bluuebunny/crossref_metadata_2025 huggingface dataset:
A mechanical study of the influence of ankle joint angle on translational traction of soccer boots
Authors: Loud Danyon , Grimshaw Paul , Kelso Richard , Robertson William S. P.
Published: July 2024

The shoe–surface interaction for soccer players has both safety and performance implications. This interaction has been widely researched in terms of outsole configuration and surface type. However, these investigations, particularly those involving translational traction, often neglect the approach angle of the foot in terms of a real-world setting. This investigation considers the foot position prior to injuries such as anterior cruciate ligament tears, and observes how the translational traction alters with various angles for simulated plantarflexion, dorsiflexion, calcaneal inversion and calcaneal eversion. It was hypothesised that, as these angles increased, the translational traction would decrease as there would be less contact area between the boot and the surface compared to the neutral, flat footform. A custom-built testing apparatus recorded the translational traction of a soccer boot moving in four different directions at different loading angles on both a natural grass and artificial grass playing surface. A one-way ANOVA was performed, with a post-hoc Tukey Test to determine the significant differences between the translational traction between each angle. It was found that the geometry of the outsole configuration, more specifically, the apparent contact area between the shoe and surface played a significant role in the level of traction obtained. These results highlight the importance of stud geometry, particularly with respect to movements when the foot is angled as it would be in a potential injury scenario. Manufacturers should consider the profile of studs relative to the expected movements to not induce excessive traction, which could lead to potential foot fixation and injury.
Estimating future bathymetric surface of Kainji Reservoir using Markov Chains and Cellular Automata algorithms
Authors: Ibrahim Pius Onoja , Sternberg Harald , Ojigi Lazarus Mustapha
Published: July 2024

The menace of sedimentation to reservoirs has a significant implication for water quality, storage capacity and reservoir lifetime. Rainfall patterns and other anthropogenic and environmental impacts alter the erosion rate and, by extension, directly affect sedimentation rates if left unchecked. This research focused on using the integration of Markov Chains and Cellular Automata (MC – CA) models to estimate and forecast the future bathymetric surface of the Kainji reservoir in Nigeria for the year 2050. The bathymetric datasets used for this research comprise two different epochs (1990 and 2020). The datasets were acquired using a Single Beam Echosounder at Low and High frequencies of 20 kHz and 200 kHz. The preliminary investigation revealed that sedimentation is exacerbating a greater danger to the reservoir functionality. The results show that the maximum observed depth is 71.2 m, indicating a 7.53% loss in depth from the 1990 archived data and a 16.24% depth loss to sedimentation from 1968 to 2020 and 22.35% depth loss in the year 2050 as shown on the projected surface. Consequently, the integrated model (MC and CA) efficiently predicted the future bathymetric surface of the Kainji reservoir for the year 2050 based on the data characteristics. However, the proven techniques for analysing spatial data, such as the Markov Chain and Cellular Automata, best suited for analysing categorical transition data, show some artefacts (black spots) on the projected generated map which is subject to further investigation.
Economic production of eco-friendly dehairing keratinase and antioxidant feather hydrolyzate using Bacillus halotolerans
Authors: Ismail Shaymaa A. , Nour Shaimaa A. , Nashy El-Shahat H. A. , Abdel-Fattah Azza M.
Published: July 2024

Feather is a high recalcitrance keratin-based biomass, and keratin-degrading microorganisms have been seen as beneficial tools for its biodegradation and production of valuable products with biomedical and industrial applications. In the current study, the isolated keratinolytic bacteria was identified on the base of its 16 S rDNA sequencing data as Bacillus halotolerans, and its efficiency in the hydrolysis of feather with the preservation of most of its amino acid constituent was estimated by high-performance liquid chromatography Pico-Tag (HPLC PICO-TAG) method. The produced hydrolysate possessed antioxidant activity of 2,2-Diphenyl-1-picrylhydrazyl (DPPH) free radical scavenging activity of 52.3 ± 5.6 mmole TE/g without possessing any cytotoxicity to human normal skin fibroplast cell line BJ-1 estimated by MTT assay. Moreover, the isolated strain was capable for producing keratinase under submerged fermentation of feather that was optimized by combining single-variable-at-a-time optimization with the application of statistical designs (Plackett-Burman and Box-Behnken). The optimum keratinase activity was 140.83 U/mL that was enhanced by 3.2-fold of the estimated initial activity, and the purified enzyme possessed optimum activity at pH 9.5 and 70 °C with a half-life of 69.3 min. Finally, the applicability of the purified enzyme in the dehairing of bovine hide was examined in comparison to sodium sulfide (Na2S) and lime (Ca(OH)2) conventional method. The results estimated the efficiency of the examined bio-treatment process, it achieved complete dehairing after 2 h with a good skin quality as manifested by scanning electron microscope (SEM). In addition, a significant reduction of the pollution load parameters was estimated.
Strengths and Limitations of BMI in the Diagnosis of Obesity: What is the Path Forward?
Authors: Sweatt Katherine , Garvey W. Timothy , Martins Catia
Published: July 2024

Purpose of Review

This review aims to discuss strengths and limitations of body mass index (BMI) in diagnosing obesity, the use of alternative anthropometric measurements, and potential new technology that may change the future of obesity diagnosis and management.

