Estimates of the prevalence of Parkinson’s disease in North America have varied widely and many estimates are based on small numbers of cases and from small regional subpopulations. We sought to estimate the prevalence of Parkinson’s disease in North America by combining data from a multi-study sampling strategy in diverse geographic regions and/or data sources. Five separate cohort studies in California (2), Minnesota (1), Hawaii USA (1), and Ontario, Canada (1) estimated the prevalence of PD from health-care records (3), active ascertainment through facilities, large group, and neurology practices (1), and longitudinal follow-up of a population cohort (1). US Medicare program data provided complementary estimates for the corresponding regions. Using our age- and sex-specific meta-estimates from California, Minnesota, and Ontario and the US population structure from 2010, we estimate the overall prevalence of PD among those aged ≥45 years to be 572 per 100,000 (95% confidence interval 537–614) that there were 680,000 individuals in the US aged ≥45 years with PD in 2010 and that that number will rise to approximately 930,000 in 2020 and 1,238,000 in 2030 based on the US Census Bureau population projections. Regional variations in prevalence were also observed in both the project results and the Medicare-based calculations with which they were compared. The estimates generated by the Hawaiian study were lower across age categories. These estimates can guide health-care planning but should be considered minimum estimates. Some heterogeneity exists that remains to be understood. A large study that combines data from five different projects in four different regions across North America provides an updated estimate of the prevalence of Parkinson’s disease (PD). Connie Marras at Toronto Western Hospital in Canada and colleagues found that PD prevalence among individuals over 45 years of age is higher among men than women and that it increases with age in both sexes. They estimate that the overall prevalence of PD is 572 per 100,000 and that in the US in 2010 there were 680,000 individuals with PD. As life expectancy increases this number is projected to increase to over one million by 2030. These figures, which the authors note should be considered minimum prevalence estimates, warn of the impact that PD will have on North America’s healthcare systems in the near future.
Ruben P. M. Deblier, Steven D M Colpaert, Debbie Van Renterghem
et al.
Introduction:
Preservation of forefoot length is crucial for gait mechanics and long-term function. However, soft-tissue defects in this region often lead to bone shortening or amputation. The superficial circumflex iliac artery perforator (SCIP) flap offers a thin and reliable reconstructive option with minimal donor-site morbidity.
Case Report:
We present three patients with complex forefoot soft tissue loss in whom SCIP flaps were used for reconstruction. In all cases, the flap provided stable coverage, preserved bone length, and allowed functional recovery.
Conclusion:
The SCIP flap is a valuable option in forefoot reconstruction, enabling preservation of viable structures while maintaining good functional and esthetic outcomes.
Orthopedic surgery, Diseases of the musculoskeletal system
Vision Loss Expert Group of the Global Burden of Disease , the GBD 2019 Blindness and Vision Impairment Collabora
ABSTRACT Purpose To assess burden of blindness and visual impairment (VI) in Sub-Saharan Africa (SSA) as of 2020, the planned end point of the Vision 2020 program. Methods A systematic review and meta-analysis assessed burden, in the better eye, of blindness (presenting distance visual acuity, VA < 3/60), moderate and severe vision impairment (MSVI; VA < 6/18 but ≥ 3/60) and mild vision impairment (VA < 6/12 and ≥ 6/18); and also functional presbyopia (<N6 or N8 in the presence of ≥ 6/12 best-corrected distance visual acuity) in SSA. Results In 2020, an estimated 5,083,000 people (95%Uncertainty Interval, UI, 4,474,000–5,696,000) in SSA were bilaterally blind; 20442,000 more (95%UI 18,568,000–22,430,000) had MSVI. The age-standardized prevalence of blindness in SSA is the highest for any GBD super-region, nearly double the world average (0.99%, 95%UI, 0.85–1.12; vs 0.52%, 95% UI, 0.46–0.59 respectively). The Western (4.15%) and Eastern (3.79%) SSA sub-regions had the highest age-standardized prevalence of blindness for the 50+ age group amongst SSA sub-regions. Improvement in age-specific prevalence since 2000 was less than the Vision 2020 target (−25%) for all subcategories of VI; improvement in blindness was the only category close to the goal (about 80–100% of goal across SSA sub-regions). Conclusions The SSA age-specific prevalence of VI has generally improved since 2000, especially for blindness. However, the number of VI cases has increased with population growth and aging, and Vision 2020 targets were not met. Because most causes of VI require individual-level clinical care, large increases in training and eye care delivery systems development/financing are critical areas of focus.
