Along the lines of neuronal global workspace theories, the paper hypothesizes that active neural signal regeneration in recurrent, re-entrant circuits could constitute an organizational basis for states of conscious awareness. In this view, brains are self-production systems that regenerate their own informational, signal states ("neural autopoiesis"). States of awareness themselves depend critically on sustained regeneration of sets of neural signals in local and global circuits. The set of regenerated signals at each moment determines the specific contents of consciousness. Two hypotheses are proposed. H1: Organizational closure and with it, awareness, is achieved when regenerative, self-production loops are completed, such that a stable set of signal productions is sustained. The organization of informational processes stabilizes and closes on itself. H2: Neural coding is critical for signal regeneration. Neural signals must be properly encoded in order for them to be regenerated and thereby affect the contents of awareness. In addition to simple signal suppressions at their points of origin, one means by which general anesthetic agents may abolish awareness is by scrambling neural signals. Rendering internal control signals incoherent by altering within- and across-neuron rate profiles and/or temporal patternings may disrupt signal regeneration in local and global circuits. The two hypotheses are agnostic with respect to neural coding. Our own signal-centric time-domain (TD) brain theory framework is presented to illustrate how signal regeneration could be mediated by local and global temporal codes and neural temporal processing networks. Similarities and differences between TD, global neuronal workspaces (GNW), recurrent processing (RP), integrated information (IIT) and predictive processing (PP) are discussed. Empirical testing will necessitate solving the neural coding problem at multiple system levels. This will involve investigating correlations and causal linkages between regeneration of tracked neural signals and states of awareness as well as between alternative candidate neural codes and the contents of awareness. Rhythm-tagged stimuli and high temporal resolution neural recordings are proposed to enable tracking of specific neural signals throughout the brain under conditions of waking vs. sleep vs. anesthesia, with masking and unmasking signal/noise levels. Some philosophical comments regarding organization as a potential basis for consciousness are made.
Climate change anxiety (CCA) has emerged as a significant psychological response to the global climate crisis. While prior research focuses on general populations, evidence derived from psychiatric clinical samples remains scarce. This study aims to investigate CCA levels and their associations with psychiatric symptoms, resilience, and disaster-related experiences among psychiatric outpatients. A cross-sectional survey was conducted on 528 psychiatric outpatients aged 18-64 years at a university hospital in South Korea. The participants completed the Korean version of the Climate Change Anxiety Scale, along with standardized measures of depression (Patient Health Questionnaire-9), anxiety (General Anxiety Disorder-7), somatic symptoms (Korean Version of Somatic Symptom Scale-8), and resilience (Brief Resilience Scale). CCA was analyzed as a continuous variable, and a high-CCA group was defined as participants in the top quartile. Group comparisons, correlation analyses, and hierarchical regression analyses were performed. The mean CCA score was 19.05 (standard deviation = 8.11), with 24.1% of the participants classified as exhibiting high levels of CCA; these elevated levels were significantly associated with greater depressive (r = 0.31), anxiety (r = 0.36), and somatic symptoms (r = 0.39) and lower resilience (r = -0.11). Patients with direct exposure to natural disasters reported significantly higher levels of CCA and greater psychiatric symptom severity, along with lower levels of resilience. In hierarchical regression analyses, somatic symptoms (β = 0.252, p < 0.001), anxiety (β = 0.194, p < 0.001), middle age (β = 0.194, p < 0.001), and cumulative disaster exposure (β = 0.133, p = 0.003) were significant factors associated with CCA, explaining 20.6% of variance. CCA among psychiatric outpatients is closely associated with broad emotional and somatic symptom burdens and decreased resilience. Instead of representing an isolated environmental concern, CCA may reflect underlying affective and physiological vulnerabilities exacerbated by cumulative exposure to climate-related stressors. These findings underscore the clinical relevance of climate-related distress and highlight the need for longitudinal studies and targeted interventions among vulnerable populations.
