bluuebunny/crossref_metadata_2025 huggingface dataset:
On the directional asymptotic approach in optimization theory
Authors: Benko Matúš , Mehlitz Patrick
Published: July 2024

As a starting point of our research, we show that, for a fixed order

$$\gamma \ge 1$$

γ
≥
1

, each local minimizer of a rather general nonsmooth optimization problem in Euclidean spaces is either M-stationary in the classical sense (corresponding to stationarity of order 1), satisfies stationarity conditions in terms of a coderivative construction of order

$$\gamma $$

γ

, or is asymptotically stationary with respect to a critical direction as well as order

$$\gamma $$

γ

in a certain sense. By ruling out the latter case with a constraint qualification not stronger than directional metric subregularity, we end up with new necessary optimality conditions comprising a mixture of limiting variational tools of orders 1 and

$$\gamma $$

γ

. These abstract findings are carved out for the broad class of geometric constraints and

$$\gamma :=2$$

γ
:
=
2

, and visualized by examples from complementarity-constrained and nonlinear semidefinite optimization. As a byproduct of the particular setting

$$\gamma :=1$$

γ
:
=
1

, our general approach yields new so-called directional asymptotic regularity conditions which serve as constraint qualifications guaranteeing M-stationarity of local minimizers. We compare these new regularity conditions with standard constraint qualifications from nonsmooth optimization. Further, we extend directional concepts of pseudo- and quasi-normality to arbitrary set-valued mappings. It is shown that these properties provide sufficient conditions for the validity of directional asymptotic regularity. Finally, a novel coderivative-like variational tool is used to construct sufficient conditions for the presence of directional asymptotic regularity. For geometric constraints, it is illustrated that all appearing objects can be calculated in terms of initial problem data.
Beyond nimodipine: advanced neuroprotection strategies for aneurysmal subarachnoid hemorrhage vasospasm and delayed cerebral ischemia
Authors: Luzzi Sabino , Bektaşoğlu Pınar Kuru , Doğruel Yücel , Güngor Abuzer
Published: July 2024

The clinical management of aneurysmal subarachnoid hemorrhage (SAH)-associated vasospasm remains a challenge in neurosurgical practice, with its prevention and treatment having a major impact on neurological outcome. While considered a mainstay, nimodipine is burdened by some non-negligible limitations that make it still a suboptimal candidate of pharmacotherapy for SAH. This narrative review aims to provide an update on the pharmacodynamics, pharmacokinetics, overall evidence, and strength of recommendation of nimodipine alternative drugs for aneurysmal SAH-associated vasospasm and delayed cerebral ischemia. A PRISMA literature search was performed in the PubMed/Medline, Web of Science, ClinicalTrials.gov, and PubChem databases using a combination of the MeSH terms “medical therapy,” “management,” “cerebral vasospasm,” “subarachnoid hemorrhage,” and “delayed cerebral ischemia.” Collected articles were reviewed for typology and relevance prior to final inclusion. A total of 346 articles were initially collected. The identification, screening, eligibility, and inclusion process resulted in the selection of 59 studies. Nicardipine and cilostazol, which have longer half-lives than nimodipine, had robust evidence of efficacy and safety. Eicosapentaenoic acid, dapsone and clazosentan showed a good balance between effectiveness and favorable pharmacokinetics. Combinations between different drug classes have been studied to a very limited extent. Nicardipine, cilostazol, Rho-kinase inhibitors, and clazosentan proved their better pharmacokinetic profiles compared with nimodipine without prejudice with effective and safe neuroprotective role. However, the number of trials conducted is significantly lower than for nimodipine. Aneurysmal SAH-associated vasospasm remains an area of ongoing preclinical and clinical research where the search for new drugs or associations is critical.
Advanced methods for treating gemfibrozil and carbamazepine in wastewater: a review
Authors: Sivanesan Jothivel , Rameshwar Sankar Sudharsan , Sivaprakash Baskaran , Rajamohan Natarajan , Osman Ahmed I. , Al-Muhtaseb Ala’a H.
Published: July 2024

The contamination of ecosystems by pharmaceuticals and personal care products represents a significant threat to public health, necessitating innovative approaches to clean wastewater before release into aquatic environments. Here, we review the emerging strategies and methods for the remediation of gemfibrozil and carbamazepine, emphasizing toxicological impacts, advanced oxidation processes, membrane-based removal techniques, and the underlying mechanisms driving these removal processes. We found that engineered composites with strong electron transfer capabilities can enhance the removal efficiency as they boost the generation of highly oxidative radicals. For instance, a nano zero-valent ion incorporated carbon–nitrogen composite removes 100% of gemfibrozil within 60 min. Similarly, a ruthenium perovskite-based heterogeneous catalyst achieved 100% elimination of carbamazepine in 7.5 min.
An In Silico Modelling Approach to Predict Hemodynamic Outcomes in Diabetic and Hypertensive Kidney Disease
Authors: Wang Ning , Benemerito Ivan , Sourbron Steven P , Marzo Alberto
Published: July 2024

