bluuebunny/crossref_metadata_2025 huggingface dataset:
Ecology meets reproductive medicine in HIV prevention: the case for geography-informed approaches for bacterial vaginosis in Africa
Authors: Passmore Jo-Ann S. , Ngcapu Sinaye , Gitome Serah , Kullin Brian R. , Welp Kirsten , Martin Darren P. , Potloane Disebo , Manhanzva Monalisa T. , Obimbo Moses M. , Gill Katherine , Fevre Mellissa Le , Happel Anna-Ursula , Jaspan Heather B. , Kasaro Margaret , Bukusi Elizabeth A.
Published: November 2024

Purpose of review

Women in Africa bear the burden of the HIV epidemic, which has been associated with the high prevalence of bacterial vaginosis (BV) in the region. However, little progress has been made in finding an effective cure for BV. Drawing on advances in microbiome-directed therapies for gastrointestinal disorders, similar live-biotherapeutic based approaches for BV treatment are being evaluated. Here, we summarize current knowledge regarding vaginal microbiota in BV, explore geographical differences in vaginal microbiota, and argue that novel BV therapeutics should be tailored specifically to meet the needs of African women.

Recent findings

Cervicovaginal microbiota dominated by Lactobacillus crispatus are optimal, although these are uncommon in African women. Besides socio-behavioural and environmental influences on the vaginal microbiota, host and microbial genetic traits should be considered, particularly those relating to glycogen metabolism. Novel microbiome-directed approaches being developed to treat BV should employ transfers of multiple microbial strains to ensure sustained colonization and BV cure.

Improving the efficacy and durability of BV treatment with microbiome-directed therapies by appropriately accounting for host and microbial genetic factors, could potentially reduce the risk of HIV infection in African women.
Knowledge and perceptions of blood donors of the Western Cape Blood Services, South Africa, toward vaginal sample donation for biobanking
Authors: Claassen-Weitz Shantelle , Kullin Brian , du Toit Elloise , Gardner-Lubbe Sugnet , Passmore Jo-Ann S. , Jaspan Heather , Happel Anna-Ursula , Bellairs Greg , Hilton Caroline , Chicken Anika , Welp Kirsten , Livingstone Hannah , Brink Adrian
Published: November 2024

Introduction

Depletion of Lactobacillus species and an overgrowth of anaerobes in the vaginal tract bacterial vaginosis (BV)], is associated with non-optimal reproductive health outcomes, and increased susceptibility to sexually transmitted infections (STIs). BV is currently treated with antibiotics, although these provide suboptimal cure levels and high recurrence rates. Vaginal microbiota transplantation (VMT), the transfer of vaginal fluid from healthy donors with an optimal vaginal microbiota to a recipient with BV, has been proposed as an alternative treatment strategy.

Methods

Here, we investigated knowledge and perceptions of blood donors to the concept of an optimal vaginal microbiome and VMT via the Western Cape Blood Service (WCBS) clinics in Cape Town, South Africa, by a self-administered questionnaire.

Results & discussion

Analysis of responses from 106 eligible women showed that 86% (91/106) would consider donating samples. Responses significantly associated with willingness to donate vaginal samples included: (1) belief that helping others outweighs the inconvenience of donating vaginal sample (p = 1.093e−05) and (2) prior knowledge of the concept of a healthy vaginal microbiome (p = 0.001). Most potential donors (59/91; 65%) were willing to receive a VMT themselves if needed. Participants who were unwilling to donate vaginal samples (15/106; 14%) indicated that vaginal sample collection would be unpleasant and/or embarrassing. The benefits of a collaboration with WCBS for this project include the naturally altruistic nature of blood donors, the constant in-flow of donors to WCBS clinics, and the infrastructure and logistical aspects in place. Data from this observational study highlight factors affecting the willingness of blood donors to become vaginal sample donors.
Tea and other diet-related practices in relation to sleep health in midlife women from Mexico City: qualitative and quantitative findings
Authors: Zamora Astrid N. , Roberts Elizabeth F. S. , Sharp Lilian , Borra Catherine , Lee Jennifer , Téllez-Rojo Martha M. , Peterson Karen E. , Torres-Olascoaga Libni A. , Cantoral Alejandra , Jansen Erica C.
Published: November 2024

Purpose

Little is known regarding women's lived experiences of how diet impacts sleep. Based on ethnographic interviews among working-class women from Mexico City, our primary aim was to identify themes related to diet and sleep among midlife women. Informed by qualitative analyses, a secondary aim was to examine associations between tea and sleep duration in a broader cohort.

Materials and methods

We conducted a cross-sectional study that entailed in-depth ethnographic interviews about sleep and other behaviors, including diet, with a purposive sample of 30 women from the ELEMENT cohort. Ethnographer field notes and transcripts were analyzed using thematic analysis. Guided by findings from the interviews demonstrating that tea consumption might be associated with sleep, we conducted post-hoc analyses of the relationship between tea and sleep duration using data from food frequency questionnaires and actigraphy, respectively, in the broader cohort (n = 406).

