bluuebunny/crossref_metadata_2025_split huggingface dataset:
Characterizing clinical progression in patients with musculoskeletal pain by pain severity and central sensitization-related symptoms
Authors: Shigetoh Hayato , Koga Masayuki , Tanaka Yoichi , Hirakawa Yoshiyuki , Morioka Shu 
Published: February 2024

AbstractCentral sensitization-related symptoms (CSS) are associated with the severity and progression of pain. The relationship between the severity of pain/CSS and clinical progresses remains unclear. This multicenter, collaborative, longitudinal study aimed to characterize the clinical outcomes of patients with musculoskeletal pain by classifying subgroups based on the severity of pain/CSS and examining changes in subgroups over time. We measured the pain intensity, CSS, catastrophic thinking, and body perception disturbance in 435 patients with musculoskeletal pain. Reevaluation of patients after one month included 166 patients for pain intensity outcome and 110 for both pain intensity and CSS outcome analysis. We classified the patients into four groups (mild pain/CSS, severe pain/mild CSS, severe pain/CSS, and mild pain/severe CSS groups) and performed multiple comparison analyses to reveal the differences between the CSS severity groups. Additionally, we performed the adjusted residual chi-square to identify the number of patients with pain improvement, group transition, changing pain, and CSS pattern groups at baseline. The most characteristic result was that the mild and severe CSS groups showed worsening pain. Moreover, many of the group transitions were to the same group, with a few transitioning to a group with mild pain/CSS. Our findings suggest that the severity and improvement of CSS influence pain prognosis.
Antiplatelet therapy prior to COVID-19 infection impacts on patients mortality: a propensity score-matched cohort study
Authors: Sokolski Mateusz , Reszka Konrad , Adamik Barbara , Kilis-Pstrusinska Katarzyna , Lis Weronika , Pomorski Michał , Sokolowski Janusz , Doroszko Adrian , Madziarska Katarzyna , Jankowska Ewa Anita , Protasiewicz Marcin 
Published: February 2024

AbstractOne of the major pathomechanisms of COVID-19 is the interplay of hyperinflammation and disruptions in coagulation processes, involving thrombocytes. Antiplatelet therapy (AP) by anti-inflammatory effect and inhibition of platelet aggregation may affect these pathways. The aim of this study was to investigate if AP has an impact on the in-hospital course and medium-term outcomes in hospitalized COVID-19 patients. The study population (2170 COVID-19 patients: mean ± SD age 60 ± 19 years old, 50% male) was divided into a group of 274 patients receiving any AP prior to COVID-19 infection (AP group), and after propensity score matching, a group of 274 patients without previous AP (non-AP group). Patients from the AP group were less frequently hospitalized in the intensive care unit: 9% vs. 15%, 0.55 (0.33–0.94), developed less often shock: 9% vs. 15%, 0.56 (0.33–0.96), and required less aggressive forms of therapy. The AP group had more coronary revascularizations: 5% vs. 1%, 3.48 (2.19–5.55) and strokes/TIA: 5% vs. 1%, 3.63 (1.18–11.2). The bleeding rate was comparable: 7% vs. 7%, 1.06 (0.54–2.06). The patients from the AP group had lower 3-month mortality: 31% vs. 39%, 0.69 (0.51–0.93) and didn’t differ significantly in 6-month mortality: 34% vs. 41%, 0.79 (0.60–1.04). When analyzing the subgroup with a history of myocardial infarction and/or coronary revascularization and/or previous stroke/transient ischemic attack and/or peripheral artery disease, AP had a beneficial effect on both 3-month: 37% vs. 56%, 0.58 (0.40–0.86) and 6-month mortality: 42% vs. 57%, 0.63 (0.44–0.92). Moreover, the favourable effect was highly noticeable in this subgroup where acetylsalicylic acid was continued during hospitalization with reduction of in-hospital: 19% vs. 43%, 0.31 (0.15–0.67), 3-month: 30% vs. 54%, 044 (0.26–0.75) and 6-month mortality: 33% vs. 54%, 0.49 (0.29–0.82) when confronted with the subgroup who had acetylsalicylic acid suspension during hospitalization. The AP may have a beneficial impact on hospital course and mortality in COVID-19 and shouldn’t be discontinued, especially in high-risk patients.
Sequential administration of paricalcitol followed by IL-17 blockade for progressive refractory IgA nephropathy patients
Authors: Uriol-Rivera Miguel G. , Obrador-Mulet Aina , Juliá Maria Rosa , Daza-Cajigal Vanessa , Delgado-Sanchez Olga , Garcia Alvarez Angel , Gomez-Lobon Ana , Carrillo-Garcia Paula , Saus-Sarrias Carlos , Gómez-Cobo Cristina , Ramis-Cabrer Daniel , Gasco Company Joan , Molina-Infante Javier ,   The Balear IgA Research and Treatment Project, Uriol-Rivera Miguel G. , Luque-Ramirez Manuel , Chavez Lia Natero 
Published: February 2024

