bluuebunny/crossref_metadata_2025 huggingface dataset:
Estimation of the number of tree species in French Guiana by extrapolation of permanent plots richness
Authors: Marcon Eric , Mirabel Ariane , Molino Jean-François , Sabatier Daniel
Published: April 2024

The biodiversity of tropical rainforest is difficult to assess. Yet, its estimation is necessary for conservation purposes, to evaluate our level of knowledge and the risks faced by the forest in relation to global change. Our contribution is to estimate the regional richness of tree species from local but widely spread inventories. We reviewed the methods available, which are nonparametric estimators based on abundance or occurrence data, log-series extrapolation and the universal species–area relationship based on maximum entropy. Appropriate methods depend on the scale considered. Harte’s self-similarity model is suitable at the regional scale, while the log-series extrapolation is not. GuyaDiv is a network of forest plots installed over the whole territory of French Guiana, where trees over 10 cm DBH are identified. We used its information (1315 species censused in 68 one-hectare plots) to estimate the exponent of the species–area relationship, assuming Arrhenius’s power law. We could then extrapolate the number of species from three local, wide inventories (over 2.5 km2). We evaluated the number of tree species around 2200 over the territory.
Algorithms for the ferromagnetic Potts model on expanders
Authors: Carlson Charlie , Davies Ewan , Fraiman Nicolas , Kolla Alexandra , Potukuchi Aditya , Yap Corrine
Published: April 2024

We give algorithms for approximating the partition function of the ferromagnetic
$q$
-color Potts model on graphs of maximum degree
$d$
. Our primary contribution is a fully polynomial-time approximation scheme for
$d$
-regular graphs with an expansion condition at low temperatures (that is, bounded away from the order-disorder threshold). The expansion condition is much weaker than in previous works; for example, the expansion exhibited by the hypercube suffices. The main improvements come from a significantly sharper analysis of standard polymer models; we use extremal graph theory and applications of Karger’s algorithm to count cuts that may be of independent interest. It is #BIS-hard to approximate the partition function at low temperatures on bounded-degree graphs, so our algorithm can be seen as evidence that hard instances of #BIS are rare. We also obtain efficient algorithms in the Gibbs uniqueness region for bounded-degree graphs. While our high-temperature proof follows more standard polymer model analysis, our result holds in the largest-known range of parameters
$d$
and
$q$
.
Weight gain in infants with congenital heart disease; breastfeeding alone versus supplemental spoon-feeding of expressed breast milk: an open-label, pilot, randomised control trial.
Authors: Jangid Varsha , Yadav Dinesh Kumar , Bhatt Dheeraj Deo
Published: April 2024

Objectives:

Infants with congenital heart disease and increased pulmonary blood flow frequently suffer from feeding difficulties and growth failure. Providing expressed breast milk by spoon has been hypothesised to decrease energy expenditure in these infants as compared to breastfeeding. This study assessed the effect of supplemental feeding of expressed breast milk on weight gain in infants with unoperated congenital heart disease.

Method:

This was a prospective open-label randomised control trial. In total, 50 infants with post tricuspid left to right shunt were enrolled in the study. In the intervention group, apart from breastfeeding, a minimum predetermined volume of expressed breast milk was targeted to be given by spoon. 30-50 kcal/kg/day was given by expressed breast milk by spoon-feeding. In the control group, the infants were given at least 8 feeds per 24 hours by direct breastfeeding. Both groups were followed up for 1 month and assessed for weight gain.

Result:

Despite a high rate of protocol breach in both groups (30% overall), infants in the intervention group had better weight gain at one-month follow-up compared to those in the control group, 780 ± 300 versus 530 ± 250 gm (p = 0.01).

Conclusion:

In infants with left to right shunts, supplemental feeding of expressed breast milk by spoon along with breastfeeding resulted in significantly higher average weight gain at 30 days compared to the control group who received breastfeeding alone. Future studies with larger sample sizes and longer follow-ups need to be done to confirm the findings of this study.
Who Participates in Focus Groups? Diagnosing Self-Selection
Authors: Boas Taylor C.
Published: April 2024

Focus groups have become increasingly popular in political science alongside the growth in field experimental and other causal inference-oriented work in comparative politics. Yet, scholars rarely provide details about recruitment processes and descriptive statistics on focus-group participants. This situation is problematic given the likelihood of self-selection and the fact that scholars often use focus groups to pretest or refine experimental treatments or survey questionnaires. By leveraging a series of focus groups that were recruited from a pool of large-N survey respondents, this article demonstrates a method for assessing which variables drive the decision to participate. I recommend that scholars diagnose self-selection into focus groups whenever possible; that they compare participants to relevant baselines when working with samples of convenience; and that they always provide descriptive statistics and details on how focus-group members were recruited.
Exploring the influence of context on social norms around Australian parents’ food provision using story completion
Authors: Scott Amelia G , Johnson Brittany J , Hunter Sarah C
Published: April 2024

Objective:

To explore the differences in social norms around parents’ food provision in different provision contexts and by demographics.

Design:

Qualitative study using story completion methodology via an online survey in September 2021. Adults 18+ with or without children were randomised to one of three story stems focusing on food provision in different contexts; food provision at home (non-visitor), with visitors present and with the involvement of sport. Stories were coded and themed using thematic analysis. A content analysis was performed to determine count and frequency of codes in stories by participant demographics and story assumptions.

