MedComm - Future medicine最新文献

{"title":"Understanding long COVID—The role of serotonin in cognitive impairment","authors":"Shuvam Sarkar,&nbsp;Olivia Monteiro","doi":"10.1002/mef2.80","DOIUrl":"https://doi.org/10.1002/mef2.80","url":null,"abstract":"<p>A recent study by Wong et al. was published in the journal “Cell” and illuminates a potential role for serotonin reduction in mediating cognitive impairment following postacute sequelae of COVID (PASC) or Long COVID.<span>¹</span> This research highlight explores the mechanisms underlying viral infection-mediated serotonin reduction, and unveils therapeutic targets which could alter the way we approach Long COVID in clinical practice.</p><p>In the aftermath of the COVID-19 pandemic, patients are increasingly presenting with debilitating symptoms persisting for months after acute SARS-CoV-2 infection.<span>²</span> The constellation of symptoms, collectively termed Long COVID, are heterogeneous and involves multiple body systems. Despite the significant impact of Long COVID on healthcare resources and patients' quality of life, the mechanisms underlying these symptoms remain largely enigmatic. However, in a groundbreaking study, Wong et al. illuminate a potential link between viral-induced inflammation, serotonin reduction, and cognitive deficits in individuals suffering from Long COVID.<span>¹</span></p><p>Wong et al. analysed a range of metabolites in the serum of patients exhibiting symptoms of both acute and post-acute COVID-19 infection, and found amino acid metabolites, such as serotonin were depleted throughout the acute and chronic phases of infection. Interestingly, patients with Long COVID had lower serotonin levels compared to those who fully recovered from their initial infection. Indeed, serotonin levels in the bloodstream were predictive of long-term symptom burden after initial COVID infection, and strongly suggests a potential role for serotonin in the pathophysiology of Long COVID. Similar reductions in serotonin levels were found in other infections such as varicella-zoster virus and lymphocytic choriomeningitis virus, suggesting that reduced serotonin may be a shared characteristic of systemic viral infections.</p><p>The study then turned to mouse models of viral infection to characterise the mechanisms underpinning serotonin reduction, and found increased type 1 interferon (IFN) signalling. Importantly, IFN signalling was persistently upregulated in long COVID, and inhibition of the IFN alpha receptor prevented viral infection-induced serotonin depletion. This effect was abolished in mice with impaired IFN signalling.</p><p>Serotonin is predominantly synthesized in the gastrointestinal tract, where it is produced from an essential dietary amino acid called tryptophan.<span>³</span> This study also found that individuals with acute and persistent COVID-19 infection had reduced plasma tryptophan levels, hinting at a potential limitation in serotonin production during viral infections. This suggests individuals with congenital or acquired tryptophan deficiency may be more susceptible to developing long COVID. RNA sequencing of small intestinal epithelium found that genes involved in a","PeriodicalId":74135,"journal":{"name":"MedComm - Future medicine","volume":"3 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mef2.80","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140633687","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A biodegradable cardiac electrotherapy device paving the way for autonomous transient implants","authors":"Mladen Veletić,&nbsp;Nureddin Ashammakhi","doi":"10.1002/mef2.78","DOIUrl":"https://doi.org/10.1002/mef2.78","url":null,"abstract":"<p>In a recent article published in <i>Science</i>, Choi et al. introduce an innovative approach to cardiac rhythm control through a newly developed, temporary, wireless, bioresorbable pacemaker.<span>¹</span> This pacemaker operates in a closed-loop fashion, dynamically adjusting pacing parameters to match metabolic demands of the heart while ensuring mechanical robustness and compatibility with magnetic resonance imaging.</p><p>The system comprises three implantable, bioresorbable components, a pacemaker, an anti-inflammatory drug-eluting patch, and a power harvesting unit. Additionally, it includes three skin-interfaced components, a set of physiological sensors, a wireless power transfer module, and a haptic actuator. An external, handheld device with a software application is used for data-management and control (Figure 1).<span>¹</span> After patient recovery, the skin-interfaced devices, including sensors are easily removed.