bluuebunny/crossref_metadata_2025 huggingface dataset:
Physiotherapiewissenschaft umfassend verstehen: Ein angewandter Überblick über verschiedene Forschungsparadigmen (Teil 1)
Authors: Bopp Katharina , Haase Laura A. , Maric Filip
Published: December 2024

Die internationale Gesundheits- und Physiotherapieforschung hat sich in den letzten Jahrzehnten durch den Gebrauch und die Weiterentwicklung verschiedenster wissenschaftstheoretischer Grundlagen vielfältig entwickelt. Dadurch wird aktuellen Fragen und Problemstellungen auf unterschiedliche Weise begegnet und aktiv zur Veränderung beigetragen. Im deutschsprachigen Raum ist diese Vielfalt der wissenschaftstheoretischen Arbeit noch nicht im selben Grade zu verzeichnen. Die übliche Unterscheidung in quantitative und qualitative Forschung trägt zu Missverständnissen bei, wodurch die in diesen Begriffen implizierte Vielfalt sowohl für die Theorieentwicklung als auch für die angewandte Forschung verloren geht.

In einem zweiteiligen Artikel wird ein Überblick über die in der internationalen Gesundheits- und Physiotherapieforschung gängigsten Forschungsparadigmen gegeben, um deren grundlegendes Verständnis und zukünftige Anwendung in der deutschsprachigen Physiotherapiewissenschaft zu fördern.

Im ersten Teil werden wichtige begriffliche Grundlagen geklärt, anschließend folgt eine Auseinandersetzung mit dem Positivismus und Interpretativismus sowie eine Zusammenfassung. Im zweiten Teil werden das kritische Paradigma und der Poststrukturalismus erläutert, anschließend werden die Bedeutung der verschiedenen Forschungsparadigmen für den wissenschaftlichen Diskurs in der Physiotherapie diskutiert.

Bei der näheren Behandlung jedes Paradigmas werden die ihnen zugrundeliegenden ontologischen, epistemologischen und methodologischen Grundannahmen besprochen sowie die sich aus diesen ergebenden praktischen Möglichkeiten. Diese Möglichkeiten werden dann anhand plakativer Forschungsfragen zum Thema der Akademisierung veranschaulicht. Damit wird auch die Notwendigkeit paradigmatischer Vielfalt in der Physiotherapieforschung verdeutlicht, die benötigt wird, um den komplexen Problemen der aktuellen Zeit gerecht zu werden.

Die vorliegende Darstellung klärt ebenfalls, dass expliziter und stringenter Theoriebezug in der Physiotherapiewissenschaft unabdingbar ist. Für diesen Theoriebezug bedarf es in der Zukunft weitere Auseinandersetzung mit den hier vorgestellten Paradigmen, deren Details, Nuancen, Unter- und Mischvarianten, die über den ersten Überblick hinausgehen. Wenn wir auf diese Weise Wissenschaft umfassender verstehen, kann diese in noch größerem Ausmaß als bisher sowohl zur Weiterentwicklung der Physiotherapie als auch zur Gesundheit beitragen.
Rassismus im Gesundheitswesen am Beispiel der Schmerzbehandlung
Authors: Schulz-Koffka Johanna
Published: December 2024

Der Umgang mit Schmerzen ist für jeden Menschen herausfordernd, was sich im individuellen Verhalten widerspiegelt. Vorurteile über das Verhalten bei Schmerzen können die Therapie beeinflussen.
Aufgewacht: postoperatives Management im Aufwachraum
Authors: Lissner Malte
Published: December 2024

Nach der Narkoseausleitung ist der Patient wieder wach und die anästhesiologische Arbeit getan – das könnte man meinen, doch auch postoperativ sind wichtige Aspekte zu beachten. Im Schwerpunkt dreht sich daher alles um das pflegerische Arbeiten in einem modernen Aufwachraum.
Präoxygenierung
Authors: Schalk Richard , Kitz Valery
Published: December 2024

Die Präoxygenierung hat zum Ziel, die inspiratorische fraktionierte Sauerstoffkonzentration (FiO2) temporär auf 1.0 anzuheben. Was es dabei zu beachten gilt, erfahren Sie in unserem Überblick.
Präparateversorgung zwischen OP und Pathologie
Authors: Gädtke Sandra , Boxhammer Franziska
Published: December 2024

Laut WHO könnten die onkologischen Erkrankungen bis 2050 um 76 % im Vergleich zu 2022 steigen, das entspräche weltweit 35 Millionen Betroffene pro Jahr 1. Diese Entwicklung unterstreicht die zentrale Bedeutung der Pathologie in der modernen Medizin. Hochwertige Präparate sind entscheidend für die Diagnosegenauigkeit und die optimale Patientenversorgung. Die Abläufe, Arten von Präparaten und Qualitätssicherungsmaßnahmen spielen eine entscheidende Rolle in der Zusammenarbeit zwischen OP und Pathologie.
Intra–Abdominal Desmoplastic Small Round Cell Tumor: A Rare Case Report and Review of Literature
Authors: Mudgal Ankur , Sharma Devender , Singhal Vikram , Vaid Ashok
Published: December 2024