Early diagnosis of kidney disease remains an unmet clinical challenge, preventing timely and effective intervention. Diabetes and hypertension are two main causes of kidney disease, can often appear together, and can only be distinguished by invasive biopsy. In this study, we developed a modelling approach to simulate blood velocity, volumetric flow rate, and pressure wave propagation in arterial networks of ageing, diabetic, and hypertensive virtual populations. The model was validated by comparing our predictions for pressure, volumetric flow rate and waveform-derived indexes with in vivo data on ageing populations from the literature. The model simulated the effects of kidney disease, and was calibrated to align quantitatively with in vivo data on diabetic and hypertensive nephropathy from the literature. Our study identified some potential biomarkers extracted from renal blood flow rate and flow pulsatility. For typical patient age groups, resistive index values were 0.69 (SD 0.05) and 0.74 (SD 0.02) in the early and severe stages of diabetic nephropathy, respectively. Similar trends were observed in the same stages of hypertensive nephropathy, with a range from 0.65 (SD 0.07) to 0.73 (SD 0.05), respectively. Mean renal blood flow rate through a single diseased kidney ranged from 329 (SD 40, early) to 317 (SD 38, severe) ml/min in diabetic nephropathy and 443 (SD 54, early) to 388 (SD 47, severe) ml/min in hypertensive nephropathy, showing potential as a biomarker for early diagnosis of kidney disease. This modelling approach demonstrated its potential application in informing biomarker identification and facilitating the setup of clinical trials.
The impact of ambient temperature and powertrains of SUVs on the environment in Slovakia during the use phase
Authors: Sečkár Michal , Schwarz Marián
Published: July 2024

This study compares different powertrains of sport utility vehicles (SUVs) with respect to ambient temperature and energy mix in Slovakia using the well-to-wheel (WTW) Life Cycle Assessment (LCA) method. Battery electric vehicles (BEV), plug-in hybrid electric vehicles (PHEV), and petrol and diesel vehicles were assessed and compared. The WTW study was conducted in SimaPro software assessing electricity/petrol/diesel production, transport, and use (energy conversion in the vehicle), with impact categories being climate change, particulates, NOx emissions, ionizing radiation, and fossil resource scarcity depending on the season (summer and winter). The results indicate that for Slovak conditions, BEV generally had the lowest environmental impact in both seasons studied. The only exceptions were ionizing radiation, which is clearly caused by the high share of nuclear power in the Slovak energy mix, and NOx emissions, which are caused by the combustion of biomass for electricity generation. The other impact categories were dominated by vehicles with an internal combustion engine. The results of emissions from fuel production are also given for each impact category. The transportation of fuel did not exceed the value of 1% for any impact category or for any powertrain. The conclusions of the study support the global trend in favour of vehicle electrification as an important way to reduce the negative environmental impacts of internal combustion engine vehicles in Slovakia.
Advances in the diagnosis and treatment of acute acquired comitant esotropia
Authors: Guo Shuyang , Zhou Yulian , Xi Sida , Zhao Chen , Wen Wen
Published: July 2024

Acute acquired comitant esotropia (AACE) is mainly characterized by sudden onset, accompanied by diplopia, without extraocular muscles paralysis or ocular motility disorders. In recent years, the incidence of AACE has been increasing, researchers have found that this phenomenon may be related to the widespread use of electronic devices and the increase in the number of people working from home during the COVID-19 pandemic. However, its neural mechanisms have not been fully elucidated. This article primarily reviews the latest developments in the diagnosis and treatment of AACE from the perspectives of etiology and treatment methods, aiming to provide direction for future in-depth exploration of the pathogenesis and treatment approaches of this disease.
Impacts of urban-rural integration on landscape patterns and their implications for landscape sustainability: The case of Changsha, China
Authors: He Yanhua , Wen Chubing , Fang Xuening , Sun Xiao
Published: July 2024

Context

Landscape patterns result from complex social-ecological interactions, such as urban-rural integration which is especially notable in China. However, the impacts of urban-rural integration on landscape sustainability remain understudied.

Objectives

Our objectives were to examine the impacts of urban-rural integration on landscape patterns and to explore its implications for landscape sustainability.

Methods

The study area is the Changsha metropolitan area in central China, which has undergone urban-rural integration since 2005. A three-step approach was used to (1) assess the spatiotemporal patterns of urban-rural integration dynamics with a multidimensional indicator system, (2) quantify landscape pattern dynamics using landscape metrics, and (3) explore the main drivers and processes involved in urban-rural integration responsible for the observed changes in landscape patterns through a time-fixed effects model.

Results

Our findings reveal a significant increase in the level of urban-rural integration in the Changsha metropolitan area from 2005 to 2020. Concurrently, the regional landscape has experienced increasing trends characterized by the loss and fragmentation of natural and agricultural patches, as well as heightened connectivity among constructed patches. Urban-rural integration exerts notable impacts on landscape patterns through processes such as societal convergence, economic interaction, technology sharing, and spatial interlinkage, subsequently influencing landscape (un)sustainability.