Results

The mean (SD) age of the ethnographic sample was 50.0 (9.0) years. The top noted theme was the use of herbal tea (in Spanish infusion) to improve sleep; most women (29/30) discussed herbal teas, characterizing them as a “natural remedy” to facilitate sleep. The mean (SD) age of the broader sample (N = 406) was 48.4 (6.2) years. Post-hoc analyses revealed positive associations between tea without sugar (though not necessarily herbal tea) and sleep duration. We found that every serving of tea without sugar consumed was associated with an 18.0 min per night [β (SE) = 18.0 (7.8); p = 0.022] and a 13.4 min per night [β (SE) =13.4 (5.6); p = 0.017] increase in weekend and 7-day sleep duration, respectively.

Conclusions

Within a sample of 30 midlife women, dietary practices were described in relation to sleep, specifically the consumption of herbal teas to promote sleep.
Modeling water availability under climate change scenarios: a systemic approach in the metropolitan area in Morelos, México
Authors: González-Zurita Jazmín , Oswald-Spring Úrsula
Published: November 2024

The research investigates integrated water management with complex socio-environmental interactions in worsening climate change scenarios. The proposed methodology involves the integration of Atmosphere–Ocean General Circulation Models (AOGCM) with Water Evaluation and Planning models (WEAP) to ensure water availability in the future. Two Shared Socioeconomic Pathways (SSP) integrate environmental, socioeconomic, and political elements under climate change scenarios with greater rainfall variability, extreme droughts, and floods in the metropolitan area of Morelos, located in the Center of México. Water availability in this region, along with population growth, industrialization, service activities, and agriculture, depends on forest conservation in the Ravines System of Northwest Morelos (RSNM). Public policy lacks interdisciplinary socio-environmental development, which prioritizes unsustainable economic growth overexploiting aquifers and polluting rivers. Official data from national and state governments do not reflect water conditions, and aquifer statistics date back decades. The majority of the analyzed models predict a delay in the monsoon, higher temperatures, extreme climate events, depletion of groundwater, and severe water scarcity during the hot months, rendering them unable to meet the increasing demand. This research provides valuable insights into the complex socioeconomic dynamics of a region with future water scarcity, which could be useful for similar conditions in the Global South.
“No one talks about it”: using emotional methodologies to overcome climate silence and inertia in Higher Education
Authors: Pigott Anna , Nuuttila Hanna , Thomas Merryn , Smith Fern , Bohata Kirsti , Murray Tavi , Palser Marega , Holmes Emily , Elias Osian
Published: November 2024

Higher Education (HE) is, at best, struggling to rise to the challenges of the climate and ecological crises (CEC) and, at worst, actively contributing to them by perpetuating particular ways of knowing, relating, and acting. Calls for HE to radically transform its activities in response to the polycrises abound, yet questions about how this will be achieved are often overlooked. This article proposes that a lack of capacity to express and share emotions about the CEC in universities is at the heart of their relative climate silence and inertia. We build a theoretical and experimental justification for the importance of climate emotions in HE, drawing on our collective experience of the Climate Lab project (2021–2023), a series of in-person and online workshops that brought together scientists, engineers, and artists. We analyse the roles of grief, vulnerability, and creativity in the conversations that occurred, and explore these exchanges as potential pathways out of socially organised climate denial in neoliberal institutions. By drawing on the emerging field of “emotional methodologies,” we make a case for the importance of emotionally reflexive practices for overcoming an institutionalised disconnect between feeling and knowing, especially in Western-disciplinary contexts. We suggest that if staff and students are afforded opportunities to connect with their emotions about the CEC, then institutional transformation is (a) more likely to happen and be meaningfully sustained and (b) less likely to fall into the same problematic patterns of knowledge and action that perpetuate these crises. This profound, sometimes uncomfortable, emotionally reflexive work is situated in the wider context of glimpsing decolonial futures for universities, which is an integral step towards climate and ecological justice.
Deployment of power-to-protein technology in Ethiopia to provide drought-related emergency relief and mitigate food insecurity
Authors: Buchner M. , Nguyen H. H. , Angenent L. T. , Zarfl C. , Usack J. G.
Published: November 2024

Food insecurity in Ethiopia is an immediate humanitarian crisis that is expected to worsen due to population growth and climate change. This study applied GIS-based approaches to evaluate the feasibility of deploying an emergent type of single-cell protein (SCP) technology to supplement the nutritional needs of Ethiopian citizens who are most vulnerable to drought. The technology—power-to-protein (PtP)—uses H2 and O2 from water electrolysis and CO2 from woody biomass combustion in a two-stage bioprocess to produce nutrient-rich protein powder for human consumption. Population density, land use, and other geographical data were used to identify optimal site locations for these PtP systems based on two deployment strategies: large centralized plants vs. small decentralized units. The model also accounted for biomass availability, collection, and distribution logistics. The analysis revealed three sites that are both (highly) vulnerable/food-insecure and accessible within walking distance. The identified sites are proximate to the urban areas of Mekele in northern Ethiopia, Addis Ababa in central Ethiopia, and Hawasa south of Addis Ababa. If centralized PtP were deployed, the protein requirements of these populations could be sustained for several months, assuming a modest biomass collection radius of 35 km. Decentralized PtP deployment was similarly effective, requiring a distribution density of 5.4–11.0 PtP units per km2 under conservative estimates and 0.76–1.1 units per km2 under optimistic estimates. Lastly, a theoretical comparison showed that PtP is more efficient than conventional agricultural food production regarding biomass-to-protein conversion yields. Overall, our study suggests that PtP technology would be a feasible approach to supplement the nutritional needs of Ethiopian people in times of drought-related emergencies. However, given logistical limitations and considering social preference factors, it would be more practical to implement PtP in conjunction with standard emergency food aid measures.
Impact of seed rate and time of sowing on rice fallow crops and their sustainable production system in machine-harvested rice fields
Authors: Jaya Singh Devi Geethika , Elangovan Subramanian , Paramasivam Arunachalam , Arumugam Gurusamy , Basir Ahmed Bhakiyathu Saliha , Gurunathan Selvarani , Krishnan Jothilakshmi , Arumugam Sathishkumar
Published: November 2024

