bluuebunny/crossref_metadata_2025_split huggingface dataset:
Being a Husband and Caregiver: The Adjustment of Roles When Caring for a Wife Who Has Dementia
Authors: Miller Michaella , Neiterman Elena , Keller Heather , McAiney Carrie 
Published: October 2024

Abstract
As demographics and gender norms shift, more older men will be providing care for their wives living with dementia than ever before. Research on husbands as caregivers is limited and offers an incomplete picture of their role development and how they experience caregiving. This study examined husbands whose wives have dementia and how they provide care and construct their sense of self. Semi-structured interviews with 11 men aged 61–88 were conducted in Ontario, Canada. Data were analyzed using constant comparison analysis and a constructivist grounded theory (CGT) approach. Two categories were developed: Adapting to the Role of Caregiver and Staying a Husband. Caregiving as a husband for a wife living with dementia required revision of the role of husband to include that of caregiver by reimaging intimacy, being a protector in new ways, and finding new meanings to being a provider and the value of wealth.
Positive impact of an inpatient early childhood literacy programme on literacy practices and family experience in a paediatric heart centre
Authors: Young Allison C. , Ruth Amanda , Ginn Lauren , Sethi Louisa , Hellsten Melody , Deshotels Kirby , Pande Chetna K. , Borges Nirica M. , Wang Eric , Mummert Kelsey , Hill Stephanie , Bryant Tasha , Brown Ginger , Puri Kriti 
Published: October 2024

AbstractObjective:CHD predisposes children to neurodevelopmental delays. Frequent, prolonged hospitalisations during infancy prevent children with heart disease from participating in recommended language and cognitive development programmes, such as outpatient early childhood literacy programmes, and contribute to caregiver stress, a risk factor for adverse developmental outcomes. This study aims to describe the implementation of a single-centre inpatient early childhood literacy programme for hospitalised infants with heart disease and assess its impact on reading practices and patient–family hospital experience.Methods:Admitted infants ≤1 year old receive books, a calendar to track reading frequency, and reading guidance at regular intervals. Voluntary feedback is solicited from caregivers using an anonymous, QR-code survey on books. A prospective survey also assessed programme impact on hospital experience.Results:From February 2021 to November 2023, the Books@Heart programme provided 1,293 books to families of 840 infants, of whom 110 voluntarily submitted feedback. Caregivers reported a significant improvement in access to books (p < 0.001) and increased reading frequency after learning about Books@Heart (p = 0.003), with the proportion reading to their child daily increasing from 27% to 62%. Among 40 prospective survey responses, caregivers reported feeling a sense of personal fulfillment (60%), self-confidence (30%), connection (98%), and personal well-being (40%) while reading to their child.Conclusion:An inpatient early childhood literacy programme is a well-received intervention for infants with heart disease that promotes development, improves book access, increases reading exposure, and engages families. Further studies are needed to assess its impact on sustained reading practices and neurodevelopmental outcomes.
The risks of adverse events with venlafaxine for adults with major depressive disorder: a systematic review of randomised clinical trials with meta-analysis and Trial Sequential Analysis
Authors: Kamp C. B. , Petersen J. J. , Faltermeier P. , Juul S. , Siddiqui F. , Moncrieff J. , Horowitz M. A. , Hengartner M. P. , Kirsch I. , Gluud C. , Jakobsen J. C. 
Published: October 2024

Abstract

Aims
Venlafaxine is used to treat depression worldwide. Previous reviews have demonstrated that venlafaxine lowers scores on depression rating scales, producing statistically significant results but the relevance to patients remains uncertain. Knowledge of the incidence of the adverse effects associated with venlafaxine has previously been based on the results of non-randomised studies. Our primary objective was to assess the risks of adverse events with venlafaxine in the treatment of adults with major depressive disorder in randomised trials.

Methods
We searched relevant databases and other sources from inception to 7 March 2024 for randomised clinical trials comparing venlafaxine versus placebo or no intervention in adults with major depressive disorder. Data were synthesised using meta-analysis and Trial Sequential Analysis. The primary outcomes were suicides or suicide attempts, serious adverse events and non-serious adverse events.