Conclusions

The different drivers and processes of urban-rural integration have varying effects on landscape patterns, with complex and intertwined impacts on landscape sustainability. Therefore, integrated landscape governance is imperative for addressing the disadvantages of urban-rural integration while strategically leveraging its advantages in various social-ecological contexts.
Complementarities between algorithmic and human decision-making: The case of antibiotic prescribing
Authors: Ribers Michael Allan , Ullrich Hannes
Published: July 2024

Artificial Intelligence has the potential to improve human decisions in complex environments, but its effectiveness can remain limited if humans hold context-specific private information. Using the empirical example of antibiotic prescribing for urinary tract infections, we show that full automation of prescribing fails to improve on physician decisions. Instead, optimally delegating a share of decisions to physicians, where they possess private diagnostic information, effectively utilizes the complementarity between algorithmic and human decisions. Combining physician and algorithmic decisions can achieve a reduction in inefficient overprescribing of antibiotics by 20.3 percent.
Examining the Strength of the Association Between Problem Gambling and Gambling to Escape. A Systematic Review and Meta-Analysis
Authors: Alaba-Ekpo Olukemi , Caudwell Kim M. , Flack Mal
Published: July 2024

Gambling to escape is often purported to play a central role in the maintenance of problem gambling. However, the strength and consistency this association is unknown. Therefore, the current systematic review and meta-analysis was conducted to explore the association between gambling to escape and problem gambling. The study protocol was registered in the PROSPERO database and protocols were developed and published studies were searched until May 2024. The PRISMA standards were adopted for screening and extraction of relevant data. Twenty-seven studies that measured gambling motives, reasons, or expectancies, related to escape, using validated multiple item measures, were included. Positive associations were found between gambling to escape and problem gambling, and this association remained after controlling for the effect of gambling for financial gain. Additional subgroup analyses were conducted to test the stability of the association by escape measure. Although the magnitude of the positive association changed depending on the scales used, the positive relationship held. The findings support the contention that problem gambling is at least, in part, maintained by the escape afforded by gambling—indicating the importance considering the emotion focused reasons in the design of initiative to reduce problem gambling behaviours.
ConKeD: multiview contrastive descriptor learning for keypoint-based retinal image registration
Authors: Rivas-Villar David , Hervella Álvaro S. , Rouco José , Novo Jorge
Published: July 2024

Retinal image registration is of utmost importance due to its wide applications in medical practice. In this context, we propose ConKeD, a novel deep learning approach to learn descriptors for retinal image registration. In contrast to current registration methods, our approach employs a novel multi-positive multi-negative contrastive learning strategy that enables the utilization of additional information from the available training samples. This makes it possible to learn high-quality descriptors from limited training data. To train and evaluate ConKeD, we combine these descriptors with domain-specific keypoints, particularly blood vessel bifurcations and crossovers, that are detected using a deep neural network. Our experimental results demonstrate the benefits of the novel multi-positive multi-negative strategy, as it outperforms the widely used triplet loss technique (single-positive and single-negative) as well as the single-positive multi-negative alternative. Additionally, the combination of ConKeD with the domain-specific keypoints produces comparable results to the state-of-the-art methods for retinal image registration, while offering important advantages such as avoiding pre-processing, utilizing fewer training samples, and requiring fewer detected keypoints, among others. Therefore, ConKeD shows a promising potential towards facilitating the development and application of deep learning-based methods for retinal image registration.

Graphical abstract
MicroRNA-513b-5p inhibits epithelial mesenchymal transition of colon cancer stem cells through IL-6/STAT3 signaling pathway
Authors: Zhang Zefeng , Sha Weihong
Published: July 2024

Objective

To reveal the mechanisms by which miR-513b-5p inhibits metastasis of colon cancer stem cells (CCSCs) through IL-6/STAT3 in HCT116 cells.

Methods

Sphere formation media and magnetic cell sorting were used to enrich and screen CCSCs. We used a colony formation assay, cell proliferation and viability assays, and a nude mouse transplantation tumor assay to identify CCSCs. ELISA was performed to identify IL-6 in the cell culture medium, and the growth, viability, wound healing, and transwell migration of distinct cell groups were compared to differentiate them. Dual-luciferase reporter assay, RT-PCR, and/or Western Blot analysis were conducted to determine the correlation between them.

Results

CD133+CD44+ HCT116 cells were shown to have higher cloning efficiency, greater proliferation ability and viability, and stronger tumorigenicity. A dual-luciferase reporter assay revealed that miR-513b-5p negatively affected STAT3 expression. RT-PCR and/or Western Blot analysis suggested that miR-513b-5p negatively affected STAT3 and Vimentin, while positively affecting E-cadherin expression. The STAT3 overexpression vector + miR-513b-5p inhibitor cell group had the highest efficiency, greatest proliferation ability and viability, and the highest IL-6 level in the experiments.

Conclusions

Mir-513b-5p inhibited the epithelial-mesenchymal transition (EMT) of CCSCs through IL-6/STAT3. This potential mechanism may provide a new therapeutic target for colon cancer.
Vertiport navigation requirements and multisensor architecture considerations for urban air mobility
Authors: García Crespillo Omar , Zhu Chen , Simonetti Maximilian , Gerbeth Daniel , Lee Young-Hee , Hao Wenhan
Published: July 2024

