bluuebunny/crossref_metadata_2025_split huggingface dataset:
Predictive models-assisted diagnosis of AIDS-associated Pneumocystis jirovecii pneumonia in the emergency room, based on clinical, laboratory, and radiological data
Authors: Chagas Oscar José , Gonçalves Fabio Augusto Rodrigues , Nagatomo Priscila Paiva , Buccheri Renata , Pereira-Chioccola Vera Lucia , Del Negro Gilda Maria Barbaro , Benard Gil 
Published: May 2024

AbstractWe assessed predictive models (PMs) for diagnosing Pneumocystis jirovecii pneumonia (PCP) in AIDS patients seen in the emergency room (ER), aiming to guide empirical treatment decisions. Data from suspected PCP cases among AIDS patients were gathered prospectively at a reference hospital's ER, with diagnoses later confirmed through sputum PCR analysis. We compared clinical, laboratory, and radiological data between PCP and non-PCP groups, using the Boruta algorithm to confirm significant differences. We evaluated ten PMs tailored for various ERs resource levels to diagnose PCP. Four scenarios were created, two based on X-ray findings (diffuse interstitial infiltrate) and two on CT scans (“ground-glass”), incorporating mandatory variables: lactate dehydrogenase, O2sat, C-reactive protein, respiratory rate (> 24 bpm), and dry cough. We also assessed HIV viral load and CD4 cell count. Among the 86 patients in the study, each model considered either 6 or 8 parameters, depending on the scenario. Many models performed well, with accuracy, precision, recall, and AUC scores > 0.8. Notably, nearest neighbor and naïve Bayes excelled (scores > 0.9) in specific scenarios. Surprisingly, HIV viral load and CD4 cell count did not improve model performance. In conclusion, ER-based PMs using readily available data can significantly aid PCP treatment decisions in AIDS patients.
Single-cell classification based on label-free high-resolution optical data of cell adhesion kinetics
Authors: Kovacs Kinga Dora , Beres Balint , Kanyo Nicolett , Szabó Balint , Peter Beatrix , Bősze Szilvia , Szekacs Inna , Horvath Robert 
Published: May 2024

AbstractSelecting and isolating various cell types is a critical procedure in many applications, including immune therapy, regenerative medicine, and cancer research. Usually, these selection processes involve some labeling or another invasive step potentially affecting cellular functionality or damaging the cell. In the current proof of principle study, we first introduce an optical biosensor-based method capable of classification between healthy and numerous cancerous cell types in a label-free setup. We present high classification accuracy based on the monitored single-cell adhesion kinetic signals. We developed a high-throughput data processing pipeline to build a benchmark database of ~ 4500 single-cell adhesion measurements of a normal preosteoblast (MC3T3-E1) and various cancer (HeLa, LCLC-103H, MDA-MB-231, MCF-7) cell types. Several datasets were used with different cell-type selections to test the performance of deep learning-based classification models, reaching above 70–80% depending on the classification task. Beyond testing these models, we aimed to draw interpretable biological insights from their results; thus, we applied a deep neural network visualization method (grad-CAM) to reveal the basis on which these complex models made their decisions. Our proof-of-concept work demonstrated the success of a deep neural network using merely label-free adhesion kinetic data to classify single mammalian cells into different cell types. We propose our method for label-free single-cell profiling and in vitro cancer research involving adhesion. The employed label-free measurement is noninvasive and does not affect cellular functionality. Therefore, it could also be adapted for applications where the selected cells need further processing, such as immune therapy and regenerative medicine.
Multi-step forecasting of dissolved oxygen in River Ganga based on CEEMDAN-AdaBoost-BiLSTM-LSTM model
Authors: Pant Neha , Toshniwal Durga , Gurjar Bhola Ram 
Published: May 2024

