Gait & Posture

PurposeQuantification of walking function, including joint motions, ground reactions, and joint loads, outside the lab is a growing research area. Because only joint motions can currently be measured outside the lab, researchers are utilizing tracking optimizations of walking to estimate associated ground reactions and inverse dynamic joint loads. However, foot-ground contact models used in such optimizations have been generic rather than personalized, which may limit the accuracy of estimated ground reactions and joint loads. This study compares the predictive capabilities of generic versus personalized foot-ground contact models. MethodsGeneric and personalized foot-ground contact models were evaluated in calibration and tracking optimizations performed using experimental walking data collected from three subjects in varying states of health. Foot-only calibration optimizations evaluated how well both models could reproduce experimental ground reaction and foot motion data while tracking both types of data simultaneously, while whole-body tracking optimizations evaluated how well both models could reproduce experimental ground reactions, joint motion, and joint load data while tracking only experimental joint motion data and achieving dynamic consistency. ResultsFor all three subjects and both types of optimizations, personalized foot-ground contact models reproduced experimental ground reaction, joint motion, and joint load data more accurately than generic foot-ground contact models. ConclusionPersonalized foot-ground contact models can improve the accuracy with which ground reactions and joint loads can be estimated via tracking optimizations of walking using only experimental motion data as inputs. Personalized models require little time and effort to calibrate using freely available software tools and should improve the accuracy of predictive simulations of walking as well.

Advanced footwear technology (AFT) shoes incorporate increased sole thickness and compliant midsole materials that may alter running biomechanics. While these effects have been widely studied during level running, little is known about how sole thickness influences running style and stability during uphill running. This study examined the effects of two AFT shoes differing in sole thickness (35 mm-AFT35; 50 mm-AFT50) and a traditional control shoe (27 mm-CON27) on running style and stability during uphill running. Seventeen experienced male runners performed treadmill running at a 10% incline at 6.5 and 10 km/h in three shoe conditions. Running style was assessed using duty factor, normalized step frequency, center-of-mass oscillation, vertical and leg stiffness, and lower-limb joint kinematics. Running stability was evaluated using local dynamic stability via the maximum Lyapunov exponent and detrended fluctuation analysis of stride time. Duty factor and normalized step frequency did not differ between shoes. However, AFT shoes showed greater center-of-mass oscillation (p = 0.004), lower vertical stiffness (p = 0.022) compared to CON27. Joint kinematics revealed significant shoe effects at the ankle (p = 0.001), particularly increased dorsiflexion and eversion in AFT conditions. Running stability showed only minor changes. Local dynamic stability differed at the trunk (p = 0.027), with reduced stability in AFT50 compared with CON27 (p = 0.006), while global stability remained unchanged. No shoe x speed interactions were observed for any variable. Overall, uphill running style and stability remained largely preserved across shoe conditions, suggesting that sole thickness alone had limited influence.

Age- and disease-related vestibular decline can cause dizziness and postural instability, motivating interventions such as noisy galvanic vestibular stimulation (nGVS). nGVS is commonly delivered at "subsensory" amplitudes and explained by stochastic resonance, yet because galvanic stimulation directly modulates vestibular afferents, even imperceptible currents may also exert deterministic effects on balance. This study examined whether low-amplitude nGVS (<1 mA), as typically used in stochastic resonance paradigms, directly influences postural behavior through stimulus-response coupling. Twenty healthy young adults stood on a force plate with feet together and eyes closed on either a rigid surface or 10-cm foam. In randomized order, they completed 300-second trials with band-limited (0-30 Hz), zero-mean nGVS at {+/-}0, 0.1, 0.2, 0.3, 0.5, and 0.7 mA. Coupling between the stimulation waveform and mediolateral ground-reaction force was assessed using coherence and time-cumulant density. Mean coherence was significant mainly at higher amplitudes (0.5-0.7 mA) on both surfaces, whereas time-cumulant density identified significant time-locked vestibular-evoked response components at much lower amplitudes, down to 0.1 mA. These included an early response around 135-155 ms and a later, prominent response around 360-410 ms. Individually, significant coherence was common at 0.5-0.7 mA (15-19 of 20 participants), while cumulant-based responses appeared in some participants even at 0.1 mA. Responses were clearer on foam, consistent with greater vestibular reliance when somatosensory input is less reliable. Overall, low-amplitude nGVS can entrain postural output, suggesting that balance changes during "subsensory" stimulation may reflect both stochastic-resonance-like effects and deterministic vestibular drive, underscoring the need to quantify coupling alongside performance outcomes.

