Artificial intelligence (AI), currently a cutting-edge concept, has the potential to improve the quality of life of human beings. The fields of AI and biological research are becoming more intertwined, and methods for extracting and applying the information stored in live organisms are constantly being refined. As the field of AI matures with more trained algorithms, the potential of its application in epidemiology, the study of host–pathogen interactions and drug designing widens. AI is now being applied in several fields of drug discovery, customized medicine, gene editing, radiography, image processing and medication management. More precise diagnosis and cost-effective treatment will be possible in the near future due to the application of AI-based technologies. In the field of agriculture, farmers have reduced waste, increased output and decreased the amount of time it takes to bring their goods to market due to the application of advanced AI-based approaches. Moreover, with the use of AI through machine learning (ML) and deep-learning-based smart programs, one can modify the metabolic pathways of living systems to obtain the best possible outputs with the minimal inputs. Such efforts can improve the industrial strains of microbial species to maximize the yield in the bio-based industrial setup. This article summarizes the potentials of AI and their application to several fields of biology, such as medicine, agriculture, and bio-based industry.

/pdf/artificial-intelligence-in-biological-sciences-sghujqdo.pdf

Artificial Intelligence in Biological Sciences

The maculopathy in highly myopic eyes is complex. Its clinical diagnosis is a huge workload and subjective. To simply and quickly classify pathologic myopia (PM), a deep learning algorithm was developed and assessed to screen myopic maculopathy lesions based on color fundus photographs.This study included 10,347 ocular fundus photographs from 7606 participants. Of these photographs, 8210 were used for training and validation, and 2137 for external testing. A deep learning algorithm was trained, validated, and externally tested to screen myopic maculopathy which was classified into four categories: normal or mild tessellated fundus, severe tessellated fundus, early-stage PM, and advanced-stage PM. The area under the precision-recall curve, the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, accuracy, and Cohen's kappa were calculated and compared with those of retina specialists.In the validation data set, the model detected normal or mild tessellated fundus, severe tessellated fundus, early-stage PM, and advanced-stage PM with AUCs of 0.98, 0.95, 0.99, and 1.00, respectively; while in the external-testing data set of 2137 photographs, the model had AUCs of 0.99, 0.96, 0.98, and 1.00, respectively.We developed a deep learning model for detection and classification of myopic maculopathy based on fundus photographs. Our model achieved high sensitivities, specificities, and reliable Cohen's kappa, compared with those of attending ophthalmologists. 

https://link.springer.com/content/pdf/10.1007/s40123-022-00621-9.pdf

Efficacy of a Deep Learning System for Screening Myopic Maculopathy Based on Color Fundus Photographs

Wound healing is a complex and meticulously orchestrated process involving multiple phases and cellular interactions. This narrative review explores the intricate mechanisms behind wound healing, emphasizing the significance of cellular processes and molecular factors. The phases of wound healing are discussed, focusing on the roles of immune cells, growth factors, and extracellular matrix components. Cellular shape alterations driven by cytoskeletal modulation and the influence of the 'Formin' protein family are highlighted for their impact on wound healing processes. This review delves into the use of absorbable meshes in wound repair, discussing their categories and applications in different surgical scenarios. Interleukins (IL-2 and IL-6), CD31, CD34, platelet rich plasma (PRP), and adipose tissue-derived mesenchymal stem cells (ADSCs) are discussed in their respective roles in wound healing. The interactions between these factors and their potential synergies with absorbable meshes are explored, shedding light on how these combinations might enhance the healing process. Recent advances and challenges in the field are also presented, including insights into mesh integration, biocompatibility, infection prevention, and postoperative complications. This review underscores the importance of patient-specific factors and surgical techniques in optimizing mesh placement and healing outcomes. As wound healing remains a dynamic field, this narrative review provides a comprehensive overview of the current understanding and potential avenues for future research and clinical applications.

The Effects of Tissue Healing Factors in Wound Repair Involving Absorbable Meshes: A Narrative Review.