A field experiment was conducted at the Department of Agronomy, Agricultural College and Research Institute, Tamil Nadu Agricultural University, Madurai to study the performance of rice fallow crops in machine-harvested rice fields. The primary objective of this study was to determine the optimal seed rate and the time of sowing rice fallow crops in machine-harvested rice fields. Rice fallow crop cultivation is the most significant low-cost production system in the delta region. However, the sustainability of the system is uncertain in the context of mechanical harvesting of rice using heavy machinery. The crops selected for the experimental trial were black gram (Vigna mungo (L.) Hepper.), sesame (Sesamum indicum), and proso millet (Panicum miliaceum). The field experiment was conducted using a strip plot design. Rice fallow crops were arranged in vertical plots, while various seed rates and sowing timings were arranged in horizontal plots. The results indicated that the sowing time and seed rate significantly influenced the growth and development of rice fallow crops in machine-harvested rice fields. On the day of rice harvest, a 20% increase in seed rate (36 kg ha−1) resulted in greater grain and straw yield among the black gram treatments. The increased seed rate compensated for the damage caused by mechanical harvesting on the day of the harvest when a combine harvester was utilized, increasing the yield and sustainability of the rice fallow crops.
Role of lymphadenectomy in advanced-stage ovarian cancer: a meta-analysis
Authors: Ronsini Carlo , Pasanisi Francesca , Andreoli Giada , De Franciscis Pasquale , Cobellis Luigi , Vizzielli Giuseppe , Restaino Stefano , Romeo Paola , Palmara Vittorio , Cianci Stefano
Published: November 2024

Background

Epithelial Ovarian Cancer is one of the most lethal cancers among gynecologic malignancies. The disease metastasizes mainly through the peritoneal spread in the abdomen and through the lymphatic system. Lymph node involvement is present in 48% up to 75% of cases of advanced-stage ovarian cancer (ASOC). In this context, the aim of our study is to analyze the current literature on the topic and to investigate survival outcomes in patients affected by advanced-stage ovarian cancer undergoing lymphadenectomy.

Methods

Following the recommendations in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement, we systematically searched the Pubmed and Scopus databases in June 2022 since the first publication. We made no limitations on the country. We included the studies containing disease-free survival (DFS) and Overall Survival (OS) data. Only comparative studies with a direct comparison between Lymphadenectomy and its avoidance were included for meta-analysis.

Results

18 studies fulfilled the inclusion criteria. The overall OS, DFS, and RR were comparable in the studies. 26965 patients were enrolled in the meta-analysis. Patients were analyzed concerning OS and DFS. Meta-analysis highlighted statistically significant higher OS than the lymphadenectomy group (RR 1.31 [95% CI 1.16–1.48] p < .00001), and no statistically different DFS RR 1.23 [95% CI 0.82–1.92] p = 0.25).

Conclusion

Our analysis showed a protective role of lymphadenectomy in advanced ovarian cancer, with a reduction in death risk.

Systematic Review Registration:www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022341646, Identifier CRD42022341646.
Efficacy and cost-effectiveness analysis of flexible ureteroscopic lithotripsy with TFDS in the treatment of urolithiasis
Authors: Gao Xiang , Han Peng , Zong Yiping , Wang Zijie , Zhang Wei , Lu Pei
Published: November 2024

Background

At present, there is no effective drug to remove residual stones. Total flavonoids of desmodium styracifolium (TFDS) is an innovative traditional Chinese medicine listed in 2022, which can be used to treat ureteral calculi. This study was to explore the effectiveness and economic value of TFDS in the treatment of residual stones after flexible ureteroscopic lithotripsy (FURL).

Methods

A total of 161 patients who underwent unilateral ureteroscopic lithotripsy for urinary calculi by the same surgeon in our center from May 2022 to February 2024 were retrospectively included. According to the use of stone-removal drugs after operation, patients were divided into TFDS group and Control group. The residual stones showed by x-ray plain film when the double J tube was removed were compared between the two groups, and the economic benefits of TFDS were analyzed by cost-benefit analysis.

Results

The data of 161 patients were collected, including 80 cases in TFDS group and 81 cases in Control group. The SFR rates at the endpoint of follow-up in TFDS group and Control group were 98.75% and 88.88%, respectively. In the subgroup analysis of post-operative residual stones, the stone clearance rate of TFDS was higher (47.62% vs. 18.18%). No obvious adverse events were reported in two groups. The cost/benefit ratio of TFDS was lower (20.43 vs. 32.57). Cost of TFDS was increased by ¥12.97 for each additional unit of total effective rate.

