bluuebunny/crossref_metadata_2025 huggingface dataset:
Exploring the Potential of Ornidazole as an Alternative Treatment for Pulpitis: Effects on Dental Pulp Cells and Macrophages
Authors: Yang Jing , Li Zikai , Zhang Chengcheng , Xiong Jiaying , Yang Xirui , Zheng Dandan , Xie Siming , Shi Haishan
Published: August 2024

Objectives: This study aimed to explore the potential of ornidazole as an alternative treatment for pulpitis, focusing on its effects on dental pulp cells (DPCs) and macrophages. We assessed the cytotoxicity of various concentrations of ornidazole, its safety and effectiveness in treating inflammatory DPCs, and its regulatory impact on inflammatory markers during inflammation.
Materials and Methods: Inflammation in dental pulp cells was induced using lipopolysaccharides (LPS), and varying doses of ornidazole were introduced. Cell proliferation, migration, regulation of inflammation, and promotion of dentinogenesis under inflammatory conditions were evaluated. Additionally, macrophages were cultured with different doses of ornidazole to analyze inflammatory gene expression.
Results: Ornidazole concentrations below 10 µg/mL showed no significant cytotoxic effects on DPCs over 7 days. The toxicity of ornidazole was concentration- and time-dependent. Ornidazole decreased the expression of IL-6 and TNF-α while enhancing IL-Ra and IL-8 expression. It also suppressed alkaline phosphatase (ALP) activity but increased the levels of odontogenic differentiation markers at both genetic and protein levels in the presence of inflammatory stimuli. Furthermore, ornidazole demonstrated immunomodulatory effects.
Conclusions: Low concentrations of ornidazole were safe for use in pulp cells. Ornidazole modulated the expression of inflammatory markers (IL-6, TNF-α, IL-8, IL-Ra) in inflamed DPCs and regulated odontogenesis-related markers. Low concentrations of ornidazole enhanced macrophage immune regulation, showing potential as a medication for treating pulpitis.
CLINICAL RELEVANCE: This study investigates ornidazole’s affinity for dental pulp cells, its effectiveness in reducing inflammation, and its regulatory effects on odontogenic processes. By examining the impact of different concentrations of ornidazole on pulp inflammation-related cells, we aim to assess its therapeutic potential for pulpitis and provide a reference for its clinical application.
Phenotype-to-genotype description of prenatal suspected and postnatal discovered upper limb anomalies: a retrospective cohort study.
Authors: Arduc Arda , Dijk Sandra , Cate Feikje , Doesburg Margriet , Linskens Ingeborg , Leeuwen Liesbeth , Maarle Merel , Eva Pajkrt
Published: August 2024

This is a retrospective cohort study to evaluate phenotype and genotype characteristics of a prenatal and postnatal cohort with upper limb anomalies from January 2007 to December 2021 in one tertiary referral center for Fetal Medicine. All prenatally on ultrasound suspected upper limb anomalies, such as transverse and longitudinal reduction defects, polydactyly, and syndactyly were evaluated. Additionally, children referred to the Congenital Hand team in the same center with upper limb anomalies that were not identified prenatally, were also evaluated separately.
The prenatal group included 199 pregnancies: 64 transverse and 19 longitudinal reduction defects, 103 polydactylies, and 13 cases with syndactyly. The majority of cases with longitudinal reduction defects (n=10, 52.6%), polydactyly (n=62, 60.2%), and syndactyly (n=10, 76.9%) were non-isolated, as opposed to transverse reduction defects which were generally isolated (n=41, 64.1%). The Congenital Hand Team received 362 new referrals of children with upper limb anomalies that were not identified prenatally. These cases included 49 transverse and 22 longitudinal reduction defects, 226 polydactylies, and 65 syndactlylies. A chromosomal or monogenic abnormality was identified in 76/199 (38.2%) cases of the prenatal group and in 31/362 (8.6%) cases of the postnatal group.
Prenatal identification of minor defects of the digits holds a challenge, since we observed more postnatal than prenatal cases. The majority of cases with isolated anomalies in both groups had no underlying chromosomal, monogenic or syndromic cause, as compared to the non-isolated cases. Conducting structural anomaly scans and genetic counselling are crucial to assess the risk of genetic abnormalities.
Short- and long-term outcomes of adrenalectomy for Primary Aldosteronism in a single UK centre: Rear Mirror View.
Authors: Abdel-Aziz Tarek , Abdelsalam Alaa , Chung Teng-Teng , Srirangalin Umasuthan , Hurel Steven , Conway Gerard , Baldeweg Stephanie E. , Kurzawinski Tom R
Published: August 2024

