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Seaweed cultivation has garnered significant interest, driven by its wide range of biomass benefits. However, comprehensive assessments from various perspectives are imperative to ensure the sustainable cultivation of seaweed. Biotic and Abiotic factors can significantly impact seaweed yield in complex commercial farming. Biotic factors include bacteria, fungi, viruses, and other algae, while abiotic factors include environmental conditions such as temperature, salinity, light intensity, and nutrient availability. Additionally, the susceptibility of seaweeds to pests and diseases further compounds the issue, leading to potential crop losses. This study endeavours to shed light on the immense potential of macroalgae cultivation and underscores the pressing need for scientific advancements in this field. The comprehensive review clearly explains the latest developments in seaweed cultivation and highlights significant advances from diverse seaweed research. Moreover, it provides insightful glimpses into possible future developments that could shape the trajectory of this promising industry.
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Background: Acellular dermal matrices (ADMs) are sometimes used in implant-based breast reconstructions (IBR), but long-term ADM-related evaluations are scarce. In this study, we evaluated early and late complications and patient-related outcomes (PROs) over an 8-year postoperative period in women who had undergone immediate IBR following risk-reducing mastectomy with bovine ADM (SurgiMend). Methods: This prospective observational single-center analysis involved 34 women at high risk for breast carcinoma. Complications were prospectively recorded during the first year, followed by 4 years of postoperative retrospective chart reviews. Long-term evaluations were done using a questionnaire. Preoperative, 1 year, and 5- to 8-year postoperative PRO assessments were obtained based on results from the BREAST-Q questionnaire. Results: In 56 breasts, complications after a mean of 12.4 months follow-up included implant loss (7.1%), implant change (1.8%), hematoma (7.1%), breast redness (41.1%), and seroma (8.9%). Most breasts (80.3%) were graded Baker I/II, which indicated a low capsular contracture incidence. After a mean of 6.9 years, the total implant explantation rate was 33.9%, and the revision surgery rate was 21.4%. Two cases of breast cancer were reported during the long-term evaluation. BREAST-Q results indicated significantly decreased satisfaction with outcome (Pâ =â 0.024). A positive trend regarding psychosocial well-being and declining trend regarding satisfaction with both breast physical- and sexual well-being parameters were reported. Conclusions: The observed complication rates agree with previous findings concerning ADM-assisted IBR. A high demand for revision surgery exists, and PROs remain relatively stable over time.
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BACKGROUND: Wrist-worn gadgets like smartphones are ideal for unobtrusively gathering user data, in various fields such as health and fitness monitoring, communication, and productivity enhancement. They seamlessly integrate into users' daily lives, providing valuable insights and features without the need for constant attention or disruption. In sensitive domains like mental health, these devices provide user-friendly, privacy-protected means of diagnosis and treatment, offering a secure and cost-effective avenue for seeking help. OBJECTIVES: This study addresses the limitations of traditional mental health assessment techniques, such as intrusive sensing and subjective self-reporting, by harnessing the unobtrusive data collection capabilities of smartphones. Equipped with accelerometers and other sensors, these devices offer a novel approach to mental health research. Our objective was to develop methods for real-time detection of stress and boredom behavior markers using smart devices and machine learning algorithms. METHODOLOGY: By leveraging data from accelerometers (A), gyroscopes (G), and magnetometers (M), we compiled a dataset indicative of stress-related behaviors and trained various machine-learning models for predictive accuracy. The methodology involved collecting data from motion sensors (A, G, and M) on the dominant arm's wrist-worn smartphone, followed by data preprocessing, transformation from time series format, and training a Deep Neural Network (DNN) model for activity recognition. FINDINGS: Remarkably, the DNN achieved an accuracy of 93.50% on test data, outperforming traditional and ensemble machine learning methods across different window sizes, and demonstrated real-time accuracy of 77.78%, validating its practical application. CONCLUSION: In conclusion, this research presents a novel dataset for detecting stress and boredom behaviors using smartphones, reducing reliance on costly devices and offering a more objective assessment. It also proposes a DNN-based method for wrist-worn devices to accurately identify complex activities associated with stress and boredom, with benefits in terms of privacy and user convenience. This advancement represents a significant contribution to the field of mental health research, providing a less intrusive and more user-friendly approach to monitoring mental well-being.
