antiviral activity. We investigated the role of IFITM3 in SVA replication. Both viral protein expression and supernatant virus titer were significantly increased when endogenous IFITM3 was knocked down by approximately 80% in human non-smallcell lung carcinoma cell line (NCI-H1299) compared to silencing RNA control. Interestingly, overexpression of exogenous IFITM3 in NCI-H1299 cells also significantly enhanced viral protein expression and virus titer compared to vector control, which was positively correlated with induction of autophagy mediated by IFITM3 overexpression. Overall, our results indicate an antiviral role of endogenous IFITM3 against SVA. The exact molecular mechanisms by which endogenous IFITM3 limits SVA replication remain to be determined in future studies.
The Therapeutic Trip of Melatonin Eye Drops: From the Ocular Surface to the Retina
Authors: Rusciano Dario , Russo Cristina
Published: March 2024

Melatonin is a ubiquitous molecule found in living organisms, ranging from bacteria to plants and mammals. It possesses various properties, partly due to its robust antioxidant nature and partly owed to its specific interaction with melatonin receptors present in almost all tissues. Melatonin regulates different physiological functions and contributes to the homeostasis of the entire organism. In the human eye, a small amount of melatonin is also present, produced by cells in the anterior segment and the posterior pole, including the retina. In the eye, melatonin may provide antioxidant protection along with regulating physiological functions of ocular tissues, including intraocular pressure (IOP). Therefore, it is conceivable that the exogenous topical administration of sufficiently high amounts of melatonin to the eye could be beneficial in several instances: for the treatment of eye pathologies like glaucoma, due to the IOP-lowering and neuroprotection effects of melatonin; for the prevention of other dysfunctions, such as dry eye and refractive defects (cataract and myopia) mainly due to its antioxidant properties; for diabetic retinopathy due to its metabolic influence and neuroprotective effects; for macular degeneration due to the antioxidant and neuroprotective properties; and for uveitis, mostly owing to anti-inflammatory and immunomodulatory properties. This paper reviews the scientific evidence supporting the use of melatonin in different ocular districts. Moreover, it provides data suggesting that the topical administration of melatonin as eye drops is a real possibility, utilizing nanotechnological formulations that could improve its solubility and permeation through the eye. This way, its distribution and concentration in different ocular tissues may support its pleiotropic therapeutic effects.
Church Governance—A Philosophical Approach to a Theological Challenge in an Anglican Context
Authors: Richards Peter D. G.
Published: March 2024

Church governance is not often debated within a philosophical or theological sphere. This is perhaps because church governance has been part of tradition since Constantine and the initial Greek philosophical world view of sovereignty and hierarchy. Such a stance has led towards a managerial mindset that follows and conforms to the world, which plays out within the Anglican polity in the setting of an adversarial parliamentary style synod. This style encourages bounded communities of power that often refute the burgeoning inspirations of the Spirit. In changing the underlying theological basis of such a stance, by invoking the understanding of an undeniable community in the singularity of the Triune God, governance becomes more open. Engaging with, primarily, Agamben but also others from philosophy, a new viewpoint is presented to challenge the manner through which tradition is wielded as the only possibility. In seeing through a differing lens, communities can be conceived as both porous and interconnected, thus allowing the body of Christ to respond with transformative action as opposed to a continuum of conformance with secular legality. In this manner, the bishop’s role may become more centralised towards a Eucharistic one, as opposed to the managerial mindset and role, to enhance the possibilities of God’s love. This then removes the need for a hierarchy driven by a sovereign mindset that tradition bolsters, whilst maintaining loving and authoritative oversight that tradition suggests.
Automatic Martian Polar Ice Cap Extraction Algorithm for Remote Sensing Data and Analysis of Their Spatiotemporal Variation Characteristics
Authors: Xu Weiye , Chen Zhulin , Zhang Huifang , Jia Kun , Yangzom Degyi , Zhao Xiang , Yao Yunjun , Zhang Xiaotong
Published: March 2024

