Ovarian cancer awareness of women in Turkey: A cross-sectional study

PURPOSE

Early diagnosis of ovarian cancer (OC) increases survival rates; however, due to low awareness levels, women may be diagnosed with OC at the advanced stage. The aim of this cross-sectional study is to reveal the OC awareness of Turkish women and affecting factors.

METHODS

Participants were invited to study via social media tools between February-June 2022. Data was collected with Personal Information Form and the "OC Awareness Scale" from 446 women.

RESULTS

81% of the participants did not recall OC symptoms, 80.8% recognized OC risk factors. The most frequently recalled and recognized OC symptom is pelvic pain (19.8%; 55.8%, respectively). The most frequently recalled and recognized OC risk factors were smoking (43.1%, 67.9%, respectively) and family history (39%, 58.7%, respectively). 2% of the participants felt very confident in recognizing the signs, 72.9% would seek help within 1-2 days when they recognized the signs of OC.

CONCLUSIONS

The awareness of OC was higher among women who had advanced age, higher education, family history and were in menopause. Turkish women have low level of awareness and knowledge about OC symptoms and risk factors. There is an urgent need for an OC awareness campaign that takes into account the socio-demographic characteristics of women. The results of the study may also guide strategies to prevent OC.

DLgram cloud service for deep-learning analysis of microscopy images

To analyze images in various fields of science and technology, it is often necessary to count observed objects and determine their parameters. This can be quite labor-intensive and time-consuming. This article presents DLgram, a universal, user-friendly cloud service that is developed for this purpose. It is based on deep learning technologies and does not require programming skills. The user labels several objects in the image and uploads it to the cloud where the neural network is trained to recognize the objects being studied. The user receives recognition results, which if necessary, can be corrected, errors removed, or missing objects added. In addition, it is possible to carry out mathematical processing of the data obtained to get information about the sizes, areas, and coordinates of the observed objects. The article describes the service features and discusses examples of its application. The DLgram service allows to reduce significantly the time spent on quantitative image analysis, reduce subjective factor influence, and increase the accuracy of analysis. RESEARCH HIGHLIGHTS: DLgram automatically recognizes and counts the number of objects in images and their parameters. DLgram is a universal service, which was created on the basis of the latest deep learning developments and does not require programming skills.

Accurate recognition of rice plants based on visual and tactile sensing

BACKGROUND

Crop recognition is the basis of intelligent agricultural machine operations. Visual perception methods have achieved high recognition accuracy. However, the reliability of such methods is difficult to guarantee because of the complex environment of paddy fields. Tactile sensing methods are not affected by background or environmental interference, and have high reliability. However, in an ideal environment, the recognition accuracy is not as high as that of the visual method.

RESULTS

To balance the accuracy and reliability of rice plant recognition, a combined visual-tactile method was proposed in this study. A rice plant recognition device was developed with a poly(vinylidene fluoride) sensor embedded inside the device as a tactile perceptron and a graphic designed as a visual perceptron. The primary role of the tactile perceptron is to initially recognize rice plants and provide a time point for image capture for visual perception. The main role of the visual perceptron is to extract features from the captured images and recognize rice plants again. The results of tactile and visual recognition were eventually fused to achieve accurate recognition of rice plants.

CONCLUSION

The contact speed between the recognition perceptron and rice-weed was selected for the field performance test based on the real situation of paddy field operation. The results showed that the accuracy and reliability of rice plant recognition decreased as the travelling speed of the paddy field operation machine increased. The results of this study provide a basis for intelligent farm machinery operations in rice fields. © 2024 Society of Chemical Industry.

Pronounced Self-Induced Diastereomeric Anisochronism in Anisidine Amino Acid Diamides

The emergent properties resulting from selective supramolecular interactions are of significant importance for materials and chemical systems. For the directed use of such properties, a fundamental understanding of the interaction mechanism and the resulting mode of function is necessary for a tailored design. The self-induced diastereomeric anisochronism effect (SIDA), which occurs in the intermolecular interaction of chiral molecules, generates unique properties such as chiral self-recognition and nonlinear effects. Here we show that anisidine amino acid diamides lead to extraordinary signal splitting in NMR spectra through supramolecular interaction and homochiral self-recognition. By systematic experiments we have investigated the underlying SIDA effect, explored its limits and finally successfully utilized it in the determination of enantiomeric ratios by NMR spectroscopy of chiral 'SIDA-inactive' compounds such as thalidomide.

Precise Capture and Dynamic Release of Circulating Liver Cancer Cells with Dual-histidine-based Cell Imprinted Hydrogels

Circulating tumor cells (CTCs) detection presents significant advantages in diagnosing liver cancer due to its non-invasiveness, real-time monitoring, and dynamic tracking. However, the clinical application of CTCs-based diagnosis is largely limited by the challenges of capturing low-abundance CTCs within a complex blood environment while ensuring them alive. Here we design an ultra-strong ligand, L-histidine-L-histidine (HH), specifically targeting sialylated glycans on the surface of CTCs. Further HH is integrated into a cell-imprinted polymer, constructing a hydrogel with precise CTCs imprinting, high elasticity, satisfactory blood-compatibility, and robust anti-interference capacities. These features endow the hydrogel with excellent capture efficiency (>95%) for CTCs in peripheral blood, as well as the ability to release CTCs controllably and alive. Clinical tests substantiate the accurate differentiation between liver cancer, cirrhosis, and healthy groups using this method. The remarkable diagnostic accuracy (94%), lossless release of CTCs, material reversibility, and cost-effectiveness (6.68 dollars per sample) make the HH-based hydrogel a potentially revolutionary technology for liver cancer diagnosis and single-cell analysis. This article is protected by copyright. All rights reserved.

Exploiting the Mechanical Bond Effect for Enhanced Molecular Recognition and Sensing

The ubiquity of charged species in biological and industrial processes has resulted in ever-increasing interest in their selective recognition, detection, and environmental remediation. Building on the established coordination chemistry principles of the chelate and macrocyclic effects, and host preorganization, supramolecular chemists seek to construct specific 3D binding cavities reminiscent of biotic systems to enhance host-guest binding affinity and selectivity. Mechanically interlocked molecules (MIMs) present a wholly unique platform for synthetic host design, wherein topologies afforded by the mechanical bond enable the decoration of 3D cavities for non-covalent interactions with a range of target guest geometries. Notably, MIM host systems exhibit mechanical bond effect augmented affinities and selectivities for a variety of charged guest species, compared to non-interlocked acyclic and macrocycle host analogs. Furthermore, the modular nature of MIM synthesis facilitates incorporation of optical and electrochemical reporter groups, enabling fabrication of highly sensitive and specific molecular sensors. This review discusses the development of recognition and sensing MIMs, from the first reports in the late 20th century through to the present day, delineating how their topologically preorganized and dynamic host cavities enhance charged guest recognition and sensing, demonstrating the mechanical bond effect as a potent tool in future chemosensing materials.

Recognizing Borderline Personality Disorder in Men: Gender Differences in BPD Symptom Presentation

Women are predominantly diagnosed with BPD, with studies estimating a 3:1 female-to-male diagnostic ratio in clinical settings. Previous studies present conflicting findings regarding gender-level criterion differences, with some indicating differences in contradictory criteria. These studies primarily utilize outpatient samples, highlighting gaps in the literature. Thus, the current study investigates gender-level criterion differences, functioning, and impairment within a novel, partial hospital sample. Participants included (a) a sample of 1,153 individuals from the total population of partial hospital patients regardless of BPD diagnosis and (b) 365 BPD-positive patients who were assessed via semistructured clinical interview and provided consent for data collection during the intake process. Results indicated that (a) women endorsed higher relationship instability than men and (b) there were no significant differences in level of functioning across the gender subsamples. Examining gender differences in BPD symptomatology has clinical implications in improving recognition and addressing potential biases associated with men and mental health.