Setting:

Australia.

Participants:

Adults (n 196).

Results:

Nine themes were identified from the data resulting in four social norms around providing healthy foods and justifying non-adherence to healthy eating guidelines, evolution of family life and mealtime values, the presence of others influencing how we engage with food provision and unhealthy foods used as incentives/rewards in sport. Following content analysis, no differences of themes or norms by participant demographics or story assumptions were found.

Conclusions:

We identified pervasive social norms around family food provision and further identified how contextual factors resulted in variations or distinct norms. This highlights the impact context may have on the social norms parents face when providing food to their children and the opportunities and risks of leveraging these social norms to influence food choice in these contexts. Public health interventions and practitioners should understand the influence of context and social environments when promoting behaviour change and providing individualised advice. Future research could explore parents’ experiences of these norms and to what extent they impact food choice.
A compact UWB MIMO antenna augmented with isolation improvement structures in situ with ground stubs and slots
Authors: Banerjee Jeet , Gorai Abhik , Ghatak Rowdra
Published: April 2024

An orthogonally oriented microstrip-fed bi-element ultra-wideband (UWB) diversity antenna possessing a super-wide bandwidth, high isolation, and band rejection attributes is proposed. The intended diversity antenna uses a 2nd-order Cayley fractal tree-shaped neutralization line among a pair of radiating square monopoles along with additional components like extended ground stubs, hybrid Koch fractal parasitic elements, and an L-shaped defected ground structure to attain high isolation of <−20 dB over 3.1–18 GHz. To nullify the intervention from the existent wireless local area network band, a hybrid Koch–Minkowski slot is carved out from the radiators. A minimal inter-element spacing of 8 mm is attained with the suggested layout measuring 28 mm (L) × 42 mm (W) in extent. The numerical as well as experimental investigations of vital diversity attributes like the envelope correlation coefficient, mean effective gain, total active reflection coefficient, and multiplexing efficiency depict high diversity actualization. The consistency amidst the simulation as well as the empirical results recommends the worthiness of the intended antenna for handy UWB and UWB multiple-input multiple-output systems.
A Deep Learning Approach to Extract Balanced Motions From Sea Surface Height Snapshot
Authors: Gao Zhanwen , Chapron Bertrand , Ma Chunyong , Fablet Ronan , Febvre Quentin , Zhao Wenxia , Chen Ge
Published: April 2024

Extracting balanced geostrophic motions (BM) from sea surface height (SSH) observations obtained by wide‐swath altimetry holds great significance in enhancing our understanding of oceanic dynamic processes at submesoscale wavelength. However, SSH observations derived from wide‐swath altimetry are characterized by high spatial resolution while relatively low temporal resolution, thereby posing challenges to extract the BM from a single SSH snapshot. To address this issue, this paper proposes a deep learning model called the BM‐UBM Network, which takes an instantaneous SSH snapshot as input and outputs the projection corresponding to the BM. Training experiments are conducted both in the Gulf Stream and South China Sea, and three metrics are considered to diagnose model's outputs. The favorable results highlight the potential capability of the BM‐UBM Network to process SSH measurements obtained by wide‐swath altimetry.
Why Does the October Effect Not Occur at Night?
Authors: Wendt Vivien , Schneider Helen , Banyś Daniela , Hansen Marc , Clilverd Mark A. , Raita Tero
Published: April 2024

The October effect is known as a rapid and strong decrease in the signal amplitude of radio waves with very low frequency (VLF), reflected at the lowest edge of the ionosphere. This strong decrease can be observed only during the daytime. Although the October effect is long known, it is hardly investigated and its mechanism is still unknown. To get closer to a mechanism, we answer why the October effect does not occur during nighttime. Therefore, average characteristics of the October effect are obtained from different VLF transmitter‐receiver combinations. The occurrence of the October effect is then compared with characteristics of the neutral atmosphere temperature at VLF reflection heights as it seems to act as a proxy for the unknown mechanism. The temperature shows an asymmetric seasonal behavior at daytime VLF reflection heights poleward of 50°N but not during the nighttime, resulting in the October effect.
Gas Seepage and Pockmark Formation From Subsurface Reservoirs: Insights From Table‐Top Experiments
Authors: Vaknin I. , Aharonov E. , Holtzman R. , Katz O.
Published: April 2024

Pockmarks are morphological depressions commonly observed in ocean and lake floors. Pockmarks form by fluid (typically gas) seepage thorough a sealing sedimentary layer, deforming and breaching the layer. The seepage‐induced sediment deformation mechanisms, and their links to the resulting pockmarks morphology, are not well understood. To bridge this gap, we conduct laboratory experiments in which gas seeps through a granular (sand) reservoir, overlaid by a (clay) seal, both submerged under water. We find that gas rises through the reservoir and accumulates at the seal base. Once sufficient gas over‐pressure is achieved, gas deforms the seal, and finally escapes via either: (a) doming of the seal followed by dome breaching via fracturing; (b) brittle faulting, delineating a plug, which is lifted by the gas seeping through the bounding faults; or (c) plastic deformation by bubbles ascending through the seal. The preferred mechanism is found to depend on the seal thickness and stiffness: in stiff seals, a transition from doming and fracturing to brittle faulting occurs as the thickness increases, whereas bubble rise is preferred in the most compliant, thickest seals. Seepage can also occur by mixed modes, such as bubbles rising in faults. Repeated seepage events suspend the sediment at the surface and create pockmarks. We present a quantitative analysis that explains the tendency for the various modes of deformation observed experimentally. Finally, we connect simple theoretical arguments with field observations, highlighting similarities and differences that bound the applicability of laboratory experiments to natural pockmarks.
PyIRI: Whole‐Globe Approach to the International Reference Ionosphere Modeling Implemented in Python
Authors: Forsythe Victoriya V. , Bilitza Dieter , Burrell Angeline G. , Dymond Kenneth F. , Fritz Bruce A. , McDonald Sarah E.
Published: April 2024