Desmoplastic small round cell tumor (DSRCT) is a rare and aggressive type of sarcomatous tumor with a high proclivity ofmetastasis.While it predominantly affects the abdominal cavity, it is most often observed in younger males and histopathologically identified by vascular and collagenous stroma containing groups of small tumor cells. However, standardized treatment approaches are currently unavailable. Here, we present the case of a 47-year-old man diagnosed with intra-abdominal metastatic DSRCT managed with multiple lines of chemotherapy followed by surgical debulking. Overall survival of 32 months is achieved with good quality of life.
Modified Keystone a Versatile Flap Reconstruction for Mastectomy Defects: Our Clinical Experience
Authors: Harsono Anastasia Dessy , Tjokrovonco Dominic Melino , Bas Birgita Maria Ratu Rosari , Putra Pratama Mandala
Published: December 2024

Introduction The closure of extensive defects in reconstructive surgery is a common challenge. The keystone flap technique has gained popularity due to its adaptability and reliance on fascia, providing a reliable blood supply and offering a better match for skin color compared with skin grafts. However, keystone flap necrosis can occur due to tension and inadequate tissue perfusion. To address this, a modified keystone flap technique called the “doubled-handle saucepan” was developed, resulting in improved flap vitality and reduced tissue necrosis, particularly in mastectomy defects.

Materials and Method We assessed 16 female patients who underwent “doubled-handle saucepan” keystone flaps after modified radical mastectomy (MRM). The average dimensions of wounds in this study were 23.1 ± 3.8 cm × 16.9 ± 2.9 cm, with the largest defect measuring 28.0 cm × 21.5 cm. The average size of the modified keystone flap was 36.3 ± 3.8 cm × 21.2 ± 2.2 cm.

Results Modified keystone flap demonstrated effective performance in managing extensive defects without any complication. The average operation time in our study was 124.3 ± 11.2 minutes.

Conclusion The “double-handled saucepan” keystone flap technique is a unique and dependable method derived from the original keystone flap, which effectively covers defects and maintains flap vitality without tension by ensuring vascularization at the skin bridge. This modified keystone flap technique proves highly effective for reconstruction after MRM, offering time efficiency and no need for a secondary donor site, making it an appealing alternative to free flaps or other local flap techniques in many cases.
Printing semiconductor-based devices and circuits for flexible electronic skin
Authors: Dahiya Abhishek Singh , Zumeit Ayoub , Christou Adamos , Loch Alex S. , Purushothaman Balaji , Skabara Peter J. , Dahiya Ravinder
Published: December 2024

Electronic skin (e-skin), capable of sensing a physical or chemical stimulus and triggering a suitable response, is critical in applications such as healthcare, wearables, robotics, and more. With a substantial number and types of sensors over a large area, the low-cost fabrication is desirable for e-skin. In this regard, printing electronics attract the attention as it allow efficient use of materials, “maskless” fabrication, and low-temperature deposition. Additionally, the use of e-skin in real-time applications calls for faster computation and communication. However, due to limitations of widely used materials (e.g., low mobility) and the printing tools (e.g., poor print resolution), the use of printed electronics has been restricted to passive devices for low-end applications until recent years. Such limitations are now being addressed through high-mobility materials and highlighted in this review article, using e-skin as a vehicle. This paper discusses techniques that allow printing of high-quality electronic layers using inorganic nanostructures, and their further processing to obtain sensors, energy harvesters, and transistors. Specifically, the contact printing, transfer printing, and direct roll printing are discussed along with working mechanisms and the influence of print dynamics. For the sake of completeness, a few examples of organic semiconductor-based devices are also included. E-skin presents a good case for 3D integration of flexible electronics, and therefore, the use of high-resolution printing to connect various devices on a substrate or 3D stack is also discussed. Finally, major challenges hindering the scalability of printing methods and their commercial uptake are discussed along with potential solutions.
Ion permeation through a narrow cavity constriction in KCNQ1 channels: Mechanism and implications for pathogenic variants
Authors: Mkrtchyan Liana , Sahakyan Harutyun , Eldstrom Jodene , Karapetyan Tatev , Abrahamyan Astghik , Nazaryan Karen , Schwarz Jürgen R. , Kneussel Matthias , Fedida David , Vardanyan Vitya
Published: December 2024

KCNQ1 potassium channels play a pivotal role in the physiology and pathophysiology of several human excitable and epithelial tissues. The latest cryo-electron microscopy (cryo-EM) structures provide unique insights into channel function and pharmacology, opening avenues for different therapeutic strategies against human diseases associated with KCNQ1 mutations. However, these structures also raise fundamental questions about the mechanisms of ion permeation. Cryo-EM structures thought to represent the open state of the channel feature a cavity region not wide enough for accommodation of hydrated K
+
. To understand how K
+
passes through the cavity constriction, we utilized microsecond-scale molecular dynamics (MD) simulations using the KCNQ1/KCNE3 cryo-EM structure, characterized mutants at the G345 residue situated at the narrowest point of the cavity, and recorded single channels. The findings indicate that ions become partially dehydrated at the constriction, which enables permeation. MD simulations demonstrate that the constriction can impede the flow of ions through the channel’s pore, a finding that is corroborated by mutational screening and single-channel recordings. Reduced channel conductance is the key mechanism underlying reported pathological KCNQ1 mutations at or near the constriction site.
A self-learning magnetic Hopfield neural network with intrinsic gradient descent adaption
Authors: Niu Chang , Zhang Huanyu , Xu Chuanlong , Hu Wenjie , Wu Yunzhuo , Wu Yu , Wang Yadi , Wu Tong , Zhu Yi , Zhu Yinyan , Wang Wenbin , Wu Yizheng , Yin Lifeng , Xiao Jiang , Yu Weichao , Guo Hangwen , Shen Jian
Published: December 2024

