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Background: Infections caused by soil-transmitted helminths (STHs) are the most prevalent neglected tropical diseases and result in a major disease burden in low- and middle-income countries, especially in school-aged children. Improved diagnostic methods, especially for light intensity infections, are needed for efficient, control and elimination of STHs as a public health problem, as well as STH management. Image-based artificial intelligence (AI) has shown promise for STH detection in digitized stool samples. However, the diagnostic accuracy of AI-based analysis of entire microscope slides, so called whole-slide images (WSI), has previously not been evaluated on a sample-level in primary healthcare settings in STH endemic countries. Methodology/Principal findings: Stool samples (n = 1,335) were collected during 2020 from children attending primary schools in Kwale County, Kenya, prepared according to the Kato-Katz method at a local primary healthcare laboratory and digitized with a portable whole-slide microscopy scanner and uploaded via mobile networks to a cloud environment. The digital samples of adequate quality (n = 1,180) were split into a training (n = 388) and test set (n = 792) and a deep-learning system (DLS) developed for detection of STHs. The DLS findings were compared with expert manual microscopy and additional visual assessment of the digital samples in slides with discordant results between the methods. Manual microscopy detected 15 (1.9%) Ascaris lumbricoides, 172 (21.7%) Tricuris trichiura and 140 (17.7%) hookworm (Ancylostoma duodenale or Necator americanus) infections in the test set. Importantly, more than 90% of all STH positive cases represented light intensity infections. With manual microscopy as the reference standard, the sensitivity of the DLS as the index test for detection of A. lumbricoides, T. trichiura and hookworm was 80%, 92% and 76%, respectively. The corresponding specificity was 98%, 90% and 95%. Notably, in 79 samples (10%)

PURPOSE: To compare the effects on verbal fluency of a supported yoga-based exercise intervention to an aerobic exercise intervention and a wait-list control group. PARTICIPANTS AND METHODS: Eighty-two physically-inactive but otherwise healthy adults (mean age 72.5 years, range 65-85, 77% female) were recruited into a 12-week, three-group, parallel randomized controlled trial. Participants were supported to complete ≥3 Hatha yoga classes per/week or ≥3 structured aerobic exercise sessions/week. A wait-list control group continued usual daily activities only. Verbal fluency, including total-FAS, animals, and verbs, was assessed before and after interventions. Group effects were assessed using analysis of covariance (ANCOVA). RESULTS: Twenty-seven participants were randomized to yoga, 29 to aerobic exercise and 26 to a waitlist. At 12-week follow-up, compared to baseline, there were increases in mean total-FAS in the yoga (+5.0 words, p=0.002) and aerobic exercise groups (+6.6 words, p=0.004). Mean total-FAS in the wait-list control group remained stable (-0.5 words, p=0.838). There were medium-magnitude estimated treatment effects on total-FAS for yoga versus wait-list control and aerobic exercise versus wait-list control: Hedges' g=0.51 (p=0.213) and 0.57 (p=0.098) respectively. In addition, small-to-medium magnitude estimated treatment effects were seen on animals and verbs for yoga versus wait-list control and aerobic exercise versus wait-list control: g=0.28 (p=0.155), 0.19 (p=0.766) and 0.50 (p=0.085), 0.59 (p=0.233) respectively. CONCLUSION: Participation in yoga or aerobic exercise was associated with estimated improvements in verbal fluency compared to a non-active control group. Yoga and aerobic exercise may be promising approaches by which to promote cognitive function among older adults. TRIAL REGISTRATION: DRKS00015093, U1111-1217-4248.

Paul Welford,1 Josefine Östh,1 Sara Hoy,2 Susan L Rossell,3 Michaela Pascoe,4 Vinod Diwan,1 Mats Hallgren1 1Department of Global Public Health, Karolinska Institutet, Solna, Sweden; 2Swedish School of Sport and Health Sciences (GIH), Stockholm, Sweden; 3Centre for Mental Health, School of Health Sciences, Swinburne University, Melbourne, Victoria, Australia; 4Institute for Health and Sport, Victoria University, Melbourne, Victoria, AustraliaCorrespondence: Mats Hallgren, Department of Global Public Health, Karolinska Institutet, Level 6, 1e Solnavägen, Solna, 11365, Sweden, Tel +46852480000, Email mats.hallgren@ki.sePurpose: To compare the effects on verbal fluency of a supported yoga-based exercise intervention to an aerobic exercise intervention and a wait-list control group.Participants and Methods: Eighty-two physically-inactive but otherwise healthy adults (mean age 72.5 years, range 65– 85, 77% female) were recruited into a 12-week, three-group, parallel randomized controlled trial. Participants were supported to complete ≥ 3 Hatha yoga classes per/week or ≥ 3 structured aerobic exercise sessions/week. A wait-list control group continued usual daily activities only. Verbal fluency, including total-FAS, animals, and verbs, was assessed before and after interventions. Group effects were assessed using analysis of covariance (ANCOVA).Results: Twenty-seven participants were randomized to yoga, 29 to aerobic exercise and 26 to a waitlist. At 12-week follow-up, compared to baseline, there were increases in mean total-FAS in the yoga (+5.0 words, p=0.002) and aerobic exercise groups (+6.6 words, p=0.004). Mean total-FAS in the wait-list control group remained stable (− 0.5 words, p=0.838). There were medium-magnitude estimated treatment effects on total-FAS for yoga versus wait-list control and aerobic exercise versus wait-list control: Hedges’ g=0.51 (p=0.213) and 0.57 (p=0.098) respectively. In addition, small-to-medium magnitude estimated treatment eff