Purpose: Primary Aldosteronism (PA) is the commonest cause of secondary hypertension and can be cured by unilateral adrenalectomy. We report the short and long-term outcomes after adrenalectomy performed at a single UK centre over a period of 24 years.
Methods: Retrospective analysis of biochemical(potassium, aldosterone, renin and ARR) radiological (CT/MRI, AVS, nuclear scans) and clinical (surgical complications, blood pressure, number of antihypertensive medications) short and long terms outcomes in patients who underwent adrenalectomy for PA between 1998 and 2021. Standardised PASO and Clavien-Dindo criteria to assess biochemical, clinical and surgical outcomes were used.
Results: 82 patients treated with adrenalectomy for PA over a 24 year period, short term follow up data (within 3 months from surgery) was available for 82 patients (M45, F37, mean age 51.7 years), 24 of them were followed at least 60 months( range 60 to 72 months) 77 (93.9%) patients had laparoscopic surgery (1 conversion). 7 patients had postoperative complications classified as Clavien-Dindo II(4), IIIa(1) and IVa(2). Median LOS was 2.5 days (1-12).
Complete and partial clinical success was achieved in 29% and 58.3% and 41.7% and 45.8% of patients in short and long term respectively. Clinical benefit was observed in 88% of patients. Complete biochemical success was achieved in 95.8% of patients in short and long term.
Conclusion: Unilateral adrenalectomy in patients with PA achieved clinical benefit in 88% and biochemical cure in almost all of them. Our data suggest that these benefits persisted for at least 5 years.
Experimental Study on Laser Cutting Process of Simulated Fast Reactor Fuel Rods
Authors: Li Tianchi , Mo Zengliang , Chen Qi , Zhou Jia , Cao Zhi , Guo Jianhua , Yang Zhongyuan , Tang Chunwei , Zhang Hongmei , Xiao Tao , Li Wensi , Ming Yuzhou , Liu Fang , Yan Taihong , Mi Gaoyang , Zheng Weifang
Published: August 2024

The cladding of fast reactor fuel rod is fabricated using stainless steel, which, owing to its ductility, presents challenges such as increased tool wear and diminished cut quality when mechanically sheared. In light of technological advancements, laser cutting has emerged as a superior method due to its flexibility and high efficiency. The quality of laser-cut fuel rod significantly influences subsequent processing of short segments. This study systematically analyzes the impact of various laser cutting parameters on the cutting quality of simulated fast reactor fuel rod. Optimization of cutting speed, focal position, power, and gas pressure has substantially improved cutting effectiveness. Experimental findings indicate that a combination of 1 m/min cutting speed, focal position ranging from − 20 mm to -25 mm, power between 7200 W and 9600 W, and 10 MPa gas pressure achieves the optimal balance between efficiency and quality, providing crucial insights for the efficient cutting of fast reactor fuel rod.
Visual short-term memory in action and non-action video game players: A focus on short and long delay intervals
Authors: Pavan Andrea , Yilmaz Seyma Koc , Kafaligonul Hulusi , Föcker Julia , Greenlee Mark W.
Published: August 2024

Previous research suggests that individuals who play action video games tend to outperform non-action video game players in various cognitive functions. In the current study, we compare the precision of visual short-term memory for the direction of coherent motion among action video game players (AVGPs) and age and gender-matched non-action video game players (NAVGPs). Participants were tasked with remembering the direction of up to four random dot kinematograms (RDKs) presented in a sequence, with the number of RDKs varying randomly between one and four in each trial. After the sequence, a probe number appeared on the screen, indicating which RDK the participant needed to reproduce. Following either a brief (0.5 s) or a longer interval (3 s), participants reproduced the direction of a designated RDK. To reach a specific performance level with a single RDK stimulus, participants underwent initial training. The training results revealed that AVGPs required slightly fewer training blocks than NAVGPs to reach the desired performance level. While the two groups did not differ in precision for the short delay, AVGPs performed the task more precisely than NAVGPs when tasked with reproducing the motion direction of a single RDK after a long interval. Using a complementary model-fitting methodology, we investigated the distribution of memory resources within the two groups. Our analysis revealed that, in contrast to the AVGPs, NAVGPs exhibited higher neural costs relative to the behavioral advantages linked to memory encoding. This was particularly evident during the long retention interval, resulting in NAVGPs allocating a reduced amount of memory-related resources in this condition. Future training studies could explore the integration of models that account for the allocation of memory resources, balancing the behavioral benefits of encoding precision against the neural costs involved.
Study on mechanical properties of particle-reinforced polymer composites
Authors: Qin Chen , Gao Wei , Guo Zhangxin , Niu Weijing , Chai Gin Boay , Zheng Jiajun
Published: August 2024

Acrylic resin is widely used in fields such as aerospace, military, coatings, and electronic equipment due to its excellent physical and chemical properties. The mechanical properties of its polymer composite materials are influenced by various factors such as component volume fractions, types, and treatment methods. In this paper, the mechanical properties of particle-reinforced acrylic composites and the factors affecting them are investigated. The effect patterns of the contents of glass beads, quartz sand, and heavy calcium carbonate on the tensile, bending, and compressive properties of the polymer composites were experimentally investigated. Combined with the digital image correlation (DIC) to observe the dynamic damage images of the specimens, the full strain field information was analyzed and the local strain distribution was studied. A finite element model of polymer composite materials was established, and the numerical simulation results were consistent with the experimental results. The progressive damage and failure process of the composite materials was analyzed. This research result can guide the experimental design and application of particle reinforced acrylic composite materials.
Radius solution of plastic zone in soft rock tunnel surroundings considering joint damage
Authors: Hu Taotao , Tu Peng , Zhao Yulong
Published: August 2024

Based on the Hohai model, a creep constitutive model of viscoelastic-plastic soft rock with joint fracture damage is proposed to solve the rheological failure problem of soft rock tunnel surrounding rock. Based on the proposed creep model of rock with joint damage and the current analytical analysis method of circular tunnel, the analytical formulas of viscoelastic-viscoplastic stress and displacement of circular tunnel with joint damage surrounding rock are derived. ABAQUS finite element software is used to simulate the excavation of surrounding rock with different joint angles. The numerical solution is compared with the analytical solution to verify the accuracy of the theoretical formula. The results show that when the joint inclination is 45°, the displacement values of the two are 16.36mm and 16.87mm respectively, and the error of the two is 3.02%. The theoretical calculation is in good agreement with the numerical simulation results, thus verifying the rationality of the derived analytical formula of viscoelastic-viscoplastic stress and displacement of the soft rock tunnel with joint damage.
Unpacking the Complexity of Corporate Sustainability: Green Innovation's Mediating Role in Risk Management and Performance
Authors: Al-Nimer Munnther
Published: August 2024