The International Reference Ionosphere (IRI) model is widely used in the ionospheric community and considered the gold standard for empirical ionospheric models. The development of this model was initiated in the late 1960s using the FORTRAN language; for its programming approach, the model outputs were calculated separately for each given geographic location and time stamp. The Consultative Committee on International Radio (CCIR) and International Union of Radio Science (URSI) coefficients provide the skeleton of the IRI model, as they define the global distribution of the maximum useable ionospheric frequency foF2 and the propagation factor M(3,000)F2. At the U.S. Naval Research Laboratory, a novel Python tool was developed that enables global runs of the IRI model with significantly lower computational overhead. This was made possible through the Python rebuild of the core IRI component (which calculates ionospheric critical frequency using the CCIR or URSI coefficients), taking advantage of NumPy matrix multiplication instead of using cyclic addition. This paper explains in detail this new approach and introduces all components of the PyIRI package.
Numerical Modeling of Potential Large Wood Entrainment in Rivers: Application of Hybrid Modeling in the Inter‐Dam Reach of the Dyje River, Czechia
Authors: Hlavňa M. , Máčka Z. , Záthurecký J.
Published: April 2024

Mobilization of large wood in river channels during floods represents a hazardous factor, augmenting flood risk and endangering infrastructures such as bridges, weirs, and reservoir dams. A hybrid modeling approach combining numerical models with field‐based surveys has been recently used to elucidate the processes of LW entrainment and deposition in rivers. We used two‐dimensional hydraulic modeling performed in HEC‐RAS to simulate LW entrainment in two valley bottom segments of the Dyje River, Czechia, where LW deposition is a significant hazard to the dam of the downstream Znojmo reservoir. We surveyed all LW pieces in the inundation area of the 2002 extreme (>Q100) flood and simulated their entrainment for eight flood scenarios (1–100‐year recurrence interval). We used the equations of Braudrick and Grant (2000, https://doi.org/10.1029/1999WR900290) to calculate the LW entrainment threshold; we introduced coefficient k accounting for the incomplete submersion of LW pieces resting on an inclined surface into the original equations. Four entrainment categories — stable, wetted stable, wetted buoyant, and wetted entrained — were defined, and the proportion of LW pieces in each category was calculated for the flood scenarios. We found marked differences in entrainment categories for respective flood scenarios between the two valley segments. These were attributed to the differences in pieces' dimensions, their spatial distribution within the inundation area, and valley‐bottom topography, which affects the hydraulic conditions for a given discharge. The presented approach enables the calculation of the LW quantity potentially mobilized by the flood of a certain magnitude indicating the degree of potential risk for the infrastructures located downstream.
Equilibrium Fractionation of Stable Strontium Isotopes During Adsorption to Mn Oxides
Authors: Liu Ben , Zhu Guanhong , Ma Jinlong , Zhang Le , Wei Gangjian
Published: April 2024

Understanding the stable strontium isotope fractionation between seawater and ferromanganese crusts/nodules is crucial for reconstructing seawater Sr isotopic history. This study explores stable Sr isotope fractionation during adsorption to manganese oxides, as preliminary experiments indicated their higher Sr adsorption capacity compared to iron oxides. We observed that equilibrium in concentration and isotopic composition can be achieved within a day. The lighter isotope (86Sr) is preferentially adsorbed, with the fractionation extent showing no significant change with respect to reaction time, pH, or Sr concentration under low ionic strength conditions (−0.14‰). Equilibrium fractionation processes, rather than Rayleigh fractionation, more accurately represent the isotopic composition trends of dissolved and adsorbed Sr. Experiments in synthetic seawater demonstrated greater Sr isotope fractionation (−0.20‰) compared to low ionic‐strength solutions. This fractionation during adsorption by manganese oxides in synthetic seawater is consistent with the isotopic discrepancy between seawater and ferromanganese nodules, suggesting that Mn oxide adsorption is the primary mechanism for Sr accumulation in ferromanganese deposits. These results imply that ferromanganese deposit Sr isotopic compositions could be proxies for reconstructing seawater Sr isotopic history, which is influenced by carbonate burial and continental weathering, reflecting the global carbon cycle changes.
Regulation of cargo selection in exosome biogenesis and its biomedical applications in cancer
Authors: Lee Yu Jin , Shin Kyeong Jin , Chae Young Chan
Published: April 2024

