bluuebunny/crossref_metadata_2025 huggingface dataset:
Towards a more objective and high-throughput spheroid invasion assay quantification method
Authors: Mungai Rozanne W. , Hartman Roger J. , Jolin Grace E. , Piskorowski Kevin W. , Billiar Kristen L.
Published: December 2024

Multicellular spheroids embedded in 3D hydrogels are prominent in vitro models for 3D cell invasion. Yet, quantification methods for spheroid cell invasion that are high‐throughput, objective and accessible are still lacking. Variations in spheroid sizes and the shapes of the cells within render it difficult to objectively assess invasion extent. The goal of this work is to develop a high-throughput quantification method of cell invasion into 3D matrices that minimizes sensitivity to initial spheroid size and cell spreading and provides precise integrative directionally-dependent metrics of invasion. By analyzing images of fluorescent cell nuclei, invasion metrics are automatically calculated at the pixel level. The initial spheroid boundary is segmented and automated calculations of the nuclear pixel distances from the initial boundary are used to compute common invasion metrics (i.e., the change in invasion area, mean distance) for the same spheroid at a later timepoint. We also introduce the area moment of inertia as an integrative metric of cell invasion that considers the invasion area as well as the pixel distances from the initial spheroid boundary. Further, we show that principal component analysis can be used to quantify the directional influence of a stimuli to invasion (e.g., due to a chemotactic gradient or contact guidance). To demonstrate the power of the analysis for cell types with different invasive potentials and the utility of this method for a variety of biological applications, the method is used to analyze the invasiveness of five different cell types. In all, implementation of this high‐throughput quantification method results in consistent and objective analysis of 3D multicellular spheroid invasion. We provide the analysis code in both MATLAB and Python languages as well as a GUI for ease of use for researchers with a range of computer programming skills and for applications in a variety of biological research areas such as wound healing and cancer metastasis.
Comparative evaluation of spatiotemporal methods for effective dengue cluster detection with a case study of national surveillance data in Thailand
Authors: Rotejanaprasert Chawarat , Chinpong Kawin , Lawson Andrew B. , Maude Richard J.
Published: December 2024

Dengue fever poses a significant public health burden in tropical regions, including Thailand, where periodic epidemics strain healthcare resources. Effective disease surveillance is essential for timely intervention and resource allocation. Various methods exist for spatiotemporal cluster detection, but their comparative performance remains unclear. This study compared spatiotemporal cluster detection methods using simulated and real dengue surveillance data from Thailand. A simulation study explored diverse disease scenarios, characterized by varying magnitudes and spatial-temporal patterns, while real data analysis utilized monthly national dengue surveillance data from 2018 to 2020. Evaluation metrics included accuracy, sensitivity, specificity, positive predictive value, and negative predictive value. Bayesian models and FlexScan emerged as top performers, demonstrating superior accuracy and sensitivity. Traditional methods such as Getis Ord and Moran’s I showed poorer performance, while other scanning-based approaches like spatial SaTScan exhibited limitations in positive predictive value and tended to identify large clusters due to the inflexibility of its scanning window shape. Bayesian modeling with a space–time interaction term outperformed testing-based cluster detection methods, emphasizing the importance of incorporating spatiotemporal components. Our study highlights the superior performance of Bayesian models and FlexScan in spatiotemporal cluster detection for dengue surveillance. These findings offer valuable guidance for policymakers and public health authorities in refining disease surveillance strategies and resource allocation. Moreover, the insights gained from this research could be valuable for other diseases sharing similar characteristics and settings, broadening the applicability of our findings beyond dengue surveillance.
Hemoglobin decrease predicts untoward outcomes better than severity of anemia
Authors: Teutsch Brigitta , Tóth Zsolt Abonyi , Ferencz Orsolya , Vörhendi Nóra , Simon Orsolya Anna , Boros Eszter , Pálinkás Dániel , Frim Levente , Tari Edina , Kalló Patrícia , Gagyi Endre Botond , Hussein Tamás , Váncsa Szilárd , Vass Vivien , Szentesi Andrea , Vincze Áron , Izbéki Ferenc , Hegyi Péter , Hágendorn Roland , Szabó Imre , Erőss Bálint
Published: December 2024

Patients with gastrointestinal bleeding (GIB) exhibit varying tolerances to acute blood loss. We aimed to investigate the effect of relative Hb decrease (ΔHb%) on GIB outcomes. Participants enrolled in the Hungarian GIB Registry between 2019 and 2022 were analyzed. The primary outcome, defined as a composite endpoint, included in-hospital bleeding-related mortality and the need for urgent intervention. Four groups were created based on the lowest Hb measured during hospitalization (nadirHb), along with four subgroups categorized by ΔHb%. Regardless of the nadirHb, participants with higher ΔHb% had a higher probability of reaching the composite endpoint. A 30–40% ΔHb% decrease to a nadirHb of 80–90 g/L resulted in a similar likelihood of reaching the primary endpoint as a 0–10% ΔHb% to 70–80 g/L or 60–70 g/L, respectively (10% vs. 12%, p = 1.00; 10% vs. 10%, p = 1.00). Our results showed that a higher Hb decrease in GIB is associated with an increased untoward outcome rate even when the lowest hemoglobin exceeds the recommended transfusion thresholds. New randomized controlled trials investigating transfusion thresholds should consider ΔHb% as a potential key variable and risk factor.
A hybrid encryption framework leveraging quantum and classical cryptography for secure transmission of medical images in IoT-based telemedicine networks
Authors: Shafique Arslan , Naqvi Syed Ali Atif , Raza Ali , Ghalaii Masoud , Papanastasiou Panagiotis , McCann Julie , Abbasi Qammer H. , Imran Muhammad Ali
Published: December 2024