Communication, Navigation and Surveillance (CNS) technologies are key enablers for future safe operation of drones in urban environments. However, the design of navigation technologies for these new applications is more challenging compared to e.g., civil aviation. On the one hand, the use cases and operations in urban environments are expected to have stringent requirements in terms of accuracy, integrity, continuity and availability. On the other hand, airborne sensors may not be based on high-quality equipment as in civil aviation and solutions need to rely on tighter multisensor solutions, whose safety is difficult to assess. In this work, we first provide some initial navigation requirements related to precision approach operations based on recently proposed vertiport designs. Then, we provide an overview of a possible multisensor navigation architecture solution able to support these types of operations and we comment on the challenges of each of the subsystems. Finally, initial proof of concept for some navigation sensor subsystems is presented based on flight trials performed during the German Aerospace Center (DLR) project HorizonUAM.
Climate policy as social policy? A comprehensive assessment of the economic impact of climate action in the UK
Authors: Sudmant Andrew , Boyle Dom , Higgins‐Lavery Ruaidhri , Gouldson Andy , Boyle Andy , Fulker James , Brogan Jamie
Published: July 2024

Co-benefits are central to the case for climate action but are side-lined in many economic analyses. This paper presents an evaluation of three dimensions of the costs and benefits of climate change interventions in six urban regions of the UK. Findings indicate that meeting the UK’s 2033–2037 climate targets could yield £164 billion in total benefits. Notably, only 13% of these benefits are financial, in contrast to the 79% of which are social benefits. These social benefits include improvements in public health, reduced traffic congestion, and increased thermal comfort in homes. These results underscore the need for economic evaluations to expand their scope and move beyond the narrow financial cost–benefit analysis that predominates. Moreover, the magnitude of the social benefits underscores the need for integrating social and climate challenges in policymaking. Concurrently, the results demonstrate the sensitivity of the social benefits of climate actions to the normative aspects of empirical analysis. Determining whether emissions reductions in the transport sector, for example, should be achieved through the deployment of electric cars, expansion of public transport, and/or increases in walking and cycling requires both technical analysis and value-based decision making. Ensuring that decision-making processes are deliberate and transparent in empirical analysis is therefore critical. We conclude by suggesting that institutions such as the UK Climate Change Committee and Scottish Climate Intelligence Service should take the opportunity to be more explicit in the normative decisions embedded in their empirical work to demonstrate best practice for the wider research community.
MicroRNA and renal fibrosis in autosomal dominant polycystic kidney disease: a longitudinal study
Authors: Lai Silvia , Mastroluca Daniela , Perrotta Adolfo Marco , Muscaritoli Maurizio , Lucciola Sara , Felli Maria Pia , Izzo Paolo , Rotondi Silverio , Izzo Sara , Tartaglione Lida , Belli Roberta , Ramaccini Cesarina , Izzo Luciano , De Intinis Claudia , Panebianco Valeria , Mazzaferro Sandro
Published: July 2024

Background

Autosomal dominant polycystic kidney disease (ADPKD) is a hereditary kidney disorder that may progress to kidney failure, accounting for 5–10% of all patients with end-stage kidney disease (ESKD). Clinical data, as well as molecular genetics and advanced imaging techniques have provided surrogate prognostic biomarkers to predict rapid decline in kidney function, nonetheless enhanced tools for assessing prognosis for ADPKD are still needed. The aim of this study was to analyze specific microRNAs involved in the pathogenesis of ADPKD and in the development of renal fibrosis, evaluating their potential role as predictors of renal function loss.

Methods

We evaluated kidney function by estimated glomerular filtration rate (eGFR) in 32 ADPKD patients in different stages of kidney disease at T0 and after a 24-month follow up (T1). Patients were divided into two groups: Rapid disease progression ([RP], n 15) and Non-rapid disease progression ([NRP], n 17), according to the Mayo Clinic classification criteria. At T0, ADPKD patients underwent plasma sampling for quantitative analysis of h-miR-17-5p, h-miR-21-5p and h-miR-199a-5p microRNA expression, using the quantitative reverse transcriptase-polymerase chain reaction (qRT-PCR) method and a 3 T magnetic resonance imaging (MRI), using an advanced MRI imaging protocol, for the quantification of total kidney volume (TKV), total perfusion volume (TPV) and total fibrotic volume (TFV).

Results

The expression of h-miR17-5p was higher (p < 0.05) in ADPKD patients with rapid disease progression. h-miR-17-5p, h-miR-21-5p and h-mir-199-5p showed a positive and significant correlation with the eGFR slope (mL/min/1.73 m2/year) (p < 0.05) but not with the eGFR at both T0 and T1. Both total fibrotic volume (cm3) and height-adjusted total fibrotic volume (cm3/m) were positively and significantly correlated to h-miR 21-5p and h-miR 199-5p (p < 0.05), but not to total kidney volume (cm3) and height-adjusted total kidney volume (cm3/m).

Conclusions

The microRNAs we studied were associated with fibrosis and renal damage, suggesting their possible role as biomarkers able to identify ADPKD patients at high risk of disease progression regardless of the degree of kidney function, and therefore suitable for medical therapy, and may help uncovering new molecular mechanisms underlying cystogenesis.