Intraosseous (IO) anaesthesia has emerged as an effective primary and supplemental technique for achieving profound pulpal anaesthesia during root canal treatment, particularly in mandibular molars. However, needle fracture during IO administration is an exceedingly rare complication with no established management protocol. A 29-year-old female presented with symptomatic irreversible pulpitis and symptomatic apical periodontitis in tooth #30 requiring non-surgical root canal treatment. A first-year postgraduate endodontic student administered intraosseous anaesthesia using the QuickSleeper® system (Dental HiTec, Cholet, France) with a 30-gauge, 16 mm Effitec needle and 4% Articaine with 1:100,000 Adrenaline. During needle retraction following an unsuccessful injection attempt, forceful manipulation resulted in separation and retention of the needle within the interdental bone between teeth #29 and #30. Needle position was confirmed with intraoral periapical radiograph and patient was informed. After administration of inferior alveolar nerve block, an envelope flap was elevated. Minimal osteotomy was performed to expose the needle head, and the intact separated needle was retrieved using the BTR pen (Broken Tool Remover, Cerkamed) via a loop/lasso technique. The surgical site was closed with interrupted 5-0 silk sutures. Root canal treatment for tooth #30 was completed in the two visits. A minimally invasive retrieval approach using the loop/lasso technique resulted in successful outcome without any postoperative complications.
Nightshift nurses commonly suffer from sleep disturbances and occupational stress due to irregular work-sleep rhythms. This Bayesian network meta-analysis (NMA) compared the efficacy of non-pharmacological therapies to identify optimal interventions for improving sleep and reducing occupational stress in night/rotating-shift nurses. Cochrane, Embase, PubMed, Web of Science, and CNKI were searched up to October 24, 2025. Studies were assessed for bias via ROB2. Primary outcomes were total sleep score and sleep duration; secondary outcomes included anxiety, depression, and fatigue scores. Bayesian NMA (R 4.5.2) calculated SMD (95% CrI) and SUCRA for intervention ranking. Eighteen studies involving 1,572 nurses were included. Sleep intervention program (SIP) appeared to be effective for optimizing total sleep score (SMD -0.80, 95% CrI [-1.2, -0.41]; SUCRA = 80.71%). Mindfulness training intervention (MTI) showed relatively good effectiveness in regulating sleep duration (SMD -1.0, 95% CrI [-1.4, -0.57]; SUCRA = 95.97%). Auricular plaster therapy (APT) appeared to be effective in alleviating depression (SMD -0.60, 95% CrI [-1.0, -0.17]; SUCRA = 84.60%). Rational emotive behavior therapy (REBT) showed superior efficacy for alleviating anxiety (SMD -3.0, 95% CrI [-3.6, -2.4]; SUCRA = 100%). Pure pelargonium essential oil (PPEO) demonstrated relatively good efficacy in relieving fatigue (SMD -0.70, 95% CrI [-1.2, -0.25]; SUCRA = 94.92%). SIP, MTI, APT, REBT, and PPEO appeared to be effective non-pharmacological interventions for optimizing nightshift nurses' total sleep score, regulating their sleep duration, and alleviating their depression, anxiety, and fatigue, respectively. Future well-designed studies are warranted to further validate the role of non-pharmacological therapies, particularly SIP and MTI, in regulating sleep among nightshift nurses. However, all findings were based on indirect evidence, which formed a star-shaped network with no closed loops. Therefore, the findings should be considered exploratory and hypothesis-generating, which are intended to provide preliminary guidance for future head-to-head comparative trials rather than establishing definitive clinical evidence. Clinical decisions should be made based on a comprehensive assessment that takes into account local resources, cultural context, and individual preferences of nurses. https://www.crd.york.ac.uk/PROSPERO/view/CRD420251180760.