Diagnosing and Discussing Sexual Abuse: A Scoping Review on Training Methods for Health Care Professionals

Purpose

Sexual abuse is a health issue with many consequences. Recognizing and discussing past sexual abuse has proven to be challenging for health care professionals. To improve overall quality of health care for sexual abuse victims, health care professionals need to be properly trained. The aim of this paper is to provide an overview of training methods for health care professionals and to report on their effectiveness.

Methods

A scoping review was conducted. A broad search was executed in six databases in December 2022. Study selection was performed by two independent reviewers, followed by quality assessment and data extraction.

Results

After screening of titles and abstracts and later full-text assessment for quality appraisal, seven articles were selected, consisting mostly of non-randomized trials, performed among a total of 1299 health care professionals. All studies were assessed to be of moderate to poor quality. The participants attended training courses with a wide variety of durations, settings, formats and methods. The outcomes showed improvements in self-perceived or measured knowledge, skills and confidence to discuss sexual violence. Changes in clinical practice were scarcely investigated. Training courses were most effective when a mix of didactic passive methods, such as lectures and videos, and active participatory strategies, such as discussions and roleplay, were applied. Timely iteration to reinforce retention of gained knowledge and skills also contributed to effectiveness. Participants most enjoyed incorporating opportunities for receiving feedback in small settings and sharing personal experiences.

Conclusion

This scoping review summarizes on how to effectively train health care professionals. Flaws and difficulties in measuring the effectiveness of training courses were discussed. Recognition and discussion of past sexual abuse by health care providers can be effectively trained using an alternating mix of multiple active and passive training methods with room for feedback and personal experiences.

sEMG-Based Robust Recognition of Grasping Postures with a Machine Learning Approach for Low-Cost Hand Control

The design and control of artificial hands remains a challenge in engineering. Popular prostheses are bio-mechanically simple with restricted manipulation capabilities, as advanced devices are pricy or abandoned due to their difficult communication with the hand. For social robots, the interpretation of human intention is key for their integration in daily life. This can be achieved with machine learning (ML) algorithms, which are barely used for grasping posture recognition. This work proposes an ML approach to recognize nine hand postures, representing 90% of the activities of daily living in real time using an sEMG human-robot interface (HRI). Data from 20 subjects wearing a Myo armband (8 sEMG signals) were gathered from the NinaPro DS5 and from experimental tests with the YCB Object Set, and they were used jointly in the development of a simple multi-layer perceptron in MATLAB, with a global percentage success of 73% using only two features. GPU-based implementations were run to select the best architecture, with generalization capabilities, robustness-versus-electrode shift, low memory expense, and real-time performance. This architecture enables the implementation of grasping posture recognition in low-cost devices, aimed at the development of affordable functional prostheses and HRI for social robots.

Recognition of nuts and seeds in children with/without food allergies and their mothers: A reflection of culinary culture

BACKGROUND

Nuts and seeds are among the leading causes of food allergy. Effective food allergy management hinges on the ability to identify and avoid relevant foods.

AIM

To evaluate the nut/seed recognition ability in both children and mothers.

METHODS

Primary caregivers (mothers) and their children (6-18 years old) with/without food allergies were shown photographs of nuts/seeds, and their products with visible/hidden allergens to assess their ability to recognize accurately.

RESULTS

A total of 196 children and 184 mothers participated. The median ages of the children and mothers were 7.6 (6.8-10) and 37.8 (33.1-41.5) years, respectively. Over 75% of the children/adolescents and over 90% of the mothers accurately identified the kernel forms of nuts/seeds, except pine nuts. Walnuts, hazelnuts, almonds, and cashews were the most accurately recognized kernel forms by both populations. Generally, the kernel forms were recognized 5-20% more accurately than their in-shell forms, followed by products with visible and hidden forms, respectively. Some Turkish culinary-specific products with visible/hidden allergens were recognized as frequently as the kernel/in-shell forms by both study groups. Although there was a similar recognition pattern between study groups and subgroups (nut/seed allergy, other food allergy, controls), higher rates of recognition were found in mothers than in their children and adolescents than in schoolchildren.

CONCLUSION

In Eastern Mediterranean region, nuts and sesame seeds are highly recognized by both mothers and their children. Accurate identification of these foods is likely a culinary feature, but not the result of increased awareness. More information is needed on whether this ability reduces the risk of exposure.

Productions Need Not Match Study Items to Confer a Production Advantage, But It Helps

The production effect is the finding that, relative to silent reading, producing information at study (e.g., reading aloud) leads to a benefit in memory. In most studies of this effect, individuals are presented with a set of unique items, and they produce a subset of these items (e.g., they are presented with the to-be-remembered target item TABLE and produce table) such that the production is both unique and representative of the target. Across two preregistered experiments, we examined the influence of a production that is unique but that does not match the target (e.g., producing fence to the target TABLE, producing car to the target TREE, and so on). This kind of production also yielded a significant effect-the mismatching production effect-although it was smaller than the standard production effect (i.e., when productions are both unique and representative of their targets) and was detectable only when targets with standard productions were included in the same study phase (i.e., when the type of production was manipulated within participant). We suggest that target-production matching is an important precursor to the production effect and that the kind of production that brings about a benefit depends on the other productions that are present.

Self-management Support for Patients with Atopic Dermatitis: A Qualitative Interview Study

Patients with a chronic skin disease, eg, atopic dermatitis, need self-management skills to increase their quality of life. We explored patients' needs for self-management support from healthcare professionals and how these needs can be met in a dermatology setting. Interpretive description methodology was chosen for iterative data collection and analysis of qualitative interviews with patients with atopic dermatitis. Two mutually dependent themes were found to be supportive of patients' self-management. Personal and disease-related recognition was fundamental to successful support. However, guidance for agenda-setting from healthcare professionals was also needed on the wide range of topics that could be covered in the consultation based on individual needs. Patients need self-management support in addition to what can be found with family, friends, or peers. It is crucial that the support is delivered with an appreciative approach by healthcare professionals with profound knowledge of atopic dermatitis. Equally important is guidance towards agenda-setting, a way to co-construct the consultation with a clear focus on the specific patient's needs.

Digital loneliness-changes of social recognition through AI companions

Inherent to the experience of loneliness is a significant change of meaningful relatedness that (usually negatively) affects a person's relationship to self and others. This paper goes beyond a purely subjective-phenomenological description of individual suffering by emphasizing loneliness as a symptomatic expression of distortions of social recognition relations. Where there is loneliness, a recognition relation has changed. Most societies face an increase in loneliness among all groups of their population, and this sheds light on the reproduction conditions of social integration and inclusion. These functions are essential lifeworldly components of social cohesion and wellbeing. This study asks whether "social" AI promotes these societal success goals of social integration of lonely people. The increasing tendency to regard AI Companions (AICs) as reproducers of adequate recognition is critically discussed with this review. My skepticism requires further justification, especially as a large portion of sociopolitical prevention efforts aim to fight an increase of loneliness primarily with digital strategies. I will argue that AICs rather reproduce than sustainably reduce the pathodynamics of loneliness: loneliness gets simply "digitized."

Institutional suicide as anomie: decedents speak out for work-related suicides through a Durkheimian exploration of suicide notes in a context without institutional responsibilization for suicide prevention

Introduction

Drawing on Durkheim's historical theorization of suicide, we extend his concept of anomic suicide, which is suicide due to a lack of social regulation, to introduce the concept of institutional suicide. We define institutional suicide as suicide due to the absence or decline of institutional policies, practices, and discourses for prevention. In this study, we explore the mechanisms for institutional suicides based on suicide notes Turkey, in a context without institutional responsibilization for prevention. Turkey provides a significant context for studying institutional suicides as policies, practices, and discourses for suicide prevention have been declining for some decades.