Graphical abstract
Storage of weights and retrieval method (SWARM) approach for neural networks hybridized with conformal prediction to construct the prediction intervals for energy system applications
Authors: Ashraf Waqar Muhammad , Dua Vivek
Published: July 2024

The prediction intervals represent the uncertainty associated with the model-predicted responses that impacts the sequential decision-making analytics. Here in this work, we present a novel model-based data-driven approach to construct the prediction intervals around the model-simulated responses using artificial neural network (ANN) model. The loss function is modified with least mean square error and standard deviation between the model-simulated and actual responses for the online-training mode of ANN model development. The parameters (weights and biases) stored during the model development are extracted and are deployed to construct the prediction intervals with 95% confidence level for the test datasets of the three energy systems-based case studies including: crease recovery angle, energy efficiency cooling & energy efficiency heating and gas turbine power plant & coal power plant which are taken from literature, benchmark datasets and industrial-scale applications, respectively. The developed ANN models present root-mean-squared error of 1.20% and 0.52% on test dataset for energy efficiency cooling and energy efficiency heating, respectively. The width of prediction intervals made by the proposed approach, called as Storage of Weights And Retrieval Method (SWARM), incorporates the information available for each test observation during the model training and the SWARM-based prediction intervals are compared to those of inductive conformal prediction (ICP) technique. It is noted that SWARM technique offers better locally adaptive prediction intervals than those of ICP, highlighting the effectiveness of the SWARM technique for the estimation of prediction intervals for the case studies. This research presents a novel data-driven approach to construct the prediction intervals using the model-based information that can be applied on different real-life applications.
Performance of the pre-trained large language model GPT-4 on automated short answer grading
Authors: Kortemeyer Gerd
Published: July 2024

Automated Short Answer Grading (ASAG) has been an active area of machine-learning research for over a decade. It promises to let educators grade and give feedback on free-form responses in large-enrollment courses in spite of limited availability of human graders. Over the years, carefully trained models have achieved increasingly higher levels of performance. More recently, pre-trained Large Language Models (LLMs) emerged as a commodity, and an intriguing question is how a general-purpose tool without additional training compares to specialized models. We studied the performance of GPT-4 on the standard benchmark 2-way and 3-way datasets SciEntsBank and Beetle, where in addition to the standard task of grading the alignment of the student answer with a reference answer, we also investigated withholding the reference answer. We found that overall, the performance of the pre-trained general-purpose GPT-4 LLM is comparable to hand-engineered models, but worse than pre-trained LLMs that had specialized training.
First evidence of metformin detected in Jakarta waters
Authors: Koagouw Wulan , Simanjuntak Erna , Hazell Richard J. , Subandi Riyana , Ciocan Corina
Published: July 2024

Pharmaceutically active compounds have been considered contaminants of emerging concern, in response to evidence that these substances may adversely affect non-target organisms. The pharmaceutical metformin is the most commonly prescribed anti-diabetes medicine throughout the world. Metformin has been detected in numerous freshwater systems as well as in seawater at a number of sites around the world over the last few years, but has never been reported in the Indonesian capital city Jakarta. Several recent studies have highlighted various ecotoxicological effects of this medicine on aquatic organisms. Here we report the first evidence of metformin’s presence in Jakarta waters. Samples from the Angke river, one of the main rivers in Jakarta, were collected from six sites. Metformin was detected at three sites in concentrations ranging from 27 ng/L to 414 ng/L. Metformin is one of the most detected APIs (active pharmaceutical ingredients) in aquatic environments worldwide, and there is increasing concern regarding its impact on the health of wildlife and humans. However, this is the first report of metformin contamination in Jakarta waters, adding to the evidence of potentially increased pollution with pharmaceuticals, as noted in our previous studies. With no natural degradation processes, these chemical compounds can be easily reintroduced to the food chain and impact human health.
Die Leiden der Alten am Geschlecht der Jungen
Authors: Lindner Christian
Published: July 2024

Zusammenfassung: Im Artikel „Sturm und Drang im Würgegriff der Medien – Die Leiden der jungen Generation am eigenen Geschlecht“ in der Zeitschrift für Kinder- und Jugendpsychiatrie und Psychotherapie (Jahrgang 51, Heft 5) setzen sich die Kollegen Korte und Tschuschke mit der Frage auseinander, inwiefern der Anstieg von Abweichungen im Geschlechtsidentitätserleben bei Jugendlichen „auch ein Resultat kultureller und vor allem medientechnologischer Umbrüche ist“. Die Autoren beziehen kritisch Stellung zum geplanten deutschen „Selbstbestimmungsgesetz“, zu sozialer Transition bei Kindern und Jugendlichen, zur sogenannter Pubertätsblockade sowie zur Hormontherapie bei Jugendlichen, und rechtfertigen den Vorzug eines genderkritischen gegenüber dem eines transaffirmativen Therapieansatzes. Obgleich der Artikel einige interessante Hypothesen aus dem Blickwinkel u. a. der Kulturwissenschaft und Philosophie einbringt, kann er doch auf Grund des transkritischen Grundtenors zur Verunsicherung von Kolleg_innen in der Behandlung von trans*Personen beitragen. Dies ist auf sprachliche Mittel, irreführende und fehlerhafte Zitate und unvollständige bzw. inkorrekte Schilderung von Fakten zurückzuführen. Die vorliegende Arbeit möchte sich daher kritisch mit dem zur Diskussion gestellten Artikel der Autoren Korte und Tschuschke befassen und bedient sich dabei einer sprachkritischen Untersuchung sowie einer Überprüfung der von den Autoren angeführten Fakten, Daten und Quellen. Sie möchte versuchen, Kolleg_innen dazu zu ermuntern, sich mit geschlechtsdysphorischen Kindern und Jugendlichen in einen gemeinsamen, partizipativen, trans*respektvollen Behandlungsprozess zu begeben und den von den Autoren Korte und Tschuschke im Artikel wenig beachteten, großen Zwischenbereich zwischen „genderkritischer“ und „transaffirmativer“ Haltung auszuloten.
Three‐Dimensional Probabilistic Hydrofacies Modeling Using Machine Learning
Authors: Kawo Nafyad Serre , Korus Jesse , Kishawi Yaser , Haacker Erin Marie King , Mittelstet Aaron R.
Published: July 2024