Abstract Background The C-reactive protein (CRP)-albumin-lymphocyte (CALLY) index is a novel biomarker reflecting inflammation, nutrition, and immune status, and its potential clinical significance and prognostic role in patients with rheumatoid arthritis (RA) has not been reported. Aim The objective of this study was to investigate whether CALLY is associated with all-cause mortality in RA patients. Methods The characteristics of 1101 RA patients and 18,047 non-RA individuals were collected from the National Health and Nutrition Examination Survey (NHANES) database between 1999 and 2010. The CALLY index is calculated as albumin × lymphocyte count / (CRP × 10). Multivariable Cox regression models were used to assess the association between the CALLY index and all-cause mortality in RA patients. Restricted cubic spline (RCS) analysis was applied to evaluate potential linear or nonlinear relationships between the CALLY index and mortality. Kaplan-Meier survival curves were used to assess survival probabilities across different CALLY levels in RA patients.The final analysis was conducted on July 10, 2024. Results Multivariable logistic regression analysis indicated that a low CALLY index was significantly associated with RA patients when compared to non-RA individuals, with an odds ratio (OR) of 0.74 (95% CI: 0.65–0.83). Cox regression models revealed that RA patients with a higher CALLY index showed a decreased risk of all-cause mortality, with a hazard ratio (HR) of 0.62 (95% CI: 0.51–0.77). RCS analysis demonstrated a L-shaped relationship between the CALLY index and survival outcomes of RA patients. Segmented regression identified an optimal cutoff value for the CALLY index at 12.79, where values below this threshold were inversely correlated with all-cause mortality risk. Subgroup analysis suggested a synergistic interaction between a high Log-CALLY index, male, and age below 60 years. Kaplan-Meier survival curve analysis showed significantly higher survival rates in the high CALLY group compared to the low CALLY group (P = 0.0012). Conclusions The CALLY index is a valuable biomarker for evaluating the prognosis of patients with RA, and a lower CALLY index indicates an increased long-term mortality risk in RA patients, which suggests the importance of comprehensive assessment for inflammatory status and immune function. Clinical trial number Not applicable.
ABSTRACT Background Ventilator‐induced diaphragmatic dysfunction (VIDD) is a major complication in critically ill patients. Prolonged mechanical ventilation (MV) triggers diaphragmatic fibrotic remodelling, but the underlying mechanisms remain unclear. This study investigated the role of the mechanosensitive channel Piezo1 in this process. Methods A rat model of MV was established for 6 or 12 h. Diaphragm structure (atrophy and fibrosis) and function (frequency‐contraction curve and fatigue index) were assessed. The roles of Piezo1 were probed using the inhibitor GsMTx4 (a nonspecific mechanosensitive channel inhibitor) and adeno‐associated virus (AAV)–mediated knockdown. Downstream signalling was identified by RNA sequencing (RNA‐seq) and validated with cytosporone‐B (CsnB, a specific agonist of Nr4a1). Results Compared with controls, MV for 12 h induced significant diaphragm fibrosis, atrophy and dysfunction, alongside increased Piezo1 expression (mRNA: 2.362 ± 0.429 vs. 0.920 ± 0.363, p = 0.0018; protein: 1.098 ± 0.103 vs. 0.676 ± 0.102, p = 0.0007). Both GsMTx4 and Piezo1 knockdown alleviated these effects. Knockdown reduced the collagen deposition area by approximately 21% and downregulated key fibrotic markers including fibronectin (0.749 ± 0.118 vs. 1.081 ± 0.117, p < 0.0001), collagen 1 (0.703 ± 0.087 vs. 1.155 ± 0.131, p < 0.0001), collagen 3 (0.879 ± 0.074 vs. 1.063 ± 0.068, p = 0.022) and α‐SMA (0.872 ± 0.657 vs. 1.108 ± 0.078, p = 0.0031) compared to the MV12 + shCtrl group. RNA‐seq identified Nr4a1 as a downstream factor (p value < 0.009). CsnB treatment increased Nr4a1 expression (1.128 ± 0.113 vs. 0.490 ± 0.084, p < 0.0001), mitigating prolonged MV‐induced diaphragm fibrosis and dysfunction but not atrophy (938.1 ± 116.2 vs. 754.7 ± 155.5, p = 0.1079). Conclusions Piezo1 upregulation is a key mechanism in ventilator‐induced diaphragm fibrosis, potentially mediated through the Akt/Nr4a1 signalling pathway. Targeted inhibition of Piezo1 or activation of Nr4a1 presents a promising therapeutic strategy to prevent fibrosis and preserve diaphragm function.
