bluuebunny/crossref_metadata_2025 huggingface dataset:
The Eye as the Window to the Heart: Optical Coherence Tomography Angiography Biomarkers as Indicators of Cardiovascular Disease
Authors: Kellner Rebecca L. , Harris Alon , Ciulla Lauren , Guidoboni Giovanna , Verticchio Vercellin Alice , Oddone Francesco , Carnevale Carmela , Zaid Mohamed , Antman Gal , Kuvin Jeffrey T. , Siesky Brent
Published: January 2024

Alterations in microvasculature represent some of the earliest pathological processes across a wide variety of human diseases. In many organs, however, inaccessibility and difficulty in directly imaging tissues prevent the assessment of microvascular changes, thereby significantly limiting their translation into improved patient care. The eye provides a unique solution by allowing for the non-invasive and direct visualization and quantification of many aspects of the human microvasculature, including biomarkers for structure, function, hemodynamics, and metabolism. Optical coherence tomography angiography (OCTA) studies have specifically identified reduced capillary densities at the level of the retina in several eye diseases including glaucoma. This narrative review examines the published data related to OCTA-assessed microvasculature biomarkers and major systemic cardiovascular disease. While loss of capillaries is being established in various ocular disease, pilot data suggest that changes in the retinal microvasculature, especially within the macula, may also reflect small vessel damage occurring in other organs resulting from cardiovascular disease. Current evidence suggests retinal microvascular biomarkers as potential indicators of major systemic cardiovascular diseases, including systemic arterial hypertension, atherosclerotic disease, and congestive heart failure.
Recurrence following Resection of Intraductal Papillary Mucinous Neoplasms: A Systematic Review to Guide Surveillance
Authors: Salahuddin Aneesa , Thayaparan Varna , Hamad Ahmad , Tarver Willi , Cloyd Jordan M. , Kim Alex C. , Gebhard Robyn , Pawlik Timothy M. , Reames Bradley N. , Ejaz Aslam
Published: January 2024

Patients who undergo resection for non-invasive IPMN are at risk for long-term recurrence. Further evidence is needed to identify evidence-based surveillance strategies based on the risk of recurrence. We performed a systematic review of the current literature regarding recurrence patterns following resection of non-invasive IPMN to summarize evidence-based recommendations for surveillance. Among the 61 studies reviewed, a total of 8779 patients underwent resection for non-invasive IPMN. The pooled overall median follow-up time was 49.5 months (IQR: 38.5–57.7) and ranged between 14.1 months and 114 months. The overall median recurrence rate for patients with resected non-invasive IPMN was 8.8% (IQR: 5.0, 15.6) and ranged from 0% to 27.6%. Among the 33 studies reporting the time to recurrence, the overall median time to recurrence was 24 months (IQR: 17, 46). Existing literature on recurrence rates and post-resection surveillance strategies for patients with resected non-invasive IPMN varies greatly. Patients with resected non-invasive IPMN appear to be at risk for long-term recurrence and should undergo routine surveillance.
Multi-Particle Tracking in Complex Plasmas Using a Simplified and Compact U-Net
Authors: Dormagen Niklas , Klein Max , Schmitz Andreas S. , Thoma Markus H. , Schwarz Mike
Published: January 2024

Detecting micron-sized particles is an essential task for the analysis of complex plasmas because a large part of the analysis is based on the initially detected positions of the particles. Accordingly, high accuracy in particle detection is desirable. Previous studies have shown that machine learning algorithms have made great progress and outperformed classical approaches. This work presents an approach for tracking micron-sized particles in a dense cloud of particles in a dusty plasma at Plasmakristall-Experiment 4 using a U-Net. The U-net is a convolutional network architecture for the fast and precise segmentation of images that was developed at the Computer Science Department of the University of Freiburg. The U-Net architecture, with its intricate design and skip connections, has been a powerhouse in achieving precise object delineation. However, as experiments are to be conducted in resource-constrained environments, such as parabolic flights, preferably with real-time applications, there is growing interest in exploring less complex U-net architectures that balance efficiency and effectiveness. We compare the full-size neural network, three optimized neural networks, the well-known StarDist and trackpy, in terms of accuracy in artificial data analysis. Finally, we determine which of the compact U-net architectures provides the best balance between efficiency and effectiveness. We also apply the full-size neural network and the the most effective compact network to the data of the PK-4 experiment. The experimental data were generated under laboratory conditions.
A Report on the Artificial Reef Use in Grenada, West Indies
Authors: LeFebre Brianna , Saye Phil , Henkel James S.
Published: January 2024

Coral reef rehabilitation in the Caribbean is of major ecological and economic importance in the West Indies. Local organizations in Grenada constructed a cement pyramid artificial reef structure with rugosity (termed “The Pyramid”) and placed a number of these artificial reefs in a shallow marine area fringing two major natural reefs in the southwest coastal region of Grenada. Benthic data for two nearby natural reefs were compared to the benthic evaluation of the artificial reef pyramids. This comparison demonstrated that the artificial reef pyramids were similar in many respects to the natural reefs but were significantly different in macro- and coralline algae cover, two key indicators of reef health. This report is the first benthic evaluation of an artificial reef through comparison to natural reefs in Grenada.
Chronology and Sedimentary Processes in the Western Ross Sea, Antarctica since the Last Glacial Period
Authors: Liu Geng , Shen Zhongshan , Han Xibin , Wang Haifeng , Chen Weiwei , Zhang Yi , Ma Pengyun , Li Yibing , Cai Yun , Xue Pengfei , Qin Huafeng , Zhang Chunxia
Published: January 2024