Methods

Drawing on publically available suicide notes and narratives in Turkish media outlets, we analyze 17 suicide notes and responses from their institutions of work and friends, family, and colleagues.

Findings and Discussion

We identify two mechanisms that lead to institutional suicides: (1) dehumanization due to lack of recognition and (2) misrecognition through a devaluation of potential. We extend the theory of anomie to institutional settings and offer social policy suggestions to improve institutional responses based on co-design based on suicide notes to prevent institutional suicides and call for institutional responsibilization for preventing work-related suicides.

Investigating Retrospective and Prospective Metamemory Judgments During Episodic Memory in Patients With Obsessive-Compulsive Disorders

It is clear evidence that individuals diagnosed with obsessive-compulsive disorder (OCD) lack confidence in their memory and have low metamemory performance (judgment and accuracy). However, it is still unclear whether low metamemory performance is specific to first, domain general or domain specific, and second, to stimulus domain. To address these issues, we compared individuals diagnosed with OCD and healthy controls (HCs) on recognition, retrospective (judgments of learning [JOL]) and prospective (feeling of knowing [FOK]) metamemory judgments and under three different episodic memory tasks, which consisted of symptom-free, familiar and unfamiliar stimuli (word, scene, and face photo). OCD patients showed lower recognition performance, JOL and FOK judgments, and accuracy in all tasks than HCs. Also, OCD patients were slower than HCs during all cognitive performances. In both groups, metamemory performances were lower in familiar items than unfamiliar items. However, recognition performances were not affected by stimulus type. Our results support the idea of general episodic memory and a metamemory deficit in OCD. Moreover, metamemory deficits in OCD are domain general.

[Perspectives on quality of life with endometriosis]

For women with endometriosis, pain, fatigue and digestive problems affect the quality of their daily lives. Many professionals work to help them find a balance between the disease and their activities, expectations and needs.

Wilderness Medical Society Clinical Practice Guidelines for the Prevention and Treatment of Heat Illness: 2024 Update

The Wilderness Medical Society (WMS) convened an expert panel in 2011 to develop a set of evidence-based guidelines for the recognition, prevention, and treatment of heat illness. The current panel retained 5 original members and welcomed 2 new members, all of whom collaborated remotely to provide an updated review of the classifications, pathophysiology, evidence-based guidelines for planning and preventive measures, and recommendations for field- and hospital-based therapeutic management of heat illness. These recommendations are graded based on the quality of supporting evidence and the balance between the benefits and risks or burdens for each modality. This is an updated version of the WMS clinical practice guidelines for the prevention and treatment of heat illness published in Wilderness & Environmental Medicine. 2019;30(4):S33-S46.

Recognizing the situation awareness of forklift operators based on EEG techniques in a field experiment

Lack of situation awareness (SA) is the primary cause of human errors when operating forklifts, so determining the SA level of the forklift operator is crucial to the safety of forklift operations. An EEG recognition approach of forklift operator SA in actual settings was presented in order to address the issues with invasiveness, subjectivity, and intermittency of existing measuring methods. In this paper, we conducted a field experiment that mimicked a typical forklift operation scenario to verify the differences in EEG states of forklift operators with different SA levels and investigate the correlation of multi-band combination features of each brain region of forklift operators with SA. Based on the sensitive EEG combination indexes, Support Vector Mechanism was used to construct a forklift operator SA recognition model. The results revealed that there were differences between forklift operators with high and low SA in the θ, α, and β frequency bands in zones F, C, P, and O; combined EEG indicators θ/β, (α + θ)/(α + β), and θ/(α + β) in zones F, P, and C were significantly correlated with SA; the recognition accuracy of the model reached 88.64% in the case of combined EEG indicators of zones C & F & P as input. It could provide a reference for SA measurement, contributing to the improvement of SA.

Evaluating the depression state during perinatal period by non-invasive scalp EEG

Perinatal depression, with a prevalence of 10 to 20% in United States, is usually missed as multiple symptoms of perinatal depression are common in pregnant women. Worse, the diagnosis of perinatal depression still largely relies on questionnaires, leaving the objective biomarker being unveiled yet. This study suggested a safe and non-invasive technique to diagnose perinatal depression and further explore its underlying mechanism. Considering the non-invasiveness and clinical convenience of electroencephalogram for mothers-to-be and fetuses, we collected the resting-state electroencephalogram of pregnant women at the 38th week of gestation. Subsequently, the difference in network topology between perinatal depression patients and healthy mothers-to-be was explored, with related spatial patterns being adopted to achieve the classification of pregnant women with perinatal depression from those healthy ones. We found that the perinatal depression patients had decreased brain network connectivity, which indexed impaired efficiency of information processing. By adopting the spatial patterns, the perinatal depression could be accurately recognized with an accuracy of 87.88%; meanwhile, the depression severity at the individual level was effectively predicted, as well. These findings consistently illustrated that the resting-state electroencephalogram network could be a reliable tool for investigating the depression state across pregnant women, and will further facilitate the clinical diagnosis of perinatal depression.

A hole in a piece of cardboard and predictive brain: the incomprehension of modern art in the light of the predictive coding paradigm

Incomprehension of and resistance to contemporaneous art have been constant features in the development of modern art. The predictive coding framework can be used to analyse this response by outlining the difference between the misunderstanding of (i) contemporary conceptual/minimalist art and (ii) early modern avant-garde art and by elucidating their underlying cognitive mechanisms. In both of these cases, incomprehension and its behavioural consequences are tied to the failure of the optimal prediction error (PE) minimization that is involved in the perception of such art works. In the case of contemporary conceptual/minimalist art the failure stems from the fact that the encounter results in non-salient visual sensations and generates no PE. In early modern avant-garde art, the occasional inability of viewers to recognize pictorial content using new pictorial conventions reflected the absence of suitable priors to explain away ambiguous sensory data. The capacity to recognize pictorial content in modernist painting, as a prerequisite for a satisfying encounter with such works and ultimately a wider acceptance of new artistic styles, required an updating of a number of expectations in order to optimize the fit between priors and sensations, from low-level perceptual priors to the development of higher-level, culturally determined expectations. This article is part of the theme issue 'Art, aesthetics and predictive processing: theoretical and empirical perspectives'.

A visual paired associate learning (vPAL) paradigm to study memory consolidation during sleep

Sleep improves the consolidation and long-term stability of newly formed memories and associations. Most research on human declarative memory and its consolidation during sleep uses word-pair associations requiring exhaustive learning. In the present study, we present the visual paired association learning (vPAL) paradigm, in which participants learn new associations between images of celebrities and animals. The vPAL is based on a one-shot exposure that resembles learning in natural conditions. We tested if vPAL can reveal a role for sleep in memory consolidation by assessing the specificity of memory recognition, and the cued recall performance, before and after sleep. We found that a daytime nap improved the stability of recognition memory and discrimination abilities compared to identical intervals of wakefulness. By contrast, cued recall of associations did not exhibit significant sleep-dependent effects. High-density electroencephalography during naps further revealed an association between sleep spindle density and stability of recognition memory. Thus, the vPAL paradigm opens new avenues for future research on sleep and memory consolidation across ages and heterogeneous populations in health and disease.

Recognition in interaction: theoretical and empirical observations

In the current paper we aim to combine the theoretical ideas of recognition theory to conversation analytical, empirical observations. We ask what recognition theories can give to conversation analysis, and vice versa. We operate on a model of recognition that consists of three different modes: respect, esteem, and love/care, and which distinguishes the levels of conversational actions and the attitudes of recognition manifested in such actions. In this study we examine data examples from various conversational settings (institutional, quasi-experimental, family interaction) and activities (decision-making, storytelling), focusing on the more complex cases of (mis)recognition. We show how recognition can appear both explicitly and implicitly in conversational sequences, and demonstrate how the levels of conversational actions and recognition can be either congruent or incongruent with each other. At the end of the article, we discuss the implications of this view for the interface of conversation analysis and sociological theory, arguing that it can inform and promote the development of interactionally based social and societal critique.