Characterizing the 3D distribution of hydraulic properties in glacial sediments is challenging due to fine‐scale heterogeneity and complexity. Borehole lithological data provide high vertical resolution but low horizontal resolution. Geophysical methods can fill gaps between boreholes, providing improved horizontal resolution but low vertical resolution. Machine learning can combine borehole and geophysical data to overcome these challenges. However, few studies have compared multiple machine learning methods for predicting hydrofacies in glacial aquifer systems. This study uses colocated airborne electromagnetic resistivity and borehole lithology data to train multiple machine learning models and predict the 3D distribution of hydrofacies in glacial deposits of eastern Nebraska, USA. Random Forest, Gradient Boosting Classifier, Extreme Gradient Boosting, Multilayer Perceptron, and Stacking Classifier were used to model 3D probabilistic distributions of hydrofacies (sand and clay) at a grid size of 200 m × 200 m × 3 m. Comparison of the predicted 3D hydrofacies models shows that the probability distributions and the contrasts between hydrofacies vary. The classification metrics show that the Stacking Classifier model performed better than other machine learning models in predicting hydrofacies. Multi‐Layer Perceptron and Stacking Classifier models show sharp vertical transitions between the low and high sand probability while other machine learning models show gradual transitions. K‐means clustering was used to translate the Stacking Classifier model into a 4‐class hydraulic conductivity model. This study shows that machine learning methods advance our understanding of glacial hydrogeology by improving the vertical and horizontal resolution of hydrofacies distribution and resolving aquifer‐aquifer and stream‐aquifer connections.
Permafrost Formation in a Meandering River Floodplain
Authors: Douglas Madison M. , Li Gen K. , West A. Joshua , Ke Yutian , Rowland Joel C. , Brown Nathan , Schwenk Jon , Kemeny Preston C. , Piliouras Anastasia , Fischer Woodward W. , Lamb Michael P.
Published: July 2024

Permafrost influences 25% of land in the Northern Hemisphere, where it stabilizes the ground beneath communities and infrastructure and sequesters carbon. However, the coevolution of permafrost, river dynamics, and vegetation in Arctic environments remains poorly understood. As rivers meander, they erode the floodplain at cutbanks and build new land through bar deposition, creating sequences of landforms with distinct formation ages. Here we mapped these sequences along the Koyukuk River floodplain, Alaska, analyzing permafrost occurrence, and landform and vegetation types. We used radiocarbon and optically stimulated luminescence (OSL) dating to develop a floodplain age map. Deposit ages ranged from modern to 10 ka, with more younger deposits near the modern channel. Permafrost rapidly reached 50% areal extent in all deposits older than 200 years then gradually increased up to ∼85% extent for deposits greater than 4 Kyr old. Permafrost extent correlated with increases in black spruce and wetland abundance, as well as increases in permafrost extent within wetland, and shrub and scrub vegetation classes. We developed an inverse model to constrain permafrost formation rate as a function of air temperature. Permafrost extent initially increased by ∼25% per century, in pace with vegetation succession, before decelerating to <10% per millennia as insulating overbank mud and moss slowly accumulated. Modern permafrost extent on the Koyukuk floodplain therefore reflects a dynamic balance between widespread, time‐varying permafrost formation and rapid, localized degradation due to cutbank erosion that might trigger a rapid loss of permafrost with climatic warming.
Estimation of Downward Heat Flux Into the F‐Region From the Inner‐Magnetosphere During Stable Auroral Red (SAR) Arc Events in the Daytime Obtained Using OI 630.0 nm Red‐Line Emissions
Authors: Upadhyay Kshitiz , Pallamraju Duggirala , Chakrabarti Supriya
Published: July 2024

Stable Auroral Red (SAR) arcs are enhanced OI 630.0 nm emissions formed due to an increased electron temperature (Te) near the equatorward wall of mid‐latitude trough during geomagnetic disturbances. The Te enhancement associated with SAR arcs is driven by electron heating through heat flux precipitation from near plasmapause region to ionospheric F‐region via heat conduction. Although Te enhancements have been reported by radar/satellite measurements along with increased 630.0 nm brightness during SAR arc events, measurements of corresponding heat flux are sparse, and almost none in the daytime. This work presents the results on the estimation of electron heat flux incident during SAR arcs formed during daytime obtained by a comprehensive suite of measurements, and forward modeling. We present observations of several SAR arc events when the ground‐based OI 630.0 nm emissions were larger than the model values during disturbed periods and were found to be existing in conjunction with increased Te at the altitude of DMSP (∼840 km). Forward modeling was carried out to determine the values of Te that would cause an enhancement in these emissions during daytime at much lower altitudes (∼400–500 km). These values of Te were used to estimate the required electron heat flux varying in the range of ∼1.0–4.6 × 1010 eV‐cm−2‐s−1. These results present the first estimates of F‐region heat flux enabled using ground‐based OI 630.0 nm emissions and open a new approach in the investigations of energy released into the ionosphere through heat conduction for daytime conditions during geomagnetically disturbed periods.
Influence of Equatorial Spring Insolation on Abrupt Asian Summer Monsoon Decline at Orbital Scale
Authors: Zhang Xiaojian , Chen Chunzhu , Zhao Wenwei
Published: July 2024

