bluuebunny/crossref_metadata_2025 huggingface dataset:
Can sex differences in spatiotemporal distribution and age composition explain the female-biased sex ratio observed in the catch of butterfly kingfish Gasterochisma melampus?
Authors: Itoh Tomoyuki
Published: June 2024

The catch of butterfly kingfish Gasterochisma melampus, a large pelagic species in southern temperate waters, is strongly biased (73%) towards females. Whether this is caused by differences in sex-specific spatiotemporal distributions or mortality of sexes is investigated herein. Analysis of sex ratios using a generalized additive model (GAM) for year, month, latitude, longitude, sea surface temperature, and fork length from Japanese longline catch data for areas where immature and adult fish occur revealed the influence of space and time on sex ratios to be small, and that of fork length to be large. Based on observation of the increments in vertebrae of immature fish (N = 179), the fork length at the time of increment formation was back-calculated from distances between increments on the anterior and posterior cones, generating 2–8 measurements per vertebra and 865 data points in total. Growth equations were calculated for each sex, with females growing faster. The age composition of males and females in the catch was similar, meaning that the mortality rate in males is unlikely to be higher than that of females. The data suggest that biased sex ratios in catches are representative of the natural sex ratio in a population for fish more than 60 cm in fork length.
Neural Network Model for Predicting Shear Wave Velocity Using Well Logging Data
Authors: Gomaa Sayed , Shahat John S. , Aboul-Fotouh Tarek M. , Khaled Samir
Published: June 2024

Efficient well design requires accurate estimation of rock petrophysical parameters that represent a reservoir. For compressional waves, particle motion is in the direction of propagation; alternatively, for shear waves, it is perpendicular to the propagation direction. Understanding the velocity of these waves reveals important details about the reservoir. Shear wave velocity (Vs) can be used for estimating mechanical properties of rock that will be used while determining casing setting depth, rate of penetration, and fracture pressure. Unfortunately, Vs data cannot be obtained directly in the field due to field constraints and high cost. On the other hand, compressional sonic data sets are available. There are many time- and money-consuming techniques that target the estimation of Vs from core analysis. Moreover, there are uncertain models such as the Xu–Payne petrophysical model, which are based on pore structures, rock compositions, and fluid properties. Although many studies provide various methods to estimate Vs from empirical correlations, petrophysical models, and artificial intelligence, these studies are limited to small ranges of used data. In this paper, a new artificial neural network (ANN) model is developed to accurately predict Vs as a function of porosity ($$\boldsymbol{\varnothing }$$

∅

), gamma-ray (GR), bulk density $$({{\varvec{\rho}}}_{{\text{b}}})$$

(

ρ

b

)

, and compressional velocity (Vc) with wide data ranges. The new model is built using data set comprising 2350 data points, where 1645 data sets are used to process the model, and the other 705 data sets are used to validate the new model. Results showed high accuracy with a coefficient of determination of about 0.958. The proposed model can be applied directly in Excel sheet without need to any other software.
Towards a Prescription for Change: Interprofessional Management of Polypharmacy and Deprescribing
Authors: Perron Aimee Elizabeth
Published: June 2024

Purpose of Review

Deprescribing, systematically discontinuing unnecessary or harmful medications, gains importance in healthcare. With rising polypharmacy concerns, optimizing medication management is crucial. This article explores deprescribing within interprofessional teams emphasizing collaborative efforts to address polypharmacy and improve patient outcomes. It examines the necessity and effectiveness of interprofessional collaboration in deprescribing initiatives, with a focus on diverse healthcare professionals optimizing medication regimens.

Recent Findings

Polypharmacy, characterized by the simultaneous use of multiple medications, poses significant challenges, highlighting the importance of deprescribing. Interprofessional collaboration, supported by evidence, has demonstrated efficacy in reducing polypharmacy and improving patient outcomes. Furthermore, diverse providers contribute valuable expertise in identifying patients who may benefit from deprescribing and non-pharmacological interventions.

Successful deprescribing relies on interprofessional collaboration to assess medication appropriateness, mitigate risks, and tailor plans to patient preferences. Screening tools identify inappropriate polypharmacy, while frameworks and action steps guide implementation. Integrating non-pharmacological interventions and prioritizing patient safety enhance care quality for older adults.
Diameter of Compact Riemann Surfaces
Authors: Stepanyants Huck , Beardon Alan , Paton Jeremy , Krioukov Dmitri
Published: June 2024

Diameter is one of the most basic properties of a geometric object, while Riemann surfaces are one of the most basic geometric objects. Surprisingly, the diameter of compact Riemann surfaces is known exactly only for the sphere and the torus. For higher genuses, only very general but loose upper and lower bounds are available. The problem of calculating the diameter exactly has been intractable since there is no simple expression for the distance between a pair of points on a high-genus surface. Here we prove that the diameters of a class of simple Riemann surfaces known as generalized Bolza surfaces of any genus greater than 1 are equal to the radii of their fundamental polygons. This is the first exact result for the diameter of a compact hyperbolic manifold.
Higher orthorexia tendency among female fashion models: an empirical international study
Authors: Bogár Nikolett , Dukay-Szabó Szilvia , Simon Dávid , Túry Ferenc
Published: June 2024

Purpose

Female fashion models are more at risk for developing eating disorders than non-models due to the intense occupational pressure they face. The present study focuses on assessing whether female models are more prone to report orthorexia nervosa signs and symptoms than non-models.