Results
We included 28 trials randomising 6,253 participants to venlafaxine versus placebo. All results were at high risk of bias, and the certainty of the evidence was very low. All trials assessed outcomes at a maximum of 12 weeks after randomisation. Meta-analysis and Trial Sequential Analysis showed insufficient information to assess the effects of venlafaxine on the risks of suicides or suicide attempts. Meta-analysis showed evidence of harm of venlafaxine versus placebo on serious adverse events (risk ratio: 2.66; 95% confidence interval: 1.67–4.25; p < 0.01; 22 trials), mainly due to a higher risk of sexual dysfunction and anorexia. Meta-analysis showed that venlafaxine also increased the risk of several non-serious adverse events: nausea, dry mouth, dizziness, sweating, somnolence, constipation, nervousness, insomnia, asthenia, tremor and decreased appetite.

Conclusions
Short-term results show that venlafaxine has uncertain effects on the risks of suicides but increases the risks of serious adverse events (especially sexual dysfunction and anorexia) and many non-serious adverse events. The long-term effects of venlafaxine for major depressive disorder are unknown. It is a particular cause for concern that there are no data on the long-term adverse effects of venlafaxine given that so many people use these drugs for several years.
Seeing or believing in hyperplexed spatial proteomics via antibodies: New and old biases for an image-based technology
Authors: Bolognesi Maddalena M. , Dall’Olio Lorenzo , Maerten Amy , Borghesi Simone , Castellani Gastone , Cattoretti Giorgio 
Published: October 2024

Abstract
Hyperplexed in-situ targeted proteomics via antibody immunodetection (i.e., >15 markers) is changing how we classify cells and tissues. Differently from other high-dimensional single-cell assays (flow cytometry, single-cell RNA sequencing), the human eye is a necessary component in multiple procedural steps: image segmentation, signal thresholding, antibody validation, and iconographic rendering. Established methods complement the human image evaluation, but may carry undisclosed biases in such a new context, therefore we re-evaluate all the steps in hyperplexed proteomics. We found that the human eye can discriminate less than 64 out of 256 gray levels and has limitations in discriminating luminance levels in conventional histology images. Furthermore, only images containing visible signals are selected and eye-guided digital thresholding separates signal from noise. BRAQUE, a hyperplexed proteomic tool, can extract, in a marker-agnostic fashion, granular information from markers which have a very low signal-to-noise ratio and therefore are not visualized by traditional visual rendering. By analyzing a public human lymph node dataset, we also found unpredicted staining results by validated antibodies, which highlight the need to upgrade the definition of antibody specificity in hyperplexed immunostaining. Spatially hyperplexed methods upgrade and supplant traditional image-based analysis of tissue immunostaining, beyond the human eye contribution.
Diurnal Soil Freeze‐Thaw Cycles and the Factors Determining Their Changes in Warming Climate in the Upper Brahmaputra Basin of the Tibetan Plateau
Authors: Li Ning , Cuo Lan , Zhang Yongxin , Flerchinger Gerald N. 
Published: October 2024

AbstractSoil freeze‐thaw cycles play a critical role in ecosystem, hydrological and biogeochemical processes, and climate. The Tibetan Plateau (TP) has the largest area of frozen soil that undergoes freeze‐thaw cycles in the low‐mid latitudes. Evidence suggests ongoing changes in seasonal freeze‐thaw cycles during the past several decades on the TP. However, the status of diurnal freeze‐thaw cycles (DFTC) of shallow soil and their response to climate change largely remain unknown. In this study, using in‐situ observations, the latest reanalysis, machine learning, and physics‐based modeling, we conducted a comprehensive assessment of the spatiotemporal variations of DFTC and their response to climate change in the upper Brahmaputra (UB) basin. About 24 ± 8% of the basin is subjected to DFTC with a mean frequency of 87 ± 55 days during 1980–2018. The area and frequency of DFTC show small long‐term changes during 1980–2018. Air temperature impacts on the frequency of DFTC changes center mainly around the freezing point (0°C). The spatial variations in the response of DFTC to air temperature can primarily be explained by three factors: precipitation (30.4%), snow depth (22.6%) and seasonal warming/cooling rates (14.9%). Both rainfall and snow events reduce diurnal fluctuations of soil temperature, subsequently reducing DFTC frequency, primarily by decreasing daytime temperature through evaporation‐cooling and albedo‐cooling effects, respectively. These results provide an in‐depth understanding of diurnal soil freeze‐thaw status and its response to climate change.
Deciphering the Characteristics and Drivers of the Summer Monsoon Precipitation Extremes Over the Indian Himalayas
Authors: Saini Rohtash , Attada Raju 
Published: October 2024