Glycan Shape, Motions, and Interactions Explored by NMR Spectroscopy

Glycans in the form of oligosaccharides, polysaccharides, and glycoconjugates are ubiquitous in nature, and their structures range from linear assemblies to highly branched and decorated constructs. Solution state NMR spectroscopy facilitates elucidation of preferred conformations and shapes of the saccharides, motions, and dynamic aspects related to processes over time as well as the study of transient interactions with proteins. Identification of intermolecular networks at the atomic level of detail in recognition events by carbohydrate-binding proteins known as lectins, unraveling interactions with antibodies, and revealing substrate scope and action of glycosyl transferases employed for synthesis of oligo- and polysaccharides may efficiently be analyzed by NMR spectroscopy. By utilizing NMR active nuclei present in glycans and derivatives thereof, including isotopically enriched compounds, highly detailed information can be obtained by the experiments. Subsequent analysis may be aided by quantum chemical calculations of NMR parameters, machine learning-based methodologies and artificial intelligence. Interpretation of the results from NMR experiments can be complemented by extensive molecular dynamics simulations to obtain three-dimensional dynamic models, thereby clarifying molecular recognition processes involving the glycans.

A Universal Aptamer for Influenza A Viruses: Selection, Recognition, and Infection Inhibition

It is crucial to develop universal inhibitors for viral inhibition due to the rapid mutation of viruses. Herein, a universal aptamer inhibitor was developed that enabled a single DNA molecule to recognize several hemeagglutinin (HA) protein subtypes, inducing broad neutralization against influenza A viruses (IAVs). Through a multi-channel enrichment (MCE) strategy, a high-affinity aptamer named UHA-2 was obtained, with its dissociation constants (Kd) for three different HA proteins being 1.5 ± 0.2 nM (H5N1), 3.7 ± 0.4 nM (H7N9), and 10.1 ± 1.1 nM (H9N2). The UHA-2 aptamer had a universal inhibition effect, by which it could broadly neutralize influenza A H5N1, H7N9, H9N2, H1N1, and H3N2 viruses. Universal aptamer inhibitors have the advantages of acquisition in vitro, stability, simple structure, small size, etc. This study not only develops a novel universal aptamer to achieve a broad inhibition effect on various IAVs, but also opens up an efficient strategy for the development of universal inhibitors against viruses.

A novel ensemble learning method for crop leaf disease recognition

Deep learning models have been widely applied in the field of crop disease recognition. There are various types of crops and diseases, each potentially possessing distinct and effective features. This brings a great challenge to the generalization performance of recognition models and makes it very difficult to build a unified model capable of achieving optimal recognition performance on all kinds of crops and diseases. In order to solve this problem, we have proposed a novel ensemble learning method for crop leaf disease recognition (named ELCDR). Unlike the traditional voting strategy of ensemble learning, ELCDR assigns different weights to the models based on their feature extraction performance during ensemble learning. In ELCDR, the models' feature extraction performance is measured by the distribution of the feature vectors of the training set. If a model could distinguish more feature differences between different categories, then it receives a higher weight during ensemble learning. We conducted experiments on the disease images of four kinds of crops. The experimental results show that in comparison to the optimal single model recognition method, ELCDR improves by as much as 1.5 (apple), 0.88 (corn), 2.25 (grape), and 1.5 (rice) percentage points in accuracy. Compared with the voting strategy of ensemble learning, ELCDR improves by as much as 1.75 (apple), 1.25 (corn), 0.75 (grape), and 7 (rice) percentage points in accuracy in each case. Additionally, ELCDR also has improvements on precision, recall, and F1 measure metrics. These experiments provide evidence of the effectiveness of ELCDR in the realm of crop leaf disease recognition.

Deep learning for medicinal plant species classification and recognition: a systematic review

Knowledge of medicinal plant species is necessary to preserve medicinal plants and safeguard biodiversity. The classification and identification of these plants by botanist experts are complex and time-consuming activities. This systematic review's main objective is to systematically assess the prior research efforts on the applications and usage of deep learning approaches in classifying and recognizing medicinal plant species. Our objective was to pinpoint systematic reviews following the PRISMA guidelines related to the classification and recognition of medicinal plant species through the utilization of deep learning techniques. This review encompassed studies published between January 2018 and December 2022. Initially, we identified 1644 studies through title, keyword, and abstract screening. After applying our eligibility criteria, we selected 31 studies for a thorough and critical review. The main findings of this reviews are (1) the selected studies were carried out in 16 different countries, and India leads in paper contributions with 29%, followed by Indonesia and Sri Lanka. (2) A private dataset has been used in 67.7% of the studies subjected to image augmentation and preprocessing techniques. (3) In 96.7% of the studies, researchers have employed plant leaf organs, with 74% of them utilizing leaf shapes for the classification and recognition of medicinal plant species. (4) Transfer learning with the pre-trained model was used in 83.8% of the studies as a future extraction technique. (5) Convolutional Neural Network (CNN) is used by 64.5% of the paper as a deep learning classifier. (6) The lack of a globally available and public dataset need for medicinal plants indigenous to a specific country and the trustworthiness of the deep learning approach for the classification and recognition of medicinal plants is an observable research gap in this literature review. Therefore, further investigations and collaboration between different stakeholders are required to fulfilling the aforementioned research gaps.

Mini review: Challenges in EEG emotion recognition

Electroencephalography (EEG) stands as a pioneering tool at the intersection of neuroscience and technology, offering unprecedented insights into human emotions. Through this comprehensive review, we explore the challenges and opportunities associated with EEG-based emotion recognition. While recent literature suggests promising high accuracy rates, these claims necessitate critical scrutiny for their authenticity and applicability. The article highlights the significant challenges in generalizing findings from a multitude of EEG devices and data sources, as well as the difficulties in data collection. Furthermore, the disparity between controlled laboratory settings and genuine emotional experiences presents a paradox within the paradigm of emotion research. We advocate for a balanced approach, emphasizing the importance of critical evaluation, methodological standardization, and acknowledging the dynamism of emotions for a more holistic understanding of the human emotional landscape.

Knowledge on Stroke Recognition and Management among Emergency Department Healthcare Professionals in the Republic of Cyprus

Stroke is a global leading cause of death and disability. Knowledge of related guidelines is crucial for emergency department (ED) staff, influencing early diagnosis and timely treatment. We investigated Greek Cypriot ED healthcare professionals' (nurses and physicians) knowledge in recognizing and managing stroke. A descriptive cross-sectional study spanned November 2019 to April 2020, encompassing four private and seven public EDs in the Republic of Cyprus. The data were collected through a self-reported questionnaire developed by the research team, consisting of 37 questions. Eight questions focused on sociodemographic and employment characteristics, twenty-eight assessed knowledge in stroke recognition and management (each item was equally weighted without deliberate prioritization), and one question addressed self-assessment of knowledge in stroke care. A total of 255 nurses (response rate (RR): 74.1%) and 26 physicians (RR: 47.3%) completed the questionnaire. The average correct response rate was 12.9 out of 28 statements (SD: 4.2), with nurses and physicians scoring 12.6 (SD: 4.1) and 15.7 (SD: 4), respectively. Work experience significantly influenced stroke knowledge, with all groups demonstrating superiority over those with less than one year of experience. Participants with previous training scored an average of 1.45 additional correct answers while educational attainment did not significantly influence stroke knowledge. Investigating stroke knowledge among emergency department nurses and physicians in the Republic of Cyprus revealed significant deficits. This study stresses targeted interventions, including education, yearly examinations, workshops with hands-on training, and repeated training, to address these gaps and enhance the overall stroke care capabilities of the healthcare professionals.