In the era of the Internet of Things (IoT), the transmission of medical reports in the form of scan images for collaborative diagnosis is vital for any telemedicine network. In this context, ensuring secure transmission and communication is necessary to protect medical data to maintain privacy. To address such privacy concerns and secure medical images against cyberattacks, this research presents a robust hybrid encryption framework that integrates quantum, and classical cryptographic methods. The proposed framework not only secure medical data against cyber threats but also protects the secret security keys. Initially, a Quantum Key Distribution (QKD) is employed to generate a shared key, which is then used to secure the symmetric keys via One-Time Pad (OTP) encryption. Next, bit-planes are extracted from each color component. The rows and columns of the extracted bit-planes are scrambled using random sequences which are generated by a 6D hyperchaotic Chen system and the Ikeda map. To further increase confusion in the original data, multiple-step pixel scrambling operations such as pixel shuffling, pixel value shuffling, and rotational and flipping operations are implemented. After the confusion phase, a combination of affine transformations with non-linear functions, Discrete Cosine Transform (DCT) with complex modulation, Discrete Wavelet Transform (DWT) with random phase modulation, bilinear transformation, and nonlinear polynomial mapping are employed to create diffusion in the scrambled components. These multiple encryption operations aim to maximize randomness in the final ciphertext image. Additionally, to reduce computational complexity, only the Most Significant Bit-Planes (MSBs) are encrypted, as they contain more than 94% of the plaintext information. Several experimental results and analyses are conducted to assess the proposed encryption framework, including entropy analysis, key sensitivity analysis, correlation analysis lossless analysis, and histogram analysis. Furthermore, the framework is tested against various cyberattacks such as brute-force attacks, clipping attacks, and noise attacks on the ciphertext images, to demonstrate its resilience against such threats.
Spinally targeted paired associative stimulation with high-frequency peripheral component induces spinal level plasticity in healthy subjects
Authors: Nätkynmäki Anna , Lauronen Leena , Haakana Piia , Kirveskari Erika , Avela Janne , Shulga Anastasia
Published: December 2024

A novel variant of paired-associative stimulation (PAS) consisting of high-frequency peripheral nerve stimulation (PNS) and high-intensity transcranial magnetic stimulation (TMS) above the motor cortex, called high-PAS, can lead to improved motor function in patients with incomplete spinal cord injury. In PAS, the interstimulus interval (ISI) between the PNS and TMS pulses plays a significant role in the location of the intended effect of the induced plastic changes. While conventional PAS protocols (single TMS pulse often applied with intensity close to resting motor threshold, and single PNS pulse) usually require precisely defined ISIs, high-PAS can induce plasticity at a wide range of ISIs and also in spite of small ISI errors, which is helpful in clinical settings where precise ISI determination can be challenging. However, this also makes the determination of high-PAS level of plasticity induction more challenging and calls for more research on the mechanism of action of high-PAS. We sought to determine if the TMS-induced orthodromic activation in upper motor neurons and PNS-induced antidromic activation in lower motor neurons arriving simultaneously to the intervening synapses at the spinal cord level can be shown to induce acute changes at the targeted location, unlike an otherwise identical but cortically targeted equivalent. Ten healthy subjects participated in two separate sessions, where high-PAS induced activation was set to target spinal (SPINAL) or cortical (CORTICAL) levels with ISI manipulation between otherwise identically applied TMS and PNS pulses. The outcomes were assessed with motor-evoked potentials (MEPs) and Hoffmann (H)-reflex before (PRE), immediately after, and 30 and 60 min after (POST, POST30, POST60) the intervention. MEPs were significantly enhanced in both interventions. In the SPINAL but not in the CORTICAL session, maximal H-reflex amplitudes significantly increased at two timepoints, indicating an increase in spinal excitability. The H/M ratio (maximal H-reflex normalized to maximal M-wave) also showed a significant increase from PRE to POST30 timepoint in the SPINAL session when compared with the CORTICAL equivalent. These results confirm that spinally targeted high-PAS with individualized ISIs indeed has an effect at the spinal level in the sensorimotor system. High-PAS is a novel PAS variant that has shown promising results in motor rehabilitation of individuals with SCI and these new findings contribute to the understanding of its mechanism of action. This provides further evidence for high-PAS as an option for clinical settings to target plasticity at different levels of the corticospinal tract.
Multi-sensor fusion and segmentation for autonomous vehicle multi-object tracking using deep Q networks
Authors: Vinoth K. , Sasikumar P.
Published: December 2024