Extracellular vesicles (EVs), including exosomes, are increasingly recognized as potent mediators of intercellular communication due to their capacity to transport a diverse array of bioactive molecules. They assume vital roles in a wide range of physiological and pathological processes and hold significant promise as emerging disease biomarkers, therapeutic agents, and carriers for drug delivery. Exosomes encompass specific groups of membrane proteins, lipids, nucleic acids, cytosolic proteins, and other signaling molecules within their interior. These cargo molecules dictate targeting specificity and functional roles upon reaching recipient cells. Despite our growing understanding of the significance of exosomes in diverse biological processes, the molecular mechanisms governing the selective sorting and packaging of cargo within exosomes have not been fully elucidated. In this review, we summarize current insights into the molecular mechanisms that regulate the sorting of various molecules into exosomes, the resulting biological functions, and potential clinical applications, with a particular emphasis on their relevance in cancer and other diseases. A comprehensive understanding of the loading processes and mechanisms involved in exosome cargo sorting is essential for uncovering the physiological and pathological roles of exosomes, identifying therapeutic targets, and advancing the clinical development of exosome-based therapeutics.
Prostate cancer detection and complications of MRI-targeted prostate biopsy using cognitive registration, software-assisted image fusion or in-bore guidance: a systematic review and meta-analysis of comparative studies
Authors: Falagario Ugo Giovanni , Pellegrino Francesco , Fanelli Antonio , Guzzi Francesco , Bartoletti Riccardo , Cash Hannes , Pavlovich Christian , Emberton Mark , Carrieri Giuseppe , Giannarini Gianluca
Published: April 2024

Background

Three primary strategies for MRI-targeted biopsies (TB) are available: Cognitive TB (COG-TB), MRI-US Fusion TB (FUS-TB), and In Bore TB (IB-TB). Despite nearly a decade of practice, a consensus on the preferred approach is lacking, with previous studies showing comparable PCa detection rates among the three methods.

Methods

We conducted a search of PubMed, EMBASE, PubMed, Web of Science, and Scopus databases from 2014 to 2023, to identify studies comparing at least two of the three methods and reporting clinically significant PCa (csPCa) detection rates. The primary and secondary outcomes were to compare the csPCa and insignificant prostate cancer (iPCa, ISUP GG 1) detection rates between TB techniques. The tertiary outcome was to compare the complication rate between TB techniques. Detection rates were pooled using random-effect models. Planned sensitivity analyses included subgroup analysis according to the definition of csPCa and positive MRI, previous biopsy status, biopsy route, prostate volume, and lesion characteristics.

Results

A total of twenty studies, involving 4928 patients, were included in the quantitative synthesis. The meta-analysis unveiled comparable csPCa detection rates among COG-TB (0.37), FUS-TB (0.39), and IB-TB (0.47). iPCa detection rate was also similar between TB techniques (COG-TB: 0.12, FUS-TB: 0.17, IB-TB: 0.18). All preplanned sensitivity analyses were conducted and did not show any statistically significant difference in the detection of csPCa between TB methods. Complication rates, however, were infrequently reported, and when available, no statistically significant differences were observed among the techniques.

Conclusions

This unique study, exclusively focusing on comparative research, indicates no significant differences in csPCa and iPCa detection rates between COG-TB, FUS-TB, and IB-TB. Decisions between these techniques may extend beyond diagnostic accuracy, considering factors such as resource availability and operator preferences. Well-designed prospective studies are warranted to refine our understanding of the optimal approach for TB in diverse clinical scenarios.
Signaling pathways of dental implants’ osseointegration: a narrative review on two of the most relevant; NF-κB and Wnt pathways
Authors: Emam Samar Mohamed , Moussa Nermine
Published: April 2024

Introduction

Cell signaling pathways are the biological reactions that control cell functions and fate. They also directly affect the body reactions to implanted biomaterials. It is well-known that dental implants success depends on a successful integration with the alveolar bone: “osseointegration” which events comprise early and later responses to the implanted biomaterials. The early events are mainly immune-inflammatory responses to the implant considered by its microenvironment as a foreign body. Later reactions are osteogenic aiming to regulate bone formation and remodeling. All these events are controlled by the cell signaling pathways in an incredible harmonious coordination.

Aim

The number of pathways having a role in osseointegration is so big to be reviewed in a single article. So the aim of this review was to study only two of the most relevant ones: the inflammatory Nuclear Factor Kappa B (NF-κB) pathway regulating the early osseointegration events and the osteogenic Wnt pathway regulating later events.

Methods

We conducted a literature review using key databases to provide an overview about the NF-κB and Wnt cell signaling pathways and their mutual relationship with dental implants. A simplified narrative approach was conducted to explain these cell signaling pathways, their mode of activation and how they are related to the cellular events of osseointegration.

Results and conclusion

NF-κB and Wnt cell signaling pathways are important cross-talking pathways that are affected by the implant’s material and surface characteristics. The presence of the implant itself in the bone alters the intracellular events of both pathways in the adjacent implant’s cellular microenvironment. Both pathways have a great role in the success or failure of osseointegration. Such knowledge can offer a new hope to treat failed implants and enhance osseointegration in difficult cases. This is consistent with advances in Omics technologies that can change the paradigm of dental implant therapy.
Malnutrition, sarcopenia and cachexia: exploring prevalence, overlap, and perceptions in older adults with cancer
Authors: Bullock Alex F. , Patterson Michael J. , Paton Lewis W. , Currow David C. , Johnson Miriam J.
Published: April 2024

Background

Older adults with cancer are a growing population requiring tailored care to achieve optimum treatment outcomes. Their care is complicated by under-recognised and under-treated wasting disorders: malnutrition, sarcopenia, and cachexia. We aimed to investigate the prevalence, overlap, and patients’ views and experiences of malnutrition, sarcopenia, and cachexia, in older adults with cancer.