The dominant influence of precession‐induced changes in summer insolation on orbital‐scale variability of the Asian summer monsoon (ASM) during the Holocene has been widely proposed; however, it remains unclear why the decline of the ASM started several thousand years after the peak summer insolation. Through comparisons of climate simulations and proxy records, our study reveals that the abrupt decline in the ASM coincided with an increase in spring insolation at the equator. The reduced spring insolation resulted in a cooler tropical Indian Ocean, which weakened and shifted northward the westerly jet due to decreased meridional thermal gradient. The South Asian high moved northward in conjunction with the westerly jet, causing anomalous upwards over northern South Asia, the Tibetan Plateau, as well as southwestern and northern China. The associated anomalous cyclone over the Tibetan Plateau enhanced the monsoonal moisture transport, subsequently intensifying the ASM circulation and precipitation. The ASM was enhanced by the decrease in spring insolation and was weakened by the opposite. The abrupt decline of the ASM was associated with an increase in spring insolation superimposed on a decrease in summer insolation. Consequently, orbital‐scale ASM variability is dominated by the precession not only via insolation changes in summer but also changes in spring.
New Criteria to Estimate Local Thermal Nonequilibrium Conditions for Heat Transport in Porous Aquifers
Authors: Shi Wenguang , Wang Quanrong , Klepikova Maria , Zhan Hongbin
Published: July 2024

A fundamental assumption in numerous studies of heat transfer in porous media is local thermal equilibrium (LTE), which assumes that the temperature of the porous media at the fluid and solid interface is in instantaneous equilibrium. Although significant efforts have been made to quantify the occurrence and consequences of local thermal nonequilibrium (LTNE), where the temperatures of the fluid and adjacent solid phases differ, there is no simple expression for quantifying the occurrence and effects of local thermal disequilibrium. Using a numerical model combining LTE and LTNE models, we develop here two simple general criteria based on Darcian velocities (q) and particle sizes (dp) of porous media for determining when LTNE effects occur (denoted as g(dp, q)) and when they become significant (denoted as f(dp, q)). Results show that using an LTE model can result in an underestimation of effective thermal diffusivity and the unaffected Darcian velocities when g(dp, q) > 0. It is possible that using the LTE model can result in an underestimation of the effective thermal diffusivity by more than 200 times within Darcian velocities ranging from 0 to 60 m/d. In the case of g(dp, q) < 0, the use of the LTE model can result in an overestimation of effective thermal diffusivity and Darcian velocities. The performances of the newly developed general criteria are demonstrated using three typical data sets and corresponding numerical models. These data sets include new heat tracer tests conducted in the laboratory and the field, as well as temperature‐time series collected in streambed sediments from a previous study by Shanafield et al. (2012, https://doi.org/10.5194/hessd‐9‐4305‐2012). The potential LTNE effects should be considered when using heat as a tracer to characterize flow and heat transport in porous media in the presence of Darcian velocities less than 2 m/d and particle sizes larger than 10 mm.
Cognitive performance in young adult women with a history of premature adrenarche
Authors: Tennilä Jussi , Muukkonen Liisa , Utriainen Pauliina , Voutilainen Raimo , Jääskeläinen Jarmo , Liimatta Jani
Published: July 2024

Background

Girls with premature adrenarche (PA) mature earlier than peers and have been found to have greater symptom accounts reflecting anxiety compared to peers. It is not known, however, whether PA effects cognitive development. This longitudinal case-control cohort study aimed: (1) To investigate whether a history of PA leads to measurable changes in adulthood cognitive performance, and (2) to assess whether findings characteristic of PA girls predict adulthood cognitive performance.

Methods

Twenty-seven girls with PA and 27 age-matched control girls were examined and followed from mid-childhood (mean age 7.2 years) until early adult age (18.5 years). Wechsler Adult Intelligence Scale, Fourth Edition scores were used as main outcome measure.

Results

Allostatic load (AL) scores, which compile multisystem variables to reflect the overall wear and tear of the body from increased and prolonged stress, were higher in the PA group in both prepuberty and adulthood, but there were no differences in WAIS-IV results between the groups (full-scale IQ 92.7 vs. 97.5, p 0.376; no differences in separate indexes). Childhood androgen levels, glucose metabolism biomarkers, and AL scores failed to predict adulthood cognitive performance outcomes.

Conclusion

The study suggests that PA does not predispose to adverse adulthood outcomes of cognitive development.

Impact

The study suggests that a history of premature adrenarche (PA) does not affect cognitive performance in adult age.

Childhood androgen levels and biomarkers of glucose metabolism failed to predict adulthood cognitive outcomes in this study.

