bluuebunny/crossref_metadata_2025 huggingface dataset:
A numerical simulation of a novel self-powered implantable respiration sensor based on a triboelectric nanogenerator for medical applications
Authors: Mozaffari Samaneh , Nateghi Mohammad Reza
Published: November 2024

The breathing rate is utilized as a reliable indicator in many cases to predict and diagnose respiratory diseases as well as the respiratory dysfunction caused by diseases such as the cystic fibrosis. Therefore, in this study, a self-powered implantable respiration sensor based on a contact-separation mode triboelectric nanogenerator (TENG) was simulated to monitor the respiratory rates by sensing the variation of the diaphragm muscle. For this purpose, a polytetrafluoroethylene (PTFE) film with a thickness of 160 μm and a nylon film with a thickness of 180 μm are employed as the negative and positive triboelectric materials, respectively. Two copper layer each with a thickness of 100 μm are placed on the outer surfaces of the triboelectric layers as the conducting electrodes. In order to uniformly deform the moving plate of the TENG, it is rigidly attached to the center of the diaphragm through a silicon mechanical coupling element with dimensions of 80 × 80 μm2. The pressure caused by breathing on the diaphragm muscle, which is in the range of 266–666 Pa, is applied to the center of the device diaphragm. The effect of various parameters including external pressure, frequency and surface charge density on the output performance of the device is also investigated. It is evident that higher external pressure results in intensive deformations of the moving plate of the TENG, leading to a more significant energy conversion efficiency of the device. Similarly, increasing the surface charge density causes an increase in all electrical output parameters. Moreover, the device achieves an output power of 0.209 nW at a load resistance of 20 GΩ by applying a constant pressure of 666 Pa at a frequency of 0.24 Hz. All the results demonstrate the potential of the new proposed sensor for detecting and monitoring real-time respiratory rates with high sensitivity and clinical applications.
A new basic air shower observable sensitive to the cosmic-ray elemental mass
Authors: Basak A , Dey R K
Published: November 2024

Based on a Monte Carlo simulation study of vertical extensive air showers (EAS) at the KASCADE location we introduce a new simple observable η

ρ(45;310) (in short η

ρ
) - the ratio between two lateral electron densities of an EAS measured at two well-defined radial distances indicated by the characteristic radial feature of the local age parameter (LAP). Our analyses of simulated data generated by the Group I nuclei with cosmic-ray elemental masses, A
actual = 1, 4, 12, 16, 24, 32, 40, 56, observed a double correlation of η

ρ
with, (i) the lateral shower age s
av, and (ii) A
actual of the EAS initiating primary particle. Applying the first correlation to a new set of simulated showers initiated by the Group II nuclei with A
actual = 7, 14, 20, 28, 40, 52, the average difference between the lateral shower age s
av obtained directly from the conventional LAP approach and the estimated one s
est is found to be close to 0. The second correlation involving η

ρ
with A
actual applied to the set of such showers estimates the average atomic mass

〈
ln

A

est

〉

of their shower initiating primaries, utilizing the η

ρ
s. Results of the work revealed that the method of estimating the lateral shower age is almost high-energy interaction model-independent. A certain level of model dependence is albeit found in the case of

〈
ln

A

est

〉

estimation.
Dependence of metrics and noise intensity on escape dynamics: mean first exit time and escape probability
Authors: Zheng Miaolei , Wang Hui , Wang Ying , Chen Xi
Published: November 2024

This paper focuses on analyzing two deterministic quantities of the dynamics of stochastic systems, mean first exit time and escape probability. Through a detailed exploration of the escape phenomenon, we have successfully fitted the complex dynamics of the mean first exit time as a function of interval length (area size) and noise intensity, respectively. We have found that the mean first exit time tends to increase monotonically with the interval length (area size). Meanwhile, we also accurately captured the dynamical behavior of the minimum escape probability under various parameter cases. The relationship between them displays a range of patterns when we observed different intervals. Our research highlights the importance of noise effects when considering escape processes, especially in the context of interaction of interval length (area size) and noise intensity. A concrete error analysis is conducted to ensure the accuracy and generalization ability of the model’s predictions.
Maximum power transfer theorem with arbitrary Efficiency for Wireless Power Transfer
Authors: Sawayama Noboru
Published: November 2024

Wireless power transfer (WPT) has been actively studied by many companies and research institutes for decades, and individual technologies have been highly developed. However, except for nearly contact WPT, it has not yet reached a standard adopted by multiple manufacturers. We believe that this is due to the lack of theory to evaluate the feasibility and validity of these proposals, while the market has high expectations for EV charging, which has led to unfeasible high specifications and many proposals for improvements. If non-physical proposals cannot be rejected, there is no way to set standard targets at a feasible level. The WPT consists of an electric circuit (Kirchhoff domain) that follows Kirchhoff’s law and a non-contact power transfer part (Maxwell domain) that follows Maxwell’s equations. Here, we show that by introducing the conduction wire electric field confinement by the free-electron model into the Axiomatic Maxwell’s equations (derived from the principle of relativity and the principle of action), the Kirchhoff and Maxwell domains can be integrated without contradiction. Furthermore, this study demonstrates the maximum power transfer theorem with arbitrary efficiency in the Kirchhoff domain, enabling the determination of all circuit constants necessary to meet specified requirements. Additionally, numerical analyses are presented to illustrate the application of this theorem in practical circuits, including switching power supplies and batteries.
3D MHD modelling of plasmoid drift following massive material injection in a tokamak
Authors: Kong M. , Nardon E. , Bonfiglio D. , Hoelzl M. , Hu D. ,   the JOREK Team,   JET Contributors,   the EUROfusion Tokamak Exploitation Team
Published: November 2024