Recent Findings

The diagnosis of obesity requires the anthropometric assessment of adiposity. In clinical settings, this should include BMI with confirmation that elevated BMI represents excess adiposity and a measure of fat distribution (i.e., waist circumference (WC), waist to height ratio (WHtR), or WC divided by height0.5 (WHR.5R). Digital anthropometry and bioelectric impedance (BIA) can estimate fat distribution and be feasibly employed in the clinic. In addition, the diagnosis should include a clinical component assessing the presence and severity of weight-related complications.

As anthropometric measures used in the diagnosis of obesity, BMI is generally sufficient if confirmed to represent excess adiposity, and there are advantages to the use of WHtR over WC to assess fat distribution. BIA and digital anthropometry have the potential to provide accurate measures of fat mass and distribution in clinical settings. There should also be a clinical evaluation for the presence and severity of obesity complications that can be used to stage the disease.
Interactive Mixed Reality Methods for Visualization of Underground Utilities
Authors: Abdul Muthalif Mohamed Zahlan , Shojaei Davood , Khoshelham Kourosh
Published: July 2024

This research aims to overcome the difficulties associated with visualizing underground utilities by proposing six interactive visualization methods that utilize Mixed Reality (MR) technology. By leveraging MR technology, which enables the seamless integration of virtual and real-world content, a more immersive and authentic experience is possible. The study evaluates the proposed visualization methods based on scene complexity, parallax effect, real-world occlusion, depth perception, and overall effectiveness, aiming to identify the most effective methods for addressing visual perceptual challenges in the context of underground utilities. The findings suggest that certain MR visualization methods are more effective than others in mitigating the challenges of visualizing underground utilities. The research highlights the potential of these methods, and feedback from industry professionals suggests that each method can be valuable in specific contexts.
Assessment of Advanced Machine and Deep Learning Approaches for Predicting CO2 Emissions from Agricultural Lands: Insights Across Diverse Agroclimatic Zones
Authors: Harsányi Endre , Mirzaei Morad , Arshad Sana , Alsilibe Firas , Vad Atilla , Nagy Adrian , Ratonyi Tamás , Gorji Manouchehr , Al-Dalahme Main , Mohammed Safwan
Published: July 2024

Prediction of carbon dioxide (CO2) emissions from agricultural soil is vital for efficient and strategic mitigating practices and achieving climate smart agriculture. This study aimed to evaluate the ability of two machine learning algorithms [gradient boosting regression (GBR), support vector regression (SVR)], and two deep learning algorithms [feedforward neural network (FNN) and convolutional neural network (CNN)] in predicting CO2 emissions from Maize fields in two agroclimatic regions i.e., continental (Debrecen-Hungary), and semi-arid (Karaj-Iran). This research developed three scenarios for predicting CO2. Each scenario is developed by a combination between input variables [i.e., soil temperature (Δ), soil moisture (θ), date of measurement (SD), soil management (SM)] [i.e., SC1: (SM + Δ + θ), SC2: (SM + Δ), SC3: (SM + θ)]. Results showed that the average CO2 emission from Debrecen was 138.78 ± 72.04 ppm (n = 36), while the average from Karaj was 478.98 ± 174.22 ppm (n = 36). Performance evaluation results of train set revealed that high prediction accuracy is achieved by GBR in SC1 with the highest R2 = 0.8778, and lowest root mean squared error (RMSE) = 72.05, followed by GBR in SC3. Overall, the performance MDLM is ranked as GBR > FNN > CNN > SVR. In testing phase, the highest prediction accuracy was achieved by FNN in SC1 with R2 = 0.918, and RMSE = 67.75, followed by FNN in SC3, and GBR in SC1 (R2 = 0.887, RMSE = 79.881). The performance of MDLM ranked as FNN > GRB > CNN > SVR. The findings of the research provide insights into agricultural management strategies, enabling stakeholders to work towards a more sustainable and climate-resilient future in agriculture.
Anti-oomycete activity of asparagus and olive by-products with potential to control Phytophthora cinnamomi root rot
Authors: Martín María Ángeles Romero , García Rosa López , Rodríguez-Arcos Rocío , Jiménez-Araujo Ana , Moral María Socorro Serrano
Published: July 2024

The development of environmentally friendly control methods to mitigate the severe damages caused by Phytophthora cinnamomi in the Mediterranean climate-type ecosystems is essential. In this way, crop waste and by-products which represent between 13 and 65% of agriculture production, are a rich source of bioactive compounds with antifungal and biocide activity. The main objective of this work was to determine the biocide activity against P. cinnamomi of three organic extracts. These extracts enriched in bioactive compounds come from residues of asparagus (Asp) and olive crops (Oliv and OH, from fruits and leaves respectively). They were evaluated at two doses (0.15 and 0.10%) on the mycelial growth and sporangial production of P. cinnamomi by in vitro experiments. Mycelial growth and sporangial production were significant reduced from the three plant extracts at the two doses tested, reaching a total inhibition with Asp at both doses. In general, no phytotoxicity symptoms were observed on seed germination and plant development, except for a plant yield reduction in the substrate treated with Oliv and Asp at the highest dose. In experiments performed in artificially infested soil, Asp induced a reduction of chlamydospores viability greater than 75% compared to unamended soil. Additionally, in planta experiments showed a significant reduction in plant mortality in substrate amended with OH. These results suggest that soil application of Asp and OH can limit P. cinnamomi infectivity and survival, setting the first steps to develop a sustainable method to control the root disease based on agricultural waste circular economy.
Implication of fault seal analysis method to evaluate the sealing conditions of major fault planes at Barapukuria basin, North-West Bangladesh
Authors: Roy Sushanta Kumar , Shemu Tamanna Meheran , Alam Mohammad Jahangir , Solaiman Mohammad
Published: July 2024