The stability of contemporary ice shelves is under threat due to global warming, and the geological records in the Ross Sea offer such an opportunity to test the linkage between them. However, the absence of calcareous microfossils in the sediments of the Ross Sea results in uncertainties in establishing a precise chronology for studies. Hence, three sediment cores were collected and studied in terms of radiocarbon dating, magnetic susceptibility, and sediment grain size to reconstruct the environmental processes in the Ross Sea since the last glacial period. The main results are as follows: (1) two grain-size components were identified for the studied cores, which can be correlated to ice-shelf and sea-ice transport, respectively; (2) due to old-carbon contamination and an inconsistent carbon reservoir, the radiocarbon dates were generally underestimated, and as an alternative, changes in magnetic susceptibility of the studied cores can be tuned to the ice-core records to establish a reliable age–depth model and; (3) integrating sediment grain-size changes and comparisons with other paleoenvironmental proxies in the Antarctic, a process from a sub-ice sheet in the last glacial period to a sub-ice shelf in the glacial maximum, and, finally, to a glaciomarine state since the last deglacial period was identified in the western Ross Sea. Integrating these findings, the warming processes in the Antarctic were highlighted in the retreat processes of the Ross Ice Shelf in the past.
Distribution and Environmental Impact of Expanded Polystyrene Buoys from Korean Aquaculture Farms
Authors: Seo Seongbong , Park Young-Gyu
Published: January 2024

Expanded polystyrene (EPS) buoys, commonly employed in South Korean aquaculture farms, are prone to fragmentation, generating substantial marine debris. The trajectories of EPS buoys dislocated from aquaculture farms were investigated using a Lagrangian particle-tracking model. Daily ocean current data from the 1/12° Hybrid Coordinate Ocean Model analysis and wind data from the 1/4° European Center for Medium-Range Weather Forecasts reanalysis were used as inputs. The particles were released daily, and the initial positions and number of particles were determined based on the usage of EPS buoys. Because EPS buoys are highly buoyant, both wind and ocean currents considerably influence their movement. To account for variations in the buoyancy of these buoys, three experiments were conducted, each considering different levels of windage. The simulation results closely aligned with the observed coastal distribution patterns of the large EPS debris. As the windage increases, the particles exhibit a swifter deviation from their original locations, highlighting the need for effective local management. Moreover, this increased windage affects the distribution patterns in regional seas, reducing the number of particles that flow into the East Sea, while increasing the number of particles that migrate into the Yellow Sea and East China Sea.
Monitoring the Extraordinary Ephemeral Emergence of Myriophyllum spicatum L. in the Coastal Lagoon Albufera of Valencia (Spain) and Assessing the Impact of Environmental Variables Using a Remote Sensing Approach
Authors: Soria Juan M. , Molner Juan Víctor , Pérez-González Rebeca , Alvado Bárbara , Vera-Herrera Lucía , Romo Susana
Published: January 2024

The Albufera of Valencia, a Mediterranean coastal lagoon, has been in a turbid state since 1974, with only four episodes of temporary water transparency in spring. Despite its average depth of 1 m and oligohaline waters, excessive turbidity, fish grazing, and toxic compounds have inhibited submerged macrophyte growth. In spring 2018, a significant area of Myriophyllum spicatum emerged and exhibited significant density until its complete disappearance in August 2018. Using Sentinel-2 and Landsat-8 imagery, we monitored water quality variables and vegetation density during these months. Our study revealed the first unique occurrence of M. spicatum in more than 40 years. A period of increased transparency from summer 2017 compared to previous years seems to be the cause of this appearance, while high summer temperatures caused its disappearance. While improving water quality may help restore submerged macrophyte meadows, our results suggest that summer maximum temperatures may inhibit recovery. Remote sensing, particularly the NDVI index, proved successful in monitoring aquatic vegetation and understanding species-environment relationships. This methodology can enhance future monitoring efforts for macrophyte colonization and expand knowledge of their occurrence and causes of disappearance in this and other similar areas.
Systems Metabolic Engineering of Saccharomyces cerevisiae for the High-Level Production of (2S)-Eriodictyol
Authors: Zhang Siqi , Liu Juan , Xiao Zhiqiang , Tan Xinjia , Wang Yongtong , Zhao Yifei , Jiang Ning , Shan Yang
Published: January 2024