Physical neural networks (PNN) using physical materials and devices to mimic synapses and neurons offer an energy-efficient way to implement artificial neural networks. Yet, training PNN is difficult and heavily relies on external computing resources. An emerging concept to solve this issue is called physical self-learning that uses intrinsic physical parameters as trainable weights. Under external inputs (i.e., training data), training is achieved by the natural evolution of physical parameters that intrinsically adapt modern learning rules via an autonomous physical process, eliminating the requirements on external computation resources. Here, we demonstrate a real spintronic system that mimics Hopfield neural networks (HNN), and unsupervised learning is intrinsically performed via the evolution of the physical process. Using magnetic texture–defined conductance matrix as trainable weights, we illustrate that under external voltage inputs, the conductance matrix naturally evolves and adapts Oja’s learning algorithm in a gradient descent manner. The self-learning HNN is scalable and can achieve associative memories on patterns with high similarities. The fast spin dynamics and reconfigurability of magnetic textures offer an advantageous platform toward efficient autonomous training directly in materials.
Quad-Port Circular Polarized MIMO Dielectric Resonator Antenna Featuring Beam Tilting for Vehicular Communication
Authors: Sahu Jayant Kumar , Gupta Anshul
Published: December 2024

This paper presents the design and implementation of a quad-port circular polarized Dielectric Resonator Antenna (DRA) with Multiple-Input Multiple-Output (MIMO) capabilities and beam tilting features. The beam tilting feature allows for dynamic adjustment of the radiation pattern, improving signal coverage and reducing interference in complex environments. Beam tilting is achieved, and correlation is minimized in the far-field patterns by positioning a conducting plate between the antenna elements. Measurements indicate that the antenna achieves an Axial-Ratio Bandwidth (ARBW) of 4.69 GHz to 4.84 GHz with an AR of less than 3 dB and an impedance bandwidth from 4.6 GHz to 5.2 GHz. The DRA's resonating frequencies are produced by electromagnetically exciting it through optimized unequal-length loaded cross slots with a microstrip line. All ports are arranged in parallel configuration. The adjacent ports are 180 degrees out of phase each other. The antenna achieves maximum beam tilting of ± 30 degrees at 4.82 GHz. Oppositely oriented ports show polarization diversity with Left Hand Circular Polarization (LHCP) and Right Hand Circular Polarization (RHCP). The MIMO DRA's optimal diversity parameters make it ideal for high-speed vehicular Communication and WLAN application.
A novel optical multi-image data protection schemebased on phase-truncated asymmetric ciphers and2D-CSCCM
Authors: Li Jinqing , Tian Keyong , Liu Zhenxun , Di Xiaoqiang , Ibrahim Makram
Published: December 2024

Existing remote sensing platforms often overlook the security of theremote sensing image acquisition process, creating opportunities for potential attackersto exploit. To address this issue, this paper proposes a novel optical encryptionframework (ECC DPM) based on elliptic curves and phase truncation to ensure thesecure transmission of optical keys. Furthermore, an optical encryption scheme isdesigned based on ECC DPM to enable synchronous secure encryption during theremote sensing data acquisition stage, ensuring that remote sensing data remains ina ciphertext state from acquisition to storage and distribution. Finally, the proposedframework and encryption scheme are evaluated for security using a threat model andsimulation experiments. The experimental results demonstrate that the encryptionscheme effectively resists various statistical analysis attacks.
Insight into the optoelectronic and thermoelectric properties of novel LaSeM (M = Cl, F) chalcohalide semiconductors: ab-initio study
Authors: Khan Muhammad Salman , Gul Banat , Mohamed Abdelhay Salah , Aziz Siti Maisarah , Abbas Faheem
Published: December 2024

Chalcohalide materials demonstrate extraordinary thermal capacity and adjustable optoelectronic properties. Here we used the density functional theory and studied the structural, electronic, optical, and thermoelectric properties of novel LaSeM (M = Cl, F) ternary chalcohalides. The formation energies of LaSeCl and LaSeF were determined to be −2.21 (eV/f. u) and −2.32 (eV/f. u), respectively. The cohesive and formation energies well impacted the stable nature and phase transition features of these materials. The studeid materials were predicted to have a direct band gap nature as observed from the band structure investigation. For LaSeCl material, the projected band gaps as determined by the PBE-GGA and TB-mBJ potentials are 1.41 eV and 1.95 eV, whereas for the LaSeF the values are 1.72 eV and 2.36 eV, respectively. The complex dielectric function along with the other noteworthy optical parameters are computed for their potential applications in optoelectronics devices. The spectral region with a negative value of ε
1(ω), suggests these materials to have a metallic behavior. The predicted negative Seebeck coefficient values throughout the temperature range for LaSeCl and LaSeF materials display n-type conduction behavior. LaSeF exhibits more noticeable temperature-dependent improvements in electrical conductivity compared to LaSeCl.
The Large Magellanic Cloud: expanding the low-mass parameter space of dark matter direct detection
Authors: Reynoso-Cordova Javier , Bozorgnia Nassim , Piro Marie-Cécile
Published: December 2024