Diseases of the musculoskeletal system, Human anatomy
Clinical translation of medical devices is determined by many factors and is challenging for certain countries or regions as no regulatory body is available to approve related applications. They must rely on application for regulatory bodies of other countries or regions who have independent medical device regulatory systems, while the major markets regulatory process is different. For example, considering the market size and policy orientation, mainland China may be a good option for Hong Kong research organizations. Typically, China National Medical Products Administration (NMPA) has positioned innovation as a key growth engine and implemented various mechanisms to expedite the registration, including Marketing Authorization Holder policy (MAH), as well as the setting up of the NMPA's Guangdong-Hong Kong-Macao Greater Bay Area (GBA) Branch Office, type test reform and application for securing innovation channel application. However, there are still many challenges in the transitional process for Hong Kong universities or research institutions, to set up a company in mainland and then prepare many documental files from very beginning. In the future, taking advantage of NMPA reform and seeking cooperation with the NMPA to establish an independent regulatory body in Hong Kong to be recognized by NMPA is recommended as this alone will boost innovation in life sciences and boost in Hong Kong, and have a positive impact on the commercialization of medical devices in mainland China. Such example may also be relevant for many countries or regions who are seeking medical device approval in the designated regulatory systems.
Mariza Fevereiro-Martins, A. C. Santos, Carlos Marques-Neves
et al.
Retinal neurodevelopment, vascularization, homeostasis, and stress response are influenced by factors such as nerve growth factor (NGF), brain-derived neurotrophic factor (BDNF), tyrosine hydroxylase (TH), and erythropoietin (EPO). As retinopathy of prematurity (ROP) is a neurovascular retinal disease, this study analyzed the contributions of NGF (rs6330), BDNF (rs7934165), TH (rs10770141), and EPO (rs507392) genetic functional polymorphisms to the modulation of hematological and biochemical parameters of the first week of life and their association with ROP development. A multicenter cohort of 396 preterm infants (gestational age < 32 weeks or birth weight < 1500 g) was genotyped using MicroChip DNA and iPlex MassARRAY® platform. Multivariate regression followed univariate assessment of ROP risk factors. NGF (GG) genotype was associated with a higher ROP risk (OR = 1.79), which increased further (OR = 2.38) when epistatic interactions with TH (allele C) and BDNF (allele G) were present. Significant circulating biomarker differences, including bilirubin, erythrocytes, monocytes, neutrophils, lymphocytes, and platelet markers, were found between ROP and non-ROP groups, with variations depending on the polymorphism. These findings suggest that NGF (rs6330) and its interactions with related genes contribute to ROP risk, providing valuable insights into the genetic and biological mechanisms underlying the disease and identifying potential predictive biomarkers.
Ibrahim Eker, Hamide Nur Çevik Özdemir, F. Yılmaz
et al.
Objective Preimplantation genetic diagnosis (PGD) with human leukocyte antigen (HLA) typing represents a significant advancement in treating inherited hematological disorders, particularly thalassemia major. This technology enables the birth of healthy children who can serve as compatible stem cell donors for their affected siblings. Türkiye is a world leader in both PGD+HLA typing technology and hematopoietic stem cell transplantation (HSCT) from savior siblings born through PGD+HLA typing. This study investigated the experiences of Turkish parents who underwent successful savior sibling procedures using PGD+HLA typing and then successful HSCT from the savior sibling for the treatment of the child with thalassemia major. We aimed to understand the medical, psychological, and sociocultural dimensions of this complex process within the Turkish healthcare context. Materials and Methods A qualitative study was undertaken using a descriptive phenomenological approach. In-depth interviews were conducted with parents from 16 families who had successfully completed PGD+HLA matching and subsequent stem cell transplantation processes from the savior sibling to the child with thalassemia. Data were analyzed using Colaizzi’s seven-step method and MAXQDA 20.0 software. Results The analysis revealed six main themes: disease stage, treatment, recovery process, social/family, support systems, and recommendations. Parents reported significant emotional challenges but demonstrated unexpected resilience. Religious and cultural factors played nuanced roles, with most parents viewing the process as compatible with their beliefs. Economic burdens, prolonged hospitalizations, and geographical access to treatment centers emerged as key challenges. Extended family support and professional healthcare guidance were identified as crucial support mechanisms. Conclusion This study highlights the complex interplay between advanced medical technologies and traditional values in Turkish society. The findings emphasize the need for comprehensive and culturally sensitive support systems and long-term follow-up for families. The results suggest the value of implementing multidisciplinary care teams and developing specialized support programs for families undergoing savior sibling procedures.
