bluuebunny/crossref_metadata_2025 huggingface dataset:
Bacillus tequilensis influences metabolite production in tomato and restores soil microbial diversity during Fusarium oxysporum infection
Authors: Bhattacharya A. , Chauhan P. , Singh S. P. , Narayan S. , Bajpai R. K. , Dwivedi A. , Mishra A.
Published: April 2024

This study evaluates cellular damage, metabolite profiling, and defence‐related gene expression in tomato plants and soil microflora during Fusarium wilt disease after treatment with B. tequilensis PBE‐1.

Histochemical analysis showed that PBE‐1 was the primary line of defence through lignin deposition and reduced cell damage. GC–MS revealed that PBE‐1 treatment ameliorated stress caused by F. oxysporum infection. PBE‐1 also improved transpiration, photosynthesis, and stomatal conductance in tomato. qRT‐PCR suggested that the defence‐related genes FLS2, SERK, NOS, WRKYT, NHO, SAUR, and MYC2, which spread infection, were highly upregulated during F. oxysporum infection, but either downregulated or expressed normally in PBE‐1 + P treated plants. This indicates that the plant not only perceives the bio‐control agent as a non‐pathogen entity but its presence in normal metabolism and gene expression within the host plant is maintained. The study further corroborated findings that application of PBE‐1 does not cause ecological disturbances in the rhizosphere.

Activity of soil microflora across four treatments, measured by Average Well Colour Development (AWCD), showed continuous increases from weeks 1 to 4 post-pathogen infection, with distinct substrate usage patterns like tannic and fumaric acids impacting microbial energy source utilization and diversity. Principal Component Analysis (PCA) and diversity indices like McIntosh, Shannon, and Simpson further illustrated significant microbial community shifts over the study period.

In conclusion, our findings demonstrate that B. tequilensis PBE‐1 is an ideal bio‐agent for field application during Fusarium wilt disease management in tomato.
Assessing the influence of dopamine and mindfulness on the formation of routines in visual search
Authors: Garner Kelly G. , Leow Li‐Ann , Uchida Aya , Nolan Christopher , Jensen Ole , Garrido Marta I. , Dux Paul E.
Published: April 2024

Given experience in cluttered but stable visual environments, our eye‐movements form stereotyped routines that sample task‐relevant locations, while not mixing‐up routines between similar task‐settings. Both dopamine signaling and mindfulness have been posited as factors that influence the formation of such routines, yet quantification of their impact remains to be tested in healthy humans. Over two sessions, participants searched through grids of doors to find hidden targets, using a gaze‐contingent display. Within each session, door scenes appeared in either one of two colors, with each color signaling a differing set of likely target locations. We derived measures for how well target locations were learned (target‐accuracy), how routine were sets of eye‐movements (stereotypy), and the extent of interference between the two scenes (setting‐accuracy). Participants completed two sessions, where they were administered either levodopa (dopamine precursor) or placebo (vitamin C), under double‐blind counterbalanced conditions. Dopamine and trait mindfulness (assessed by questionnaire) interacted to influence both target‐accuracy and stereotypy. Increasing dopamine improved accuracy and reduced stereotypy for high mindfulness scorers, but induced the opposite pattern for low mindfulness scorers. Dopamine also disrupted setting‐accuracy invariant to mindfulness. Our findings show that mindfulness modulates the impact of dopamine on the target‐accuracy and stereotypy of eye‐movement routines, whereas increasing dopamine promotes interference between task‐settings, regardless of mindfulness. These findings provide a link between non‐human and human models regarding the influence of dopamine on the formation of task‐relevant eye‐movement routines and provide novel insights into behavior‐trait factors that modulate the use of experience when building adaptive repertoires.
miRSNP rs188493331: A key player in genetic control of microRNA‐induced pathway activation in hypertrophic scars and keloids
Authors: Chen Meiqing , Pan Yuyan , Chen Zhiwei , Qi Fazhi , Gu Jianying , Qiu Yangyang , He Anqi , Liu Jiaqi
Published: April 2024

Background

Our study aims to delineate the miRSNP–microRNA–gene–pathway interactions in the context of hypertrophic scars (HS) and keloids.

Materials and Methods

We performed a computational biology study involving differential expression analysis to identify genes and their mRNAs in HS and keloid tissues compared to normal skin, identifying key hub genes and enriching their functional roles, comprehensively analyzing microRNA‐target genes and related signaling pathways through bioinformatics, identifying MiRSNPs, and constructing a pathway‐based network to illustrate miRSNP‐miRNA‐gene‐signaling pathway interactions.

Results

Our results revealed a total of 429 hub genes, with a strong enrichment in signaling pathways related to proteoglycans in cancer, focal adhesion, TGF‐β, PI3K/Akt, and EGFR tyrosine kinase inhibitor resistance. Particularly noteworthy was the substantial crosstalk between the focal adhesion and PI3K/Akt signaling pathways, making them more susceptible to regulation by microRNAs. We also identified specific miRNAs, including miRNA‐1279, miRNA‐429, and miRNA‐302e, which harbored multiple SNP loci, with miRSNPs rs188493331 and rs78979933 exerting control over a significant number of miRNA target genes. Furthermore, we observed that miRSNP rs188493331 shared a location with microRNA302e, microRNA202a‐3p, and microRNA20b‐5p, and these three microRNAs collectively targeted the gene LAMA3, which is integral to the focal adhesion signaling pathway.