Mechanisms of plasmoid drift following massive material injection are studied via 3D non-linear MHD modelling with the JOREK code, using a transient neutral source deposited at the low field side midplane of a JET H-mode plasma to clarify basic processes and compare with existing theories. The simulations confirm the important role of the propagation of shear Alfvén wave (SAW) packets from both ends of the plasmoid (‘SAW braking’) and the development of external resistive currents along magnetic field lines (‘Pégourié braking’) in limiting charge separation and thus the

E

×

B

plasmoid drift, where E and B are the electric and magnetic fields, respectively. The drift velocity is found to be limited by the SAW braking on the few microseconds timescale for cases with relatively small source amplitude while the Pégourié braking acting on a longer timescale is shown to set in earlier with larger toroidal extent of the source, both in good agreement with existing theories. The simulations also identify the key role of the size of the

E

×

B

flow region on plasmoid drift and show that the saturated velocity caused by dominant SAW braking agrees well with theory when considering an effective pressure within the

E

×

B

flow region. The existence of SAWs in the simulations is demonstrated and the 3D picture of plasmoid drift is discussed.
Macroporous coating of silver-doped hydroxyapatite/silica nanocomposite on dental implants by EDTA intermediate to improve osteogenesis, antibacterial, and corrosion behavior
Authors: Farmani Maryam , Mirahmadi-Zare Seyede Zohreh , Masaeli Elahe , Tabatabaei Farideh , Houreh Arezou Baharlou
Published: November 2024

Coating a titanium (Ti) implant with hydroxyapatite (HA) increases its bioactivity and biocompatibility. However, implant-related infections and biological corrosion have restricted the success of implant. To address these issues, a modified HA nanocomposite (HA/silica-EDTA-AgNPs nanocomposite) was proposed to take advantage of the sustained release of silver nanoparticles (AgNPs) and silicate ions through the silica-EDTA chelating network. As a result, a uniform layer of nanocomposite, compared to HA as the gold standard, was formed on Ti implants without fracture and with a high level of adhesion, using plasma electrolytic oxidation (PEO). Bioactivity assessment evidenced a shift in the surface phase of the Ti implant to generation of beta-tricalcium phosphate, a more bioresorbable material than HA. Metabolic activity assessments using human dental pulp stem cells revealed that Ti surfaces modified by the new nanocomposite are superior to bare and HA-modified Ti surfaces for cell attachment and proliferation in vitro. In addition, it successfully inhibited bacterial growth and induced osteogenesis on the implant surface. Finally, potentiodynamic polarization behavior of Ti implants before and after coating confirmed that a thick oxide interface layer on the modified Ti surface acts as an electrical barrier and protects the substrate layer from corrosion. Therefore, the HA/silica-EDTA/Ag nanocomposite presented here, compared to HA, can better coat Ti dental implants due to its good biocompatibility and osteoinductive activity, along with improved biological stability.
Enhancing the porosity of biphasic calcium phosphate using polyethylene glycol as the porogen for bone regeneration applications
Authors: Nguyen Hong Anh Phuong , Nguyen Ngoc Hoi , Ho Quoc Vinh , Nguyen Luan Minh , Le Ngoc Thuy Trang , Thi Phuong Le , Yen Pham Nguyen Dong , Cu Thanh Son , Nguyen Thi Thanh Thuy , Nguyen Dai Hai
Published: November 2024

Biphasic calcium phosphate (BCP) has been used as a material to support bone grafting, repair, recovery, and regeneration over the past decades. However, the inherent weakness of BCP is its low porosity, which limits the infiltration, differentiation, and proliferation of bone cells. To address this issue, porous BCP was synthesized using polyethylene glycol (PEG) 1000 with weight ratio ranging from 20%–60% in BCP as the porogen through the powder-forming method. Analytical methods such as Fourier transform infrared spectroscopy, x-ray diffraction, scanning electron microscopy were used to demonstrate the purity, morphology and functional groups on the material surface of the obtained BCP samples. Structurally, the BCP sample with 60% PEG, named B60, possessed the highest porosity of 71% and its pore diameters ranging from 5 to 75 µm. Besides, the in vitro biocompatibility of B60 material have been demonstrated on the L929 cell line (90% cell viability) and simulated body fluid (apatite formation after 1 d). These results suggested that B60 should be further studied as a promising artificial material for bone regenerating applications.
A hybrid statistical–dynamical framework for compound coastal flooding analysis
Authors: Wang Zhenqiang , Leung Meredith , Mukhopadhyay Sudarshana , Sunkara Sai Veena , Steinschneider Scott , Herman Jonathan , Abellera Marriah , Kucharski John , Nederhoff Kees , Ruggiero Peter
Published: November 2024