Populus deltoides is a key species for industrial timber and ecological construction in temperate regions, where increasingly frequent and persistent heat waves pose serious challenges to its survival. However, the epigenetic mechanisms by which DNA methylation regulates environmental responses remain poorly understood. Here, whole-genome bisulfite sequencing and RNA-seq were performed on five P. deltoides genotypes grown in temperate and tropical regions. Results revealed that CG/CHG methylation stability is closely correlated with environmental sensitivity. Significant CG/CHG methylation variations may occur specifically in sensitive genotypes with large provenance-environment differences, thereby threatening the survival of P. deltoides by inhibiting the expression of key genes involved in life processes. CHH methylation variation may act as a potential epigenetic regulator of environmental adaptation. Promoter CHH-hypermethylation appears to represent a general response of P. deltoides under high-temperature and short-photoperiod (HS) stress, potentially regulating the expression of 56 genes to activate Ca2+ influx and heat shock proteins, repressing auxin, cytokinin, and cell cycle pathways, thereby initiating stress-protective responses. PdeCNGC13, PdeARF6, PdeLOG3, and PdeHSP15.7 were identified as potential regulatory genes of HS adaptation that are associated with DNA methylation. The mechanism of PdeLOG3 may involve HS-induced CHH-hypermethylation at its PdeLOG3 promoter, which may be associated with suppressed expression, reduced dihydrozeatin levels, and growth. This effect was partially reversed by 5-Azacytidine administration, accompanying increased cytokinin synthesis, enhanced antioxidant capacity, and coinciding with alleviation of HS stress. Our work preliminarily reveals the molecular mechanisms underlying DNA methylation-associated environmental adaptation in poplar, providing potential genetic targets for breeding climate-resilient trees.
Selecting an appropriate mask is crucial for the success of continuous positive airway pressure (CPAP). Using a patient-centered approach, the purpose of this narrative review is to provide the clinician with the rationale to support the choice of the most suitable mask for the obstructive sleep apnea (OSA) patient that requires CPAP treatment. Despite the larger studies comparing nasal and oronasal masks being observational and potentially selection-biased, they suggest that nasal masks are associated with better objective and patient-reported outcomes. New technologies that use 3-D facial scanning and artificial intelligence have been developed to improve mask selection. Close follow-up combining in-person and telehealth-based models can detect mask-related adverse effects. Excessive leak is a common challenge during CPAP follow-up and may impair treatment adherence. The distinction between mouth and mask leak allows the use of adequate corrective strategies to control leak that may improve CPAP adherence and avoid unnecessary mask changes.
Early and accurate prediction of rheumatoid arthritis (RA) is critical for improving patient prognosis; however, existing approaches rely excessively on single autoantibody markers, neglect the systematic predictive value of routine hematological parameters, and lack mechanistic interpretability. In this study, 500 patients attending a rheumatology outpatient clinic were enrolled, and 29 routine laboratory features were collected. Anti-CCP positivity and early RA onset within 12 months were defined as dual binary prediction targets. Five traditional machine learning models (logistic regression, random forest, gradient boosting, SVM, and KNN) and five deep learning models (MLP, ResNet, Transformer, AE-Classifier, and TCN) were systematically compared using six evaluation metrics: accuracy, AUC-ROC, F1-score, precision, recall, and Matthews correlation coefficient (MCC). A four-dimensional SHAP explainability analysis was subsequently applied to the best-performing deep learning model. Logistic regression achieved the best overall performance (Accuracy = 0.848, AUC = 0.857, F1 = 0.910, MCC = 0.441). Among deep learning models, the Transformer performed relatively well (AUC = 0.812), whereas ResNet and TCN exhibited severe class collapse (MCC ≈ 0). SHAP analysis identified ESR (Mean|SHAP| = 0.097) and CRP (0.090) as the most important positive predictive drivers, and albumin (ALB, 0.062) as the key protective factor, together forming a core biomarker triad for early RA risk prediction. Dependence plots further revealed the synergistic interaction between ESR and CRP, as well as a non-linear protective threshold effect of ALB. Individual waterfall plots confirmed close alignment between model decisions and clinical pathological mechanisms. The proposed machine learning pipeline based on routine laboratory parameters can effectively predict early RA risk, and the SHAP explainability analysis transforms the model "black box" into clinically readable decision rationale, providing evidence-based support for optimizing early screening strategies in rheumatology.