Conclusion

The combination of dusting FURL and TFDS can effectively remove the urolithiasis when compared to only FURL, which showed highly economic benefits.
Heterogenous bioluminescence patterns, cell viability, and biofilm formation of Photobacterium leiognathi strains exposed to ground microplastics
Authors: De Jesus Rener , Iqbal Sameera , Mundra Sunil , AlKendi Ruwaya
Published: November 2024

Microplastics (MPs) have been detected in various aquatic environments and negatively affect organisms, including marine luminous bacteria. This study investigated the differences in bioluminescence patterns, cell viability, and biofilm formation of Photobacterium leiognathi strains (LB01 and LB09) when exposed to various concentrations of ground microplastics (GMPs; 0.25%, 0.50%, 1%, or 2% [w/v] per mL) at 22°C or 30°C for 3.1 days (75 h) and 7 days. The strains exhibited heterogenous responses, including variable bioluminescence patterns, cell viability, and biofilm formation, due to the GMPs having effects such as hormesis and bioluminescence quenching. Moreover, the bioluminescence and cell viability differed between the two strains, possibly involving distinct cellular mechanisms, suggesting that GMPs affect factors that influence quorum sensing. Furthermore, the biofilm formation of LB01 and LB09 was observed following exposure to GMPs. Both strains showed increased biofilm formation at higher GMP concentrations (1% and 2%) after 3.1 days at 30°C and 22°C. However, in the 7-day experiment, LB01 significantly (p < 0.05) increased biofilms at 22°C, while LB09 significantly (p < 0.05) produced biofilms at 30°C. These findings highlight the strain-specific responses of Phb. leiognathi to MP pollutants. Therefore, this study underscores the importance of evaluating MPs as environmental stressors on marine microorganisms and their role in the ecophysiological repercussions of plastic pollution in aquatic environments.
Development of a deep learning model for automatic detection of narrowed intervertebral disc space sites in caudal thoracic and lumbar lateral X-ray images of dogs
Authors: Park Junseol , Cho Hyunwoo , Ji Yewon , Lee Kichang , Yoon Hakyoung
Published: November 2024

Intervertebral disc disease is the most common spinal cord-related disease in dogs, caused by disc material protrusion or extrusion that compresses the spinal cord, leading to clinical symptoms. Diagnosis involves identifying radiographic signs such as intervertebral disc space narrowing, increased opacity of the intervertebral foramen, spondylosis deformans, and magnetic resonance imaging findings like spinal cord compression and lesions, alongside clinical symptoms and neurological examination findings. Intervertebral disc space narrowing on radiographs is the most common finding in intervertebral disc extrusion. This study aimed to develop a deep learning model to automatically recognize narrowed intervertebral disc space on caudal thoracic and lumbar X-ray images of dogs. In total, 241 caudal thoracic and lumbar lateral X-ray images from 142 dogs were used to develop and evaluate the model, which quantified intervertebral disc space distance and detected narrowing using a large-kernel one-dimensional convolutional neural network. When comparing veterinary clinicians and the deep learning model, the kappa value was 0.780, with 81.5% sensitivity and 95.6% specificity, showing substantial agreement. In conclusion, the deep learning model developed in this study, automatically and accurately quantified intervertebral disc space distance and detected narrowed sites in dogs, aiding in the initial screening of intervertebral disc disease and lesion localization.
Induction of CD4 T cell memory responses following BCG vaccination in cattle
Authors: Sterle Haley M. , Putz Ellie J. , Olsen Steven C. , Boggiatto Paola M.
Published: November 2024

Mycobacterium bovis, the causative agent of bovine tuberculosis (bTB), is a zoonotic pathogen that contributes to economic losses in the cattle industry and poses a public health risk worldwide. Bacillus Calmette-Guerin, or BCG, is a live attenuated strain of M. bovis that is used for human vaccination against tuberculosis and is considered a potential vaccine candidate against bTB. However, BCG affords widely variable levels of protection against challenge and interferes with current diagnostic methods, and as such, it is not currently approved for use as a livestock or wildlife vaccine in the United States. Many efforts have been made to develop bTB vaccines that are reliable and do not interfere with diagnostic testing, but BCG continues to be the most effective option. Previous work has shown that a T helper 1 immune response is essential for protection against virulent M. bovis infection, characterized by CD4+ central and effector memory T cells. In an effort to identify an efficacious bTB intervention strategy, the study presented here used an in vitro recall response assay and concurrent evaluation of CD4+ T cell proliferation and cytokine production to characterize the surface and functional phenotypes of memory responses to BCG vaccination in cattle. Our findings enhance understanding of the bovine immune response to BCG and provide insights into the development of improved vaccines for the control of bTB.
Effects of surface sterilization of fertile eggs on the yolk microbiota during the chicken embryo development
Authors: Ding Peng , He Xi , Li Minxi , Jiang Sai , Peng Yanmei
Published: November 2024