Antitumor Immunity: Role of NK Cells and Extracellular Vesicles in Cancer Immunotherapy

The immune system plays a crucial role in recognizing and eliminating altered tumor cells. However, tumors develop mechanisms to evade the body's natural immune defenses. Therefore, methods for specifically recognizing/targeting tumor cells, for instance, through the activation, directed polarization, and training of immune cells, have been developed based on the body's immune cells. This strategy has been termed cellular immunotherapy. One promising strategy for treating tumor diseases is NK cell-based immunotherapy. NK cells have the ability to recognize and destroy transformed cells without prior activation as well as tumor cells with reduced MHC-I expression. A novel approach in immunotherapy is the use of extracellular vesicles (EVs) derived from NK cells. The main advantages of NK cell-derived EVs are their small size and better tissue penetration into a tumor. The aim of this review is to systematically present existing information on the mechanisms of antitumor immunity and the role of NK cells and extracellular vesicles in cancer immunotherapy. Clinical and preclinical studies utilizing NK cells and extracellular vesicles for anticancer therapy currently underway will provide valuable insights for researchers in the field of cancer.

Barriers to healthcare professionals recognizing and managing delirium in older adults during a hospital stay: A mixed-methods systematic review

AIM

To investigate barriers to healthcare professionals recognizing and managing delirium in hospitalized older people.

DESIGN

A mixed-methods systematic review.

PROSPERO ID

CRD42020187932.

DATA SOURCES

MEDLINE, EMBASE, PsycINFO and CINAHL were searched (2007 to February 2023).

REVIEW METHODS

Included studies focused on healthcare professionals' recognition and management of delirium for patients aged 65 years and over in a hospital ward or emergency department. Enhancing rigour, screening of results was conducted independently by two researchers. Qualitative and quantitative data were tabulated separately and grouped. Data were compared to identify similarities and differences. All studies were quality appraised.

RESULTS

43 studies were included; 24 quantitative, 16 qualitative and three mixed-methods. Data synthesis highlighted synergy between qualitative and quantitative findings. Barriers were reflected in six themes: (1) healthcare professionals' knowledge and understanding; (2) communication; (3) workforce development; (4) interprofessional working; (5) confounders; and (6) organizational constraints.

CONCLUSIONS

Of significance, for older adults in hospital experiencing delirium, there is variability in whether and how well it is recognized and managed. To prevent adverse outcomes best practice guidance for screening, recognizing, diagnosing and managing delirium in older people needs to be agreed and disseminated widely. Supporting healthcare professionals to care for this patient population using an integrated approach is essential, how to involve and communicate with patients and their family and friends, how to recognize and manage delirium for patients with additional needs, e.g., those living with dementia and/or a learning disability. Hospitals need to have policy and guidance in place for the recognition and management of delirium in older adults presenting to a ward or to an emergency department. An IT infrastructure is needed that integrates assessments and care management plans in patient electronic records and makes them accessible within and across teams in hospital, primary and community care settings.

PATIENT OR PUBLIC CONTRIBUTION

There was no patient or public contribution to this systematic review.

IMPLICATIONS FOR THE PROFESSION AND PATIENT CARE

Healthcare professionals can be better supported to be able to recognize and manage delirium during an acute hospital stay for older adults. This includes maximizing best care for those patients living with dementia, involving families and friends to help understand patients' baseline status and changes and supporting families and friends during this process. Of significance, attention to hospital IT infrastructures is warranted, integrating screening, assessment and care management plans in patients' electronic records and making these accessible to healthcare professionals caring for this patient population across care settings.

IMPACT

What problem did the study address? Delirium is a common condition experienced by older hospitalized patients, but it is consistently under-recognized which has implications for patient and organization outcomes. To help address this, understanding barriers to healthcare professionals recognizing and managing delirium for this patient population is paramount. What were the main findings? Barriers to healthcare professionals recognizing and managing delirium for this patient population were synthesized in six themes: (1) healthcare professionals' knowledge and understanding, (2) communication; (3) workforce development; (4) interprofessional working; (5) confounders; and (6) organizational constraints. Where and on whom will the research have an impact? The findings of this original systematic review can contribute to hospital policy and protocol for the recognition and management of delirium in older patients. The findings can meaningfully contribute to workforce professional development for practitioners caring for older people during an acute hospital stay and for practitioners in primary and community settings involved in the follow-up of patients post hospital discharge. For researchers, the findings indicate several research recommendations including investigating the impact of an education programme for nurses and other healthcare professionals on the recognition and management of the condition and understanding and investigating how best to support delirium-related distress experienced by patients and their families and practitioners.

REPORTING METHOD

This systematic review was reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (Page et al., 2021).

Alexithymia is associated with insomnia in Chinese patients with schizophrenia

Background

Sleep disorders are prevalent among patients with schizophrenia and are associated with several negative consequences. Although, researchers have recently suggested that sleep disorders have a close correlation with alexithymia, and schizophrenia also has a strong correlation with alexithymia, there have been few studies on the relationships between schizophrenia, sleep disorders and alexithymia. Therefore, this study aimed to explore the relationships between psychiatric symptoms, alexithymia and sleep problems in patients with schizophrenia so as to provide a reference for the clinical treatment of this comorbidity.

Methods

In total, 977 patients with schizophrenia were recruited for this study. The Insomnia Severity Index (ISI) was used to assess sleep disorders, and the Positive and Negative Syndrome Scale (PANSS), Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) and Toronto Alexithymia Scale (TAS) were used to evaluate clinical symptoms, cognitive functions and the ability to express emotion, respectively.

Results

The results indicated that the PANSS subscales (G-subscore) and TAS group were risk factors for insomnia in schizophrenia patients (all p < 0.05). The mediation model showed the standardized path coefficients from schizophrenia to alexithymia (β = 0.104, p < 0.001) and from alexithymia to insomnia (β = 0.038, p < 0.001) were statistically significant.

Conclusion

The results of this study indicated that alexithymia is associated with sleep disturbance in patients with schizophrenia. These findings may provide a new avenue for the treatment of schizophrenia patients with sleep disorders.

Your place or mine? The neural dynamics of personally familiar scene recognition suggests category independent familiarity encoding

Recognizing a stimulus as familiar is an important capacity in our everyday life. Recent investigation of visual processes has led to important insights into the nature of the neural representations of familiarity for human faces. Still, little is known about how familiarity affects the neural dynamics of non-face stimulus processing. Here we report the results of an EEG study, examining the representational dynamics of personally familiar scenes. Participants viewed highly variable images of their own apartments and unfamiliar ones, as well as personally familiar and unfamiliar faces. Multivariate pattern analyses were used to examine the time course of differential processing of familiar and unfamiliar stimuli. Time-resolved classification revealed that familiarity is decodable from the EEG data similarly for scenes and faces. The temporal dynamics showed delayed onsets and peaks for scenes as compared to faces. Familiarity information, starting at 200 ms, generalized across stimulus categories and led to a robust familiarity effect. In addition, familiarity enhanced category representations in early (250-300 ms) and later (>400 ms) processing stages. Our results extend previous face familiarity results to another stimulus category and suggest that familiarity as a construct can be understood as a general, stimulus-independent processing step during recognition.