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Saúde Mental , Smartphone , Humanos , Exercício Físico , Redes Neurais de Computação , AlgoritmosRESUMO
PURPOSE: To describe the treatment outcomes of adalimumab in noninfectious pediatric uveitis. METHODS: The electronic medical records of children with noninfectious uveitis were reviewed retrospectively. The visual improvement and ocular inflammation were assessed according to the Standardization of Uveitis Nomenclature criteria before and after treatment with adalimumab. RESULTS: Twenty-nine eyes of 16 patients were included. The mean age of children was 9.4 ± 3.8 years. There were eight (50%) males and eight (50%) females. Juvenile idiopathic arthritis was the most common cause of uveitis in these children (N = 10, 62.5%), followed by Behçet's disease (N = 3, 18.75%) and Vogt-Koyanagi-Harada disease (N = 2, 12.5%). One child (6.25%) was diagnosed with Crohn's disease. Nine (56.3%) children were previously treated with methotrexate, one each with mycophenolate mofetil (MMF) (6.3%), azathioprine (6.3%), and tofacitinib (6.3%), and one child received MMF followed by azathioprine and cyclosporine before shifting to adalimumab. Three (18.8%) children did not receive prior immunosuppressive therapy. The average number of adalimumab injections given was 20.3 ± 12.0 at an interval of 2 weeks. The mean follow-up duration was 22.2 ± 16.6 months. Disease inactivity was achieved in 28 (96.6%) eyes at last visit ( P < 0.001). The best-corrected visual acuity (BCVA) improved from 0.48 ± 0.6 logMAR (logarithm of minimum of resolution) units at baseline to 0.20 ± 0.2 logMAR units at last visit ( P = 0.018). Disease remission was achieved in 23 (79.3%) eyes at the third month ( P = 0.001). CONCLUSION: Adalimumab is effective in the treatment of pediatric noninfectious uveitis by achieving disease inactivity, reducing the recurrence rate and improving BCVA. The drug is safe and well tolerated.
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This article presents a dataset of activities associated with stress and boredom obtained through wearable sensors. Data was collected from 40 right-handed participants aged 20 to 25, evenly split between males and females. Each individual wore a smart device on their dominant arm's wrists to facilitate the capture of data. This dataset covers five activities associated with stress and boredom, namely, smoking, eating, nail biting, face touching, and staying still. These activities were selected for their potential psychological implications and captured in an uncontrolled environment to mimic real-life scenarios. The data provides a unique resource for developing machine learning models aimed at recognizing these behaviors, which could lead to real-time analysis and interventions for stress. A custom holder was used to hold the device on the wrists in order to ensure that all participants had consistent orientation and placement. This holder was situated just above the wrist joint, a location typically associated with the placement of smartwatches. The dataset provides a unique opportunity for developing machine learning models for stress & boredom associated activities recognition apart from real-time symptomatic analysis of stress and boredom.
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PURPOSE: This retrospective observational study aimed to comprehensively analyse the clinical profile and treatment modalities of patients diagnosed with type 2 diabetes mellitus (T2DM) who were treated at a tertiary care centre. METHODS: The study included a cohort of 300 individuals who sought medical care at the hospital from January 2023 to January 2024. The analysis primarily examined parameters such as the mean number of anti-diabetic medications per prescription, the proportion of various categories of anti-diabetic medications prescribed, the predominant class and type of anti-diabetic medications prescribed, and the proportion of anti-diabetic medications prescribed from the essential drug lists. RESULTS: The age distribution demonstrated that 52.0% of participants were above 60 years old, showcasing a substantial elderly representation. Gender distribution emphasized a male predominance at 65.0%, highlighting potential gender-specific implications in type II diabetes. The blood profile analysis of patients with T2DM revealed a range of values for key parameters. Fasting blood glucose levels ranged from a minimum of 101 mg/dL to a maximum of 359 mg/dL, with a mean of 180.01 mg/dl. The comprehensive analysis of anti-diabetic drug utilization, based on the total number of units prescribed, sheds light on the diverse treatment approaches employed for managing diabetes mellitus (DM). Insulin, comprising 31.3% of the total units, plays a pivotal role in glycemic control, with both regular and biphasic formulations contributing significantly at 26.3% and 9.3%, respectively. Among the 300 patients, the overall utilization of anti-diabetic drugs reveals that 38.7% of individuals are using a combination of insulin with oral anti-diabetic drugs, while 61.3% are relying on oral anti-diabetic drugs alone. The most frequently prescribed drug combinations for diabetes management include sulphonylurea with biguanides, emerging as the most prevalent combination with 22 occurrences. CONCLUSION: The study's findings contribute valuable insights into the socio-demographic profiles and anti-diabetic drug utilization patterns among diabetes patients.