We investigate how the Large Magellanic Cloud (LMC) impacts the predicted signals in near-future direct detection experiments for non-standard dark matter (DM) interactions, using the Auriga cosmological simulations. We extract the local DM distribution of a simulated Milky Way-like halo that has an LMC analogue and study the expected signals in DarkSide-20k, SBC, DARWIN/XLZD, SuperCDMS, NEWS-G, and DarkSPHERE considering DM-nucleon effective interactions, as well as inelastic DM scattering. We find that the LMC causes substantial shifts in direct detection exclusion limits towards smaller cross sections and DM masses for all non-relativistic effective field theory (NREFT) operators, with the impact being highly pronounced for velocity-dependent operators at low DM masses. For inelastic DM, where the DM particle up-scatters to a heavier state, the LMC shifts the direct detection exclusion limits towards larger DM mass splitting and smaller cross sections. Thus, we show that the LMC significantly expands the parameter space that can be probed by direct detection experiments towards smaller DM-nucleon cross sections for all NREFT operators and larger values of mass splitting for inelastic DM.
Projected gravitational wave constraints on primordial black hole abundance for extended mass distributions
Authors: Dizon G.L.A. , Reyes R.C.
Published: December 2024

We investigate the projected minimum constraints set by next-generation gravitational wave detectors Einstein Telescope and LISA on the abundance of primordial black holes relative to dark matter from both resolvable mergers and the stochastic gravitational wave background (SGWB) for extended primordial black hole mass distributions. We consider broad power law distributions for a range of negative and positive exponents γ and top-hat distributions (with γ = 0) and use the IMRPhenomXAS waveforms to simulate binary sources up to mass ratios q
max = 1000 and redshifts z = 300. Our results suggest that accounting for extended mass distributions have the most apparent impact when considering mergers at high redshifts z > 30, for which the constraint curves have broader mass windows and shift to higher abundances compared to when a monochromatic distribution is assumed; on the other hand, constraints from low-redshift mergers and the SGWB do not change much with the assumed mass distribution. At high redshifts, astrophysical black holes are not expected to contribute significantly, providing possible smoking-gun evidence for PBHs. Constraints derived from LISA and ET observations would complement each other by probing different PBH mass windows and this holds for the extended mass distributions studied.
Influence of Deposition Temperature ZrO2 Thin Films Deposited on Transparent Conductive ITO Substrates
Authors: Xiao Ruiheng , Sun Wenrui , Gan Neng , Liu Zhifeng , Tong Zhengfu
Published: December 2024

In this paper, ZrO
2 thin films were deposited by magnetron sputtering DC method on transparent electrode ITO, The effects of different deposition temperatures on the physical phase, surface morphology and electrical properties of ZrO
2 thin films are investigated. The films were amorphous when the deposition temperature was increased from room temperature(RT) to 260°C, and turn to the orthorhombic crystal when the temperature was increased to 350°C. At the deposition temperature of 260 °C, the ZrO2 film had a dense surface with a roughness of 2.94 nm.At 260 °C, the film exhibit the best electric performance with the lowest leakage current density 7.580×10−4
A/cm
2, and is not breakdown when electric field is up to 200K(V/cm).
Enzymatic Hydrolysis and Composition Analysis of Polypeptide from Eggshell Membrane
Authors: Jian Weijie , Yan Zheng , Zhao Xinqiang , Wang Zhangang , Wang Haiyan
Published: December 2024

Eggshell membrane, also called “Feng Huang Yi” in traditional Chinese medicine, is a protein-based fibrous tissue and has various biological functions. This study aims to obtain an optimal condition for preparing eggshell membrane peptides (ESMP) using alkaline protease. Then the free and protein amino acid compositions, and the molecular weight distribution of the ESMP were analyzed in order to investigate the effect of enzymatic hydrolysis. Through single factor experiments and orthogonal optimization, the optimal condition for preparing ESMP was obtained. Under the conditions of enzyme dosage 13,000 U/g, hydrolysis time 6.5 h, and solid-liquid ratio 1:35, the hydrolysis degree was 62.10%. The top five predominant protein amino acids in ESMP were Glu, Asp, Pro, Cys and Arg, and the predominant free amino acids in ESMP were Met, Val, His and Cys. The content of peptides below 10,000 Da in ESMP was 98.07%.
Influence of mesoscale sea surface temperature anomaly on polar lows
Authors: Lin Ting , Rutgersson Anna , Wu Lichuan
Published: December 2024

Sea surface temperature anomaly (SSTA) associated with mesoscale oceanic processes, which are prevalent throughout the ocean, can significantly influence the atmospheric boundary layer and consequently atmospheric systems. While its influences on tropical and extratropical cyclones have been well-documented, the influence of mesoscale SSTA on polar lows (PLs) remains unexplored. To bridge this knowledge gap, we conducted a series of sensitivity numerical experiments with different SST configurations. The simulation results indicate that, over the lifespan of a PL, SSTA does not significantly influence PL intensity but does enhance latent heat release. On a longer time scale, based on simulations of five winter seasons over the Nordic Sea, we found that the accumulated impact of mesoscale SSTA creates favorable environments for PL intensification, characterized by higher moisture levels and lower static stability. These results highlight the importance of considering high-resolution SST boundary conditions, i.e. resolving mesoscale SST, in climate simulations of PLs.
Predictions of H-mode access and edge pedestal instability in the EHL-2 spherical torus
Authors: WANG 王 Yumin 嵎民 , LI 李 Kai 凯 , HUANG 黄 Zhuo 卓 , LIU 刘 Yiliang 一良 , DAI 戴 Shuyu 舒宇 , ZHANG 张 Jie 洁 , HUANG 黄 Yanqing 艳清 , GU 顾 Xiang 翔 , ZHAO 赵 Yihang 毅航 , XU 徐 Shuai 帅 , WANG 王 Erhui 二辉 , GUO 郭 Dong 栋 , SHI 石 Yuejiang 跃江 , XIE 谢 Huasheng 华生 , LIANG 梁 Yunfeng 云峰 , LIU 刘 Minsheng 敏胜 , the EHL-2 Team
Published: December 2024