Methods

Female fashion models (n = 179, mean age: 25.9 SD = 4.40 years) and an age adjusted control group (n = 261, mean age: 25.0 SD = 4.97 years) were selected by snowball sampling. Participants filled out an online survey containing anthropometric questions and the 18-item Eating Habits Questionnaire.

Results

According to BMI, fashion models were underweight (mean BMI = 18.1 SD = 1.68) while control participants’ BMI was in the normal range (mean = 22.1 SD = 4.23, p < 0.001). On all three of Eating Habits Questionnaire subscales fashion models showed significantly higher average value (Knowledge subscale: M = 2.42 among models versus M = 2.08 in the control group, p < 0.01, Cohen’s d = 0.52; Problems subscale: M = 1.93 among models versus M = 2.61 in the control group, p < 0.01, Cohen’s d = 0.49; Feelings subscale: M = 3.20 among models versus M = 2.96 in the control group, p < 0.01, Cohen’s d = 0.38). Orthorexic tendencies were reported by 35.1% of the models versus 20.2% of controls.

Conclusion

Fashion models are at risk for the development of eating disorders. Even though not yet included in the DSM-5, the assessment of orthorexia nervosa among fashion models seems to be important. It is suggested to take appropriate measures to prevent the spread of disordered eating habits among models as they can lead to the development of anorexia nervosa or bulimia nervosa.

Level of evidence

Level III, well-designed cohort study.
Advanced Materials for NH3 Capture: Interaction Sites and Transport Pathways
Authors: Jiang Hai-Yan , Wang Zao-Ming , Sun Xue-Qi , Zeng Shao-Juan , Guo Yang-Yang , Bai Lu , Yao Ming-Shui , Zhang Xiang-Ping
Published: June 2024

Ammonia (NH3) is a carbon-free, hydrogen-rich chemical related to global food safety, clean energy, and environmental protection. As an essential technology for meeting the requirements raised by such issues, NH3 capture has been intensively explored by researchers in both fundamental and applied fields. The four typical methods used are (1) solvent absorption by ionic liquids and their derivatives, (2) adsorption by porous solids, (3) ab-adsorption by porous liquids, and (4) membrane separation. Rooted in the development of advanced materials for NH3 capture, we conducted a coherent review of the design of different materials, mainly in the past 5 years, their interactions with NH3 molecules and construction of transport pathways, as well as the structure–property relationship, with specific examples discussed. Finally, the challenges in current research and future worthwhile directions for NH3 capture materials are proposed.
A bibliometric analysis and comprehensive review of magnetized water effects on concrete properties
Authors: Hatem Wadhah Amer , Rashid Farhan Lafta , Al-Obaidi Mudhar A. , Dulaimi Anmar , Mydin Md Azree Othuman
Published: June 2024

This study is a critical review to assess the feasibility of using magnetic water to boost the overall performance of concrete. This is specifically conducted by evaluating the improvements of mechanical properties (split tensile strength, compressive strength, and flexural strength), cement particle water absorption, and cement hydration of concrete as a result of adding magnetic water if compared to concrete made with regular tap water. The benefits and associated challenges of utilising magnetic water in concrete are thoroughly discussed based on the most recent experimental and numerical studies published in the open literature between 2019 and 2023. According to the findings, the tensile strength, compressive strength, flexural strength, and electrical conductivity increase by 6.1%, 24.4%, 3.9%, and 0.5%, respectively, in concretes created with MW compared to regular tap water. Also, the magnetic field intensity of 1.3 Tesla yields the greatest improvement in the slump by 5–13 mm. However, the magnetic water shows the highest sorptivity at a magnetic field intensity of 0.9 Tesla. Also, using magnetic water makes concrete block pavers less absorbent of water and more resistant to assault by sulfuric acid. This review would encourage future research and widespread use of magnetic water in concrete production.
Impact of navigation apps on congestion and spread dynamics on a transportation network
Authors: Bagabaldo Alben Rome , Gan Qianxin , Bayen Alexandre M. , González Marta C.
Published: June 2024

In recent years, the widespread adoption of navigation apps by motorists has raised questions about their impact on local traffic patterns. Users increasingly rely on these apps to find better, real-time routes to minimize travel time. This study uses microscopic traffic simulations to examine the connection between navigation app use and traffic congestion. The research incorporates both static and dynamic routing to model user behavior. Dynamic routing represents motorists who actively adjust their routes based on app guidance during trips, while static routing models users who stick to known fastest paths. Key traffic metrics, including flow, density, speed, travel time, delay time, and queue lengths, are assessed to evaluate the outcomes. Additionally, we explore congestion propagation at various levels of navigation app adoption. To understand congestion dynamics, we apply a susceptible–infected–recovered (SIR) model, commonly used in disease spread studies. Our findings reveal that traffic system performance improves when 30–60% of users follow dynamic routing. The SIR model supports these findings, highlighting the most efficient congestion propagation-to-dissipation ratio when 40% of users adopt dynamic routing, as indicated by the lowest basic reproductive number. This research provides valuable insights into the intricate relationship between navigation apps and traffic congestion, with implications for transportation planning and management.
High Carbohydrate, Fat, and Protein Diets Have a Critical Role in Folliculogenesis and Oocyte Development in Rats
Authors: Gül Semir , Gül Mehmet , Otlu Barış , Erdemli Mehmet Erman , Gözükara Bağ Harika Gözde
Published: June 2024