Conclusions

The study successfully unveils the complex interactions between miRSNPs, miRNAs, genes, and signaling pathways, shedding light on the genetic factors contributing to HS and keloid formation.
Transfusion management and hemoglobin‐based oxygen carrier treatment in a patient with anti‐Rh17 antibody
Authors: Mehr Noah , Fuja Christine , Simon Cody , Carll Timothy , Alkhateb Rahaf , Wu Sulin , Patel Anand A. , Aldarweesh Fatima
Published: April 2024

Background

A 54‐year‐old Hispanic OPos female with known history of anti‐Rh17 antibodies was diagnosed with Philadelphia‐Chromosome positive (Ph+) acute lymphoblastic leukemia (ALL). Rh17, also known as Hr0, is a high‐frequency antigen composed of several epitopes on the RhCE protein. Anti‐Rh17 antibodies can be made by individuals with missing or varied C/c, E/e antigens. Anti‐Rh17 antibodies are clinically significant given multiple case reports of hemolytic disease of the fetus and newborn (HDFN). Finding compatible units for patients with anti‐Rh17 can be particularly difficult given that only 1 in 100,000 people are Rh17 negative.

Study Design and Methods

Search for compatible units was conducted by the American Rare Donor Program (ARDP) with no leads. After chemotherapy induction and despite erythropoiesis stimulating agent administration, the patient's hemoglobin continued to trend down to a nadir of 2.8 g/dL. Here we report transfusion of incompatible pRBC to this patient with critically symptomatic anemia. HBOC‐201 (Hemopure) was obtained and administered under an emergency compassionate/expanded access designation from the Food and Drug Administration (FDA) under an emergency Investigational New Drug (IND) application.

Results and Discussion

Overall difficulties in this case included the challenge of finding compatible units, dilemma of transfusing incompatible units in a patient with severe anemia and obtaining alternatives to blood products. This case report demonstrates the successful use of HBOC‐21 in treating life‐threatening anemia.
Comparison of hematologic variables among Warmbloods, Thoroughbreds, and Western stock horse breeds
Authors: Schaefer E. A. , Edman J. , Magdesian K. G.
Published: April 2024

Background

Hematology is a diagnostic tool used to evaluate the health status of horses. However, breed differences are often not considered.

Objectives

The objective was to compare complete blood count variables among Warmbloods, Thoroughbreds, and stock horses (SH).

Methods

Ninety‐six healthy horses were grouped by breed (Warmbloods, Thoroughbreds, and SH). Samples were collected through venipuncture for complete blood count analysis. One‐way ANOVA with Tukey's tests or Kruskal–Wallis with Dunn's post hoc tests were used to compare hematologic variables among groups.

Results

Warmbloods had a significantly lower total white blood cell (WBC) count (6.08 ± 1.11 × 109/L) and lymphocyte count (1.76 ± 0.41 × 109/L) than Thoroughbreds (7.28 ± 1.45; 2.28 ± 5.16 × 109/L, respectively; P < .001) and SH (7.21 ± 1.18 × 109/L, P < .01; 2.10 ± 5.17 × 109/L; P < .05). Warmbloods had a significantly lower red blood cell count (7.7 ± 0.8 × 1012/L) and higher mean corpuscular volume (MCV, 49.4 ± 2.2 fL) than Thoroughbreds (8.42 ± 1.2 × 1012/L, P < .01; 47.3 ± 3.0 fL). Warmbloods had lower MCVs than SH (49.4 ± 2.2 vs 51.2 ± 2.6 fL). The mean cell hemoglobin concentration (MCHC) was higher in Warmbloods (35.0, 33.8–36.2 g/dL) and Thoroughbreds (34.9, 33.4–35.7 g/dL) than in SH breeds (34.0, 33.4–35.4 g/dL; P < .001, both). Total protein concentrations were significantly lower in Thoroughbreds (67, 59–80 g/L) compared with SH (71, 64–83 g/dL) (P < .05).

Conclusions

Warmbloods had decreased WBC and lymphocyte counts compared with Thoroughbreds and SH, and Thoroughbreds had increased red blood cell counts. Thoroughbreds had lower total protein concentrations than SH. Clinicians should consider breed differences when interpreting hematologic values.
Re-Estimating Inflation Threshold Level for Tanzania
Authors: Mbowe Wilfred E. , Mpango Hossana P.
Published: April 2024

The study seeks to estimate the relationship between inflation and economic growth, as well as the headline inflation threshold level beyond or below which Tanzania’s economic growth is constrained. This was achieved through the Ordinary Least Squares (OLS) regressions employing quarterly data spanning the period 2001:1 to 2021:4. The findings suggest that the coefficient of inflation variable that captures the effect of low inflation on growth is statistically significant and positive, implying that low inflation is pro-growth. One percent increase in inflation leads to an economic growth of 0.352 percent. Furthermore, the coefficient of the high inflation proxy variable has a negative sign with the inflation threshold level being seven percent. At this level, the total effect of inflation on growth is estimated at 0.3494 percent.  Moreover, optimal inflation levels of one to three percent have no impact on growth, as mirrored by invariable adjusted R2.The recommendations from the results of this study are three-fold. First, the Bank of Tanzania may consider inflation targets below seven percent but above three percent in the monetary policy planning to continue supporting economic growth. Second, since the Bank has largely depended on inflation behaviour in informing inflation targets to choose, which ended into picking targets far from the optimal inflation, it is essential that the Bank also benefits from empirically estimated threshold rates. Third, in order to utilize any new information emanating from structural changes and developments in the economy, inflation threshold level should be re-estimated regularly.
On noncommutative distributional Khintchine type inequalities
Authors: Jiao Yong , Quan Xingyan , Sukochev Fedor , Zanin Dmitriy
Published: April 2024