The EHL-2 spherical torus is designed to demonstrate proton-boron (p-11B) fusion within a compact spherical tokamak. Its planned heating system includes a negative ion-based neutral beam injection (N-NBI), two positive ion-based NBI systems (P-NBI), electron cyclotron resonance heating (ECRH), ion cyclotron resonance heating (ICRH), and high harmonic fast wave (HHFW), with a total power output of 31 MW. According to scaling law estimates, the device is capable of achieving H-mode operation. The plasma density,

, at the minimum L-H power threshold,

, is estimated to be

. The pedestal parameters were calculated using the REPED model. Assuming B as the primary impurity ion, the predicted pedestal width and height are lower compared to the typical case with carbon impurities. The pedestal collisionality for EHL-2 is estimated to range between 0.06 and 0.17, indicating the potential for significant energy loss due to edge localized modes (ELMs). The heat flux on the divertor plate has been calculated using the JOREK code. The peak heat fluxes during ELM bursts are approximately 31.0 MW/m2 at the lower inboard target and 39.5 MW/m2 at the lower outboard target. A preliminary design of the resonant magnetic perturbation (RMP) coils has been completed to both control type-I ELMs and correct error fields. The system comprises 16 coils arranged into 2

4 pairs. In ELM control mode, a 14/2 component is generated at 1.7 G/kAt, with a current of 4.9 kA required to achieve

at the resonant surface, where the normalized poloidal magnetic flux is 0.85. In error field (EF) modulation mode, 2/1 and 3/1 components are generated at 3.5 G/kAt and 2.8 G/kAt, respectively.
Hamiltonian and Liouvillian learning in weakly-dissipative quantum many-body systems
Authors: Olsacher Tobias , Kraft Tristan , Kokail Christian , Kraus Barbara , Zoller Peter
Published: December 2024

We discuss Hamiltonian and Liouvillian learning for analog quantum simulation from non-equilibrium quench dynamics in the limit of weakly dissipative many-body systems. We present and compare various methods and strategies to learn the operator content of the Hamiltonian and the Lindblad operators of the Liouvillian. We compare different ansätze based on an experimentally accessible ‘learning error’ which we consider as a function of the number of runs of the experiment. Initially, the learning error decreases with the inverse square root of the number of runs, as the error in the reconstructed parameters is dominated by shot noise. Eventually the learning error remains constant, allowing us to recognize missing ansatz terms. A central aspect of our approaches is to (re-)parametrize ansätze by introducing and varying the dependencies between parameters. This allows us to identify the relevant parameters of the system, thereby reducing the complexity of the learning task. Importantly, this (re-)parametrization relies solely on classical post-processing, which is compelling given the finite amount of data available from experiments. We illustrate and compare our methods with two experimentally relevant spin models.
Financing structural and non-structural extreme heat adaptation measures in Southeast Asian cities: statuses and prospects
Authors: Lam Rainbow Yi Hung , Delina Laurence L
Published: December 2024

Extreme heat, often called a ‘silent killer,’ poses significant threats, particularly in Southeast Asia, where rapid urbanisation and increasing population density exacerbate vulnerability. Populations in this region face heightened risks of heat-related mortality and illness and diminished efficiency of the energy systems essential for cooling. Additionally, limited financial resources impede cities’ adaptation efforts, establishing finance as a critical factor influencing vulnerability to extreme heat. Despite growing recognition of the necessity for climate adaptation and mitigation financing, as highlighted by the Sendai Framework for Disaster Risk Reduction and the outcomes of the Conferences of the Parties to the United Nations Framework Convention on Climate Change, the adaptation finance gap continues to widen. This review article examines the literature on potential structural and non-structural adaptation strategies for extreme heat and identifies financing opportunities in Southeast Asia, thereby contributing to the Priority 3 agenda of the Sendai Framework. The review concludes with three recommendations: promoting assessment tools to increase adaptation finance and facilitate adoption, addressing issues of maladaptation related to adaptation finance, and aligning adaptation finance with long-term investment benefits.
Machine-learning-assisted dual harmonic generation FROG for enhanced ultrafast pulse recovery
Authors: Jaffray Wallace , Guo Ziheng , Di Falco Andrea , Ferrera Marcello
Published: December 2024

Ultrafast pulse characterisation is crucial for studying processes that occur at femtosecond timescales and below. Because of this, various methods have been developed to recover a pulse’s electric field profile at these durations, with the frequency-resolved optical gating (FROG) technique being the most common. However, this approach is computationally expensive and suffers from limitations in terms of robustness and reliability. In this regard, recent publications have demonstrated that applying machine learning towards ultrafast pulse recovery can alleviate these issues, providing more accurate retrievals. Inspired by these works, we propose an encoder–decoder scheme for a FROG system which exploits dual harmonic generation in low-index thin films. Specifically, we demonstrate enhanced reliability and accuracy of ultrafast pulse recovery when compared to machine learning approaches using second or third harmonic signals independently. As the amount of information used to train each neural network is kept constant, this study demonstrates and benchmarks the technological advantages of contextual information analysis involving multiple nonlinear processes.
Many-body expansion based machine learning models for octahedral transition metal complexes
Authors: Meyer Ralf , Chu Daniel B K , Kulik Heather J
Published: December 2024