BackgroundAlthough neurogenic orthostatic hypotension (nOH) is a common and debilitating feature of multiple system atrophy (MSA), little is known about the burden of symptoms in the real world. ObjectivesTo design and conduct a cross-sectional community-based research survey targeting patients with MSA, with and without nOH. MethodsWe recruited patients with MSA to complete an anonymous online survey covering three core themes: 1) timely diagnosis, 2) nOH pharmacotherapy and refractory symptoms, and 3) confidence in physician knowledge. Responses were grouped by pre-specified diagnostic certainty levels. Relationships between symptoms, function, and pharmacotherapy were assessed using univariate and multivariate methods. ResultsWe analyzed 259 respondents with a self-reported diagnosis of MSA (age: M=64.38, SD=8.09 years; 44% female). In total, 42% also had a diagnosis nOH; 40% had symptoms highly suspicious of nOH, but no diagnosis; and 21% reported having never had their blood pressure measured in the standing position at a clinical visit. Treatment with a pressor agent was independently associated with the presence of other symptoms of autonomic failure. Each additional nOH symptom reported increased the odds of requiring pharmacotherapy by 18%. Yet, despite anti-hypotensive medication use, 97% of patients reported limitations in their ability to bathe, cook, or arise from a chair/bed with 76% needing caregiver support for refractory nOH symptoms. ConclusionsThis cross-sectional representative sample shows nOH is underrecognized and undertreated in MSA patients, leading to substantial functional limitations. It is our hope that these findings are leveraged for planning future trials and advocating for better treatments.

BackgroundPatients who have undergone Anterior Cruciate Ligament Reconstruction (ACLR) have a 6-24% chance of either re-tearing or having subsequent knee surgery. To date there have been no practical validated risk prediction models that can be easily implemented into clinical workflow for re-injury risk. Micro-Doppler radar (MDR) provides a promising solution. ObjectiveThe purpose of this study was to investigate the predictive ability of MDR to identify persons with a previous ACLR relative to an age and sex matched healthy control. MethodsACLR patients (n=81) and controls (n=100) performed drop box jump, sit to stand (STS), and walking trials as MDR signatures were collected. A 1D Convolutional Neural Network was developed to evaluate each activity individually followed by the development of a fusion model validation using all three activities. ResultsThe STS model individually achieved the highest overall accuracy of 82.3%, with a sensitivity of 71.6% and specificity of 91.0%. The fusion model using all activities achieved a peak overall accuracy to detect ACLR of 86.2%, 80.3% sensitivity, and 91% specificity. ConclusionsCurrently, there is no clinically validated, efficient approach to objectively evaluate human motion at the point of care. When coupled with machine learning, MDR accurately differentiates ACLR from control groups by identifying complex biomechanical asymmetries, with classification performance comparable to or exceeding that of motion capture. Future research is needed to determine if MDR can be used in conjunction with risk prediction modeling. Key pointsMicro-Doppler radar provides a promising new solution to identify important human motion asymmetries in clinical settings. Here we evaluated a group of patients who have a history of Anterior Cruciate Ligament reconstruction versus a control group. Simple movements performed in the presence of the micro-Doppler radar system were used to identify the 2 groups with accuracy comparable or superior to motion capture systems.