Aseptic processing remains one of the most challenging and closely scrutinized areas in pharmaceutical manufacturing. Using Redica Systems' global inspection and enforcement database spanning FDA, EMA/MHRA, and other PIC/S member agencies, this presentation analyzes compliance findings from 2022 to the present to highlight both persistent challenges and emerging risks in sterile manufacturing.Key themes include environmental monitoring and contamination control strategies, aseptic technique and human factors, sterilization validation, gowning and operator qualification, airflow visualization and smoke studies, and cleaning and disinfection effectiveness. We will also examine how regulatory expectations have shifted following the implementation of the revised EU GMP Annex 1, with particular attention to contamination control strategy and the adoption of barrier technologies.To illustrate these broader global trends, FDA enforcement serves as a case study. Sterility-related issues account for over 40% of production observations in 483s and over half of production deficiencies in Warning Letters. Inspections citing sterility issues were far more likely to escalate. Viewed alongside inspection findings from EMA and PIC/S agencies, these insights will give attendees a clear view of the compliance landscape and how global regulators are converging-or diverging-on expectations for sterile manufacturing.
This case report describes a patient with rapidly progressive organizing pneumonia accompanied by cavitary lesions, in whom concomitant nontuberculous mycobacterial (NTM) infection caused significant diagnostic difficulty. Initial imaging showed rapidly worsening pulmonary consolidation and nodules with cavitation, raising concerns for pneumonia, tuberculosis, fungal infection, or vasculitis. However, surgical wedge resection confirmed the diagnosis of organizing pneumonia, and bronchoalveolar lavage cultures subsequently yielded NTM. This case highlights that NTM-associated organizing pneumonia with cavitary lesions can closely mimic other infectious diseases as well as vasculitic disorders presenting with an organizing pneumonia pattern on imaging, leading to substantial diagnostic challenges.
Workforce stability remains a major challenge for sustainable healthcare systems. Retention research increasingly distinguishes between organizational conditions, professional identification, and mobility or place-related preferences. However, less is known about how these factors operate within closely related Central European contexts and in samples that include respondents connected to healthcare education and practice. This study examined whether workplace relationships and leadership, professional commitment, and place-related mobility preferences predict intention to stay in healthcare and compared these associations in the Czech Republic and Slovakia. A descriptive, correlational, cross-sectional study was conducted among healthcare students and professionals in the Czech Republic and Slovakia. The analytical sample included 2103 respondents, comprising 1011 participants from the Czech Republic and 1092 from Slovakia. Data were collected using an author-developed questionnaire focused on workplace relationships and leadership, professional commitment, place-related mobility preferences, and related aspects of the work and educational environment. Exploratory and confirmatory factor analyses were used to examine the latent structure of the instrument and assess reliability, followed by multiple linear regression and cross-national comparison. The final model supported three interpretable dimensions: workplace relationships and leadership, professional commitment, and place-related mobility preferences. In the Czech and Slovak samples, the regression models explained 23.2% and 23.3% of the variance in intention to stay, respectively. In the regression analyses, Q41 was used exclusively as the dependent variable and was not included in the professional-commitment predictor composite. Within the tested model, professional commitment showed the largest standardized association with intention to stay in both national samples, workplace relationships and leadership showed a significant but smaller association, and place-related mobility preferences were not statistically significant predictors. Although the omnibus country comparison reached statistical significance, differences in individual dimensions were trivial or very small, indicating substantial similarity between the Czech and Slovak samples. In these cross-sectional data, intention to stay in healthcare was more strongly associated with professional commitment than with workplace relationships and leadership or place-related mobility preferences. The findings should be interpreted with caution because the outcome was assessed using a single, conditionally worded item and because the sample included respondents connected to both healthcare education and practice. Nevertheless, the results suggest that retention strategies may benefit from combining improvements in organizational conditions with deliberate support for professional meaning, commitment, and identification with the healthcare role. The findings suggest that nursing managers, educators, and healthcare leaders should not rely solely on structural or logistical retention measures, such as staffing arrangements, geographic flexibility, or financial incentives. Although supportive workplace relationships and leadership remain important, the largest association with intention to stay was observed for professional commitment within the tested model. Retention strategies should therefore include systematic efforts to strengthen professional meaning, value congruence, identification with the healthcare role, mentoring, recognition, and supportive leadership practices. Nursing management interventions may be most effective when they create working and learning environments that reinforce professional commitment rather than addressing workplace conditions in isolation.
