bluuebunny/crossref_metadata_2025_split huggingface dataset:
KIF11 serves as a cell cycle mediator in childhood acute lymphoblastic leukemia
Authors: Zhu Liwen , Chen Chuqin , Kang Meiyun , Ma Xiaopeng , Sun Xiaoyan , Xue Yao , Fang Yongjun 
Published: September 2023

Abstract
Objective
To identify key gene in childhood acute lymphoblastic leukemia (ALL) through weighted gene co-expression network analysis (WGCNA), and their enriched biological functions and signaling pathways.

Methods
Array data of the GSE73578 dataset, involving 46 childhood ALL samples, were acquired from the Gene Expression Omnibus (GEO) database. Hub modules associated with childhood ALL were screened out by WGCNA. Enriched biological functions and signaling pathways were then identified by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Hub genes were selected by overlapping those between down-regulated genes in GSE73578, GSE4698 and the hub module. Guilt by association (GBA) was adopted to verify the function of the identified KIF11 gene and to predict its target genes. Regulatory effects of KIF11 on the proliferation and cell cycle progression of ALL in vitro were determined by cytological experiments.

Results
WGCNA showed that the yellow module was the most relevant to childhood ALL treatment, containing 698 genes that were enriched in cell division, mitotic nuclear division, DNA replication and DNA repair, cell cycle, DNA replication and the P53 signaling pathway. The KIF11 gene was screened out and predicted as a cell cycle mediator in childhood ALL. Knockdown of KIF11 in ALL cells inhibited cell proliferation and arrested cell cycle progression in G2/M phase.

Conclusions
The KIF11 gene is critical in the treatment process of childhood ALL, which is a promising therapeutic target for childhood ALL.
Congenital anomalies of the kidney and urinary tract: antenatal diagnosis, management and counselling of families
Authors: Walker Emma Y. X. , Winyard Paul , Marlais Matko 
Published: September 2023

AbstractCongenital anomalies of the kidney and urinary tract are collectively one of the most commonly diagnosed antenatal conditions. Clinicians have several tools available to diagnose anomalies, including imaging, biomarkers, family history and genetic studies. In certain cases, antenatal interventions such as vesico-amniotic shunting may be considered to improve postnatal outcomes.Congenital kidney anomalies detected antenatally can vary in clinical significance from almost no impact postnatally to significant morbidity and perinatal mortality. Prognosis broadly depends on kidney size, structure and amount of amniotic fluid, alongside genetics and family history, and progression on subsequent scans. It is important to counsel parents appropriately using a parent-focused and personalised approach. The use of a multidisciplinary team should always be considered.
Strategies for difficult times: physiological and morphological responses to drought stress in seedlings of Central European tree species
Authors: Niemczyk Marzena , Thomas Barb R. , Jastrzębowski Szymon 
Published: September 2023

Abstract
Key message
Picea abies and Pinus sylvestris seedlings conserve soil water and are more sensitive to drought showing photoinhibition even under moderate stress, while Quercus robur and Fagus sylvatica seedlings have higher soil water uptake, they show photoinhibition only under severe drought.

Abstract
Drought is an important factor in ecological change and species distribution shifts. We conducted a greenhouse experiment with seedlings of four Central European tree species: Pinus sylvestris (PS), Picea abies (PA), Fagus sylvatica (FS), and Quercus robur (QR) to investigate their response to drought. We monitored maximum quantum yield of photosystem II (Fv/Fm) during a 60-day drought treatment and measured above- and below-ground characteristics as morphophysiological responses to drought stress. Due to the fast, juvenile growth of the deciduous species (FS and QR), they had higher soil water uptake and suffered more quickly from severe drought than conifers (PS and PA). The deciduous species maintained a higher Fv/Fm, until volumetric water content (VWC) was very low (< 5%), oscillating within a narrow safety margin. Both conifers PA and PS conserved soil water; photoinhibition in these species occurred at VWC of 14.5% and 5.5%, respectively. There were no differences in height between drought-stressed and irrigated seedlings, while drought reduced all root characteristics of the deciduous seedlings. Our study revealed trade-offs between different water management strategies, growth rate, and photoinhibition during the juvenile growth stage of our focal species. For climate change adaptation, anisohydric deciduous tree species seem to be more suitable. However, PS, with its water-conserving management and low photoinhibition threshold, holds promise for successful regeneration on drought-prone sites. Since species selection is critical for forest sustainability, our study contributes to the broader discussion of tree species' drought resistance during the vulnerable juvenile phase in the face of climate change.
Expert design thinking workshops to analyze users’ perceived applicability of NUTRI-ONCOCARE algorithm to prevent and treat malnutrition in cancer patients under routine clinical practice conditions in Spain: the ALLIANCE study
Authors: Grande Enrique , Moreno Fernando , Trigo José , Capdevila Jaume , Abilés Jimena , Sirvent Mariola , Garrido-Siles Margarita , Olveira Gabriel , Ocón Julia , Soto Maria Luisa Fernández 
Published: September 2023