AbstractAccurate prediction of Dissolved Oxygen (DO) is an integral part of water resource management. This study proposes a novel approach combining Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) with AdaBoost and deep learning for multi-step forecasting of DO. CEEMDAN generates Intrinsic Mode Functions (IMFs) with different frequencies, capturing non-linear and non-stationary characteristics of the data. The high-frequency and medium-frequency IMFs, characterized by complex patterns and frequent changes over time, are predicted using Adaboost with Bidirectional Long Short-Term Memory (BiLSTM) as the base estimator. The low-frequency IMFs, characterized by relatively simple patterns, are predicted using standalone Long Short-Term Memory (LSTM). The proposed CEEMDAN-AdaBoost-BiLSTM-LSTM model is tested on data from ten stations of river Ganga. We compare the results with six models without decomposition and four models utilizing decomposition. Experimental results show that using a tailored prediction technique based on each IMF’s distinctive features leads to more accurate forecasts. CEEMDAN-AdaBoost-BiLSTM-LSTM outperforms CEEMDAN-BiLSTM with an average improvement of 25.458% for RMSE and 37.390% for MAE. Compared with CEEMDAN-AdaBoost-BiLSTM, an average improvement of 20.779% for RMSE and 28.921% for MAE is observed. Diebold-Mariano test and t-test suggest a statistically significant difference in performance between the proposed and compared models.
The effect of a suspension training on physical fitness, lower extremity biomechanical factors, and occupational health in Navy personnel: a randomized controlled trial
Authors: Mozafaripour Esmaeil , Shirvani Hossein , Alikhani Sobhan , Bayattork Mohammad , Yaghoubitajani Zohreh , Andersen Lars Louis 
Published: May 2024

AbstractOptimal physical fitness is essential for military personnel to effectively meet their rigorous physical demands. This study aimed to investigate the effectiveness of a suspension training program on physical fitness, biomechanical risk factors for lower extremity injury, mental health, and work-related factors in Navy personnel. A total of 50 young men participated in a randomized controlled trial. The participants were randomly assigned to two groups (n = 25): the intervention group and the control group. The intervention group performed an eight-week suspension training session three times per week, while the control group maintained their daily duties. The primary outcome was physical performance. The secondary outcomes were determined biomechanical risk factors for lower extremity injuries, mental health, and work-related factors. The data were analyzed using the analysis of covariance (ANCOVA). Compared with the control group, the intervention group showed significant improvements in physical performance, biomechanical risk for lower extremity injuries, and work-related factors from baseline to follow-up (p ≤ 0.05). However, there was no improvement in mental health. Based on these findings, suspension training positively impacted physical fitness, reduced injury risk, and enhanced the work-related factors of Navy personnel. This study provides new insights for various related experts and military coaches because it is an easy-to-use and feasible method with minimal facilities.
Transcutaneous auricular vagus nerve stimulation enhances short-latency afferent inhibition via central cholinergic system activation
Authors: Horinouchi Takayuki , Nezu Tomohisa , Saita Kazuya , Date Shota , Kurumadani Hiroshi , Maruyama Hirofumi , Kirimoto Hikari 
Published: May 2024

AbstractThe present study examined the effects of transcutaneous auricular vagus nerve stimulation (taVNS) on short-latency afferent inhibition (SAI), as indirect biomarker of cholinergic system activation. 24 healthy adults underwent intermittent taVNS (30 s on/30 s off, 30 min) or continuous taVNS at a frequency of 25 Hz (15 min) along with earlobe temporary stimulation (15 min or 30 min) were performed in random order. The efficiency with which the motor evoked potential from the abductor pollicis brevis muscle by transcranial magnetic stimulation was attenuated by the preceding median nerve conditioning stimulus was compared before taVNS, immediately after taVNS, and 15 min after taVNS. Continuous taVNS significantly increased SAI at 15 min post-stimulation compared to baseline. A positive correlation (Pearson coefficient = 0.563, p = 0.004) was observed between baseline SAI and changes after continuous taVNS. These results suggest that 15 min of continuous taVNS increases the activity of the cholinergic nervous system, as evidenced by the increase in SAI. In particular, the increase after taVNS was more pronounced in those with lower initial SAI. This study provides fundamental insight into the clinical potential of taVNS for cholinergic dysfunction.
Sustainable coatings for green solar photovoltaic cells: performance and environmental impact of recyclable biomass digestate polymers
Authors: Alhodaib Aiyeshah , Yahya Zeinebou , Khan Osama , Equbal Azhar , Equbal Md Shaquib , Parvez Mohd , Kumar Yadav Ashok , Idrisi M. Javed 
Published: May 2024