To present an up-to-date summary of the association between ocular shape and myopia. We systematically searched PubMed, Embase, Web of Science, the Cochrane Library, CNKI and Wanfang from June 2009 to September 2025 for cross-sectional and cohort studies examining the association between ocular shape and myopia (PROSPERO: CRD42024558271). The Newcastle-Ottawa Scale and the Agency for Healthcare Research and Quality were used to evaluate the quality of included studies. Thirty-four studies were included. Ocular growth appears relatively uniform in non-myopic eyes whereas myopic eyes tend to show non-uniform expansion. Greater myopia is associated with asymmetric changes in both anterior and posterior ocular shape. Highly myopic eyes frequently display spheroid shapes with equatorial pyriform contours and macular staphylomas, with more pronounced posterior deformities linked to a higher risk of myopic complications. Longitudinal evidence suggests that baseline ocular shape may be associated with subsequent ocular morphological changes and myopia progression. Ocular shape is closely associated with myopia and myopic retinopathy. Existing studies remain mostly observational and heterogeneous, with small sample sizes in some studies limiting causal inference and precluding meta-analysis. Future studies are needed to better understand the potential value of ocular shape in myopia control. CRD 42024558271.
Autism Spectrum Disorder (ASD) screening requires multimodal biomarkers to capture the heterogeneous neurological and behavioral phenotypes. Current screening approaches remain siloed across EEG analysis and conversational assessment, limiting integrated diagnostic architecture. Privacy-preserving machine learning frameworks for mental health screening are underdeveloped, particularly for multilingual deployment contexts. This paper presents NeuroCon-AutismNet, a candidate multimodal architecture integrating diffusion-regularized EEG synthesis, multilingual conversational screening, and formal differential privacy as architectural proof-of-concept. No diagnostic discrimination capability is claimed; all validation is scoped to synthetic evaluation. NeuroCon-AutismNet comprises four modules: (1) Temporal Diffusion Biomarker Generator (TDBG), a latent diffusion model over VAE-encoded 19-channel EEG; (2) Multilingual Affective Dialogue Screening Network (MADSN), a fine-tuned GPT-2-small module deployed in English, Spanish, and Hindi; (3) Neuro-Linguistic Fusion Transformer (NLFT), enforcing positional alignment as a design prior rather than learned cross-modal association; and (4) Adaptive Mixture-of-Experts Layer (AMEL-X) for entropy-regularized multimodal fusion. Formal (ε, δ)-differential privacy (ε = 1.0, δ = 1e-5) is verified via DP-SGD RDP composition (σ = 1.2, q = 0.0914, T = 550 steps, verified ε = 0.97). Privacy verification establishes architectural readiness for future real-data deployment; no real patient records are present in the training set. Within closed synthetic evaluation, held-out diagnostic AUC is 0.503 (95% CI: 0.487-0.519, DeLong p = 0.67), statistically indistinguishable from chance and the central limitation of this study. Two partial external benchmarks are provided. Spectral comparison against three independently published real ASD EEG studies yields Pearson r = 0.87 across five frequency bands; delta and alpha directions are reproduced, but theta and gamma reproduce poorly with large amplitude errors (delta MAE 14.79%, alpha MAE 11.57%). Expert evaluation of MADSN outputs by 50 annotators under single-blind protocol yields 90% empathy satisfaction and Cohen's κ = 0.82, reflecting text quality rather than clinical screening validity. The null diagnostic AUC and synthetic-only evaluation prevent any current screening or clinical-utility claims. Real-data EEG validation, clinician-caregiver interaction studies for MADSN, and DP-protected training on real patient records are prerequisites for future clinical deployment.