ObjectiveUnlike several other fields of healthcare, little is known about the size of therapist effects on patient outcomes following rehabilitation for musculoskeletal conditions. We aimed to estimate the proportion of variance in patient outcomes from a structured rehabilitation program explained by therapist effects. MethodsFor our observational cohort study we accessed data from the national multicentre Good Life with osteoArthritis in Denmark (GLA:D) osteoarthritis management program. Analyses included 23,021 consecutive eligible adults with hip or knee osteoarthritis (mean (SD) age 65.0 (9.8) years, 71% female) treated by 657 therapists between October 2014 and February 2019. The primary outcome was [&ge;]30% reduction in pain intensity on 0-100 VAS at 3 months. Therapist effects were estimated as the variance partition coefficient (intra-class correlation coefficient (ICC)) from two-level random intercept logistic regression models before and after adjusting for patient-level case-mix factors and therapist-level characteristics (number of patients treated, days since therapist certification). Analyses were repeated for a range of secondary outcomes using multiply imputed data and complete-case analysis. Results52% of patients reported a [&ge;]30% reduction in pain intensity on 0-100 VAS at 3 months. In the null model the ICC was 0.007 (95%CI: 0.005, 0.009), which changed little after adjusting for patient- and therapist-level covariates. Upper confidence limits for ICC estimates across all secondary outcomes in multiply imputed and complete case analyses were less than 0.03. ConclusionsIn a nationally implemented osteoarthritis management program delivered by trained healthcare professionals, therapist effects made a minimal contribution to variation in patient outcomes. KEY MESSAGESO_ST_ABSWhat is already known on this topicC_ST_ABS Therapist effects - defined as the effect of a given therapist on patient outcomes as compared to another therapist - have been observed in several fields of healthcare and have important consequences for selection, training, and service improvement. In musculoskeletal rehabilitation five previous studies suggest that 1-12% of variation in patient-reported outcomes may be attributable to therapist effects, but these estimates were based on relatively small datasets resulting in substantial uncertainty. What this study addsOur cohort study analysed registry data from 2014-2019 on 23,021 patients and 647 trained therapists from the nationally implemented GLA:D structured osteoarthritis management program in Denmark. We found that therapist effects accounted for less than 3% of total variation in patient-reported pain and quality of life outcomes 3 months after beginning the program How this study might affect research, practice, or policyOur findings suggest that contextual factors that relate to therapist effects - therapist characteristics or therapist-patient interaction and alliance - make a minimal contribution to variation in patient outcomes from this structured, group-based rehabilitation intervention. Any contextual effects must be attributable to alternative sources, e.g. patient expectations, intervention setting.

An increasing number of studies highlight the role of saccadic remodulation in compensatory mechanisms following vestibular injury, and the reappearance of SHIMP saccades correlates with symptom improvement measured by the Dizziness Handicap Inventory (DHI). To investigate the influence of attentional processes and working memory on visuo-vestibular interaction, three independent but interrelated experiments were conducted. In the first two experiments, healthy subjects and patients with unilateral or bilateral vestibular deficits underwent vHIT in SHIMP mode and the Functional Head Impulse Test (fHIT), performed first separately and subsequently simultaneously. Mean latency and clustering of SHIMP saccades, together with Landolt C recognition rates, were analyzed. Differences between separate and combined protocols were assessed, and, in patients, correlated with symptom severity measured by the DHI, to determine whether the near-simultaneous execution of tasks mediated by shared parietal cortical substrates influenced performance. In the third experiment, vHIT in HIMP mode and fHIT were performed using separate and combined protocols to evaluate whether recognition-related cognitive load affected recovery saccade latency and clustering. Results suggest that visual recognition modulates visuo-vestibular interaction, supporting integrated dual-task protocols for ecological balance assessment and helping explain clinical discrepancies.