AbstractThere is no established treatment for progressive IgA nephropathy refractory to steroids and immunosuppressant drugs (r-IgAN). Interleukin 17 (IL-17) blockade has garnered interest in immune-mediated diseases involving the gut-kidney axis. However, single IL-17A inhibition induced paradoxical effects in patients with Crohn’s disease and some cases of de novo glomerulonephritis, possibly due to the complete Th1 cell response, along with the concomitant downregulation of regulatory T cells (Tregs). Seven r-IgAN patients were treated with at least six months of oral paricalcitol, followed by the addition of subcutaneous anti-IL-17A (secukinumab). After a mean follow-up of 28 months, proteinuria decreased by 71% (95% CI: 56–87), P < 0.001. One patient started dialysis, while the annual eGFR decline in the remaining patients [mean (95% CI)] was reduced by 4.9 mL/min/1.73 m2 (95% CI: 0.1–9.7), P = 0.046. Circulating Th1, Th17, and Treg cells remained stable, but Th2 cells decreased, modifying the Th1/Th2 ratio. Intriguingly, accumulation of circulating Th17.1 cells was observed. This novel sequential therapy appears to optimize renal advantages in patients with r-IgAN and elicit alterations in potentially pathogenic T helper cells.
A study combining microbubble-mediated focused ultrasound and radiation therapy in the healthy rat brain and a F98 glioma model
Authors: Fletcher Stecia-Marie P. , Chisholm Amanda , Lavelle Michael , Guthier Romy , Zhang Yongzhi , Power Chanikarn , Berbeco Ross , McDannold Nathan 
Published: February 2024

AbstractFocused Ultrasound (FUS) has been shown to sensitize tumors outside the brain to Radiotherapy (RT) through increased ceramide-mediated apoptosis. This study investigated the effects of FUS + RT in healthy rodent brains and F98 gliomas. Tumors, or striata in healthy rats, were targeted with microbubble-mediated, pulsed FUS (220 kHz, 102–444 kPa), followed by RT (4, 8, 15 Gy). FUS + RT (8, 15 Gy) resulted in ablative lesions, not observed with FUS or RT only, in healthy tissue. Lesions were visible using Magnetic Resonance Imaging (MRI) within 72 h and persisted until 21 days post-treatment, indicating potential applications in ablative neurosurgery. In F98 tumors, at 8 and 15 Gy, where RT only had significant effects, FUS + RT offered limited improvements. At 4 Gy, where RT had limited effects compared with untreated controls, FUS + RT reduced tumor volumes observed on MRI by 45–57%. However, survival benefits were minimal (controls: 27 days, RT: 27 days, FUS + RT: 28 days). Histological analyses of tumors 72 h after FUS + RT (4 Gy) showed 93% and 396% increases in apoptosis, and 320% and 336% increases in vessel-associated ceramide, compared to FUS and RT only. Preliminary evidence shows that FUS + RT may improve treatment of glioma, but additional studies are required to optimize effect size.
Interactions between the protein barnase and co-solutes studied by NMR
Authors: Trevitt Clare R. , Yashwanth Kumar D. R. , Fowler Nicholas J. , Williamson Mike P. 
Published: February 2024