Miscarriage is a common reproductive loss that can have significant psychological consequences, including post-traumatic stress disorder (PTSD). The present study aimed to examine the association between attachment anxiety, attachment avoidance, post-loss period and gestational stage at pregnancy loss with PTSD symptom severity among women who have experienced miscarriage in Cyprus. A cross-sectional study employing convenience sampling was conducted. A total of 176 women who had experienced a miscarriage completed an online questionnaire. PTSD symptoms were assessed using the Post-traumatic Stress Disorder Checklist for DSM-5 (PCL-5), while romantic attachment anxiety and attachment avoidance were measured using the Experiences in Close Relationships-Revised (ECR-R) questionnaire. Participants also provided demographic information, including gestational stage at miscarriage and post-loss period. Descriptive statistics, Pearson correlation analyses and multiple linear regression analyses were conducted to examine predictors of PTSD symptom severity. Attachment anxiety and attachment avoidance were both significantly associated with increased PTSD symptom severity following miscarriage. Women who had experienced a miscarriage within the previous 12 months as well as women who experienced later miscarriage reported significantly higher PTSD symptoms. Multiple regression analysis further demonstrated that attachment anxiety, attachment avoidance, post-loss period and gestational stage independently predicted PTSD symptom severity. The findings indicate that partner attachment anxiety, attachment avoidance, post-loss period and gestational stage are important factors associated with PTSD symptom severity following miscarriage. These results highlight the importance of early psychological screening and attachment-informed support following miscarriage, particularly within the first year after loss.
This study represents the first methodological stage of a broader AI-assisted Cameriere European dental age estimation workflow. The aim of this first stage was to evaluate the performance of YOLOv8-based deep learning models in automatically detecting the anatomical landmarks and apical structures required for the Cameriere European method. Rather than directly estimating dental age, the proposed system was designed to automate the measurement-related inputs needed for subsequent Cameriere European-based age calculation. This retrospective first-stage validation study included 4,050 panoramic radiographs of boys and girls aged 5-13 years. Two YOLOv8-based models were developed to automate the anatomical measurement components of the Cameriere European method: a YOLOv8x-pose model for open-apex landmark detection and tooth-length reference point localization, and a YOLOv8x-seg model for closed-apex segmentation. Owing to model-specific anatomical eligibility criteria, 3,796 images were used for the pose model and 2,971 images for the segmentation model. Image annotations were performed using CranioCatch software according to a standardized annotation protocol. Model outputs were compared with manual reference annotations to evaluate landmark detection, measurement-related localization, and apical segmentation performance. In the YOLOv8x-pose model, mAP_0.5 = 0.963 and mAP_0.5:0.95 = 0.842 were achieved; recall was 0.928 and precision was 0.918. Error metrics were MAE = 0.0032, RMSE = 0.0045, SMAPE = 2.09%, and the coefficient of determination R² = 0.9992. YOLOv8-based pose and segmentation models demonstrated technical feasibility for automating anatomical measurement extraction required for the Cameriere European dental age estimation method. Because dental age was not calculated in this first-stage analysis, the findings should be interpreted as measurement-level validation rather than complete dental age-estimation accuracy. Further validation is required to integrate AI-derived measurements into the Cameriere European formula and to compare AI-assisted dental age estimates with manual Cameriere-based assessment and chronological age.