Compound coastal flooding due to astronomic, atmospheric, oceanographic, and hydrologic drivers poses severe threats to coastal communities. While physics-driven approaches are able to dynamically simulate temporally and spatially varying compound flooding generated by multiple drivers with correlations between some of them, computational burdens limit their capability to explore the full range of conditions that contribute to compound coastal hazards. Data-driven statistical approaches address some of these computational challenges; however, they are also unable to explore all possible forcing combinations due to short observational records, and projections are typically limited to a few locations. This study proposes a hybrid statistical–dynamical framework for compound coastal flooding analysis that integrates a stochastic generator of compound flooding drivers, a hydrodynamic model, and machine learning-based surrogate models. The framework was demonstrated in San Francisco Bay (SF) over the past 500 years with accuracy similar to the physics-driven approach but with much higher computational efficiency. The stochastic generator of compound flooding drivers is developed by coupling a sea surface temperature (SST) reconstruction model with a climate emulator, weather generator, and model of the hydrological and reservoir system. Using reconstructed SSTs as input, the generator of compound flooding drivers is employed to simulate time series of the forcing factors contributing to compound flooding (e.g. surge, waves, river discharge, etc) in SF Bay. A process-based hydrodynamic model is built to predict total water levels varying in time and space throughout SF Bay based on stochastically generated drivers. The machine learning-based surrogate models are then developed from a relatively small library (several hundred) of hydrodynamic model simulations to efficiently predict water levels for compound flooding analysis under the full range of stochastic drivers. This study contributes a hybrid statistical–dynamical framework to better understand the spatial distribution and temporal evolution of compound coastal-fluvial flooding, along with the relative contributions of drivers in complex nearshore, estuarine, and river environments for centennial timescales under past, present, and future climates.
Effect of phantom‐making error in the calculation of quantitative values of single‐photon emission computed tomography/computed tomography using system planar sensitivity
Authors: Nojima Yuta , Yamazaki Yoshihiro
Published: November 2024

This study aimed to clarify the effect of the accuracy of phantom-making on quantification accuracy in the measurement of system planar sensitivity using a disc source. We measured the system planar sensitivity using the method recommended by the equipment manufacturer. A container of 99mTc solution was placed at a height of 10 cm from the surface of the collimator using styrofoam. The system planar sensitivity was the average of the values obtained from the two detectors, the measurements were taken thrice. The system planar sensitivity values obtained when the disc source size (5.0, 14.5 and 20 cm), solution volume (50, 100 and 150 ml) and radioactivity (nine points between 36 MBq and 505 MBq) changed were used to evaluate the quantification accuracy. The relative error for the 5.0 cm source significantly exceeded for the other source sizes (p < 0.05); however, no statistically significant difference was observed between the 14.5 cm and 20.0 cm sources. The smaller the solution volume, the smaller the relative error and the higher the quantification accuracy. The quantification accuracy increased as radioactivity decreased. The relative error was lowest at 36 MBq and highest at 505 MBq, with a difference of approximately 10%. Quantification accuracy improved as the size of the surface source exceeded 14.5 cm and the amount of solution decreased. Radioactivity at the time of measurement significantly affected quantification accuracy and 73–103 MBq of radioactivity was sufficient for repeatable and quantification accuracy.
Effect of Cherenkov light on cell survival in x-ray irradiation of LINAC based on Monte Carlo simulation and cell survival measurements
Authors: Hirano Yoshiyuki , Terada Yuka
Published: November 2024

Cherenkov radiation is emitted during x-ray irradiation in a linear accelerator (LINAC). Cherenkov light contains many short wavelength components, including ultraviolet (UV) light, which is well-known for its bactericidal effects. A similar phenomenon is probable for human cancer cells. To assess the effect of Cherenkov light on cell death in x-ray irradiation, we employed simulations and UV cell survival data. We measured the survival rates of HeLa cells exposed to 254 nm (UVC) and 310 nm (UVB) light to determine the 50% lethal dose (LD50) required to kill 50% of the cells. For other wavelengths, we utilized literature values to establish the relationship between wavelength and LD50. Due to the broad range of the Cherenkov light spectrum, we need LD50 as a function of wavelength to estimate cell survival solely from Cherenkov light. A Monte Carlo simulation was used to calculate the fluence distribution of Cherenkov light in a 300 mm3 phantom comprised of soft tissue, both with and without absorption of visible light. The latter scenario is considered to be most influenced by Cherenkov light. By combining the fluence distribution and the wavelength-LD50 relationship, we determined the distribution of the survival rate. Our findings indicate that, in the absence of absorption, a radiation dose of approximately 90 Gy or greater is necessary for Cherenkov light to have any effect. As a result, the impact of Cherenkov light on cell survival can be considered negligible for typical dose of 2 Gy.
Monitoring and predicting marine heatwaves in Vanuatu
Authors: Bhardwaj Jessica , Kuleshov Yuriy
Published: November 2024