Graph-based machine learning (ML) models for material properties show great potential to accelerate virtual high-throughput screening of large chemical spaces. However, in their simplest forms, graph-based models do not include any 3D information and are unable to distinguish stereoisomers such as those arising from different orderings of ligands around a metal center in coordination complexes. In this work we present a modification to revised autocorrelation descriptors, a molecular graph featurization method, for predicting spin state dependent properties of octahedral transition metal complexes (TMCs). Inspired by analytical semi-empirical models for TMCs, the new modeling strategy is based on the many-body expansion (MBE) and allows one to tune the captured stereoisomer information by changing the truncation order of the MBE. We present the necessary modifications to include this approach in two commonly used ML methods, kernel ridge regression and feed-forward neural networks. On a test set composed of all possible isomers of binary TMCs, the best MBE models achieve mean absolute errors (MAEs) of 2.75 kcal mol−1 on spin-splitting energies and 0.26 eV on frontier orbital energy gaps, a 30%–40% reduction in error compared to models based on our previous approach. We also observe improved generalization to previously unseen ligands where the best-performing models exhibit MAEs of 4.00 kcal mol−1 (i.e. a 0.73 kcal mol−1 reduction) on the spin-splitting energies and 0.53 eV (i.e. a 0.10 eV reduction) on the frontier orbital energy gaps. Because the new approach incorporates insights from electronic structure theory, such as ligand additivity relationships, these models exhibit systematic generalization from homoleptic to heteroleptic complexes, allowing for efficient screening of TMC search spaces.
Few-shot classification of Cryo-ET subvolumes with deep Brownian distance covariance
Authors: Yu Xueshi , Han Renmin , Jiao Haitao , Meng Wenjia
Published: December 2024

Few-shot learning is a crucial approach for macromolecule classification of the cryo-electron tomography (Cryo-ET) subvolumes, enabling rapid adaptation to novel tasks with a small support set of labeled data. However, existing few-shot classification methods for macromolecules in Cryo-ET consider only marginal distributions and overlook joint distributions, failing to capture feature dependencies fully. To address this issue, we propose a method for macromolecular few-shot classification using deep Brownian Distance Covariance (BDC). Our method models the joint distribution within a transfer learning framework, enhancing the modeling capabilities. We insert the BDC module after the feature extractor and only train the feature extractor during the training phase. Then, we enhance the model’s generalization capability with self-distillation techniques. In the adaptation phase, we fine-tune the classifier with minimal labeled data. We conduct experiments on publicly available SHREC datasets and a small-scale synthetic dataset to evaluate our method. Results show that our method improves the classification capabilities by introducing the joint distribution.
TG-CDDPM: text-guided antimicrobial peptides generation based on conditional denoising diffusion probabilistic model
Authors: Cao Junhang , Zhang Jun , Yu Qiyuan , Ji Junkai , Li Jianqiang , He Shan , Zhu Zexuan
Published: December 2024

Antimicrobial peptides (AMPs) have emerged as a promising substitution to antibiotics thanks to their boarder range of activities, less likelihood of drug resistance, and low toxicity. Traditional biochemical methods for AMP discovery are costly and inefficient. Deep generative models, including the long-short term memory model, variational autoencoder model, and generative adversarial model, have been widely introduced to expedite AMP discovery. However, these models tend to suffer from the lack of diversity in generating AMPs. The denoising diffusion probabilistic model serves as a good candidate for solving this issue. We proposed a three-stage Text-Guided Conditional Denoising Diffusion Probabilistic Model (TG-CDDPM) to generate novel and homologous AMPs. In the first two stages, contrastive learning and inferring models are crafted to create better conditions for guiding AMP generation, respectively. In the last stage, a pre-trained conditional denoising diffusion probabilistic model is leveraged to enrich the peptide knowledge and fine-tuned to learn feature representation in downstream. TG-CDDPM was compared to the state-of-the-art generative models for AMP generation, and it demonstrated competitive or better performance with the assistance of text description as supervised information. The membrane penetration capabilities of the identified candidate AMPs by TG-CDDPM were also validated through molecular weight dynamics experiments.
Optimal adaptive SMART designs with binary outcomes
Authors: Ghosh Rik , Chakraborty Bibhas , Nahum-Shani Inbal , Patrick Megan E , Ghosh Palash
Published: December 2024

In a sequential multiple-assignment randomized trial (SMART), a sequence of treatments is given to a patient over multiple stages. In each stage, randomization may be done to allocate patients to different treatment groups. Even though SMART designs are getting popular among clinical researchers, the methodologies for adaptive randomization at different stages of a SMART are few and not sophisticated enough to handle the complexity of optimal allocation of treatments at every stage of a trial. Lack of optimal allocation methodologies can raise critical concerns about SMART designs from an ethical point of view. In this work, we develop an optimal adaptive allocation procedure using a constrained optimization that minimizes the total expected number of treatment failures for a SMART with a binary primary outcome, subject to a fixed asymptotic variance of a predefined objective function. Issues related to optimal adaptive allocations are explored theoretically with supporting simulations. The applicability of the proposed methodology is demonstrated using a recently conducted SMART study named M-bridge for developing universal and resource-efficient dynamic treatment regimes for incoming first-year college students as a bridge to desirable treatments to address alcohol-related risks.
Estimation of a genetic Gaussian network using GWAS summary data
Authors: Yang Yihe , Lorincz-Comi Noah , Zhu Xiaofeng
Published: December 2024