The purpose of this paper is to provide distributional estimates for the series of the form with being elements from noncommutative Lorentz spaces and being Rademacher functions. To this end, we introduce a novel class of operators that are closely related to the dual Cesáro operator and construct a new extrapolation theorem that is of independent interest.
Koszul self‐duality of manifolds
Authors: Malin Connor
Published: April 2024

We show that Koszul duality for operads in can be expressed via generalized Thom complexes. As an application, we prove the Koszul self‐duality of the right module associated to a framed manifold . We discuss implications for factorization homology, embedding calculus, and confirm an old conjecture of Ching on the relation of Goodwillie calculus to manifold calculus.
Improved Durability of a Modular Axial Fixator for Stable and Unstable Proximal Femoral Fractures: A Patient-Specific Finite Element Analysis
Authors: Celık H. Kursat , Içen Mustafa , Ozdemır Hakan , Rennıe Allan E.W.
Published: April 2024

Femoral neck fractures, comprising 8–10% of all bodily fractures in the elderly, often necessitate alternatives to extensive surgical interventions. Despite limited research, external fixators are considered promising. This study evaluates the design and durability of a novel modular axial fixator (MAF) for stable and unstable proximal femoral fractures, using numerical method-based engineering analysis. Employing patient-specific CT scan data, three-dimensional (3D) solid modeling, and finite element analysis (FEA), the MAF-bone fixation is examined in eight simulation scenarios under static loading conditions. FEA results show a peak femur head displacement of 7.429 mm in FEA 001, with Schanz screw no. 2 reaching the maximum equivalent stress at 431.060 MPa in FEA-006. Notably, the 7.429-mm displacement improves stability compared to previous studies, yet interfragmentary movement surpasses the 100–200 μm reference range for primary fracture healing, posing challenges to direct healing despite enhanced stability. This study validates the durability of the innovative MAF for femoral neck fractures through engineering simulations. It contributes to understanding MAF durability issues, with implications for improving medical implant design in the industry. Simulation results offer opportunities for optimizing structure and production, enhancing the MAF's design, and ultimately benefiting medical implant manufacturing.
Physics-Informed Approximation of Internal Thermal History for Surface Deformation Predictions in Wire Arc Directed Energy Deposition
Authors: Zamiela Christian , Stokes Ryan , Tian Wenmeng , Doude Haley , Priddy Matthew W. , Bian Linkan
Published: April 2024

This work presents a physics-informed fusion methodology for deformation detection using multi-sensor thermal data. A challenge with additive manufacturing (AM) is that abnormalities commonly occur due to rapid changes in the thermal gradient. Different non-destructive in-situ thermal sensors capture parts of the thermal history but are limited by the visible temperature spectrum and sensor field of view of the fabrication process. Various sensors mitigate problems with the loss of thermal history information; however, it brings forth challenges with integrating different data streams and the need to interpolate the internal thermal history. This study develops a thermal data-informed heat flux methodology that fills the gap in fusing numerical temperature approximation with data-driven knowledge of the surface of additive manufactured components. First, this study fuses infrared (IR) thermal data complexities during the AM process with the Goldak double ellipsoidal heat flux to model the energy input into the component. Second, a thermal physics-informed model input (PIMI) is created with thermal data-informed heat flux to capture internal thermal history. Lastly, a regression convolutional neural network (CNN) captures the relationship between the three-dimensional thermal gradient and the resulting surface deformation. The rapid thermal gradient formation and identification of deformation is a key step toward using thermal history data and machine learning to improve quality control in AM. The proposed surface deformation detection model achieved an mean squared error of 1.14 mm and an R2 of 0.89 in the case study when fabricating thin-walled structures.
Transient Performance Analysis of Centrifugal Left Ventricular Assist Devices Coupled With Windkessel Model: Large Eddy Simulations Study on Continuous and Pulsatile Flow Operation
Authors: Gil Antonio , Navarro Roberto , Quintero Pedro , Mares Andrea
Published: April 2024

Computational fluid dynamics (CFD) simulations are widely used to develop and analyze blood-contacting medical devices such as left ventricular assist devices (LVADs). This work presents an analysis of the transient behavior of two centrifugal LVADs with different designs: HeartWare VAD and HeartMate3. A scale-resolving methodology is followed through Large Eddy Simulations, which allows for the visualization of turbulent structures. The three-dimensional (3D) LVAD models are coupled to a zero-dimensional (0D) 2-element Windkessel model, which accounts for the vascular resistance and compliance of the arterial system downstream of the device. Furthermore, both continuous- and pulsatile-flow operation modes are analyzed. For the pulsatile conditions, the artificial pulse of HeartMate3 is imposed, leading to a larger variation of performance variables in HeartWare VAD than in HeartMate3. Moreover, CFD results of pulsatile-flow simulations are compared to those obtained by accessing the quasi-steady maps of the pumps. The quasi-steady approach is a predictive tool used to provide a preliminary approximation of the pulsatile evolution of flow rate, pressure head, and power, by only imposing a speed pulse and vascular parameters. This preliminary quasi-steady solution can be useful for deciding the characteristics of the pulsatile speed law before running a transient CFD simulation, as the former entails a significant reduction in computational cost in comparison to the latter.
Development of Freeze Resistant Heat Pipe With Water as Working Fluid for Automotive Applications
Authors: Date Ashwin , Singh Randeep , Oridate Tomoki , Mochizuki Masataka , Date Abhijit , Akbarzadeh Aliakbar , Nag Sarthak
Published: April 2024