The Barapukuria coal basin stands as Bangladesh’s sole active underground coal mining site. The geological setting of this basin is marked by two major faults, the Eastern Boundary Fault and FB fault encircling the basin perimeter, alongside several smaller faults and those induced by underground longwall mining activities. A major concerning issue of this mine is the water inrush into the mine area from the extensive groundwater aquifer, Upper DupiTila (UDT). Using the Fault Seal Analysis technique employed by (Yielding et al. in Am Assoc Pet Geol Bull 81:897–917, 1997) algorithm, this analysis attempts to identify susceptible areas and potential unsealed faults that could provide the risk of water invasion into the mine area. Evaluation of Fault Seal Analysis reveals varying Shale Gauge Ratio (SGR) values: 0.08 and 0.13 for the major Eastern Boundary Fault, 0.05 for the second largest FB fault, 0.35 and 0.53 for FB-1, and 5.65, 1.69, and 1.22 for the smaller faults BGP-N-F11, BGP-N-F2, and F-24, respectively. According to SGR values, the Eastern Boundary Fault and the FB fault plane are anticipated to be unsealed and dip westward at an angle of 75°-80°,  rendering them vulnerable to water inflow through the fault planes. The analysis also suggests that the Lower DupiTila (LDT) aquiclude which can impede the groundwater flow from the UDT aquifer into the mine area, is very thin or absent in the northern region of the basin making this region highly susceptible to water inundation.
Assessment of suitability for photovoltaic power generation in periurban seminatural grasslands: toward the coexistence of seminatural grasslands and photovoltaic power generation
Authors: Nakatani Miharu , Osawa Takeshi
Published: July 2024

Renewable energy has grown substantially in recent years due to its efficacy in mitigating climate change. The rapid proliferation of solar photovoltaic (PV) systems and subsequent alterations in land use have led to concerns about the impact on local ecosystems. Particularly in Japan, seminatural grasslands, which are valuable habitats, are being developed as solar PVs. Here, we focused on stilt-mounted agrivoltaic systems, capable of both photovoltaic power generation and plant growth beneath solar panels. By repurposing this technology, the coexistence of vegetation and solar PV systems can be possibly ensured. To assess the feasibility of this proposed approach, we initially examined the suitability of installing solar PV in seminatural grasslands. The suitability of seminatural grasslands, solar PVs, and random points for solar PV was evaluated in terms of electricity generation and construction costs. The environmental conditions of seminatural grasslands were found to be advantageous for electricity generation. On the other hand, in terms of construction costs, seminatural grasslands were comparable to randomly selected sites. These findings indicate that the suitability of existing seminatural grasslands for solar PV plant installations is not considerably lower than that of other land types. The idea of reconciling solar power generation with ecosystem conservation holds promise and warrants further investigation toward its realization.
Effects of dietary nitrate supplementation on markers of oral health: A systematic review
Authors: Alhulaefi S. , Watson A. , Ramsay S.E , Jakubovics N. , Matu J. , Griffiths A. , Kimble R. , Brandt K. , Shannon OM.
Published: July 2024

The oral cavity is a vital part of the digestive system. Poor oral health can impact an individual’s ability to eat and has been associated with increased risk of non-communicable diseases and reduced longevity. Conversely, positive oral health has been associated with improved cardiometabolic, cognitive and systemic health and greater longevity. Consumption of dietary nitrate, which is processed in the mouth into nitrite, and is subsequently converted into nitric oxide (NO) in the body (1), has been demonstrated to reduce blood pressure, improve endothelial function, and enhance exercise performance. Interestingly, recent studies suggest that nitrate consumption could also positively modulate markers of oral health (2). To our knowledge, no systematic review has been published examining the effect of inorganic dietary nitrate on oral health. However, this could be valuable to summarise current state of the knowledge, identify effect modifiers and highlight gaps for future research. Therefore, this systematic review aims to investigate the effects of dietary nitrate supplements on markers of oral health in vivo in randomised controlled trials (RCTs).

This study was pre-registered with PROSPERO (CRD42023411159). Five databases (PubMed, The Cochrane Library, CINAHL, MEDLINE, and SPORTDiscus) were searched from inception until March 2023 to identify studies that met the following criteria: adult participants (≥ 18 years) and RCTs investigating the effects of oral dietary nitrate versus placebo on markers of oral health. A narrative synthesis of data was conducted. Risk of bias was assessed using the Cochrane Risk of Bias 2 tool.