Methods

Mixed-methods study with cross-sectional study and qualitative interviews. Interviews were thematically analysed through a phenomenological lens, with feedback loop analysis investigating relationships between themes and findings synthesised using modified critical interpretative synthesis.

Findings

n = 30 were screened for malnutrition, sarcopenia, and cachexia, n = 8 completed semi-structured interviews. Eighteen (60.0%) were malnourished, 16 (53.3%) sarcopenic, and 17 (56.7%) cachexic. One or more condition was seen in 80%, and all three in 30%. In univariate analysis, Rockwood clinical frailty score (OR 2.94 [95% CI: 1.26–6.89, p = 0.013]) was associated with sarcopenia, reported percentage meal consumption (OR 2.28 [95% CI: 1.24–4.19, p = 0.008]), and visible wasting (OR 8.43 [95% CI: 1.9–37.3] p = 0.005) with malnutrition, and percentage monthly weight loss (OR 8.71 [95% CI: 1.87–40.60] p = 0.006) with cachexia. Screening tools identified established conditions rather than ‘risk’. Nutritional and functional problems were often overlooked, overshadowed, and misunderstood by both patients and (in patients’ perceptions) by clinicians; misattributed to ageing, cancer, or comorbidities. Patients viewed these conditions as both personal impossibilities, yet accepted inevitabilities.

Conclusion

Perceptions, identification, and management of these conditions needs to improve, and their importance recognised by clinicians and patients so those truly ‘at risk’ are identified whilst conditions are more remediable to interventions.
Quality of vision clinical outcomes for a new fully-refractive extended depth of focus Intraocular Lens
Authors: Corbett Dean , Black Daniel , Roberts Timothy V. , Cronin Brendan , Gunn David , Bala Chandra , Versace Patrick , Tsai Linda , Papadatou Eleni , Alarcon Aixa , Vilupuru Srividhya
Published: April 2024

Background/objective

To evaluate the visual performance of a purely refractive extended depth of focus (EDF) intraocular lens (IOL).

Subjects/methods

A prospective, multi-center, randomized, subject/evaluator-masked study. Subjects were bilaterally implanted with the EDF test (Model ZEN00V, TECNIS PureSee™ IOL, N = 60) or an enhanced monofocal control (Model ICB00, TECNIS Eyhance™ IOL, N = 57) IOL. Monocular corrected distance (CDVA), intermediate (DCIVA), near acuities (DCNVA) and patient reported visual symptoms were evaluated at the 6-month visit. Monocular mesopic contrast sensitivity (CS) and depth of focus (DOF) testing were assessed at 3 months.

Results

CDVA (Mean ± SD) was −0.06 ± 0.08 for test and −0.05 ± 0.08 logMAR for control groups. DCIVA was 0.13 ± 0.08 for test and 0.18 ± 0.14 logMAR for control groups (p = 0.0127). DCNVA was 0.37 ± 0.10 for test and 0.43 ± 0.16 logMAR for control groups (p = 0.0137). Test lens was statistically superior for intermediate and near. Overall, 91.7% (halos), 95.0% (starbursts) and 95.0% (glare) of test lens patients reported that they did not experience, were not bothered, or were slightly bothered by specific visual symptoms, compared to 98.2%, 100% and 96.5% in the control group. The DOF range over which monocular visual acuity was 0.20 logMAR or better was −1.6 D for the test lens. Mesopic CS was comparable between both groups, falling within 0.11 log units for all measured cycles per degree with and without glare.

Conclusion

The EDF IOL demonstrated extended range of vision and statistically superior intermediate and near performance compared to the monofocal IOL. Distance visual acuity, contrast sensitivity and dysphotopsia profile were similar to the monofocal IOL.
Tolerance to refractive error with a new extended depth of focus intraocular lens
Authors: Black Daniel A. , Bala Chandra , Alarcon Aixa , Vilupuru Srividhya
Published: April 2024

Purpose

To evaluate the tolerance to refractive errors of a new purely refractive extended depth of focus (EDF) intraocular lens (IOL), TECNIS PureSee™ IOL, using preclinical and clinical metrics.

Methods

Preclinical evaluation included computer simulations of visual acuity (sVA) and dysphotopsia profile of different IOL designs (refractive EDF, diffractive EDF, multifocal, standard, and enhanced monofocals) using an appropriate eye model with and without ±0.50 D defocus and/or +0.75 D of astigmatism. Patients bilaterally implanted with a refractive EDF (Model ZEN00V, TECNIS PureSee™ IOL) or an enhanced monofocal (Model ICB00, TECNIS Eyhance™ IOL) IOL from a prospective, randomized study were included. At the 6-month postoperative visit, uncorrected and corrected distance vision (UDVA and CDVA), visual symptoms, satisfaction and dependency on glasses were evaluated in a subgroup of patients with absolute residual refractive error of >0.25 D in one or both eyes.