Marine Heatwaves (MHWs) have disastrous impacts on ecosystems and communities in the south-west Pacific but there is limited research investigating their onset and evolution in this region. In collaboration with local fisheries and marine sectors, this study applied a MHW framework to define and categorize MHW events in the waters around Vanuatu. A range of events amongst the most intense and longest were investigated, as well as an anecdotally notable event from February 2016. This event was neither in the top five longest, nor the most intense of events, highlighting how impacts in marine ecosystems are non-linear and have cascading interactions with a region’s exposure and vulnerability. In analysing these events, we also explore how sub-seasonal to seasonal (S2S) prediction can be used to forecast MHW events. Hindcasts from the Bureau of Meteorology’s operational coupled ocean-atmosphere model were used to create weekly and monthly forecasts for each MHW event in the period from 1980 to 2018. We found that chance above 90th percentile hindcasts had promising accuracy with average hit rates highest for lead 0 weekly and monthly hindcast but conclude that hindcast accuracy is not always indicative of real time forecast accuracy as real time forecasts use a larger set of model ensembles. We also investigated an event outside the hindcast study period (May 2022) due to its notably ‘off the charts’ impacts. This event was the longest and most intense event on record, surpassing the previously longest and most intense event by 144 days and 0.56 °C. As climate change intensifies, such extreme events will become more frequent and will likely compound with other extremes, making the use and uptake of monitoring and prediction services critical to the long-term resilience of marine-reliant communities and sectors.
Resonant structure for improved directionality and extraction of single photons
Authors: Chowdhury Sagar , Rituraj  , Krishnamurthy Srini , Bhallamudi Vidya Praveen
Published: November 2024

Fluorescent atomic defects, particularly in dielectric materials such as diamond, are promising for several emerging quantum applications. However, efficient light extraction, directional emission, and narrow spectral emission are key challenges. We have designed a dielectric metasurface exploiting Mie-resonance and Kerker conditions to address these issues. Our designed diamond metasurface, tailored for nitrogen-vacancy (NV) defect centers in diamond, predicts up to 500× improvement in the collection of 637 nm (zero phonon line) photons over that from the bare diamond. Our design achieves highly directional emission, predominantly emitting in a

20
∘

lobe in the forward direction. This makes the light collection more efficient, including fiber-based collection. The predicted results are stable against the position of the emitter placed in the metaelement, thus alleviating the challenging fabrication requirement of precise positioning of the defect center. Equally importantly, our design approach can be applied to enhance single photon emission also from other defects such as SiV, other materials such as hBN, and other sources such as quantum dots.
Atmospheric water harvesting using a desiccant-based solar still: experimental investigation and economic analysis
Authors: Safoui Rachid , Belaaribi Rachida , Achahour Omar , Elfanaoui Abdeslam , Ihlal Ahmed , Mouaky Ammar , Amagour Mohamed El Habib , Abou Oualid Hicham , Awad Mohamed M
Published: November 2024

Water scarcity is currently a major worldwide issue, and many unconventional solutions are being tested to provide water to populations in remote areas. A promising method involves harvesting water from ambient air using a humidity adsorbent and solar energy. This approach was explored through a desiccant-based solar still, using river sand impregnated with a calcium chloride solution. The sorption-desorption stability of the bed sorbent was studied over five consecutive days. Absorption occurred at night, allowing the bed to capture water vapor from the surrounding air. Various parameters that influenced the kinetics of water vapor absorption were studied. The results showed that the bed could harvest 671.02 ml m−2 of water vapor from the ambient air at an average ambient temperature of 25 °C and an average relative humidity of 80%. The daytime process involved simultaneous desiccant regeneration and water vapor condensation. Several parameters were recorded during the trials to evaluate their influence on the evaporation rate and collected condensate. Experimental findings showed that the total amount of evaporated water is affected by the initial desiccant concentration in the bed and the cumulative solar energy. Optimal conditions yielded 908.67 ml m−2 of evaporated water at an initial desiccant concentration of 50% and 25.47 MJ m−2 of solar energy. The water yield ranged from 561.51 ml m−2 to 645.39 ml m−2, with a maximum energy efficiency of 24.60%. The estimated cost of collected water was $0.086 per liter, with a payback period of 18.25 months.
Establishing best practices for modeling multi-day energy storage in deeply decarbonized energy systems
Authors: Mantegna Gabriel , Ricks Wilson , Manocha Aneesha , Patankar Neha , Mallapragada Dharik , Jenkins Jesse
Published: November 2024

Multi-day energy storage (MDS), a subset of long-duration energy storage, may become a critical technology for the decarbonization of the power sector, as current commercially available Lithium-ion battery storage technologies cannot cost-effectively shift energy to address multi-day or seasonal variability in demand and renewable energy availability. MDS is difficult to model in existing energy system planning models (such as electricity system capacity expansion models (CEMs)), as it is much more dependent on an accurate representation of chronology than other resources. Techniques exist for modeling MDS in these planning models; however, it is not known how spatial and temporal resolution affect the performance of these techniques, creating a research gap. In this study we examine what spatial and temporal resolution is necessary to accurately capture the full value of MDS, in the context of a continent-scale CEM. We use the results to draw conclusions and present best practices for modelers seeking to accurately model MDS in a macro-energy systems planning context. Our key findings are: (1) modeling MDS with linked representative periods is crucial to capturing its full value, (2) MDS value is highly sensitive to the cost and availability of other resources, and (3) temporal resolution is more important than spatial resolution for capturing the full value of MDS, although how much temporal resolution is needed will depend on the specific model context.
Understanding and Effectively Utilizing Experiential Therapy
Authors: Laser Julie Anne , Nicotera Nicole
Published: November 2024