The wide spread adoption of heat pipes in automotive and aviation application is hampered by the fact that they require protection against frost damage caused by the repetitive exposure to subzero temperatures. Here, we present heat pipe with ethylene glycol and water as working fluid that can prevent damage to the copper container on exposure to cyclic freezing and thaw. In this research, different mass concentrations of water and ethylene glycol have been tested for freeze protection of heat pipes. Experimental investigations have shown that 3.5% by mass concentration of ethylene glycol in water is able to sustain the cyclic freezing and avoid any damage to the copper pipe. In this research, the freezing and heating cycle is set to operate between −40 °C and 90 °C. Heat pipes used for testing in this research were 6 mm in diameter and 150 mm long with copper fiber spiral wick. Thermal performance tests were carried out on these heat pipes with charging ratio of working fluid varying between 10% to 30% by volume. It is observed that the thermal resistance of heat pipe with working fluid charging ratio in range of 10% to 25% by volume varies from 0.6 °C/W to 0.2 °C/W for the rate of heat transfer of 10 W–50 W. While the charging ratios beyond 25% have shown the higher thermal resistance in the range of 0.8 to 1.0 °C/W for similar rate of heat transfer. All the samples were subjected to 150 freezing and thaw cycles and did not show any signs of frost damage. Accelerated life tests were performed on these heat pipes for up to 500 h and did not presented any signs of degradation in their thermal performance.
Experimental Study on Parameters Optimization of Selective Laser Melting 316L Stainless Steel Based on the Response Surface Methodology
Authors: Wang Yali , Li Zhiyong , Cui Jingran , Zhang Wei , Liu Yuchen
Published: April 2024

The use of 3D printing technology can prepare flexible and varied special-shaped complex structures while realizing resource-saving and cost reduction. For this purpose, a 316L stainless steel sample was formed by selective laser melting technology, and the quality of samples was optimized by the Box–Behnken surface response method. Taking the surface roughness Sa as the response value, a regression analysis of four parameters of selective laser melting (laser power, scanning speed, scanning spacing, and scanning strategy) was designed using design expert software. The results showed that the scanning spacing and scanning speed have the greatest influence on the surface roughness, while the laser power and scanning strategy have no significant influence on the surface roughness. Meanwhile, the established surface roughness response surface model is effective and can be used for quality optimization of 316L structural trim. When the laser power was 185 W, the scanning speed was 615 mm/s, the scanning spacing was 110 μm and concentric scanning strategy was adopted, the surface adhesion powder was less, and the minimum surface roughness Sa was 9.001 μm.
Analysis of Gaps in Techno-Economic Analysis to Advance Heliostat Technologies for Concentrating Solar-Thermal Power
Authors: Augustine Chad , Zolan Alexander , Armijo Kenneth
Published: April 2024

The Heliostat Consortium (HelioCon) was launched in 2021 to advance heliostat technology. One of its first efforts was to do a detailed analysis of gaps in technology and capabilities in the heliostat industry and complete a roadmap study describing high-priority gaps. HelioCon gathered gaps through a series of outreach activities with representatives and experts from industries and research institutes. This paper discusses the gap analysis for the techno-economic analysis (TEA) topic. One of the main objectives of the TEA topic is to relate the cost and performance of heliostats and heliostat components to the overall system performance. In this study, we limit the scope of this topic to the heliostat field, tower, and receiver and do not consider downstream applications or uses of thermal energy. We conducted a thorough review of existing models and compiled a list of the state of the art in open-source tools currently available to researchers. We collected an initial list of gaps for the TEA of heliostats from industry developers and experts. Each gap is briefly described, and the heliostat development cycle stages that the gap impacts are indicated. We ranked the initial list of TEA gaps into tiers depending on their potential impact. For TEA, most of the gaps identified are related to developing models or data. Strictly speaking, none of these gaps are essential for heliostat development, but all would aid in the heliostat development process.
Humeral Torsion in Relation to Shoulder Range of Motion in Elite Field Hockey Players
Authors: Vanderstukken Fran , Spanhove Valentien , Cools Ann , Borms Dorien
Published: April 2024

Context: Sport-specific adaptations in shoulder rotation range of motion (ROM) and the relationship with humeral torsion have been described in overhead-throwing sports. However, information is lacking for other shoulder-loading sports such as field hockey. Therefore, this study’s purpose was to evaluate humeral torsion in elite, male field hockey players and explore its association with shoulder ROM. Design: Cross-sectional study. Methods: Twenty-five male, elite field hockey players were included. Humeral torsion and shoulder external and internal rotation ROM were evaluated bilaterally by ultrasound and an inclinometer smartphone application, respectively. Results: Field hockey players showed a significantly increased humeral retroversion on the dominant compared with the nondominant side (P < .001; Cohen d = 1.75), along with a significantly increased external (P = .004; Cohen d = −0.64) and decreased internal rotation ROM (P = .003; Cohen d = 0.65). This finding illustrates a shift in total shoulder rotational ROM arc. Correlation analysis showed a significant moderate association between the increased humeral retroversion and decreased internal rotation ROM on the dominant side (r = .523). Conclusions: Elite male field hockey athletes show sport-specific adaptations regarding humeral torsion and shoulder rotation ROM, similar to throwing athletes. These findings increase our insight into the field hockey athlete’s shoulder, which is essential to optimize performance and assist in correctly interpreting shoulder rotational ROM measurements.
Development and performance evaluation of a qPCR-based assay for the fully automated detection of group B
Streptococcus
(GBS) on the Panther Fusion Open Access system
Authors: Caballero Méndez Andy , Reynoso de la Rosa Roberto A. , Abreu Bencosme Miguel E. , Sosa Ortiz Mayeline N. , Pichardo Beltré Eliezel , de la Cruz García Darah M. , Piñero Santana Nelson J. , Bacalhau de León Joana C.
Published: April 2024