AbstractProtein solubility and stability depend on the co-solutes present. There is little theoretical basis for selection of suitable co-solutes. Some guidance is provided by the Hofmeister series, an empirical ordering of anions according to their effect on solubility and stability; and by osmolytes, which are small organic molecules produced by cells to allow them to function in stressful environments. Here, NMR titrations of the protein barnase with Hofmeister anions and osmolytes are used to measure and locate binding, and thus to separate binding and bulk solvent effects. We describe a rationalisation of Hofmeister (and inverse Hofmeister) effects, which is similar to the traditional chaotrope/kosmotrope idea but based on solvent fluctuation rather than water withdrawal, and characterise how co-solutes affect protein stability and solubility, based on solvent fluctuations. This provides a coherent explanation for solute effects, and points towards a more rational basis for choice of excipients.
A framework for demonstrating practical quantum advantage: comparing quantum against classical generative models
Authors: Hibat-Allah Mohamed , Mauri Marta , Carrasquilla Juan , Perdomo-Ortiz Alejandro 
Published: February 2024

AbstractGenerative modeling has seen a rising interest in both classical and quantum machine learning, and it represents a promising candidate to obtain a practical quantum advantage in the near term. In this study, we build over an existing framework for evaluating the generalization performance of generative models, and we establish the first quantitative comparative race towards practical quantum advantage (PQA) between classical and quantum generative models, namely Quantum Circuit Born Machines (QCBMs), Transformers (TFs), Recurrent Neural Networks (RNNs), Variational Autoencoders (VAEs), and Wasserstein Generative Adversarial Networks (WGANs). After defining four types of PQAs scenarios, we focus on what we refer to as potential PQA, aiming to compare quantum models with the best-known classical algorithms for the task at hand. We let the models race on a well-defined and application-relevant competition setting, where we illustrate and demonstrate our framework on 20 variables (qubits) generative modeling task. Our results suggest that QCBMs are more efficient in the data-limited regime than the other state-of-the-art classical generative models. Such a feature is highly desirable in a wide range of real-world applications where the available data is scarce.
Complex chemistry of carbon nanotubes toward efficient and stable p-type doping
Authors: Kawasaki Kaho , Harada Ikuyo , Akaike Kouki , Wei Qingshuo , Koshiba Yasuko , Horike Shohei , Ishida Kenji 
Published: February 2024

AbstractDeveloping efficient and stable carbon nanotube (CNT) doping techniques and elucidating their chemistry is essential for their further implementation in electronic and energy devices. Here, protonic acids and lithium salts are employed as p-type inducers and stabilizers of the doped state, respectively. Leveraging the electron-withdrawing capability of protons, protonic acids can easily induce heavily p-doped states in CNTs. Anionic species from the acids attach to the positively charged CNTs to achieve charge compensation. Introducing lithium salts with bulky, charge-delocalized anions to the p-doped CNTs results in an anion replacement driven by the free energy gain. The newly formed complexes demonstrate outstanding thermal stability in air, enduring a temperature of 100 °C for over a year. The chemical hardness of the applied anion effectively explains the difference in stability of the doped CNTs, indicating that the doping process and its stabilization can be understood and controlled through complex chemistry.
Tremor along the Dead Sea Transform remotely triggered by the 2023 MW7.6 Kahramanmaraş earthquake
Authors: Inbal Asaf 
Published: February 2024

AbstractTremor signals are weak and emergent, and the physics governing their generation is not well understood. Here, I report on tremor occurring along the Dead Sea Transform (DST), and a microearthquake on the Carmel-Fari’a Fault (CFF), both remotely triggered by the 2023 MW7.6 Kahramanmaraş earthquake. The triggered events location coincides with maxima of long-period velocity gradients, concentrated in the CFF-DST intersection and near a CFF fault-jump. Relative to other remotely triggered tremors, the DST tremor is strong and deficient in high-frequency seismic energy. Furthermore, analysis of several remotely triggered tremor episodes suggests that tremors spectral fall-off rates are not universal. I discuss the seismological attributes that may give rise to these observations in the context of two models. In the first, tremor is produced due to inertial vibrations of a frictionally-controlled oscillator, and in the second it is produced by a swarm of Low-Frequency Earthquakes.
Machine learning models identify predictive features of patient mortality across dementia types
Authors: Zhang Jimmy , Song Luo , Miller Zachary , Chan Kwun C. G. , Huang Kuan-lin 
Published: February 2024

Abstract
Background
Dementia care is challenging due to the divergent trajectories in disease progression and outcomes. Predictive models are needed to flag patients at risk of near-term mortality and identify factors contributing to mortality risk across different dementia types.

Methods
Here, we developed machine-learning models predicting dementia patient mortality at four different survival thresholds using a dataset of 45,275 unique participants and 163,782 visit records from the U.S. National Alzheimer’s Coordinating Center (NACC). We built multi-factorial XGBoost models using a small set of mortality predictors and conducted stratified analyses with dementiatype-specific models.