Surface sterilization of the fertile eggs is a common process for commercial broiler breeding to avoid pathogenic bacterial infections before incubation. However, it is also possible to remove the beneficial microbes that might contribute to the development of chicken embryos. Thus, we established a model to mimic surface sterilization in the laboratory by rubbing fertile eggs with 70% ethanol and investigated the effect of eggshell surface sterilization on the yolk microbiota and its potential role in chicken (Gallus gallus) embryo development. In total, 460 Ross 308 fertile eggs were randomly divided equally into the eggshell surface sterilized group (CS, commercial egg sterilization group) and the eggshell surface unsterilized group (CC, commercial egg control group). The shell surface of group CS was sterilized with 70% alcohol before incubation (E0, embryonic stage), while that of group CC was not sterilized before incubation. At each sampling day (E0, E07, E15, and E21), 24 fertile eggs from each of the two groups were randomly selected to collect the yolk samples and weigh the embryos. The results showed that the surface sterilization of eggshells before incubation improved the development of chicken embryos from E15 to E21 but reduced the diversity of the yolk microbiota. In the whole process of embryogenesis, the relative abundance of Firmicutes, Bacteroidetes, and Actinobacteria in the egg yolk of group CS was lower than that of group CC before incubation. Indeed, the surface sterilization of fertile eggs significantly reduced the relative abundance of Staphylococcus saprophyticus and other pathogenic bacteria in the yolk, which may result in the better development of chicken embryos.
How Dryland-to-Paddy Conversion Affects the Carbon Emission Efficiency in the Short Term: Evidence from Soil Carbon-Fixing Bacteria and the Carbon Pool in an Experimental Study
Authors: Yang Yongjun , Gong Renjie , Pan Xuyue , Li Xiaoxiao , Hua Ziyi , Ma Jing , Duan Xueying , Chen Fu
Published: November 2024

To amplify grain production capacity, a global trend is emerging in which many regions are transitioning from dependence on rainfall to irrigated agriculture. An illustrative example of this form of land consolidation is the conversion from dryland to paddy fields, which has changed the ecological environment of farmlands, resulting in significant effects on carbon fixation and emissions. However, there currently exists a deficiency in essential understanding regarding the short-term effects of dryland-to-paddy conversion on ecological processes tied to soil carbon-fixation bacteria and carbon emission efficiency (CEE). Therefore, field monitoring and high-throughput sequencing were carried out to monitor the changes in soil carbon emission efficiency and carbon-fixation bacteria before and after the conversion. Our results indicate that while conversion from dryland to paddy fields can boost grain yield, it also results in an increase in soil carbon emissions and a consequent decrease of 25.78% in carbon emission efficiency. This transition has resulted in an increased soil carbon-fixing bacterial alpha diversity index and enhanced network complexity. The structural equation model indicates that changes in soil environmental factors, especially soil moisture, soil organic carbon (SOC), readily oxidizable carbon (ROC), and carbon-fixing bacteria, are the primary drivers of CEE variation (p < 0.05). Given the critical role that the soil carbon cycle plays in global climate change, there is a pressing need for increased global attention towards the carbon emissions triggered by the transition from rainfed to irrigated agriculture.
Evaluating Dietary Red Lentil Screenings on Performance, Antioxidant Status, Caecal Environment, and Intestinal Morphometric Features in Rabbits
Authors: Pugliese Gianluca , Losacco Caterina , Passantino Letizia , Lentini Giovanni , Cavalluzzi Maria M. , Schiavitto Michele , Tarricone Simona , Laudadio Vito , Tufarelli Vincenzo
Published: November 2024

Among the goals of global environmental policies, one is to achieve a critical rethinking of the agro-industrial production chain aimed at enhancing its sustainability and resilience while addressing its environmental impact. Lentils are widespread worldwide and are consumed as part of traditional dishes, and their health-promoting benefits are currently well recognized. Their industrial processing for human consumption implies the generation of different by-products which can be used as promising alternative feedstuff. Calling for the future sustainable development of rabbit farming, the present study questions the dietary inclusion of red lentil screenings (RLS) as an upcycling strategy for this by-product, as well as to ease the challenges faced by the rabbit-farming system. A total of 120 male Bianca Italiana breed growing rabbits aged 42 days were allotted to three dietary treatments containing different levels of RLS: 0 (RLS0), 5 (RLS5), or 10% (RLS10), respectively, for 6 weeks. At 84 days (slaughter age), meat, plasma, and intestinal samples were collected. The RLS inclusion showed no adverse effects on growth performance. However, significant differences were found in the meat fatty acid profile, where both RLS5 and RLS10 groups showed reduced C18:0 percentage and higher MUFA content owing to an increase in C18:1 n-9; moreover, RLS5 showed a significant increase in C16:1 trans. On the other hand, only RLS10 recorded a significant reduction in the PUFA total content due to decreased single unsaturated fatty acid (C18:2 n-6; C20:3 n-6; C22:5 n-3). Dietary RLS significantly decreased serum total cholesterol, LDL, and HDL, along with an enhancement of the overall serum antioxidant capacity. The results regarding the rabbit caecal characteristics and microbial population were found to be similar among the groups. However, referring to histomorphometric measurements, both RLS5 and RLS10 groups displayed significant increases in villus height and an improved villus height to crypt depth ratio. In conclusion, up to 10% RLS in the diets rabbits can be considered an effort-effective feeding strategy to modulate rabbit meat fatty acid profiles, to enhance the endogenous antioxidant capacity, and to improve the serum lipid profile and intestinal morphology.
FRESH: Fusion-Based 3D Apple Recognition via Estimating Stem Direction Heading
Authors: Son Geonhwa , Lee Seunghyeon , Choi Yukyung
Published: November 2024