Autonomous vehicles, often known as self-driving cars, have emerged as a disruptive technology with the promise of safer, more efficient, and convenient transportation. The existing works provide achievable results but lack effective solutions, as accumulation on roads can obscure lane markings and traffic signs, making it difficult for the self-driving car to navigate safely. Heavy rain, snow, fog, or dust storms can severely limit the car’s sensors’ ability to detect obstacles, pedestrians, and other vehicles, which pose potential safety risks. So, we have presented a multi-sensor fusion and segmentation for multi-object tracking using DQN in self-driving cars. Our proposed scheme incorporates the handling of pipelines for camera and LiDAR data and the development of an autonomous solution for object detection by handling sensor images. An Improved Adaptive Extended Kalman Filter (IAEKF) was used for noise reduction. The Contrast enhancement was done using a Normalised Gamma Transformation based CLAHE (NGT-CLAHE), and the adaptive thresholding was implemented using an Improved Adaptive Weighted Mean Filter (IAWMF) which was used for preprocessing. The multi-segmentation based on orientation employs various segmentation techniques and degrees. The dense net-based multi-image fusion gives more efficiency and a high memory in terms of fast processing time. The Energy Valley Optimizer (EVO) approach is used to select grid map-based paths and lanes. This strategy solves complicated tasks in a simple manner, which leads to ease of flexibility, resilience, and scalability. In addition, the YOLO V7 model is used for detection and categorization. The proposed work is evaluated using metrics such as velocity, accuracy rate, success rate, success ratio, mean squared error, loss rate, and accumulated reward.
The comparison of the antioxidant, antibacterial and antiviral potential of Polish fir honeydew and Manuka honeys
Authors: Grabek-Lejko Dorota , Miłek Michał , Dżugan Małgorzata
Published: December 2024

The aim of the present study was to compare the antioxidant, antibacterial and antiviral activities of Podkarpackie coniferous honeydew honey and Manuka honey. The quality of tested honey samples (honeydew-12 and Manuka-4) regarding honey standard was evaluated as well as additional indicators (methylglyoxal, total phenolics and HPTLC phenolic profile, antioxidant potential, glucose oxidase activity, and hydrogen peroxide) were compared. Antibacterial potential was analyzed against Gram-positive (S. aureus and B. cereus) and Gram-negative (E. coli and S. enterica) bacteria. Antiviral activity against different RNA (phi6, MS2) and DNA (T7, phiX174) bacteriophages considered as “viral surrogates” was determined. Based on the determined physicochemical parameters the good quality of tested honeys was confirmed, excluding two samples. The content of polyphenolic compounds in honeydew honey ranged from 583.87 to 1102.42 mg of gallic acid/kg and was strongly correlated with the antioxidant properties. Moreover, for samples with the strongest activity these parameters were comparable to Manuka honey. However, the obtained HPTLC polyphenolic profiles were completely different for honeydew than for Manuka honey which exhibited additional bands (Rf = 0.74 and 0.52). Honeydew honeys were characterized by a strong antiviral and antibacterial properties most of all against Gram-positive bacteria. The MICs (minimal inhibitory concentrations) for S. aureus and B. cereus ranged 15–35% and 8–15% for honeydew and Manuka honeys, respectively. The strongest antiviral properties of honeydew honey were demonstrated mainly against RNA bacteriophages (phi6, MS2) which was even higher than for Manuka honey, especially against MS2 virus. The obtained results suggest that Podkarpackie honeydew honey with the controlled glucose oxidase activity may be a natural substance used to combat viral and bacterial diseases.
Recovery in soil carbon stocks but reduced carbon stabilization after near-natural restoration in degraded alpine meadows
Authors: He Guoxing , Liu Xiaoni , Li Yali , Xu Heguang , Ji Tong , Yang Zhuoli , Qi Hao , Ma Chenglong , Wang Yunjun , Zhang Degang , Lin Dong , Shi Yafei , Jiang Jiachang
Published: December 2024

Near-natural restoration is acknowledged as an effective strategy for enhancing soil organic carbon (SOC) sequestration in degraded grasslands. However, the alterations in SOC fractions, stability, and relative sequestration capacity after restoration of degraded alpine meadows remain uncertain. In this study, we utilized the degraded alpine meadows on the northeastern edge of the Tibetan Plateau as a research area, with grazing as the control (CK) and restoration of 20 years of banned grazing (BG) and growing season resting grazing (RG). We analyzed the characteristics of SOC, SOC fractions, recalcitrant index (RI), and relative capacity of soil C sequestration (SCScapacity) under near-natural restoration measures. The objective of this study was to assess the recovery of SOC following near-natural restoration. The results showed that soil water content (SWC), SOC, soil total nitrogen (TN), and soil total phosphorus (TP) increased, while bulk density (BD) decreased in the degraded alpine meadow after near-natural restoration. In addition, near-natural restoration led to significant increases in particulate organic carbon (POC), readily oxidizable carbon (ROC), dissolved organic carbon (DOC), and microbial biomass carbon (MBC) content (P < 0.05). The SOC stock significantly increased, while the RI decreased. Compared to RG, BG had a greater increase in SOC stock. The study showed that 20 years of near-natural restoration in degraded alpine meadows mainly enhanced soil active carbon pools, while short-term restoration did not increase soil carbon stability. Therefore, avoiding re-exposure to overgrazing is essential to maintaining the restoration effect.
Comparative soil bacterial metabarcoding after aboveground vs. subsurface decomposition of Mus musculus
Authors: Bisker Chawki , Taylor Gillian , Carney Helen , Orr Caroline H. , Javan Gulnaz T. , Ralebitso-Senior Theresia Komang
Published: December 2024