Nine articles reporting data on 284 participants were included. Nitrate was provided via beetroot juice (six studies), a beetroot-derived supplement dissolved in mineral water (one study), and lettuce juice (two studies). The duration of the interventions ranged from one day to a maximum of six weeks. Dietary nitrate supplementation increased the relative abundance of several individual bacterial genera including Neisseria (increased in three studies) and Rothia (increased in three studies). Dietary nitrate supplementation increased salivary pH (increased in two studies) and decreased salivary acidification resulting from the consumption of a sugar-sweetened beverage (decreased in two studies). Furthermore, dietary nitrate supplementation resulted in a decrease in the gingival inflammation index in one study. Overall, the risk of bias in studies was mixed. One study had a low risk of bias, while the rest were rated as having some concerns. No study was considered to have a high risk of bias.

The results show that dietary nitrate is a potential nutritional strategy that can potentially benefit oral health by modifying the oral microbiome, altering salivary pH, and minimising gingival inflammation.
Exploring healthcare professionals’ perceptions of diet and exercise as a form of symptom management in Parkinson’s Disease
Authors: Calladine A. , Coe S. , Daly A. , Lawrie S.
Published: July 2024

Parkinson’s Disease (PD) is a neurodegenerative disorder in which dopaminergic neurons of the substantia nigra, a region of the brain that controls movement, are lost over time (1). This results in motor symptoms, such as bradykinesia, and non-motor symptoms such as depression (2). Evidence- based resources and programmes utilising exercise for symptom management are widely available (3). However, despite emerging evidence showing that diet changes can improve quality of life and reduce disease severity (4), there are few dietary guidelines and programmes. This study aims to address a current literature gap in qualitative studies assessing the opinions of healthcare professionals (HCPs) towards diet and exercise in PD care, and to identify barriers and facilitators of this in care.

A qualitative design was used to assess the views and beliefs of HCPs. Semi-structured interviews were conducted via telephone, using a topic guide developed by the research team, consisting of 20 questions. The data were analysed using the six-phase process of Reflexive Thematic analysis to determine key themes in the data (5).

Five HCPs participated in this study. One main theme and two subthemes were identified. The main theme was that provisions of care and dietary advice are limited by a lack of knowledge of evidence- based, PD-specific, dietary guidelines. Subtheme 1 was that evidence-based exercise guidelines have been important facilitators in supporting care provision. Subtheme 2 was that lack of dietary guidance has been a barrier to optimum care provision and self-efficacy of HCPs.

HCPs were less likely to discuss diet, due to barriers including lack of available resources or knowledge thereof, self-efficacy to recommend dietary changes, time constraints in the clinic, and less well-established referral pathways for dietitians. HCPs were unaware of the influence of diet in PD treatment, despite diet’s impact on symptoms being discussed in clinic. However, HCPs agreed that evidence-based resources would benefit HCPs’ practice, to improve symptom severity and nutritional status of patients. Exercise was more likely to be discussed, as evidence-based guidelines and empirical understanding meant HCPs were more aware of the beneficial effects on symptoms.

While limited by small numbers, these findings suggest that a lack of knowledge, low self-efficacy, and time pressures mean that patients may not receive dietary guidelines which may be beneficial to their care. Self-efficacy of HCPs should be improved through PD-specific nutritional education, development and dissemination of PD-specific nutrition guidelines and resources. Future research should aim to determine the effectiveness of relevant dietary strategies’ in managing and caring for PD.
Relationship between carrot intake, dietary/circulating α-carotene and cancer risk: A systematic review and meta-analysis of prospective observational studies
Authors: Ojobor C.C , O’Brien G.M , Siervo M. , Ogbonnaya C. , Brandt K.
Published: July 2024

Carrot consumption reduces tumour development in several animal models. The constituent alpha- carotene has not by itself shown anti-cancer properties, however carrots typically provide >85% of alpha-carotene dietary intake(1-3), justifying its use as an indicator of carrot intake(3). We conducted a meta-analysis to investigate inverse associations of carrot/dietary α-carotene intakes and cancer risk, and to quantify potential dose–response relationships.

PubMed, Cochrane Library, Web of Science, Scopus, EBSCO, and JSTOR were searched (from database inception to August 2021) for studies reporting risk estimates with 95% CIs for the relationship between carrot intake or α-carotene and cancer risk. Meta-analyses were conducted using a random-effects model comparing highest and lowest intakes to estimate summary risk estimates (RRs).

Of 80 prospective studies included, 15 (with 25738 cases) reported data on carrot intake, 35 (26262 cases) on dietary α-carotene intake and 30 (9331 cases) on plasma α-carotene levels. A significantly (P<0.01) decreased risk of overall cancer was associated with carrot intake (RR = 0·90), dietary α- carotene intake (RR = 0·90) and plasma α-carotene (RR = 0·80). In addition, both carrot intake and plasma α-carotene level manifested linear dose-response relationships with cancer risk, with increasing carrot intake reaching 20% risk reduction at 5 servings (400g) per week (p < 0·0001),and successive 50μg/L increments in plasma α-carotene associated with 11% risk reduction (p < 0·0058).