The detection of Martian polar ice cap change patterns is important for understanding their effects on driving Mars’s global water cycle and for regulating atmospheric circulation. However, current Martian ice cap identification using optical remote sensing data mainly relies on visual interpretation, which makes it difficult to quickly extract ice caps from multiple images and analyze their fine-scale spatiotemporal variation characteristics. Therefore, this study proposes an automatic Martian polar ice cap extraction algorithm for remote sensing data and analyzes the dynamic change characteristics of the Martian North Pole ice cap using time-series data. First, the automatic Martian ice cap segmentation algorithm was developed based on the ice cap features of high reflectance in the blue band and low saturation in the RGB band. Second, the Martian North Pole ice cap was extracted for the three Martian years MY25, 26, and 28 using Mars Orbiter Camera (MOC) Mars Daily Global Maps (MDGMs) data, which had better spatiotemporal continuity to analyze its variation characteristics. Lastly, the spatiotemporal variation characteristics of the ice cap and the driving factors of ice cap ablation were explored for the three aforementioned Martian years. The results indicated that the proposed automatic ice cap extraction algorithm had good performance, and the classification accuracy exceeded 93%. The ice cap ablation boundary retreat rates and spatiotemporal distributions were similar for the three years, with approximately 105 km2 of ice cap ablation for every one degree of areocentric longitude of the Sun (Ls). The main driving factor of ice cap ablation was solar radiation, which was mainly related to Ls. In addition, elevation had a different effect on ice cap ablation at different Ls in the same latitude area near the ablation boundary of the ice cap.
Weakly Supervised Object Detection for Remote Sensing Images via Progressive Image-Level and Instance-Level Feature Refinement
Authors: Zheng Shangdong , Wu Zebin , Xu Yang , Wei Zhihui
Published: March 2024

Weakly supervised object detection (WSOD) aims to predict a set of bounding boxes and corresponding category labels for instances with only image-level supervisions. Compared with fully supervised object detection, WSOD in remote sensing images (RSIs) is much more challenging due to the vast foreground-related context regions. In this paper, we propose a progressive image-level and instance-level feature refinement network to address the problems of missing detection and part domination for WSOD in RSIs. Firstly, we propose a multi-label attention mining loss (MAML)-guided image-level feature refinement branch to effectively allocate the computational resources towards the most informative part of images. With the supervision of MAML, all latent instances in images are emphasized. However, image-level feature refinement further expands responsive gaps between the informative part and other sub-optimal informative ones, which results in exacerbating the problem of part domination. In order to alleviate the above-mentioned limitation, we further construct an instance-level feature refinement branch to re-balance the contributions of different adjacent candidate bounding boxes according to the detection task. An instance selection loss (ISL) is proposed to progressively boost the representation of salient regions by exploring supervision from the network itself. Finally, we integrate the image-level and instance-level feature refinement branches into a complete network and the proposed MAML and ISL functions are merged with class classification and box regression to optimize the whole WSOD network in an end-to-end training fashion. We conduct experiments on two popular WSOD datasets, NWPU VHR-10.v2 and DIOR. All the experimental results demonstrate that our method achieves a competitive performance compared with other state-of-the-art approaches.
Prediction of Sea Surface Temperature Using U-Net Based Model
Authors: Ren Jing , Wang Changying , Sun Ling , Huang Baoxiang , Zhang Deyu , Mu Jiadong , Wu Jianqiang
Published: March 2024

