julilili42/papers huggingface dataset:
Clinical translation of 3D-printed patient-specific bone implants: a consensus statement
2025-07-17

Background: Extensive defects in long bones, resulting from trauma, disease, or other etiologies, impose significant morbidity on patients and may necessitate amputation, long-term disability, or premature mortality. While 3D-printed, patient-specific implants offer promising regenerative solutions, their clinical implementation remains hindered by regulatory challenges, lack of standardized guidelines, and gaps in translational research. Addressing these barriers is critical to improving patient outcomes and optimizing healthcare resource utilization. Materials and methods: A multidisciplinary group of 29 experts—including clinicians (surgeons, anesthesiologists), biomaterial scientists, biomedical engineers, legal/regulatory professionals, health economists, meta-researchers, artificial intelligence experts, trialists, and biomaterial industry representatives—convened for the Consensus Meeting on 3D-printed patient-specific Bone Implants (CoMBI). Preceding the meeting, key questions were discussed in individual interviews and categorized into fundamental research, preclinical studies, and clinical trials &amp; implementation (CoMBI themes). Experts presented on each theme, followed by structured discussions. Statements were synthesized, iteratively refined, and validated through open review. Results: The consensus meeting resulted in 20 key statements addressing the CoMBI themes, outlining a framework to advance regulatory compliance and facilitate the clinical adoption of 3D-printed implants. Key statements include the need for harmonized regulatory pathways, clear guidelines on preclinical validation, and innovative trial designs tailored to complex, patient-specific implants. Strengthening collaboration among policymakers, regulatory agencies, and clinicians is crucial to overcoming current implementation barriers and ensuring equitable patient access to these advanced technologies. Conclusion: This Consensus Statement presents 20 key statements across fundamental research, preclinical studies, and clinical trials &amp; implementation, offering a roadmap for accelerating the regulatory and clinical translation of 3D-printed patient-specific bone implants. The findings emphasize the critical role of interdisciplinary collaboration in overcoming challenges, such as standardizing implant development and navigating complex regulatory landscapes. By addressing these barriers and outlining practical strategies, the consensus highlights actionable steps to bridge the gap between innovation and clinical application.
Comparative Analysis of Initial Full Blood Count Parameters in Adults Infected With Plasmodium falciparum for Classification of Disease Severity and Previous Exposure Across Endemic (Gabon) and Nonendemic (Germany) Settings
2025-07-17

Abstract Background The clinical presentation of individuals infected with Plasmodium falciparum is exceptionally diverse, ranging from asymptomatic parasitemia to life-threatening disease. Frequent previous exposure to Plasmodium spp results in partial protection from severe disease; however, this protection wanes in individuals emigrating from holoendemic regions, and there are currently no reliable biomarkers that accurately indicate this semi-immunity. Methods Data were analyzed from 1392 adults infected with P falciparum in Gabon and Germany. Full blood count parameters and ratios were evaluated individually and as a combined ensemble-based machine learning classifier to predict disease severity, ranging from asymptomatic infection to severe malaria. As a secondary objective, the influence of previous exposure to Plasmodium spp was assessed. Results Comparing asymptomatic parasitemia with uncomplicated malaria in Gabonese and comparing uncomplicated with severe malaria in German patients revealed significantly lower platelet counts (218 vs 150 ×103/μL, P &amp;lt; .0001; 85 vs 40 ×103/μL, P &amp;lt; .0001, respectively) and higher neutrophil counts (2.32 vs 2.57 ×103/μL, P = .0037; 3.08 vs 4.49 ×103/μL, P &amp;lt; .0001) in those with greater infection severity. The machine learning classifier outperformed single parameters in differentiating infection severity in both comparisons (area under the receiver operating characteristic curve, 0.94 and 0.84). Lymphocyte and monocyte counts showed a pattern that follows the level of previous malaria exposure, with lower cell counts in naive vs previously exposed patients, regardless of infection severity. Conclusions The value of simple full blood count parameters for classification of P falciparum infection severity and previous exposure is considerable. The accuracy can be increased by integrating individual parameters into a joint machine learning model.
High-Quality In Vivo Chemical Probes for Protein Kinases Disclosed in 2024
2025-07-17