This study investigates the relationships among Corporate Sustainability Development (CSD), Enterprise Risk Management Performance (ERMP), and Green Innovation (GI) in the Jordanian manufacturing sector. Using data from 97 companies listed on the Amman Stock Exchange, we employed structural equation modeling to examine these complex dynamics. Our findings reveal that CSD negatively impacts both ERMP and enterprise sustainable performance in the short term, challenging conventional wisdom. However, CSD strongly promotes GI, which in turn positively influences ERMP while negatively affecting short-term performance. GI acts as a significant mediator, positively mediating the CSD-ERMP relationship and negatively mediating the CSD-performance link. These results extend the sustainability paradox concept to emerging economies and highlight the critical role of green innovation in balancing sustainability initiatives with risk management and performance outcomes. The study suggests that firms may experience initial disruptions when implementing sustainability practices, but these initiatives can drive innovation within organizations. Based on these findings, we recommend that managers in emerging economies adopt a long-term perspective when implementing sustainability initiatives and develop more flexible risk management systems. Policymakers should consider supportive frameworks to help firms navigate the tensions between sustainability, innovation, and short-term performance. Future research should employ longitudinal designs to capture the dynamic nature of these relationships and explore potential moderating factors such as firm size or industry-specific characteristics.
Socio-demographic and clinical predictors of post-acute, mid-and long-term psychological sequelae of COVID-19: A two-year cross-sectional investigation on 1317 patients at the University Hospital of Verona
Authors: Perlini Cinzia , Marcanti Maddalena , Zonta Marco Pattaro , Mazzi Maria Angela , Mason Anna , Apollonio Massimo , Calì Debora , Fasoli Michela , Brocco Chiara , Nesto Silvia Tulla , Humphris Gerald , Maccarrone Gaia , Gentilotti Elisa , Tacconelli Evelina , Piccolo Lidia Del
Published: August 2024

Background
The present paper focuses on socio-demographics, clinical variables, and the distance from the infection in predicting the long-term psycho-social consequences of COVID-19.
Methods
Patients were screened with a cross-sectional design at the Psychological Service of the University Hospital of Verona (Italy) at 3, 6, 12, and 18 months after their SARS-CoV-2 infection. The assessment was part of the Horizon 2020-funded ORCHESTRA Project and included the Hospital Anxiety and Depression Scale (HADS), the Short Form Health Survey 36 (SF-36), the Impact of Event Scale-Revised (IES-R), and ad-hoc questions measuring pre-post COVID-19 changes on psycho-social dimensions (sleep quality, nutrition, level of autonomy, work, social relationships, emotional wellbeing).
Results
Between June 2021 and June 2023, we evaluated 1317 patients (mean age 56.6 ± 14.8 years; 48% male): 35% at three months, 40% at 6, 20% at 12, and 5% at 18 months after the infection. Thirty-five percent were hospitalized due to COVID-19. Overall, 16% reported some form of clinically significant mental distress following the infection (HADS-TOT), with 13% and 6%, respectively, experiencing anxiety (HADS-Anxiety) and depressive symptoms (HADS-Depression). Four percent testified post-traumatic symptoms. The SF-36 scale revealed that 16% and 17% of subjects had physical or psychological deterioration in quality of life, respectively. The regression analyses showed that females experienced higher levels of anxiety and depression compared to males, along with worse mental and physical quality of life and pre-post infection changes in nearly all the investigated psycho-social dimensions. Younger people felt more anxiety and had a reduced mental quality of life than their older counterparts, who, in turn, had poorer scores in terms of autonomy and physical functioning. Hospitalized patients had lower levels of self-sufficiency, social relationships, and work than non-hospitalized people. The latter were more anxious and reported a lower physical quality of life. Finally, patients evaluated for the first time at 12- and 18 months showed a more significant impairment in mental and physical quality of life than those assessed at three months.
Conclusions
our data show that COVID-19 psychological sequelae tend to persist over time, still needing clinical attention and intervention planning, especially for females.
The Effect of Topical Curcumin Nanoparticles Encapsulated with β- Cyclodextrin into Hyaluronic Acid-Based Hydrogel Complex on Experimental Ulcerative Keratitis in Comparison with N-Acetylcysteine in Rabbit Model
Authors: Sohani Zahra , Jamshidi Shahram , Koohi Mohammad Kazem , Malakootikhah Javad , Abarkar Mohammad , Golchin Diba , Roshani Sarina , Liyeh Haniyeh Naghdi , Gazafroudi Negin Aghajanpour Moghaddam , Amjadi Nava , Niaki Reihaneh Izadi
Published: August 2024