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Sortilin (SORT1) is a multifunctional protein intricately involved in atherogenesis, coronary artery disease (CAD), and various neurological disorders. It has materialized as a potential pharmacological target for therapeutic development due to its diverse biological roles in pathological processes. Despite its central role under these conditions, effective therapeutic strategies targeting SORT1 remain challenging. In this study, we introduce a drug repurposing strategy guided by structural insights to identify potent SORT1 inhibitors with broad therapeutic potential. Our approach combines molecular docking, virtual screening, and molecular dynamics (MD) simulations, enabling the systematic evaluation of 3648 FDA-approved drugs for their potential to modulate SORT1. The investigation reveals a subset of repurposed drugs exhibiting highly favorable binding profiles and stable interactions within the binding site of SORT1. Notably, two hits, ergotamine and digitoxin, were carefully chosen based on their drug profiles and subjected to analyze their interactions with SORT1 and stability assessment via all-atom MD simulations spanning 300 ns (ns). The structural analyses uncover the complex binding interactions between these identified compounds and SORT1, offering essential mechanistic insights. Additionally, we explore the clinical implications of repurposing these compounds as potential therapeutic agents, emphasizing their significance in addressing atherogenesis, CAD, and neurological disorders. Overall, this study highlights the efficacy of structure-guided drug repurposing and provides a solid foundation for future research endeavors aimed at the development of effective therapies targeting SORT1 under diverse pathological conditions.
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Choroidal detachment (CD) is a rare and potentially vision-threatening complication of glaucoma surgery. Inflammation and prolonged ocular hypotony can promote fluid accumulation between the choroid and sclera. Risk factors include trauma, advanced age, use of anticoagulant medications, systemic hypertension, atherosclerosis, and diabetes. CD ultrasound findings will show 2 layers, detaching as far anteriorly as the ciliary bodies, that protrude convexly into the vitreous without extending to the optic disc, often described as the appositional or kissing choroidal sign. In contrast, retinal detachments will show a distinct "V" shape due to the retina's fixation to the optic nerve head posteriorly. In the case of hemorrhagic CD, therapy should be targeted at reducing intraocular pressure. In this case, the patient was started on atropine and prednisolone drops and discontinued on all glaucoma medications in the left eye. While serous choroidal detachments are usually benign, persistent choroidal effusions may cause significant morbidity with hemorrhagic CD having a worse prognosis. Point of care ultrasound can help emergency physicians quickly distinguish between choroidal and retinal detachments and thus guide management in a safe and timely manner.
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Heart failure (HF) with normal ejection fraction - the isolated diastolic heart failure, depicts increasing prevalence and health care burden in recent times. Having less mortality rate compared to systolic heart failure but high morbidity, it is evolving as a major cardiac concern. With increasing clinical use of Left atrial volume (LAV) quantitation in clinical settings, LAV has emerged as an important independent predictor of cardiovascular outcome in HF with normal ejection fraction. This article is intended to review the diastolic and systolic heart failure, their association with left atrial volume, in depth study of Left atrial function dynamics with determinants of various functional and structural changes.