(2S)-eriodictyol (ERD) is a flavonoid widely found in citrus fruits, vegetables, and important medicinal plants with neuroprotective, cardioprotective, antidiabetic, and anti-obesity effects. However, the microbial synthesis of ERD is limited by complex metabolic pathways and often results in a low production performance. Here, we engineered Saccharomyces cerevisiae by fine-tuning the metabolism of the ERD synthesis pathway. The results showed that the ERD titer was effectively increased, and the intermediate metabolites levels were reduced. First, we successfully reconstructed the de novo synthesis pathway of p-coumaric acid in S. cerevisiae and fine-tuned the metabolic pathway using promoter engineering and terminator engineering for the high-level production of (2S)-naringenin. Subsequently, the synthesis of ERD was achieved by introducing the ThF3′H gene from Tricyrtis hirta. Finally, by multiplying the copy number of the ThF3′H gene, the production of ERD was further increased, reaching 132.08 mg L−1. Our work emphasizes the importance of regulating the metabolic balance to produce natural products in microbial cell factories.
Laboratory Diagnostics Accuracy for COVID-19 versus Post-COVID-19 Syndrome in Lung Disease Patients with Multimorbidity
Authors: Robu Popa Daniela , Melinte Oana Elena , Dobrin Mona-Elisabeta , Cernomaz Andrei Tudor , Grigorescu Cristina , Nemes Alexandra Floriana , Todea Doina Adina , Vulturar Damiana Maria , Grosu-Creangă Ionela Alina , Lunguleac Tiberiu , Trofor Antigona Carmen
Published: January 2024

The laboratory tests and identification of risk factors such as comorbidities are essential in the management, treatment and prognosis of patients with chronic respiratory diseases. Performing rigorous monitoring among patients with post-COVID-19 syndrome and early identification of risk factors associated with poor prognosis are crucial in improving patient outcomes. In the present study, 182 patients diagnosed with COVID-19 and PCI during 2020–2022 were included. A clinical and epidemiological evaluation was performed for each patient. Laboratory tests at admission included complete blood count, Erythrocyte Sedimentation Rate (ESR) and biochemical tests. Receiver operating curve (ROC) and area under the curve (AUC) were calculated to compare the diagnostic performance of each parameter. Regarding comorbidities, arterial hypertension, diabetes mellitus and obesity were the most frequent ones. In the case of chronic lung diseases, asthma and Chronic Obstructive Pulmonary Disease (COPD) were the most frequent. Pleurisy was found especially in patients with PCI Variations in serum LDH values were observed, especially in severe forms of COVID-19 in 2020, with a mean value of 481.44 U/L, compared to patients with PCI, whose mean values (122 U/L) were within the biological range of reference. High neutrophil/lymphocyte ratio (NLR) values quantified in this study were especially associated with moderate and severe forms of COVID-19 and also PCI. The Spearman correlation coefficient was determined to measure the correlations between the clinical parameters of all investigated subjects. A value of p < 0.05 was considered statistically significant. The statistical results indicated that serum lactate dehydrogenase (LDH), glucose and C-reactive protein (CRP) are sensitive markers with a diagnostic role in COVID-19, and lymphocyte (Ly) count, CRP, ESR and glucose were evidenced to be target markers in PCI. LDH values were observed to be statistically significant (p < 0.005) in patients with COVID-19 and obesity evaluated in 2021, while Ly count was statistically significant (p = 0.05) in patients with PCI and arterial hypertension. Regarding comorbidities, it has been observed that obesity, arterial hypertension and cardiovascular diseases represent risk factors in COVID-19/PCI, associated especially with the severe forms of the disease.
Developing a Model for Quantifying QTc-Prolongation Risk to Enhance Medication Safety Assessment: A Retrospective Analysis
Authors: Giovannoni Luis , Kullak-Ublick Gerd A. , Jetter Alexander
Published: January 2024

There are currently no established methods to predict quantitatively whether the start of a drug with the potential to prolong the QTc interval poses patients at risk for relevant QTc prolongation. Therefore, this retrospective study aimed to pave the way for the development of models for estimating QTc prolongation in patients newly exposed to medications with QTc-prolonging potential. Data of patients with a documented QTc prolongation after initiation of a QTc-prolonging drug were extracted from hospital charts. Using a standard model-building approach, general linear mixed models were identified as the best models for predicting both the extent of QTc prolongation and its absolute value after the start of a QTc-time-prolonging drug. The cohort consisted of 107 adults with a mean age of 64.2 years. Patients were taking an average of 2.4 drugs associated with QTc prolongation, with amiodarone, propofol, pipamperone, ondansetron, and mirtazapine being the most frequently involved. There was a significant but weak correlation between measured and predicted absolute QTc values under medication (r2 = 0.262, p < 0.05), as well as for QTc prolongation (r2 = 0.238, p < 0.05). As the developed models are based on a relatively small number of subjects, further research is necessary to ensure their applicability and reliability in real-world scenarios. Overall, this research contributes to the understanding of QTc prolongation and its association with medications, providing insight into the development of predictive models. With improvements, these models could potentially aid healthcare professionals in assessing the risk of QTc prolongation before adding a new drug and in making informed decisions in clinical settings.
The Spatial–Temporal Characteristics of Land De-Urbanization in Metropolises: A Case Study of the Guangdong–Hong Kong–Macao Greater Bay Area
Authors: Chen Xiaochun , Zhou Yongni , Zhao Hanbing , Zhou Jinhao , Liu Yilun
Published: January 2024

