The comeback of hand drawing in modern life sciences.

Scientific manuscripts are full of images. Since the birth of the life sciences, these images were in a form of hand drawings, with great examples from da Vinci, Hooke, van Leeuwenhoek, Remak, Buffon, Bovery, Darwin, Huxley, Haeckel and Gray's Anatomy to name a few. However, in the course of the past century, photographs and simplified schematics have gradually taken over as a way of illustrating scientific data and concepts, assuming that these are 'accurate' representations of the truth. Here, we argue for the importance of reviving the art of scientific drawings as a way of effectively communicating complex scientific ideas to both specialists and the general public.

Online images amplify gender bias.

Each year, people spend less time reading and more time viewing images1, which are proliferating online2-4. Images from platforms such as Google and Wikipedia are downloaded by millions every day2,5,6, and millions more are interacting through social media, such as Instagram and TikTok, that primarily consist of exchanging visual content. In parallel, news agencies and digital advertisers are increasingly capturing attention online through the use of images7,8, which people process more quickly, implicitly and memorably than text9-12. Here we show that the rise of images online significantly exacerbates gender bias, both in its statistical prevalence and its psychological impact. We examine the gender associations of 3,495 social categories (such as 'nurse' or 'banker') in more than one million images from Google, Wikipedia and Internet Movie Database (IMDb), and in billions of words from these platforms. We find that gender bias is consistently more prevalent in images than text for both female- and male-typed categories. We also show that the documented underrepresentation of women online13-18 is substantially worse in images than in text, public opinion and US census data. Finally, we conducted a nationally representative, preregistered experiment that shows that googling for images rather than textual descriptions of occupations amplifies gender bias in participants' beliefs. Addressing the societal effect of this large-scale shift towards visual communication will be essential for developing a fair and inclusive future for the internet.

FSC-certified forest management benefits large mammals compared to non-FSC.

More than a quarter of the world's tropical forests are exploited for timber1. Logging impacts biodiversity in these ecosystems, primarily through the creation of forest roads that facilitate hunting for wildlife over extensive areas. Forest management certification schemes such as the Forest Stewardship Council (FSC) are expected to mitigate impacts on biodiversity, but so far very little is known about the effectiveness of FSC certification because of research design challenges, predominantly limited sample sizes2,3. Here we provide this evidence by using 1.3 million camera-trap photos of 55 mammal species in 14 logging concessions in western equatorial Africa. We observed higher mammal encounter rates in FSC-certified than in non-FSC logging concessions. The effect was most pronounced for species weighing more than 10 kg and for species of high conservation priority such as the critically endangered forest elephant and western lowland gorilla. Across the whole mammal community, non-FSC concessions contained proportionally more rodents and other small species than did FSC-certified concessions. The first priority for species protection should be to maintain unlogged forests with effective law enforcement, but for logged forests our findings provide convincing data that FSC-certified forest management is less damaging to the mammal community than is non-FSC forest management. This study provides strong evidence that FSC-certified forest management or equivalently stringent requirements and controlling mechanisms should become the norm for timber extraction to avoid half-empty forests dominated by rodents and other small species.

Automated AI labeling of optic nerve head enables insights into cross-ancestry glaucoma risk and genetic discovery in >280,000 images from UKB and CLSA.

Cupping of the optic nerve head, a highly heritable trait, is a hallmark of glaucomatous optic neuropathy. Two key parameters are vertical cup-to-disc ratio (VCDR) and vertical disc diameter (VDD). However, manual assessment often suffers from poor accuracy and is time intensive. Here, we show convolutional neural network models can accurately estimate VCDR and VDD for 282,100 images from both UK Biobank and an independent study (Canadian Longitudinal Study on Aging), enabling cross-ancestry epidemiological studies and new genetic discovery for these optic nerve head parameters. Using the AI approach, we perform a systematic comparison of the distribution of VCDR and VDD and compare these with intraocular pressure and glaucoma diagnoses across various genetically determined ancestries, which provides an explanation for the high rates of normal tension glaucoma in East Asia. We then used the large number of AI gradings to conduct a more powerful genome-wide association study (GWAS) of optic nerve head parameters. Using the AI-based gradings increased estimates of heritability by ∼50% for VCDR and VDD. Our GWAS identified more than 200 loci associated with both VCDR and VDD (double the number of loci from previous studies) and uncovered dozens of biological pathways; many of the loci we discovered also confer risk for glaucoma.