Diabetic kidney disease (DKD) is a frequent complication of type 2 diabetes and is closely linked to systemic inflammation. Peripheral blood mononuclear cells (PBMCs) are markers of systemic inflammatory and metabolic stress. It is unknown if metabolism-related transcriptomic alterations in these cells is associated with DKD. Using the nCounter® Human Metabolic Pathways Panel we profiled PBMC metabolic transcripts in individuals with type 2 diabetes or DKD and in controls (n = 12/group), and integrated transcriptomic data with clinical, inflammatory, and mitochondrial parameters. Patients with DKD showed increased inflammatory biomarkers and reduced PBMC mitochondrial membrane potential and mass, consistent with mitochondrial dysfunction. Metabolism-related transcriptomic profiling identified 13 differentially expressed genes across groups. DKD subjects displayed downregulation of SLC7A11 versus controls and HLA-DQA1 versus type 2 diabetes, and upregulation of CPT1A and GBA1 versus controls. CPT1A upregulation was confirmed by RT-qPCR and supported by external GEO datasets, though ROC analyses indicated a limited discriminatory performance. Pathway analyses revealed enrichment of immune-related, fatty acid oxidation, and fructose-6-phosphate pathways and reduced cell proliferation pathways in DKD patients. Inflammatory markers correlated positively with energy-regulating pathways and negatively with anabolic processes. In conclusion, these findings suggest that PBMCs reflect immunometabolic remodeling in response to DKD, thus highlighting an association between systemic inflammation, mitochondrial dysfunction, and altered energy metabolism in circulating immune cells.
Isobaric chemical tag labels are the 'gold standard' for quantifying proteins in bottom-up proteomics. Recently, our group developed and optimized an intact protein-level tandem mass tag (TMT) labeling platform to identify and quantify intact proteoforms in complex biological samples. This intact-protein TMT labeling strategy enables multiplexed quantification and minimizes variability introduced during downstream sample preparation. Here, to achieve deeper proteome coverage, we developed an integrated TMT-labeling and online 2D high-pH/low-pH RPLC top-down workflow for proteoform quantification in complex cell lysates. TMT-labeled intact proteoforms derived from HeLa lysate were mixed at defined ratios and analyzed using the developed platform. The measured TMT reporter ion ratios for detected intact proteoforms closely matched the expected theoretical values, demonstrating high quantitative accuracy. The platform was further applied to quantify changes in proteoform abundance induced by staurosporine (STS) in HeLa cells. Using six channels of TMT10plex reagents, with 3.3 μg of protein labeled per channel and 20 μg total protein injected, we identified 47 proteoforms from 21 proteins exhibiting significant abundance changes in microgram-level samples. Functional enrichment analysis using DAVID associated these proteoforms with metabolic and apoptotic pathways previously linked to STS-induced cellular responses. These results underscore the platform's ability to resolve biologically relevant proteoform-level regulation. This work establishes a multiplexed, quantitative, multidimensional top-down proteomics platform that enables deep proteoform characterization using only microgram-level sample amounts. Data are available via ProteomeXchange with identifier PXD078120.
Autonomic dysfunction (AD) is present in nearly all people with Parkinson disease (PD), contributing to tremendous morbidity and mortality. Highly variable presentations including cardiovascular, gastrointestinal, urogenital, and thermoregulatory dysfunction can substantially affect daily function, safety, medication tolerance, and quality of life. Although autonomic symptoms are frequently encountered in neurologic practice, their management frequently extends beyond the traditional scope of neurologic care and may require input from multiple disciplines. Despite the increasing complexity of PD care and the need for coordinated multidisciplinary involvement, there are currently limited practical frameworks to guide specialist collaboration. Consequently, people with PD and their caregivers are often left to navigate fragmented care systems, conflicting recommendations, and uncertainty regarding which clinician should guide management. To help address these gaps, we provide a framework for the possible indications for specialist referrals and the potential roles of different healthcare practitioners in evaluating and treating AD. The manuscript also discusses the intersection between autonomic and neuropsychiatric manifestations in PD and offers practical clinical guidance for addressing this overlap. By providing a framework informed by coauthors in movement disorders, autonomic disorders, cardiology, nephrology, gastroenterology, urogynecology, physical therapy, and psychiatry, we hope to encourage neurologists - who often serve as the central point of contact - to collaborate closely and actively engage multidisciplinary team members in the management of these complex patients.