Objectives: The aim of this study was to explore the impact of the 2020–2022 pandemic on the levels of fear and anxiety in pregnant women and to identify risk and protective factors. Methods: A systematic review was conducted. Electronic databases were consulted for studies published between January 2020 and August 2022. The methodological quality was assessed using a critical appraisal tool for non-randomised studies. Results: Seventeen studies were included in the review. A high prevalence of levels of fear and anxiety were observed. Risk factors such as unplanned pregnancy, poor support from partners, or intolerance of uncertainty were identified for high levels of fear. Regarding anxiety, risk factors such as maternal age, social support, financial status, or concern about being able to maintain antenatal follow-ups were identified. Conclusion: The COVID-19 pandemic had a significant impact on the mental health of pregnant women through increased levels of fear and anxiety. It has not been possible to establish a relationship between significant factors such as gestational age or health emergency control measures with high levels of fear or anxiety.

/pdf/fear-and-anxiety-in-pregnant-women-during-the-covid-19-1i680pz8.pdf

Fear and Anxiety in Pregnant Women During the COVID-19 Pandemic: A Systematic Review

Fear of childbirth (FOC) is a prevalent issue among pregnant women and significantly relates to adverse outcomes for the mother and child. However, it is not clear the prevalence and risk factors of FOC among pregnant women in a region with a moderate level of economic development in China. The aim of this study was to investigate the prevalence and risk factors of FOC among pregnant women in the third trimester of pregnancy in Lianyungang city, Eastern China.A cross-sectional survey was conducted from December 2022 to February 2023 among pregnant women in the third trimester who met the inclusion criteria and visited Lianyungang Maternal and Child Health Hospital in Jiangsu Province, Eastern China. A structured questionnaire including sociodemographic characteristics, clinical characteristics, FOC, family function, doctor-patient communication, social support, general self-efficacy, anxiety, depression, insomnia symptoms, and quality of life was used to collect data. A multiple linear regression model was used to identify predictors of FOC.This study included 535 pregnant women in the third trimester. The mean score of FOC was 30.67 ± 10.18, and the median score was 29.00. The prevalence of FOC was 56.64%. Multiple linear regression analysis revealed that pregnant women with electronic screen exposure time more than 5 h per day (β = 2.02, 95%CI: 0.50-3.53, P < 0.05), no history of cesarean section (β = 2.66, 95%CI: 0.61-4.71, P < 0.05), likes sour food or hates greasy food (β = 1.75, 95%CI: 0.00-3.50, P < 0.05), anxiety (β = 0.50, 95%CI: 0.21-0.80, P < 0.05) and depression (β = 0.30, 95%CI: 0.04-0.57, P < 0.05) were more likely to have a greater level of FOC than their counterparts. However, a significantly lower level of FOC was observed in pregnant women who were multipara (β=-1.64, 95%CI: -3.27-0.01, P < 0.05), not worrying about delivery without family members (β=-3.75, 95%CI: -5.26-2.25, P < 0.001), had good family function (β=-0.32, 95%CI: -0.64-0.00, P < 0.05) and doctor-patient communication (β=-0.33, 95%CI: -0.64-0.02, P < 0.05).The prevalence of FOC was high in Lianyungang city, Eastern China. FOC is influenced by multiple factors. There is an urgent need to develop interventions to reduce the prevalence of FOC in the third trimester of pregnancy, and to pay attention to pregnant women with risk factors for FOC. 

Fear of childbirth and its determinants in pregnant women in the third trimester: a cross-sectional study

Fibrosis is a detrimental outcome of most chronic inflammatory disorders and is defined by the buildup of excess extracellular matrix (ECM) components, which eventually leads to organ failure and death. Interleukin 6 (IL-6) is promptly produced by immune cells in response to tissue injuries and has a wide range of effects on cellular processes such as acute responses, hematopoiesis, and immune reactions. Furthermore, high levels of IL-6 have been found in a variety of chronic inflammatory disorders characterized by fibrosis, and this factor plays a significant role in fibrosis in various organs via Janus kinase/signal transducer and activator of transcription 3 (JAK/STAT3) activation. Here, we review what is known about the role of IL-6 in fibrosis and why targeting IL-6 for fibrotic disease treatment makes sense.