In 3D apple detection, the challenge of direction for apple stem harvesting for agricultural robotics has not yet been resolved. Addressing the issue of determining the stem direction of apples is essential for the harvesting processes employed by automated robots. This research proposes a 3D apple detection framework to identify stem direction. First, we constructed a dataset for 3D apple detection that considers the 3-axis rotation of apples based on stem direction. Secondly, we designed a 3D detection algorithm that not only recognizes the dimensions and location of apples, as existing methods do, but also predicts their 3-axis rotation. Furthermore, we effectively fused 3D point clouds with 2D images to leverage the geometric data from point clouds and the semantic information from images, enhancing the apple detection performance. Experimental results indicated that our method achieved AP@0.25 89.56% for 3D detection by considering apple rotation, surpassing the existing methods. Moreover, we experimentally validated that the proposed loss function most effectively estimated the rotation among the various approaches we explored. This study shows the effectiveness of 3D apple detection with consideration of rotation, emphasizing its potential for practical application in autonomous robotic systems.
Design of an Autonomous Orchard Navigation System Based on Multi-Sensor Fusion
Authors: Su Zhengquan , Zou Wei , Zhai Changyuan , Tan Haoran , Yang Shuo , Qin Xiangyang
Published: November 2024

To address the limitations of traditional GNSS-based navigation systems in orchard environments, we propose a multi-sensor fusion-based autonomous navigation method for orchards. A crawler-type agricultural platform was used as a test vehicle, and an autonomous orchard navigation system was constructed using a 2D LiDAR, a dynamic electronic compass, and an encoder. The proposed system first filters LiDAR point cloud data and uses the DBSCAN–ratio–threshold method to process data and identify clusters of tree trunks. By matching the center coordinates of trunk clusters with a fruit tree distribution map, the platform’s positional measurements are determined. An extended Kalman filter fusion algorithm is then employed to obtain a posterior estimate of the platform’s position and pose. Experimental results demonstrate that in localization accuracy tests and navigation tests, the proposed system provides high navigation accuracy and robustness, making it suitable for autonomous walking operations in orchard environments.
Increased Levels of Anti-Anisakis Antibodies During Hospital Admission in Septic Patients
Authors: Andreu-Ballester Juan Carlos , Navarro Amparo , Arribas Miguel Angel , Rico Moises , Albert Laura , García-Ballesteros Carlos , Galindo-Regal Lorena , Sorando-Serra Rosa , López-Chuliá Francisca , Peydro Federico , Rodero Marta , González-Fernández Juan , Cuéllar Carmen
Published: November 2024

Background/Objectives: In a previous study, we described elevated anti-Anisakis IgG levels in septic patients in relation to disease severity. In this study, our objective was to analyze the evolution of anti-Anisakis immunoglobulins in septic patients during hospital admission and their association with αβ and γδ T cell subsets. Methods: We recruited 80 subjects: 40 patients with sepsis and 40 controls. αβ and γδ T cells were analyzed using flow cytometry. Apoptosis was also assessed, and anti-Anisakis antibodies were measured by ELISA in the sera of patients with sepsis and controls. Results: In the second analysis (7–10 after sepsis evolution), an increase in all specific antibody isotypes was identified in individuals with septic shock, except IgE. The levels of anti-Anisakis IgG and IgA were higher in the subjects with sepsis in the first analysis and continued to increase in the second analysis compared with the healthy control subjects. There was an increase in anti-Anisakis IgG and IgA levels in surviving patients and an increase in IgA levels in non-surviving patients. A rise in specific IgG and IgE levels was noted in the second analysis of patients with sepsis with αβ CD3+ T cell deficiency. Patients without γδ T cell deficiency had increased anti-Anisakis IgA levels 7–10 days after admission. Conclusions: Our results suggest a previous infection by Anisakis that could be involved in the subsequent septic process and be related to patients who have negative cultures in which the pathogen causing sepsis has not been identified.
Oxidative Stress in Kidney Injury and Hypertension
Authors: Arendshorst Willaim J. , Vendrov Aleksandr E. , Kumar Nitin , Ganesh Santhi K. , Madamanchi Nageswara R.
Published: November 2024