With a series of redevelopment activities, such as land consolidation and urban renewal, many cities in China have experienced land de-urbanization phenomena. These include the conversion of construction land into green spaces (such as parks, forests, and lawns), blue spaces (such as rivers, lakes, and wetlands), and farmland. However, there is currently limited research on diverse land de-urbanization types and pathways. This study focuses on investigating the land de-urbanization in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) from 2014 to September 2023 using the Continuous Change Detection and Classification (CCDC) method. The results demonstrate that the GBA experienced 72.74 square kilometers of de-urbanization during the study period, primarily through the conversion of construction land to land with low plant coverage, including grassland and farmland. There were significant differences in the quantity and spatial agglomeration of de-urbanization between cities and within individual cities. Temporally, de-urbanization predominantly occurred in the period of 2016 to 2021, with a sharp decline in 2022. The temporal changes were significantly influenced by urban renewal policies and the impact of the COVID-19 pandemic. In terms of spatial clustering characteristics, the de-urbanization process in the GBA exhibited spatial agglomeration but was primarily characterized by low-level clustering. This study also examines the correlations between de-urbanization and factors including location and the stage of urbanization. The analysis showed that de-urbanization within cities tended to concentrate near the main urban roads within a range of 10–30 km from city centers. The trend of de-urbanization followed a pattern that is consistent with the Northam curve, where de-urbanization tends to increase during the rapid urbanization phase and decline as urbanization reaches a mature stage. Overall, this study provides valuable insights for the redevelopment of construction land within the context of ecological civilization construction. It also offers suggestions for urban land development and redevelopment in metropolitan areas.
Integrating Landscape Character Assessment with Community Values in a Scenic Evaluation Methodology for Regional Landscape Planning
Authors: Tara Ata , Lawson Gillian , Davies Wendy , Chenoweth Alan , Pratten Georgina
Published: January 2024

The Landscape Character Assessment (LCA) method from the UK has proven effective in identifying landscape values and characteristics through a comprehensive mapping process. However, it is predominantly expert-led and lacks an evaluation of scenery, hindering the inclusion of the broader community’s preferences and visual attachment to their landscape. In Australia, the application of the Scenic Amenity Methodology (SAM) using Geographical Information System (GIS) mapping has engaged communities but has often overlooked the importance of landscape character. To overcome these limitations, this study presents an innovative scenic assessment methodology, referred to as modified Scenic Amenity Methodology (modified SAM). The methodology establishes landscape character types (LCTs) to map scenic preference ratings derived from community photo surveys. Simultaneously, it incorporates the visual exposure of the landscape from publicly accessible viewpoints, modelled using a Digital Elevation Model (DEM). The combination of scenic preferences and visual exposure enables mapping of the scenic amenity values held by the community. This methodology was first trialled in Bundaberg, then Cairns, the Whitsunday Islands, and, most recently, Toowoomba in Queensland, Australia. This paper presents the results of the Toowoomba study and reports on the challenges and limitations of informing landscape character type (LCT) values through a public photo survey, developing a scenic preference map from ratings of photos across a region, a map of the visual exposure of landscape elements from key public viewing locations, and, ultimately, a map of scenic amenity values across the Toowoomba Region. It indicates that integrating previous LCA approaches with public participation through community preferences is indeed feasible for regional landscape planning.
Enhancing Sustainability and Yield in Maritime Pine Forests: Evaluating Silvicultural Models for Natural Regeneration
Authors: Sandim André , Silva Maria Emília , Fernandes Paulo , Fonseca Teresa
Published: January 2024

The maritime pine (Pinus pinaster Ait.) forest is an essential element of the Portuguese forest landscape due to its social, economic, and environmental importance. The sustainability of these forests in the Mediterranean region faces challenges due to recurrent forest fires and the absence of or delayed management. The species has a high capacity for regeneration, but the perpetuation of pine forests in sustainable conditions depends on adequate management to achieve high biomass production and assure fire resilience. This study aimed to analyse four management scenarios (C1 to C4) for the natural regeneration of maritime pine in six areas with stand ages ranging from 6 to 16 years and densities varying from 15,000 to circa 93,000 trees per ha. The same four scenarios were implemented in each of the six areas. The scenarios considered the evolution of forest growth according to different management prescriptions and were simulated using Modispinaster and PiroPinus models. Scenario C1 considered no intervention, with only the final cut. Scenario C2 considered a thinning schedule to maintain the stand within the 50–60% range of the Stand Density Index (SDI). Scenario C3 followed the area’s Forest Management Plan (PGF), which typically includes two or three thinning operations throughout the cycle. Scenario C4 was adapted from the MS1 silvicultural model of the National Institute for Nature Conservation and Forests—ICNF, which involves opening strips at earlier ages (3 and 6 years), with the selection of trees to remain in the wooded area carried out between 4 and 10 years of age and performing thinning whenever the Wilson Spacing Factor (FW) reaches 0.21. The final cutting age was assumed to be 45 years but could be lowered to 35 years in Scenario 3 if defined in the plan. Based on the indicators generated by the simulators, the results showed variations in the total volume of timber produced at the time of harvest depending on the silvicultural guidelines. Scenario C4 was the most effective in generating the highest individual tree volume at the end of the cycle and the total volume of timber collected throughout the cycle. The ability of the forest to resist fire was evaluated before and after the first treatment for density reduction. The treatments performed did not decrease the resistance to fire control.
Acute Myocardial Infarction during the COVID-19 Pandemic: Long-Term Outcomes and Prognosis—A Systematic Review
Authors: Rus Marius , Ardelean Adriana Ioana , Andronie-Cioara Felicia Liana , Filimon Georgiana Carmen
Published: January 2024