To date, there is no comparative data on the effects of carbohydrates, fat, and proteins, which are macronutrients, on female reproductive functions. Therefore, in this study, we investigated the effects of diets enriched with carbohydrates, fats, and proteins on folliculogenesis and oocyte development in female rats. 21-day-old rats that were just weaned were divided into 4 groups: control, carbohydrate, fat, and protein. The control group was fed with standard chow and the carbohydrate, fat, and protein groups were fed diets enriched with 75% carbohydrate, 60% fat, and 50% protein for 11 weeks, respectively. It was found that high-fat and high-protein diets caused an increase in the estrous cycle length compared to carbohydrate group (p < 0.05). Graafian follicle number decreased in the protein group compared to the control (p < 0.05). However, the atretic follicle number was higher in the fat group compared to the control group (p < 0.05). In the carbohydrate group, Zp1 was found to be lower than the control and protein groups, Zp2 was found to be lower than the control, and Zp3 was found to be lower than the fat group (p < 0.05). While BMP15 was similar between groups (p > 0.05), GDF9 was lower in all diet groups compared to the control (p < 0.05). Foxo3a was lower in the protein group compared to carbohydrate and control (p < 0.05). GAS2 was found to be higher in the control group than the fat group, and higher in the carbohydrate group than the fat and protein groups (p < 0.05). FSH, LH, Progesterone, and E2 levels were higher in all three diet groups than in the control (p < 0.05). Also, significant differences were observed between the groups regarding adiponectin, resistin, and leptin levels. Taken together, high carbohydrate, fat, and protein intake are associated with impairment of the menstrual cycle, depletion of the developing follicle types, and altered expression of folliculogenesis-specific genes and hormones. Therefore, long-term macronutrient diets may result in shortened reproductive periods and reduced fertilization potential in females in the long run.
Infiltration and permeability of porous ceramics simulated by random networks
Authors: Mityushev Vladimir , Rylko Natalia , Dolata Anna Janina , Dyzia Maciej
Published: June 2024

A network computational model for a 3D ceramic structure is developed. The model is applied to study the impact of geometric and material parameters of structure on the liquid metal flow through random porous ceramic medium in pressure infiltration processes. The characteristic geometric features of the ceramic structure favorable for liquid metal flow during the infiltration process are determined. The method of structural approximation and constructive homogenization are applied, and the discrete stationary Stokes equations on random graphs are considered. This approach gives a robust algorithm to determine the macroscopic permeability K of interpenetrating phases. The dependencies of K on the distribution of connections (windows) between the cells (inclusions) are derived. The numerical simulations demonstrate that the permeability K does not depend on the scaled distribution sizes of windows. This implies that K is proportional to the mean value of the window areas. The considered model takes into account a random complex structure of 3D ceramic. Hence, it complements the previous study on the local transport properties of tubes (windows) connecting the cells.
Pediatric Posterior Fossa Tumors Classification and Explanation-Driven with Explainable Artificial Intelligence Models
Authors: Ashry Eman Ragab , Maghraby Fahima A. , El-Latif Yasser M. Abd , Agag Mohamed
Published: June 2024

The use of deep learning for identifying defects in medical images has rapidly emerged as a significant area of interest across various medical diagnostic applications. The automated recognition of Posterior Fossa Tumors (PFT) in Magnetic Resonance Imaging (MRI) plays a vital role, as it furnishes essential data about irregular tissue, essential for treatment planning. Human examination has traditionally been the standard approach for identifying defects in brain MRI. This technique is unsuitable for a massive quantity of data. Therefore, automated PFT detection techniques are being established to minimize radiologist's time. In this paper, the posterior fossa tumor is detected and classified in brain MRI using Convolutional Neural Network (CNN) algorithms, and the model result and accuracy obtained from each algorithm are explained. A dataset collection made up of 3,00,000 images with an average of 500 patients from the Children's Cancer Hospital Egypt (CCHE) was used. The CNN algorithms investigated to classify the PFT were VGG19, VGG16, and ResNet50. Moreover, explanations for the behavior of networks were investigated using three different techniques: LIME, SHAP, and ICE. Overall, the results showed that the best model was VGG16 compared with other CNN-used models with accuracy rate values of 95.33%, 93.25%, and 87.4%, respectively.
Spectral Solutions of Specific Singular Differential Equations Using A Unified Spectral Galerkin-Collocation Algorithm
Authors: Ahmed H. M. , Abd-Elhameed W. M.
Published: June 2024

This paper presents a novel numerical approach to addressing three types of high-order singular boundary value problems. We introduce and consider three modified Chebyshev polynomials (CPs) of the third kind as proposed basis functions for these problems. We develop new derivative operational matrices for the three modified CPs of the third kind by deriving formulas for their first derivatives. Our approach follows a unified method for numerically handling singular differential equations (DEs). To transform these equations into algebraic systems suitable for numerical treatment, we employ the collocation method in combination with the introduced operational matrices of derivatives of the modified CPs of the third kind. We address the convergence examination for the three expansions in a unified manner. We present numerous numerical examples to demonstrate the accuracy and efficiency of our unified numerical approach.
Local Nanostructure in Multicomponent High-Entropy Materials
Authors: Cantor Brian
Published: June 2024