Corneal ulcers, whether melting or indolent, are common in humans and companion animals. Treatment involves local administration of antibiotic eye drops and corneal healing drugs. Compared to traditional treatments for ulcerative keratitis, herbal medicines have unique advantages, such as potent anti-inflammatory effects and inhibition of proinflammatory cytokines. Curcumin, extracted from the Curcuma Longa plant, possesses extensive pharmacological properties, such as anti-inflammatory, anti-cancer, and antioxidant properties, and is used in various medicines. In this study, using a formulation of Curcumin NPs encapsulated with β-cyclodextrin and hyaluronic acid, an ophthalmic drop hydrogel was developed to accelerate corneal healing and improve the quality of healed structures. The formation of Curcumin NPs into Hyaluronic acid-based hydrogels was characterized by Fourier transform infrared (FTIR), zeta, and scanning electron microscope (SEM) analyses. A total of 25 healthy male New Zealand Albino rabbits were experimentally induced with ulcerative keratitis and treated individually with topical medication. Rabbits were divided into five groups. Fluorescein dye staining, corneal clarity score, Schirmer tear test, proinflammatory cytokine measurement, and pathologic factors assessments were used to evaluate the optimised Curcumin NPs with β-cyclodextrin in Hyaluronic acid hydrogel. Intriguingly, the frequency of administering medication is reduced compared to conventional therapies, which enhances the quality of healed structures and harnesses ulcerative keratitis. (p<0.05) All findings in this study provide new insight into designing and fabricating novel ophthalmic medicine for ulcerative keratitis for topical usage.
Predicting substrates for orphan Solute Carrier Proteins using multi- omics datasets
Authors: Zhang Y. , Newstead S. , Sarkies P.
Published: August 2024

Solute carriers (SLC) are integral membrane proteins responsible for transporting a wide variety of metabolites, signaling molecules and drugs across cellular membranes. Despite key roles in metabolism, signaling and pharmacology, around one third of SLC proteins are ‘orphans’ whose substrates are unknown. Experimental determination of SLC substrates is technically challenging given the wide range of possible physiological candidates. Here, we develop a predictive algorithm to identify correlations between SLC expression levels and intracellular metabolite concentrations by leveraging existing cancer multi-omics datasets. Our predictions recovered known SLC-substrate pairs with high sensitivity and specificity compared to simulated random pairs. CRISPR loss-of-function screen data and metabolic pathway adjacency data further improved the performance of our algorithm. In parallel, we combined drug sensitivity data with SLC expression profiles to predict new SLC-drug interactions. Together, we provide a novel bioinformatic pipeline to predict new substrate predictions for SLCs, offering new opportunities to de-orphanise SLCs with important implications for understanding their roles in health and disease.
The IgLON family of cell adhesion molecules expressed in developing neural circuits ensure the proper functioning of the sensory system in mice
Authors: Singh Katyayani , Jayaram Mohan , Hanumantharaju Arpana , Tõnissoo Tambet , Jagomäe Toomas , Mikheim Kaie , Muthuraman Srirathi , Gilbert Scott F. , Plaas Mario , Schäfer Michael K.E. , Innos Jürgen , Lilleväli Kersti , Philips Mari-Anne , Vasar Eero
Published: August 2024

Deletions and malfunctions of the IgLON family of cell adhesion molecules are associated with anatomical, behavioral, and metabolic manifestations of neuropsychiatric disorders. We have previously shown that IgLON genes are expressed in sensory nuclei/pathways and that IgLON proteins modulate sensory processing. Here, we examined the expression of IgLON alternative promoter-specific isoforms during embryonic development and studied the sensory consequences of the anatomical changes when one of the IgLON genes, Negr1, is knocked out. At the embryonal age of E12.5 and E13.5, various IgLONs were distributed differentially and dynamically in the developing sensory areas within the central and peripheral nervous system, as well as in limbs and mammary glands. Sensory tests showed that Negr1 deficiency causes differences in vestibular function and temperature sensitivity in the knockout mice. Sex-specific differences were noted across olfaction, vestibular functioning, temperature regulation, and mechanical sensitivity. Our findings highlight the involvement of IgLON molecules during sensory circuit formation and suggest Negr1's critical role in somatosensory processing.
Low-Light Image Enhancement Model with Nonlinear Enhancement Probability
Authors: Chen Zefei , Lin Yongjie , Xu Jianmin , Lu Kai , Shou Yanfang
Published: August 2024

Because low-light image enhancement is of great significance for improving the accuracy of object detection, it has gained the attention of many researchers. In the process of low-light image enhancement, darker pixels have a greater probability of being enhanced, while brighter pixels have a greater probability of being suppressed. Therefore, based on the Zero DCE, we propose a low-light image enhancement model with nonlinear enhancement probability, named TransNEP. On the one hand, an enhancement function with attention is proposed to simultaneously enhance over-dark pixels and suppress over-bright pixels with a greater probability than the existing methods. On the other hand, we split the low-light image into multiple patches and embed these patches as patch queries. Then, based on the transformer’s key-query mechanism, patch queries are decoded to obtain the enhancement probability corresponding to each patch. Finally, this study verify the improvement in texture and object detection’s accuracy of the image enhanced with TransNEP through comprehensive experiments.
Graph Neural Networks with Autoregressive Moving Average Graph Filter and Graph- Regularized Sparse Coding for Accurate Hyperspectral Image Classification on FPGA
Authors: Muralikrishnan P , M Maheswari
Published: August 2024

