Generative artificial intelligence to produce high-fidelity blastocyst-stage embryo images.

STUDY QUESTION: Can generative artificial intelligence (AI) models produce high-fidelity images of human blastocysts? SUMMARY ANSWER: Generative AI models exhibit the capability to generate high-fidelity human blastocyst images, thereby providing substantial training datasets crucial for the development of robust AI models. WHAT IS KNOWN ALREADY: The integration of AI into IVF procedures holds the potential to enhance objectivity and automate embryo selection for transfer. However, the effectiveness of AI is limited by data scarcity and ethical concerns related to patient data privacy. Generative adversarial networks (GAN) have emerged as a promising approach to alleviate data limitations by generating synthetic data that closely approximate real images. STUDY DESIGN, SIZE, DURATION: Blastocyst images were included as training data from a public dataset of time-lapse microscopy (TLM) videos (n = 136). A style-based GAN was fine-tuned as the generative model. PARTICIPANTS/MATERIALS, SETTING, METHODS: We curated a total of 972 blastocyst images as training data, where frames were captured within the time window of 110-120 h post-insemination at 1-h intervals from TLM videos. We configured the style-based GAN model with data augmentation (AUG) and pretrained weights (Pretrained-T: with translation equivariance; Pretrained-R: with translation and rotation equivariance) to compare their optimization on image synthesis. We then applied quantitative metrics including Fréchet Inception Distance (FID) and Kernel Inception Distance (KID) to assess the quality and fidelity of the generated images. Subsequently, we evaluated qualitative performance by measuring the intelligence behavior of the model through the visual Turing test. To this end, 60 individuals with diverse backgrounds and expertise in clinical embryology and IVF evaluated the quality of synthetic embryo images. MAIN RESULTS AND THE ROLE OF CHANCE: During the training process, we observed consistent improvement of image quality that was measured by FID and KID scores. Pretrained and AUG + Pretrained initiated with remarkably lower FID and KID values compared to both Baseline and AUG + Baseline models. Following 5000 training iterations, the AUG + Pretrained-R model showed the highest performance of the evaluated five configurations with FID and KID scores of 15.2 and 0.004, respectively. Subsequently, we carried out the visual Turing test, such that IVF embryologists, IVF laboratory technicians, and non-experts evaluated the synthetic blastocyst-stage embryo images and obtained similar performance in specificity with marginal differences in accuracy and sensitivity. LIMITATIONS, REASONS FOR CAUTION: In this study, we primarily focused the training data on blastocyst images as IVF embryos are primarily assessed in blastocyst stage. However, generation of an array of images in different preimplantation stages offers further insights into the development of preimplantation embryos and IVF success. In addition, we resized training images to a resolution of 256 × 256 pixels to moderate the computational costs of training the style-based GAN models. Further research is needed to involve a more extensive and diverse dataset from the formation of the zygote to the blastocyst stage, e.g. video generation, and the use of improved image resolution to facilitate the development of comprehensive AI algorithms and to produce higher-quality images. WIDER IMPLICATIONS OF THE FINDINGS: Generative AI models hold promising potential in generating high-fidelity human blastocyst images, which allows the development of robust AI models as it can provide sufficient training datasets while safeguarding patient data privacy. Additionally, this may help to produce sufficient embryo imaging training data with different (rare) abnormal features, such as embryonic arrest, tripolar cell division to avoid class imbalances and reach to even datasets. Thus, generative models may offer a compelling opportunity to transform embryo selection procedures and substantially enhance IVF outcomes. STUDY FUNDING/COMPETING INTEREST(S): This study was supported by a Horizon 2020 innovation grant (ERIN, grant no. EU952516) and a Horizon Europe grant (NESTOR, grant no. 101120075) of the European Commission to A.S. and M.Z.E., the Estonian Research Council (grant no. PRG1076) to A.S., and the EVA (Erfelijkheid Voortplanting & Aanleg) specialty program (grant no. KP111513) of Maastricht University Medical Centre (MUMC+) to M.Z.E. TRIAL REGISTRATION NUMBER: Not applicable.

The outcomes of team-based learning vs small group interactive learning in the obstetrics and gynecology course for undergraduate students.