Streptococcus agalactiae
[group B
Streptococcus
(GBS)] poses a major threat as the primary cause of early-onset neonatal invasive disease, particularly when mothers are colonized rectovaginally. Although culture remains the gold standard for antepartum GBS screening, quantitative polymerase chain reaction (qPCR) offers advantages in terms of sensitivity and turnaround time. The aim of this study was to validate the clinical utility of an automated qPCR laboratory-developed test (LDT) for antepartum GBS screening using the Panther Fusion Open Access system (Hologic, California, USA). The LDT targeted a conserved region of the GBS
surface immunogenic protein
gene, demonstrating no cross-reactivity and high coverage (99.82%–99.99%). The limit of detection (LoD) was 118 CFU/mL. Comparison with commercial qPCR assays (Panther Fusion GBS and VIASURE
Streptococcus
B Real-Time) revealed an overall agreement of 99.7%, with a robust Cohen’s kappa coefficient of 0.992. Testing of 285 rectovaginal swabs from pregnant women and 15 external quality assessment samples demonstrated exceptional diagnostic performance of the LDT, achieving a diagnostic sensitivity and specificity of 100%, underscoring its accuracy. Prevalence and predictive values were also determined to reinforce test reliability. Our research highlights the limitations of culture-based screening and supports the suitability of our qPCR-based LDT for GBS detection in a clinical setting.

IMPORTANCE

Rectovaginal colonization by GBS is a major risk factor for early-onset invasive neonatal disease. The most effective approach to reducing the incidence of early-onset disease (EOD) has been described as universal screening, involving assessment of GBS colonization status in late pregnancy and intrapartum antibiotic prophylaxis. Despite its turnaround time and sensitivity limitations, culture remains the gold standard method for GBS screening. However, nucleic acid amplification-based tests, such as qPCR, have been utilized due to their speed and high sensitivity and specificity. This study validated the clinical usefulness of an automated qPCR-LDT for antepartum GBS screening through the Panther Fusion Open Access system (Hologic). Our study addresses the critical need for more robust, sensitive, and rapid strategies for GBS screening in pregnant women that could favorably impact the incidence of EOD.
Case of metastatic clear cell odontogenic carcinoma with response to chemoimmunotherapy
Authors: Robertson Ian J , Robbins Quinn C , Li Peter C
Published: April 2024

Our patient initially presented with 6 months of left jaw pain and gingival bleeding, leading to the discovery of a radiolucent left maxillary mass on dental evaluation. A biopsy confirmed clear cell odontogenic carcinoma, and the patient was treated with definitive surgery and radiation for localised disease. Unfortunately, the patient was found to have pulmonary metastases 3 months after initial management and was subsequently treated with a combination of cytotoxic chemotherapy and immunotherapy with a partial response. To our knowledge, this is the first case demonstrating the successful use of chemoimmunotherapy in metastatic clear cell odontogenic carcinoma.
Alzheimer’s disease-related presenilins are key to intestinal epithelial cell function and gut immune homoeostasis
Authors: Erkert Lena , Gamez-Belmonte Reyes , Kabisch Melanie , Schödel Lena , Patankar Jay V , Gonzalez-Acera Miguel , Mahapatro Mousumi , Bao Li-Li , Plattner Christina , Kühl Anja A , Shen Jie , Serneels Lutgarde , De Strooper Bart ,   TRR241 IBDome Consortium, Neurath Markus F , Wirtz Stefan , Becker Christoph
Published: April 2024

Objective

Mutations in presenilin genes are the major cause of Alzheimer’s disease. However, little is known about their expression and function in the gut. In this study, we identify the presenilins Psen1 and Psen2 as key molecules that maintain intestinal homoeostasis.

Design

Human inflammatory bowel disease (IBD) and control samples were analysed for Psen1 expression. Newly generated intestinal epithelium-specific Psen1-deficient, Psen2-deficient and inducible Psen1/Psen2 double-deficient mice were used to dissect the functional role of presenilins in intestinal homoeostasis.

Results

Psen1 expression was regulated in experimental gut inflammation and in patients with IBD. Induced deletion of Psen1 and Psen2 in mice caused rapid weight loss and spontaneous development of intestinal inflammation. Mice exhibited epithelial barrier disruption with bacterial translocation and deregulation of key pathways for nutrient uptake. Wasting disease was independent of gut inflammation and dysbiosis, as depletion of microbiota rescued Psen-deficient animals from spontaneous colitis development but not from weight loss. On a molecular level, intestinal epithelial cells lacking Psen showed impaired Notch signalling and dysregulated epithelial differentiation.