Allostatic load scores were elevated in the PA group both in childhood and adulthood but did not predict adulthood cognitive outcomes.
Cancer stem cells: advances in knowledge and implications for cancer therapy
Authors: Chu Xianjing , Tian Wentao , Ning Jiaoyang , Xiao Gang , Zhou Yunqi , Wang Ziqi , Zhai Zhuofan , Tanzhu Guilong , Yang Jie , Zhou Rongrong
Published: July 2024

Cancer stem cells (CSCs), a small subset of cells in tumors that are characterized by self-renewal and continuous proliferation, lead to tumorigenesis, metastasis, and maintain tumor heterogeneity. Cancer continues to be a significant global disease burden. In the past, surgery, radiotherapy, and chemotherapy were the main cancer treatments. The technology of cancer treatments continues to develop and advance, and the emergence of targeted therapy, and immunotherapy provides more options for patients to a certain extent. However, the limitations of efficacy and treatment resistance are still inevitable. Our review begins with a brief introduction of the historical discoveries, original hypotheses, and pathways that regulate CSCs, such as WNT/β-Catenin, hedgehog, Notch, NF-κB, JAK/STAT, TGF-β, PI3K/AKT, PPAR pathway, and their crosstalk. We focus on the role of CSCs in various therapeutic outcomes and resistance, including how the treatments affect the content of CSCs and the alteration of related molecules, CSCs-mediated therapeutic resistance, and the clinical value of targeting CSCs in patients with refractory, progressed or advanced tumors. In summary, CSCs affect therapeutic efficacy, and the treatment method of targeting CSCs is still difficult to determine. Clarifying regulatory mechanisms and targeting biomarkers of CSCs is currently the mainstream idea.
Is depression a global brain disorder with topographic dynamic reorganization?
Authors: Northoff Georg , Hirjak Dusan
Published: July 2024

Major depressive disorder (MDD) is characterized by a multitude of psychopathological symptoms including affective, cognitive, perceptual, sensorimotor, and social. The neuronal mechanisms underlying such co-occurrence of psychopathological symptoms remain yet unclear. Rather than linking and localizing single psychopathological symptoms to specific regions or networks, this perspective proposes a more global and dynamic topographic approach. We first review recent findings on global brain activity changes during both rest and task states in MDD showing topographic reorganization with a shift from unimodal to transmodal regions. Next, we single out two candidate mechanisms that may underlie and mediate such abnormal uni-/transmodal topography, namely dynamic shifts from shorter to longer timescales and abnormalities in the excitation-inhibition balance. Finally, we show how such topographic shift from unimodal to transmodal regions relates to the various psychopathological symptoms in MDD including their co-occurrence. This amounts to what we describe as ‘Topographic dynamic reorganization’ which extends our earlier ‘Resting state hypothesis of depression’ and complements other models of MDD.
Hematopoietic stem cell transplantation for DLBCL: a report from the European Society for Blood and Marrow Transplantation on more than 40,000 patients over 32 years
Authors: Berning Philipp , Fekom Mathilde , Ngoya Maud , Goldstone Anthony H. , Dreger Peter , Montoto Silvia , Finel Hervé , Shumilov Evgenii , Chevallier Patrice , Blaise Didier , Strüssmann Tim , Carpenter Ben , Forcade Edouard , Castilla-Llorente Cristina , Trneny Marek , Ghesquieres Hervé , Capria Saveria , Thieblemont Catherine , Blau Igor Wolfgang , Meijer Ellen , Broers Annoek E. C. , Huynh Anne , Caillot Denis , Rösler Wolf , Nguyen Quoc Stephanie , Bittenbring Jörg , Nagler Arnon , Galimard Jacques-Emmanuel , Glass Bertram , Sureda Anna , Schmitz Norbert
Published: July 2024

Autologous(auto-) and allogeneic(allo-) hematopoietic stem cell transplantation (HSCT) are key treatments for relapsed/refractory diffuse large B-cell lymphoma (DLBCL), although their roles are challenged by CAR-T-cells and other immunotherapies. We examined the transplantation trends and outcomes for DLBCL patients undergoing auto-/allo-HSCT between 1990 and 2021 reported to EBMT. Over this period, 41,148 patients underwent auto-HSCT, peaking at 1911 cases in 2016, while allo-HSCT saw a maximum of 294 cases in 2018. The recent decline in transplants corresponds to increased CAR-T treatments (1117 cases in 2021). Median age for auto-HSCT rose from 42 (1990–1994) to 58 years (2015–2021), with peripheral blood becoming the primary stem cell source post-1994. Allo-HSCT median age increased from 36 (1990–1994) to 54 (2015–2021) years, with mobilized blood as the primary source post-1998 and reduced intensity conditioning post-2000. Unrelated and mismatched allo-HSCT accounted for 50% and 19% of allo-HSCT in 2015–2021. Three-year overall survival (OS) after auto-HSCT improved from 56% (1990–1994) to 70% (2015–2021), p < 0.001, with a decrease in relapse incidence (RI) from 49% to 38%, while non-relapse mortality (NRM) remained unchanged (4%). After allo-HSCT, 3-year-OS increased from 33% (1990–1999) to 46% (2015–2021) (p < 0.001); 3-year RI remained at 39% and 1-year-NRM decreased to 19% (p < 0.001). Our data reflect advancements over 32 years and >40,000 transplants, providing insights for evaluating emerging DLBCL therapies.