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Doenças Cardiovasculares , Insuficiência Cardíaca Sistólica , Insuficiência Cardíaca , Disfunção Ventricular Esquerda , Humanos , Função Ventricular Esquerda , Volume Sistólico , Insuficiência Cardíaca Sistólica/complicações , Doenças Cardiovasculares/complicações , Fatores de Risco , Disfunção Ventricular Esquerda/etiologia , Átrios do Coração/diagnóstico por imagem , Insuficiência Cardíaca/complicações , Fatores de Risco de Doenças Cardíacas , Hipertrofia/complicaçõesRESUMO
BACKGROUND: Detection of early chronic changes in the kidney allograft is important for timely intervention and long-term survival. Conventional and novel ultrasound-based investigations are being increasingly used for this purpose with variable results. AIM: To compare the diagnostic performance of resistive index (RI) and shear wave elastography (SWE) in the diagnosis of chronic fibrosing changes of kidney allograft with histopathological results. METHODS: This is a cross-sectional and comparative study. A total of 154 kidney transplant recipients were included in this study, which was conducted at the Departments of Transplantation and Radiology, Sindh Institute of Urology and Transplan tation, Karachi, Pakistan, from August 2022 to February 2023. All consecutive patients with increased serum creatinine levels and reduced glomerular filtration rate (GFR) after three months of transplantation were enrolled in this study. SWE and RI were performed and the findings of these were evaluated against the kidney allograft biopsy results to determine their diagnostic utility. RESULTS: The mean age of all patients was 35.32 ± 11.08 years. Among these, 126 (81.8%) were males and 28 (18.2%) were females. The mean serum creatinine in all patients was 2.86 ± 1.68 mg/dL and the mean estimated GFR was 35.38 ± 17.27 mL/min/1.73 m2. Kidney allograft biopsy results showed chronic changes in 55 (37.66%) biopsies. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of SWE for the detection of chronic allograft damage were 93.10%, 96.87%%, 94.73%, and 95.87%, respectively, and the diagnostic accuracy was 95.45%. For RI, the sensitivity, specificity, PPV, and NPV were 76.92%, 83.33%, 70.17%, and 87.62%, respectively, and the diagnostic accuracy was 81.16%. CONCLUSION: The results from this study show that SWE is more sensitive and specific as compared to RI in the evaluation of chronic allograft damage. It can be of great help during the routine follow-up of kidney transplant recipients for screening and early detection of chronic changes and selecting patients for allograft biopsy.
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Pathogenic platelet factor 4 (PF4) antibodies contributed to the abnormal coagulation profiles in COVID-19 and vaccinated patients. However, the mechanism of what triggers the body to produce these antibodies has not yet been clarified. Similar patterns and many comparable features between the COVID-19 virus and heparin-induced thrombocytopenia (HIT) have been reported. Previously, we identified a new mechanism of autoimmunity in HIT in which PF4-antibodies self-clustered PF4 and exposed binding epitopes for other pathogenic PF4/eparin antibodies. Here, we first proved that the SARS-CoV-2 spike protein (SP) also binds to PF4. The binding was evidenced by the increase in mass and optical intensity as observed through quartz crystal microbalance and immunosorbent assay, while the switching of the surface zeta potential caused by protein interactions and binding affinity of PF4-SP were evaluated by dynamic light scattering and isothermal spectral shift analysis. Based on our results, we proposed a mechanism for the generation of PF4 antibodies in COVID-19 patients. We further validated the changes in zeta potential and interaction affinity between PF4 and SP and found that their binding mechanism differs from ACE2-SP binding. Importantly, the PF4/SP complexes facilitate the binding of anti-PF4/Heparin antibodies. Our findings offer a fresh perspective on PF4 engagement with the SARS-CoV-2 SP, illuminating the role of PF4/SP complexes in severe thrombotic events.