Results
Our models achieved an area under the receiver operating characteristic curve (AUC-ROC) of over 0.82 utilizing nine parsimonious features for all 1-, 3-, 5-, and 10-year thresholds. The trained models mainly consisted of dementia-related predictors such as specific neuropsychological tests and were minimally affected by other age-related causes of death, e.g., stroke and cardiovascular conditions. Notably, stratified analyses revealed shared and distinct predictors of mortality across eight dementia types. Unsupervised clustering of mortality predictors grouped vascular dementia with depression and Lewy body dementia with frontotemporal lobar dementia.

Conclusions
This study demonstrates the feasibility of flagging dementia patients at risk of mortality for personalized clinical management. Parsimonious machine-learning models can be used to predict dementia patient mortality with a limited set of clinical features, and dementiatype-specific models can be applied to heterogeneous dementia patient populations.
Cardiologist-level interpretable knowledge-fused deep neural network for automatic arrhythmia diagnosis
Authors: Jin Yanrui , Li Zhiyuan , Wang Mengxiao , Liu Jinlei , Tian Yuanyuan , Liu Yunqing , Wei Xiaoyang , Zhao Liqun , Liu Chengliang 
Published: February 2024

Abstract
Background
Long-term monitoring of Electrocardiogram (ECG) recordings is crucial to diagnose arrhythmias. Clinicians can find it challenging to diagnose arrhythmias, and this is a particular issue in more remote and underdeveloped areas. The development of digital ECG and AI methods could assist clinicians who need to diagnose arrhythmias outside of the hospital setting.

Methods
We constructed a large-scale Chinese ECG benchmark dataset using data from 272,753 patients collected from January 2017 to December 2021. The dataset contains ECG recordings from all common arrhythmias present in the Chinese population. Several experienced cardiologists from Shanghai First People’s Hospital labeled the dataset. We then developed a deep learning-based multi-label interpretable diagnostic model from the ECG recordings. We utilized Accuracy, F1 score and AUC-ROC to compare the performance of our model with that of the cardiologists, as well as with six comparison models, using testing and hidden data sets.

Results
The results show that our approach achieves an F1 score of 83.51%, an average AUC ROC score of 0.977, and 93.74% mean accuracy for 6 common arrhythmias. Results from the hidden dataset demonstrate the performance of our approach exceeds that of cardiologists. Our approach also highlights the diagnostic process.

Conclusions
Our diagnosis system has superior diagnostic performance over that of clinicians. It also has the potential to help clinicians rapidly identify abnormal regions on ECG recordings, thus improving efficiency and accuracy of clinical ECG diagnosis in China. This approach could therefore potentially improve the productivity of out-of-hospital ECG diagnosis and provides a promising prospect for telemedicine.
Why do people not prepare for disasters? A national survey from China
Authors: Han Ziqiang , Wu Guochun 
Published: February 2024

AbstractLimited studies investigated the reasons for not adopting specific preparedness actions. This paper addresses this gap using national survey data from China. Seven disaster preparedness actions are used to measure preparedness behaviors, including “preparing food and water at home,” “paying attention to disaster-related information,” “making emergency plans,” “being aware of nearest shelters,” “being aware of building codes,” “participating in exercises or drills,” and “volunteering for emergencies.” The primary reasons for not adopting are “lack of awareness,” “not knowing where to buy or reach resources,” and “perceiving the action as unnecessary.” Other less chosen reasons ranking from high to low are the “financial cost,” “need for special knowledge,” “lack of time,” “need for collaboration with others,” “human energy consuming,” and “not feeling responsible.” Trust in government, relocation due to disasters, living in urban areas, and higher socioeconomic status are positively correlated with higher probabilities of adopting all seven preparedness activities. These findings emphasize the importance of community outreach by emergency management professionals to increase public awareness of disaster preparedness.
Progesterone inhibits endometrial cancer growth by inhibiting glutamine metabolism through ASCT2
Authors: Guo Jinqiu , Fan Jianhui , Zhang Yaru , Li Mengyue , Jin Zeen , Shang Yuhong , Zhang Hongshuo , Kong Ying 
Published: February 2024