Hypertension (HTN) is a major contributor to kidney damage, leading to conditions such as nephrosclerosis and hypertensive nephropathy, significant causes of chronic kidney disease (CKD) and end-stage renal disease (ESRD). HTN is also a risk factor for stroke and coronary heart disease. Oxidative stress, inflammation, and activation of the renin–angiotensin–aldosterone system (RAAS) play critical roles in causing kidney injury in HTN. Genetic and environmental factors influence the susceptibility to hypertensive renal damage, with African American populations having a higher tendency due to genetic variants. Managing blood pressure (BP) effectively with treatments targeting RAAS activation, oxidative stress, and inflammation is crucial in preventing renal damage and the progression of HTN-related CKD and ESRD. Interactions between genetic and environmental factors impacting kidney function abnormalities are central to HTN development. Animal studies indicate that genetic factors significantly influence BP regulation. Anti-natriuretic mechanisms can reset the pressure–natriuresis relationship, requiring a higher BP to excrete sodium matched to intake. Activation of intrarenal angiotensin II receptors contributes to sodium retention and high BP. In HTN, the gut microbiome can affect BP by influencing energy metabolism and inflammatory pathways. Animal models, such as the spontaneously hypertensive rat and the chronic angiotensin II infusion model, mirror human essential hypertension and highlight the significance of the kidney in HTN pathogenesis. Overproduction of reactive oxygen species (ROS) plays a crucial role in the development and progression of HTN, impacting renal function and BP regulation. Targeting specific NADPH oxidase (NOX) isoforms to inhibit ROS production and enhance antioxidant mechanisms may improve renal structure and function while lowering blood pressure. Therapies like SGLT2 inhibitors and mineralocorticoid receptor antagonists have shown promise in reducing oxidative stress, inflammation, and RAAS activity, offering renal and antihypertensive protection in managing HTN and CKD. This review emphasizes the critical role of NOX in the development and progression of HTN, focusing on its impact on renal function and BP regulation. Effective BP management and targeting oxidative stress, inflammation, and RAAS activation, is crucial in preventing renal damage and the progression of HTN-related CKD and ESRD.
GoalBERT: A Lightweight Named-Entity Recognition Model Based on Multiple Fusion
Authors: Xu Yingjie , Tan Xiaobo , Wang Mengxuan , Zhang Wenbo
Published: November 2024

Named-Entity Recognition (NER) as a core task in Natural Language Processing (NLP) aims to automatically identify and classify specific types of entities from unstructured text. In recent years, the introduction of Transformer architecture and its derivative BERT model has pushed the performance of NER to unprecedented heights. However, these models often have high requirements for computational power and memory resources, making it difficult to train and deploy them on small computing platforms. Although ALBERT as a lightweight model uses parameter sharing and matrix decomposition strategies to reduce memory consumption to some extent consumption, it does not effectively reduce the computational load of the model. Additionally, due to its internal sharing mechanism, the model’s understanding ability of text is reduced leading to poor performance in named-entity recognition tasks. To address these challenges, this manuscript proposes an efficient lightweight model called GoalBERT. The model adopts multiple fusion technologies by integrating a lightweight and efficient BiGRU that excels at handling context into part of the Transformer’s self-attention layers. This reduces the high computational demand caused by stacking multiple self-attention layers while enhancing the model’s ability to process context information. To solve the problem of gradient disappearance and explosion during training, residual connections are added between core layers for more stable training and steady performance improvement. Experimental results show that GoalBERT demonstrates recognition accuracy comparable to standard models with accuracy surpassing ALBERT by 10% in multi-entity type scenarios. Furthermore, compared to standard models, GoalBERT reduces memory requirements by 200% and improves training speed by nearly 230%. Experimental results indicate that GoalBERT is a high-quality lightweight model.
Design of a Noise Mitigation System Using Lightweight Graded Micro-Porous Material
Authors: Kenchappa Bharath , Shivakumar Kunigal
Published: November 2024

Noise is a concern in industries like aviation. Existing acoustic materials have limitations in terms of effective broadband sound attenuation and operating conditions. This work addresses these limitations by designing and developing a noise mitigation system using lightweight graded micro-porous material made from Cenospheres and high-char binder. However, Cenospheres are nearly spherical with rough surfaces, so determining the flow properties of sound propagation is challenging, and direct measurements are expensive. We developed a multivariable-fit inverse method to estimate these properties using an experimental absorption coefficient, validated first with smooth-surface glass beads and then applied to micro-porous material. The determined flow properties were used in a predictive acoustic analysis and validated experimentally. It was demonstrated that a microstructurally graded material is needed to optimize both sound absorption and transmission loss. A graded material system designed for turbofan engine acoustic liners (50 mm thick) met the target broadband sound absorption coefficient of ≥0.50 and transmission loss of ≥20 dB above 500 Hz. The study also highlights that larger particles in thicker layers enhance sound absorption, while a graded micro-structure improves overall acoustic performance. This research offers a novel approach for designing a lightweight acoustic material for aviation, marking a breakthrough in passive noise mitigation technology.
A Framework for Symmetric-Quality S3D Video Streaming Services
Authors: Lee Juhyeon , Lee Seungjun , Kim Sunghoon , Kang Dongwook
Published: November 2024