Hydrolysis of Oligodeoxyribonucleotides on the Microarray Surface and in Solution by Catalytic Anti-DNA Antibodies in Systemic Lupus Erythematosus

Anti-DNA antibodies are known to be classical serological hallmarks of systemic lupus erythematosus (SLE). In addition to high-affinity antibodies, the autoantibody pool also contains natural catalytic anti-DNA antibodies that recognize and hydrolyze DNA. However, the specificity of such antibodies is uncertain. In addition, DNA binding to a surface such as the cell membrane, can also affect its recognition by antibodies. Here, we analyzed the hydrolysis of short oligodeoxyribonucleotides (ODNs) immobilized on the microarray surface and in solution by catalytic anti-DNA antibodies from SLE patients. It has been shown that IgG antibodies from SLE patients hydrolyze ODNs more effectively both in solution and on the surface, compared to IgG from healthy individuals. The data obtained indicate a more efficient hydrolysis of ODNs in solution than immobilized ODNs on the surface. In addition, differences in the specificity of recognition and hydrolysis of certain ODNs by anti-DNA antibodies were revealed, indicating the formation of autoantibodies to specific DNA motifs in SLE. The data obtained expand our understanding of the role of anti-DNA antibodies in SLE. Differences in the recognition and hydrolysis of surface-tethered and dissolved ODNs need to be considered in DNA microarray applications.

Implicit versus explicit processing of visual, olfactory, and multimodal landmark information in human wayfinding

Despite the predominant focus on visual perception in most studies, the role of humans' sense of smell in navigation has often been neglected. Recent research, however, could show that humans are indeed able to use their sense of smell for orientation, particularly when processed implicitly. In this study, we investigate whether implicit perception of olfactory landmarks enhanced wayfinding performance compared to explicit perception. Fifty-two people completed a wayfinding and a recognition task in a virtual maze at two times of testing 1 month apart. Participants either received olfactory, visual, or both cues at the intersections. Wayfinding performance was better for olfactory landmarks, which were not correctly remembered in the recognition task. In contrast, wayfinding performance was better when visual landmarks were correctly remembered. In the multimodal condition, wayfinding performance was better with landmarks being remembered at t1 and remained the same at t2. Our results suggest distinct implicit processing mechanisms within the olfactory system and therefore hold important implications for the nature of spatial odor processing extending beyond explicit odor localization tasks. The study highlights the importance for future studies to develop and employ further experimental methods that capture implicit processing across all of our senses. This is crucial for a comprehensive understanding of consciousness, as olfaction strongly influences our behavior, but remains largely latent unless deliberately honed through practice.

The top 100 most-cited studies on monkeypox: a brief bibliometric analysis

Background

A plethora of monkeypox papers have been published; however, pinpointing key and pivotal studies can be challenging amongst the ever-expanding literature. Bibliometric analyses are helpful in identifying the most influential articles and their impact pertinent to this field, which has helped mould the recognition and management of monkeypox.

Methods

The Web of Science Core Collection (WoSCC) was searched on 27 October 2022. The top 100 most-cited articles on monkeypox were identified and evaluated by author, country, institution, type of articles, theme, journal of publication, keywords, and citations.

Results

The top 100 most-cited studies were published between 1997 and 2022, and the 5-year period with the largest number of articles was 2007-2011. The median number of citations among the top 100 most-cited articles was 78.23. Of the top 100 most-cited studies, 91 were original articles, and nine were reviews, the median of annual citations was significantly higher in the review group than the original group, 7.86 (4.20-13.80) versus 4.50 (3.07-7.59; P=0.023). The 100 articles were classified into different research theme, with the top three being Immunology (31%), Infectious Diseases (30%), and Virology (26%), respectively. The keywords with the highest co-occurrence frequency were "monkeypox", "smallpox," and "smallpox virus." The largest number of articles in the top 100 were published in Emerging Infectious Diseases (n=13), followed by Journal of Virology (n=11), Journal of Infectious Diseases (n=5), and PLoS One (n=5). The authors identified 711 different authors from 195 institutions and 28 countries in the top 100 most-cited articles, with the majority based in the USA.

Conclusion

The top 100 most-cited studies provide an important insight into the historical developments of monkeypox. The authors should strengthen the recognition and management of monkeypox worldwide and strengthen research cooperation among scholars in order to better respond to the ongoing or future outbreak.

Good Saves: How Emergency Medicine Residents are Learning From Success

INTRODUCTION

 The practice of learning from medical errors is well-established and well-researched in the literature on morbidity and mortality conferences. However, durable learning from case-based education occurs not only through the analysis of medical errors but also through the evaluation of how critical decisions were made to result in a positive clinical outcome, what we will call a "good save." The aim of the current study is to provide an overview of how US-based emergency medicine residencies are teaching using "good saves."

METHODS

A national survey of emergency medicine (EM) residency leadership was distributed through the Council of Residency Directors (CORD) and the Society of Academic Emergency Medicine (SAEM) listservs. A descriptive analysis of the results was undertaken.

RESULTS

Residency leadership representing 67 different US EM training programs participated in our survey. Of these, only 19 programs use formal learning objectives and dedicated education time to teach from "good saves." Thirty-six programs provide informal recognition, often in the form of a "shout-out." Residency leadership is motivated to provide this recognition and learning through efforts to promote wellness and resiliency among EM residents. Notably, the use of prizes and awards is not necessary.

DISCUSSION

Some EM residencies in the United States are making targeted efforts to promote the recognition of successful clinical care. This recognition and education are being used as tools both to promote wellness and to teach resiliency. However, there is wide heterogeneity in approaches. Our survey provides examples of the many ways that "good saves" can be incorporated into any EM residency curriculum with the potential for significant impact.

(Bio)Functionalisation of Metal-Organic Polyhedra by Using Click Chemistry

The surface chemistry of Metal-Organic Polyhedra (MOPs) is crucial to their physicochemical properties because it governs how they interact with external substances such as solvents, synthetic organic molecules, metal ions, and even biomolecules. Consequently, the advancement of synthetic methods that facilitate the incorporation of diverse functional groups onto MOP surfaces will significantly broaden the range of properties and potential applications for MOPs. This study describes the use of copper(I)-catalysed, azide-alkyne cycloaddition (CuAAC) click reactions to post-synthetically modify the surface of alkyne-functionalised cuboctahedral MOPs. To this end, a novel Rh(II)-based MOP with 24 available surface alkyne groups was synthesised. Each of the 24 alkyne groups on the surface of the "clickable" Rh-MOP can react with azide-containing molecules at room temperature, without compromising the integrity of the MOP. The wide substrate catalogue and orthogonal nature of CuAAC click chemistry was exploited to densely functionalise MOPs with diverse functional groups, including polymers, carboxylic and phosphonic acids, and even biotin moieties, which retained their recognition capabilities once anchored onto the surface of the MOP.

A Closed Cavity Strategy for Selective Dipeptide Binding by a Polyaromatic Receptor in Water

Precise recognition of peptides is a daunting task owing to the substantial number of available amino acids and their combination into various oligo/polymeric structures in addition to the high hydration of their flexible frameworks. Here, we report the selective recognition of a dipeptide through a closed cavity strategy, in contrast to previous synthetic receptors with open cavities. A polyaromatic receptor with a virtually isolated, hydrophobic cavity exclusively binds one molecule of phenylalanine dipeptide from a mixture with its amino acid and tripeptide in water via multiple CH-π and hydrogen-bonding interactions in the complementary cavity. The binding selectivity persists even in the presence of other dipeptides, such as leucine-leucine, leucine-phenylalanine, tyrosine-phenylalanine, tryptophan-tryptophan, and aspartame, revealed by NMR/MS-based competitive binding experiments. ITC studies reveal that the selective binding of the phenylalanine dipeptide is relatively strong (Ka = 1.1 × 105 M-1) and an enthalpically and entropically favorable process (ΔH = -11.7 kJ mol-1 and TΔS = 17.0 kJ mol-1). In addition, the present receptor can be used for the emission detection of the dipeptide through a combination with a fluorescent dye in water.