Abstract
Purpose
NUTRI-ONCOCARE algorithm has been developed to identify and treat patients with solid tumors who are at risk of malnutrition. The present study is aimed at analyzing users’ opinion about this new tool and at assessing whether it is perceived as useful to achieve the behavioral change required for a successful integration of nutritional assessment into routine cancer care.

Methods
Design thinking Double Diamond process was applied. A multidisciplinary team composed of ten potential end-users (four oncologists, three endocrinologists, one nutritionist, and two hospital pharmacists) participated in three different workshops aiming to analyze the different tasks included within the NUTRI-ONCOCARE algorithm.

Results
Users agreed on the need to perform nutritional assessment around cancer diagnosis and through the course of the disease using standardized tools included in hospital nutritional protocols and involving healthcare professionals with nutrition expertise. Nutritional evaluation and intervention should be individual and comprehensive, considering not only nutritional parameters but also patients’ functional status. According to participants’ opinion, the implementation of nutritional screening in routine clinical practice is limited by the lack of time and staff to conduct nutritional assessments, the low level of nutrition expert participation, and the poor support provided by hospital managers, which are often unaware of nutrition’s impact in cancer care.

Conclusions
Experts recognized the importance of considering nutritional status in cancer patients and identified the opportunity provided by the NUTRI-ONCOCARE algorithm for this purpose, as it meets main requirements for being used routinely in clinical practice.
Neural nets for sustainability conversations: modeling discussion disciplines and their impacts
Authors: Pugh Katrina , Musavi Mohamad , Johnson Teresa , Burke Christopher , Yoeli Erez , Currie Emily , Pugh Benjamin 
Published: September 2023

AbstractWe live in the age polarization, where conversations on matters of sustainability more often produce acrimony or stalemate than productive action. Better understanding conversation features and their impacts may lead to better innovation, solution-design, and ongoing collaboration. We describe a study to test alternate machine learning models for classifying six “discussion disciplines”, which are conversation features associated with rhetorical intent. The model providing the best outcome used the Bi-directional Encoder Representations from Transformers (BERT) layered with a Residual Network (ResNet). The training data were 1135 utterances from Maine aquaculture town hall-like meetings and similar conversations, which had been hand-coded for the discussion disciplines. In addition, we generated 300 phrases corresponding to three conversation outcomes: Intent-to-Act, Options-Generation, and Relationship-Building. We then used the trained model and information retrieval to classify a large corpus of 591 open-source transcripts, containing over 21,000 utterances. A binary logistic regression analysis showed that two discussion disciplines, “Inclusion” and “Courtesy,” had positive, statistically significant, impacts on Intent-to-act: a 10 percentage point increase in the share of the Inclusion or Courtesy yielded a 45% or 34% increase, respectively, in the likelihood of Intent-to-Act. This study shows the applicability of neural networks in modeling conversations and identifying the dialog acts that can provide measurable and predictable impact on conversation outcomes. Conversational intelligence can support a variety of human interactions, such as town halls, policy-deliberations, private–public partnerships, and sustainability teamwork.
Stability of Hardy Littlewood Sobolev inequality under bubbling
Authors: Aryan Shrey 
Published: September 2023

AbstractIn this note we will generalize the results deduced in Figalli and Glaudo (Arch Ration Mech Anal 237(1):201–258, 2020) and Deng et al. (Sharp quantitative estimates of Struwe’s Decomposition. Preprint http://arxiv.org/abs/2103.15360, 2021) to fractional Sobolev spaces. In particular we will show that for $$s\in (0,1)$$

s
∈
(
0
,
1
)