Multicomponent phase space contains extended regions of random or near-random multicomponent solid-solution single phases, stabilised by a relatively large configurational entropy of mixing that can often (though not always) suppress compound formation between the different atomic species. The present paper shows that there are very extensive variations of local nanostructure, local atomic clusters and associated local lattice strains within multicomponent high-entropy solid-solution single phases such as the fcc Cantor alloys, bcc Senkov alloys and rock-salt-structured Rost mono-oxides, even when there is no short-range ordering, i.e. even when the solid solution is completely random or ideal. There are, for instance, many billions of different local nanostructures and different local atomic clusters in equiatomic five-component fully random solid-solution single-phase materials such as the original fcc Cantor alloy CrMnFeCoNi and the original bcc Senkov alloy VNbMoTaW, extending over distances of many microns, with associated fluctuating hydrostatic and shear lattice strains of several percent. The number and extent of the variations in local nanostructure, atomic clusters and lattice strains increase dramatically to even higher values with increasing number of components in the material. The present paper also shows that there are similar variations in local nanostructure, local atomic clusters and associated local lattice strains surrounding point defects such as vacancies, line defects such as dislocations and planar defects such as grain boundaries and external surfaces, influencing many important material properties such as diffusion, plastic flow, recrystallisation, grain growth and catalysis. The number and extent of the variations in local nanostructure, atomic clusters and lattice strains make it difficult to have too much confidence in structures and properties of multicomponent high-entropy materials calculated using ab initio and other atomistic computer modelling techniques, since these techniques are restricted to relatively small numbers of atoms and are unable to sample effectively the full range of local structures and properties.
Wired for society? From ego-logy to eco-logy
Authors: Kaufmann Laurence , Clément Fabrice
Published: June 2024

Somewhat questioning Elizabeth Spelke's attempt to account for infants’ social knowledge, our commentary argues that social cognition might be divided into several specialized systems. In addition to the core system dedicated to the intersubjective dimension of close relationships, infants could be prewired to process social relationships, such as dominance, characterized by their impersonal, normative dimension.
First language effects on incidental vocabulary learning through bimodal input
Authors:   The TwiLex Group
Published: June 2024

Despite accumulating evidence, accounts for the efficacy of reading-while-listening (RWL) in facilitating vocabulary learning are largely unexamined, hindering a thorough understanding of the reasons underlying the usefulness of such bimodal input. In this article, we report a close replication of Malone (2018), purposefully manipulating the participants’ native language background to shed light on whether the auditory component in RWL promotes spoken-written form mappings. One hundred and eighty-eight English learners from Austria, Belgium, Hong Kong, and Beijing read or read and listened to four stories containing target words for learning. They completed two surprise vocabulary tests and two assessments of working memory capacity. We only replicated a correlation between working memory capacity and the form recognition test reported in the initial study. Thanks to our manipulation, we discovered an important role of L1 background in the effectiveness of RWL for form recognition knowledge. We discuss the implications for RWL research.
Modeling the Propagation of Extremely Low Frequency Electromagnetic Emissions From the Power Lines to the Inner Magnetosphere in a Dipole Field
Authors: Xu Xiang , Zhou Chen , Wang Zhuangkai , Du Xiaohui
Published: June 2024

Different from power line harmonic radiation (PLHR) events at high harmonics (∼kHz) in the ionosphere and inner magnetosphere, the wave dynamics of power line emission (PLE) (the fundamental frequency 50/60 Hz or PLHR at low harmonics) can be significantly affected by various ion species. In order to investigate the evolution of the wave properties of PLE from power lines to satellite altitudes in a dipole field, a numerical model is developed to perform full‐wave simulations, in which the lithosphere and atmosphere are characterized by electrical conductivity and the ionosphere (inner magnetosphere) is treated as collisional (collisionless) cold plasma consisting of electron, H+, He+, O+, and NO+. Our simulation results show that the spatial distribution and wave properties of PLE are determined by the magnetic latitudes of power lines and plasma densities. PLE from power lines at middle and high magnetic latitudes (|MLAT| > 40°) can propagate to high L shells as whistler waves; PLE from power lines at |MLAT| < 30° usually propagate at low L shells below local He+ cyclotron frequency as left‐handedly polarized or right‐handedly He+ band electromagnetic ion cyclotron (EMIC) waves. The amplitude of PLE is usually stronger with smaller electron density in the space plasma medium. With power lines at |MLAT| < 30°, the coupling efficiency between different right‐handedly polarized EMIC wave modes of PLE decreases significantly with electron density. Wave properties of PLE including Poynting vector direction, wave normal angle and wave polarization obtained from our simulation results are consistent with some of the recent observations using Van Allen Probes.
Intensification of Mid‐Latitude Cyclone by Aerosol‐Radiation Interaction Increases Transport of Canadian Wildfire Smoke to Northeastern US
Authors: Wang Zilin , Huang Xin , Xue Lian , Ding Ke , Lou Sijia , Zhu Anbao , Ding Aijun
Published: June 2024