Protein kinases are highly relevant drug targets, yet a significant fraction of the human kinome remains underexplored. Highly potent and selective small-molecule inhibitors used as chemical probes are invaluable tools for enabling the validation and translation of new kinase targets. This review provides an overview and analysis of the high-quality in vivo chemical probes for protein kinases published and deposited at the Chemical Probes Portal in the year 2024. We discuss the design strategies, molecular mechanism of action, details of their use in vitro and in vivo, as well as their application in target (in)-validation. We also highlight the importance of wisely selecting chemical probes and encourage best practices in using such tool compounds.
A Generative Framework for Probabilistic, Spatiotemporally Coherent Downscaling of Climate Simulation
2025-07-18

Abstract Local climate information is crucial for impact assessment and decision-making, yet coarse global climate simulations cannot capture small-scale phenomena. Current statistical downscaling methods infer these phenomena as temporally decoupled spatial patches. However, to preserve physical properties, estimating spatio-temporally coherent high-resolution weather dynamics for multiple variables across long time horizons is crucial. We present a novel generative framework that uses a score-based diffusion model trained on high-resolution reanalysis data to capture the statistical properties of local weather dynamics. After training, we condition on coarse climate model data to generate weather patterns consistent with the aggregate information. As this predictive task is inherently uncertain, we leverage the probabilistic nature of diffusion models and sample multiple trajectories. We evaluate our approach with high-resolution reanalysis information before applying it to the climate model downscaling task. We then demonstrate that the model generates spatially and temporally coherent weather dynamics that align with global climate output.
Streamlining a Patchwork - Exploring the Challenges of Digital Transformation in Pathology: Ethnographic Study
2025-07-18

Background To transition to a fully digital workflow, a pathology department in a German university hospital reorganized its processes, upgrading and integrating new technologies such as an updated laboratory information system and high-throughput scanners. While the visions of digital pathology follow a “promissory rhetoric” of improved patient care, studies name technological and professional challenges of digital pathology. We examined the experiences of the pathology staff with the digital transformation process from an occupational health perspective, focusing on the mutual influences between digital transformation and work-related psychosocial demands and resources. Objective The purpose of this study was to explore the interactions between occupational health and digital transformation in the workplace based on a holistic analysis of an ongoing digital transformation process. Methods We conducted participant observation, focus groups, qualitative interviews, and document analysis using an ethnographic research design. The pathology department had approximately 100 employees. More than 30 pathology staff members and supervisors from the diagnostics, laboratory, quality management, administration, and IT areas participated. Data were collected in 3 field phases between July 2022 and December 2023, representing different stages of the digital transformation. Data were analyzed using the reflexive thematic analysis method of Braun and Clarke. In addition, 2 member-checking workshops were conducted with the entire pathology team. Results We identified 2 key themes and 7 subthemes. The 2 key themes were (1) highly demanding work in a complex system that does not fit and (2) striving for steadiness in an open-ended process. What we found was that the pathology department under study experienced a digital transformation process with scarce human, time, and technological resources. The results showed that the process was at the expense of the people. Digital transformation remained a compromise and did not (yet) deliver on the promise of increased work efficiency and reduced workload. The demand-resource mismatch emerged as a major digital transformation stressor. However, the slower transformation was leveraged by the pathology staff to improve the organizational culture and (again) find creative workarounds. Digital transformation led to the renegotiation of work roles and identity. It also led to the creation of a new network of connections through the implementation of new technologies but also through the creation of new forms of team communication. Conclusions The modernization of the health care system is necessary, but it risks taking place under inadequate working conditions. Increased work intensity and perceived psychosocial stress during the transformation process threaten to drive even more people out of the health care system. Therefore, protecting the occupational health of the people implementing digital transformation should be at the core of planning digital transformation projects.
The Minimal Clinically Important Difference in Allergen Immunotherapy: An Evidence‐Based Approach
2025-07-18