Coronavirus disease 2019 (COVID-19) was a global pandemic with high mortality and morbidity that led to an increased health burden all over the world. Although the virus mostly affects the pulmonary tract, cardiovascular implications are often observed among COVID-19 patients and are predictive of poor outcomes. Increased values of myocardial biomarkers such as troponin I or NT-proBNP were proven to be risk factors for respiratory failure. Although the risk of acute coronary syndromes (ACSs) was greater in the acute phase of COVID-19, there were lower rates of hospitalization for ACSs, due to patients’ hesitation in presenting at the hospital. Hospitalized ACSs patients with COVID-19 infection had a prolonged symptom-to-first-medical-contact time, and longer door-to-balloon time. The mechanisms of myocardial injury in COVID-19 patients are still not entirely clear; however, the most frequently implicated factors include the downregulation of ACE2 receptors, endothelial dysfunction, pro-coagulant status, and increased levels of pro-inflammatory cytokines. The aim of this paper is to evaluate the long-term outcomes and prognosis of COVID-19 survivors that presented an acute myocardial infarction, by reviewing existing data. The importance of the association between this infectious disease and myocardial infarction arises from the increased mortality of patients with SARS-CoV-2 infection and AMI (10–76%, compared with 4.6% for NSTEMI patients and 7% for STEMI patients without COVID-19). The literature review showed an increased risk of cardiovascular events in COVID-19 survivors compared with the general population, even after the acute phase of the disease, with poorer long-term outcomes.
Factors Related to Bacillus thuringiensis and Gut Physiology. Comment on Rajan, V. An Alkaline Foregut Protects Herbivores from Latex in Forage, but Increases Their Susceptibility to Bt Endotoxin. Life 2023, 13, 2195
Authors: Berry Colin
Published: January 2024

A recent article has proposed that alkaline guts may lead to a general susceptibility to the biological control agent Bacillus thuringiensis and the pesticidal proteins derived from it. An analysis of the literature presented here clarifies our knowledge on the activity and safety of these agents, indicating that alkaline guts are not determinant of sensitivity and that the generalized conclusions proposed in the previous article cannot be substantiated.
Reply to Berry, C. Factors Related to Bacillus thuringiensis and Gut Physiology. Comment on “Rajan, V. An Alkaline Foregut Protects Herbivores from Latex in Forage, but Increases Their Susceptibility to Bt Endotoxin. Life 2023, 13, 2195”
Authors: Rajan Vidya
Published: January 2024

The comment titled “Factors related to Bacillus thuringiensis and gut physiology” disputes some of the inferences in the paper “An Alkaline Foregut Protects Herbivores from Latex in Forage, but Increases Their Susceptibility to Bt Endotoxin” published in this journal. The key points in the dissent are the following: 1. Bt is generally safe to non-target species. 2. Transgenic Bt crops provide additional ecological benefits due to reductions in conventional pesticide use. 3. Susceptibility to Bt does not indicate alkalinity, nor vice versa. My response is summarized as follows: 1. Bt can form non-specific pores at concentrations of 100 ng/mL in culture, and so is potentially unsafe for animals with gut environments in which Bt persists at or above this level. 2. Initial reductions in insecticide applications have not been sustained and are even increasing in areas planted with transgenic Bt cotton. 3. Acidic guts degrade Bt more efficiently, but I concede that gut alkalinity does not imply susceptibility to Bt due to many factors including resistance in target species, toxin heterogeneity and variable modes of action. However, the susceptibility of foregut-fermenting herbivores with alkaline guts to Bt intoxication cannot be invalidated without further study.
Vitamin D Levels as a Marker of Severe SARS-CoV-2 Infection
Authors: Athanassiou Lambros , Kostoglou-Athanassiou Ifigenia , Nikolakopoulou Sofia , Konstantinou Alexandra , Mascha Olga , Siarkos Evangelos , Samaras Charilaos , Athanassiou Panagiotis , Shoenfeld Yehuda
Published: January 2024