, $$n>2s$$

n
>
2
s

and $$\nu \in \mathbb {N}$$

ν
∈
N

there exists constants $$\delta = \delta (n,s,\nu )>0$$

δ
=
δ
(
n
,
s
,
ν
)
>
0

and $$C=C(n,s,\nu )>0$$

C
=
C
(
n
,
s
,
ν
)
>
0

such that for any function $$u\in \dot{H}^s(\mathbb {R}^n)$$

u
∈

H
˙

s

(

R

n

)

satisfying,
$$\begin{aligned} \left\| u-\sum _{i=1}^{\nu } \tilde{U}_{i}\right\| _{\dot{H}^s} \le \delta \end{aligned}$$

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-

∑

i
=
1

ν

U
~

i

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˙

s

≤
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where $$\tilde{U}_{1}, \tilde{U}_{2},\ldots \tilde{U}_{\nu }$$

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~

1

,

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2

,
…

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~

ν

is a $$\delta $$
δ
-interacting family of Talenti bubbles, there exists a family of Talenti bubbles $$U_{1}, U_{2},\ldots U_{\nu }$$

U
1

,

U
2

,
…

U
ν

such that $$\begin{aligned} \left\| u-\sum _{i=1}^{\nu } U_{i}\right\| _{\dot{H}^s} \le C\left\{ \begin{array}{ll} \Gamma &{} \text{ if } 2s< n < 6s,\\ \Gamma |\log \Gamma |^{\frac{1}{2}} &{} \text{ if } n=6s, \\ \Gamma ^{\frac{p}{2}} &{} \text{ if } n > 6s \end{array}\right. \end{aligned}$$

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∑

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if

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=
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,

Γ

p
2

if

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>
6
s

for $$\Gamma =\left\| \Delta u+u|u|^{p-1}\right\| _{H^{-s}}$$

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=

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+

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|
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|

p
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and $$p=2^*-1=\frac{n+2s}{n-2s}.$$

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=

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∗

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=

n
+
2
s

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-
2
s

.
Energy load forecasting: one-step ahead hybrid model utilizing ensembling
Authors: Tsalikidis Nikos , Mystakidis Aristeidis , Tjortjis Christos , Koukaras Paraskevas , Ioannidis Dimosthenis 
Published: September 2023

AbstractIn the light of the adverse effects of climate change, data analysis and Machine Learning (ML) techniques can provide accurate forecasts, which enable efficient scheduling and operation of energy usage. Especially in the built environment, Energy Load Forecasting (ELF) enables Distribution System Operators or Aggregators to accurately predict the energy demand and generation trade-offs. This paper focuses on developing and comparing predictive algorithms based on historical data from a near Zero Energy Building. This involves energy load, as well as temperature data, which are used to develop and evaluate various base ML algorithms and methodologies, including Artificial Neural Networks and Decision-trees, as well as their combination. Each algorithm is fine-tuned and tested, accounting for the unique data characteristics, such as the presence of photovoltaics, in order to produce a robust approach for One-Step-Ahead ELF. To this end, a novel hybrid model utilizing ensemble methods was developed. It combines multiple base ML algorithms the outputs of which are utilized to train a meta-model voting regressor. This hybrid model acts as a normalizer for any new data input. An experimental comparison of the model against unseen data and other ensemble approaches, showed promising forecasting results (mean absolute percentage error = 5.39%), particularly compared to the base algorithms.
Explanation Paradigms Leveraging Analytic Intuition (ExPLAIn)
Authors: Jansen Nils , Nolte Gerrit , Steffen Bernhard 
Published: September 2023

AbstractIn this paper, we present the envisioned style and scope of the new topic “Explanation Paradigms Leveraging Analytic Intuition” (ExPLAIn) with the International Journal on Software Tools for Technology Transfer (STTT). Intention behind this new topic is to (1) explicitly address all aspects and issues that arise when trying to, if possible, reveal and then confirm hidden properties of black-box systems, or (2) to enforce vital properties by embedding them into appropriate system contexts. Machine-learned systems, such as Deep Neural Networks, are particularly challenging black-box systems, and there is a wealth of formal methods for analysis and verification waiting to be adapted and applied. The selection of papers of this first Special Section of ExPLAIn, most of which were co-authored by editorial board members, is an illustrative example of the style and scope envisioned: In addition to methodological papers on verification, explanation, and their scalability, case studies, tool papers, literature reviews, and position papers are also welcome.
Automatic music emotion classification model for movie soundtrack subtitling based on neuroscientific premises
Authors: Lucia-Mulas Maria Jose , Revuelta-Sanz Pablo , Ruiz-Mezcua Belen , Gonzalez-Carrasco Israel 
Published: September 2023