Outdoor microcosms, metabarcoding with next-generation sequencing of the 16S rRNA bacterial gene, total body score (TBS) and physicochemical analyses were used to monitor Mus musculus decomposition aboveground (A) and in the subsurface (S), and compared to soil-only controls (C). As determined by MaAsLin2 analysis, significant shifts in bacterial communities at 30 cm depths within the A, S and C treatments distinguished control from experimental soils, and between aboveground and subsurface deposition, demonstrating the potential for gravesoil discrimination during the first 90 days. For example, Dokdonella (p = 0.0002), Edaphobaculum (p = 0.0004) and Lacibacter (p = 0.0034) recorded significant shifts relative to sampling time. Furthermore, Massilia (p = 0.0005), Mycobacterium (p = 0.0006) and Sandaracinus (p = 0.0007) increased in abundance for the aboveground mice treatments. This was confirmed with ANOSIM where p = 0.0082 showed statistically significant difference between the aboveground and subsurface deposition. TBS and physicochemical analyses suggested that nutrient release into the soils occurred during active decay and skin rapture on days 7–13 in the subsurface and days 13–20 aboveground, with a particular increase in soil potassium concentration on day 15. Significant differences in soil temperatures resulted between A and S vs. C microcosms, aligning with atmospheric temperature changes. In summary, complementary application of metabarcoding, total body score, exogenous and physicochemical methods for postmortem interval estimation and clandestine grave location highlighted the feasibility of using temperature records downloaded from meteorological stations and portable X-ray fluorescence as indicators for various phases of decomposition.
Temporal-thermal enhancement of porous cooking burners
Authors: Soltanian Hossein , Targhi Mohammad Zabetian , Maerefat Mehdi
Published: December 2024

Porous combustion has drawn vast attention over the last few decades leading to a variety of progressing applications particularly in industrial kitchens and household appliances that require time sensitive heating. The present study experimentally investigates the relationship between cooking duration and the thermal efficiency of a cooking pot heated on a porous burner providing a valuable insights into the effectiveness of the heating process in terms of both time and fuel consumption. To facilitate this investigation, a dedicated test bench is designed and constructed, equipped with thermometers and timer to effectively monitor the temporal/thermal behavior of the heating process. A mixed temporal/thermal metric is utilized to evaluate a premixed natural gas fueled porous burner with a typical cooking firing rate (FR) ranging from 800 to 2050 kW/m2. The results show that the optimal burner-pot distance is D = 1.5 cm, minimizing the load-averaged time to thermal efficiency (TT) to 19.5 s. Compared to D = 3 cm with FR = 800 kW/m2, thermal efficiency improves by 5.5%, heating time shortens by 120 s, and average firing rates save 51 s overall. An open conventional burner is also explored to show that by shifting towards temporally promoted porous burners, up to 2 minutes of cooking time could be saved.
Trains scheduling problem with multiple lines
Authors: Danavulapadu Venkata Prathap , Singamsetty Purusotham
Published: December 2024

This study explores the problem of train scheduling (or) train timetabling and its impact on the administration of railway management. This is a highly dependable and effective public transportation system. The problem considers both single and multiple tracks along with multiple platforms with varying train capacities (like speed, passengers, and so on). Let the tracks link two major stations source and destination with intermediate stations. A subset of intermediate stations will function as junctions. A finite number of trains be available at the source for the passengers/cargo transit movements. The profit which is generated from the shipment of passengers between a pair of stations is known in advance. The train’s travel time between the stations and halting time at the stations are predefined. The arrival and departure times at the stations are calculated through the travel time and halting time. All the trains should starts from the source station and continue the journey through the intermediate stations to reach the destination station. Overtaking of the trains is permitted only at the intermediate stations. The trains must make a halt at one or more intermediate stations before reaching the destination. Now the objective is to find the best train operating schedule that maximizes the profit within the admissible travel time threshold. A zero–one integer linear programming is used to model this problem mathematically. For a better understanding of this problem, a case study is considered from the Indian railway network with two major stations Chennai and Hyderabad. A branch and bound $$(B\&B)$$ algorithm is proposed to determine an optimal operating schedule. In addition, the experiments are carried out on a wide range of randomly generated instances of small and medium sizes, to test the efficiency of the algorithm. The computational results indicate that the algorithm is capable of finding the optimal schedules within a reasonable amount of time.
Inhibiting CFTR through inh-172 in primary neutrophils reveals CFTR-specific functional defects
Authors: Da Silva Cunha Ana Lúcia , Blanter Marfa , Renders Janne , Gouwy Mieke , Lorent Natalie , Boon Mieke , Struyf Sofie , Carlon Marianne S.
Published: December 2024