Effectiveness of Conventional Digital Fundus Photography-Based Teleretinal Screening for Diabetic Retinopathy and Diabetic Macular Edema: A Report by the American Academy of Ophthalmology.

PURPOSE: This American Academy of Ophthalmology Ophthalmic Technology Assessment aims to assess the effectiveness of conventional teleretinal screening (TS) in detecting diabetic retinopathy (DR) and diabetic macular edema (DME). METHODS: A literature search of the PubMed database was conducted most recently in July 2023 to identify data published between 2006 and 2023 on any of the following elements related to TS effectiveness: (1) the accuracy of TS in detecting DR or DME compared with traditional ophthalmic screening with dilated fundus examination or 7-standard field Early Treatment Diabetic Retinopathy Study photography, (2) the impact of TS on DR screening compliance rates or other patient behaviors, and (3) cost-effectiveness and patient satisfaction of TS compared with traditional DR screening. Identified studies then were rated based on the Oxford Centre for Evidence-Based Medicine grading system. RESULTS: Eight level I studies, 14 level II studies, and 2 level III studies were identified in total. Although cross-study comparison is challenging because of differences in reference standards and grading methods, TS demonstrated acceptable sensitivity and good specificity in detecting DR; moderate to good agreement between TS and reference-standard DR grading was observed. Performance of TS was not as robust in detecting DME, although the number of studies evaluating DME specifically was limited. Two level I studies, 5 level II studies, and 1 level III study supported that TS had a positive impact on overall DR screening compliance, even increasing it by more than 2-fold in one study. Studies assessing cost-effectiveness and patient satisfaction were not graded formally, but they generally showed that TS was cost-effective and preferred by patients over traditional surveillance. CONCLUSIONS: Conventional TS is an effective approach to DR screening not only for its accuracy in detecting referable-level disease, but also for improving screening compliance in a cost-effective manner that may be preferred by patients. Further research is needed to elucidate the ideal approach of TS that may involve integration of artificial intelligence or other imaging technologies in the future. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Black Veterans Experiences with and Recommendations for Improving Weight-Related Health Care: A Photovoice Study.

BACKGROUND: Non-Hispanic Black or African American (hereafter Black) veterans lose less weight than other users of the Veterans Health Administration's (VHA) weight management program (MOVE!), despite higher enrollment. OBJECTIVE: To understand factors that affect weight loss disparities between Black veterans and other veterans. DESIGN: Qualitative study using Photovoice methods. PARTICIPANTS: Self-identified Black veterans in MOVE! across the USA (two women, seven men). APPROACH: We conducted six virtual Photovoice sessions with Black veterans. Session one provided orientation to the goal of understanding factors that might affect weight loss disparities. Participants chose missions related to weight management and VHA care, bringing photos or other media (e.g., poems) to discuss during remaining sessions. Facilitators/participants identified themes related to each session in real time. Between and after sessions, facilitators/investigators conducted rapid qualitative analysis of transcripts/audio to group similar themes, identify illustrative quotes/photos/other media, and prepare dissemination products (e.g., this manuscript). Participants provided feedback on the manuscript during an additional session. KEY RESULTS: Themes were identified across three categories: (1) Food in Our Lives and Health Care; (2) Body Image; and (3) Healthcare Bias and Discrimination. The emotional impact of food and the negative effects of bias and discrimination on health care quality and trust were especially salient. Participants provided recommendations for weight-related and general care. Notable recommendations included the need for VHA to hire and retain providers-especially Black providers-who understand and respect Black patients and are committed to delivering evidence-based, culturally sensitive care. In addition, weight management care should be tailored to individual patients' diets and health beliefs and deemphasize body mass index. CONCLUSIONS: Photovoice resulted in concrete targets that could reduce health disparities. Institutions should consider Photovoice and similar approaches to build trust with and incorporate input from marginalized communities. This approach requires sustained commitment from leaders to engage stakeholders and implement solutions.