The SARS-CoV-2 virus may cause severe infection, which is associated with diverse clinical manifestations. Vitamin D has immunomodulating properties and may enhance the body’s defense system against invading pathogenic organisms. The aim was to assess 25(OH)D3 levels in patients hospitalized for severe infection from the SARS-CoV-2 virus and explore the relationship between 25(OH)D3 and outcomes. In a group of 88 patients hospitalized for severe infection from the SARS-CoV-2 virus and a control group matched for age and sex, the levels of 25(OH)D3 were analyzed. Levels of 25(OH)D3 were 17.36 ± 8.80 ng/mL (mean ± SD) compared with 24.34 ± 10.34 ng/mL in patients with severe SARS-CoV-2 infection and the control group, respectively, p < 0.001 (Student’s t-test). 25(OH)D3 levels were significantly related to outcomes, i.e., survival as opposed to non-survival, as more patients with 25(OH)D3 deficiency (0–10 ng/mL) and insufficiency (10–20 ng/mL) had a fatal outcome as compared with those with vitamin D sufficiency (p < 0.001, chi-square test, p < 0.001, Fisher’s exact test). Levels of 25(OH)D3 were inversely related to C-reactive protein (CRP), ferritin, d-dimer, and fibrinogen levels (p < 0.001, linear regression analysis, beta coefficient of variation, −0.176, −0.160, −0.178, and −0.158, respectively). Vitamin D deficiency observed in severe SARS-CoV-2 infection was related to disease outcomes.
Individual Factors Modifying Postoperative Pain Management in Elective Total Hip and Total Knee Replacement Surgery
Authors: Jurewicz Alina , Gasiorowska Agata , Leźnicka Katarzyna , Pawlak Maciej , Sochacka Magdalena , Machoy-Mokrzyńska Anna , Bohatyrewicz Andrzej , Maciejewska-Skrendo Agnieszka , Pawlus Grzegorz
Published: January 2024

Total hip and knee replacements are the most common orthopedic procedures performed due to osteoarthritis. Pain is an intrinsic symptom accompanying osteoarthritis, persisting long before surgery, and continuing during the preoperative and postoperative periods. Appropriate pain management after surgery determines the comfort, duration, and cost of hospitalization, as well as the effectiveness of postoperative rehabilitation. Individual differences in pain perception and tolerance in orthopedic patients remain an important research topic. Therefore, the aim of this study was to investigate the predictors of analgesic requirements (morphine, acetaminophen, and ketoprofen), including individual pain threshold and tolerance, body mass index (BMI), diabetes, and beliefs about pain control in patients undergoing elective hip or knee arthroplasty using a multilevel regression model (N = 147, 85 women, 62 men, 107 after hip replacement, and 40 after knee replacement). Results: Higher pain tolerance was associated with a lower dose of morphine per kg after surgery. Patients undergoing hip surgery received a lower dose of ketoprofen than patients undergoing knee surgery. The more the patient believed in personal pain control, the stronger the negative relationship between pain tolerance and morphine requirement. The lowest doses were given to patients with the highest pain tolerance and the greatest belief in personal control. Factors such as belief in pain control and pain tolerance should be considered in comprehensive postoperative pain management in orthopedic patients to reduce opioid doses and, thus, side effects.
High-Dose Acetaminophen as a Treatment for Cancer
Authors: Wu Jeffrey , Maller Bradley , Kaul Rujul , Galabow Andrea , Bryan Allyn , Neuwelt Alexander
Published: January 2024

The use of high-dose acetaminophen (AAP) with n-acetylcysteine (NAC) rescue was studied as an anti-cancer treatment in phase I trials with promising signals of anti-tumor efficacy. Correlative analysis suggested that AAP has a free-radical-independent mechanism of anti-tumor activity—in contrast to the well-established mechanism of AAP hepatotoxicity. Subsequent “reverse translational” studies in the pre-clinical setting have identified novel mechanisms of action of high-dose AAP, including modulation of JAK-STAT signaling in both the tumor cell and the tumor immune microenvironment. Importantly, these effects are free-radical-independent and not reversed by concurrent administration of the established AAP rescue agents fomepizole and NAC. By administering high-dose AAP concurrently with fomepizole and NAC, 100-fold higher AAP levels than those of standard dosing can be achieved in mice without detected toxicity and with substantial anti-tumor efficacy against commonly used mouse models of lung and breast cancer that are resistant to standard first-line anti-cancer therapies. With these recent advances, additional clinical trials of high-dose AAP with concurrent NAC and fomepizole-based rescue are warranted.
A Text-Based Predictive Maintenance Approach for Facility Management Requests Utilizing Association Rule Mining and Large Language Models
Authors: Lowin Maximilian
Published: January 2024

Introduction: Due to the lack of labeled data, applying predictive maintenance algorithms for facility management is cumbersome. Most companies are unwilling to share data or do not have time for annotation. In addition, most available facility management data are text data. Thus, there is a need for an unsupervised predictive maintenance algorithm that is capable of handling textual data. Methodology: This paper proposes applying association rule mining on maintenance requests to identify upcoming needs in facility management. By coupling temporal association rule mining with the concept of semantic similarity derived from large language models, the proposed methodology can discover meaningful knowledge in the form of rules suitable for decision-making. Results: Relying on the large German language models works best for the presented case study. Introducing a temporal lift filter allows for reducing the created rules to the most important ones. Conclusions: Only a few maintenance requests are sufficient to mine association rules that show links between different infrastructural failures. Due to the unsupervised manner of the proposed algorithm, domain experts need to evaluate the relevance of the specific rules. Nevertheless, the algorithm enables companies to efficiently utilize their data stored in databases to create interpretable rules supporting decision-making.
Real-Time Droplet Detection for Agricultural Spraying Systems: A Deep Learning Approach
Authors: Huynh Nhut , Nguyen Kim-Doang
Published: January 2024