The lungs of people with cystic fibrosis (PwCF) are characterized by recurrent bacterial infections and inflammation. Infections in cystic fibrosis (CF) are left unresolved despite excessive neutrophil infiltration. The role of CFTR in neutrophils is not fully understood. In this study, we aimed to assess which antimicrobial functions are directly impaired by loss of CFTR function in neutrophils. In order to do so, we used a specific inhibitor of CFTR ion channel activity, inh-172. CF neutrophils from PwCF harboring severe CFTR mutations were additionally isolated to further discern CFTR-specific functional defects. We evaluated phagocytosis, reactive oxygen species (ROS) production, neutrophil elastase (NE) and myeloperoxidase (MPO) exocytosis and bacterial killing. The inh-172 model identified decreased acidification of the phagosome, increased bacterial survival and decreased ROS production upon stimulation. In PwCF neutrophils, we observed reduced degranulation of both NE and MPO. When co-culturing neutrophils with CF sputum supernatant and airway epithelial cells, the extent of phagocytosis was reduced, underscoring the importance of recreating an inflammatory environment as seen in PwCF lungs to model immune responses in vitro. Despite low CFTR expression in blood neutrophils, functional defects were found in inh-172-treated and CF neutrophils. The inh-172 model disregards donor variability and allows pinpointing neutrophil functions directly impaired by dysfunctional CFTR.
Forgetting is comparable between healthy young and old people
Authors: Studer Martina , Heinemann Dörthe , Gutbrod Klemens , Henke Katharina
Published: December 2024

Aging is typically associated with declines in episodic memory, executive functions, and sleep quality. Therefore, the sleep-dependent stabilization of episodic memory is suspected to decline during aging. This might reflect in accelerated long-term forgetting, which refers to normal learning and retention over hours, yet an abnormal retention over nights and days. Accelerated long-term forgetting has been observed in dementia, mild cognitive impairment, and in people with memory complaints. Here, we explored whether accelerated long-term forgetting also manifests in healthy aging. We investigated verbal episodic memory in 236 healthy men and women between 18 and 77 years of age. All participants were mentally intact in terms of executive functions, working memory, episodic memory, verbal intelligence, and mood. We related their forgetting rates over one week following learning to their subjective sleep quality and executive functions. Fifteen words were freely recalled and then recognized among 30 distractor words at 30 min and again at one week following learning. Although the healthy older adults compared to the healthy younger adults reported a diminished sleep efficiency and learned fewer words, they exhibited no disproportionate forgetting over days. Hence, accelerated long-term forgetting is not present in healthy aging but might be a first sign of memory dysfunction due to neuropathology.
Aero-TiO2 three-dimensional nanoarchitecture for photocatalytic degradation of tetracycline
Authors: Ciobanu Vladimir , Galatonova Tatiana , Braniste Tudor , Urbanek Pavel , Lehmann Sebastian , Hanulikova Barbora , Nielsch Kornelius , Kuritka Ivo , Sedlarik Vladimir , Tiginyanu Ion
Published: December 2024

One of the biggest issues of wide bandgap semiconductor use in photocatalytic wastewater treatment is the reusability of the material and avoiding the contamination of water with the material itself. In this paper, we report on a novel TiO2 aeromaterial (aero-TiO2) consisting of hollow microtetrapods with Zn2Ti3O8 inclusions. Atomic layer deposition has been used to obtain particles of unique shape allowing them to interlock thereby protecting the photocatalyst from erosion and damage when incorporated in active filters. The performance of the aero-TiO2 material was investigated regarding photocatalytic degradation of tetracycline under UV and visible light irradiation. Upon irradiation with a 3.4 mW/cm2 UV source, the tetracycline concentration decreases by about 90% during 150 min, while upon irradiation with a Solar Simulator (87.5 mW/cm2) the concentration of antibiotic decreases by about 75% during 180 min. The experiments conducted under liquid flow conditions over a photocatalyst fixed in a testing cell have demonstrated the proper reusability of the material.
Nutrient loading as a key cause of short- and long-term anthropogenic ecological degradation of the Salton Sea
Authors: Hung Caroline , Diamond Charles , Sinclair Ryan , Lee Meng-Chen , Stenstrom Michael , Freilich Mara A. , Montgomery Quinn , Marquez Consuelo , Lyons Timothy W.
Published: December 2024

The Salton Sea (SS), California’s largest inland lake at 816 square kilometers, formed in 1905 from a levee breach in an area historically characterized by natural wet-dry cycles as Lake Cahuilla. Despite more than a century of untreated agricultural drainage inputs, there has not been a systematic assessment of nutrient loading, cycling, and associated ecological impacts at this iconic waterbody. The lake is now experiencing unprecedented degradation, particularly following the 2003 Quantification Settlement Agreement—the largest agricultural-to-urban water transfer in the United States. Combined with high evaporation rates, reduced inflows have led to rapid lake shrinkage, with current maximum depths of only 10 m. Here we report distinct temporal and spatial patterns for nutrient dynamics at the SS for two decades spanning the period before and after major water transfer agreement. While external nutrient loading remains relatively consistent year-round, internal cycling varies seasonally. Winter exhibits high total phosphates and nitrate levels due to reduced primary productivity, with lower ammonium concentrations from increased oxygenation. Summer conditions shift to decreased phosphate and nitrate levels from enhanced primary production, sustained partly by internal phosphorus release from sediments during anoxic periods. Although N:P molar ratios can exceed 50:1 to 100:1 (far above the Redfield ratio of 16:1), phosphorus consistently remains at hypereutrophic levels (> 0.05 mg/L) challenging previous assumptions of phosphorus limitation. Post-2020 data show disrupted stratification patterns. Despite higher oxygen levels in bottom waters compared to 2004–2009, overall water column oxygenation has declined, reflecting altered hydrodynamics in the shallowing lake. These changes have intensified environmental challenges stemming from cultural eutrophication including harmful algal blooms, threatening both ecosystem and public health. Effective remediation will require significant reduction in external nutrient loading through constructed wetlands and/or treatment facilities at tributary mouths to reduce the lake’s overall nutrient inventory over time.
Assessing COVID-19 transmission through school and family networks using population-level registry data from the Netherlands
Authors: Garcia-Bernardo Javier , Hedde-von Westernhagen Christine , Emery Tom , van Hoek Albert Jan
Published: December 2024