Conclusion

Overall, our study provides evidence that Psen1 and Psen2 are important guardians of intestinal homoeostasis and future targets for barrier-promoting therapeutic strategies in IBD.
Hybrid choice modeling offers an interdisciplinary perspective on angler preferences for the future
Authors: Golebie Elizabeth J. , van Riper Carena J. , Johnson Dana N. , Lindberg Kreg , Joffe-Nelson North , Shin Seunguk , Stedman Richard , Suski Cory , Hunt Len M.
Published: April 2024

Angler decisions are shaped by an interplay between “internal” psychological processes and “external” institutional factors that are equally important yet often evaluated in isolation. We therefore developed a hybrid choice model whereby a structural equation model of behavioral antecedents was integrated with a discrete choice experiment to evaluate competing preferences for fisheries management scenarios across the Great Lakes region. We observed that preferences for native fish populations, invasive species impacts, wash station availability, habitat quality, and added cost per fishing trip were rooted in nature-based (i.e., biospheric), human-focused (i.e., altruistic) and self-driven (i.e., egoistic) values. Specifically, preferences for reduced invasive species impacts were more pronounced among anglers with stronger altruistic values, and less pronounced among those with strong egoistic values. Preferences also varied by fishing mode, in that boaters were more sensitive to cost than shoreline or mixed mode users, and younger anglers were more open to change. This study showcases a novel interdisciplinary methodological approach that builds more complete knowledge of the interrelationships between psychological and institutional factors that underpin angler decision-making.
Reactor neutrino physics potentials of cryogenic pure-CsI crystal
Authors: Wang Lei , Li Guanda , Yu Zeyuan , Liang Xiaohua , Wang Tian’an , Liu Fang , Sun Xilei , Guo Cong , Zhang Xin , Lei Yu , Chen Yuede
Published: April 2024

This paper presents a world-leading scintillation light yield among inorganic crystals measured from a 0.5 kg pure-CsI detector operated at 77 Kelvin. Scintillation photons were detected by two 2-inch Hamamatsu SiPM arrays equipped with cryogenic front-end electronics. Benefiting the light yield enhancement of pure-CsI at low temperatures and the high photon detection efficiency of SiPM, a light yield of 30.1 photoelectrons per keV energy deposit was obtained for X-rays and $$\gamma $$
γ
-rays with energies from 5.9 to 59.6 keV. Instrumental and physical effects in the light yield measurement are carefully analyzed. This is the first stable cryogenic operation of kg-scale pure-CsI crystal readout by SiPM arrays at liquid nitrogen temperatures for several days. The world-leading light yield opens a door for the usage of pure-CsI crystal in several fields, particularly in detecting the coherent elastic neutrino-nucleus scattering of reactor neutrinos. The potential of using pure-CsI crystals in neutrino physics is discussed in the paper.
Terahertz Wave Power Multiplication by Combining Photocurrents from Arrayed UTC-PDs
Authors: Ssali Hussein , Kamiura Yoshiki , Doi Ryo , Agemori Hiroki , Che Ming , Mikami Yuya , Kato Kazutoshi
Published: April 2024

A terahertz (THz) wave generator for multiplying the output power from arrayed photomixers is developed. The generator is composed of two uni-traveling carrier photodiodes (UTC-PDs) as the photomixers, a [Formula: see text] T-junction power combiner and a microstrip rectangular patch antenna on a silicon carbide (SiC) substrate in which photocurrents of 300 GHz from the UTC-PDs are combined to be fed to the antenna. Experimental results show that the output power is multiplied by 5.8 dB (approximately fourfold) compared to that of a single UTC-PD. This advancement has the potential for further multiplication of THz power by cascaded combining of a larger number of UTC-PDs.
Optimal Layout of (Kp − Cp)n into Wheel-Like Networks
Authors: Sundara Rajan R. , Rini Dominic D. , Sadagopan N.
Published: April 2024

The problem of finding the induced subgraph with the maximum number of edges among all subsets of a fixed cardinality is known as the maximum subgraph problem (MSP). The lexicographic order has been proven optimal for Cartesian products of specific regular graphs [B. Sergei, B. Pavle and K. Nikola, New infinite family of regular edge isoperimetric graphs, Theoretical Computer Science 721 (2018) 42–53]. This paper is dedicated to the precise calculation of edge values within the resulting subgraphs, enhancing our comprehension of their structural properties and implications. In this paper, we focus on solving the MSP of [Formula: see text] for any [Formula: see text] and for odd [Formula: see text], [Formula: see text] and [Formula: see text], where [Formula: see text] is obtained by the Cartesian product of a complete graph with [Formula: see text] vertices with a removal of a cycle on [Formula: see text] vertices. It has been observed that the graph obtained by deleting a cycle of length [Formula: see text] from a complete graph [Formula: see text] is isomorphic to a circulant graph [Formula: see text], while the particular case [Formula: see text] has been previously studied in [A. Syeda and M. Rajesh, MinLA of [Formula: see text] and its optimal layout into certain trees, The Journal of Supercomputing (2023), https://doi.org/10.1007/s11227-023-05140-3]. Our work extends the understanding of the MSP to a broader class of graphs with similar properties and applications.
Economic Policy Uncertainty and Stock Market Index: Fresh Insights from Augmented-ARDL and Multiple Structural Breaks
Authors: Odionye Joseph Chukwudi , Ojiaku Ethelbert Ukachukwu , Okpara Godwin Chigozie , Agoh Ndubuisi , Okpara Roy M.
Published: April 2024