This book is about the clinical modality of Experiential Therapy with the addition of mindfulness practices and a trauma-sensitive lens. Experiential Therapy provides hands-on, engaged, holistic experiences aimed at exploring, better understanding, and resolving clinical issues. The experience is a conduit that gives rise to words, thoughts, feelings, and future actions that the client would not have found through traditional talk therapy alone. Experiential Therapy is an alternative to traditional talk therapy because the clients and clinicians are actively and physically engaged in activities that foster introspection, change, well-being, and resilience. Movement and/or being outdoors creates an atmosphere where clinical conversations are often more natural and less forced than in an office or online. Due to this, clients are often more open and willing to do the work of clinical therapy.
Experiential Therapy Activities With Specific Group Characteristics
Authors: Laser Julie Anne , Nicotera Nicole
Published: November 2024

Chapter 11 discusses Experiential Therapy with some of the diverse populations the authors work with: survivors of human trafficking, veterans and military service members, persons with substance use disorders (SUDs), juvenile justice–involved youth, and grief groups. The authors discuss specific issues that each group needs to address in therapy and strategies and considerations for each specific group (survivors of human trafficking, veterans and military service members, persons with substance use disorders (SUDs), juvenile justice–involved youth, and grief groups). They share twelve Experimental Therapy activities for these particular groups. These may not be the specific populations that the reader works with, but the reader can see how versatile Experiential Therapy is for a variety of populations. This also gives the reader more activities that can be modified for their particular clientele.
Locating the Scientific Sublime
Authors: Glauthier Patrick
Published: November 2024

This chapter considers the definition of the sublime and methods for locating it in ancient texts. Important concepts include the sublime subject, greatness of soul, the flight of the mind, and the view from above. The scientific sublime itself emerges as a discourse that configures the study of nature as an exhilarating adventure through which our consciousness expands and our perspective shifts as we leave behind the trivialities of everyday life and approach something that appears truer and more real, something divine. Frequently, images of falling underscore the potentially electrifying proposition that we may not arrive at correct or even consistent answers; this paradigm is related to the idea of flawed sublimity, and an important model for it is Phaethon. The chapter concludes with a survey of philosophical and rhetorical discussions that link natural inquiry with the sublime. Illustrative passages come from Plato, Aristotle, Cicero, Lucretius, Virgil, Ovid, Horace, Longinus, and others.
Thatcher, the New Right, and Rebel Tours in the Early 1980s
Authors: Llewellyn Matthew P , Rider Toby C
Published: November 2024

This chapter begins in 1979 with the election of the Conservative Prime Minister, Margaret Thatcher, and delves into the attitudes of the ‘New Right’ to the sporting boycott throughout the early 1980s. In particular, we focus our attention on the actions of the Tory MP, John Carlisle, a dedicated ‘Thatcherite’ and the most public and persistent critic of the Gleneagles Agreement. Interestingly, as we show, Thatcher struggled to reconcile her instinct to support South Africa with the practical challenges of Gleneagles. Conservative strategists recognized that withdrawing from the Agreement could be a political disaster, so much so that when Thatcher swept to victory in the General Election, she refused to renege on Britain’s obligations to Gleneagles, despite the fact that it ran counter to her broader policy of ‘constructive engagement’ with Pretoria. Carlisle spearheaded a campaign for Britain to break with the Commonwealth consensus and, in so doing, absorbed support from a growing body of Tory MPs and the wider bridge-building community. Using and applying core principles of ‘New Right’ social and economic policy, Carlisle and others reformulated the bridge-builder thesis to a point that it clearly aligned with Thatcher’s own vision on the size, scope, and policies of a British government. For the leaders of the sports boycott in Britain, it soon became clear where Thatcher’s real sympathies lay. As emboldened British teams rebelled against the boycott and thrust British sport back into the dock of international opinion during the early 1980s, the Prime Minister tended to say that she would uphold Gleneagles, rarely that she thought it was right or just.
Interconnected idioblasts in Peltaea polymorpha: a novel component of the mucilage-secretory apparatus in Malvaceae
Authors: Rodrigues Tatiane Maria , de Almeida Aline Rodrigues , de Nicolai Juan , dos Santos Igor Soares , Machado Silvia Rodrigues
Published: November 2024