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COVID-19 , Trombocitopenia , Humanos , Anticorpos Monoclonais Humanizados , Fatores Imunológicos , Fator Plaquetário 4/química , Fator Plaquetário 4/metabolismo , SARS-CoV-2/metabolismo , Glicoproteína da Espícula de CoronavírusRESUMO
The COVID-19 pandemic has become a significant global issue in terms of public health. While it is largely associated with respiratory complications, recent reports indicate that patients also experience neurological symptoms and other health issues. The objective of this study is to examine the network of protein-protein interactions (PPI) between SARS-CoV-2 proteins and human host proteins, pinpoint the central genes within this network implicated in disease pathology, and assess their viability as targets for drug development. The study adopts a network-based approach to construct a network of 29 SARS-CoV-2 proteins interacting with 2896 host proteins, with 176 host genes being identified as interacting genes with all the viral proteins. Gene ontology and pathway analysis of these host proteins revealed their role in biological processes such as translation, mRNA splicing, and ribosomal pathways. We further identified EEF2, RPS3, RPL9, RPS16, and RPL11 as the top 5 most connected hub genes in the disease-causing network, with significant interactions among each other. These hub genes were found to be involved in ribosomal pathways and cytoplasmic translation. Further a disease-gene interaction was also prepared to investigate the role of hub genes in other disorders and to understand the condition of comorbidity in COVID-19 patients. We also identified 13 drug molecules having interactions with all the hub genes, and estradiol emerged as the top potential drug target for the COVID-19 patients. Our study provides valuable insights using the protein-protein interaction network of SARS-CoV-2 proteins with host proteins and highlights the molecular basis of manifestation of COVID-19 and proposes drug for repurposing. As the pandemic continues to evolve, it is anticipated that investigating SARS-CoV-2 proteins will remain a critical area of focus for researchers globally, particularly in addressing potential challenges posed by specific SARS-CoV-2 variants in the future.
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When integrating AI tools in healthcare settings, complex interactions between technologies and primary users are not always fully understood or visible. This deficient and ambiguous understanding hampers attempts by healthcare organizations to adopt AI/ML, and it also creates new challenges for researchers to identify opportunities for simplifying adoption and developing best practices for the use of AI-based solutions. Our study fills this gap by documenting the process of designing, building, and maintaining an AI solution called SepsisWatch at Duke University Health System. We conducted 20 interviews with the team of engineers and scientists that led the multi-year effort to build the tool, integrate it into practice, and maintain the solution. This "Algorithm Journey Map" enumerates all social and technical activities throughout the AI solution's procurement, development, integration, and full lifecycle management. In addition to mapping the "who?" and "what?" of the adoption of the AI tool, we also show several 'lessons learned' throughout the algorithm journey maps including modeling assumptions, stakeholder inclusion, and organizational structure. In doing so, we identify generalizable insights about how to recognize and navigate barriers to AI/ML adoption in healthcare settings. We expect that this effort will further the development of best practices for operationalizing and sustaining ethical principles-in algorithmic systems.
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Research on the applications of artificial intelligence (AI) tools in medicine has increased exponentially over the last few years but its implementation in clinical practice has not seen a commensurate increase with a lack of consensus on implementing and maintaining such tools. This systematic review aims to summarize frameworks focusing on procuring, implementing, monitoring, and evaluating AI tools in clinical practice. A comprehensive literature search, following PRSIMA guidelines was performed on MEDLINE, Wiley Cochrane, Scopus, and EBSCO databases, to identify and include articles recommending practices, frameworks or guidelines for AI procurement, integration, monitoring, and evaluation. From the included articles, data regarding study aim, use of a framework, rationale of the framework, details regarding AI implementation involving procurement, integration, monitoring, and evaluation were extracted. The extracted details were then mapped on to the Donabedian Plan, Do, Study, Act cycle domains. The search yielded 17,537 unique articles, out of which 47 were evaluated for inclusion based on their full texts and 25 articles were included in the review. Common themes extracted included transparency, feasibility of operation within existing workflows, integrating into existing workflows, validation of the tool using predefined performance indicators and improving the algorithm and/or adjusting the tool to improve performance. Among the four domains (Plan, Do, Study, Act) the most common domain was Plan (84%, n = 21), followed by Study (60%, n = 15), Do (52%, n = 13), & Act (24%, n = 6). Among 172 authors, only 1 (0.6%) was from a low-income country (LIC) and 2 (1.2%) were from lower-middle-income countries (LMICs). Healthcare professionals cite the implementation of AI tools within clinical settings as challenging owing to low levels of evidence focusing on integration in the Do and Act domains. The current healthcare AI landscape calls for increased data sharing and knowledge translation to facilitate common goals and reap maximum clinical benefit.