Omar Faruq Shikdar, Fahad Ahammed, B. M. Shahria Alam
et al.
Tea is among the most widely consumed drinks globally. Tea production is a key industry for many countries. One of the main challenges in tea harvesting is tea leaf diseases. If the spread of tea leaf diseases is not stopped in time, it can lead to massive economic losses for farmers. Therefore, it is crucial to identify tea leaf diseases as soon as possible. Manually identifying tea leaf disease is an ineffective and time-consuming method, without any guarantee of success. Automating this process will improve both the efficiency and the success rate of identifying tea leaf diseases. The purpose of this study is to create an automated system that can classify different kinds of tea leaf diseases, allowing farmers to take action to minimize the damage. A novel dataset was developed specifically for this study. The dataset contains 5278 images across seven classes. The dataset was pre-processed prior to training the model. We deployed three pretrained models: DenseNet, Inception, and EfficientNet. EfficientNet was used only in the ensemble model. We utilized two different attention modules to improve model performance. The ensemble model achieved the highest accuracy of 85.68%. Explainable AI was introduced for better model interpretability.
Commercialized non-autologous biologics are produced from a variety of human tissues and are intended to treat a wide range of musculoskeletal pathologies. This survey focuses on non-autologous biologic products that are delivered via the topical or percutaneous (i.e., injected) routes. The regulatory framework established in the USA will be reviewed, including an assessment of specific categories of non-autologous biologics with their intended uses, since regulatory compliance of a specific composition or physical form of a non-autologous biologic is tightly linked to its advertised use. Guidance is provided on how to manage emerging products whose regulatory status might be unclear. Clinical safety and efficacy for non-autologous biologics for wound and burn care, including minimally processed placental products in sheet form as well as bio-engineered viable cell composite products, are well established, although efficacy tends to be wound type-specific. Micronized placental tissue products have been investigated in treating osteoarthritis of the knee and hip, and for plantar fasciitis, but require large-scale clinical studies and remain to be approved by the United States Food and Drug Administration (USFDA). Several emerging types (secretomes, exosomes) of non-autologous biologics are well documented in pre-clinical studies, but human studies are lacking. There are no Phase 3 studies reported on a secretome-based product, while there is just one Phase 3 clinical trial on-going for a bone marrow progenitor cell derived exosome product that is being used to treat acute respiratory distress syndrome. There has been substantial progress in the commercialization of exosome-based products, with studies in treating musculoskeletal pathologies a priority. Progress has been made in assessing the treatment of osteoarthritic knees and discogenic low back pain with cultured progenitor cells. However, utility and safety of these investigational products remains to be determined.
Macrophage activation syndrome (MAS) is a state of immune hyperactivation that can result in life‐threatening multisystem end‐organ dysfunction. Often termed a “cytokine storm,” MAS occurs among the rheumatic diseases most typically in Still's disease but also in systemic lupus erythematosus and Kawasaki disease. MAS can also accompany infection, malignancy, and inborn errors of immunity. This review provides a practical, evidence‐based guide to the understanding, recognition, and management of MAS in children and adults, with a primary focus on MAS complicating Still's disease.
Marco Angelozzi, Anirudha Karvande, Véronique Lefebvre
AbstractPivotal in many ways for human health, the control of adult bone mass is governed by complex, incompletely understood crosstalk namely between mesenchymal stem cells, osteoblasts and osteoclasts. The SOX4, SOX11 and SOX12 (SOXC) transcription factors were previously shown to control many developmental processes, including skeletogenesis, and SOX4 was linked to osteoporosis, but how SOXC control adult bone mass remains unknown. Using SOXC loss- and gain-of-function mouse models, we show here that SOXC redundantly promote prepubertal cortical bone mass strengthening whereas only SOX4 mitigates adult trabecular bone mass accrual in early adulthood and subsequent maintenance. SOX4 favors bone resorption over formation by lowering osteoblastogenesis and increasing osteoclastogenesis. Single-cell transcriptomics reveals its prevalent expression in Lepr+ mesenchymal cells and ability to upregulate genes for prominent anti-osteoblastogenic and pro-osteoclastogenic factors, including interferon signaling-related chemokines, contributing to these adult stem cells’ secretome. SOXC, with SOX4 predominantly, are thus key regulators of adult bone mass.