Carrot consumption is robustly associated with decreased cancer risk. Carrot consumption should be encouraged, and the causal mechanisms further investigated.
The effectiveness of e-storybook on children’s vegetable acceptance
Authors: Mohd Nor N.D , Che Mustafa M. , Bacotang J.
Published: July 2024

A diet high in fruit and vegetables is beneficial to reduce the risk of many diseases such as cardiovascular diseases, certain cancers and hypertension(1,2). However, reports show that vegetable consumption among children is still low. Intervention must be made to encourage children to eat more vegetables as a dietary pattern in childhood will determine a dietary pattern in adulthood(3). This current study investigated the effects of an e-storybook on children’s vegetable acceptance.

Sixty-five parents and their children aged 4 to 7 years participated in this study and they were divided into 2 groups. Parents in an experimental group read an e-storybook about a target vegetable (asparagus) with their child for 10 days, while the control group did not receive an e-book. Parents in both groups were asked to offer the target vegetable and a match control vegetable (peas) before and after the intervention and record their child’s vegetable intake (measured using a 6-point scale) and liking (measured using a 6-point scale).

In the experimental group, liking of target vegetable increased from 2.5 ± 1.5 to 3.0 ± 1.4 (p = 0.01), but not for control vegetable. There was a tendency that intake of target vegetable increased following exposure to the e-storybook, from 1.6 ± 1.6 to 1.9 ± 1.7 (p=0.052), but there was no significant increase in intake for control vegetable. While in the control group, there were no significant increases in intake and liking for both vegetables post-intervention. When comparing means between groups, there were no significant differences in intake and liking at pre-intervention, however at post-intervention, there was a significant difference in intake (p=0.02), where the intervention group had a higher intake than the control group by 0.9 ± 1.9. There was also a significant difference in liking between these groups at post-intervention (p=0.001), where the intervention group had a higher liking than the control group by 1.1 ± 1.8.

Results suggest that e-storybooks are an effective strategy for parents to use to increase vegetable acceptance in children.
Forecasting West Nile Virus With Graph Neural Networks: Harnessing Spatial Dependence in Irregularly Sampled Geospatial Data
Authors: Tonks Adam , Harris Trevor , Li Bo , Brown William , Smith Rebecca
Published: July 2024

Machine learning methods have seen increased application to geospatial environmental problems, such as precipitation nowcasting, haze forecasting, and crop yield prediction. However, many of the machine learning methods applied to mosquito population and disease forecasting do not inherently take into account the underlying spatial structure of the given data. In our work, we apply a spatially aware graph neural network model consisting of GraphSAGE layers to forecast the presence of West Nile virus in Illinois, to aid mosquito surveillance and abatement efforts within the state. More generally, we show that graph neural networks applied to irregularly sampled geospatial data can exceed the performance of a range of baseline methods including logistic regression, XGBoost, and fully‐connected neural networks.
Picky Eaters: Carbon Isotopic Evidence for the Uniform Bioavailability of Riverine Dissolved Organic Matter to a Model Marine Microorganism
Authors: Baumser Lea , Potts Lindsey , Walker Brett D. , Mahmoudi Nagissa
Published: July 2024

Dissolved organic matter (DOM) is a key component of the global carbon cycle, with rivers delivering significant amounts of DOM to oceans. Urbanization and agricultural land‐use alter the age and chemical composition of riverine DOM, which likely impact the downstream bioavailability of riverine DOM. Here, we use bioreactor incubations of a marine bacterium (Pseudoalteromonas sp. 3D05) to investigate DOM bioavailability from two distinct rivers: the Suwannee River (natural, non‐urbanized), and the Upper Mississippi River Basin (anthropogenically influenced). We measured rates of microbial CO2 production and radiocarbon ages (as Δ14C) to assess DOM remineralization. We observed nearly identical cell densities and degradation patterns for both riverine DOM incubations. Respired DOM Δ14C values were also similar and decreased over time indicative of preferential utilization of recently synthesized “modern” substrates. These findings reveal unexpected similarities in riverine DOM bioavailability, indicating similar short term biological reactivity despite large DOM compositional differences.
Geology Matters for Antarctic Geothermal Heat
Authors: Stål Tobias , Halpin Jacqueline A. , Goodge John W. , Reading Anya M.
Published: July 2024

Geothermal heat plays a vital role in Antarctic ice sheet stability. The continental geothermal heat flow distribution depends on lithospheric composition and ongoing tectonism. Heat‐producing elements are unevenly enriched in the crust over deep time by various geological processes. The contribution of crustal heat production to geothermal heat flow is widely recognized; however, in Antarctica, crustal geology is largely hidden, and its complexity has frequently been excluded in thermal studies due to limited observations and oversimplified assumptions. Li and Aitken (2024), https://doi.org/10.1029/2023GL106201 take a significant step forward, focusing on Antarctic crustal radiogenic heat. Utilizing gravity inversion and rock composition data, they show that the crustal heterogeneity introduces considerable variability to heat flow. However, modeling crustal heat production proves challenging because it lacks distinct associations with geophysical observables and has a narrow spatial association. Robust quantification of geothermal heat production and heat flow must incorporate explicit aspects of geology.
Shortcut to multipartite entanglement generation: A graph approach to boson subtractions
Authors: Chin Seungbeom , Kim Yong-Su , Karczewski Marcin
Published: July 2024