</p><p>The motivation behind the use of biodegradable implantable sensors stems from the necessity to monitor and treat postoperative complications effectively. Such implants mitigate risks associated with nonbiodegradable alternatives, including bacterial colonization and infection, as well as the challenges associated with their removal, particularly in sensitive areas. Clinical trials will determine the accuracy of pacing and electrocardiogram (ECG) recordings with skin-interfaced sensors. It also remains to be found whether combinatorial sensor-actuator transient implants with biodegradable sensors will be more accurate since implantable sensors may provide more accurate data compared to skin-interfaced sensors.</p><p>Biodegradable sensors also offer opportunities for minimally invasive and temporary monitoring and therapeutic interventions, enabling real-time tracking of physiological parameters and targeted delivery of therapeutic agents or electrical stimulation to specific areas of the body.<span>²</span> Unlike skin-interfaced sensors, implantable biodegradable sensors do not need to withstand the movements of the body, and they minimally infringe on them. They are also less cumbersome, and they are comfortable for patients.</p><p>Although it is advantageous to have implants that can degrade and disappear, their degradation can lead to a inflammatory reaction. Uncontrolled, it becomes chronic and leads to fibrous tissue encapsulation of the implant and sensor and hindrance of their function. Therefore, the fibro-inflammatory reaction needs to be properly kept under control. Choi et al.<span>¹</span> used an anti-inflammatory steroid (dexamethasone acetate)-eluting patch. Alternative strategies that may be considered in the future are using anti-inflammatory drug release, implant coating, micro- and nanopatterning, and surface functionalization, which may simplify the implant design. Because the use of stiff materials leads to the activation of integrin and the release","PeriodicalId":74135,"journal":{"name":"MedComm - Future medicine","volume":"3 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mef2.78","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140552956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"PO-AKID-teller: An interpretable machine learning tool for predicting acute kidney injury requiring dialysis after acute type A aortic dissection surgery","authors":"Qiuying Chen,&nbsp;Biao Fu,&nbsp;Jue Yang,&nbsp;Zhe Jin,&nbsp;Lu Zhang,&nbsp;Ruixin Fan,&nbsp;Bin Zhang,&nbsp;Shuixing Zhang","doi":"10.1002/mef2.77","DOIUrl":"https://doi.org/10.1002/mef2.77","url":null,"abstract":"<p>Postoperative acute kidney injury requiring dialysis (PO-AKID) is a serious adverse event that not only affects acute morbidity and mortality, but also long-term prognosis. Here, we developed a practical and explainable web-based calculator (PO-AKID-teller) to detect patients who might experience PO-AKID after acute type A aortic dissection (ATAAD) surgery. This retrospective study reviewed 549 patients undergoing ATAAD surgery from October 2016 to June 2021. PO-AKID frequency was 19.7% (108 of 549 patients). The initial dataset was split into an 80% training cohort (<i>n</i> = 439) and a 20% test cohort (<i>n</i> = 110). There were seven predictors that could indicate PO-AKID, including prior cardiovascular surgery, platelet, serum creatinine, the terminal site of dissection involvement, right coronary artery involvement, estimated blood loss, and urine output. Among six machine learning classifiers, the random forest model exhibited the best predictive performance, with an area under the curve of 0.863 in the training cohort and 0.763 in the test cohort. This model was translated into a web-based risk calculator PO-AKID-teller to estimate an individual's probability of PO-AKID. The PO-AKID-teller can accurately estimate an individual's risk for PO-AKID in an interpretable manner, which may aid in informed decision-making, patient counseling, perioperative optimization, and longer-term care provision.</p>","PeriodicalId":74135,"journal":{"name":"MedComm - Future medicine","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mef2.77","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140291397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advancing systemic disease diagnosis through ophthalmic image-based artificial intelligence","authors":"Hanpei Miao,&nbsp;Zixing Zou,&nbsp;Jie Xu,&nbsp;Yuanxu Gao","doi":"10.1002/mef2.75","DOIUrl":"https://doi.org/10.1002/mef2.75","url":null,"abstract":"<p>The eye serves as a unique window into systemic health, offering clinicians a valuable opportunity for early detection and targeted treatment. Against this backdrop, advancements in artificial intelligence (AI) and ophthalmic imaging are converging to