A genetic Gaussian network of multiple phenotypes, constructed through the inverse matrix of the genetic correlation matrix, is informative for understanding the biological dependencies of the phenotypes. However, its estimation may be challenging because the genetic correlation estimates are biased due to estimation errors and idiosyncratic pleiotropy inherent in GWAS summary statistics. Here, we introduce a novel approach called estimation of genetic graph (EGG), which eliminates the estimation error bias and idiosyncratic pleiotropy bias with the same techniques used in multivariable Mendelian randomization. The genetic network estimated by EGG can be interpreted as shared common biological contributions between phenotypes, conditional on others. We use both simulations and real data to demonstrate the superior efficacy of our novel method in comparison with the traditional network estimators.
Demography and income in the 21st century: a long-run perspective
Authors: Brakman Steven , Kohl Tristan , van Marrewijk Charles
Published: December 2024

The world faces massive demographic changes in the 21st century. We analyse the impact of changes in the share of the working-age population for the global income distribution. First, the historical impact of demography on economic growth indicates that a 1% higher share of the working-age population in the total population results in a 0.173 percentage points higher income growth rate. Second, we use United Nations population projections to predict income changes for the remainder of this century. Third, we show how the share of income shifts away from Europe, North America and China towards South Asia and Africa, such that the current global economic powers will see their influence on world affairs decline.
Perception of nephrology in Europe: a strategy to improve recruitment of motivated fellows
Authors: Weinstein Talia , Vogelsang Nadine , Sonkodi Sandor , Slotki Itzchak , Martín-Carro Beatriz , Lappin David , Cannata-Andía Jorge B ,   the UEMS Renal Section and Board, Huyn-Do Uyen , Papagianni Aikaterini , Apostolou Theofanis , Ott Michael , Heering Peter J , Marn-Pernat Andreja , Certikova Vera , Haapio Mikko , Broberg Bo , Resic Halima , Rosenberg Mai , Arici Mustafa , Ferreira Anibal
Published: December 2024

Background

The shortage of applications for fellowships in nephrology is a worldwide challenge. This is the first survey to explore in Europe the reasons physicians choose (and do not choose) a career in nephrology.

Methods

An anonymous questionnaire was sent to the presidents of societies that are members of the European Renal Association (ERA), who invited trainees and nephrologists to respond. Statistical analysis was performed using SPSS v.26. (SPSS Inc., Chicago, IL, USA). Continuous variables were compared by Student's t-test or by one-way ANOVA.

Results

Responders included 516 (49%) females and 542 (51%) males. They comprised 278 (26%) trainees, and 780 (74%) nephrologists. The majority (64%) believe that students have an unfavourable perception of nephrology. For trainees, nephrology is not considered an attractive option due to ‘chronically ill patients’ (35%), ‘lack of contact during undergraduate training’ (37%), ‘nephrology is too challenging’ (38%), ‘poor remuneration’ (22%), ‘negative role models’ (15%), and ‘long working hours’ (14%). The factors with the greatest impact on choosing a career include a positive role model (46%), practical experience during medical school and early postgraduate training (42%).

Conclusion

Trainees emphasize that work–life balance is very important for the younger generation. A strong mentorship along with early engagement is associated with a higher likelihood of pursuing a career in nephrology. It is crucial to create a strategy that will provide a positive experience, renew the interest in nephrology careers and ensure enough nephrologists to treat the growing number of patients with kidney disease.
The endangered common hamster needs proteins: identifying diversified crop-based diets improving hibernation and reproductive success
Authors: Gérard Timothée , Robin Jean-Patrice , Kletty Florian , Habold Caroline
Published: December 2024

Modern production-oriented farming has led to a decline in agricultural biodiversity. In Europe, one example of concern is the common hamster Cricetus cricetus, a hibernating rodent once largely distributed in farmlands and now listed as Critically Endangered. The decline of this species is tied to a significant decrease in hamsters’ body mass at emergence from hibernation and in reproduction rate. Previous work has shown that monocultures of maize and wheat, which induce severe nutrient deficiencies, are a major cause of this phenomenon. To prevent such deficiencies, we tested in controlled conditions the effect of eight nutritive diets on hamsters’ hibernation and reproduction. Diets were selected for their nutritional content and based on farmers’ consultation. We tested three lipid-rich associations (‘oat–sunflower’, ‘potato–sunflower’ and ‘buckwheat–sunflower’), two protein-rich associations (‘maize–bean’ and ‘maize–pea’) and an intermediate association (‘wheat–soybean’), as well as ‘sprouted wheat’ and ‘sugar beet’. Hamsters fed the lipid-rich diets showed a better body condition at the end of hibernation. However, a low reproductive success was recorded in all groups, with only 17% of reproductive trials leading to birth. Nonetheless, the amount of protein ingested by the mothers before reproduction increased birth probability whilst pups’ survival to weaning was positively correlated to mothers’ body condition. Overall, our results show that hamsters need a balanced diet to ensure their ability to reproduce. Indeed, low-protein diets led to lower birth rates and low-lipid diets led to reduced body condition and subsequently low pups’ survival. The ‘wheat–soybean’ association best fulfilled hamsters’ nutritional needs. Overall, these results highlight the need to improve current farming practices to provide a more fulfilling nutritional environment for common hamsters and the farmland fauna.
Fulminant immune checkpoint inhibitor-associated myocarditis bridged to recovery with a temporary left ventricular assist device: a case report
Authors: Mallery Quinn , Walsh Kevin , Pelka Mark , Genev Ivo , Darki Amir
Published: December 2024

Background

Immune checkpoint inhibitors (ICIs) are effective antineoplastic agents but can cause adverse effects in many organ systems. Cardiovascular toxicities include arrhythmias, myocarditis, heart failure, takotsubo syndrome, pericarditis, coronary artery disease, and vasculitis.