AbstractThe ability of music to induce emotions has been arousing a lot of interest in recent years, especially due to the boom in music streaming platforms and the use of automatic music recommenders. Music Emotion Recognition approaches are based on combining multiple audio features extracted from digital audio samples and different machine learning techniques. In these approaches, neuroscience results on musical emotion perception are not considered. The main goal of this research is to facilitate the automatic subtitling of music. The authors approached the problem of automatic musical emotion detection in movie soundtracks considering these characteristics and using scientific musical databases, which have become a reference in neuroscience research. In the experiments, the Constant-Q-Transform spectrograms, the ones that best represent the relationships between musical tones from the point of view of human perception, are combined with Convolutional Neural Networks. Results show an efficient emotion classification model for 2-second musical audio fragments representative of intense basic feelings of happiness, sadness, and fear. Those emotions are the most interesting to be identified in the case of movie music captioning. The quality metrics have demonstrated that the results of the different models differ significantly and show no homogeneity. Finally, these results pave the way for an accessible and automatic captioning of music, which could automatically identify the emotional intent of the different segments of the movie soundtrack.
Multi-directional Interaction Force Control with an Aerial Manipulator Under External Disturbances
Authors: Malczyk Grzegorz , Brunner Maximilian , Cuniato Eugenio , Tognon Marco , Siegwart Roland 
Published: September 2023

AbstractTo improve accuracy and robustness of interactive aerial robots, the knowledge of the forces acting on the platform is of uttermost importance. The robot should distinguish interaction forces from external disturbances in order to be compliant with the firsts and reject the seconds. This represents a challenge since disturbances might be of different nature (physical contact, aerodynamic, modeling errors) and be applied to different points of the robot. This work presents a new $$\hbox {extended Kalman filter (EKF)}$$

extended Kalman filter (EKF)

based estimator for both external disturbance and interaction forces. The estimator fuses information coming from the system’s dynamic model and it’s state with wrench measurements coming from a Force-Torque sensor. This allows for robust interaction control at the tool’s tip even in presence of external disturbance wrenches acting on the platform. We employ the filter estimates in a novel hybrid force/motion controller to perform force tracking not only along the tool direction, but from any platform’s orientation, without losing the stability of the pose controller. The proposed framework is extensively tested on an omnidirectional aerial manipulator (AM) performing push and slide operations and transitioning between different interaction surfaces, while subject to external disturbances. The experiments are done equipping the AM with two different tools: a rigid interaction stick and an actuated delta manipulator, showing the generality of the approach. Moreover, the estimation results are compared to a state-of-the-art momentum-based estimator, clearly showing the superiority of the EKF approach.
A physical neuroscience-themed escape room: Design, implementation, and students’ perceptions
Authors: Lim Iris 
Published: September 2023

AbstractTeaching soft skills like team dynamics and critical thinking in content-heavy higher education curriculum can be challenging. Employing educational escape rooms is a novel game-based learning strategy in various disciplines, including health sciences. Escape rooms provide the opportunity for a group to work together as they solve puzzles within a limited time. The skills harnessed and developed within the game by participants are parallel to these soft skills. The present study sought to design a neuroscience-themed physical escape room for the purpose of soft skills development and obtain feedback from undergraduate biomedical or health science students following the completion of the room. Likert-type scale statements in the feedback survey regarding the enjoyability, teamwork development and critical thinking within the game scored positively. Unsurprisingly, the recurring positive theme in the qualitative responses collected revolved around how participants found the activity fun and how it encouraged them to think critically. The present findings suggest that this escape room can in a brief period encourage students to employ communication and teamwork skills and naturally comes with an element of fun, making the experience memorable and engaging.
Chromosome evolution in Iberolacerta, a genus that deviates from the standard karyotype formula of Lacertidae
Authors: Naveira Horacio , Rojo Verónica , Gómez-Seoane Iván , Ferguson-Smith Malcolm A. , Pereira Jorge C. , Martínez-Lage Andrés 
Published: September 2023