ABSTRACT Background Regulatory authorities recommend a combination of symptom and medication scores during the grass pollen season as a primary endpoint for Phase III allergen immunotherapy (AIT) trials targeting allergic rhinoconjunctivitis. However, many composite primary endpoint scales exist; none are validated, nor do they have a well‐justified minimal clinically important difference (MCID). Methods Direct patient feedback from 1071 grass‐allergic patients was obtained to determine the minimally relevant improvement in allergic symptoms and translated into an MCID for the EAACI recommended CSMS 0–6 . Additionally, a clinically relevant threshold for the validated Rhinitis Quality of Life Questionnaire (RQLQ(S)) was determined from studies of registered SLIT products and subsequently used as an anchor to derive the MCID for CSMS 0–6 using the data of a Phase III clinical trial with PQ Grass 27,600 SU (RESONATE). Results 69% of grass‐allergic patients were satisfied with a 1‐point‐improvement (e.g., from “severe” to “moderate”) in their most severe symptom. This translated into an MCID range for CSMS 0–6 of −0.23 to −0.21 points or −17% to −16%. Furthermore, a −0.34 point difference in RQLQ(S) compared to placebo was justified as clinically meaningful based on Phase III data from 2 registered SLIT grass tablets. Using this RQLQ(S) threshold as an anchor, an MCID of CSMS 0–6 of −0.21 points (−16%) was derived using RESONATE. Conclusions Both patient feedback and RESONATE results support an average MCID of −0.22 points on the CSMS 0–6 scale and −16% on a composite primary endpoint scale, providing minimal thresholds to be achieved after AIT compared to placebo to conclude a positive Phase III trial outcome.
Longitudinal analysis of humoral and cellular immunity in SARS-CoV-2 exposed families
2025-07-18

Abstract Identification of previous SARS-CoV-2 infection typically relies on serology, yet T-cells play a key role in the adaptive immune response against SARS-CoV-2. Here, we investigated in parallel the SARS-CoV-2-specific as well as endemic human coronavirus-specific humoral and cross-reactive cellular responses in children and adults. We analyzed clinical data and blood samples from a family cohort of 96 children and 144 adults at 3–4 and 11–12 months after their first contact with SARS-CoV-2. Humoral response was assessed by a multiplex immunoassay with high sensitivity and specificity (MULTICOV-AB). Cellular responses were analyzed by IFN-γ ELISPOT using four different established epitope compositions (ECs) to discriminate between SARS-CoV-2 specific and HCoV cross-reactive T-cell responses. While the majority of adults had a combined serological and T-cell response, relatively more children had a T-cell response alone rather than a combined response. The magnitude of the T-cell response correlated with symptoms and the humoral response. In addition, SARS-CoV-2 infection significantly boosted the endemic coronavirus-specific cellular response. Overall, our data suggest discordant humoral and cellular responses, reflecting either abortive infection, cellular sensitization with rapid viral clearance or rapid antibody waning or a combination of these phenomena. Restricting epidemiologic analysis to SARS-CoV-2 serological data may underestimate rates of infection with or at least exposure to SARS-CoV-2 in children.
Inference generation in older adults: Comparing pictorial and textual comprehension in the context of cognitive decline.
2025-07-18

Narrative comprehension, a cognitive skill essential for social participation, relies on a range of abilities, including memory and inference-making. While aging-related cognitive changes are well-documented, research on narrative comprehension in aging populations yields mixed findings, underscoring the importance of this study. This preregistered study examines how age, education, and presentation format (i.e., the narrative's codality: pictorial vs. textual) influence inference generation in older adults (N = 143, ages 62-86 years). Participants were presented with pictorial and textual stories consisting of three panels, with the second panel replaced with a blank panel. Their task was to comprehend the stories and determine whether the inferences provided for the missing event were correct or incorrect. Results reveal that pictorial narratives were better comprehended than textual ones; however, this advantage attenuates with increasing age. Contrary to expectations, narrative comprehension was largely resilient to age-related declines, as neither age nor education significantly impaired performance. Exploratory analyses tested the influence of protective (e.g., physical and mental activity, companionship) and risk factors (e.g., depression, anxiety, chronic pain, stress, and poor sleep) but found no significant impact on comprehension. Notably, narrative comprehension correlated with memory performance but not with other cognitive abilities, underscoring its specificity within the broader cognitive domain. These findings highlight the stability of narrative comprehension across media and aging, while also suggesting a narrowing pictorial advantage with age. Implications for existing cognitive theories and future research directions are discussed.
High-field fMRI at 7 Tesla reveals topographic responses tuned to number in the developing human brain
2025-07-18