Abstract
Endometrial carcinoma (EC) is a common malignancy that originates from the endometrium and grows in the female reproductive system. Surgeries, as current treatments for cancer, however, cannot meet the fertility needs of young women patients. Thus, progesterone (P4) therapy is indispensable due to its effective temporary preservation of female fertility. Many cancer cells are often accompanied by changes in metabolic phenotypes, and abnormally dependent on the amino acid glutamine. However, whether P4 exerts an effect on EC via glutamine metabolism is unknown. In the present study, we found that P4 could inhibit glutamine metabolism in EC cells and down-regulate the expression of the glutamine transporter ASCT2. This regulation of ASCT2 affects the uptake of glutamine. Furthermore, the in vivo xenograft studies showed that P4 inhibited tumor growth and the expression of key enzymes involved in glutamine metabolism. Our study demonstrated that the direct regulation of glutamine metabolism by P4 and its anticancer effect was mediated through the inhibition of ASCT2. These results provide a mechanism underlying the effects of P4 therapy on EC from the perspective of glutamine metabolism.
Spectral variations within solar flare ribbons
Authors: Pietrow A. G. M. , Druett M. K. , Singh V. 
Published: February 2024

Context.Solar flare ribbons are intense brightenings of primarily chromospheric material that are responsible for a large fraction of the chromospheric emission in solar and stellar flares. We present an on-disc observation of flare ribbon substructures in an X9.3-class flare observed by the Swedish 1-m Solar Telescope.Aims.We aim to identify categories of ribbon substructures seen in the Ca II8542 Å, Hα, and Ca IIK lines, focusing on their spatial locations and their (spectro-)polarimetric properties.Methods.We used COlor COllapsed Plotting (COCOPLOT) software to assist in identifying areas of interest.Results.We present five categories of spectral profiles within the general body of the flare ribbon: (1) extremely broadened spectral line profiles, where the standard Fabry–Perot interferometer wavelength windows (≈70 km s−1) are not sufficiently wide to allow for a complete analysis of the dynamics and atmospheric conditions. The mechanisms causing this degree of this broadening are not yet clearly understood; (2) long-lived, dense kernels that manifest as more saturated chromospheric line profiles with lower signal in both Stokes parameters. They are interpreted as footpoints of bunched magnetic field loops, whose chromospheric lines form at greater heights than the nearby areas; (3) Doppler-shifted leading edges of the flare ribbon in regions that transiently display lower Stokes signals due to the emission dominating at greater heights in the atmosphere; (4) condensed coronal rain overlapping the flare ribbons in the line of sight, producing exceptionally high Doppler shifts near the footpoints; and (5) compact blueshifted areas close to areas with coronal rain down-flows, which are understood to be material that has been thrown up as a result of the down-flowing material impacting the chromosphere. Additionally, a ribbon formation height of about 700 km with respect to penumbral features is estimated using correlating structures on the ribbon and the underlying photosphere.Conclusions.When selecting areas of the flare ribbon for more general analysis (especially small regions consisting of a few pixels or low-resolution averages), it is important to be aware of the variety of substructures present within a flare ribbon and of the spatial context that can produce these differences. General behaviors across the ribbon should not be inferred from regions that show localized differences.
Four new eclipsing accreting ultracompact white dwarf binaries found with the Zwicky Transient Facility
Authors: Khalil J. M. , van Roestel J. , Bellm E. C. , Bloom J. S. , Dekany R. , Drake A. J. , Graham M. J. , Groom S. L. , Kulkarni S. R. , Laher R. R. , Mahabal A. A. , Prince T. , Riddle R. 
Published: February 2024

Context. Accreting ultracompact white dwarf binaries contain a white dwarf that is accreting from a degenerate object. They have orbital periods shorter than 65 min.
Aims. We report the discovery and the orbital period of four new eclipsing accreting ultracompact white dwarf binaries found using the Zwicky Transient Facility (ZTF) and discuss their photometric properties.
Methods. We searched through a list of 4171 dwarf novae compiled using the ZTF and used the box least square method to search for periodic signals in the data.
Results. We found four eclipsing accreting ultracompact binaries with orbital periods between 25.9 and 56 min. One had previously been published as an AM Canum Venaticorum (AM CVn), and the other three systems are new discoveries. The two shorter-period systems are likely also AM CVn systems, while the longest-period system, with a period of 56 min, showed multiple super-outbursts over two years, which is more consistent with it being a helium CV.