Pulegone reductase from peppermint (Mentha × piperita; MpPulR) is an NADPH-dependent medium-chain dehydrogenase/reductase that catalyzes asymmetric reduction of the C4-C7 double bond of (+)-pulegone to (-)-menthone and (+)-isomenthone. To define the structural determinants of substrate recognition and catalytic turnover, we integrated structure-based modeling (docking and molecular dynamics (MD) simulations) with experimental mutagenesis and comprehensive substrate profiling. Residues positioned closely to (+)-pulegone in homology-based structural models were subjected to L-Ala-scanning mutagenesis. Four substitutions (Y53A, F66A, Y78A, Y257A) caused severe activity losses, consistent with a binding pocket in which Y78 supports carbonyl anchoring via hydrogen bonding and aromatic residues (Y53, F66, and Y257) creating a hydrophobic cavity that enforces productive substrate orientation. Other residues, including L56, I63, M135, F281, and V282, line the perimeter of the active site cavity, thus providing architectural constraints for substrate binding. Screening of 40 candidate monoterpenoids revealed measurable activity with only six substrates, and kinetic analysis demonstrated exceptionally high catalytic efficiency toward piperitenone and piperitenone oxide, moderate efficiency with (+)-pulegone, and lower efficiency with citral, (-)-pulegone, and isoegomaketone. MD simulations of productive versus non-productive ligands indicated binding requirements that include stable carbonyl-Y78 hydrogen bonding, enzyme-ligand complex stability, and favorable cofactor-double bond alignment. Finally, an essential oil survey across diverse accessions of the genus Mentha and functional characterization of two M. longifolia orthologs indicate that MpPulR-like enzymes are promiscuous reductases likely contributing to the interspecific diversification of essential oil profiles.
This cross-sectional study examined whether shoulder pain and muscle strength of kinetic chain components are associated with performance on the modified Closed Kinetic Chain Upper Extremity Stability Test (mCKCUEST), Upper Quarter Y Balance Test (UQYBT), and Upper Limb Rotation Test (ULRT) in swimmers. Sixty-two competitive swimmers (aged 12-60 years; 30 with shoulder pain, 32 asymptomatic) across all competition levels were included. Isometric strength of the scapular protractors, lower trapezius, trunk flexors, Hip Stability Isometric Test (HIPSIT), and knee extensor was assessed. Participants also completed the mCKCUEST, UQYBT, and ULRT. Hierarchical multiple linear regression analyses were conducted to examine the associations between shoulder pain, kinetic chain muscle strength, and upper limb performance tests. The model explained 28% of the variance in mCKCUEST performance, with shoulder pain and HIPSIT reaching statistical significance. Knee extensors and scapular protractors strength were significantly associated with the medial direction of the UQYBT, explaining 35% of the variance. Lower trapezius strength was associated with the superolateral direction (11% of variance), while knee extensor strength was associated with the inferolateral direction (37% of variance). Knee extensors and scapular protractors strength were associated with the composite score (38% of variance). For the ULRT, pain, scapular protractors, knee extensors, and trunk flexors strength showed significant associations, explaining 38% of the variance. Shoulder pain and isometric strength of kinetic chain muscles may be associated with performance on the mCKCUEST, UQYBT, and ULRT, highlighting the relevance of kinetic chain assessment in swimmers.
As population needs continuously evolve new technologies have to find ways to address healthcare challenges. Inputs of key stakeholders are critical when adopting new technologies. Our objective was to map stakeholders along the Access and Delivery Partnership value chain framework (ADP) in relation to the RTS,S malaria vaccine introduction in Ghana. Stakeholders engaged with the SAVING consortium were identified and an online questionnaire distributed to map stakeholders positioning in relation to the ADP framework. A workshop was also held to validate findings and to examine the decision processes in adopting new interventions. 31 stakeholders responded the questionnaire reporting their involvement in the ADP framework, most of them identified with stages close to "service delivery", as opposed to the preceding research and regulatory stages. A few stakeholders were seen as having the highest interest and influence on vaccine introduction. There is an imbalance between Ghana's high demand for vaccines and its Research and Development (R&D) capacity, similar to other African countries. Enhancing upstream R&D capacity and fostering more inclusive stakeholder contributions could strengthen the pathway to new technologies adoption.