In the adult brain, hemodynamic responses to visually presented numerosities reveal receptive field-like tuning curves in topographically organized maps across association cortices. It is currently unknown whether such tuned topographic responses to numerosities can also be detected in the developing brain. Here we conducted a 7 Tesla fMRI experiment in which we presented a large set of visual dot displays to children and adults. We found that developing hemodynamic responses indeed already revealed logarithmic Gaussian tuning to quantitative information in children. Remarkably, tuning models explained comparable amounts of variance in children and adults. In most subjects, six bilateral cortical maps consistently exhibited topographic responses to numerosities. The present study goes beyond previous work by uncovering a population code for quantity detection in individual developing human brains. Our work lays a foundation for a model-based neuroimaging approach to individual cognitive differences in the context of developmental dyscalculia and mathematical giftedness.
Flexible use of multimodal communicative strategies in adult chimpanzees (Pan troglodytes)
2025-07-18

<title>Abstract</title> Human communication is remarkable for its flexibility, a trait largely reflected in its multimodal nature and shared to some extent with nonhuman primates. Although individual differences in social behaviour have known evolutionary implications, their role in shaping primate communication remains largely unexplored. This study adopts a multimodal framework to partition variation in chimpanzees’ use of multicomponent and multisensory communicative strategies into socio-environmental, between-individual, and within-individual sources. Results showed that research setting and signaller’s sex affected communicative expression. Importantly, we also detected consistent between-individual differences in both strategies, independent of age, sex, or setting. While only multicomponent signal use was predicted by behavioural context at the population level, only for the use of multisensory acts did individuals vary in how they adjusted to context. These findings reveal profound flexibility in chimpanzee communication, highlighting individual-specific patterns and supporting a gradual evolutionary pathway toward the complexity of human multimodal communication.
Influence of ATXN2 intermediate CAG repeats, 9bp duplication and alternative splicing on SCA3 pathogenesis
2025-07-19

Abstract Spinocerebellar ataxia type 3 (SCA3) is a neurodegenerative disease whose exact disease pathogenesis is not yet fully understood. We performed a genetic in-depth analysis of ataxin-2 ( ATXN2) , a gene that has already been described as a modulator of neurodegenerative diseases. We focused on the influence of an intermediate CAG repeat, a 9bp duplication (9bp), and isoform expression of ATXN2 on the pathogenesis of SCA3. Clinical and genetic data from a large European SCA3 cohort (total 390 probands) were analyzed. Fragment analyses were performed to determine the cytosine-adenine-guanine (CAG) repeat length and the 9bp duplication in ATXN2 . RNA sequencing was performed on blood and cerebellum to evaluate ATXN2 isoform profile. Cell culture and SCA3 mice were used to investigate the influence of intermediate ATXN2 length on ataxin-3 protein abundance, aggregation, and cell viability. SCA3 carriers with an intermediate ATXN2 repeat presented a significant increase in non-ataxic symptoms. A greater age at onset and faster disease progression were found in SCA3 carriers with a 9bp duplication. Co-expression of ATXN2 and ATXN3 in cell models revealed an influence of ATXN2 on ataxin-3 abundance and aggregation patterns. Determination of soluble ATXN2 abundance demonstrated a significant genotype-independent reduction in mouse brain. Aggregate analyses indicated that ataxin-2 is not co-localized with ataxin-3-containing aggregates. Our comprehensive genetic study confirmed ATXN2 as a modulator of SCA3 pathogenesis, including onset and presence of clinical symptoms. For the first time, the ATXN2 isoform profile was compared in blood and cerebellar tissue, revealing a unique profile depending on the genotype and tissue. Here, a significant higher expression of ATXN2 splice variant type I in blood and significantly lower expression in cerebellar tissue were found compared to ATXN2 splice variant type II. Molecular and biochemical analyses in SCA3 mice and cell culture provide further evidence on mechanistic aspects, including differences in protein abundance and co-aggregation propensity. In summary, our study provides new insights into the modulatory effects of ATXN2 on SCA3 pathogenesis. Graphical Abstract
Medin drives Aβ40 to adopt Aβ42-like fibril polymorphs in vitro
2025-07-20