Adsorption and Recognition Property of Tyrosine Molecularly Imprinted Polymer Prepared via Electron Beam Irradiation

To realize the selective separation of L-tyrosine (L-Tyr) and avoid the drawbacks of traditional thermal polymerization, electron beam irradiation polymerization was developed for the fabrication of L-Tyr molecularly imprinted polymers (MIPs). Firstly, L-Tyr MIPs were prepared with methacrylic acid and ethylene glycol dimethacrylate and without an initiator. Then, the influence of absorbed dosage and temperature on the adsorption capacity of L-Tyr, as well as the thermodynamic behavior, were investigated. The maximum adsorption capacity of 10.96 mg/g for MIPs was obtained with an irradiation dosage of 340 kGy under 15 °C, and the ΔH0 and ΔS0 of the adsorption process are -99.79 kJ/mol and -0.31 kJ/mol·K, respectively. In addition, the effect of adsorption time on adsorption performance was evaluated under different initial concentrations, and the kinetic behavior was fitted with four different models. Finally, the recognition property of the obtained MIPs was investigated with L-Tyr and two analogues. The obtained MIPs have an imprinting factor of 5.1 and relatively high selective coefficients of 3.9 and 3.5 against L-tryptophan and L-phenylalanine, respectively. This work not only provided an L-Tyr MIP with high adsorption capacity and selectivity but also provided an effective and clean method for the synthesis of MIPs.

Association of diagnostic error education and recognition frequency among Japanese medical students: a nationwide cross-sectional study

OBJECTIVES

Diagnostic errors pose a significant risk to patient safety and have substantial medical and economic consequences. Despite their importance, diagnostic error education is currently lacking in standard pre-graduate curricula. This study aimed to investigate the incidence of diagnostic errors and the frequency of recognition among medical students in Japan.

METHODS

A pilot survey was conducted immediately after the General Medicine In-Training Examination (GM-ITE), a comprehensive post-graduation test, administered to new residents right after graduation from medical school. The survey assessed whether they received education on diagnostic errors during their formal undergraduate medical education and whether they recognized diagnostic errors during their clinical training.

RESULTS

Of the 564 examinees, 421 participated in the study. The majority of participants (63.9 %) reported receiving education on diagnostic errors, and 15.7 % recognized diagnostic errors during their clinical training. Significantly, those who received education on diagnostic errors had a higher rate of recognizing such errors compared to those who did not (19.7 vs. 8.6 %; p=0.0017).

CONCLUSIONS

These findings suggest that the recognition rate of diagnostic errors increases with improved literacy in diagnostic error education. This highlights the importance of incorporating diagnostic error education into medical curricula to develop effective strategies to prevent and manage diagnostic errors, and thereby enhance medical and patient safety. However, this study did not examine the specific educational content of the errors or the details of the recognition, necessitating further investigation in the future.

subcortical distinction

INTRODUCTION

Within clinical neuropsychology, a classic diagnostic distinction is made between cortical and subcortical disorders, especially based on their memory profiles. Typically, this is based on the comparison of recall and recognition trials, where individuals with cortical conditions do not tend to benefit (i.e., score well) on recognition trials and individuals with subcortical conditions do. Although the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) is a widely used brief cognitive battery, there is a lack of evidence to support this measure's utility in distinguishing between the memory profiles of these conditions.

METHOD

Thirty-six mild Alzheimer's disease (AD), 55 Parkinson's disease (PD), and 105 essential tremor (ET) participants (N = 196) were administered the RBANS with additional Story and Figure Recognition subtests. Group differences on recall and recognition scores (Total Correct, Hits or True Positives, False Positive Errors, and discriminability index) were examined across the three groups, while controlling for the influence of age and gender.

RESULTS

As expected, individuals with AD had poorer recognition scores compared to the other clinical groups across tasks (all p-values < .05), while the ET sample largely performed comparably to the PD sample. With the exception of comparable Figure Recognition and Recall in the PD sample, all groups exhibited significantly greater recognition Hit performance compared to Recall (all p-values < .05).

CONCLUSIONS

The group differences in performance across RBANS recognition subtests suggest support for traditional "cortical" and "subcortical" profiles. However, all groups, including the mild AD sample, demonstrated a benefit from recognition cues compared to free recall. Overall, these findings support the inclusion of the newly developed Story and Figure Recognition subtests in future clinical practice and research endeavors.

Perception and Recognition of Clinical Medical Physicist Roles and Responsibilities by Specialist Physician Staff: The First Mexican Survey

Introduction

Although medical physics as a profession is recognized as part of the health-care professional workforce by the International Labor Organization, in the Mexican context, the figure of the medical physicist (MP) is often inappropriately associated solely with technical work, leading to perception, recognition, and salary implications. The aim of this study was to explore the perception of medical specialists regarding the role and responsibilities of MPs in clinical practice in Mexico.

Methods

A national survey was answered by medical personnel, ranging from residents to qualified specialists in November 2019. The questionnaire consisted of ten questions related to perception of MPs. The survey was open to all medical specialists regardless of their involvement in the use of ionizing radiations or otherwise.

Results

It was shown that approximately two-thirds of specialists know and recognize the medical physics profession in hospitals and the roles and responsibilities of MPs. However, 19% of medical specialists considered the standard of service as inadequate.

Conclusion

MPs must exert greater efforts to promote their status and enhance the recognition of their contribution to health care. The low level of recognition in diagnostic and interventional radiology and in nuclear medicine in Mexico might be related to nonexistent or unclear documentation and inadequate regulations, policies, or directives promoted by the health-care authorities.

Artificial intelligence for automated identification of total shoulder arthroplasty implants

BACKGROUND

Accurate and rapid identification of implant manufacturer and model is critical in the evaluation and management of patients requiring revision total shoulder arthroplasty (TSA). Failure to correctly identify implant designs in these circumstances may lead to delay in care, unexpected intraoperative challenges, increased morbidity, and excess health care costs. Deep learning (DL) permits automated image processing and holds the potential to mitigate such challenges while improving the value of care rendered. The purpose of this study was to develop an automated DL algorithm to identify shoulder arthroplasty implants from plain radiographs.

METHODS

A total of 3060 postoperative images from patients who underwent TSA between 2011 and 2021 performed by 26 fellowship-trained surgeons at 2 independent tertiary academic hospitals in the Pacific Northwest and Mid-Atlantic Northeast were included. A DL algorithm was trained using transfer learning and data augmentation to classify 22 different reverse TSA and anatomic TSA prostheses from 8 implant manufacturers. Images were split into training and testing cohorts (2448 training and 612 testing images). Optimized model performance was assessed using standardized metrics including the multiclass area under the receiver operating characteristic curve (AUROC) and compared with a reference standard of implant data from operative reports.

RESULTS

The algorithm classified implants at a mean speed of 0.079 seconds (±0.002 seconds) per image. The optimized model discriminated between 8 manufacturers (22 unique implants) with AUROCs of 0.994-1.000, accuracy of 97.1%, and sensitivities between 0.80 and 1.00 on the independent testing set. In the subset of single-institution implant predictions, a DL model identified 6 specific implants with AUROCs of 0.999-1.000, accuracy of 99.4%, and sensitivity >0.97 for all implants. Saliency maps revealed key differentiating features across implant manufacturers and designs recognized by the algorithm for classification.

CONCLUSION

A DL model demonstrated excellent accuracy in identifying 22 unique TSA implants from 8 manufacturers. This algorithm may provide a clinically meaningful adjunct in assisting with preoperative planning for the failed TSA and allows for scalable expansion with additional radiographic data and validation efforts.