Computer-aided diagnostic screen for Congenital Central Hypoventilation Syndrome with facial phenotype.

BACKGROUND: Congenital Central Hypoventilation Syndrome (CCHS) has devastating consequences if not diagnosed promptly. Despite identification of the disease-defining gene PHOX2B and a facial phenotype, CCHS remains underdiagnosed. This study aimed to incorporate automated techniques on facial photos to screen for CCHS in a diverse pediatric cohort to improve early case identification and assess a facial phenotype-PHOX2B genotype relationship. METHODS: Facial photos of children and young adults with CCHS were control-matched by age, sex, race/ethnicity. After validating landmarks, principal component analysis (PCA) was applied with logistic regression (LR) for feature attribution and machine learning models for subject classification and assessment by PHOX2B pathovariant. RESULTS: Gradient-based feature attribution confirmed a subtle facial phenotype and models were successful in classifying CCHS: neural network performed best (median sensitivity 90% (IQR 84%, 95%)) on 179 clinical photos (versus LR and XGBoost, both 85% (IQR 75-76%, 90%)). Outcomes were comparable stratified by PHOX2B genotype and with the addition of publicly available CCHS photos (n = 104) using PCA and LR (sensitivity 83-89% (IQR 67-76%, 92-100%). CONCLUSIONS: Utilizing facial features, findings suggest an automated, accessible classifier may be used to screen for CCHS in children with the phenotype and support providers to seek PHOX2B testing to improve the diagnostics. IMPACT: Facial landmarking and principal component analysis on a diverse pediatric and young adult cohort with PHOX2B pathovariants delineated a distinct, subtle CCHS facial phenotype. Automated, low-cost machine learning models can detect a CCHS facial phenotype with a high sensitivity in screening to ultimately refer for disease-defining PHOX2B testing, potentially addressing gaps in disease underdiagnosis and allow for critical, timely intervention.

Prediction of cardiovascular risk factors from retinal fundus photographs: Validation of a deep learning algorithm in a prospective non-interventional study in Kenya.

AIM: Hypertension and diabetes mellitus (DM) are major causes of morbidity and mortality, with growing burdens in low-income countries where they are underdiagnosed and undertreated. Advances in machine learning may provide opportunities to enhance diagnostics in settings with limited medical infrastructure. MATERIALS AND METHODS: A non-interventional study was conducted to develop and validate a machine learning algorithm to estimate cardiovascular clinical and laboratory parameters. At two sites in Kenya, digital retinal fundus photographs were collected alongside blood pressure (BP), laboratory measures and medical history. The performance of machine learning models, originally trained using data from the UK Biobank, were evaluated for their ability to estimate BP, glycated haemoglobin, estimated glomerular filtration rate and diagnoses from fundus images. RESULTS: In total, 301 participants were enrolled. Compared with the UK Biobank population used for algorithm development, participants from Kenya were younger and would probably report Black/African ethnicity, with a higher body mass index and prevalence of DM and hypertension. The mean absolute error was comparable or slightly greater for systolic BP, diastolic BP, glycated haemoglobin and estimated glomerular filtration rate. The model trained to identify DM had an area under the receiver operating curve of 0.762 (0.818 in the UK Biobank) and the hypertension model had an area under the receiver operating curve of 0.765 (0.738 in the UK Biobank). CONCLUSIONS: In a Kenyan population, machine learning models estimated cardiovascular parameters with comparable or slightly lower accuracy than in the population where they were trained, suggesting model recalibration may be appropriate. This study represents an incremental step toward leveraging machine learning to make early cardiovascular screening more accessible, particularly in resource-limited settings.

Image-based non-invasive assessment of suction blister wounds for clinical safety and efficacy.