Wildfires have long been regarded as one chief culprit in regional air pollution, and pose great impacts on climate change. Although climate forcing of wildfire smoke has been widely investigated, its influence on synoptic systems remains unclear. Based on measurement and modeling analysis, the impact of wildfire smoke on the development of a mid‐latitude cyclone was revealed for Canadian wildfires in early June of 2023. The radiative forcing induced by smoke at surface and in the atmosphere reached up to −150 and 100 W m−2, posing opposite tendencies of atmospheric stratification over the land and ocean. Such perturbations contributed to the enhancement and stagnation of the cyclone, which favored the transport of smoke from the fire‐intensive region, indicated by nearly 40% increment of PM2.5 mass flux. With escalating wildfire risk in the future, the inclusion of smoke aerosols' impacts on meteorology in weather forecast models is of great importance.
Quantitative phase imaging based on holography: trends and new perspectives
Authors: Huang Zhengzhong , Cao Liangcai
Published: June 2024

In 1948, Dennis Gabor proposed the concept of holography, providing a pioneering solution to a quantitative description of the optical wavefront. After 75 years of development, holographic imaging has become a powerful tool for optical wavefront measurement and quantitative phase imaging. The emergence of this technology has given fresh energy to physics, biology, and materials science. Digital holography (DH) possesses the quantitative advantages of wide-field, non-contact, precise, and dynamic measurement capability for complex-waves. DH has unique capabilities for the propagation of optical fields by measuring light scattering with phase information. It offers quantitative visualization of the refractive index and thickness distribution of weak absorption samples, which plays a vital role in the pathophysiology of various diseases and the characterization of various materials. It provides a possibility to bridge the gap between the imaging and scattering disciplines. The propagation of wavefront is described by the complex amplitude. The complex-value in the complex-domain is reconstructed from the intensity-value measurement by camera in the real-domain. Here, we regard the process of holographic recording and reconstruction as a transformation between complex-domain and real-domain, and discuss the mathematics and physical principles of reconstruction. We review the DH in underlying principles, technical approaches, and the breadth of applications. We conclude with emerging challenges and opportunities based on combining holographic imaging with other methodologies that expand the scope and utility of holographic imaging even further. The multidisciplinary nature brings technology and application experts together in label-free cell biology, analytical chemistry, clinical sciences, wavefront sensing, and semiconductor production.
Fully flexible implantable neural probes for electrophysiology recording and controlled neurochemical modulation
Authors: Malekoshoaraie Mohammad Hassan , Wu Bingchen , Krahe Daniela D. , Ahmed Zabir , Pupa Stephen , Jain Vishal , Cui Xinyan Tracy , Chamanzar Maysamreza
Published: June 2024

Targeted delivery of neurochemicals and biomolecules for neuromodulation of brain activity is a powerful technique that, in addition to electrical recording and stimulation, enables a more thorough investigation of neural circuit dynamics. We have designed a novel, flexible, implantable neural probe capable of controlled, localized chemical stimulation and electrophysiology recording. The neural probe was implemented using planar micromachining processes on Parylene C, a mechanically flexible, biocompatible substrate. The probe shank features two large microelectrodes (chemical sites) for drug loading and sixteen small microelectrodes for electrophysiology recording to monitor neuronal response to drug release. To reduce the impedance while keeping the size of the microelectrodes small, poly(3,4-ethylenedioxythiophene) (PEDOT) was electrochemically coated on recording microelectrodes. In addition, PEDOT doped with mesoporous sulfonated silica nanoparticles (SNPs) was used on chemical sites to achieve controlled, electrically-actuated drug loading and releasing. Different neurotransmitters, including glutamate (Glu) and gamma-aminobutyric acid (GABA), were incorporated into the SNPs and electrically triggered to release repeatedly. An in vitro experiment was conducted to quantify the stimulated release profile by applying a sinusoidal voltage (0.5 V, 2 Hz). The flexible neural probe was implanted in the barrel cortex of the wild-type Sprague Dawley rats. As expected, due to their excitatory and inhibitory effects, Glu and GABA release caused a significant increase and decrease in neural activity, respectively, which was recorded by the recording microelectrodes. This novel flexible neural probe technology, combining on-demand chemical release and high-resolution electrophysiology recording, is an important addition to the neuroscience toolset used to dissect neural circuitry and investigate neural network connectivity.
Dramatic improvements in outcome following pancreatoduodenectomy for pancreatic and periampullary cancers
Authors: Xu Hui , Bretthauer Michael , Fang Fang , Ye Weimin , Yin Li , Adami Hans-Olov
Published: June 2024

Background

Pancreatoduodenectomy is the only cure for cancers of the pancreas and the periampullary region but has considerable operative complications and uncertain prognosis. Our goal was to analyse temporal improvements and provide contemporary population-based benchmarks for outcomes following pancreatoduodenectomy.

Methods

We empanelled a cohort comprising all patients in Sweden with pancreatic or periampullary cancer treated with pancreatoduodenectomy from 1964 to 2016 and achieved complete follow-up through 2016. We analysed postoperative deaths and disease-specific net survival.

Results

We analysed 5923 patients with cancer of the pancreas (3876), duodenum (444), bile duct (504), or duodenal papilla (963) who underwent classic (3332) or modified (1652) Whipple’s procedure or total pancreatectomy (803). Postoperative deaths declined from 17.2% in the 1960s to 1.6% in the contemporary time period (2010–2016). For all four cancer types, median, 1-year and 5-year survival improved substantially over time. Among patients operated between 2010 and 2016, 5-year survival was 29.0% (95% confidence interval (CI): 25.5, 33.0) for pancreatic cancer, 71.2% (95% CI: 62.9, 80.5) for duodenal cancer, 30.8% (95% CI: 23.0, 41.3) for bile duct cancer, and 62.7% (95% CI: 55.5, 70.8) for duodenal papilla cancer.