Parkinson's Disease (PD) is a complex neurodegenerative disorder that manifests through systemic, large-scale physiological reorganizations. While research often focuses on region-specific neural changes, there is a growing need for multidomain approaches to capture the complexity of the disease and its clinical heterogeneity. This study proposes an analytical pipeline to evaluate Brain-Heart Interplay (BHI) as a novel systemic biomarker for neurodegeneration and healthy ageing. In this study we assessed BHI across three open-source datasets (EEG and ECG signals). We compared Healthy Young, Healthy Elderly, and PD patients in resting state to investigate the effects of ageing and cognitive performance. Additionally, we studied BHI trends in PD patients in the moment of freezing of gait (FOG). Methodologically, brain network organization was quantified using coherence-based EEG connectivity and graph theory, while heart activity was analyzed through Poincare plot-derived measures of cardiac autonomic activity. The coupling between these two systems was measured using the Maximal Information Coefficient to capture linear and non-linear dependencies between global cortical organization and cardiac autonomic outflow. The results demonstrate that BHI is a sensitive biomarker for detecting early multisystem dysfunction in both neurodegeneration and ageing. Furthermore, the identification of specific BHI trends during FOG onset suggests new opportunities for understanding the physiological mechanisms driving motor complications in PD. Our proposed pipeline provides a guiding tool for large-scale physiological assessment in clinical research.

This cross-sectional derivation and internal validation study aimed to develop and internally validate a clinical triage scoring system (CTSS) for field-based identification of collegiate athletes requiring priority intervention for lumbopelvic-hip (LPH) dysfunction. A total of 864 collegiate athletes (mean age 21.3 {+/-} 2.4 years; 80.8% male) were recruited from 10 universities. Participants underwent standardized assessments including demographic characteristics, clinical history, and LPH functional testing. Using an expert-adjudicated binary reference standard (priority intervention vs self-management), a multivariable logistic regression model was developed to derive the weighted CTSS. Model performance was evaluated using discrimination, calibration, and decision curve analysis (DCA), and internal validation was performed using 1,000 bootstrap resamples. Of the 864 participants, 463 athletes (53.6%) were classified as requiring priority intervention. The final 14-factor CTSS comprised 12 positive-weight predictors, such as localized LPH pain, muscle weakness, and higher body mass index, and 2 negative-weight predictors, positive Lasegues sign and hamstring weakness, which functioned served as safety-related modifiers. The model demonstrated acceptable discrimination (AUROC = 0.851, 95% CI: 0.824-0.876), with minimal optimism (optimism-corrected AUROC = 0.842) and excellent calibration (calibration slope = 1.000; calibration intercept = 0.000). A total score of [&ge;]9 was identified as the optimal threshold, yielding a sensitivity of 84.4% and specificity of 71.8%. DCA showed greater net benefit than treat-all and treat-none strategies across clinically relevant threshold probabilities (20%-50%), with a net benefit of 0.319 at a 50% threshold probability. The CTSS may provide a pragmatic field-based triage tool to support early identification of athletes who may require priority intervention, although external validation is needed before broader implementation in sports medicine settings.

Introduction Cervical spondylotic myelopathy (CSM) surgery is frequently associated with residual neurological deficits, partly due to unrecognized dynamic spinal cord compression on conventional MRI. Current static imaging may miss position-dependent stenosis, resulting in insufficient or inappropriate decompression. This study aims to evaluate whether dynamic MRI-guided individualized surgery improves neurological outcomes compared to conventional MRI-based planning. Objectives This study aims to examine the association between dynamic MRI-guided surgical planning and neurological recovery in cervical spondylotic myelopathy, and to evaluate its role in identifying responsible segments, avoiding excessive surgery, and improving clinical outcomes. Methods This single-center retrospective cohort study will include 300 patients who underwent cervical spine surgery between January 2020 and December 2025 at the First Affiliated Hospital of Guangxi University of Chinese Medicine. Patients will be categorized into the dynamic MRI-guided group (n=150) or conventional MRI-based group (n=150) based on preoperative imaging modality. 1:1 propensity score matching will be performed using age, sex, BMI, disease duration, baseline mJOA score, and number of compressed segments. The primary outcome is the rate of improvement in the mJOA score at 6 months postoperatively. Secondary outcomes include VAS, NDI, reoperation rate, and time to first complication. Between-group comparisons will use t-tests/Mann-Whitney U tests for continuous variables, {chi}{superscript 2} tests/Fisher's exact tests for categorical variables, and Kaplan-Meier estimates with the log-rank test for time-to-event outcomes. A two-sided P<0.05 will be considered significant. Analyses will be performed using R software (version 4.4.1). Ethical approval was obtained from the Medical Ethics Committee of the First Affiliated Hospital of Guangxi University of Chinese Medicine (Approval No. 2025-080-KY-01) from February 06, 2026 to February 05, 2027. Expected outcomes We hypothesize that dynamic MRI-guided surgical planning will improve neurological recovery and decompression accuracy in cervical spondylotic myelopathy, providing evidence for optimized preoperative imaging and precision spine surgery.