Nozzles are ubiquitous in agriculture: they are used to spray and apply nutrients and pesticides to crops. The properties of droplets sprayed from nozzles are vital factors that determine the effectiveness of the spray. Droplet size and other characteristics affect spray retention and drift, which indicates how much of the spray adheres to the crop and how much becomes chemical runoff that pollutes the environment. There is a critical need to measure these droplet properties to improve the performance of crop spraying systems. This paper establishes a deep learning methodology to detect droplets moving across a camera frame to measure their size. This framework is compatible with embedded systems that have limited onboard resources and can operate in real time. The method leverages a combination of techniques including resizing, normalization, pruning, detection head, unified feature map extraction via a feature pyramid network, non-maximum suppression, and optimization-based training. The approach is designed with the capability of detecting droplets of various sizes, shapes, and orientations. The experimental results demonstrate that the model designed in this study, coupled with the right combination of dataset and augmentation, achieved a 97% precision and 96.8% recall in droplet detection. The proposed methodology outperformed previous models, marking a significant advancement in droplet detection for precision agriculture applications.
Semantic-Enhanced Knowledge Graph Completion
Authors: Yuan Xu , Chen Jiaxi , Wang Yingbo , Chen Anni , Huang Yiou , Zhao Wenhong , Yu Shuo
Published: January 2024

Knowledge graphs (KGs) serve as structured representations of knowledge, comprising entities and relations. KGs are inherently incomplete, sparse, and have a strong need for completion. Although many knowledge graph embedding models have been designed for knowledge graph completion, they predominantly focus on capturing observable correlations between entities. Due to the sparsity of KGs, potential semantic correlations are challenging to capture. To tackle this problem, we propose a model entitled semantic-enhanced knowledge graph completion (SE-KGC). SE-KGC effectively addresses the issue by incorporating predefined semantic patterns, enabling the capture of semantic correlations between entities and enhancing features for representation learning. To implement this approach, we employ a multi-relational graph convolution network encoder, which effectively encodes the KG. Subsequently, we utilize a scoring decoder to evaluate triplets. Experimental results demonstrate that our SE-KGC model outperforms other state-of-the-art methods in link-prediction tasks across three datasets. Specifically, compared to the baselines, SE-KGC achieved improvements of 11.7%, 1.05%, and 2.30% in terms of MRR on these three datasets. Furthermore, we present a comprehensive analysis of the contributions of different semantic patterns, and find that entities with higher connectivity play a pivotal role in effectively capturing and characterizing semantic information.
Nonlinear Modeling and Vibration Response Analysis of a Dual-Rotor System with an Inter-Shaft Graphite Seal
Authors: Xiao Sen , Yu Pingchao , Jiang Zihan , Wang Cun , Chen Jiayu , Zhang Qicheng
Published: January 2024

The inter-shaft graphite seal is a common structure in the dual-rotor system, and may generate nonlinear lateral excitation when there is large relative angular motion at the seal position. This paper represents the first attempt to study the nonlinear behaviors of a dual-rotor system with inter-shaft graphite seal excitations. First, an excitation model of the inter-shaft graphite seal is proposed by the analytical method. This model is then introduced into the beam finite element model of a dual rotor system, and the dynamic equations of the whole system are finally obtained. The vibration responses under the effect of the inter-shaft seal are clarified by analyzing 3D waterfall plots, rotor orbits, and time and frequency domain waveforms. The results show that the inter-shaft seal can lead to vibration coupling between HP and LP rotors. The axial spring stiffness and contact end face friction coefficient of the graphite seal have a significant effect on rotor vibration. When those two parameters are small, only coupling vibration phenomena can be observed, i.e., the rotation frequency of one rotor can be observed in another rotor vibration. With the increase in axial spring stiffness or contact end face friction coefficient, multiple modes of LP and HP rotors are excited, which dominates the vibration behaviors of the dual rotor system.
Parallel Accelerating Number Theoretic Transform for Bootstrapping on a Graphics Processing Unit
Authors: Li Huixian , Pan Deng , Li Jinglei , Wang Hao
Published: January 2024

The bootstrapping procedure has become the main bottleneck affecting the efficiency of all known fully homomorphic encryption (FHE) schemes. The state-of-the-art scheme for efficient bootstrapping, which is called fully homomorphic encryption over the torus (TFHE), accelerates polynomial multiplication by leveraging number theoretic transform (NTT) and implementing NTT in parallel on a GPU. Unfortunately, almost none of the recent advancements in NTT take full advantage of a GPU, leading to the need for more time. With this in mind, in this work, a novel faster number theoretic transform based on a GPU is proposed, in which matrix multiplication is used to implement a decomposed small-point NTT. When implementing matrix multiplication, we introduce a merging preprocessing method to merge multiple inputs of the small-point NTT, aiming to effectively minimize the count of modulo operations. Subsequently, when the merged result is multiplied by rotation factors, we use logical left shift rather than arithmetic multiplication to improve the computational efficiency. Our scheme can easily be used to realize a 1024-point NTT and the results of the experiments show that the speedup ratio of our method over the butterfly algorithm is about 2.49.
On Value Distribution of Certain Beurling Zeta-Functions
Authors: Laurinčikas Antanas
Published: January 2024