Understanding the impact of different types of social interactions is key to improving epidemic models. Here, we use extensive registry data—including PCR test results and population-level networks—to investigate the impact of school, family, and other social contacts on SARS-CoV-2 transmission in the Netherlands (June 2020–October 2021). We isolate and compare different contexts of potential SARS-CoV-2 transmission by matching pairs of students based on their attendance at the same or different primary school (in 2020) and secondary school (in 2021) and their geographic proximity. We then calculate the probability of temporally associated infections—i.e. the probability of both students testing positive within a 14-day period. Our results highlight the relative importance of household and family transmission in the spread of SARS-CoV-2 compared to school settings. The probability of temporally associated infections for siblings and parent-child pairs living in the same household ranged from 22.6–23.2%. Interestingly, a high probability (4.7–7.9%) was found even when family members lived in different households, underscoring the persistent risk of transmission within family networks. In contrast, the probability of temporally associated infections was 0.52% for pairs of students living nearby but not attending the same primary or secondary school, 0.66% for pairs attending different secondary schools but having attended the same primary school, and 1.65% for pairs attending the same secondary school. It is worth noting, however, that even small increases in school-related infection probabilities can trigger large-scale outbreaks due to the dense network of interactions in these settings. Finally, we used multilevel regression analyses to examine how individual, school, and geographic factors contribute to transmission risk. We found that the largest differences in transmission probabilities were due to unobserved individual (60%) and school-level (35%) factors. Only a small proportion (3%) could be attributed to geographic proximity of students or to school size, denomination, or the median income of the school area.
Age-specific vulnerability and high prevalence of delirium in pediatric intensive care based on a prospective cohort study
Authors: AlDaithan AbdulRahman , Shaheen Naila , Alahmari Eidah , Smari Abeer Al , Al Ahmadi Arwa , Almalahi Abdulaziz , Alotaibi Msaed , AlGhuraibi Abdullah , Alhusaini Abdulaziz , Bin Shaman Abdullah , Hazwani Tarek
Published: December 2024

Background

Delirium, a neuropsychiatric syndrome characterized by acute disruptions in attention and awareness, significantly impacts children in Pediatric Intensive Care Units (PICUs), leading to prolonged hospitalization, increased infection risk, and dependence on mechanical ventilation. Despite growing recognition, its true burden and risk factors in children remain poorly understood. This prospective cohort study investigated the prevalence, characteristics, and potential therapeutic targets for delirium in 890 children admitted to a tertiary PICU between January and December 2022. Delirium was screened every 12 hours using the validated Cornell Assessment of Pediatric Delirium (CAPD). We analyzed data on demographics, comorbidities, medications, interventions, and clinical outcomes to identify associations with the development of delirium. Our study revealed a high prevalence of delirium, affecting 69.4% (95% CI: 66.33–72.3) of admitted children. Notably, infants were disproportionately affected, accounting for 33.5% of delirium cases. Respiratory diagnoses were significantly associated with delirium (78.6%), while oncology cases had the lowest prevalence (29.4%). Opioid use was identified as a risk factor, increasing the risk of delirium by 45.2%. Furthermore, 97.6% of children with withdrawal syndrome also experienced delirium, highlighting a strong association between these conditions. Delirium was significantly associated with longer PICU stays, and all 20 mortalities during the study period occurred in delirious patients. The adjusted odds ratios from multi-level regression modeling further elucidated the risk factors associated with the development of delirium. This study demonstrates a high prevalence of delirium in PICUs, with infants and those with respiratory diagnoses being particularly vulnerable. Opioid use and withdrawal syndrome emerged as risk factors. Further research is needed to elucidate the mechanisms underlying these associations and develop targeted interventions to prevent, manage, and improve outcomes for children suffering from delirium in critical care settings.
Multi-label classification to predict antibiotic resistance from raw clinical MALDI-TOF mass spectrometry data
Authors: Astudillo César A. , López-Cortés Xaviera A. , Ocque Elias , Manríquez-Troncoso José M.
Published: December 2024

Antimicrobial resistance (AMR) poses a significant global health challenge, necessitating advanced predictive models to support clinical decision-making. In this study, we explore multi-label classification as a novel approach to predict antibiotic resistance across four clinically relevant bacteria: E. coli, S. aureus, K. pneumoniae, and P. aeruginosa. Using multiple datasets from the DRIAMS repository, we evaluated the performance of four algorithms – Multi-Layer Perceptron, Support Vector Classifier, Random Forest, and Extreme Gradient Boosting – under both single-label and multi-label frameworks. Our results demonstrate that the multi-label approach delivers competitive performance compared to traditional single-label models, with no statistically significant differences in most cases. The multi-label framework naturally captures the complex, interconnected nature of AMR data, reflecting real-world scenarios more accurately. We further validated the models on external datasets (DRIAMS B and C), confirming their generalizability and robustness. Additionally, we investigated the impact of oversampling techniques and provided a reproducible methodology for handling MALDI-TOF data, ensuring scalability for future studies. These findings underscore the potential of multi-label classification to enhance predictive accuracy in AMR research, offering valuable insights for developing diagnostic tools and guiding clinical interventions.
Structural MRI study of Pareidolia and Visual Hallucinations in Drug–Naïve Parkinson’s disease
Authors: Ozawa Masakazu , Shiraishi Tomotaka , Murakami Hidetomo , Yoshimaru Daisuke , Onda Asako , Matsuno Hiromasa , Komatsu Teppei , Sakuta Kenichi , Sakai Kenichiro , Umehara Tadashi , Mitsumura Hidetaka , Okano Hirotaka James , Iguchi Yasuyuki
Published: December 2024