Chronotype reflects individual circadian preference for timing of sleep, wakefulness, and peak performance and has been linked to variability in prefrontal cognitive function across the day. Whether chronotype independently relates to dual-task gait cost (DTC) and whether this relationship differs by cognitive task domain is unclear. Sixty-nine healthy young adults (37 female; mean age 21.3 years) completed the Morningness-Eveningness Questionnaire (MEQ). Spatiotemporal gait parameters were recorded with three-dimensional motion capture during single-task walking and three dual-task conditions: backward word spelling (5LWB; phonological), serial subtraction by seven (SS7; arithmetic), and reverse month recitation (RMR; sequential). DTC was calculated for eight gait parameters. Condition differences were assessed with nonparametric tests and post-hoc comparisons. Multiple linear regression, adjusting for age, sex, BMI, and baseline gait velocity, tested the independent association between MEQ score and mean velocity DTC; exploratory Spearman correlations examined other parameters. SS7 produced the largest mean velocity DTC (-12.76%), significantly greater than 5LWB (-7.95%; p = 0.002) and RMR (-9.57%; p = 0.021). MEQ score independently predicted mean velocity DTC in 5LWB ({beta} = -0.51, p < 0.001, R{superscript 2} = 0.269) and RMR ({beta} = -0.55, p = 0.004, R{superscript 2} = 0.222), indicating greater morningness associated with better gait-speed preservation under cognitive load; the SS7 association was not significant ({beta} = -0.33, p = 0.071). Exploratory correlations showed MEQ-DTC associations across 7/8 parameters in 5LWB, 4/8 in RMR, and 3/8 in SS7. Chronotype is independently associated with dual-task gait cost in a task-domain-specific manner, with stronger effects for phonological and sequential tasks than for arithmetic processing. The SS7 condition yielded the largest interference but weakest chronotype modulation, suggesting arithmetic dual-task disruption may be less sensitive to circadian arousal. Fixed testing time and cross-sectional design warrant within-subject, multi-timepoint studies to confirm chronotype effects separate from time-of-day confounds.

The theory of island biogeography and its trophic extensions predict that both species richness and food-web complexity should increase with increasing ecosystem surface area. Accordingly, Species-Area Relationships (SARs) and Network-Area Relationships (NARs) are often observed to be positively-sloped, an observation that came to be considered as a law, and on which rest many area-based conservation plans for biodiversity. However, our mechanistic understanding of the driving mechanisms of SARs and NARs slopes remains limited, undermining our ability to predict how biodiversity will respond to habitat gain or loss. We show in 180 rural ponds sampled across five years that invasive alien predators reversed the SAR and NARs from positive in invader-free ponds, to negative in invaded ponds. Relationship reversal resulted from a higher prevalence of invasive alien predators driving magnified prey extinctions and simplified food webs in larger ponds. The ability of invasive alien predators to reverse SAR and NARs presumably reflected disproportionately high predation rates combined with a low sensitivity to prey extinction conferred by a wide trophic generalism. In a world where virtually all ecosystems face biological invasions, omnipresent invasive alien predators stress the pivotal role played by predation in shaping biocomplexity-area relationships, and highlight a growing need to preserve small ecosystems where invasive alien predators are less prevalent.

Cellular organelle content is fairly constant within a given cell type. This is accomplished in part by ensuring equitable organelle partitioning during division. Much of our understanding of organelle inheritance has come from investigating cells that divide in half producing two daughter cells. However, more elaborate division strategies that give rise to multiple daughters are not uncommon in nature. Here, we present the first characterization of organelle inheritance in a fungus that grows by multi-budding, producing several (2-20) daughter cells in a single cell cycle. We find that some organelles (mitochondria and ER) are evenly delivered to all growing buds, while others (vacuole and peroxisomes) are more variably inherited. We discuss the implications of even and uneven inheritance for this polyextremotolerant fungus capable of growing in dynamic, and diverse, environments.