Results

In the presence of defocus and astigmatism, sVA was comparable for all except the multifocal IOL design. The refractive EDF was more tolerant to myopic outcomes and maintained a monofocal-like dysphotopsia profile with defocus. Binocular logMAR UDVA was −0.03 ± 0.08 for ZEN00V and −0.02 ± 0.11 for ICB00. 100% ZEN00V and 97% ICB00 patients did not need glasses and were satisfied with their distance vision. Monocular CDVA, contrast sensitivity and visual symptoms were also similar between both groups.

Conclusions

The clinical outcomes of the refractive EDF IOL demonstrated high quality distance vision and dysphotopsia comparable to a monofocal IOL, even in the presence of refractive error, thus matching the design expectations of the EDF IOL.
Accurate machine learning force fields via experimental and simulation data fusion
Authors: Röcken Sebastien , Zavadlav Julija
Published: April 2024

Machine Learning (ML)-based force fields are attracting ever-increasing interest due to their capacity to span spatiotemporal scales of classical interatomic potentials at quantum-level accuracy. They can be trained based on high-fidelity simulations or experiments, the former being the common case. However, both approaches are impaired by scarce and erroneous data resulting in models that either do not agree with well-known experimental observations or are under-constrained and only reproduce some properties. Here we leverage both Density Functional Theory (DFT) calculations and experimentally measured mechanical properties and lattice parameters to train an ML potential of titanium. We demonstrate that the fused data learning strategy can concurrently satisfy all target objectives, thus resulting in a molecular model of higher accuracy compared to the models trained with a single data source. The inaccuracies of DFT functionals at target experimental properties were corrected, while the investigated off-target properties were affected only mildly and mostly positively. Our approach is applicable to any material and can serve as a general strategy to obtain highly accurate ML potentials.
MultiSenseBadminton: Wearable Sensor–Based Biomechanical Dataset for Evaluation of Badminton Performance
Authors: Seong Minwoo , Kim Gwangbin , Yeo Dohyeon , Kang Yumin , Yang Heesan , DelPreto Joseph , Matusik Wojciech , Rus Daniela , Kim SeungJun
Published: April 2024

The sports industry is witnessing an increasing trend of utilizing multiple synchronized sensors for player data collection, enabling personalized training systems with multi-perspective real-time feedback. Badminton could benefit from these various sensors, but there is a scarcity of comprehensive badminton action datasets for analysis and training feedback. Addressing this gap, this paper introduces a multi-sensor badminton dataset for forehand clear and backhand drive strokes, based on interviews with coaches for optimal usability. The dataset covers various skill levels, including beginners, intermediates, and experts, providing resources for understanding biomechanics across skill levels. It encompasses 7,763 badminton swing data from 25 players, featuring sensor data on eye tracking, body tracking, muscle signals, and foot pressure. The dataset also includes video recordings, detailed annotations on stroke type, skill level, sound, ball landing, and hitting location, as well as survey and interview data. We validated our dataset by applying a proof-of-concept machine learning model to all annotation data, demonstrating its comprehensive applicability in advanced badminton training and research.
Morphometric dataset of Varanus salvator for non-invasive sex identification using machine learning
Authors: Alymann Ariff Azlan , Alymann Imann Azlan , Ong Song-Quan , Rusli Mohd Uzair , Ahmad Abu Hassan , Salim Hasber
Published: April 2024

Reliable sex identification in Varanus salvator traditionally relied on invasive methods like genetic analysis or dissection, as less invasive techniques such as hemipenes inversion are unreliable. Given the ecological importance of this species and skewed sex ratios in disturbed habitats, a dataset that allows ecologists or zoologists to study the sex determination of the lizard is crucial. We present a new dataset containing morphometric measurements of V. salvator individuals from the skin trade, with sex confirmed by dissection post- measurement. The dataset consists of a mixture of primary and secondary data such as weight, skull size, tail length, condition etc. and can be used in modelling studies for ecological and conservation research to monitor the sex ratio of this species. Validity was demonstrated by training and testing six machine learning models. This dataset has the potential to streamline sex determination, offering a non-invasive alternative to complement existing methods in V. salvator research, mitigating the need for invasive procedures.
Impact of the COVID-19 pandemic on mortality and loss to follow-up among patients with dementia receiving anti-dementia medications
Authors: Kwon Hyuk Sung , Sung Wonjae , Park Keun U. , Kim Seung Hyun , Koh Seong-Ho , Lim Jae-Sung , Choi Hojin
Published: April 2024