The anatomical and cytological characteristics of the mucilage-secretory system have been widely studied in Malvaceae. However, conflicting information regarding the morphological nature of secretory structures exists, and some remain poorly understood. In this sense, some secretory structures in Malvaceae are not characterized as typical isolated idioblasts, canals, or cavities. Here, we describe a novel component of the mucilage-secretory apparatus in the Malvaceae family. Samples of the shoot apex, mature stem and fully expanded leaves were obtained from adult Peltaea polymorpha, which grow in the Cerrado (Brazilian savanna). The samples were processed using standard light and transmission electron microscopy methods. Mucilage cells occurred in the cortex and pith of petioles and stems, and in the midrib of leaves. These cells originate early in the stem apex from successive divisions of cells of the fundamental meristem, resulting in a row of interconnected secretory cells enveloped by a sheath of parenchyma cells devoid of secretory activity. Mucilage is stored in both protoplast and apoplast. In the same row, some cells filled with mucilage become very swollen and compress the neighbouring idioblasts that become flattened. This phenomenon results in a sandwich panel structure consisting of the swollen transversal walls of adjacent cells. As the differentiation progresses, the transversal walls of the rowed mucilage cells became very swollen, multilayered, and porous. Cytoplasmic strands cross such transversal walls connecting rowed cells. Mucilage-secreting cells in P. polymorpha are interconnected idioblasts and represent a novel component of the mucilage-secretory apparatus in Malvaceae. These findings open new avenues for understanding the structure and dynamics of mucilage-secreting cells from a functional perspective.
TriTan: an efficient triple nonnegative matrix factorization method for integrative analysis of single-cell multiomics data
Authors: Ma Xin , Lin Lijing , Zhao Qian , Iqbal Mudassar
Published: November 2024

Single-cell multiomics have opened up tremendous opportunities for understanding gene regulatory networks underlying cell states by simultaneously profiling transcriptomes, epigenomes, and proteomes of the same cell. However, existing computational methods for integrative analysis of these high-dimensional multiomics data are either computationally expensive or limited in interpretation. These limitations pose challenges in the implementation of these methods in large-scale studies and hinder a more in-depth understanding of the underlying regulatory mechanisms. Here, we propose TriTan (Triple inTegrative fast non-negative matrix factorization), an efficient joint factorization method for single-cell multiomics data. TriTan implements a highly efficient factorization algorithm, greatly improving its computational performance. Three matrix factorization produced by TriTan helps in clustering cells, identifying signature features for each cell type, and uncovering feature associations across omics, which facilitates the identification of domains of regulatory chromatin and the prediction of cell-type-specific regulatory networks. We applied TriTan to the single-cell multiomics data obtained from different technologies and benchmarked it against the state-of-the-art methods where it shows highly competitive performance. Furthermore, we showed a range of downstream analyses conducted utilizing TriTan outputs, highlighting its capacity to facilitate interpretation in biological discovery.
Keeping it in the family: using protein family templates to rescue low confidence AlphaFold2 models
Authors: Costa Francesco , Blum Matthias , Bateman Alex
Published: November 2024

Motivation

High confidence structure prediction models have become available for nearly all protein sequences. More than 200 million AlphaFold2 models are now publicly available. We observe that there can be significant variability in the prediction confidence as judged by plDDT scores across a protein family. We have explored whether the predictions with lower plDDT in a family can be improved by the use of higher plDDT templates from the family as template structures in AlphaFold2.

Results

Our work shows that about one-third of the time structures with a low plDDT can be “rescued,” moved from low to reasonable confidence. We also find that surprisingly in many cases we get a higher plDDT model when we switch off the multiple sequence alignment (MSA) option in AlphaFold2 and solely rely on a high-quality template. However, we find the best overall strategy is to make predictions both with and without the MSA information and select the model with the highest average plDDT. We also find that using high plDDT models as templates can increase the speed of AlphaFold2 as implemented in ColabFold. Additionally, we try to demonstrate that as well as having increased overall plDDT, the models are likely to have higher quality structures as judged by two metrics.

Availability and implementation

We have implemented our pipeline in NextFlow and it is available in GitHub: https://github.com/FranceCosta/AF2Fix.
Fast polypharmacy side effect prediction using tensor factorization
Authors: Lloyd Oliver , Liu Yi , Gaunt Tom R
Published: November 2024

Motivation

Adverse reactions from drug combinations are increasingly common, making their accurate prediction a crucial challenge in modern medicine. Laboratory-based identification of these reactions is insufficient due to the combinatorial nature of the problem. While many computational approaches have been proposed, tensor factorization (TF) models have shown mixed results, necessitating a thorough investigation of their capabilities when properly optimized.

Results

We demonstrate that TF models can achieve state-of-the-art performance on polypharmacy side effect prediction, with our best model (SimplE) achieving median scores of 0.978 area under receiver-operating characteristic curve, 0.971 area under precision–recall curve, and 1.000 AP@50 across 963 side effects. Notably, this model reaches 98.3% of its maximum performance after just two epochs of training (approximately 4 min), making it substantially faster than existing approaches while maintaining comparable accuracy. We also find that incorporating monopharmacy data as self-looping edges in the graph performs marginally better than using it to initialize embeddings.

Availability and implementation

All code used in the experiments is available in our GitHub repository (https://doi.org/10.5281/zenodo.10684402). The implementation was carried out using Python 3.8.12 with PyTorch 1.7.1, accelerated with CUDA 11.4 on NVIDIA GeForce RTX 2080 Ti GPUs.
lefser: implementation of metagenomic biomarker discovery tool, LEfSe, in R
Authors: Khleborodova Asya , Gamboa-Tuz Samuel D , Ramos Marcel , Segata Nicola , Waldron Levi , Oh Sehyun
Published: November 2024

LEfSe is a widely used Python package and Galaxy module for metagenomic biomarker discovery and visualization, utilizing the Kruskal–Wallis test, Wilcoxon Rank-Sum test, and Linear Discriminant Analysis. R/Bioconductor provides a large collection of tools for metagenomic data analysis but has lacked an implementation of this widely used algorithm, hindering benchmarking against other tools and incorporation into R workflows. We present the lefser package to provide comparable functionality within the R/Bioconductor ecosystem of statistical analysis tools, with improvements to the original algorithm for performance, accuracy, and reproducibility. We benchmark the performance of lefser against the original algorithm using human and mouse metagenomic datasets.