We propose a graph method for systematically searching for schemes that can generate multipartite entanglement in linear bosonic systems with heralding. While heralded entanglement generation offers more tolerable schemes for quantum tasks than postselected ones, it is generally more challenging to find appropriate circuits for multipartite systems. We show that our graph mapping from boson subtractions provides handy tactics to overcome the limitations in circuit designs. Within our graph framework, we identify enhanced schemes for qubit N-partite GHZ, W, and the superposition of N = 3 GHZ and W states. Furthermore, we have found a qudit N-partite GHZ state generation scheme, which requires substantially fewer particles than previous proposals. These results demonstrate the power of our approach in discovering optimized solutions for the generation of intricate heralded entangled states. We expect our method to serve as a promising tool in generating diverse entanglement.
The cortical amygdala consolidates a socially transmitted long-term memory
Authors: Liu Zhihui , Sun Wenfei , Ng Yi Han , Dong Hua , Quake Stephen R. , Südhof Thomas C.
Published: July 2024

Social communication guides decision-making, which is essential for survival. Social transmission of food preference (STFP) is an ecologically relevant memory paradigm in which an animal learns a desirable food odour from another animal in a social context, creating a long-term memory1,2. How food-preference memory is acquired, consolidated and stored is unclear. Here we show that the posteromedial nucleus of the cortical amygdala (COApm) serves as a computational centre in long-term STFP memory consolidation by integrating social and sensory olfactory inputs. Blocking synaptic signalling by the COApm-based circuit selectively abolished STFP memory consolidation without impairing memory acquisition, storage or recall. COApm-mediated STFP memory consolidation depends on synaptic inputs from the accessory olfactory bulb and on synaptic outputs to the anterior olfactory nucleus. STFP memory consolidation requires protein synthesis, suggesting a gene-expression mechanism. Deep single-cell and spatially resolved transcriptomics revealed robust but distinct gene-expression signatures induced by STFP memory formation in the COApm that are consistent with synapse restructuring. Our data thus define a neural circuit for the consolidation of a socially communicated long-term memory, thereby mechanistically distinguishing protein-synthesis-dependent memory consolidation from memory acquisition, storage or retrieval.
Semantic encoding during language comprehension at single-cell resolution
Authors: Jamali Mohsen , Grannan Benjamin , Cai Jing , Khanna Arjun R. , Muñoz William , Caprara Irene , Paulk Angelique C. , Cash Sydney S. , Fedorenko Evelina , Williams Ziv M.
Published: July 2024

From sequences of speech sounds1,2 or letters3, humans can extract rich and nuanced meaning through language. This capacity is essential for human communication. Yet, despite a growing understanding of the brain areas that support linguistic and semantic processing4–12, the derivation of linguistic meaning in neural tissue at the cellular level and over the timescale of action potentials remains largely unknown. Here we recorded from single cells in the left language-dominant prefrontal cortex as participants listened to semantically diverse sentences and naturalistic stories. By tracking their activities during natural speech processing, we discover a fine-scale cortical representation of semantic information by individual neurons. These neurons responded selectively to specific word meanings and reliably distinguished words from nonwords. Moreover, rather than responding to the words as fixed memory representations, their activities were highly dynamic, reflecting the words’ meanings based on their specific sentence contexts and independent of their phonetic form. Collectively, we show how these cell ensembles accurately predicted the broad semantic categories of the words as they were heard in real time during speech and how they tracked the sentences in which they appeared. We also show how they encoded the hierarchical structure of these meaning representations and how these representations mapped onto the cell population. Together, these findings reveal a finely detailed cortical organization of semantic representations at the neuron scale in humans and begin to illuminate the cellular-level processing of meaning during language comprehension.
Assessing the antioxidant properties of Naringin and Rutin and investigating their oxidative DNA damage effects in breast cancer
Authors: Pravin Badhe , Nanaware Vivek , Ashwini Badhe , Wondmie Gezahign Fentahun , Jardan Yousef A. Bin , Bourhia Mohammed
Published: July 2024