AbstractThis study investigates the physical processes behind extreme precipitation events (EPEs) in the Himalayas, notorious for causing frequent floods and significant loss of life and property. Due to the presence of complex terrain, understanding the driving factors of these EPEs is challenging. Here, we decipher the precipitation characteristics and their driving factors responsible for the occurrence of EPEs in the Western Himalayas (WH) for the period 1979–2020. EPEs are defined as events exceeding the 99th percentile threshold. The extreme precipitation in the WH is contributed by both large‐scale precipitation (accounting for 61%) and convective precipitation (39%). Moreover, 25.49% of EPEs in this region are directly associated with monsoon depressions. The presence of distinct upper‐tropospheric gyres flanking the WH, along with a prominent zonal wave pattern, promotes a southward extension of the trough. This intensifies the low‐level convergence of moisture‐laden winds from the adjoining seas, resulting in substantial moisture availability for the EPEs. An omega‐type blocking pattern emerges 4 days before EPEs, facilitating the intrusion of an extratropical cyclonic circulation. This circulation, characterized by its slow eastward and equatorward movement, leads to low‐level moisture flux convergence and ascending motions, which in turn trigger the EPEs. This highlights the crucial role of extratropical signals in driving EPEs and implies that tropical‐extratropical interactions play an important role in these EPEs. Furthermore, the shifting of the Intertropical Convergence Zone is strongly linked to the enhancement of the intensity of EPEs. Moreover, moisture budget analysis shows that EPEs over the WH are primarily driven by vertical advection, with the dynamic (thermodynamic) terms explaining 92% (8%) contribution. The intensified diabatic heating structure further enhances the convection, facilitating the development of deep convection which controls the local thermodynamics of these EREs. Lastly, our study demonstrated that most intensified and persistent EPEs over the Himalayas are found to be linked with Quasi‐Resonance Amplification, which is driven by baroclinic waves with 5 and 8 zonal wave numbers that contribute to these EPEs.
Bridging Hydrological Ensemble Simulation and Learning Using Deep Neural Operators
Authors: Sun Alexander Y. , Jiang Peishi , Shuai Pin , Chen Xingyuan 
Published: October 2024

AbstractEnsemble‐based simulation and learning (ESnL) has long been used in hydrology for parameter inference, but computational demands of process‐based ESnL can be quite high. To address this issue, we propose a deep neural operator learning approach. Neural operators are generic machine learning algorithms that can learn functional mappings between infinite‐dimensional spaces, providing a highly flexible tool for scientific machine learning. Our approach is built upon DeepONet, a specific deep neural operator, and is designed to address several common problems in hydrology, namely, model parameter estimation, prediction at ungaged locations, and uncertainty quantification. Here we demonstrate the effectiveness of our DeepONet‐based workflow using an existing large model ensemble created for an eastern U.S. watershed that is instrumented with 10 streamflow gages. Results suggest DeepONet achieves high efficiency in learning an ML surrogate model from the model ensemble, with the modified Kling‐Gupta Efficiency exceeding 0.9 on holdout test sets. Parameter inference, carried out using the trained DeepONet surrogate model and genetic algorithm, also yields robust results. Additionally, we formulate and train a separate DeepONet model for physics‐informed, seq‐to‐seq streamflow forecasting, which further reduces biases in the pre‐trained DeepONet surrogate model. While this study focuses primarily on a single watershed, our approach is general and may be extended to enable learning from model ensembles across multiple basins or models. Thus, this research represents a significant contribution to the application of hybrid machine learning in hydrology.
C/EBPα-mediated ACSL4-dependent ferroptosis exacerbates tubular injury in diabetic kidney disease
Authors: Xia Ziru , Wei Zhaonan , Li Xin , Liu Yunzi , Gu Xiangchen , Tong Jianhua , Huang Siyi , Zhang Xiaoyue , Wang Weiming 
Published: October 2024