Sea surface temperature (SST) is a key parameter in ocean hydrology. Currently, existing SST prediction methods fail to fully utilize the potential spatial correlation between variables. To address this challenge, we propose a spatiotenporal UNet (ST-UNet) model based on the UNet model. In particular, in the encoding phase of ST-UNet, we use parallel convolution with different kernel sizes to efficiently extract spatial features, and use ConvLSTM to capture temporal features based on the utilization of spatial features. Atrous Spatial Pyramid Pooling (ASPP) module is placed at the bottleneck of the network to further incorporate the multi-scale features, allowing the spatial features to be fully utilized. The final prediction is then generated in the decoding stage using parallel convolution with different kernel sizes similar to the encoding stage. We conducted a series of experiments on the Bohai Sea and Yellow Sea SST data set, as well as the South China Sea SST data set, using SST data from the past 35 days to predict SST data for 1, 3, and 7 days in the future. The model was trained using data spanning from 2010 to 2021, with data from 2022 being utilized to assess the model’s predictive performance. The experimental results show that the model proposed in this research paper achieves excellent results at different prediction scales in both sea areas, and the model consistently outperforms other methods. Specifically, in the Bohai Sea and Yellow Sea sea areas, when the prediction scales are 1, 3, and 7 days, the MAE of ST-UNet outperforms the best results of the other three compared models by 17%, 12%, and 2%, and the MSE by 16%, 18%, and 9%, respectively. In the South China Sea, when the prediction ranges are 1, 3, and 7 days, the MAE of ST-UNet is 27%, 18%, and 3% higher than the best of the other three compared models, and the MSE is 46%, 39%, and 16% higher, respectively. Our results highlight the effectiveness of the ST-UNet model in capturing spatial correlations and accurately predicting SST. The proposed model is expected to improve marine hydrographic studies.
Parameterization of Biomechanical Variables through Inertial Measurement Units (IMUs) in Occasional Healthy Runners
Authors: Pareja-Cano Álvaro , Arjona José María , Caulfield Brian , Cuesta-Vargas Antonio
Published: March 2024

Running is one of the most popular sports practiced today and biomechanical variables are fundamental to understanding it. The main objectives of this study are to describe kinetic, kinematic, and spatiotemporal variables measured using four inertial measurement units (IMUs) in runners during treadmill running, investigate the relationships between these variables, and describe differences associated with different data sampling and averaging strategies. A total of 22 healthy recreational runners (M age = 28 ± 5.57 yrs) participated in treadmill measurements, running at their preferred speed (M = 10.1 ± 1.9 km/h) with a set-up of four IMUs placed on tibias and the lumbar area. Raw data was processed and analysed over selections spanning 30 s, 30 steps and 1 step. Very strong positive associations were obtained between the same family variables in all selections. The temporal variables were inversely associated with the step rate variable in the selection of 30 s and 30 steps of data. There were moderate associations between kinetic (forces) and kinematic (displacement) variables. There were no significant differences between the biomechanics variables in any selection. Our results suggest that a 4-IMU set-up, as presented in this study, is a viable approach for parameterization of the biomechanical variables in running, and also that there are no significant differences in the biomechanical variables studied independently, if we select data from 30 s, 30 steps or 1 step for processing and analysis. These results can assist in the methodological aspects of protocol design in future running research.
Research on the Vision-Based Dairy Cow Ear Tag Recognition Method
Authors: Gao Tianhong , Fan Daoerji , Wu Huijuan , Chen Xiangzhong , Song Shihao , Sun Yuxin , Tian Jia
Published: March 2024

With the increase in the scale of breeding at modern pastures, the management of dairy cows has become much more challenging, and individual recognition is the key to the implementation of precision farming. Based on the need for low-cost and accurate herd management and for non-stressful and non-invasive individual recognition, we propose a vision-based automatic recognition method for dairy cow ear tags. Firstly, for the detection of cow ear tags, the lightweight Small-YOLOV5s is proposed, and then a differentiable binarization network (DBNet) combined with a convolutional recurrent neural network (CRNN) is used to achieve the recognition of the numbers on ear tags. The experimental results demonstrated notable improvements: Compared to those of YOLOV5s, Small-YOLOV5s enhanced recall by 1.5%, increased the mean average precision by 0.9%, reduced the number of model parameters by 5,447,802, and enhanced the average prediction speed for a single image by 0.5 ms. The final accuracy of the ear tag number recognition was an impressive 92.1%. Moreover, this study introduces two standardized experimental datasets specifically designed for the ear tag detection and recognition of dairy cows. These datasets will be made freely available to researchers in the global dairy cattle community with the intention of fostering intelligent advancements in the breeding industry.
Decentralised Global Service Discovery for the Internet of Things
Authors: Kurte Ryan , Salcic Zoran , Wang Kevin I-Kai
Published: March 2024