This work examines the capacity of Naringin and Rutin to influence the DNA damage response (DDR) pathway by investigating their interactions with key DDR proteins, including PARP-1, ATM, ATR, CHK1, and WEE1. Through a combination of in silico molecular docking and in vitro evaluations, we investigated the cytotoxic and genotoxic effects of these compounds on MDA-MB-231 cells, comparing them to normal human fibroblast cells (2DD) and quiescent fibroblast cells (QFC). The research found that Naringin and Rutin had strong affinities for DDR pathway proteins, indicating their capacity to specifically regulate DDR pathways in cancer cells. Both compounds exhibited preferential cytotoxicity towards cancer cells while preserving the vitality of normal 2DD fibroblast cells, as demonstrated by cytotoxicity experiments conducted at a dose of 10 µM. The comet experiments performed particularly on QFC cells provide valuable information on the genotoxic impact of Naringin and Rutin, highlighting the targeted initiation of DNA damage in cancer cells. The need to use precise cell models to appropriately evaluate toxicity and genotoxicity is emphasized by this discrepancy. In addition, ADMET and drug-likeness investigations have emphasized the pharmacological potential of these compounds; however, they have also pointed out the necessity for optimization to improve their therapeutic profiles. The antioxidant capabilities of Naringin and Rutin were assessed using DPPH and free radical scavenging assays at a concentration of 10 µM. The results confirmed that both compounds have a role in reducing oxidative stress, hence enhancing their anticancer effects. Overall, Naringin and Rutin show potential as medicines for modulating the DDR in cancer treatment. They exhibit selective toxicity towards cancer cells while sparing normal cells and possess strong antioxidant properties. This analysis enhances our understanding of the therapeutic uses of natural chemicals in cancer treatment, supporting the need for more research on their mechanisms of action and clinical effectiveness.
Colon cancer diagnosis by means of explainable deep learning
Authors: Di Giammarco Marcello , Martinelli Fabio , Santone Antonella , Cesarelli Mario , Mercaldo Francesco
Published: July 2024

Early detection of the adenocarcinoma cancer in colon tissue by means of explainable deep learning, by classifying histological images and providing visual explainability on model prediction. Considering that in recent years, deep learning techniques have emerged as powerful techniques in medical image analysis, offering unprecedented accuracy and efficiency, in this paper we propose a method to automatically detect the presence of cancerous cells in colon tissue images. Various deep learning architectures are considered, with the aim of considering the best one in terms of quantitative and qualitative results. As a matter of fact, we consider qualitative results by taking into account the so-called prediction explainability, by providing a way to highlight on the tissue images the areas that from the model point of view are related to the presence of colon cancer. The experimental analysis, performed on 10,000 colon issue images, showed the effectiveness of the proposed method by obtaining an accuracy equal to 0.99. The experimental analysis shows that the proposed method can be successfully exploited for colon cancer detection and localisation from tissue images.
Clinical features and treatment outcomes of intraocular and ocular adnexal metastasis
Authors: Tsutsumi Wantanee Dangboon , Rattanasuwan Apinya , Aryasit Orapan
Published: July 2024

The aim of this study was to investigate the primary sites, clinical characteristics, and treatment outcomes of patients with metastatic tumors in the eye and ocular adnexa. This retrospective case series consisted of 42 patients diagnosed with intraocular metastasis (IM) or ocular adnexal metastasis (OAM) at a tertiary center between January 2001 and June 2023. The patients comprised 18 men and 24 women; 24 (57%) and 18 (43%) patients were diagnosed with IM and OAM, respectively. In the IM group, the primary tumors originated from the lungs (79%), followed by the breasts (17%). In the OAM group, the primary tumors originated from the breasts (33%). Previously, 57% of the patients had been diagnosed with cancer. In the IM group, 38% exhibited bilateral involvement. Only 6% of the patients with OAM had bilateral diseases. The 1-, 3-, and 5-year overall survival (OS) was 42%, 18%, and 7%, respectively. The median OS since metastasis diagnosis in the lungs and breast was 11.8 and 10.5 months, respectively. Lung cancer remains the predominant primary cancer in IM, whereas breast cancer is the major cancer in OAM. Despite poor OS, early detection will facilitate the prompt treatment of primary cancer and metastatic sites.
Bergenin inhibits growth of human cervical cancer cells by decreasing Galectin-3 and MMP-9 expression
Authors: Chauhan Ravi , Malhotra Lakshay , Gupta Ashna , Dagar Gunjan , Mendiratta Mohini , Masoodi Tariq , Hashem Sheema , Al Marzooqi Sara , Das Dayasagar , Uddin Shahab , Ethayathulla Abdul Samath , Macha Muzafar A. , Akil Ammira Al-Shabeeb , Sahoo Ranjit Kumar , Rai Ekta , Bhat Ajaz A. , Singh Mayank
Published: July 2024

Cervical cancer is still the leading cause of cancer mortality worldwide even after introduction of vaccine against Human papillomavirus (HPV), due to low vaccine coverage, especially in the developing world. Cervical cancer is primarily treated by Chemo/Radiotherapy, depending on the disease stage, with Carboplatin/Cisplatin-based drug regime. These drugs being non-specific, target rapidly dividing cells, including normal cells, so safer options are needed for lower off-target toxicity. Natural products offer an attractive option compared to synthetic drugs due to their well-established safety profile and capacity to target multiple oncogenic hallmarks of cancer like inflammation, angiogenesis, etc. In the current study, we investigated the effect of Bergenin (C-glycoside of 4-O-methylgallic acid), a natural polyphenol compound that is isolated from medicinal plants such as Bergenia crassifolia, Caesalpinia digyna, and Flueggea leucopyrus. Bergenin has been shown to have anti-inflammatory, anti-ulcerogenic, and wound healing properties but its anticancer potential has been realized only recently. We performed a proteomic analysis of cervical carcinoma cells treated with bergenin and found it to influence multiple hallmarks of cancers, including apoptosis, angiogenesis, and tumor suppressor proteins. It was also involved in many different cellular processes unrelated to cancer, as shown by our proteomic analysis. Further analysis showed bergenin to be a potent-angiogenic agent by reducing key angiogenic proteins like Galectin 3 and MMP-9 (Matrix Metalloprotease 9) in cervical carcinoma cells. Further understanding of this interaction was carried out using molecular docking analysis, which indicated MMP-9 has more affinity for bergenin as compared to Galectin-3. Cumulatively, our data provide novel insight into the anti-angiogenic mechanism of bergenin in cervical carcinoma cells by modulation of multiple angiogenic proteins like Galectin-3 and MMP-9 which warrant its further development as an anticancer agent in cervical cancer.
Phenotypic characterization and genomic analysis of a Salmonella phage L223 for biocontrol of Salmonella spp. in poultry
Authors: Khan Md Abu Sayem , Islam Zahidul , Barua Chayan , Sarkar Md. Murshed Hasan , Ahmed Md. Firoz , Rahman Sabita Rezwana
Published: July 2024