Jeremy C Heard, Yunsoo A Lee, Nicholas D D'Antonio
et al.
Objectives: To evaluate the (1) 90-day surgical outcomes and (2) 1-year revision rate of robotic versus nonrobotic lumbar fusion surgery.
Methods: Patients >18 years of age who underwent primary lumbar fusion surgery at our institution were identified and propensity-matched in a 1:1 fashion based on robotic assistance during surgery. Patient demographics, surgical characteristics, and surgical outcomes, including 90-day surgical complications and 1-year revisions, were collected. Multivariable regression analysis was performed. Significance was set to P < 0.05.
Results: Four hundred and fifteen patients were identified as having robotic lumbar fusion and were matched to a control group. Bivariant analysis revealed no significant difference in total 90-day surgical complications (P = 0.193) or 1-year revisions (P = 0.178). The operative duration was longer in robotic surgery (287 + 123 vs. 205 + 88.3, P ≤ 0.001). Multivariable analysis revealed that robotic fusion was not a significant predictor of 90-day surgical complications (odds ratio [OR] = 0.76 [0.32–1.67], P = 0.499) or 1-year revisions (OR = 0.58 [0.28–1.18], P = 0.142). Other variables identified as the positive predictors of 1-year revisions included levels fused (OR = 1.26 [1.08–1.48], P = 0.004) and current smokers (OR = 3.51 [1.46–8.15], P = 0.004).
Conclusion: Our study suggests that robotic-assisted and nonrobotic-assisted lumbar fusions are associated with a similar risk of 90-day surgical complications and 1-year revision rates; however, robotic surgery does increase time under anesthesia.
With the advancement of internet communication and telemedicine, people are increasingly turning to the web for various healthcare activities. With an ever-increasing number of diseases and symptoms, diagnosing patients becomes challenging. In this work, we build a diagnosis assistant to assist doctors, which identifies diseases based on patient-doctor interaction. During diagnosis, doctors utilize both symptomatology knowledge and diagnostic experience to identify diseases accurately and efficiently. Inspired by this, we investigate the role of medical knowledge in disease diagnosis through doctor-patient interaction. We propose a two-channel, knowledge-infused, discourse-aware disease diagnosis model (KI-DDI), where the first channel encodes patient-doctor communication using a transformer-based encoder, while the other creates an embedding of symptom-disease using a graph attention network (GAT). In the next stage, the conversation and knowledge graph embeddings are infused together and fed to a deep neural network for disease identification. Furthermore, we first develop an empathetic conversational medical corpus comprising conversations between patients and doctors, annotated with intent and symptoms information. The proposed model demonstrates a significant improvement over the existing state-of-the-art models, establishing the crucial roles of (a) a doctor's effort for additional symptom extraction (in addition to patient self-report) and (b) infusing medical knowledge in identifying diseases effectively. Many times, patients also show their medical conditions, which acts as crucial evidence in diagnosis. Therefore, integrating visual sensory information would represent an effective avenue for enhancing the capabilities of diagnostic assistants.
The intricate relationship between genetic variation and human diseases has been a focal point of medical research, evidenced by the identification of risk genes regarding specific diseases. The advent of advanced genome sequencing techniques has significantly improved the efficiency and cost-effectiveness of detecting these genetic markers, playing a crucial role in disease diagnosis and forming the basis for clinical decision-making and early risk assessment. To overcome the limitations of existing databases that record disease-gene associations from existing literature, which often lack real-time updates, we propose a novel framework employing Large Language Models (LLMs) for the discovery of diseases associated with specific genes. This framework aims to automate the labor-intensive process of sifting through medical literature for evidence linking genetic variations to diseases, thereby enhancing the efficiency of disease identification. Our approach involves using LLMs to conduct literature searches, summarize relevant findings, and pinpoint diseases related to specific genes. This paper details the development and application of our LLM-powered framework, demonstrating its potential in streamlining the complex process of literature retrieval and summarization to identify diseases associated with specific genetic variations.