Classification techniques based on hyperspectral images (HSIs) have gained significant importance in target identification, mineral mapping, and environmental management due to rapid advancements in hyperspectral remote sensing technology. Graph Neural Networks (GNNs) have become a key technique, attracting considerable attention in HSI analysis. However, GNN-based techniques frequently depend on a graph filter to extract the intricate spectral-spatial characteristics inherent in HSI data, which limits the ability to fully exploit the diverse and rich information available. This can lead to less comprehensive feature representation. To overcome these limitations, we propose a novel method called AMAGC-GNN, Autoregressive Moving Average Graph Filter and Graph-Regularized Sparse Coding for the GNN. The ARMA graph filters play a crucial role in spectral filtering, effectively capturing and preserving complex spectral relationships while mitigating the common oversmoothing problem in traditional GNNs, ensuring node features retain their uniqueness and discriminative power. Concurrently, graph-regularized sparse coding transforms the input HSI data into sparse coefficients, representing the most relevant features efficiently. This combined approach leverages the strengths of both techniques, providing adaptive and precise spectral filtering and compact, discriminative feature representation. AMAGC-GNN outperforms other techniques, achieving significant improvements in Cohen's Kappa coefficient (6.58% and 6.15%), per-class accuracy (6.24% and 5.57%), and overall accuracy (6.24% and 6.30%) across Kennedy Space Centre and Indian pines datasets. Furthermore, our implementation of AMAGF-GNN on Virtex-7 field-programmable gate arrays (FPGAs) demonstrates promising results for real-world applications in HSI classification, particularly in achieving highly accurate target localization.
Risk-based Mapping of Pesticide Usage and Social Vulnerability in the Contiguous United States
Authors: Taiba Jabeen , Beseler Cheryl , Kolok Alan , Zahid Muhammad , Bartelt-Hunt Shannon , Rogan Eleanor
Published: August 2024

Background In the contiguous United States, environmental justice burdens and disparities in pesticide exposure are prevalent among racial and ethnic minorities and low socioeconomic groups. Identifying the counties with high pesticide exposure and social vulnerability is essential to mitigating risk.
Methods We created an index for pesticides commonly used in the contiguous US states from 1992 to 2019, as well as a social vulnerability index. We identified the US counties with elevated pesticide exposure and elevated social vulnerability. The USGS Pesticide National Synthesis Project quantified pesticide exposures at a county scale for frequently applied pesticides from 1992 to 2019 in 3069 contiguous US counties. We retrieved social vulnerability data from five-year estimates (2015–2019) of the American Community Survey (ACS) for selected variables: race, income, and educational attainment, and created a social vulnerability index. We implemented the pesticide index and social vulnerability index using a principal component analysis (PCA) approach. We used an Intergovernmental Panel on Climate Change ICCP risk-based approach to identify the counties with both high pesticide exposure and social vulnerability.
Results One hundred and forty-three US counties had high pesticide use and social vulnerability. Illinois, North Carolina, Michigan, California, Ohio, Indiana, Iowa, and Pennsylvania had significantly higher proportions of these high pesticide application and social vulnerability counties than any other state. In conclusion, disparities in pesticide exposure and associated health outcomes due to social vulnerability are widespread across the contiguous US counties in both rural and urban communities.
Conclusions Our study will inform regulatory bodies about areas with both high pesticide exposure and social vulnerability areas, as well as facilitate regulatory and public health decisions.
Prevalence of pulmonary hypertension and associated factors among rheumatic heart disease patients having follow up at public referral hospitals in Bahir Dar, Ethiopia, 2023.
Authors: Gedefaw Asmamaw , Yabebal Yihealem , Wudie Gebeyaw , Tefera Abiyot , Kassa Agerye , Demilew Tadele
Published: August 2024

Background
In developing countries evidences regarding pulmonary hypertension in rheumatic heart disease patients are lacking, despite being responsible for significant morbidity and mortality. As a result, identifying the factors that influence pulmonary hypertension is crucial to improve the quality of care.
Objective
To determine prevalence of pulmonary hypertension and its associated factors among rheumatic heart disease patients at the public hospitals of Bahir Dar city, 2023.
Methods
An institution based cross sectional study was conducted among Rheumatic heart disease patients who had follow up at the two public hospitals of Bahir Dar city form January 2022 to December 2023. It involved 310 patients selected by systematic random sampling technique. Pretested, structured, and interviewer-administered questionnaires were used to collect sociodemographic and diseases related parameters. Trans thoracic echocardiography by cardiologist was used to assess pulmonary hypertension. Data were entered using Epidata Manager version 4.6 and analyzed using SPSS version 27. Multivariate logistic regression analysis was used to identify determinants of glycemic control, considering with a p-value of < 0.05 as statically significant, with a 95% confidence interval.
Results
The mean sPAP of the participants were 50.2 mmHg [SD ± 25.0mmHg]. The prevalence of pulmonary hypertension among RHD patients were 56.5% (95% CI 50.9–61.9) from which 51.4% had severe pulmonary hypertension. Severe mitral valve stenosis (AOR 7.8, 95% CI 2.4–25.7), duration of illness ≥ 3 years (AOR 7.7, 95% CI 2.1–28.5), diuretics use (AOR 5.6, 95% CI 2.2–14.3,), valvular intervention (AOR 0.06, 95% CI 0.01 0.29) and LVEF ≥ 50% (AOR 0.14, 95% CI 0.02–0.81) were factors associated with pulmonary hypertension.
Conclusions
This study revealed more than half of the participants had pulmonary hypertension. And this was associated with having sever mitral valve stenosis, long duration of illness, diuretics use, valvular intervention and LVEF of ≥ 50%. Effective and tailored interventions are needed to mitigate these risk factors to improve pulmonary hypertension related comorbidities in rheumatic heart disease patients.
Effects of Planting Date and Genotypes on Potato Growth and Yield Determination in a Sub-Tropical Continental Growing Environment
Authors: Khan Muhammad Sohail , Hoogenboom Gerrit , Gillani Syeda Mehwish , Shah Alam Syed , Khan Ilham
Published: August 2024