This paper proposes an efficient encoding framework based on Scalable High Efficiency Video Coding (SHVC) technology, which supports both low- and high-resolution 2D videos as well as stereo 3D (S3D) video simultaneously. Previous studies have introduced Cross-View SHVC, which encodes two videos with different viewpoints and resolutions using a Cross-View SHVC encoder, where the low-resolution video is encoded as the base layer and the other video as the enhancement layer. This encoder provides resolution diversity and allows the decoder to combine the two videos, enabling 3D video services. Even when 3D videos are composed of left and right videos with different resolutions, the viewer tends to perceive the quality based on the higher-resolution video due to the binocular suppression effect, where the brain prioritizes the high-quality image and suppresses the lower-quality one. However, recent experiments have shown that when the disparity between resolutions exceeds a certain threshold, it can lead to a subjective degradation of the perceived 3D video quality. To address this issue, a conditional replenishment algorithm has been studied, which replaces some blocks of the video using a disparity-compensated left-view image based on rate–distortion cost. This conditional replenishment algorithm (also known as VEI technology) effectively reduces the quality difference between the base layer and enhancement layer videos. However, the algorithm alone cannot fully compensate for the quality difference between the left and right videos. In this paper, we propose a novel encoding framework to solve the asymmetry issue between the left and right videos in 3D video services and achieve symmetrical video quality. The proposed framework focuses on improving the quality of the right-view video by combining the conditional replenishment algorithm with Cross-View SHVC. Specifically, the framework leverages the non-HEVC option of the SHVC encoder, using a VEI (Video Enhancement Information) restored image as the base layer to provide higher-quality prediction signals and reduce encoding complexity. Experimental results using animation and live-action UHD sequences show that the proposed method achieves BD-RATE reductions of 57.78% and 45.10% compared with HEVC and SHVC codecs, respectively.
Microstructural Evaluation of Dental Implant Success Using Micro-CT: A Comprehensive Review
Authors: Setiawan Krisnadi , Primarti Risti Saptarini , Sitam Suhardjo , Suridwan Wawan , Usri Kosterman , Latief Fourier Dzar Eljabbar
Published: November 2024

Micro-computed tomography (micro-CT) is an invaluable tool for the evaluation of dental implant success, whereby the assessment of bone microstructure is conducted. This review examines the role of micro-CT in evaluating bone microstructure in dental implants. A review of the current literature reveals that micro-CT enables the accurate measurement of bone volume, trabecular morphology, and connectivity density, all of which play a crucial role in implant stability. The high-resolution three-dimensional visualization capabilities of micro-CT are also beneficial for the analysis of osseointegration and the evaluation of bone augmentation biomaterials. Despite the existence of challenges such as imaging artifacts and limitations in in vivo applications, advancements in sub-micron resolution and artificial intelligence integration offer promise for improving diagnostic capabilities. Micro-CT provides valuable insights into bone microarchitecture and osseointegration dynamics, which have the potential to enhance pre-operative planning and clinical outcomes in dental implantology. Future research should prioritize the standardization of micro-CT analysis protocols and the exploration of direct clinical applications of this technology.
Autonomous Robot Goal Seeking and Collision Avoidance in the Physical World: An Automated Learning and Evaluation Framework Based on the PPO Method
Authors: Cheng Wen-Chung , Ni Zhen , Zhong Xiangnan , Wei Minghan
Published: November 2024

Mobile robot navigation is a critical aspect of robotics, with applications spanning from service robots to industrial automation. However, navigating in complex and dynamic environments poses many challenges, such as avoiding obstacles, making decisions in real-time, and adapting to new situations. Reinforcement Learning (RL) has emerged as a promising approach to enable robots to learn navigation policies from their interactions with the environment. However, application of RL methods to real-world tasks such as mobile robot navigation, and evaluating their performance under various training–testing settings has not been sufficiently researched. In this paper, we have designed an evaluation framework that investigates the RL algorithm’s generalization capability in regard to unseen scenarios in terms of learning convergence and success rates by transferring learned policies in simulation to physical environments. To achieve this, we designed a simulated environment in Gazebo for training the robot over a high number of episodes. The training environment closely mimics the typical indoor scenarios that a mobile robot can encounter, replicating real-world challenges. For evaluation, we designed physical environments with and without unforeseen indoor scenarios. This evaluation framework outputs statistical metrics, which we then use to conduct an extensive study on a deep RL method, namely the proximal policy optimization (PPO). The results provide valuable insights into the strengths and limitations of the method for mobile robot navigation. Our experiments demonstrate that the trained model from simulations can be deployed to the previously unseen physical world with a success rate of over 88%. The insights gained from our study can assist practitioners and researchers in selecting suitable RL approaches and training–testing settings for their specific robotic navigation tasks.
Optimizing Smart City Strategies: A Data-Driven Analysis Using Random Forest and Regression Analysis
Authors: Bafail Omer
Published: November 2024

This study investigates the critical factors influencing smart city program success through a comprehensive data-driven analysis of 140 urban centers. Advanced machine learning techniques, specifically random forest algorithms, in conjunction with regression analysis, were employed to examine the correlations between 45 distinct attributes and respective smart city rankings. The findings reveal that the human development index (HDI) is a key predictor of smart city performance. Furthermore, the regression analysis revealed that elements such as education, healthcare, infrastructure, and digital services significantly enhance achieving higher HDI scores. Similarly, factors like education, sanitation, healthcare, and government transparency are closely associated with successfully implementing sharing platforms. These findings highlight the importance of investing in human capital, developing digital infrastructure, and promoting community engagement to create sustainable and resilient smart cities. Policymakers can utilize these findings to prioritize investments and devise effective strategies to improve their city’s ranking.