pave the way for more precise and predictive diagnostics. This review aims to elucidate the transformative role of AI in utilizing ophthalmic imaging for the detection and prediction of systemic diseases. We begin by introducing the advantages of the eye as a valuable tool for detecting systemic diseases. We also provide an overview of various ophthalmic imaging techniques that have proven useful in predicting systemic ailments. Then, we summarize two research patterns for analyzing ocular data, followed by the introduction of current AI applications using ophthalmic images that significantly increase diagnostic precision. Despite the promise, challenges such as data heterogeneity and model interpretability persist, which are also covered in this review. We conclude by discussing future directions and the immense potential these AI-enabled approaches hold for revolutionizing healthcare. As AI technologies advance, their potential integration with ophthalmic imaging offers promising avenues for improving the diagnosis, prediction, and management of various systemic diseases, thereby contributing to the evolving landscape of integrated healthcare.</p>","PeriodicalId":74135,"journal":{"name":"MedComm - Future medicine","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mef2.75","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140114201","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Innate immunity in diabetic nephropathy: Pathogenic mechanisms and therapeutic targets","authors":"Le-Xin Chen,&nbsp;Shu-Ru Lu,&nbsp;Zhi-Hao Wu,&nbsp;En-Xin Zhang,&nbsp;Qing-Qun Cai,&nbsp;Xiao-Jun Zhang","doi":"10.1002/mef2.76","DOIUrl":"https://doi.org/10.1002/mef2.76","url":null,"abstract":"<p>Diabetic nephropathy (DN) represents a prevalent chronic microvascular complication of diabetes mellitus (DM) and is a major cause of end-stage renal disease. The anfractuous surrounding of DN pathogenesis and the intricate nature of this metabolic disorder often pose challenges in both the diagnosis and treatment of DN compared to other kidney diseases. Hyperglycaemia in DM predispose vulnerable renal cells into microenvironmental disequilibrium and thereby results in innate immunocytes infiltration including neutrophils, macrophages, myeloid-derived suppressor cells, dendritic cells, and so forth. These immune cells play dual roles in kidney injury and closely correlated with the degree of proteinuria in DN patients. Additionally, innate immune signaling cascades, initiated by altered metabolic and hemodynamic in diabetic context, are crucial in instigating and perpetuating renal inflammation, which detrimentally contribute to DN pathogenesis. As such, anti-inflammatory therapies, particularly those targeting innate immunity, hold renoprotective promise in DN. In this article, we reviewed the origin and feature of the above four prominent kidney innate immune cells, analyze their pathogenic role in DN, and discuss potential targeted-therapeutic strategies, aiming to enhance the current understanding of renal innate immunity and hence help to discover promising therapeutic approaches for DN.</p>","PeriodicalId":74135,"journal":{"name":"MedComm - Future medicine","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mef2.76","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140053247","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Acetyl-methyllysine: A new posttranslational modification used to mark chromatin","authors":"Hua Guo,&nbsp;Fangfang Zhou,&nbsp;Long Zhang","doi":"10.1002/mef2.74","DOIUrl":"https://doi.org/10.1002/mef2.74","url":null,"abstract":"<p>A recent study, conducted by Lu-Culligan et al., published in <i>Nature</i>, proposed <i>N^ε</i>-acetyl-<i>N^ε</i> -methyllysine (Kacme) that both methylation and acetylation occur on the same side chain of lysine as a cellular posttranslational modification (PTM) on histone H4.<span>¹</span> Kacme can be recognized and bound by the chromatin protein bromodomain-containing 2 (BRD2), associating with active chromatin marks and enhanced transcriptional initiation. This discovery offers a novel avenue for investigation of chromatin biology (Figure 1).</p><p>Histones play a crucial role in regulating gene expression and chromatin structure through PTMs such as acetylation (Kac) and methylation (Kme), impacting transcriptional activity. Acetylation neutralizes histone's positive charge, weakening the DNA–histone interaction for easier binding with transcription factors. Unlike acetylation, methylation affects reader protein binding and leads to changes in chromatin structure, resulting in transcription suppression or activation.