Availability and implementation

Our software, lefser, is distributed through the Bioconductor project (https://www.bioconductor.org/packages/release/bioc/html/lefser.html), and all the source code is available in the GitHub repository https://github.com/waldronlab/lefser.
easySCF: a tool for enhancing interoperability between R and Python for efficient single-cell data analysis
Authors: Zhang Haoyun , Zhang Wentao , Zhao Shuai , Xu Guangyu , Shen Yi , Jiang Feng , Qin An , Cui Lei
Published: November 2024

This study introduces easySCF, a tool designed to enhance the interoperability of single-cell data between the two major bioinformatics platforms, R and Python. By supporting seamless data exchange, easySCF improves the efficiency and accuracy of single-cell data analysis.

Availability and implementation

easySCF utilizes a unified data format (.h5 format) to facilitate data transfer between R and Python platforms. The tool has been evaluated for data processing speed, memory efficiency, and disk usage, as well as its capability to handle large-scale single-cell datasets. easySCF is available as an open-source package, with implementation details and documentation accessible at https://github.com/xleizi/easySCF.
Imaging and endovascular management of haemoptysis in congenital heart disease
Authors: Chacko Vimal , Radhakrishnan Jayakrishnan , Valakkada Jineesh , Ayyappan Anoop , Kannath Santhosh , Kumar Deepa S , Gopalakrishnan Arun
Published: November 2024

Haemoptysis, a rare but serious complication that can arise in patients with congenital heart disease, necessitates prompt diagnosis and specialized care. The radiologist plays a critical role in this scenario, including identifying the source of haemoptysis, devising treatment plans, and delivering endovascular interventions. This article highlights the importance of imaging techniques, especially computed tomography, in identifying the cause of haemoptysis and the therapeutic value of endovascular interventions. Furthermore, a suggested algorithmic approach is presented to assist with the diagnostic and management process.
Decoupling of motor cortex to movement in Parkinson’s dyskinesia rescued by sub-anaesthetic ketamine
Authors: Vishwanath Abhilasha , Bartlett Mitchell J , Falk Torsten , Cowen Stephen L
Published: November 2024

Gamma band and single-unit neural activity in primary motor cortex (M1) are involved in the control of movement. This activity is disrupted in Parkinson’s disease (PD) and levodopa-induced dyskinesia (LID), a debilitating consequence of dopamine replacement therapy for PD. Physiological features of LID include pathological narrowband gamma oscillations, finely tuned gamma (FTG), and altered M1 firing activity. Since most studies characterize LID through visual scoring, little is known about the relationships between ongoing dyskinetic movements, gamma, and neuronal activity at fast (sub-second) and slow (seconds) timescales. Here, we investigate how motor cortex activity changes with movement at multiple timescales in animal models of PD and LID. Furthermore, sub-anesthetic ketamine has emerged as a possible therapy for LID. How ketamine may reduce LID is not fully understood. Consequently, we investigate how ketamine affects the relationship between motor cortex activity and movement.

To investigate these questions, local-field and single-unit activity from >3000 motor cortex neurons was acquired using a standard model of PD/LID (n = 10 male rats). Data in LID and sham animals was acquired following levodopa (L-DOPA; 12 mg/kg, i.p.) and ketamine (20 mg/kg, i.p.) administration. Movement was assessed using traditional abnormal involuntary movements (AIMs) scores and head-mounted inertial sensors sampled at 200 Hz.

While correlations between movement, gamma, and single-unit activity were high in all animals during control conditions, correlations decreased considerably in animal models of LID following L-DOPA administration. This suggests that M1 can become functionally decoupled from ongoing movements in LID. Interestingly, this effect was observed in both the dopamine depleted and non-depleted hemispheres. Ketamine disrupted FTG, decreased LID, and moderately increased single-unit correlations to movement during LID. Ketamine, however, did not enhance the correlation between gamma-band activity and movement. Finally, ketamine exerted a selective effect on neuronal interactions and ensemble activity in LID animals. Specifically, analysis of cell-pair firing-rate correlations showed that ketamine induced a distinct neural ensemble state in LID by reorganizing the pattern of cell-pair interactions.