AbstractThe underutilization of digestate-derived polymers presents a pressing environmental concern as these valuable materials, derived from anaerobic digestion processes, remain largely unused, contributing to pollution and environmental degradation when left unutilized. This study explores the recovery and utilization of biodegradable polymers from biomass anaerobic digestate to enhance the performance of solar photovoltaic (PV) cells while promoting environmental sustainability. The anaerobic digestion process generates organic residues rich in biodegradable materials, often considered waste. However, this research investigates the potential of repurposing these materials by recovering and transforming them into high-quality coatings or encapsulants for PV cells. The recovered biodegradable polymers not only improve the efficiency and lifespan of PV cells but also align with sustainability objectives by reducing the carbon footprint associated with PV cell production and mitigating environmental harm. The study involves a comprehensive experimental design, varying coating thickness, direct normal irradiance (DNI) (A), dry bulb temperature (DBT) (B), and relative humidity (C) levels to analyze how different types of recovered biodegradable polymers interact with diverse environmental conditions. Optimization showed that better result was achieved at A = 8 W/m2, B = 40 °C and C = 70% for both the coated material studied. Comparative study showed that for enhanced cell efficiency and cost effectiveness, EcoPolyBlend coated material is more suited however for improving durability and reducing environmental impact NanoBioCelluSynth coated material is preferable choice. Results show that these materials offer promising improvements in PV cell performance and significantly lower environmental impact, providing a sustainable solution for renewable energy production. This research contributes to advancing both the utilization of biomass waste and the development of eco-friendly PV cell technologies, with implications for a more sustainable and greener energy future. This study underscores the pivotal role of exploring anaerobic digestate-derived polymers in advancing the sustainability and performance of solar photovoltaic cells, addressing critical environmental and energy challenges of our time.Please confirm if the author names are presented accurately and in the correct sequence (given name, middle name/initial, family name). Author 7 Given name: [Ashok] Last name [Kumar Yadav]. Also, kindly confirm the details in the metadata are correct.correct
AI-based disease category prediction model using symptoms from low-resource Ethiopian language: Afaan Oromo text
Authors: Dinsa Etana Fikadu , Das Mrinal , Abebe Teklu Urgessa 
Published: May 2024

AbstractAutomated disease diagnosis and prediction, powered by AI, play a crucial role in enabling medical professionals to deliver effective care to patients. While such predictive tools have been extensively explored in resource-rich languages like English, this manuscript focuses on predicting disease categories automatically from symptoms documented in the Afaan Oromo language, employing various classification algorithms. This study encompasses machine learning techniques such as support vector machines, random forests, logistic regression, and Naïve Bayes, as well as deep learning approaches including LSTM, GRU, and Bi-LSTM. Due to the unavailability of a standard corpus, we prepared three data sets with different numbers of patient symptoms arranged into 10 categories. The two feature representations, TF-IDF and word embedding, were employed. The performance of the proposed methodology has been evaluated using accuracy, recall, precision, and F1 score. The experimental results show that, among machine learning models, the SVM model using TF-IDF had the highest accuracy and F1 score of 94.7%, while the LSTM model using word2vec embedding showed an accuracy rate of 95.7% and F1 score of 96.0% from deep learning models. To enhance the optimal performance of each model, several hyper-parameter tuning settings were used. This study shows that the LSTM model verifies to be the best of all the other models over the entire dataset.
Receptor-mediated cargo hitchhiking on bulk autophagy
Authors: Takeda Eigo , Isoda Takahiro , Hosokawa Sachiko , Oikawa Yu , Hotta-Ren Shukun , May Alexander I , Ohsumi Yoshinori 
Published: May 2024

AbstractWhile the molecular mechanism of autophagy is well studied, the cargoes delivered by autophagy remain incompletely characterized. To examine the selectivity of autophagy cargo, we conducted proteomics on isolated yeast autophagic bodies, which are intermediate structures in the autophagy process. We identify a protein, Hab1, that is highly preferentially delivered to vacuoles. The N-terminal 42 amino acid region of Hab1 contains an amphipathic helix and an Atg8-family interacting motif, both of which are necessary and sufficient for the preferential delivery of Hab1 by autophagy. We find that fusion of this region with a cytosolic protein results in preferential delivery of this protein to the vacuole. Furthermore, attachment of this region to an organelle allows for autophagic delivery in a manner independent of canonical autophagy receptor or scaffold proteins. We propose a novel mode of selective autophagy in which a receptor, in this case Hab1, binds directly to forming isolation membranes during bulk autophagy.
Early-stage lung cancer is driven by a transitional cell state dependent on a KRAS-ITGA3-SRC axis
Authors: Moye Aaron L , Dost Antonella FM , Ietswaart Robert , Sengupta Shreoshi , Ya VanNashlee , Aluya Chrystal , Fahey Caroline G , Louie Sharon M , Paschini Margherita , Kim Carla F 
Published: May 2024