<span>²</span> Although it is commonly believed that acetylation and monomethylation are mutually exclusive modifications on a single residue, chemical principles permit a lysine residue to be stably acetylated and monomethylated to create a tertiary amide, Kacme.</p><p>To provide evidence for the existence of Kacme in cellular proteins, researchers synthesized Fmoc–Lys (Ac, Me)-OH as a building block to create a central Kacme residue peptide library and used them as an antigen to generate a specific antiserum against Kacme.<span>¹</span> Kacme antisera demonstrated high specificity toward Kacme peptides but not otherwise identical Kac, Kme1, and propionyllysine (Kpr). By utilizing this antiserum, researchers analyzed intracellular Kacme modifications in fruit fly, mouse, and human cell lines and identified histone H4 Lys5 and Lys12 as Kacme-modified sites in human cells. To confirm Kacme modification through an antisera-independent approach, the authors isotopically labeled the synthetic H4K5acme peptide to obtain distinct ion diagnostic peaks before conducting intracellular proteomic analysis, which further supported the presence of Kacme in histones.</p><p>Chromatin immunoprecipitation sequencing (ChIP-seq) is an extremely powerful tool for studying interactions between multiple transcription factors and other chromatin-associated proteins and DNA.<span>³</span> By performing ChIP-seq with Kacme antisera in fruit flies and human cells, the authors found that Kacme was significantly enriched around gene promoters, especially in highly expressed genes, and its localization was strongly associated with active chromatin modifications. Subsequently, Lu-Culligan et al. conducted transient-transcriptome time-lapse sequencing to examine transcriptional activity, and start-time-lapse sequencing to investigate the kinetics of promoter–proximal pausing,<span><sup>1</sup","PeriodicalId":74135,"journal":{"name":"MedComm - Future medicine","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mef2.74","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139942923","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Computed tomography-based artificial intelligence in lung disease—Chronic obstructive pulmonary disease","authors":"Fangfei Wang,&nbsp;Sixiang Li,&nbsp;Yuanxu Gao,&nbsp;Shiyue Li","doi":"10.1002/mef2.73","DOIUrl":"https://doi.org/10.1002/mef2.73","url":null,"abstract":"<p>Chronic obstructive pulmonary disease (COPD) stands as a global health crisis, responsible for substantial morbidity and mortality on a worldwide scale. Its insidious nature underscores the importance of early detection and accurate diagnosis. While spirometry has been the cornerstone for COPD diagnosis, the role of computed tomography (CT) imaging has evolved, offering a valuable avenue for early detection and subtype classification. Recently, the advent of artificial intelligence (AI) has brought forth the potential to revolutionize the accuracy and efficiency of COPD diagnosis, with a specific focus on CT images. This intersection of healthcare and technology signifies a paradigm shift in the way we approach COPD management. The transformative capacity of AI positions it as a vital instrument for early detection and precise subtype classification of COPD. Moreover, the synergistic relationship between medical imaging and AI paves the way for more precise and efficient disease management. Therefore, in this perspective, we tend to offer a comprehensive exploration of the latest breakthroughs in the field of CT-based AI in COPD diagnosis, aiming to demonstrate the promise and potential of AI in refining the accuracy of COPD classification and to illuminate the evolving landscape of AI's impact on COPD management.</p>","PeriodicalId":74135,"journal":{"name":"MedComm - Future medicine","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mef2.73","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139901662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Antitumor effects of TIM-1 blockade in B cells","authors":"Wenwen Liu,&nbsp;Jian Huang","doi":"10.1002/mef2.71","DOIUrl":"https://doi.org/10.1002/mef2.71","url":null,"abstract":"<p>A research by Bod et al.<span>¹</span> has been published recently in <i>Nature</i> entitled “B-cell-specific checkpoint molecules that regulate anti-tumor immunity‘.” It revealed that T-cell immunoglobulin and mucin domain protein 1 (TIM-1) blockade can strikingly reduce the melanoma size in mouse models.</p><p>In the field of antitumor immunotherapy, researchers have been extensively studying the role of T cells in fighting against tumors. However, the function of B cells in antitumor immunity has remained unclear or controversial. To address this gap, this collaboration study among Harvard, MIT, and many others has shed light on a crucial molecule called TIM-1, which for the first time, has been claimed to act as a specific checkpoint on B cells.