This study provides unique insights into the link between economic policy uncertainty (EPU) and stock market index in Sub-Saharan African (SSA) countries. Basically, the dearth of evidence in this perspective, especially in the context of SSA motivates this new assessment. Thus, on account of the monthly longitudinal series for 11 SSA countries over 2014M1–2023M6, the novel multiple structural break test in panel (MSBP) and cross-sectional ARDL (CS-ARDL) provide the following upshots: first, the high level of EPU worsens the region’s stock index in the short run; second, there is a long-term negative but insignificant effect of EPU on the stock index; third, EPU significantly reduces the stock index in the three identified structural break regimes, but outside it, it is insignificant; fourth, the devastating influence of EPU on stock prices is more pronounced during the COVID-19 era demonstrating that the response of the region’s stock market to EPU is highly sensitive to global shocks. The policy implication from the major findings is for the government authorities to put up plans that can strengthen the stock markets’ resilience to economic policy-induced uncertainty.
Impact of Design Decisions on Performance of Embarrassingly Parallel .NET Database Application
Authors: Karwaczyński Piotr , Sitko Marcin , Pietras Sylwia , Marczuk Bogdan , Wasielewski Mariusz , Kwiatkowski Jan , Fraś Mariusz
Published: April 2024

The implementation of parallel applications is always a challenge. It embraces many distinctive design decisions that are to be taken. The paper presents issues of parallel processing with use of .NET applications and popular Database Management Systems (DBMSes). In the paper, four design dilemmas are addressed: how efficient is the auto-parallelism implemented in the .NET TPL library, how do popular DBMSes differ in serving parallel requests, what is the optimal size of data chunks in the data parallelism scheme, and how the TPL auto-parallelism behaves in the public clouds. They are analyzed in the context of the typical and practical business case originated from IT solutions which are dedicated for the energy market participants. The paper presents the results of experiments conducted in a controlled, on-premises and cloud environments. The experiments allowed to compare the performance of the TPL auto-parallelism with a wide range of manually set numbers of worker threads. They also helped to evaluate four DBMSes: Oracle, MySQL, PostgreSQL, and MSSQL in the scenario of serving parallel queries. Finally, they showed the impact of data chunk sizes on the overall performance.
New methodological approach for deep penetrating geochemistry and environmental studies, Part 2: field determination of Co(II)/Ni(II) and Pb(II)/Zn(II) of on-site soil extractions by electrochemical stripping techniques
Authors: Hackel Laetitia , Rotureau Elise , Guilleux Camille , Poszwa Anne , de Junet Alexis , Middleton Maarit , Morrin Aoife , Pinheiro José Paulo
Published: April 2024

In the framework of deep penetrating geochemistry for mineral exploration, we report a field electroanalytical method using disposable screen-printed working electrodes able to quantify metal pathfinders in partial extracts of soil samples at the nanomolar level on-site. Four metal pathfinders (Co, Ni, Pb and Zn) were chosen due to their geological interest and suitability of electrochemical detection. Square-wave anodic stripping voltammetry (SW-ASV) was developed for the simultaneous detection of Pb(II) and Zn(II) providing limits of detection (LOD) of 1.2 and 5.3 nM, respectively. A linear-scan cathodic stripping voltammetry (LS-CSV) methodology was developed for the joint detection of Co(II) and Ni(II) yielding LOD of 1.8 and 3.5 nM, respectively. Method validation was carried out on 14 upper B-horizon soil samples during a field survey. Two wet extraction procedures were applied for soil samples – a strong extraction using nitric acid (HNO
3
) and a weak extraction using calcium chloride (CaCl
2
). Excellent agreement between electroanalytical methods and inductively coupled plasma mass spectrometry (ICP-MS) was found for Pb(II), while a small underestimation was observed for Zn(II). For Co(II) and Ni(II) the LS-CSV measurements in the HNO
3
extractions were impossible due to the change from low pH to pH to 7.15 which induces precipitation of iron and aluminium. For the CaCl
2
extractions, the Co(II)/Ni(II) results obtained by LS-CSV were in excellent agreement with ICP-MS measurements.
Deep Multiscale Soft‐Threshold Support Vector Data Description for Enhanced Heavy‐Duty Gas Turbine Generator Sets’ Anomaly Detection
Authors: Kun Zhang , Hongren Li , Xin Wang , Daxing Xie , Xiaokai Sun
Published: April 2024

This paper introduces an innovative approach, Deep Multiscale Soft‐Threshold Support Vector Data Description (DMS‐SVDD), designed for the detection of anomalies and prediction of faults in heavy‐duty gas turbine generator sets (GENSETs). The model combines a support vector data description (SVDD) with a deep autoencoder backbone network framework, integrating a multiscale convolutional neural network (M) and soft‐threshold activation network (S) into the Deep‐SVDD framework. In comparison with conventional methods, such as One‐Class Support Vector Machine (OCSVM) and autoencoder (AE), DMS‐SVDD demonstrates improvements in accuracy (by 22.94%), recall (by 32%), F1 score (by 12.02%), and smoothness (by 39.15%). The model excels particularly in feature extraction, denoising, and early fault detection, offering a proactive strategy for maintenance. Furthermore, the DMS‐SVDD demonstrated enhanced training efficiency with a reduction in the convergence rounds by 66% and overall training times by 34.13%. The study concludes that DMS‐SVDD presents a robust and efficient solution for gas turbine anomaly detection, with practical advantages for decision support in turbine maintenance. Future research could explore additional refinements and applications of the DMS‐SVDD model across diverse industrial contexts.
Impacts of Sustainable Land Management Intervention on the Soil Condition and Landscape Greenness: Evidence from Jimma Arjo District, Southwestern Ethiopia
Authors: Belayneh Mengie , Masha Mamush , Abera Alemayehu , Terefa Kitesa
Published: April 2024