Conclusion

There is a continuous and substantial improvement in the benefit-harm ratio after pancreatoduodenectomy for cancer.
4-1BB-encoding CAR causes cell death via sequestration of the ubiquitin-modifying enzyme A20
Authors: Dou Zhangqi , Bonacci Thomas Raphael , Shou Peishun , Landoni Elisa , Woodcock Mark G. , Sun Chuang , Savoldo Barbara , Herring Laura E. , Emanuele Michael J. , Song Feifei , Baldwin Albert S. , Wan Yisong , Dotti Gianpietro , Zhou Xin
Published: June 2024

CD28 and 4-1BB costimulatory endodomains included in chimeric antigen receptor (CAR) molecules play a critical role in promoting sustained antitumor activity of CAR-T cells. However, the molecular events associated with the ectopic and constitutive display of either CD28 or 4-1BB in CAR-T cells have been only partially explored. In the current study, we demonstrated that 4-1BB incorporated within the CAR leads to cell cluster formation and cell death in the forms of both apoptosis and necroptosis in the absence of CAR tonic signaling. Mechanistic studies illustrate that 4-1BB sequesters A20 to the cell membrane in a TRAF-dependent manner causing A20 functional deficiency that in turn leads to NF-κB hyperactivity, cell aggregation via ICAM-1 overexpression, and cell death including necroptosis via RIPK1/RIPK3/MLKL pathway. Genetic modulations obtained by either overexpressing A20 or releasing A20 from 4-1BB by deleting the TRAF-binding motifs of 4-1BB rescue cell cluster formation and cell death and enhance the antitumor ability of 4-1BB-costimulated CAR-T cells.
C-H-activated Csp2-Csp3 diastereoselective gridization enables ultraviolet-emitting stereo-molecular nanohydrocarbons with mulitple H···H interactions
Authors: Wei Ying , Zhong Chunxiao , Sun Yue , Ma Shuwei , Ni Mingjian , Wu Xiangping , Yan Yongxia , Yang Lei , Khodov Ilya A. , Ge Jiaoyang , Li Yang , Lin Dongqing , Wang Yongxia , Bao Qiujing , Zhang He , Wang Shasha , Song Juan , Lin Jinyi , Xie Linghai , Huang Wei
Published: June 2024

Gridization is an emerging molecular integration technology that enables the creation of multifunctional organic semiconductors through precise linkages. While Friedel-Crafts gridization of fluorenols is potent, direct linkage among fluorene molecules poses a challenge. Herein, we report an achiral Pd-PPh3-cataylized diastereoselective (>99:1 d.r.) gridization based on the C-H-activation of fluorene to give dimeric and trimeric windmill-type nanogrids (DWGs and TWGs). These non-conjugated stereo-nanogrids showcase intramolecular multiple H…H interactions with a low field shift to 8.51 ppm and circularly polarized luminescence with high luminescent dissymmetry factors (|gPL | = 0.012). Significantly, the nondoped organic light-emitting diodes (OLEDs) utilizing cis-trans-TWG1 emitter present an ultraviolet electroluminescent peak at ~386 nm (CIE: 0.17, 0.04) with a maximum external quantum efficiency of 4.17%, marking the highest record among nondoped ultraviolet OLEDs based on hydrocarbon compounds and the pioneering ultraviolet OLEDs based on macrocycles. These nanohydrocarbon offer potential nanoscafflolds for ultraviolet light-emitting optoelectronic applications.
Lung injury-induced activated endothelial cell states persist in aging-associated progressive fibrosis
Authors: Raslan Ahmed A. , Pham Tho X. , Lee Jisu , Kontodimas Konstantinos , Tilston-Lunel Andrew , Schmottlach Jillian , Hong Jeongmin , Dinc Taha , Bujor Andreea M. , Caporarello Nunzia , Thiriot Aude , von Andrian Ulrich H. , Huang Steven K. , Nicosia Roberto F. , Trojanowska Maria , Varelas Xaralabos , Ligresti Giovanni
Published: June 2024

Progressive lung fibrosis is associated with poorly understood aging-related endothelial cell dysfunction. To gain insight into endothelial cell alterations in lung fibrosis we performed single cell RNA-sequencing of bleomycin-injured lungs from young and aged mice. Analysis reveals activated cell states enriched for hypoxia, glycolysis and YAP/TAZ activity in ACKR1+ venous and TrkB+ capillary endothelial cells. Endothelial cell activation is prevalent in lungs of aged mice and can also be detected in human fibrotic lungs. Longitudinal single cell RNA-sequencing combined with lineage tracing demonstrate that endothelial activation resolves in young mouse lungs but persists in aged ones, indicating a failure of the aged vasculature to return to quiescence. Genes associated with activated lung endothelial cells states in vivo can be induced in vitro by activating YAP/TAZ. YAP/TAZ also cooperate with BDNF, a TrkB ligand that is reduced in fibrotic lungs, to promote capillary morphogenesis. These findings offer insights into aging-related lung endothelial cell dysfunction that may contribute to defective lung injury repair and persistent fibrosis.
CHARMM-GUI Multicomponent Assembler for modeling and simulation of complex multicomponent systems
Authors: Kern Nathan R. , Lee Jumin , Choi Yeol Kyo , Im Wonpil
Published: June 2024