/pdf/the-role-of-il-6-in-fibrotic-diseases-molecular-and-cellular-2mymi30s.pdf

The Role of IL-6 in Fibrotic Diseases: Molecular and Cellular Mechanisms

With the continuous development of computer technology, big data acquisition and imaging methods, the application of artificial intelligence (AI) in medical fields is expanding. The use of machine learning and deep learning in the diagnosis and treatment of ophthalmic diseases is becoming more widespread. As one of the main causes of visual impairment, myopia has a high global prevalence. Early screening or diagnosis of myopia, combined with other effective therapeutic interventions, is very important to maintain a patient's visual function and quality of life. Through the training of fundus photography, optical coherence tomography, and slit lamp images and through platforms provided by telemedicine, AI shows great application potential in the detection, diagnosis, progression prediction and treatment of myopia. In addition, AI models and wearable devices based on other forms of data also perform well in the behavioral intervention of myopia patients. Admittedly, there are still some challenges in the practical application of AI in myopia, such as the standardization of datasets; acceptance attitudes of users; and ethical, legal and regulatory issues. This paper reviews the clinical application status, potential challenges and future directions of AI in myopia and proposes that the establishment of an AI-integrated telemedicine platform will be a new direction for myopia management in the post-COVID-19 period.

/pdf/applications-of-artificial-intelligence-in-myopia-current-1u8ew08o.pdf

Applications of Artificial Intelligence in Myopia: Current and Future Directions

Background Fear of childbirth (FOC) is one of the most common psychological symptoms among pregnant women and significantly relates to cesarean section, anxiety, and depression. However, it is not clear the prevalence and risk factors of FOC among Chinese pregnant women since the outbreak of the COVID-19 pandemic. Aims The objective of this study was to examine the associations between coping styles, intolerance of uncertainty, and FOC. Method From December 2021 to April 2022, a cross-sectional survey was conducted in two hospitals in China through convenient sampling. The cross-sectional survey was conducted among 969 pregnant women, which included the Childbirth Attitude Questionnaire (CAQ), Intolerance of Uncertainty Scale-12 (IUS-12), and Simplified Coping Style Questionnaire (SCSQ). Results The total prevalence of FOC was 67.8%. The percentages of women with mild (a score of 28–39), moderate (40–51), and severe FOC (52–64) were 43.6, 20.2, and 4.0%, respectively. The regression results indicated that primiparas, unplanned pregnancy, few spousal support, intolerance of uncertainty, and negative coping styles were significant risk factors of FOC. Women who adopt positive coping strategies experienced a lower level of childbirth fear. Conclusion These findings suggest that cultivating positive coping styles and obtaining sufficient childbirth information may be helpful for mothers' mental health. Regular screening assessment of perinatal psychological symptoms, such as the high level of intolerance of uncertainty and negative coping styles, should be adopted to reduce the risk of fear of childbirth.

/pdf/the-prevalence-of-fear-of-childbirth-and-its-association-3d386eqv.pdf

The Prevalence of Fear of Childbirth and Its Association With Intolerance of Uncertainty and Coping Styles Among Pregnant Chinese Women During the COVID-19 Pandemic

Abstract Corneal neovascularization (CNV) is an ocular pathological change that results from an imbalance between angiogenic factors and antiangiogenic factors as a result of various ocular insults, including infection, inflammation, hypoxia, trauma, corneal degeneration, and corneal transplantation. Current clinical strategies for the treatment of CNV include pharmacological treatment and surgical intervention. Despite some degree of success, the current treatment strategies are restricted by limited efficacy, adverse effects, and a short duration of action. Recently, gene-based antiangiogenic therapy has become an emerging strategy that has attracted considerable interest. However, potential complications with the use of viral vectors, such as potential genotoxicity resulting from long-term expression and nonspecific targeting, cannot be ignored. The use of ocular nanosystems (ONS) based on nanotechnology has emerged as a great advantage in ocular disease treatment during the last two decades. The potential functions of ONS range from nanocarriers, which deliver drugs and genes to target sites in the eye, to therapeutic agents themselves. Various preclinical studies conducted to date have demonstrated promising results of the use of ONS in the treatment of CNV. In this review, we provide an overview of CNV and its current therapeutic strategies and summarize the properties and applications of various ONS related to the treatment of CNV reported to date. Our goal is to provide a comprehensive review of these considerable advances in ONS in the field of CNV therapy over the past two decades to fill the gaps in previous related reports. Finally, we discuss existing challenges and future perspectives of the use of ONS in CNV therapy, with the goal of providing a theoretical contribution to facilitate future practical growth in the area.

An Update on Novel Ocular Nanosystems with Possible Benefits in the Treatment of Corneal Neovascularization

/pdf/paracentral-acute-middle-maculopathy-secondary-to-high-196z7ekm.pdf

Paracentral acute middle maculopathy secondary to high intraocular pressure: a case report.

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