Soil degradation has been a major environmental and agricultural challenge in Ethiopia in general and in the study area in particular. Recently, several governmental and nongovernmental organizations have made efforts to reduce the problem and improve the productivity of land through sustainable land management (SLM) practices. The main objective of this study was to investigate the impact of sustainable land management practices on soil condition and landscape greenness in the Jimma Arjo District, Southwestern Ethiopia. The impact of SLM practices on soil condition was examined by collecting twenty-eight (28) composite and core (28) soil samples from treated (14) and nontreated (14) lands. Landsat satellite images of 2012 and 2022 were used to detect changes in landscape greenness using the Normalized Difference Vegetation Index (NDVI). ArcGIS® 10.3, ERDAS® 2014, and Microsoft Excel software packages were used for analysis. The significance test was performed using a one-way ANOVA. The result showed a significant difference in soil physiochemical properties (soil texture, soil pH, soil organic carbon, soil organic matter, total nitrogen, and available phosphorous and calcium) between treated and nontreated lands (P<0.01). However, the landscape greenness result shows that the lowest NDVI value in the SLM-treated kebele during 2012 was −0.15 but increased to 0.09 in 2022. Similarly, the highest value was found to be 0.41 in 2012 and the value rose to 0.53 in 2022. It is concluded that sustainable land management practices implemented in the area have resulted in an important positive effect on improving the soil condition and landscape greenness. Hence, strengthening and scaling up SLM practices and continuous maintenance are advisable for better results in land productivity and livelihood improvement.
Detection of Asymptomatic Sickle Cell Hemoglobin Carriers and Fetal Hemoglobin Regulating Genetic Variants in African Descendants from Oaxaca, Mexico
Authors: Romero-Tlalolini María De Los Ángeles , Aguilar-Ruiz Sergio Roberto , Baltiérrez-Hoyos Rafael , Vargas-Arzola Jaime , Hernández-Osorio Luis Alberto , Vásquez-Garzón Verónica Rocío , Bernardino-Hernández Héctor Ulises , Torres-Aguilar Honorio
Published: April 2024

Sickle cell anemia has been classified as a noninfectious neglected tropical disease and, although not exclusively, affects African descendants more frequently. This study aimed to detect asymptomatic sickle cell hemoglobin carriers (HbAS) in marginalized and vulnerable populations during a public health screening in African descendants from Oaxaca, Mexico, and to validate an amplification refractory mutation system (ARMS)-PCR methodology to detect fetal-hemoglobin (HbF)-regulating genetic variants in BCL11A toward affordable routine association of single nucleotide variants (SNVs) with HbF concentrations. To this aim, hemoglobin variants were detected by acidic citrate agar and alkaline cellulose acetate electrophoreses. SNVs in the hemoglobin subunit beta gene (HBB) were identified by the β-globin mutation detection assay (β-GMDA) and ARMS-PCR, respectively, and validated by Sanger sequencing. The association between genotypes and HbF concentrations was evaluated using Spearman’s correlation coefficient. The results obtained during a directed screening in 140 self-identified African descendants revealed 42 HbS-carriers (30%), of which 39 showed normal total hemoglobin concentrations (92.8%), only 3 presented anemia (7.2%), and 9 showed quantifiable HbF concentration (21.4%). As validated by Sanger sequencing, the designed ARMS-PCR efficiently detected homozygous and heterozygous variants in BCL11A. In a cohort of 42 heterozygous (HbAS) and 27 healthy (HbAA) individuals from the same population, only one SNV (rs766432) showed statistically significant association with increasing HbF concentration, and two new unrelated homozygous silent variants were identified. This study reveals the need to raise coverage of HbS screening in vulnerable populations and shows a feasible low-cost ARMS-PCR methodology to determine the presence of SNVs in quantitative trait loci affecting HbF.
Convolutional Neural Networks to Facilitate the Continuous Recognition of Arabic Speech with Independent Speakers
Authors: Sayed Sally A. , Ahmed Abdel Azeem Abul Seoud Rania , Abdel Naby Howida Y.
Published: April 2024

Automatic speech recognition (ASR) is a field of research that focuses on the ability of computers to process and interpret speech feedback from humans and to provide the highest degree of accuracy in recognition. Speech is one of the simplest ways to convey a message in a basic context, and ASR refers to the ability of machines to process and accept speech data from humans with the greatest degree of accuracy. As the human-to-machine interface continues to evolve, speech recognition is expected to become increasingly important. However, the Arabic language has distinct features that set it apart from other languages, such as the dialect and the pronunciation of words. Until now, insufficient attention has been devoted to continuous Arabic speech recognition research for independent speakers with a limited database. This research proposed two techniques for the recognition of Arabic speech. The first uses a combination of convolutional neural network (CNN) and long short-term memory (LSTM) encoders, and an attention-based decoder, and the second is based on the Sphinx-4 recognizer, which includes pocket sphinx, base sphinx, and sphinx train, with various types and number of features to be extracted (filter bank and mel frequency cepstral coefficients (MFCC)) based on the CMU Sphinx tool, which generates a language model for different sentences spoken by different speakers. These approaches were tested on a dataset containing 7 hours of spoken Arabic from 11 Arab countries, covering the Levant, Gulf, and African regions, which make up the Arab world, and achieved promising results. CNN-LSTM achieved a word error rate (WER) of 3.63% using 120 features for filter bank and 4.04% WER using 39 features for MFCC, respectively, while the Sphinx-4 recognizer technique achieved 8.17% WER and an accuracy of 91.83% using 25 features for MFCC and 8 Gaussian mixtures, respectively, when tested on the same benchmark dataset.