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The host type I interferon (IFN) pathway is a major signature of inflammation induced by the human fungal pathogen, Candida albicans. However, the molecular mechanism for activating this pathway in the host defence against C. albicans remains unknown. Here we reveal that mice lacking cyclic GMP-AMP synthase (cGAS)-stimulator of IFN genes (STING) pathway components had improved survival following an intravenous challenge by C. albicans. Biofilm-associated C. albicans DNA packaged in extracellular vesicles triggers the cGAS-STING pathway as determined by induction of interferon-stimulated genes, IFNß production, and phosphorylation of IFN regulatory factor 3 and TANK-binding kinase 1. Extracellular vesicle-induced activation of type I IFNs was independent of the Dectin-1/Card9 pathway and did not require toll-like receptor 9. Single nucleotide polymorphisms in cGAS and STING potently altered inflammatory cytokine production in human monocytes challenged by C. albicans. These studies provide insights into the early innate immune response induced by a clinically significant fungal pathogen.
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Candidíase , Interferon Tipo I , Animais , Camundongos , Candida albicans/patogenicidade , Proteínas Adaptadoras de Sinalização CARD/metabolismo , Imunidade Inata , Interferon Tipo I/metabolismo , Nucleotidiltransferases/genética , Nucleotidiltransferases/metabolismo , Transdução de Sinais , Candidíase/metabolismo , Candidíase/patologiaRESUMO
BACKGROUND: Gastrointestinal stromal tumor is considered the most common mesenchymal neoplasm of the gastrointestinal tract. The majority of gastrointestinal stromal tumor cases are located in the stomach and usually affects older adults. Most of gastrointestinal stromal tumor cases are sporadic; however, few have a syndromic association, including Carney triad, Carney-Stratakis syndrome, familial gastrointestinal stromal tumor syndrome, and neurofibromatosis type 1. CASE PRESENTATION: Herein, we report a rare case of a 54-year-old Middle-Eastern female with multifocal gastrointestinal stromal tumor mixed type (epithelioid and spindle cell type) with osseous metaplasia. Fluoresce in situ hybridization analysis of platelet-derived growth factor receptor alpha revealed deletion in 42% of the tumor cells studied. Interestingly, next generation sequencing revealed platelet-derived growth factor receptor alpha exon 12 mutation (p.Y555C) and exon 14 mutation (p.N659Y). CONCLUSIONS: In conclusion, osseous metaplasia in GIST is a very rare event and only few cases are reported in the literature. The number of reported cases is inadequate to confirm the pathogenesis and the prognosis.
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Tumores do Estroma Gastrointestinal , Neoplasias Gástricas , Humanos , Feminino , Idoso , Pessoa de Meia-Idade , Tumores do Estroma Gastrointestinal/patologia , Neoplasias Gástricas/patologia , Metaplasia , Receptores do Fator de Crescimento Derivado de Plaquetas/genética , MutaçãoRESUMO
This article aims to conduct a literature review to gain insight into point-of-care ultrasound (PoCUS). PoCUS is a rapid, accurate, non-invasive, and radiation-free imaging modality that can be used in stable and unstable patients. PoCUS can be performed parallel to physical examination, resuscitation, and stabilization; repeated exams in critical patients are essential for improving sensitivity. The review highlights how PoCUS, which was initially used to detect free intraperitoneal fluid in trauma patients, has developed into a life-saving diagnostic tool that could be utilized by treating physicians during various stages of diagnosis, resuscitation, operation, and postoperative critical care when managing sick patients. The review also notes the barriers to the widespread uptake of PoCUS in general internal medicine and the recent commercial availability of "pocket" or handheld probes that have made PoCUS more readily available. This review concludes that adopting a focused binary decision-making approach can maximize PoCUS's value in many clinical settings, including emergency departments, intensive care units, and operation theatres. Overall, the review emphasizes the importance of awareness of common indications, limitations, and strengths of this evolving and promising technology to determine its future trajectory: Providing comprehensive PoCUS training within internal medicine curriculums and supporting trainers to do so.