<span>¹</span></p><p>TIM-1 is also known as hepatitis A virus cellular receptor 1 (HAVCR1) and kidney injury molecule 1 as well. It is a membrane glycoprotein encoded by the <i>Havcr1</i> gene. Expressed on various cells as a receptor for many viruses and ligands, TIM-1 has been reported to involve in kidney diseases, atopic diseases, T-cell activation and cancers.<span>^2-4</span> Antibody–drug targeting TIM-1 has also been developed for treating cancers with high TIM-1 expression.<span>⁴</span> In Phase I clinical trial, CDX-014, an antibody–drug conjugate against TIM-1, exhibited a manageable toxicity profile and early signs of activity in 16 patients with advanced refractory renal cell cancer.<span>⁴</span> However, no scholar considers the role of TIM-1 on B cells in these studies, not to speak of as a B-cell-specific checkpoint molecule.</p><p>Immune checkpoints are host molecules that have the ability to suppress immune responses.<span>⁵</span> Their expression will suppress antitumor immune responses in cancer. In past studies, researchers have primarily focused on enhancing the immune response of T cells, particularly cytotoxic T lymphocytes, in the fight against cancer. The discovery of immune checkpoints, such as the PD-1/PD-L1 and the CTLA4/B7 pathways sparked a wave of interest in T-cell-specific immune checkpoint inhibitors for cancer treatment. However, the authors of this study sought to investigate B cells, as they are one of the most abundant cell types that infiltrate tumors, especially in melanoma.</p><p>To understand the role of B cell subsets in melanoma, the researchers employed the well-established B16F10 melanoma mouse model and collected immune cells at 7, 10, and 16 days after tumor cell injection. Subsequently, bulk messenger RNA-sequencing was performed on the tumor group along with draining lymph nodes (dLNs), nondraining lymph nodes (ndLNs), and spleen groups at Day 16 postinjection to examine the expression profiles of B cells across different groups. To further comprehend the heterogeneity of B cells within tumor infiltration, single-cell RNA sequencing (scRNA-seq) combined with B-cell receptor sequenci","PeriodicalId":74135,"journal":{"name":"MedComm - Future medicine","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mef2.71","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139643902","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep-learning-based diagnosis of myopia in children using optical coherence tomography angiography","authors":"Wenchao Xiao,&nbsp;Lu Yuxing,&nbsp;Hanpei Miao,&nbsp;Wenting Zhao,&nbsp;David Schanzlin","doi":"10.1002/mef2.72","DOIUrl":"https://doi.org/10.1002/mef2.72","url":null,"abstract":"<p>As myopia develops and progresses at an accelerated pace during adolescence, a timely diagnosis is beneficial for preventing its further progression. Optical coherence tomography angiography (OCTA) can visualize distinct layers of retinal microvessels, offering valuable insights into structural changes associated with myopia. This capability facilitates the early detection and monitoring of myopia-related complications, such as choroidal neovascularization and myopic maculopathy. Previous research suggests that alterations in the superficial capillary plexus (SCP) vessel density and deep capillary plexus (DCP) of OCTA images occur in myopic eyes, but few studies have focused on myopia in younger children.<span>¹</span> A recent study compared retinal microvasculature in the SCP of children and adolescents using OCTA imaging, which indicated that there were no obvious variations in microvessel density, perfusion density (PD), and the size of the foveal avascular zone within the SCP between groups with mild and moderate/high myopia.<span>²</span> Conversely, another study demonstrated a negative correlation between children's myopia diopter and the microvessel density of both the superficial and deep retinal capillary plexus in the macula, as well as retinal thickness.<span>³</span> Nonetheless, these studies only scrutinized a limited number of OCTA image parameters in the macular region and involved a relatively small number of subjects. Further research is warranted to fully understand the potential of OCTA images in assessing myopia during adolescence.