Atomic-scale molecular modeling and simulation are powerful tools for computational biology. However, constructing models with large, densely packed molecules, non-water solvents, or with combinations of multiple biomembranes, polymers, and nanomaterials remains challenging and requires significant time and expertise. Furthermore, existing tools do not support such assemblies under the periodic boundary conditions (PBC) necessary for molecular simulation. Here, we describe Multicomponent Assembler in CHARMM-GUI that automates complex molecular assembly and simulation input preparation under the PBC. In this work, we demonstrate its versatility by preparing 6 challenging systems with varying density of large components: (1) solvated proteins, (2) solvated proteins with a pre-equilibrated membrane, (3) solvated proteins with a sheet-like nanomaterial, (4) solvated proteins with a sheet-like polymer, (5) a mixed membrane-nanomaterial system, and (6) a sheet-like polymer with gaseous solvent. Multicomponent Assembler is expected to be a unique cyberinfrastructure to study complex interactions between small molecules, biomacromolecules, polymers, and nanomaterials.
Sequence-specific dynamic DNA bending explains mitochondrial TFAM’s dual role in DNA packaging and transcription initiation
Authors: Huh Hyun , Shen Jiayu , Ajjugal Yogeeshwar , Ramachandran Aparna , Patel Smita S. , Lee Sang-Hyuk
Published: June 2024

Mitochondrial transcription factor A (TFAM) employs DNA bending to package mitochondrial DNA (mtDNA) into nucleoids and recruit mitochondrial RNA polymerase (POLRMT) at specific promoter sites, light strand promoter (LSP) and heavy strand promoter (HSP). Herein, we characterize the conformational dynamics of TFAM on promoter and non-promoter sequences using single-molecule fluorescence resonance energy transfer (smFRET) and single-molecule protein-induced fluorescence enhancement (smPIFE) methods. The DNA-TFAM complexes dynamically transition between partially and fully bent DNA conformational states. The bending/unbending transition rates and bending stability are DNA sequence-dependent—LSP forms the most stable fully bent complex and the non-specific sequence the least, which correlates with the lifetimes and affinities of TFAM with these DNA sequences. By quantifying the dynamic nature of the DNA-TFAM complexes, our study provides insights into how TFAM acts as a multifunctional protein through the DNA bending states to achieve sequence specificity and fidelity in mitochondrial transcription while performing mtDNA packaging.
Observation of heat pumping effect by radiative shuttling
Authors: Li Yuxuan , Dang Yongdi , Zhang Sen , Li Xinran , Chen Tianle , Choudhury Pankaj K. , Jin Yi , Xu Jianbin , Ben-Abdallah Philippe , Ju Bing-Feng , Ma Yungui
Published: June 2024

Heat shuttling phenomenon is characterized by the presence of a non-zero heat flow between two bodies without net thermal bias on average. It was initially predicted in the context of nonlinear heat conduction within atomic lattices coupled to two time-oscillating thermostats. Recent theoretical works revealed an analog of this effect for heat exchanges mediated by thermal photons between two solids having a temperature dependent emissivity. In this paper, we present the experimental proof of this effect using systems made with composite materials based on phase change materials. By periodically modulating the temperature of one of two solids we report that the system akin to heat pumping with a controllable heat flow direction. Additionally, we demonstrate the effectiveness of a simultaneous modulation of two temperatures to control both the strength and direction of heat shuttling by exploiting the phase delay between these temperatures. These results show that this effect is promising for an active thermal management of solid-state technology, to cool down solids, to insulate them from their background or to amplify heat exchanges.
Substantial contribution of slush to meltwater area across Antarctic ice shelves
Authors: Dell Rebecca L. , Willis Ian C. , Arnold Neil S. , Banwell Alison F. , de Roda Husman Sophie
Published: June 2024

Surface melting occurs across many of Antarctica’s ice shelves, mainly during the austral summer. The onset, duration, area and fate of surface melting varies spatially and temporally, and the resultant surface meltwater is stored as ponded water (lakes) or as slush (saturated firn or snow), with implications for ice-shelf hydrofracture, firn air content reduction, surface energy balance and thermal evolution. This study applies a machine-learning method to the entire Landsat 8 image catalogue to derive monthly records of slush and ponded water area across 57 ice shelves between 2013 and 2021. We find that slush and ponded water occupy roughly equal areas of Antarctica’s ice shelves in January, with inter-regional variations in partitioning. This suggests that studies that neglect slush may substantially underestimate the area of ice shelves covered by surface meltwater. Furthermore, we found that adjusting the surface albedo in a regional climate model to account for the lower albedo of surface meltwater resulted in 2.8 times greater snowmelt across five representative ice shelves. This extra melt is currently unaccounted for in regional climate models, which may lead to underestimates in projections of ice-sheet melting and ice-shelf stability.
A large-scale and PCR-referenced vocal audio dataset for COVID-19
Authors: Budd Jobie , Baker Kieran , Karoune Emma , Coppock Harry , Patel Selina , Payne Richard , Tendero Cañadas Ana , Titcomb Alexander , Hurley David , Egglestone Sabrina , Butler Lorraine , Mellor Jonathon , Nicholson George , Kiskin Ivan , Koutra Vasiliki , Jersakova Radka , McKendry Rachel A. , Diggle Peter , Richardson Sylvia , Schuller Björn W. , Gilmour Steven , Pigoli Davide , Roberts Stephen , Packham Josef , Thornley Tracey , Holmes Chris
Published: June 2024