Recognising the need for objective imaging-based technologies to assess wound healing in clinical studies, the suction blister wound model offers an easily accessible wound model that creates reproducible epidermal wounds that heal without scarring. This study provides a comprehensive methodology for implementing and evaluating photography-based imaging techniques utilising the suction blister wound model. Our method encompasses a protocol for capturing consistent, high-quality photographs and procedures for quantifying these images via a visual wound healing score and a computer-assisted colour analysis of wound exudation and wound redness. We employed this methodology on 16 suction blister wounds used as controls in a clinical phase-1 trial. Our method enabled us to discern and quantify subtle differences between individual wounds concerning healing progress, erythema and wound exudation. The wound healing score exhibited a high inter-rater agreement. There was a robust correlation between the spectrophotometer-measured erythema index and photography-based wound redness, as well as between dressing protein content and photography-based dressing yellowness. In conclusion, this study equips researchers conducting clinical wound studies with reproducible methods that may support future wound research and aid in the development of new treatments.

Unveiling decomposition dynamics: leveraging 3D models for advanced forensic analysis.

Forensic taphonomy, the study of post-mortem processes, is pivotal in modern forensic science. This short communication illuminates limitations in traditional 2D imaging, specifically digital photographs, within forensic taphonomy, and highlights the vast potential of 3D modeling techniques. Drawing from a recent study in Hawaii's tropical savanna, we unveil disparities between real-time observations and 2D photographs when assessing decomposition, emphasizing the importance of scoring method selection and the need to scrutinize 2D imaging's accuracy in forensic taphonomy. Conversely, 3D modeling techniques, an emerging powerhouse in forensic science, offer multidimensional data, including volume, surface area, and spatial relationships, allowing for comprehensive and precise representation of decomposition dynamics. Despite concerns about texture quality, 3D models yield objective data amenable to analysis by multiple experts, thus minimizing subjectivity and augmenting the reliability of forensic assessments. The potential for 3D modeling to bridge the gap between 2D imaging and real-time decomposition requires tailored methodologies. Future research should focus on standardizing protocols and fostering collaboration among forensic experts, technologists, and researchers to unleash 3D technology's full potential in advancing forensic taphonomy.

Fatal child abuse detected by systematic post-mortem fundus photograph in sudden death in infancy.

In living children, the use of a wide field fundus camera such as RetCam is the gold standard practice to document retinal haemorrhages in suspected cases of abusive head trauma (AHT). In case of sudden unexpected death in infancy (SUDI), child abuse must be considered as a possible cause of death and an eye examination is required. However, no example of post-mortem fundus photograph (PMFP) of retinal haemorrhages related to AHT is yet available for clinicians.We report a SUDI case, with no external traumatic lesions or limb fractures, for which prompt PMFP showed retinal haemorrhages typical of AHT: child abuse was subsequently confirmed by the forensic investigation. We discuss why PMFP is a relevant screening test to detect retinal haemorrhages in the case of SUDI and why the use of the RetCam should be further investigated.

Prioritising quality: investigating the influence of image quality on forensic facial comparison.

Morphological analysis in forensic facial comparison was recently validated for judicial use. However, no image quality assurance systems exist for this purpose, despite image triage being considered the best practice approach. Hence, this study aimed at testing a semi-quantitative scoring method to assess image quality and investigated facial image resolution and lighting quality quantitatively in a context of forensic facial comparison. For this purpose, 400 facial comparison photographic and CCTV image pools developed from the Wits Face Database were used. These facial images were analysed in prior studies that investigated the validity of morphological analysis. A semi-quantitative image quality scoring system was adapted and tested on the above sample and compared across correct and incorrect matches obtained as part of previous studies using a logistic regression model. In addition, facial images were cropped to the closest pixel comprising the face, head and neck areas; then, a face-to-image pixel proportion was calculated as an estimator of resolution quality; and pixel exposure qualities were obtained to be compared to facial comparison outcomes. Ideal and high image quality scores were related to correctness of matches, while low-quality scores were related to incorrect matches. High pixel proportions were related to true matches and low exposure was related to false positives, while high exposure was related to false negatives. These results suggest that an easy method for image triage could be employed by scoring image quality. Quantitative measures should be investigated further for thresholding quality suitability for confidence of facial comparisons.

Role of noninvasive ocular imaging as a biomarker in peripheral artery disease (PAD): A systematic review.