Toxoplasma gondii is a widespread human pathogen that has multiple, clinically relevant stages in its complex life cycle, including fast-replicating tachyzoites and latent bradyzoites. Bradyzoite differentiation is triggered by stress responses that lead to changes in transcription, translation, and metabolism. Two aspects of this process are addressed in this report: first, whether proteins that play roles in bradyzoite differentiation are specific to T. gondii and other bradyzoite-forming parasites of the Sarcocystidae family, and second, whether new bradyzoite differentiation proteins can be identified in T. gondii. To answer these questions, a phylogenetic approach was used, comparing proteomes of select members of the Sarcocystidae family that form morphologically different bradyzoite cysts and members of the Eimeriidae family that do not form cysts. This approach resulted in 8 distinct clusters of T. gondii proteins that reflected different conservation patterns; for example, one cluster showed conservation among all organisms, while another showed conservation in bradyzoite cyst-forming organisms. Known T. gondii proteins involved in bradyzoite differentiation were found in all clusters, indicating that this process uses both highly conserved pathways as well as bradyzoite-specific pathways. Importantly, the cluster containing proteins that are conserved in bradyzoite-forming organisms contained several known regulators of bradyzoites, and will be a source for identifying novel T. gondii proteins that are involved in bradyzoite differentiation.

AO_SCPLOWBSTRACTC_SCPLOWSpatially resolved characterization of nanomaterial (NM) distribution within cellular ultrastructure is essential for understanding NM fate and activity in biological systems. Volume electron microscopy (vEM) is uniquely positioned to address this challenge, yet fully documented quantitative pipelines that simultaneously segment NMs and cellular structures remain scarce. Here, an end-to-end analytical pipeline is presented based on the example of serial block-face scanning electron microscopy (SBF-SEM) data of tumor spheroids containing nanoparticles (NPs). A hybrid segmentation strategy is adopted: a fine-tuned Cellpose-SAM model for cells and nuclei, and an empirical Bayes approach for AuNPs. The fine-tuned model outperforms both the pre-trained baseline and benchmark experiments in Amira, and shows good generalization to 2D EM datasets of varying sample types, suggesting potential as a general-purpose segmentation model for electron microscopy. Full 3D reconstruction of NP distributions reveals preferential clustering in the perinuclear region, with a median nucleus-to-NP distance of 2.57 {micro}m and NM uptake spanning several orders of magnitude across cells. Furthermore, morphological analysis of segmented cells and nuclei using 3D shape descriptors and local curvature metrics provides quantitative access to features inaccessible from single sections. Together, these results establish a reproducible, open framework for the joint quantitative analysis of NM distribution and cellular morphology in vEM data.

This report identifies a bidirectional signaling axis connecting lipid metabolism to nuclear mechanotransduction, with the potential to control fatty acid/triglyceride metabolism. The sterol regulatory element-binding (SREBP) family of transcription factors control fatty acid, triglyceride and cholesterol synthesis and metabolism. The family consists of three members: SREBP1a, SREBP1c, and SREBP2, that are regulated by intracellular cholesterol levels and insulin signaling. The SREBP2-dependent control of the LDL receptor gene is a well-established target for cholesterol-lowering therapeutics and the activity of SREBP1c is an attractive target in metabolic disease. In the current report, we identify SYNE4 (nesprin-4), a component of the Linker of Nucleoskeleton and Cytoskeleton (LINC) complex, as a direct target of the SREBP family of transcription factors, and show that nesprin-4 in turn supports SREBP1c function. We identify functional SREBP binding sites in the human SYNE4 promoter and demonstrate that these are required for the sterol- and SREBP-dependent regulation of the promoter. Furthermore, we show that the endogenous SYNE4 gene is also regulated by SREBP1/2 and intracellular sterol levels. Interestingly, SREBP2 is responsible for the sterol regulation of the SYNE4 gene in HepG2 cells, while SREBP1 is the major regulator in MCF7 cells, demonstrating that diberent cell types use diberent SREBP paralogs to regulate the same promoter/gene. Importantly, we find that nesprin-4 is a positive regulator of SREBP1c expression and function in HepG2 cells and during the diberentiation of human adipose-derived stem cells. In summary, the current report identifies a novel regulatory interaction between lipid metabolism and the LINC complex. Importantly, we demonstrate that this signaling axis is bidirectional, forming a closed loop that has the potential to control SREBP1c activity and thereby fatty acid and triglyceride synthesis/metabolism. Based on our data, we propose that the nesprin-4-dependent regulation of SREBP1c could represent a novel therapeutic target in metabolic disease.