The coronavirus disease 2019 (COVID-19) pandemic has profoundly impacted vulnerable groups, such as patients with dementia. We examined changes in mortality and loss to follow-up in patients with dementia using data from the Korean National Health Insurance Service research database. Patients with dementia who visited a medical institution with a recorded dementia-related diagnostic code, including Alzheimer’s disease, and who received anti-dementia medication between February 2018 and January 2020 were included in this study. We divided patients with dementia receiving anti-dementia medications into two cohorts: those newly diagnosed with dementia between February 2018 and January 2019 (n = 62,631) and those diagnosed between February 2019 and January 2020 (n = 54,494). Then, we conducted a one-year follow-up of their records, tracking the cohort diagnosed between February 2018 and January 2019 from February 2019 to January 2020, as well as the cohort diagnosed between February 2019 and January 2020 from February 2020 to January 2021. There was a significant increase in follow-up loss among patients newly diagnosed with dementia during the COVID-19 outbreak, from 42.04% in 2019 to 45.89% in 2020. Female sex, younger age, fewer comorbidities, diagnosis of dementia at the Department of Neurology or Psychiatry, and higher income were associated with decreased follow-up loss and mortality. This study highlights the importance of paying extra attention to patients with dementia receiving anti-dementia medications, particularly during pandemics, given their increased risk of loss to follow-up.
Novel evaluation method based on critical arch height as instability criterion for sustaining arch locked-segment-type slopes
Authors: Wang Lijin , Jia Hang , Jiang Tong , Zhang Junran , Jia Yanchang , Li Longfei , Wan Li
Published: April 2024

In sustaining arch locked-segment-type slopes, natural soil arches play a key anti-sliding role in the slope's evolution. In this study, a self-developed model test device was used to simulate the whole process of deformation evolution of sustaining arch locked-segment-type slopes, and the formation of natural sustaining arch and its locking control effect on slope stability were studied. The test results show that the continuous formation and progressive destruction of the sustaining arch were observed. The sustaining arch formed in the second time has the best locking effect, and the anti-sliding force reaches its stress peak point. However, the slope is not in a critically unstable state, instead, the stress is continuously adjusted to form a larger range of soil arch to resist the slope thrust. Consequently, the slope destabilizes until the ultimate shear strength of arch foots is exceeded, at which point the critical arch height of the arch is reached. The critical arch height mechanical model for slope stability analysis was developed based on the soil arching effect and limit equilibrium theory. The applicability of the model was demonstrated by the physical test and Xintan slope data, which can provide some guidance for early warning of landslides.
Dryland hydroclimatic response to large tropical volcanic eruptions during the last millennium
Authors: Zhou Shangrong , Liu Fei , Dai Aiguo , Zhao Tianbao
Published: April 2024

Drylands are highly vulnerable to climate change due to their fragile ecosystems and limited ability to adapt. In contrast to the global drying after tropical volcanic eruptions shown previously, we demonstrate that large tropical volcanic eruptions can induce significant two-year hydroclimatic wetting over drylands by employing the last millennium simulations. During this wetting period, which extends from the first to the third boreal winter after the eruption, several hydroclimatic indicators, such as self-calibrating Palmer Drought Severity Index based on the Penman-Monteith equation for potential evapotranspiration (scPDSIpm), standard precipitation evapotranspiration index (SPEI), aridity index (AI), top-10cm soil moisture (SM10cm), and leaf area index (LAI), show significant positive anomalies over most drylands. The primary contribution to the wetting response is the potential evapotranspiration (PET) reduction resulting from dryland surface cooling and reduced solar radiation, as well as a weak contribution from increased precipitation. The latter is due to the wind convergence into drylands caused by slower tropical cooling compared to drylands. The wetting response of drylands to volcanic eruptions also demonstrates some benefits over the global hydrological slowdown resulting from stratospheric aerosol injection, which replicates the cooling effects of volcanic eruptions to address global warming.
Elevated glucocorticoid alters the developmental dynamics of hypothalamic neurogenesis in zebrafish
Authors: Eachus Helen , Choi Min-Kyeung , Tochwin Anna , Kaspareit Johanna , Ho May , Ryu Soojin
Published: April 2024

Exposure to excess glucocorticoid (GC) during early development is implicated in adult dysfunctions. Reduced adult hippocampal neurogenesis is a well-known consequence of exposure to early life stress or elevated GC, however the effects on neurogenesis during development and effects on other brain regions are not well understood. Using an optogenetic zebrafish model, here we analyse the effects of GC exposure on neurogenesis during development in the whole brain. We identify that the hypothalamus is a highly GC-sensitive region where elevated GC causes precocious development. This is followed by failed maturation and early decline accompanied by impaired feeding, growth, and survival. In GC-exposed animals, the developmental trajectory of hypothalamic progenitor cells is strikingly altered, potentially mediated by direct regulation of transcription factors such as rx3 by GC. Our data provide cellular and molecular level insight into GC-induced alteration of the hypothalamic developmental trajectory, a process crucial for health across the life-course.
Unsupervised deep representation learning enables phenotype discovery for genetic association studies of brain imaging
Authors: Patel Khush , Xie Ziqian , Yuan Hao , Islam Sheikh Muhammad Saiful , Xie Yaochen , He Wei , Zhang Wanheng , Gottlieb Assaf , Chen Han , Giancardo Luca , Knaack Alexander , Fletcher Evan , Fornage Myriam , Ji Shuiwang , Zhi Degui
Published: April 2024