These findings provide insight into the role that motor cortex neurons and gamma-band activity play during healthy movement and LID. Results suggest that primary motor cortex does not directly trigger specific dyskinetic movements during LID but, instead, dysregulated motor cortex activity may permit aberrant movements to spontaneously emerge in downstream circuits. These data further support the anti-dyskinetic properties of ketamine and suggest that ketamine acts to reduce LID by disrupting pathological interactions between motor cortex neurons during dyskinesia.
Functional network disruption in cognitively unimpaired autosomal dominant Alzheimer’s disease: a magnetoencephalography study
Authors: van Nifterick Anne M , de Haan Willem , Stam Cornelis J , Hillebrand Arjan , Scheltens Philip , van Kesteren Ronald E , Gouw Alida A
Published: November 2024

Understanding the nature and onset of neurophysiological changes, and the selective vulnerability of central hub regions in the functional network, may aid in managing the growing impact of Alzheimer’s disease on society. However, the precise neurophysiological alterations occurring in the pre-clinical stage of human Alzheimer’s disease remain controversial. This study aims to provide increased insights on quantitative neurophysiological alterations during a true early stage of Alzheimer’s disease. Using high spatial resolution source-reconstructed magnetoencephalography, we investigated regional and whole-brain neurophysiological changes in a unique cohort of 11 cognitively unimpaired individuals with pathogenic mutations in the presenilin-1 or amyloid precursor protein gene and a 1:3 matched control group (n = 33) with a median age of 49 years. We examined several quantitative magnetoencephalography measures that have been shown robust in detecting differences in sporadic Alzheimer’s disease patients and are sensitive to excitation-inhibition imbalance. This includes spectral power and functional connectivity in different frequency bands. We also investigated hub vulnerability using the hub disruption index. To understand how magnetoencephalography measures change as the disease progresses through its pre-clinical stage, correlations between magnetoencephalography outcomes and various clinical variables like age were analysed. A comparison of spectral power between mutation carriers and controls revealed oscillatory slowing, characterized by widespread higher theta (4–8 Hz) power, a lower posterior peak frequency and lower occipital alpha 2 (10–13 Hz) power. Functional connectivity analyses presented a lower whole-brain (amplitude-based) functional connectivity in the alpha (8–13 Hz) and beta (13–30 Hz) bands, predominantly located in parieto-temporal hub regions. Furthermore, we found a significant hub disruption index for (phase-based) functional connectivity in the theta band, attributed to both higher functional connectivity in ‘non-hub’ regions alongside a hub disruption. Neurophysiological changes did not correlate with indicators of pre-clinical disease progression in mutation carriers after multiple comparisons correction. Our findings provide evidence that oscillatory slowing and functional connectivity differences occur before cognitive impairment in individuals with autosomal dominant mutations leading to early onset Alzheimer’s disease. The nature and direction of these alterations are comparable to those observed in the clinical stages of Alzheimer’s disease, suggest an early excitation-inhibition imbalance, and fit with the activity-dependent functional degeneration hypothesis. These insights may prove useful for early diagnosis and intervention in the future.
Efficacy and safety of ixekizumab in psoriatic patients: a long-term real-world retrospective multicentre study from Southern Italy
Authors: Musumeci Maria Letizia , Trecarichi Andrea Calogero , Megna Matteo , Potestio Luca , Micali Giuseppe
Published: November 2024

This is a long-term retrospective multicentre study on adult patients with moderate to severe psoriasis in order to assess the long-term efficacy and safety of ixekizumab in a real-world setting. Our observation considered all patients who started treatment between 1 July 2017 and 31 December 2019, maintaining the treatment for at least 4 years. The majority of our cohort (52 patients; 74.3%) was between 260 and 312 weeks (6 years) under continuous treatment with ixekizumab. Our data confirm that ixekizumab may be considered a long-term effective and safe therapeutic option of moderate to severe plaque psoriasis.
Coronavirus Disease 2019 Antiviral Medication Use Among Pregnant and Recently Pregnant US Outpatients
Authors: Regan Annette K , Rowe Stacey L , Sullivan Sheena G , Coates Matthew M , Muñoz Flor M , Arah Onyebuchi A
Published: November 2024

Background

Pregnant people are at risk of severe coronavirus disease 2019 (COVID-19) and associated complications. While withholding treatment from pregnant patients is not recommended, little is known about the frequency of antiviral medication use during pregnancy.

Methods

Using Medicaid and commercial insurance databases, we constructed a national claims-based cohort study of pregnant, recently pregnant, and nonpregnant female patients 18–49 years old with an outpatient diagnosis of COVID-19 between 21 December 2021 and 30 September 2022. Outpatient treatment with a recommended antiviral medication was identified within 5 days of diagnosis, using national drug codes in outpatient prescription drug claims. Propensity score–matched prevalence ratios (PRs) were used to compare antiviral treatment by pregnancy status.

Results

A total of 412 755 publicly and privately insured patients with COVID-19 were identified, including 33 855 currently pregnant, 2460 recently pregnant, and 376 440 nonpregnant female patients; 6.8% had a record of antiviral medication use, including 1.3% of pregnant, 5.4% of recently pregnant, and 7.3% of nonpregnant women. Most commonly ritonavir-boosted nirmatrelvir was administered. The prevalence of antiviral medication use was 67% lower among pregnant patients compared with nonpregnant patients (PR, 0.33 [95% confidence interval, .30–.36]), even among patients with ≥1 high-risk medical condition (0.29 [.25–.33]). Antiviral medication use was slightly lower among recently pregnant women with ≥1 high-risk medical condition than among nonpregnant women with similar conditions (PR, 0.57; [95% confidence interval, .44–.72]).

Conclusions

Despite US clinical guidelines, we observed low rates of outpatient treatment for COVID-19 among pregnant patients, indicating possible missed opportunities to treat COVID-19 illness during pregnancy and lactation.