AbstractThis paper describes the preparation of flow-sorted chromosome paints from the Iberian Rock lizard Iberolacerta monticola, exemplifying their subsequent use in cross-species comparisons of chromosome painting. We carried out comparative analyses of chromosome evolution in the congeneric species I. galani and I. bonnali, as well as in two other species of Lacertini (Lacerta schreiberi and Timon lepidus) whose sex chromosomes were also studied through comparative genomic hybridization. Most species of Lacertini possess a diplod number of 2n = 38, with 36 acrocentric macrochromosomes and 2 microchromosomes. However, the nine species included in the genus Iberolacerta do not possess microchromosomes. Furthermore, very conspicuous differences from the standard Lacertini karyotype were observed in the three Pyrenean species of this genus, which included several biarmed metacentrics and a Z1Z2W multiple sex-chromosome system. With the possible exception of L. schreiberi, all the species of the family Lacertidae described to date appear to share homologous Z chromosomes, which date back to the last common ancestor of the whole group. We provide conclusive evidence that L. schreiberi should no longer be considered an exception to this rule, and demonstrate that the loss of microchromosomes in Iberolacerta was produced by their fusion to a middle-sized chromosome. Furthermore, we show that the multiple sex-chromosome system of the Pyrenean species of Iberolacerta originated from the fusion of the ancestral W chromosome with one of the shortest autosomes, and provide additional evidence of the fast evolution of DNA sequences linked to the W chromosome in Lacertini.
Fluoride stress affects seed germination and seedling growth by altering the morpho-physiology of an African local bean variety
Authors: Chahine Sara , Melito Sara , Giannini Vittoria , Seddaiu Giovanna , Roggero Pier Paolo 
Published: September 2023

AbstractIncreased fluorine pollution represents a serious limitation for the productivity of important crops such as beans. The present study was conducted to detect antagonistic/synergistic ion mobility during seed germination in the presence of F contamination (KF and NaF). NaCl was used as a benchmark. The results showed that germination of Jesca, an African (Tanzania) bean variety, significantly dropped with high F levels (10% KF and 3% NaF). High F levels reduced Jesca growth and decreased root and shoot biomass (by 50% and 95% with KF and NaF, respectively). NaF 200 mg kg−1 had the most depressive effect on the seedling stage. Elevated F levels negatively affected seedling health, revealing toxicity symptoms such as chlorophyll degradation and low photosynthetic activities that degraded after a threshold level of 80 mg kg−1. In addition, an inhibitory effect of F on the mineral status of the seedlings, especially on the Ca content, was observed. An opposite trend of endogenous Ca response to NaCl stress was observed. Indeed, while endogenous Ca content increased with increasing NaCl concentration, it decreased when the F level increased. Therefore, tolerance to F at the germination and seedling stages might be used as a criterion for selecting F-tolerant bean varieties.
Wind dispersal differences between rotifer cryptic species: a proof of principle from a wind tunnel experiment
Authors: Arenas-Sánchez Cristina , Brendonck Luc , García-Roger Eduardo M. , Carmona María José , Ortells Raquel 
Published: September 2023

AbstractWind is expected to be one of the main vectors of passive dispersal for small zooplankters between discrete, unconnected habitats. However, little is known about the differences in the dispersal capacity of species in relation to their propagule traits. Here we assessed the effect of volume and weight of diapausing eggs and substrate granulometry on the dispersal departure propensity of two differently body-sized rotifer species belonging to the Brachionus plicatilis complex using a wind tunnel experiment. Diapausing eggs of the larger species were also larger but, counterintuitively, were lifted by the wind to a greater extent than those of the smaller one. Further, diapausing eggs on the finer substrate were more exposed to the wind than those over the coarser one, and therefore higher departure rates were observed in the former. Overall, results show that wind is a relevant dispersal vector for the rotifers of the B. plicatilis species complex, with egg morphological traits and substrate granulometry being important factors modulating their dispersal. This study is a proof of concept for the departure phase of dispersal. Further studies on transfer and settlement phases are needed to get a complete picture of the dispersal potential of these organisms.