The UK COVID-19 Vocal Audio Dataset is designed for the training and evaluation of machine learning models that classify SARS-CoV-2 infection status or associated respiratory symptoms using vocal audio. The UK Health Security Agency recruited voluntary participants through the national Test and Trace programme and the REACT-1 survey in England from March 2021 to March 2022, during dominant transmission of the Alpha and Delta SARS-CoV-2 variants and some Omicron variant sublineages. Audio recordings of volitional coughs, exhalations, and speech were collected in the ‘Speak up and help beat coronavirus’ digital survey alongside demographic, symptom and self-reported respiratory condition data. Digital survey submissions were linked to SARS-CoV-2 test results. The UK COVID-19 Vocal Audio Dataset represents the largest collection of SARS-CoV-2 PCR-referenced audio recordings to date. PCR results were linked to 70,565 of 72,999 participants and 24,105 of 25,706 positive cases. Respiratory symptoms were reported by 45.6% of participants. This dataset has additional potential uses for bioacoustics research, with 11.3% participants self-reporting asthma, and 27.2% with linked influenza PCR test results.
Unraveling the therapeutic potential of quercetin and quercetin-3-O-glucuronide in Alzheimer's disease through network pharmacology, molecular docking, and dynamic simulations
Authors: Sabarathinam Sarvesh
Published: June 2024

Quercetin is a flavonoid with notable pharmacological effects and promising therapeutic potential. Quercetin plays a significant role in neuroinflammation, which helps reduce Alzheimer's disease (AD) severity. Quercetin (Q) and quercetin 3-O-glucuronide (Q3OG) are some of the most potent antioxidants available from natural sources. However, the natural form of quercetin converted into Q3OG when reacted with intestinal microbes. The study aims to ensure the therapeutic potential of Q and Q3OG. In this study, potential molecular targets of Q and Q3OG were first identified using the Swiss Target Prediction platform and pathogenic targets of AD were identified using the DisGeNET database. Followed by compound and disease target overlapping, 77 targets were placed in that AKT1, EGFR, MMP9, TNF, PTGS2, MMP2, IGF1R, MCL1, MET and PARP1 was the top-ranked target, which was estimated by CytoHubba plug-in. The Molecular docking was performed for Q and Q3OG towards the PDB:1UNQ target. The binding score of Q and Q3OG was − 6.2 kcal/mol and − 6.58 kcal/mol respectively. Molecular dynamics simulation was conducted for Q and Q3OG towards the PDB:1UNQ target at 200 ns. This study's results help identify the multiple target sites for the bioactive compounds. Thus, synthesizing new chemical entity-based quercetin on structural modification may aid in eradicating AD complications.
Micromachined needle-like calorimetric flow sensor for sap flux density measurement in the xylem of plants
Authors: Kim Gigyu , Lee Junghoon
Published: June 2024

Miniaturized silicon thermal probes for plant’s sap flow measurement, or micro sap flow sensors, have advantages in minimum invasiveness, low power consumption, and fast responses. Practical applications in sap flow measurement has been demonstrated with the single-probe silicon micro sensors. However, the sensors could not detect flow directions and require estimating zero sap flow output that leads to significant source of uncertainty. Furthermore, silicon-needles would break easily during the insertion into plants. We present the first three-element micro thermal sap flow sensor packaged on a durable printed circuit board needle that can measure bidirectional flows with improved dynamics and precision. The performance of the newly designed calorimetric flow sensor was confirmed through precision calibration and field test on tomato stems. A calibration curve for a tomato stem was obtained with a sensitivity of 0.299 K/(µL mm−2 s−1) under the maximum temperature increase of 4.61 K. Results from the field test for one month revealed a correlation between the measured sap flux density and related conditions such as solar radiation, vapor pressure deficit, sunshade and irrigation. The developed sensor will contribute to practical long-term sap flow monitoring for small and delicate plants with minimal physical invasion.
Construction of warfarin population pharmacokinetics and pharmacodynamics model in Han population based on Bayesian method
Authors: Xia Xiaotong , Cai Xiaofang , Chen Jiana , Jiang Shaojun , Zhang Jinhua
Published: June 2024

The purpose of this paper is to study the genetic polymorphisms of related gene loci (CYP2C9*3, VKORC1-1639G > A) based on demographic and clinical factors, and use the maximum a posterior Bayesian method to construct a warfarin individualized dose prediction model in line with the Chinese Han population. Finally, the built model is compared and analyzed with the widely used models at home and abroad. In this study, a total of 5467 INR measurements are collected from 646 eligible subjects in our hospital, and the maximum a posterior Bayesian method is used to construct a warfarin dose prediction that conforms to the Chinese Han population on the basis of the Hamberg model. The model is verified and compared with foreign models. This study finds that body weight and concomitant use of amiodarone have a significant effect on the anticoagulant effect of warfarin. The model can provide an effective basis for individualized and rational dosing of warfarin in Han population more accurately. In the performance of comparison with different warfarin dose prediction models, the new model has the highest prediction accuracy, and the prediction percentage is as high as 72.56%. The dose predicted by the Huang model is the closest to the actual dose of warfarin. The population pharmacokinetics and pharmacodynamics model established in this study can better reflect the distribution characteristics of INR values after warfarin administration in the Han population, and performs better than the models reported in the literature.