AbstractDiabetic kidney disease (DKD) is a prevalent and debilitating complication of diabetes characterized by progressive renal function decline and a lack of effective treatment options. Here, we investigated the role of the transcription factor CCAAT/enhancer binding protein alpha (C/EBPα) in DKD pathogenesis. Analysis of renal biopsy samples revealed increased C/EBPα expression in patients with DKD. Using RNA sequencing and proteomics, we explored the mechanisms through which the C/EBPα contributes to DKD. Our findings demonstrated that C/EBPα exacerbated tubular injury by promoting acyl-CoA synthetase long-chain family member 4 (ACSL4)-dependent ferroptosis. We identified that C/EBPα upregulated ACSL4 expression by binding to its transcription regulatory sequence (TRS), leading to elevated lipid peroxidation and ferroptosis. Furthermore, inhibition or genetic ablation of C/EBPα attenuated ferroptosis and mitigated tubular injury in DKD. These results highlighted the C/EBPα-ACSL4-ferroptosis pathway as a promising therapeutic target for DKD treatment.
The effect of digital therapeutics intervention on improving hypertension management in adults: a meta-analysis of randomized controlled trial
Authors: Liu Lu , Guo Jiayue , Jiao Xitong , You Lili 
Published: October 2024

Abstract
Digital therapeutics (DTx) intervention is an emerging therapy for the treatment and long-term management of hypertension. We aim to systematically evaluate the overall effect of DTx intervention on improving hypertension management. The systematic review and meta-analysis of RCTs was conducted and the PubMed, EMBASE, Web of Science, and Cochrane Library were searched to identify eligible RCTs published between Jan 1, 1982 and Sep 10, 2023. Random-effect models were utilized to pool estimates of net changes in systolic blood pressure (BP), diastolic BP, BP control rate, body mass index, weight, waist circumference, and physical activity between the DTx group and control group. 15 RCTs were included with a total of 3789 participants. Compared with the control group, DTx intervention was associated with significant changes in systolic BP, diastolic BP, and BP control rate of –3.75 mmHg(95% CI –5.74 to 1.77), –1.79 mmHg (95% CI –2.81 to –0.77) and 1.47% (95% CI 1.10 to 1.95), respectively. In addition, DTx intervention was statistically significant for improving other risk factors such as lower BMI (−0.5 kg/m2, 95% CI –0.86 to −0.15), increased physical activity (66.73 min/week, 95%CI 49.64 to 83.81), and reduced waist circumference (−2.91 cm, 95% CI −5.15 to −0.66). No difference between groups was demonstrated in weight (P = 0.30). Subgroup analyses revealed consistent effects of the change in SBP and DBP across study duration, age, sample size, patient baseline status, and intervention scenario settings(P > 0.05). DTx intervention may be useful for lowering BP and long-term management of hypertension. More large-size trials providing evidence on the same product are needed.
Impact of retinal traction induced by epiretinal membrane on aniseikonia
Authors: Hirano Masayuki , Minakawa Shun , Imamura Yuta , Yamamoto Naoko 
Published: October 2024

AbstractWe investigated the effect of retinal traction caused by epiretinal membranes (ERMs) on aniseikonia and retinal microstructures in 81 unilateral ERMs. Retinal traction was quantified by measuring the maximum depth of the retinal fold (MDRF) using en face optical coherence tomography (OCT) images. Measurements included the mean inner nuclear layer (INL), outer plexiform layer (OPL), outer nuclear layer (ONL), central retinal thickness (CRT), and interocular ratios of the foveal avascular zone (FAZ) area (FAZ ratio). Significant correlations were found between the preoperative MDRF and preoperative aniseikonia (P < 0.001), INL thickness (P < 0.001), CRT (P < 0.001), and FAZ ratio (P = 0.003). Preoperative aniseikonia was significantly correlated with preoperative INL and OPL-ONL thicknesses (P < 0.001 and P = 0.020, respectively) and CRT (P = 0.003). Multiple regression analysis revealed that preoperative aniseikonia was significantly associated with preoperative MDRF, INL, and OPL-ONL thicknesses (P = 0.029, 0.006, and 0.006, respectively). Twenty-nine eyes underwent membrane peeling, resolving all retinal folds 6 months postoperatively. A significant correlation was observed between preoperative MDRF and postoperative aniseikonia (P = 0.011). Our findings suggest that retinal traction by ERM is significantly associated with aniseikonia both pre- and postoperatively, alongside other OCT parameters.
An in vitro evaluation of tensile strength of molar endocrown milled from various computer aided design and manufacturing materials
Authors: Taha Ahmed Ismail , Saad Aya Ehab 
Published: October 2024