BackgroundTransposable elements (TEs) are repetitive genetic elements that can jump to new loci causing genome expansions, structural rearrangements, and can, ultimately, propel the evolution of genomes. Despite their significance, the role of TEs in the evolution of genomes and phylogenetic groups remains largely understudied in early diverging lineages. Further, the extent to which TE content varies across species is still an open question. Medusozoa, a group within Cnidaria encompassing jellyfish and hydroids, exhibits an exceptional diversity of life history strategies, body plans, and physiological capabilities. These characteristics, along with its early-diverging phylogenetic position, establish Medusozoa as an ideal system for investigating the composition and evolutionary history of TEs within the group. ResultsWe generated a custom repeat library built from annotations of 25 Medusozoan genomes and used it to characterize TEs, aiming to identify lineage-specific TE content and activity that may correlate with the diversity observed within the group. We found that repetitive element percentage and genome size varied considerably, with Hydrozoa exhibiting the most variation among classes in both respects. DNA transposons were the most prevalent TE classification in all but two genomes, averaging 28% of all genomes. Intra-genus comparisons revealed a surprising degree of differences in TE content. In the genus Aurelia, the expansion of a single DNA transposon superfamily accounted for much of the difference in repetitive element percentage between two species, whereas in the genus Turritopsis, a similar divergence resulted from the proliferation of multiple superfamilies. Interestingly, most genomes showed evidence of recent TE expansions, suggesting ongoing activity in many medusozoan species. ConclusionWe present the first comparative analysis of TEs across all medusozoan classes. Our results reveal class-specific TE dynamics and highlight cases of TE proliferations as lineages diverge. This research provides data on TE activity and diversity that can be used as a resource for future study and fills important gaps in our understanding of TEs in early diverging animal lineages.

Diabetes mellitus is characterized by chronic hyperglycemia and loss of pancreatic {beta}-cell function and mass. Current therapies focus on {beta}-cell protection and regeneration, led by GLP-1 receptor agonists. The G protein -subunit (Gs) acts as a key signaling node downstream of numerous GPCRs, integrating diverse signals that impact {beta}-cell mass and function. Elucidating the integrative role of pancreatic Gs signaling is thus crucial for understanding {beta}-cell biology. Our map of the pancreatic Gs-coupled GPCR landscape reveals sophisticated, cell-type-specific networks, positioning Gs as a central hub for intra-pancreatic communication. Previous studies in mice with {beta}-cell-specific or whole-pancreatic Gs deletion demonstrated reduced {beta}-cell mass, impaired insulin secretion, and glucose intolerance. The stronger phenotype in the whole-pancreas model--marked by -cell expansion and abnormal distribution--points to a crucial role for Gs in differential control of postnatal - and {beta}-cell proliferation. Here, we analyze the organ-wide consequences of Gs deletion using pancreas-specific Gs knockout mice (PGsKO). Consistent with prior findings, PGsKO mice exhibit reduced weight gain from four weeks and severe diabetes due to decreased {beta}-cell mass and concomitant -cell expansion. Furthermore, Gs loss induces profound architectural and functional defects in the exocrine pancreas, linked to YAP reactivation in acinar cells. Importantly, we observed attempted {beta}-cell regeneration in PGsKO mice. Although insufficient to reverse diabetes, our results delineate the full pancreatic phenotype that may facilitate these regenerative efforts and suggest that strategically biasing GPCR signaling network away from Gs could be a viable strategy to promote {beta}-cell regeneration from other pancreatic cell types. ARTICLE HIGHLIGHTSO_LIGs is a central signaling hub that integrates diverse GPCR inputs across pancreatic cell types, yet its organ-wide role remained poorly defined. C_LIO_LIWe addressed how pancreas-wide Gs deletion disrupts both endocrine and exocrine compartments, and whether regenerative programs are engaged. C_LIO_LIGs loss caused severe diabetes through {beta}-cell loss and -cell expansion, induced profound exocrine defects with YAP reactivation, and triggered attempted {beta}-cell regeneration from ducts and potentially other cell types. C_LIO_LIOur findings suggest that strategically biasing GPCR signaling away from Gs could promote regeneration from non-{beta}-cell sources, offering new therapeutic avenues for diabetes. C_LI