</p><p>Deep learning can extract high-dimensional features from images through its multilayer network architecture, leading to improved task performance. However, to our knowledge, there is limited research on the use of artificial intelligence for analyzing OCTA images related to myopia. Our study contributes to addressing this research gap by highlighting the potential of deep learning in OCTA image analysis for myopia assessment. In this study, we aimed to employ end-to-end deep learning models to classify children with mild versus severe myopia. This study aimed to evaluate the potential of deep and superficial blood vessels in the macula and optic disc as indicators of myopia severity in children, utilizing a classification task based on OCTA images.</p><p>Initially, we collected four images from both the superficial and deep retinal capillary plexus in the macula, as well as from the optic disc, of children aged 8–16. Exclusion criteria included poor quality OCTA images, patients with other ocular conditions, or those who had undergone eye surgery. Ultimately, a total of 129 children (242 eyes) were included in this study. The subjects were divided into two groups based on their degree of refractive error: emmetropia/mild myopia (177 eyes, with a mean spherical equivalent between −3.00 and ≤0.50 D) and moderate/high myopia (65 eyes, with a mean spherical e","PeriodicalId":74135,"journal":{"name":"MedComm - Future medicine","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mef2.72","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139434995","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AlphaMissense, a groundbreaking advancement in artificial intelligence for predicting the effects of missense variants","authors":"Ming Yi,&nbsp;Yunqiang Liu,&nbsp;Zhiguang Su","doi":"10.1002/mef2.70","DOIUrl":"https://doi.org/10.1002/mef2.70","url":null,"abstract":"<p>In a recent study published in <i>Science</i>,<span>¹</span> Cheng and colleagues developed a highly accurate protein structuring model named AlphaMissense, which can predict and characterize the pathogenicity of all possible missense variants in the human genome at a single amino acid substitution level. As a community resource, AlphaMissense is absolutely helping us to gain better insights into the functional consequences of genetic variation.</p><p>Despite the identification of over 4 million missense variants in the human genome, only approximately 2% are definitively annotated as pathogenic or benign, and the significance of the large proportion of missense variants is unknown. As such, there has been a push to search for highly effective methods to accurately predict the variants' clinical implications.</p><p>Presently, four primary methodologies have been used to predict the pathogenicity of genetic variations. The first class of methods is known as “database-driven approaches,” which rely extensively on meticulously curated databases. Such strategies suffer from data leakage caused by unintended information transfer between the training and test halves, posing a significant challenge to reliability and accuracy.<span>^{1, 2}</span> The second class of methods is referred to as “weak-labeling approaches,” which circumvent circularity concerns by eliminating human annotations. However, such models often encounter false labels in the training data, necessitating the use of more reliable labels for accurate evaluation. A third class of approaches focuses on the recognition of naturally evolved amino acid sequence distributions and hidden structures of proteins, providing insights into the evolutionary patterns and functional characteristics of proteins.<span>¹</span> Such models, however, do not possess the advanced understanding of protein structure achieved by AlphaFold (AF).<span>³</span> A fourth approach utilizes protein structure information to improve the assessment of genetic constraints. However, this approach encounters a new challenge in the accuracy of predicting variant pathogenicity based solely on structural features. The limited performance of the structure-based approach in predicting pathogenicity in ClinVar variations suggests that additional factors, such as functional annotations as well as population frequencies and clinical evidence, play a crucial role in determining the pathogenicity of a genetic variant.<span>¹</span></p><p>AlphaMissense, constructed upon the protein structure prediction model of AF, is a machine-learning model that utilizes advancements in unsupervised protein language modeling (Figure 1). AF represents a groundbreaking method that enables the prediction of a protein's three-dimensional structure solely from its amino acid sequence.<span>³</span> By incorporating the structural insights provided by AF, researchers have achieved notabl","PeriodicalId":74135,"journal":{"name":"MedComm - Future medicine","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mef2.70","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139109790","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}