An estimated 350 million cases of STIs occur globally each year. In Sweden, Chlamydia is the most common STI with approximately 30 000 cases annually, disproportionally affecting youth. National surveys report low condom use among youth. Smartphone coverage is high among this tech-savvy group. In collaboration with youth, we developed an interactive smartphone application comprising games, peer experiences and information snippets to promote condom use. Objectives: To evaluate in a randomised controlled trial, the effectiveness of this smartphone application to improve condom use among youth in Stockholm, Sweden. Methods: This two-arm, individually randomised controlled trial was implemented through the Youth Health Clinics (YHC) in Stockholm, Sweden. Youth aged 18–23 years, who owned a smartphone and had ≥2 sexual partners during the past 6 months were eligible. The intervention delivered the interactive elements described above over 180 days. The control group received a ‘dummy’ application. Both groups received standard of care at the YHC. The primary outcome was proportion of consistent (100%) self-reported condom use at 6 months. Secondary outcomes included self-reported number of partners, occurrence of STIs/pregnancy and STI tests during the study period. An intention-to-treat approach was used. Results: 214 and 219 youth were randomised to the intervention and control groups, respectively. Consistent condom use was reported for 32/214 (15.0%) in the intervention group and for 35/219 (16.0%) in the control group (OR 0.9, 95% CI 0.5 to 1.6). No significant differences in secondary outcomes were seen. Conclusion: We were unable to detect an effect of the intervention. Future research should focus on targeting different subgroups within the overall risk group, with tailored mHealth interventions. The potential for such interventions in settings where sexual health services are unavailable should be evaluated. Trial registration number: ISRCTN13212899.

Importance: Cervical cancer is highly preventable but remains a common and deadly cancer in areas without screening programs. The creation of a diagnostic system to digitize Papanicolaou test samples and analyze them using a cloud-based deep learning system (DLS) may provide needed cervical cancer screening to resource-limited areas. Objective: To determine whether artificial intelligence-supported digital microscopy diagnostics can be implemented in a resource-limited setting and used for analysis of Papanicolaou tests. Design, Setting, and Participants: In this diagnostic study, cervical smears from 740 HIV-positive women aged between 18 and 64 years were collected between September 1, 2018, and September 30, 2019. The smears were digitized with a portable slide scanner, uploaded to a cloud server using mobile networks, and used to train and validate a DLS for the detection of atypical cervical cells. This single-center study was conducted at a local health care center in rural Kenya. Exposures: Detection of squamous cell atypia in the digital samples by analysis with the DLS. Main Outcomes and Measures: The accuracy of the DLS in the detection of low- and high-grade squamous intraepithelial lesions in Papanicolaou test whole-slide images. Results: Papanicolaou test results from 740 HIV-positive women (mean [SD] age, 41.8 [10.3] years) were collected. The DLS was trained using 350 whole-slide images and validated on 361 whole-slide images (average size, 100 387 x 47 560 pixels). For detection of cervical cellular atypia, sensitivities were 95.7% (95% CI, 85.5%-99.5%) and 100% (95% CI, 82.4%-100%), and specificities were 84.7% (95% CI, 80.2%-88.5%) and 78.4% (95% CI, 73.6%-82.4%), compared with the pathologist assessment of digital and physical slides, respectively. Areas under the receiver operating characteristic curve were 0.94 and 0.96, respectively. Negative predictive values were high (99%-100%), and accuracy was high, particularly for the detection of high-g

BACKGROUND: Malaria remains a major global health problem with a need for improved field-usable diagnostic tests. We have developed a portable, low-cost digital microscope scanner, capable of both brightfield and fluorescence imaging. Here, we used the instrument to digitize blood smears, and applied deep learning (DL) algorithms to detect Plasmodium falciparum parasites. METHODS: Thin blood smears (n = 125) were collected from patients with microscopy-confirmed P. falciparum infections in rural Tanzania, prior to and after initiation of artemisinin-based combination therapy. The samples were stained using the 4',6-diamidino-2-phenylindole fluorogen and digitized using the prototype microscope scanner. Two DL algorithms were trained to detect malaria parasites in the samples, and results compared to the visual assessment of both the digitized samples, and the Giemsa-stained thick smears. RESULTS: Detection of P. falciparum parasites in the digitized thin blood smears was possible both by visual assessment and by DL-based analysis with a strong correlation in results (r = 0.99, p < 0.01). A moderately strong correlation was observed between the DL-based thin smear analysis and the visual thick smear-analysis (r = 0.74, p < 0.01). Low levels of parasites were detected by DL-based analysis on day three following treatment initiation, but a small number of fluorescent signals were detected also in microscopy-negative samples. CONCLUSION: Quantification of P. falciparum parasites in DAPI-stained thin smears is feasible using DL-supported, point-of-care digital microscopy, with a high correlation to visual assessment of samples. Fluorescent signals from artefacts in samples with low infection levels represented the main challenge for the digital analysis, thus highlighting the importance of minimizing sample contaminations. The proposed method could support malaria diagnostics and monitoring of treatment response through automated quantification of parasitaemia and