Abstract Medin, a vascular amyloid derived from MFG-E8, is the most prevalent form of localized human amyloid and co-localizes with Aβ in Alzheimer’s disease and, in particular, cerebral amyloid angiopathy (CAA). While it was shown that medin can promote Aβ aggregation, it remains unclear whether this amyloid-amyloid interaction affects the structure of the resulting fibrils. Here, we investigate how medin modulates Aβ40 fibril assembly in vitro using cryo-electron microscopy, aggregation kinetics, and immunogold electron microscopy. We show that medin accelerates Aβ40 aggregation, co-assembles into hybrid fibrils, and modulates fibril morphology. Cryo-EM analysis reveals two fibril populations: one corresponding to a previously described in vitro Aβ40 morphology, and a second, previously unobserved polymorph with Aβ42-like features, including a structured N-terminus and a compact hydrophobic C-terminal core. The presence of a peripheral, unresolved cryo-EM density near the fibril surface suggests that the new polymorph is stabilised through heterotypic interactions, yet the atomic details remain unresolved, likely due to substantial structural heterogeneity. Rather than representing a limitation, this highlights how not all determinants critical for fibril assembly are necessarily ordered or resolvable in the final fibril structure, reflecting the inherent dynamic and heterogeneous nature of amyloid interactions. Our findings provide structural evidence that heterotypic co-aggregation can redirect Aβ40 into distinct conformational states and suggest that dynamic or transient interactions contribute to fibril polymorphism beyond what can be fully captured in static structural models.
Associations between digital speech features of automated cognitive tasks and trajectories of brain atrophy and cognitive decline in early Alzheimer's disease
2025-07-20

Background Speech-based features extracted from telephone-based cognitive tasks show promise for detecting cognitive decline in prodromal and manifest dementia. Little is known about the cerebral underpinnings of these speech features. Objective To examine associations between speech features, brain atrophy, and longitudinal cognitive decline in individuals at risk for Alzheimer's disease (AD). Methods Healthy volunteers, individuals with subjective cognitive decline, and those with mild cognitive impairment completed phonebot-guided semantic verbal fluency (SVF) and 15-word verbal learning task (VLT). Speech features were automatically extracted, and a global cognitive score (SB-C score) was computed. We analyzed data from 161 participants for cognitive trajectories, 141 for cross-sectional brain atrophy, and 102 for longitudinal brain changes. Analyses were conducted using multiple linear regressions, mixed-effects models, and voxel-based morphometry. Results The SB-C score was associated with bilateral hippocampal volumes, SVF features were primarily associated with left hemisphere regions, including the inferior frontal, parahippocampal, and superior/middle temporal gyri ( p uncorr &lt; 0.001). SB-C score, SVF correct counts, and VLT delayed recall were associated with atrophy rates in the hippocampal/parahippocampal gyrus and left middle/inferior temporal gyri ( p FDR &lt; 0.05). These features were also associated with cognitive decline assessed via Preclinical Alzheimer's Cognitive Composite 5, SVF, and Wordlist learning delayed recall ( p FDR &lt; 0.01). Word frequency and temporal cluster switches showed varying associations with cognitive trajectories. Other features did not show robust associations. Conclusions In this study, we highlight the potential of digital speech features for identifying brain atrophy and cognitive decline over time in at-risk AD populations.