Exploring Lived Experience of Family and Domestic Violence Against Women With Disability: A Scoping Review

This article reports on a scoping review exploring understandings of family and domestic violence (FDV) against women with disability (WWD) within the literature and constitutes the second article in a two-part series, the first critiquing the categorization and measurement of FDV and disability. We report findings from qualitative studies included in the review, predominantly interpretivist and critical in orientation. The scoping review included 43 articles, 15 of which are included here, as they draw upon data directly from the perspectives of WWD. Reflexive thematic analysis was conducted, utilizing both inductive and deductive coding, and consultation between the authors. The analysis highlighted experiences of disability-based abuse, the nexus of ableism and sexism within the everyday, and meanings of justice and resilience for WWD. Disability-based abuse was perpetrated primarily by intimate partners, including financial and physical disability-based abuse, and was used to exploit and perpetuate situations of isolation. Sexist and ableist expectations, assumptions, and attitudes converged in everyday encounters within the community, with workers and systems. However, WWD reported strategies of resistance, healing, coping, and moving on in the aftermath of FDV and indicated what can be done to promote justice, both personally and within systems. The findings were discussed drawing on Axel Honneth's theory of recognition to highlight the mechanisms by which recognition and respect can be enhanced to enable full access to citizenship, in particular, for WWD to live free from violence.

Does point value structure influence measures of memory selectivity?

ABSTRACTIn reward-based learning and value-directed remembering, many different value structures for the to-be-remembered information have been used by researchers. I was interested in whether different scoring structures used in a value-directed remembering task impact measures of memory selectivity. Participants studied lists of words paired with point values and some lists included words paired with values ranging from 1 to 20, 1 to 10 (repeating twice), either a high value (10 points) or a low value (1 point), and either a high value (10 points), a medium value (5 points) or a low value (1 point). Results suggest that (1) in tests of free recall, if using a continuous value scale, the range of values matters in terms of selective memory, (2) analysing the selectivity index can yield different results than modelling item-level recall using point values (and the latter may be a preferable approach), (3) measures of selectivity using different value structures may lack construct validity when testing memory via recognition tests, and (4) the effect of value on memory is much larger on recall than recognition tests. Thus, I suggest that researchers carefully consider and justify the value structure used when examining selective memory for valuable information in list learning tasks.

Parallel G-quadruplex recognition by neomycin

G-quadruplex-forming nucleic acids have evolved to have applications in biology, drug design, sensing, and nanotechnology, to name a few. Together with the structural understanding, several attempts have been made to discover and design new classes of chemical agents that target these structures in the hope of using them as future therapeutics. Here, we report the binding of aminoglycosides, in particular neomycin, to parallel G-quadruplexes that exist as G-quadruplex monomers, dimers, or compounds that have the propensity to form dimeric G-quadruplex structures. Using a combination of calorimetric and spectroscopic studies, we show that neomycin binds to the parallel G-quadruplex with affinities in the range of Ka ∼ 105-108 M-1, which depends on the base composition, ability to form dimeric G-quadruplex structures, salt, and pH of the buffer used. At pH 7.0, the binding of neomycin was found to be electrostatically driven potentially through the formation of ion pairs formed with the quadruplex. Lowering the pH resulted in neomycin's association constants in the range of Ka ∼ 106-107 M-1 in a salt dependent manner. Circular dichroism (CD) studies showed that neomycin's binding does not cause a change in the parallel conformation of the G-quadruplex, yet some binding-induced changes in the intensity of the CD signals were seen. A comparative binding study of neomycin and paromomycin using d(UG4T) showed paromomycin binding to be much weaker than neomycin, highlighting the importance of ring I in the recognition process. In toto, our results expanded the binding landscape of aminoglycosides where parallel G-quadruplexes have been discovered as one of the high-affinity sites. These results may offer a new understanding of some of the undesirable functions of aminoglycosides and help in the design of aminoglycoside-based G-quadruplex binders of high affinity.

The hidden borderline patient: patients with borderline personality disorder who do not engage in recurrent suicidal or self-injurious behavior

BACKGROUND

Despite the significant psychosocial morbidity associated with borderline personality disorder (BPD), its underrecognition is a significant clinical problem. BPD is likely underdiagnosed, in part, because patients with BPD usually present with chief complaints associated with mood, anxiety, and substance use disorders. When patients with BPD do not exhibit self-harm behavior, we suspect that BPD is less likely to recognized. An important question is whether the absence of this criterion, which might attenuate the likelihood of recognizing and diagnosing the disorder, identifies a subgroup of patients with BPD who are 'less borderline' than patients with BPD who do not manifest this criterion.

METHODS

Psychiatric outpatients were evaluated with a semi-structured diagnostic interview for DSM-IV BPD, 390 of whom were diagnosed with BPD. We compared the demographic and clinical characteristics of patients with BPD who do and do not engage in repeated suicidal and self-harm behavior.

RESULTS

Approximately half of the patients with BPD did not meet the suicidality/self-injury diagnostic criterion for the disorder. There were no differences between the patients who did and did not meet this criterion in occupational impairment, likelihood of receiving disability payments, impairment in social functioning, level of educational achievement, comorbid psychiatric disorders, history of childhood trauma, or severity of depression, anxiety, or anger upon presentation for treatment.

CONCLUSIONS

Repeated self-injurious and suicidal behavior is not synonymous with BPD. It is critical for clinicians to be aware that the absence of repeated self-injury and suicide threats/gestures or attempts does not rule out the diagnosis of BPD.

High School Students' and Teachers' Mental Health Literacy Levels in Istanbul, Turkey: A Comprehensive Analysis

BACKGROUND

Mental health literacy is important for awareness of mental illnesses in adolescence, which is the initial period of mental disorders. Determining the levels of mental health literacy guides studies in activities promoting mental health. This study aimed to determine the mental health literacy levels of high school students and teachers and related factors.

METHODS

Our study is a cross-sectional study. A total of 1051 people (students and teachers) were included in the Fatih District of Istanbul were included in our study. The mental health literacy levels of the participants were evaluated with the Mental Health Literacy Questionnaire. This questionnaire includes scenarios about mental problems called "vignettes" and questions about them.

RESULTS

Students' recognition percentages of depression, schizophrenia, and social phobia vignettes were found to be 28.1%, 46.5%, and 5.9%, respectively. For the person who was described in the vignettes, the "family physician" was chosen as the least by students and teachers. A statistically significant relationship was found between students' mental health literacy levels and sex, grade, father education levels, and experiencing vignette similar issues (p < .005). Additionally, teachers who were not school administrators and experienced vignette similar issues levels were higher (p < .005).

CONCLUSIONS

These results showed us that mental health literacy levels are low in high schools. School-based intervention studies on this issue are of critical importance. In addition, it is seen that individuals do not consider asking for help with mental health problems from primary care services. This shows the inadequacy of the integration of primary health care services and mental health services.

A New Principle toward Robust Matching in Human-like Stereovision

Visual signals are the upmost important source for robots, vehicles or machines to achieve human-like intelligence. Human beings heavily depend on binocular vision to understand the dynamically changing world. Similarly, intelligent robots or machines must also have the innate capabilities of perceiving knowledge from visual signals. Until today, one of the biggest challenges faced by intelligent robots or machines is the matching in stereovision. In this paper, we present the details of a new principle toward achieving a robust matching solution which leverages on the use and integration of top-down image sampling strategy, hybrid feature extraction, and Restricted Coulomb Energy (RCE) neural network for incremental learning (i.e., cognition) as well as robust match-maker (i.e., recognition). A preliminary version of the proposed solution has been implemented and tested with data from Maritime RobotX Challenge. The contribution of this paper is to attract more research interest and effort toward this new direction which may eventually lead to the development of robust solutions expected by future stereovision systems in intelligent robots, vehicles, and machines.