Case summary

A 66-year-old woman with Stage 3C2 endometrial carcinoma presented for her second cycle of pembrolizumab, carboplatin, and paclitaxel. She subsequently suffered cardiac arrest and was brought to the emergency department. Spontaneous circulation returned following resuscitation, but she was haemodynamically unstable. An electrocardiogram revealed complete heart block. Initial management included intubation, vasopressor support, and transcutaneous pacing before transfer to the catheterization lab. Coronary angiography revealed no coronary artery disease. Right heart catheterization confirmed severe cardiogenic shock despite inotropic support and a temporary transvenous pacemaker in place. A micro-axial flow pump (Impella CP) was implanted for deteriorating cardiogenic shock. She was treated with high-dose corticosteroids (dexamethasone 190 mg i.v.) for suspected ICI-associated myocarditis, with significant improvement in cardiac function. The Impella was weaned and removed on Day 5. Cardiac magnetic resonance imaging showed elevated T1 and T2 signal intensities, consistent with the 2018 Lake Louise Criteria for myocarditis. The complete heart block was resolved, but a leadless pacemaker was implanted due to pre-existing conduction abnormalities.

Discussion

Early recognition of ICI-associated myocarditis can be achieved with biochemical testing, electrocardiography, imaging, and expedited investigation of alternative causes for cardiac decompensation. Our case demonstrates that temporary left ventricular assist devices can support cardiac output for patients in cardiogenic shock due to ICI-associated myocarditis, allowing for recovery following high-dose corticosteroids.
Diagnosis and management of dilated cardiomyopathy: a systematic review of clinical practice guidelines and recommendations
Authors: Sorella Anna , Galanti Kristian , Iezzi Lorena , Gallina Sabina , Mohammed Selma F , Sekhri Neha , Akhtar Mohammed Majid , Prasad Sanjay K , Chahal Choudhary Anwar Ahmed , Ricci Fabrizio , Khanji Mohammed Yunus
Published: December 2024

Dilated cardiomyopathy (DCM) is extensively discussed in numerous expert consensus documents and international guidelines, with differing recommendations. To support clinicians in daily practice and decision-making, we conducted a systematic review of key guidelines and recommendations concerning the diagnosis and clinical management of DCM. Our research encompassed MEDLINE and EMBASE databases for relevant articles published, as well as the websites of relevant scientific societies. We identified two guidelines and one scientific statement that met stringent criteria, thereby qualifying them for detailed systematic analysis. Our review revealed consensus on several key aspects: the definition of DCM, the use of B-type natriuretic peptides and high-sensitivity troponin in laboratory testing, the essential role of multimodality cardiovascular imaging for initial diagnosis, genetic counselling, and the management of advanced disease. Nonetheless, notable areas of variation included the formation of multidisciplinary management teams, the role of cascade genetic testing, pathways for arrhythmic risk stratification, and the criteria for prophylactic defibrillator implantation. Significant evidence gaps persist, particularly regarding the clinical trajectory of genetic, non-genetic and gene-elusive forms of DCM, the use of cardiovascular magnetic resonance in phenotype-negative family members with genotype-positive probands, and the development of potential aetiology-oriented therapies. Addressing these gaps could enhance clinical outcomes and inform future research directions and guideline development.
Association of childhood dehydroepiandrosterone sulfate concentration, pubertal development, and DNA methylation at puberty-related genes
Authors: Sudman Maya , Stöger Reinhard , Bentley Gillian R , Melamed Philippa
Published: December 2024

Objective

High concentrations of dehydroepiandrosterone sulfate (DHEAS) often precede premature puberty and sometimes polycystic ovary syndrome (PCOS). We hypothesized that the underlying mechanisms might involve DNA methylation. As an indicator of the downstream effects of DHEAS, we looked for associations between prepubertal DHEAS concentration, pubertal progression, and DNA methylation at puberty-related genes in blood cells.

Design

Blood methylome and DHEAS concentration at 7.5 and 8.5 years, respectively, were analyzed in 91 boys and 82 girls. Pubertal development data were collected between 8.1 and 17 years (all from UK birth cohort, Avon Longitudinal Study of Parents and Children [ALSPAC]).

Methods

Correlation between DHEAS and pubertal measurements was assessed by Spearman’s correlation. DHEAS association with methylation at individual CpGs or regions was evaluated by linear regression, and nearby genes examined by enrichment analysis and intersection with known puberty-related genes.

Results

Boys and girls with higher childhood DHEAS concentrations had more advanced pubic hair growth throughout puberty; girls also had advanced breast development, earlier menarche, and longer menstrual cycles. DHEAS concentration was associated with methylation at individual CpGs near several puberty-related genes. In boys, 14 genes near CpG islands with DHEAS-associated methylation were detected, and in girls, there were 9 which included LHCGR and SRD5A2; FGFR1 and FTO were detected in both sexes.

Conclusions

The association between DHEAS and pubertal development, as reported previously, suggests a physiological connection. Our novel findings showing that DHEAS concentration correlates negatively and linearly with DNA methylation levels at regulatory regions of key puberty-related genes, provide a mechanism for such a functional relationship.