The escalating incidence of foodborne salmonellosis poses a significant global threat to food safety and public health. As antibiotic resistance in Salmonella continues to rise, there is growing interest in bacteriophages as potential alternatives. In this study, we isolated, characterized, and evaluated the biocontrol efficacy of lytic phage L223 in chicken meat. Phage L223 demonstrated robust stability across a broad range of temperatures (20–70 °C) and pH levels (2–11) and exhibited a restricted host range targeting Salmonella spp., notably Salmonella Typhimurium and Salmonella Enteritidis. Characterization of L223 revealed a short latent period of 30 min and a substantial burst size of 515 PFU/cell. Genomic analysis classified L223 within the Caudoviricetes class, Guernseyvirinae subfamily and Jerseyvirus genus, with a dsDNA genome size of 44,321 bp and 47.9% GC content, featuring 72 coding sequences devoid of antimicrobial resistance, virulence factors, toxins, and tRNA genes. Application of L223 significantly (p < 0.005) reduced Salmonella Typhimurium ATCC 14,028 counts by 1.24, 2.17, and 1.55 log CFU/piece after 2, 4, and 6 h of incubation, respectively, in experimentally contaminated chicken breast samples. These findings highlight the potential of Salmonella phage L223 as a promising biocontrol agent for mitigating Salmonella contamination in food products, emphasizing its relevance for enhancing food safety protocols.
Optimal conditions of algal breeding using neutral beam and applying it to breed Euglena gracilis strains with improved lipid accumulation
Authors: Imamura Sousuke , Yamada Koji , Takebe Hiroaki , Kiuchi Ryu , Iwashita Hidenori , Toyokawa Chihana , Suzuki Kengo , Sakurai Atsushi , Takaya Kazuhiro
Published: July 2024

Microalgae are considered to be more useful and effective to use in biomass production than other photosynthesis organisms. However, microalgae need to be altered to acquire more desirable traits for the relevant purpose. Although neutron radiation is known to induce DNA mutations, there have been few studies on its application to microalgae, and the optimal relationship between irradiation intensity and mutation occurrence has not been established. In this study, using the unicellular red alga Cyanidioschyzon merolae as a model, we analyzed the relationship between the absorbed dose of two types of neutrons, high-energy (above 1 MeV) and thermal (around 25 meV) neutrons, and mutation occurrence while monitoring mutations in URA5.3 gene encoding UMP synthase. As a result, the highest mutational occurrence was observed when the cells were irradiated with 20 Gy of high-energy neutrons and 13 Gy of thermal neutrons. Using these optimal neutron irradiation conditions, we next attempted to improve the lipid accumulation of Euglena gracilis, which is a candidate strain for biofuel feedstock production. As a result, we obtained several strains with a maximum 1.3-fold increase in lipid accumulation compared with the wild-type. These results indicate that microalgae breeding by neutron irradiation is effective.
Ensemble learning for fetal ultrasound and maternal–fetal data to predict mode of delivery after labor induction
Authors: Ferreira Iolanda , Simões Joana , Pereira Beatriz , Correia João , Areia Ana Luísa
Published: July 2024

Providing adequate counseling on mode of delivery after induction of labor (IOL) is of utmost importance. Various AI algorithms have been developed for this purpose, but rely on maternal–fetal data, not including ultrasound (US) imaging. We used retrospectively collected clinical data from 808 subjects submitted to IOL, totaling 2024 US images, to train AI models to predict vaginal delivery (VD) and cesarean section (CS) outcomes after IOL. The best overall model used only clinical data (F1-score: 0.736; positive predictive value (PPV): 0.734). The imaging models employed fetal head, abdomen and femur US images, showing limited discriminative results. The best model used femur images (F1-score: 0.594; PPV: 0.580). Consequently, we constructed ensemble models to test whether US imaging could enhance the clinical data model. The best ensemble model included clinical data and US femur images (F1-score: 0.689; PPV: 0.693), presenting a false positive and false negative interesting trade-off. The model accurately predicted CS on 4 additional cases, despite misclassifying 20 additional VD, resulting in a 6.0% decrease in average accuracy compared to the clinical data model. Hence, integrating US imaging into the latter model can be a new development in assisting mode of delivery counseling.