AbstractGlycine-12 mutations in the GTPase KRAS (KRASG12) are an initiating event for development of lung adenocarcinoma (LUAD). KRASG12 mutations promote cell-intrinsic rewiring of alveolar type-II progenitor (AT2) cells, but to what extent such changes interplay with lung homeostasis and cell fate pathways is unclear. Here, we generated single-cell RNA-seq (scRNA-seq) profiles from AT2-mesenchyme organoid co-cultures, mice, and stage-IA LUAD patients, identifying conserved regulators of AT2 transcriptional dynamics and defining the impact of KRASG12D mutation with temporal resolution. In AT2WT organoids, we found a transient injury/plasticity state preceding AT2 self-renewal and AT1 differentiation. Early-stage AT2KRAS cells exhibited perturbed gene expression dynamics, most notably retention of the injury/plasticity state. The injury state in AT2KRAS cells of patients, mice, and organoids was distinguishable from AT2WT states via altered receptor expression, including co-expression of ITGA3 and SRC. The combination of clinically relevant KRASG12D and SRC inhibitors impaired AT2KRAS organoid growth. Together, our data show that an injury/plasticity state essential for lung repair is co-opted during AT2 self-renewal and LUAD initiation, suggesting that early-stage LUAD may be susceptible to interventions that target specifically the oncogenic nature of this cell state.
Uncovering the dynamics and consequences of RNA isoform changes during neuronal differentiation
Authors: Ulicevic Jelena , Shao Zhihao , Jasnovidova Olga , Bressin Annkatrin , Gajos Martyna , Ng Alex HM , Annaldasula Siddharth , Meierhofer David , Church George M , Busskamp Volker , Mayer Andreas 
Published: May 2024

AbstractStatic gene expression programs have been extensively characterized in stem cells and mature human cells. However, the dynamics of RNA isoform changes upon cell-state-transitions during cell differentiation, the determinants and functional consequences have largely remained unclear. Here, we established an improved model for human neurogenesis in vitro that is amenable for systems-wide analyses of gene expression. Our multi-omics analysis reveals that the pronounced alterations in cell morphology correlate strongly with widespread changes in RNA isoform expression. Our approach identifies thousands of new RNA isoforms that are expressed at distinct differentiation stages. RNA isoforms mainly arise from exon skipping and the alternative usage of transcription start and polyadenylation sites during human neurogenesis. The transcript isoform changes can remodel the identity and functions of protein isoforms. Finally, our study identifies a set of RNA binding proteins as a potential determinant of differentiation stage-specific global isoform changes. This work supports the view of regulated isoform changes that underlie state-transitions during neurogenesis.
The Accompanying Effect in Responses to Auditory Perturbations: Unconscious Vocal Adjustments to Unperturbed Parameters
Authors: Ning Li-Hsin , Hui Tak-Cheung 
Published: May 2024

Purpose:
The present study examined whether participants respond to unperturbed parameters while experiencing specific perturbations in auditory feedback. For instance, we aim to determine if speakers adjust voice loudness when only pitch is artificially altered in auditory feedback. This phenomenon is referred to as the “accompanying effect” in the present study.

Method:
Thirty native Mandarin speakers were asked to sustain the vowel /ɛ/ for 3 s while their auditory feedback underwent single shifts in one of the three distinct ways: pitch shift (±100 cents; coded as PT), loudness shift (±6 dB; coded as LD), or first formant (F1) shift (±100 Hz; coded as FM). Participants were instructed to ignore the perturbations in their auditory feedback. Response types were categorized based on pitch, loudness, and F1 for each individual trial, such as Popp_Lopp_Fopp indicating opposing responses in all three domains.

Results:
The accompanying effect appeared 93% of the time. Bayesian Poisson regression models indicate that opposing responses in all three domains (Popp_Lopp_Fopp) were the most prevalent response type across the conditions (PT, LD, and FM). The more frequently used response types exhibited opposing responses and significantly larger response curves than the less frequently used response types. Following responses became more prevalent only when the perturbed stimuli were perceived as voices from someone else (external references), particularly in the FM condition. In terms of isotropy, loudness and F1 tended to change in the same direction rather than loudness and pitch.