In this paper, the approximation of analytic functions by shifts ζP(s+iτ) of Beurling zeta-functions ζP(s) of certain systems P of generalized prime numbers is discussed. It is required that the system of generalized integers NP generated by P satisfies ∑m⩽x,m∈N1=ax+O(xδ), a>0, 0⩽δ<1, and the function ζP(s) in some strip lying in σ^<σ<1, σ^>δ, which has a bounded mean square. Proofs are based on the convergence of probability measures in some spaces.
A Study on Determining the Optimal Feedback Rate in Distributed Block Diagonalization with Limited Feedback for Dense Cellular Networks
Authors: Kim Taehwi , Min Moonsik
Published: January 2024

In this study, we explore a downlink cellular network where each base station (BS) engages in simultaneous communication with multiple users through spatial division multiple access (SDMA). The positions of both BSs and users are established through independent random point processes, effectively representing the cellular network. SDMA utilizes block diagonalization (BD) at each BS, employing multiple receive antennas for each user. To implement BD, users quantize and provide feedback on their downlink channels to their respective BSs. The net spectral efficiency, measuring the effective rate accounting for both downlink and uplink resource usage, serves as a performance metric. In prior research, the optimal feedback rate in terms of maximizing net spectral efficiency has been approximated in this scenario. The corresponding approximations effectively illustrate the asymptotic behavior of the optimal number as a function of the length of the coherent channel block. However, the accuracy of the approximation diminishes when the length of the coherent channel block is relatively small. Given that the length of the coherent channel block can assume relatively small values depending on wireless environments, achieving a precise estimate across the entire range of the coherent block length holds significant importance. Consequently, this paper focuses primarily on enhancing the accuracy of the approximation for the optimal feedback rate. In order to achieve a more precise estimation, we analyze the derivative of the net spectral efficiency, which encompasses two functions that demonstrate distinct growth rates. In contrast to prior studies, both functions are rigorously approximated through mathematical analysis. As a result, the proposed approximation significantly improves the accuracy compared to previous studies, particularly when dealing with short coherent channel block lengths. Moreover, this approximation generally achieves near-optimal performance, regardless of system parameters.
Point-Wise Ribosome Translation Speed Prediction with Recurrent Neural Networks
Authors: Bongini Pietro , Pancino Niccolò , Lachi Veronica , Graziani Caterina , Giacomini Giorgia , Andreini Paolo , Bianchini Monica
Published: January 2024

Escherichia coli is a benchmark organism, which has been deeply studied by the scientific community for decades, obtaining a vast amount of metabolic and genetic data. Among these data, estimates of the translation speed of ribosomes over their genome are available. These estimates are based on Ribo-Seq profiles, where the abundance of a particular fragment of mRNA in a profile indicates that it was sampled many times inside a cell. Various measurements of Ribo-Seq profiles are available for Escherichia coli, yet they do not always show a high degree of correspondence, which means that they can vary significantly in different experimental setups, being characterized by poor reproducibility. Indeed, within Ribo-Seq profiles, the translation speed for some sequences is easier to estimate, while for others, an uneven distribution of consensus among the different estimates is evidenced. Our goal is to develop an artificial intelligence method that can be trained on a small pool of highly reproducible sequences to establish their translation rate, which can then be exploited to calculate a more reliable estimate of the translation speed on the rest of the genome.
The Use of Allograft Bone in the Lateral Approach of Sinus Floor Elevation: A Systematic Review of Clinical Studies
Authors: Pogacian-Maier Alexandra-Camelia , Mester Alexandru , Morariu Rares-Luca , Campian Radu Septimiu , Tent Andrei
Published: January 2024

Background and Objectives: The aim of this systematic review was to assess the efficiency of using allografts for sinus lift. Materials and Methods: This systematic review was written under the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and recommendation of the Cochrane Handbook for Systematic Reviews of Interventions. Three electronic databases were screened until October 2023. The risk of bias was assessed according to the Strengthening the Reporting of Observational studies in Epidemiology (STROBE) guidelines. Statistical analysis was performed for median bone volume and implant survival rate. Results: From 321 articles retrieved, 7 articles were included in this review. A comparison between freeze-dried bone allograft (FDBA) and deproteinized bovine bone (DBB) for mean bone volume indicated a weighted mean difference (WMD) of −0.17 [−0.69, 0.36] (95% confidence interval (CI)), p = 0.53. For implant survival rate, a comparison was made between FDBA and autogenous bone indicating a risk ratio (RR) of 1.00 [0.96, 1.05] (95% CI), p = 1.00. Conclusions: The available evidence suggested that allograft bone can be used in sinus lift procedures. The results obtained are insufficient to compare with other types of bone graft, requiring a longer follow-up time. Future clinical trials are needed in order to evaluate the advantages of using allograft bone.