We have curated and annotated the topologic determinants for all human membrane proteins made at the endoplasmic reticulum (ER). This census of 4,863 proteins allowed us to systematically analyze the physical properties of their 20,546 TMDs and flanking soluble regions. Single-pass proteins house the majority of large exoplasmic and cytosolic domains, whereas multipass proteins overwhelmingly contain short loops and tails. All classes of transmembrane domains (TMDs) have positively charged cytosolic flanks, but negatively charged exoplasmic flanks feature primarily on TMDs inserted by Oxa1-family insertases. The TMD-pair, a topologic unit of two TMDs with a short exoplasmic loop, is the dominant building block of multipass proteins. TMD-pairs accommodate high-hydrophilicity and charge-containing TMDs crucial for multipass protein functions. We interpret these context-dependent TMD features in light of current mechanistic models for membrane protein biogenesis and function. Our findings have implications for the evolution of membrane proteomes and for engineering new membrane proteins.

BackgroundTau aggregation is the defining feature of tauopathies, however, the mechanisms by which distinct tau strains drive disease-specific responses remain unclear. Existing models largely rely on recombinant tau seeding or tau overexpression, which fail to capture the biochemical diversity of pathological tau. The aim of this study was to develop a robust and reproducible human cell-based model of disease-specific tau pathology and to use this model to determine how tau from unique diseases impact tau accumulation and lysosomal dysfunction. MethodsPatient-derived tau aggregates were enriched from post-mortem brain tissue obtained from sporadic Alzheimers disease (AD), Picks disease (PiD), progressive supranuclear palsy (PSP), and control cases using phosphotungstic acid precipitation. Patient-derived tau preparations were biochemically characterised by immunoblotting and mass spectrometry and normalised for tau content prior to seeding. Patient-derived tau aggregates were seeded into multiple human immortalised cell lines (SH-SY5Y, M03.13, U-87 MG, and U-118 MG cells) and iPSC-derived astrocytes. Tau seeding efficiency, aggregate morphology, and integrity of the autophagy-lysosomal pathway was assessed using quantitative imaging approaches. ResultsPatient-derived tau seeds retained disease-specific phosphorylation patterns and isoform composition and led to reproducible, dose-dependent insoluble tau accumulation in all cell lines tested. Despite equivalent tau input and similar background protein composition, PiD-derived tau had the most aggressive pathological signature, showing the highest number of tau aggregates per cell and inducing system wide disruptions in the autophagy lysosomal system including increased SQSTM1 puncta and lysosomal damage markers. Seeding with AD-derived tau led to a high number of tau aggregates per cell and more specifically depleted the lysosomal protease CTSD and uniquely co-seeded A{beta} pathology. Seeding with PSP-derived tau resulted in only a moderate number of tau aggregates per cell and uniquely caused increased lysosomal biogenesis. ConclusionsTogether, these results demonstrate that intrinsic properties of human tau strains drive disease-specific cellular responses and establish a scalable, physiologically relevant platform for dissecting tau-cell interactions and screening therapeutics across tauopathies.