Conclusion:
The presence of the accompanying effect suggests that the motor systems responsible for regulating pitch, loudness, and formants are not entirely independent but rather interconnected to some degree.
Single-atom catalysis in space
Authors: Pareras G. , Cabedo V. , McCoustra M. , Rimola A. 
Published: May 2024

Context. The presence of grains is key to the synthesis of molecules in the interstellar medium that cannot form in the gas phase due to its low density and temperature conditions. In these reactions, the role of the grains is to enhance the encounter rate of the reactive species on their surfaces and to dissipate the energy excess of largely exothermic reactions, but less is known about their role as chemical catalysts; namely, bodies that provide low activation energy pathways with enhanced reaction rates. Different refractory materials with catalytic properties, such as those containing space-abundant d-block transition metals like iron (Fe), are present in astrophysical environments.
Aims. Here, we report for first time mechanistic insights into the Fischer-Tropsch-type (FTT) synthesis of ethanol (CH3CH2OH), through ketene (CH2CO) and acetaldehyde (CH3CHO) intermediates, and methane (CH4) via a chain growing mechanism using a single-Fe atom supported on silica (SiO2) surfaces as a heterogeneous astrocatalyst.
Methods. Quantum chemical simulations based on extended periodic surfaces were carried out to characterize the potential energy surfaces of the FTT chain growing mechanism. Calculations of the binding energies of reaction intermediates and products and Rice–Ramsperger–Kassel–Marcus kinetic calculations were performed to evaluate catalytic efficiencies and determine the feasibility of the reactions in different astrophysical environments.
Results. Mechanistic studies demonstrate that the FTT chain growing mechanism enters into direct competition with FTT methanol formation, since formation of the CH2 chain growth initiator is feasible. The coupling of the CH2 with CO (forming ketene) and subsequent H2 additions yield acetaldehyde and finally ethanol, while direct H2 addition to CH2 produces methane. Thermodynamically, both processes are largely exergonic, but they present energy barriers that require external energy inputs to be overcome. Kinetic calculations demonstrate the strong temperature dependency of the FTT processes as tunneling does not dominate.
Conclusions. The results could explain the presence of CH3CH2OH and CH4 in diverse astrophysical regions where current models fail to reproduce their observational quantities. The evidence that the chain growing mechanism is operating opens a new reactivity paradigm toward the formation of complex organic molecules, which is constrained by the temperature-dependent behaviour of the FTT reactions and by making their energy features a crucial aspect.
Positive und negative (Neben)Effekte bei
Osteoporose-Sequenztherapie
Authors: Obermayer-Pietsch Barbara , Fößl Ines , Thomasius Friederike 
Published: May 2024

ZusammenfassungIndikationen und Abläufe rund um pharmakologischen Optionen für die
Osteoporosetherapie wurden in den vergangenen Jahren neu beleuchtet. Dazu zählen
neben den bekannten therapeutischen Effekten auf Knochenstoffwechsel, -struktur
und Frakturrisiko auch teils weniger bekannte positive (Neben-)Effekte und
einige, wenn auch seltene, gravierende Nebenwirkungen dieser Medikamente. Als
positive (Neben-)Effekte wurden bei Bisphosphonaten u. a. die Reduktion von
kardiovaskulären Ereignissen, die verminderte Inzidenz von Karzinomen und eine
insgesamt verminderte Mortalität beschrieben, es gab bei suffizienter
Basistherapie aber u. a. auch reduzierte Raten für COVID-Infektionen und
-Hospitalisierungen. Antiresorptiva können seltene, aber erhebliche
Nebenwirkungen bei Betroffenen bewirken, u. a. sind es atypische
Schenkelhalsbrüche (AFF, „atypical femoral fractures“), die in 0.02% der Fälle
bei langdauernder Behandlung auftreten. Vielbeachtet sind Kieferosteonekrosen
(MRONJ, „Medication-Related OsteoNecrosis of the Jaw“), die vermehrt bei hohen
und häufigen Dosen, etwa bei onkologischer Indikation auftreten und bei
Osteoporose-Indikation in 0.001%-0.01% der Betroffenen mit
Osteoporosetherapie-Schemata gefunden werden. Zu Augen-assoziierten Symptomen
(BROSE, „Bisphosphonat-Related Ocular Side Effects”) sind bisher etwa zwei
Dutzend Fälle weltweit publiziert worden. In dieser Übersichtsarbeit werden
wichtige Daten und Mechanismen zu Nebeneffekten der Osteoporose-Therapeutika
auch bei speziellen Personengruppen zusammengefasst und neue Entwicklungen im
Rahmen einer Osteoporose-Sequenztherapie sowie Vorsorgemaßnahmen
beschrieben.