The Internet of Things (IoT) consists of millions of devices deployed over hundreds of thousands of different networks, providing an ever-expanding resource to improve our understanding of and interactions with the physical world. Global service discovery is key to realizing the opportunities of the IoT, spanning disparate networks and technologies to enable the sharing, discovery, and utilisation of services and data outside of the context in which they are deployed. In this paper, we present Decentralised Service Registries (DSRs), a novel trustworthy decentralised approach to global IoT service discovery and interaction, building on DSF-IoT to allow users to simply create and share public and private service registries, to register and query for relevant services, and to access both current and historical data published by the services they discover. In DSR, services are registered and discovered using signed objects that are cryptographically associated with the registry service, linked into a signature chain, and stored and queried for using a novel verifiable DHT overlay. In contrast to existing centralised and decentralised approaches, DSRs decouple registries from supporting infrastructure, provide privacy and multi-tenancy, and support the verification of registry entries and history, service information, and published data to mitigate risks of service impersonation or the alteration of data. This decentralised approach is demonstrated through the creation and use of a DSR to register and search for real-world IoT devices and their data as well as qualified using a scalable cluster-based testbench for the high-fidelity emulation of peer-to-peer applications. DSRs are evaluated against existing approaches, demonstrating the novelty and utility of DSR to address key IoT challenges and enable the sharing, discovery, and use of IoT services.
A Systematic Review on Privacy-Aware IoT Personal Data Stores
Authors: Pinto George P. , Donta Praveen Kumar , Dustdar Schahram , Prazeres Cássio
Published: March 2024

Data from the Internet of Things (IoT) enables the design of new business models and services that improve user experience and satisfaction. These data serve as important information sources for many domains, including disaster management, biosurveillance, smart cities, and smart health, among others. However, this scenario involves the collection of personal data, raising new challenges related to data privacy protection. Therefore, we aim to provide state-of-the-art information regarding privacy issues in the context of IoT, with a particular focus on findings that utilize the Personal Data Store (PDS) as a viable solution for these concerns. To achieve this, we conduct a systematic mapping review to identify, evaluate, and interpret the relevant literature on privacy issues and PDS-based solutions in the IoT context. Our analysis is guided by three well-defined research questions, and we systematically selected 49 studies published until 2023 from an initial pool of 176 papers. We analyze and discuss the most common privacy issues highlighted by the authors and position the role of PDS technologies as a solution to privacy issues in the IoT context. As a result, our findings reveal that only a small number of works (approximately 20%) were dedicated to presenting solutions for privacy issues. Most works (almost 82%) were published between 2018 and 2023, demonstrating an increased interest in the theme in recent years. Additionally, only two works used PDS-based solutions to deal with privacy issues in the IoT context.
The Use of Virtual Tissue Constructs That Include Morphological Variability to Assess the Potential of Electrical Impedance Spectroscopy to Differentiate between Thyroid and Parathyroid Tissues during Surgery
Authors: Matella Malwina , Hunter Keith , Balasubramanian Saba , Walker Dawn
Published: March 2024

Electrical impedance spectroscopy (EIS) has been proposed as a promising noninvasive method to differentiate healthy thyroid from parathyroid tissues during thyroidectomy. However, previously reported similarities in the in vivo measured spectra of these tissues during a pilot study suggest that this separation may not be straightforward. We utilise computational modelling as a method to elucidate the distinguishing characteristics in the EIS signal and explore the features of the tissue that contribute to the observed electrical behaviour. Firstly, multiscale finite element models (or ‘virtual tissue constructs’) of thyroid and parathyroid tissues were developed and verified against in vivo tissue measurements. A global sensitivity analysis was performed to investigate the impact of physiological micro-, meso- and macroscale tissue morphological features of both tissue types on the computed macroscale EIS spectra and explore the separability of the two tissue types. Our results suggest that the presence of a surface fascia layer could obstruct tissue differentiation, but an analysis of the separability of simulated spectra without the surface fascia layer suggests that differentiation of the two tissue types should be possible if this layer is completely removed by the surgeon. Comprehensive in vivo measurements are required to fully determine the potential for EIS as a method in distinguishing between thyroid and parathyroid tissues.