Potato tuber yield-determining seasonal changes, especially in subtropical growing settings, are poorly investigated. This study examined eleven potato genotypes ‘G’ under four planting dates ‘P’ (very early (02 Oct), early (14 Oct), late (26 Oct), and very late (07 Nov)) and their interactive response (P×G) on potato growth and tuber yield in southern Khyber Pakhtunkhwa, Pakistan over two years (2017-18 and 2018-19). Early planting improved most yield-determining traits over late planting, extending the growing period (PMD) and maximizing green canopy cover (CG, 72.3%), mother stems plant-1 (MSN, 4.1), leaf number plant-1 (LN, 50.8), leaf area plant-1 (LAP, 5343 cm2), cumulative photosynthetic active radiation (PARINTC, 900.9 MJ m-2), thermal days (TDC, 52.9 td), and tubers plant-1 (TN, 11.8), marketable tuber weight (TWM, 103.0 g), marketable (TYM, 30.7 t ha-1), and total (TYT, 32.9 t ha-1) tuber yield. Late plantings reduced PMD and thus these traits. Considerable genotypic variation was found in plant phenology, growth, and tuber yield traits, however, genotype ranking also varied by planting date, indicating strong P×G interactions. The genotype ‘Arizona’ outperformed others with maximum TYM (29.2 t ha-1) and TYT (30.4 t ha-1) across planting dates. We identified key traits including days to emergence (ED), CG, PARINTC, and TDC, which are vital indicators of yield potential and important for breeding and selection. Our findings highlight the complexity of yield formation in potatoes and suggest tailored genotype selection and planting strategies to enhance yield stability and resilience, which are crucial for adapting to climate change and meeting food demand.
LLM-KGMQA: Large Language Model-Augmented Multi-Hop Question-Answering System based on Knowledge Graph in Medical Field
Authors: Wang FeiLong , Shi Donghui , Aguilar Jose , Cui Xinyi , Jiang Jinsong , Shen Longjian , Li Mengya
Published: August 2024

In response to the problems of poor performance of large language models in specific domains, limited research on knowledge graphs and question-answering systems incorporating large language models, this paper proposed a multi-hop question-answering system framework based on a knowledge graph in the medical field, which was fully augmented by large language models (LLM-KGMQA). The method primarily addressed the problems of entity linking and multi-hop knowledge path reasoning. To address the entity linking problem, an entity fast-linking algorithm was proposed, which categorized entities based on multiple attributes. Then, it used user mentions to obtain the target attribute set of attributes and further narrowed the entity search scope through attribute intersection operations. Finally, for entities that remained too numerous after the intersection, the method suggested using a pre-trained model for similarity calculation and ranking, and to determine the final entity through construction instructions. Regarding multi-hop knowledge path reasoning, the paper proposed a three-step reasoning framework that included an n-hop subgraph construction algorithm, a knowledge fusion algorithm, and a semantics-based knowledge pruning algorithm. In the entity fast-linking experiments, the maximum computational complexity was reduced by 99.9% through intersection operations. Additionally, a new evaluation metric, top@n, was introduced. When using the Roberta model for similarity calculations, the top@n score reached a maximum of 96.4, and the entity fast-linking accuracy was 96.6%. In multi-hop knowledge path reasoning, the paper first validated the need for knowledge fusion by constructing three different forms of instructions. Subsequently, experiments were conducted with several large language models, concluded that the GLM4 model showed the best performance in Chinese semantic reasoning. The accuracy rates for GLM4 after pruning were 99.9%, 83.3%, and 86.6% for 1-hop, 2-hop, and 3-hop, respectively, compared to 95.0%, 6.6%, and 5.0% before pruning. The average response time was reduced by 1.36s, 6.21s and 27.07s after pruning compared to before pruning.
A Novel Three-Dimensional Analysis Method for Accurate Evaluation of Cutaneous Small Sensory Nerve Fibers in Mice
Authors: Kojima Minori Inanaga , Matsuura Tetsuro , Ozaki Kiyokazu
Published: August 2024

The evaluation of intraepidermal nerve fiber (IENF) density is commonly used to diagnose peripheral neuropathy. However, conventional two-dimensional (2D) analysis methods using rodent models show high interstudy variability. Three-dimensional (3D) IENF analysis has been proposed for human skin biopsies because the spatial location of each nerve is easily determined. However, to date, no studies have compared 2D and 3D analysis of mouse cutaneous nerve fibers under the same conditions. This study aimed to establish a more accurate analysis method for mouse cutaneous nerve fibers, addressing the limitations of 2D analysis. Using tissue transparency, nerve fiber-specific antibodies, confocal microscopy, and 3D analysis software (IMARIS), we analyzed the 3D structure of IENFs in mice. In the 2D analysis, the IENF density was not accurately determined due to the inability to ascertain the continuity of the nerve from dermis to epidermis. In contrast, the 3D analysis clearly defined branching points and continuity, allowing for the accurate measurement of IENF density. As a result, the actual IENF density from the 3D analysis was significantly less than that indicated by the 2D analysis. This 3D approach enables the precise capture of IENF trajectories with various parameters, establishing a standard method for evaluating peripheral neuropathy models.
DSP-free coherent receivers in frequency-synchronous optical networks for next-generation datacenter interconnects
Authors: Liu Lei , Liu Feng , Peng Cheng , Xu Bo , Shieh William
Published: August 2024