Understanding the genetic architecture of brain structure is challenging, partly due to difficulties in designing robust, non-biased descriptors of brain morphology. Until recently, brain measures for genome-wide association studies (GWAS) consisted of traditionally expert-defined or software-derived image-derived phenotypes (IDPs) that are often based on theoretical preconceptions or computed from limited amounts of data. Here, we present an approach to derive brain imaging phenotypes using unsupervised deep representation learning. We train a 3-D convolutional autoencoder model with reconstruction loss on 6130 UK Biobank (UKBB) participants’ T1 or T2-FLAIR (T2) brain MRIs to create a 128-dimensional representation known as Unsupervised Deep learning derived Imaging Phenotypes (UDIPs). GWAS of these UDIPs in held-out UKBB subjects (n = 22,880 discovery and n = 12,359/11,265 replication cohorts for T1/T2) identified 9457 significant SNPs organized into 97 independent genetic loci of which 60 loci were replicated. Twenty-six loci were not reported in earlier T1 and T2 IDP-based UK Biobank GWAS. We developed a perturbation-based decoder interpretation approach to show that these loci are associated with UDIPs mapped to multiple relevant brain regions. Our results established unsupervised deep learning can derive robust, unbiased, heritable, and interpretable brain imaging phenotypes.
Catalytic-dependent and -independent roles of TET3 in the regulation of specific genetic programs during neuroectoderm specification
Authors: Ketchum Harmony C. , Suzuki Masako , Dawlaty Meelad M.
Published: April 2024

The ten-eleven-translocation family of proteins (TET1/2/3) are epigenetic regulators of gene expression. They regulate genes by promoting DNA demethylation (i.e., catalytic activity) and by partnering with regulatory proteins (i.e., non-catalytic functions). Unlike Tet1 and Tet2, Tet3 is not expressed in mouse embryonic stem cells (ESCs) but is induced upon ESC differentiation. However, the significance of its dual roles in lineage specification is less defined. By generating TET3 catalytic-mutant (Tet3m/m) and knockout (Tet3–/–) mouse ESCs and differentiating them to neuroectoderm (NE), we identify distinct catalytic-dependent and independent roles of TET3 in NE specification. We find that the catalytic activity of TET3 is important for activation of neural genes while its non-catalytic functions are involved in suppressing mesodermal programs. Interestingly, the vast majority of differentially methylated regions (DMRs) in Tet3m/m and Tet3–/– NE cells are hypomethylated. The hypo-DMRs are associated to aberrantly upregulated genes while the hyper-DMRs are linked to downregulated neural genes. We find the maintenance methyltransferase Dnmt1 as a direct target of TET3, which is downregulated in TET3-deficient NE cells and may contribute to the increased DNA hypomethylation. Our findings establish that the catalytic-dependent and -independent roles of TET3 have distinct contributions to NE specification with potential implications in development.
Mechano-sensitivity of β2-adrenoceptors enhances constitutive activation of cAMP generation that is inhibited by inverse agonists
Authors: Cullum Sean A. , Platt Simon , Dale Natasha , Isaac Oliver C. , Wragg Edward S. , Soave Mark , Veprintsev Dmitry B. , Woolard Jeanette , Kilpatrick Laura E. , Hill Stephen J.
Published: April 2024

The concept of agonist-independent signalling that can be attenuated by inverse agonists is a fundamental element of the cubic ternary complex model of G protein-coupled receptor (GPCR) activation. This model shows how a GPCR can exist in two conformational states in the absence of ligands; an inactive R state and an active R* state that differ in their affinities for agonists, inverse agonists, and G-protein alpha subunits. The proportion of R* receptors that exist in the absence of agonists determines the level of constitutive receptor activity. In this study we demonstrate that mechanical stimulation can induce β2-adrenoceptor agonist-independent Gs-mediated cAMP signalling that is sensitive to inhibition by inverse agonists such as ICI-118551 and propranolol. The size of the mechano-sensitive response is dependent on the cell surface receptor expression level in HEK293G cells, is still observed in a ligand-binding deficient D113A mutant β2-adrenoceptor and can be attenuated by site-directed mutagenesis of the extracellular N-glycosylation sites on the N-terminus and second extracellular loop of the β2-adrenoceptor. Similar mechano-sensitive agonist-independent responses are observed in HEK293G cells overexpressing the A2A-adenosine receptor. These data provide new insights into how agonist-independent constitutive receptor activity can be enhanced by mechanical stimulation and regulated by inverse agonists.
Enhancing property and activity prediction and interpretation using multiple molecular graph representations with MMGX
Authors: Kengkanna Apakorn , Ohue Masahito
Published: April 2024

Graph Neural Networks (GNNs) excel in compound property and activity prediction, but the choice of molecular graph representations significantly influences model learning and interpretation. While atom-level molecular graphs resemble natural topology, they overlook key substructures or functional groups and their interpretation partially aligns with chemical intuition. Recent research suggests alternative representations using reduced molecular graphs to integrate higher-level chemical information and leverages both representations for model. However, there is a lack of studies about applicability and impact of different molecular graphs on model learning and interpretation. Here, we introduce MMGX (Multiple Molecular Graph eXplainable discovery), investigating the effects of multiple molecular graphs, including Atom, Pharmacophore, JunctionTree, and FunctionalGroup, on model learning and interpretation with various perspectives. Our findings indicate that multiple graphs relatively improve model performance, but in varying degrees depending on datasets. Interpretation from multiple graphs in different views provides more comprehensive features and potential substructures consistent with background knowledge. These results help to understand model decisions and offer valuable insights for subsequent tasks. The concept of multiple molecular graph representations and diverse interpretation perspectives has broad applicability across tasks, architectures, and explanation techniques, enhancing model learning and interpretation for relevant applications in drug discovery.