Visual hallucinations (VH) and pareidolia, a type of minor hallucination, share common underlying mechanisms. However, the similarities and differences in their brain regions remain poorly understood in Parkinson’s disease (PD). A total of 104 drug-naïve PD patients underwent structural MRI and were assessed for pareidolia using the Noise Pareidolia Test (NPT) were enrolled. Subcortical gray matter volume and cortical surface volume were analyzed using the FreeSurfer software. Structural analyses revealed associations between NPT scores and atrophy in the right thalamus, right hippocampus, right temporal cortex, and right orbitofrontal cortex in all PD participants. These results were almost the same after adjusting for right-handed 97 patients with PD. It is considered that hallucinations in patients with PD are related to altered integration of sensory input (bottom-up) and prior knowledge (top-down) within the visual system. Our findings indicate that pareidolia in PD involves both bottom-up (thalamus and temporal cortex) and top-down (orbitofrontal cortex) processing disturbances; in contrast, VH predominantly involves bottom-up but not top-down regions. Understanding these distinctions could aid in the development of targeted interventions for hallucinations in patients with PD.
Survey evidence on public support for AI safety oversight
Authors: Vesely Stepan , Kim Byungdoo
Published: December 2024

A number of AI safety concerns are being increasingly discussed by experts, including misinformation, invasion of privacy, job displacement, and criminal misuse. Two exploratory studies conducted in Germany and Spain (combined n = 2864) provide evidence that the general public largely supports strict oversight over safety of commercial artificial intelligence research. Among the factors that are associated with preferences for strict oversight are age, anticipated job displacement, innovativeness, and risk, time and altruistic preferences.
Effects of water-fertiliser coupling on the photosynthesis and quality of Lycium barbarum based on predicted crop evapotranspiration (ETc)
Authors: Liang Yunfeng , Feng Dongpu , Sun Zhaojun , Ye Ping , Liang Shengfan , Shi Taiyue
Published: December 2024

Lycium barbarum is an important economic crop in the arid region of Northwest China, and the regulation of irrigation and fertilisation is an important way to improve the quality and yield of Lycium barbarum. To explore the effects of water-fertiliser coupling on photosynthesis, quality and yield of Lycium barbarum under irrigation methods based on predicted crop evapotranspiration (ETc), ETc was calculated via reference evapotranspiration (ETo) predicted on the basis of public weather forecasts, and the irrigation water volume was determined as a proportion of this ETc. A field experiment was conducted via a completely randomised experimental design with five irrigation water volumes (W0 (100% ETc), W1 (90% ETc), W2 (80% ETc), W3 (70% ETc) and W4 (65% ETc)) and three fertiliser application rates (high fertiliser (FH), medium fertiliser (FM) and low fertiliser (FL)). The results revealed that the chlorophyll content, Gsw, Ci of Lycium barbarum leaves and 100-grain weight and yield of fresh fruit of Lycium barbarum increased with increasing irrigation, and the protein content, fat content, total sugar content and polysaccharide content in the dried fruits of Lycium barbarum first increased and then decreased with increasing irrigation under the same level of fertilisation, and the maximum value of these indexes reached 70% ETc − 100% ETc. At the same irrigation level, E, A, Gsw, Ci of Lycium barbarum leaves and protein content, fat content, total sugar content and polysaccharide content in the dried fruits of Lycium barbarum increased and then decreased with increasing of fertiliser application volume, and these indexes reached the maximum value at the fertiliser application rate of FM. A comprehensive evaluation based on principal component analysis (PCA) revealed that the optimum treatment in both years was W0FM (irrigation level of 100% ETc, corresponding to irrigation water in the range of 254.2–309.4 mm, and fertiliser application of N-P2O5-K2O of 315-82-135 kg ha−1), which was significantly greater in 2021 (2022) than in the CK. E, A, Gsw and Ci of daily changes of Lycium barbarum leaves in the W0FM treatment in 2021 (2022) increased by 46.54% (31.53%), 7.08% (59.26%), 18.55% (10.74%) and 34.58% (29.81%), respectively. In 2021 (2022), W0FM treatment increased fat content, polysaccharide content, and betaine content of dried fruits of Lycium barbarum and the 100-grain weight and yield of fresh fruit by 2.88% (10.11%), 1.56% (10.02%), 8.37% (21.69%), 13.57% (24.81%) and 31.39% (71.50%), respectively. The results of this study may provide a theoretical basis for improving the quality and efficiency of Lycium barbarum in the field in the arid zone of Northwest China.
Uniform dipole resonance and suppressed quadrupole resonance for constant transmittivity full phase control plasmonic metasurfaces
Authors: Karmakar Subrata , Ringne Anil , Kumar Nirjhar , Krishnan Ananth
Published: December 2024