Propelled by the rise of artificial intelligence (AI), cloud services and data center applications, next-generation low-power, local-oscillator-less, and DSP-free short-reach coherent optical communication has evolved into an increasingly prominent area of research in recent years. Here, we demonstrate DSP-free coherent optical transmission by analog signal processing in frequency synchronous optical networks (FSON) architecture, which supports polarization multiplexing and higher-order modulation formats. The FSON architecture allows that the numerous laser sources of optical transceivers within a data center can be quasi-synchronized by means of a tree-distributed homology architecture. In conjunction with our proposed novel pilot-tone assisted Costas Loop for an analog coherent receiver, we achieve a record dual-polarization 224-Gb/s 16-QAM 5-km mismatch transmission with reset-free carrier phase recovery in the optical domain. Our proposed DSP-free analog coherent detection system based on the FSON makes it a promising solution for next-generation low-power, high-capacity coherent data center interconnects (DCI).
Decoding the effect of fibroblast heterogeneity on prognosis and drug resistance in high-grade serous ovarian cancer through tumor evolution analysis
Authors: wang tingjie
Published: August 2024

Tumor heterogeneity is associated with poor prognosis and drug resistance, leading to therapeutic failure. Here, we used tumor evolution analysis to determine the intra- and intertumoral heterogeneity of high-grade serous ovarian cancer (HGSOC) and analyze the correlation between tumor heterogeneity and prognosis, as well as chemotherapy response, through single-cell and spatial transcriptomic analysis. We collected and curated 28 HGSOC patients’ single-cell transcriptomic data from five datasets. Then, we developed a novel text-mining-based machine-learning approach to deconstruct the evolutionary patterns of tumor cell functions. We then identified key tumor-related genes within different evolutionary branches, characterized the microenvironmental cell compositions that various functional tumor cells depend on, and analyzed the intra- and intertumoral heterogeneity as well as the tumor microenvironments. These analyses were conducted in relation to the prognosis and chemotherapy response in HGSOC patients. We validated our findings in two spatial and seven bulk transcriptomic datasets (total: 1,030 patients). Using transcriptomic clusters as proxies for functional clonality, we identified a significant increase in tumor cell state heterogeneity that was strongly correlated with patient prognosis and treatment response. Furthermore, increased intra- and intertumoral functional clonality was associated with the characteristics of cancer-associated fibroblasts (CAFs). The spatial proximity between CXCL12-positive CAFs and tumor cells, mediated through the CXCL12/CXCR4 interaction, was highly positively correlated with poor prognosis and chemotherapy resistance in HGSOC. In this study, we constructed a panel of 24 genes through statistical modeling that correlate with CXCL12-positive fibroblasts and can predict both prognosis and the response to chemotherapy in HGSOC patients.
Huge single bladder stone: A case report from Leku general hospital, Sidama, Ethiopia
Authors: Kibret Asfaw , Asres Muluken , Sime Bizuneh , Adisu Derbe
Published: August 2024

Urinary tract calculi are common but huge bladder stones weighing more than 100gm are the rarest occurrences. This is a case of huge bladder stone in 22yrs old adult who presented with acute urinary retension who had repeated urinary tract infection but used to take oral antibiotics from his nearby health centers. Otherwise he has no predisposing infra vesical obstructive causes. 800gm single stne removed by oprn cystolithotomy and few reported cases available from Ethiopia.
Discovering methylation markers and development of a sense-antisense and dual-MGB probe PCR assay in plasma for colorectal cancer early detection
Authors: Zhao Yanteng , Wang Zhijie , Yu Qiuning , Liu Xin , Liu Xue , Dong Shuling , Lv Xianping , Zhang Tiao , Zhou Dihan , Yang Qiankun
Published: August 2024

Background: Screening for colorectal cancer (CRC) using plasma cell-free DNA (cfDNA) methylation is more challenging than stool testing due to the low abundance of cfDNA. Therefore, the development of signal amplification assays based on appropriate markers is essential to increase sensitivity.
Methods: A total of 17 existing 450K microarray datasets including tissue, healthy white blood cell (WBC) and plasma cfDNA data from public databases were used to identify differentially methylated CpGs (DMCs) common to CRC and adenoma. The methylation status of candidate DMCs was confirmed by Sanger sequencing with CRC and normal tissues. A sense-antisense and dual MGB probe (SADMP) assay was then developed. Subsequently, the biomarkers were validated in 712 plasma samples using the SADMP method.
Results: A total of 2237 DMCs showed overlap between the cancer vs. normal and adenoma vs. normal groups. Of these, 75 were hypomethylated in 30 other non-CRC cancers. After LASSO regression, this number was reduced to eight. Two of these, NTMT1 and MAP3K14-AS1, were identified as promising candidate markers following WBC validation and primer/probe design evaluation. The SADMP technology demonstrated the ability to amplify the detection signal to approximately twice the original level. Overall, the dual-target SADMP assay demonstrated a sensitivity of 84.8% for CRC (stage I: 75.0%), a sensitivity of 32.0% for advanced adenomas (AA), and a specificity of 91.5% in controls.
Conclusions: The dual-target assay demonstrated high performance for CRC and AA detection in plasma-based tests, suggesting that it may serve as a promising noninvasive tool for CRC detection.
Multiscale Deep Learning Convolutional Neural Network for ADHD Detection using EEG
Authors: Sanchis Javier , Kechadi Tahar , Teruel Miguel A. , Trujillo Juan
Published: August 2024