This study aimed to review the current literature exploring the utility of noninvasive ocular imaging for the diagnosis of peripheral artery disease (PAD). Our search was conducted in early April 2022 and included the databases Medline, Scopus, Embase, Cochrane, and others. Five articles were included in the final review. Of the five studies that used ocular imaging in PAD, two studies used retinal color fundus photography, one used optical coherence tomography (OCT), and two used optical coherence tomography angiography (OCTA) to assess the ocular changes in PAD. PAD was associated with both structural and functional changes in the retina. Structural alterations around the optic disc and temporal retinal vascular arcades were seen in color fundus photography of patients with PAD compared to healthy individuals. The presence of retinal hemorrhages, exudates, and microaneurysms in color fundus photography was associated with an increased future risk of PAD, especially the severe form of the disease. The retinal nerve fiber layer (RNFL) was significantly thinner in the nasal quadrant in patients with PAD compared to age-matched healthy individuals in OCT. Similarly, the choroidal thickness in the subfoveal region was significantly thinner in patients with PAD compared to controls. Patients with PAD also had a significant reduction in the retinal and choroidal circulation in OCTA compared to healthy controls. As PAD causes thinning and ischemic changes in retinal vessels, examination of the retinal vessels using retinal imaging techniques can provide useful information about early microvascular damage in PAD. Ocular imaging could potentially serve as a biomarker for PAD. PROSPERO ID: CRD42022310637.

Evaluating imaging repeatability of fully self-service fundus photography within a community-based eye disease screening setting.

PURPOSE: This study aimed to investigate the imaging repeatability of self-service fundus photography compared to traditional fundus photography performed by experienced operators. DESIGN: Prospective cross-sectional study. METHODS: In a community-based eye diseases screening site, we recruited 65 eyes (65 participants) from the resident population of Shanghai, China. All participants were devoid of cataract or any other conditions that could potentially compromise the quality of fundus imaging. Participants were categorized into fully self-service fundus photography or traditional fundus photography group. Image quantitative analysis software was used to extract clinically relevant indicators from the fundus images. Finally, a statistical analysis was performed to depict the imaging repeatability of fully self-service fundus photography. RESULTS: There was no statistical difference in the absolute differences, or the extents of variation of the indicators between the two groups. The extents of variation of all the measurement indicators, with the exception of the optic cup area, were below 10% in both groups. The Bland-Altman plots and multivariate analysis results were consistent with results mentioned above. CONCLUSIONS: The image repeatability of fully self-service fundus photography is comparable to that of traditional fundus photography performed by professionals, demonstrating promise in large-scale eye disease screening programs.

Ecosystem warming extends vegetation activity but heightens vulnerability to cold temperatures.

Shifts in vegetation phenology are a key example of the biological effects of climate change1-3. However, there is substantial uncertainty about whether these temperature-driven trends will continue, or whether other factors-for example, photoperiod-will become more important as warming exceeds the bounds of historical variability4,5. Here we use phenological transition dates derived from digital repeat photography6 to show that experimental whole-ecosystem warming treatments7 of up to +9 °C linearly correlate with a delayed autumn green-down and advanced spring green-up of the dominant woody species in a boreal Picea-Sphagnum bog. Results were confirmed by direct observation of both vegetative and reproductive phenology of these and other bog plant species, and by multiple years of observations. There was little evidence that the observed responses were constrained by photoperiod. Our results indicate a likely extension of the period of vegetation activity by 1-2 weeks under a 'CO2 stabilization' climate scenario (+2.6 ± 0.7 °C), and 3-6 weeks under a 'high-CO2 emission' scenario (+5.9 ± 1.1 °C), by the end of the twenty-first century. We also observed severe tissue mortality in the warmest enclosures after a severe spring frost event. Failure to cue to photoperiod resulted in precocious green-up and a premature loss of frost hardiness8, which suggests that vulnerability to spring frost damage will increase in a warmer world9,10. Vegetation strategies that have evolved to balance tradeoffs associated with phenological temperature tracking may be optimal under historical climates, but these strategies may not be optimized for future climate regimes. These in situ experimental results are of particular importance because boreal forests have both a circumpolar distribution and a key role in the global carbon cycle11.