Transmission-type plasmonic phase metasurfaces utilizing the Pancharatnam-Berry (PB) phase require constant transmittivity with complete phase variation from 0 to 2$$\pi$$. Usually, this is achieved by rotating metallic nanoparticles in an otherwise uniform lattice arrangement. However, this rotation and the chosen lattice structure cause a significant change in the transmittivity, resulting in a lower intensity of light with certain phases and a higher intensity for other phases. Even though they are called full phase metasurfaces, their intensities can be near maximum or near minimum depending on the rotation and the lattice structure. We show that it is possible to achieve full phase constant transmittivity metasurfaces using the PB phase and the most elementary metallic anisotropic nanoparticles (elliptical) by inserting a thin metal sheet between the nanoparticles and the substrate. Without this metal sheet, while full phase control could be achieved by merely rotating the particles, the transmittivity varies by about 50% depending on the nanoparticles’ orientation. With the metal sheet, full phase control from 0-2$$\pi$$ with a transmittivity variation of only 13%, even in a square lattice, is demonstrated with simulations and experiments. We show that this is due to the annihilation of quadrupole resonances along with broader uniform dipole resonance in the case of the nanoparticles with the metal sheet below. We also show that precise phase control is possible by generating varieties of orbital angular momentum beams and complex beams in the visible spectrum using nanofabricated metasurfaces.
Infectious agent release and Pacific salmon exposure at Atlantic salmon farms revealed by environmental DNA
Authors: Bass Arthur L. , DiCicco Emiliano , Kaukinen Karia H. , Li Shaorong , Johnson Rick , Powell John , Isaac Victor , Dedeluk Nicola B. , Bateman Andrew W. , Miller Kristina M.
Published: December 2024

The potential risk posed by infectious agents (IAs) associated with netpen aquaculture to wild fishes is determined based on the “release” of IAs from netpens into the environment, the “exposure” of the wild fish to those released agents, and the “consequence” for wild fish experiencing infection by those agents. Information available to characterize these three factors is often lacking, and the occurrence of transmission from aquaculture to wild fish as well as potential consequences of such transmission are difficult to observe. In this study, we utilized environmental DNA (eDNA) to characterize the release of dozens of IAs from, and exposure of Pacific salmon to, Atlantic salmon aquaculture. We combined these factors with the consequence of infection, as determined by the literature, to identify IAs that may pose a risk to wild salmon exposed to aquaculture in British Columbia, Canada. Over an 18-month period, eDNA samples were collected from seven active and four inactive netpen aquaculture sites in the Broughton Archipelago, BC. A meta-analytical mean across 22 IAs showed that the odds of IA detection at active sites was 4.3 (95% confidence interval = 2.3:8.1) times higher than at inactive sites, with 11 IAs in particular demonstrating a pattern consistent with elevated release. Oncorhynchus tshawytscha was the only Pacific salmon species presenting eDNA detections more likely to occur around and within active netpens relative to inactive sites. After considering the evidence of negative consequences of infection (from previous literature) in tandem with release model results, we determined that Tenacibaculum maritimum, Tenacibaculum finnmarkense, Ichthyobodo spp., and Piscine orthoreovirus are potential risks to Pacific salmon exposed to marine netpen aquaculture. These IAs, and others demonstrating patterns consistent with release but with insufficient prior research to evaluate the consequences of infection, require further studies that identify the factors influencing the intensity of release, the spatial extent of release around netpens, and the prevalence of infection in wild fish within known distances from netpens.
MXene-based composite photocatalysts for efficient degradation of antibiotics in wastewater
Authors: Akbari Masoud , Rasouli Jamal , Rasouli Kamal , Ghaedi Samaneh , Mohammadi Milad , Rajabi Hamid , Sabbaghi Samad
Published: December 2024

MXene-based (nano)materials have recently emerged as promising solutions for antibiotic photodegradation from aquatic environments, yet they are limited by scalability, stability, and selectivity challenges in practical settings. We formulated Fe2O3-SiO2/MXene ternary nano-photocomposites via coupled wet impregnation and sonochemistry approach for optimised tetracycline (TC) removal (the second most used antibiotic worldwide) from water using response surface methodology-central composite design (RSM-CCD). The photocatalysts containing various loading of Fe2O3/SiO2 (5–45 wt%) on the MXene with a range of calcination temperatures (300–600 °C) via RSM optimisation were synthesised, characterised regarding crystallinity properties, surface morphology, binding energy, and light absorption capability, and analysed for TC degradation efficiency. The 25FeS/MX-450 composite among all samples demonstrated a superior efficiency in TC photocatalytic removal (98%) under optimised conditions (TC degradation: 39.75 mg/L, time: 68.28 min, pH: 5.57, catalyst dosage: 0.75 g/L). The developed surface area, with a reduced band gap due to FeS nanoparticles incorporation with improved light absorption within the visible spectrum, played a crucial role in the 25FeS/MX-450 heterostructure matrix, enhancing photogenerated carriers’ separation and transportation capabilities. The tetracycline photoreduction mechanism involved electron transfer from FeS to the surface of MXene, engaging with O2 to produce •O2−, attributed to the high electron mobility of MXene. Our findings for such nano-photocomposites materials can underscore the considerable potential of MXene-based nanomaterials for pharmaceutical removal from waterways.