Background: Attention-Deficit Hyperactivity Disorder (ADHD) is one of the mostcommon neuro-developmental disorders diagnosed in childhood. The medical diagnosis of ADHDtypically involves extensive time-consuming interviews and tests. Electroencephalography (EEG) is amethodology to record brain activity. In recent years, several Machine Learning (ML) models havebeen developed for diagnosing ADHD using EEG data. However, they are unreliable for two reasons: 1)Performing manual pre-processing and feature selection are error-prone, and 2) training and testingthe model using the same subjects is defective. The main goal of this study is to develop a morerobust and reliable learning model for detecting ADHD.
Methods: To achieve this objective, we developed an effective Deep-Learning MultiscaleConvolutional Neural Network called EEG-MSCNet. We used a Leave-One-Out subject-cross-validation approach validation to obtain more reliable results.
Results: Our EEG-MSCNet model achieved an accuracy of 88.42%, surpassing the previous state-of-the-art models, including EEGNet with an accuracy of 83%. It features robust, automatic feature extraction directly from raw EEG signals. To support transparency and reproducibility, we have made the source code, databases, and logs publicly available, facilitating validation and further research.
Conclusion: The proposed model achieved the best f1-score and accuracy compared withstate-of-the-art DL models. Second, an automatic end-to-end classification process could beperformed using our proposal. Consequently, it can be applied on an outpatient basis, allowingphysicians to follow their patients more closely and, as a result, speed up their treatment time.
Multi-Performance Optimization of the Mechanical Characteristics of Basalt Fiber and Silicon Carbide-Filled Aluminum Matrix Composites
Authors: Veeranaath V. V. , Dinesh S.G. , Natarajan G.
Published: August 2024

In the existing state, aluminum metal matrix composites (AlMMCs) are a category of materials that have successfully fulfilled the majority of demanding requirements in applications where moderate strength, high stiffness, and lightweight are necessary. This paper is focused on processing aluminum hybrid composites by reinforcing the aluminum alloy with a novel combination of fillers: basalt fibers and silicon carbide via stir casting. The main aim is to study the impact of processing conditions on the properties of the developed composite. Nine samples are produced by varying the reinforcement content, stirring rate, and duration based on the L9 Taguchi Array. SEM analysis is utilized to examine the microstructure of the developed composites. The samples were also machined and tested for their mechanical, physical, and wear behavior as per ASTM standards. The maximum density and hardness of 2883.3 kg/m3 and 45.6 HRB, respectively, are observed at higher filler content conditions. In contrast, the minimum specific wear rate, maximum ultimate tensile, and impact strength of 1.86·10–5 mm3/(N·m), 263.5 MPa, and 93 N/mm are observed in higher stirring duration conditions. So, to avoid conflicting combinations of optimal input factors, grey relational analysis (GRA) tied with principle component analysis (PCA) is employed to determine the multi-objective performance parameter and the optimal combination of input factors for better response. Confirmatory tests were also performed to verify and validate the same. ANOVA analysis is also utilized to assess the significance of the process parameters on the responses.
An Ethereal Study of Drakshavaleha and Punarnavadi Mandura in Managing Pandu Roga with Special Reference to Iron Deficiency Anemia
Authors: Joshi Pashmina , Sud Sushant , Prajapati Dilip , Ghetiya Hitesh , Nandakumar Aparna
Published: August 2024

Introduction: Anemia is a public health problem affecting both developing and developed countries with major consequences for human health as well as social and economic development. We can find the references for numerous medications indicated for the treatment of Pandu in various treatises of Ayurveda. The formulations Punarnavadi Mandura and Drakshavaleha when administered in combination are supposed to act as iron and nutrition supplement, which will improve the overall health of the patients especially females of reproductive age group. Aim: The aim of the study was to evaluate the probable mode of action of Drakshavaleha and P. Mandura in Pandu Roga w.s.r to iron deficiency anemia. Materials and Methods: The information in this article is centered on various articles published in indexed and non-indexed journals of Ayurveda and Contemporary medical sciences, Ayurveda Samhitas, and their respective commentaries and textbooks of concerned subjects of both Ayurveda and Modern Medicine. Results: The ingredients of Drakshavaleha and P. Mandura mainly possess activities such as immunomodulatory, anti-oxidant, and bio-availability enhancers which can act collectively against the symptomatology of P. roga. Ingredients such as ManduraBhasma, Gomutra, Punarnava, Haridra, and Guda are proven to enhance the process of erythropoiesis. Conclusion: Based on the review, it can be considered that P. Mandura, a poly herb-mineral formulation and Drakshavaleha, a Naimittika Rasayana which can act as nutritional supplement, can counteract most of the pathological manifestations related to Pandu.
Right-Sided Pleural Effusion Secondary to Acute Pancreatitis: A Rare Entity
Authors: Lalsiddiqui Omarbi , Hasan Ashfaq , Abdullah Fahad , Naveed Aleemuddin , Mahmood Syed , Ali Moid Mir Siddiq
Published: August 2024

Pleural effusion as a consequence of acute pancreatitis is transient, usually left-sided, and straw colored and accounts for 1% of all cases.[1] Rarely, it can be right-sided, causing difficulty in establishing the diagnosis, especially if new symptoms are disproportionate to the pre-existing symptoms. We present a case of a young chronic alcoholic male patient with gross right-sided pleural effusion and moderate ascites.