AbstractNew computer-aided design and computer-aided manufacturing (CAD-CAM) materials have been reported to have suitable mechanical and physical properties for endocrown restorations. However, there is a lack of literature on evaluating the retention of endocrown using these materials. This in vitro study aimed to compare the retention of endocrowns fabricated from 3 different CAD-CAM materials. Sixty human mandibular third molars were divided into 3 groups (n = 20) according to the material used: (e.max CAD, Ivoclar AG, Schaan, Liechtenstein), (HC, Shofu, Koyoto, Japan), and (Brilliant Crios, Coltene, Altstätten, Switzerland) (n = 20). Specimens were stored in distilled water at 37 °C for 1 week and subjected to 5000 thermal cycles. A universal testing machine (5500R/1123, Instron, Norwood, USA) was used to measure the tensile force. All results were statistically analyzed using one-way ANOVA (α = 0.05), and different failure modes were demonstrated. The results revealed that e. max CAD showed the highest mean tensile force value (402.35 ± 15.812) N, and the lowest mean tensile force value was for Brilliant Coris (118.90 ± 12.430) N (P < .001). It is concluded that e.max CAD endocrowns showed the highest tensile force values after thermocycling in comparison to other materials with a significant difference, which may have a promising impact on the survival of endocrown restorations.
Leveraging weak complementary labels enhances semantic segmentation of hepatocellular carcinoma and intrahepatic cholangiocarcinoma
Authors: Hägele Miriam , Eschrich Johannes , Ruff Lukas , Alber Maximilian , Schallenberg Simon , Guillot Adrien , Roderburg Christoph , Tacke Frank , Klauschen Frederick 
Published: October 2024

AbstractIn this paper we present a deep learning segmentation approach to classify and quantify the two most prevalent primary liver cancers – hepatocellular carcinoma and intrahepatic cholangiocarcinoma – from hematoxylin and eosin (H&E) stained whole slide images. While semantic segmentation of medical images typically requires costly pixel-level annotations by domain experts, there often exists additional information which is routinely obtained in clinical diagnostics but rarely utilized for model training. We propose to leverage such weak information from patient diagnoses by deriving complementary labels that indicate to which class a sample cannot belong to. To integrate these labels, we formulate a complementary loss for segmentation. Motivated by the medical application, we demonstrate for general segmentation tasks that including additional patches with solely weak complementary labels during model training can significantly improve the predictive performance and robustness of a model. On the task of diagnostic differentiation between hepatocellular carcinoma and intrahepatic cholangiocarcinoma, we achieve a balanced accuracy of 0.91 (CI 95%: 0.86-0.95) at case level for 165 hold-out patients. Furthermore, we also show that leveraging complementary labels improves the robustness of segmentation and increases performance at case level.
Medical large language models are susceptible to targeted misinformation attacks
Authors: Han Tianyu , Nebelung Sven , Khader Firas , Wang Tianci , Müller-Franzes Gustav , Kuhl Christiane , Försch Sebastian , Kleesiek Jens , Haarburger Christoph , Bressem Keno K. , Kather Jakob Nikolas , Truhn Daniel 
Published: October 2024

AbstractLarge language models (LLMs) have broad medical knowledge and can reason about medical information across many domains, holding promising potential for diverse medical applications in the near future. In this study, we demonstrate a concerning vulnerability of LLMs in medicine. Through targeted manipulation of just 1.1% of the weights of the LLM, we can deliberately inject incorrect biomedical facts. The erroneous information is then propagated in the model’s output while maintaining performance on other biomedical tasks. We validate our findings in a set of 1025 incorrect biomedical facts. This peculiar susceptibility raises serious security and trustworthiness concerns for the application of LLMs in healthcare settings. It accentuates the need for robust protective measures, thorough verification mechanisms, and stringent management of access to these models, ensuring their reliable and safe use in medical practice.