INTRODUCTION: Team-based learning (TBL) is a well-established active teaching method which has been shown to have pedagogical advantages in some areas such as business education and preclinical disciplines in undergraduate medical education. Increasingly, it has been adapted to clinical disciplines. However, its superiority over conventional learning methods used in clinical years of medical school remains unclear. The aim of this study was to compare TBL with traditional seminars delivered in small group interactive learning (SIL) format in terms of knowledge acquisition and retention, satisfaction and engagement of undergraduate medical students during the 6-week obstetrics and gynecology clerkship. MATERIAL AND METHODS: The study was conducted at Karolinska Institutet, a medical university in Sweden, and had a prospective, crossover design. All fifth-year medical students attending the obstetrics and gynecology clerkship, at four different teaching hospitals in Stockholm (approximately 40 students per site), in the Autumn semester of 2022 were invited to participate. Two seminars (one in obstetrics and one in gynecology) were designed and delivered in two different formats, ie TBL and SIL. The student:teacher ratio was approximately 10:1 in the traditional SIL seminars and 20:1 in the TBL. All TBL seminars were facilitated by a single teacher who had been trained and certified in TBL. Student knowledge acquisition and retention were assessed by final examination scores, and the engagement and satisfaction were assessed by questionnaires. For the TBL seminars, individual and team readiness assurance tests were also performed and evaluated. RESULTS: Of 148 students participating in the classrooms, 132 answered the questionnaires. No statistically significant differences were observed between TBL and SIL methods with regard to student knowledge acquisition and retention, engagement and satisfaction. CONCLUSIONS: We found no differences in student learning outcomes or satisfaction using TBL or SIL methods. However, as TBL had a double the student to teacher ratio as compared with SIL, in settings where teachers are scarce and suitable rooms are available for TBL sessions, the method may be beneficial in reducing faculty workload without compromising students' learning outcomes.

Outcomes of SARS-CoV-2 infection in early pregnancy-A systematic review and meta-analysis.

INTRODUCTION: Available data on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and pregnancy outcomes mostly refer to women contracting the infection during advanced pregnancy or close to delivery. There is limited information on the association between SARS-CoV-2 infection in early pregnancy and outcomes thereof. MATERIAL AND METHODS: We aimed to systematically review the maternal, fetal and neonatal outcomes following SARS-CoV-2 infection in early pregnancy, defined as <20 weeks of gestation (PROSPERO Registration 2020 CRD42020177673). Searches were carried out in PubMed, Medline, EMBASE, and Scopus databases from January 2020 until April 2023 and the WHO database of publications on coronavirus disease 2019 (COVID-19) from December 2019 to April 2023. Cohort and case-control studies on COVID-19 occurring in early pregnancy that reported data on maternal, fetal, and neonatal outcomes were included. Case reports and studies reporting only exposure to SARS-CoV-2 or not stratifying outcomes based on gestational age were excluded. Data were extracted in duplicate. Meta-analyses were conducted when appropriate, using R meta (R version 4.0.5). RESULTS: A total of 18 studies, 12 retrospective and six prospective, were included in this review, reporting on 10 147 SARS-CoV-2-positive women infected in early pregnancy, 9533 neonates, and 180 882 SARS-CoV-2 negative women. The studies had low to moderate risk of bias according to the Newcastle-Ottawa quality assessment Scale. The studies showed significant clinical and methodological heterogeneity. A meta-analysis could be performed only on the outcome miscarriage rate, with a pooled random effect odds ratio of 1.44 (95% confidence interval 0.96-2.18), showing no statistical difference in miscarriage in SARS-CoV-2-infected women. Individual studies reported increased incidences of stillbirth, low birthweight and preterm birth among neonates born to mothers affected by COVID-19 in early pregnancy; however, these results were not consistent among all studies. CONCLUSIONS: In this comprehensive systematic review of available evidence, we identified no statistically significant adverse association between SARS-CoV-2 infection in early pregnancy (before 20 weeks of gestation) and fetal, neonatal, or maternal outcomes. However, a 44% increase in miscarriage rate is concerning and further studies of larger sample size are needed to confirm or refute our findings.

Team-based learning (TBL) in clinical disciplines for undergraduate medical students-a scoping review.

BACKGROUND: Team-based learning (TBL) is an evidence-based pedagogical method that has been used in undergraduate medical education since 2001. However, its use in clinical disciplines is rarely reported, and the impact of its implementation is not known. The aim of this study was to explore and map the published literature on the impact of implementing TBL in clinical disciplines in undergraduate medical education. METHODS: A comprehensive search of Medline, Education Resources Information Center (ERIC), and Web of Science databases was performed on November 24, 2021 and updated April 6, 2023, using relevant Medical Subject Headings (MeSH) and free-text terms. Original research studies reporting on the implementation of TBL in clinical disciplines in undergraduate medical education published in peer-reviewed English language journals were included irrespective of their methodological design. RESULTS: The initial search identified 2,383 records. Of these, 49 met the inclusion criteria. Most of the studies (n = 44, 90%) described the implementation of a modified version of TBL in which one or more TBL steps were missing, and one study had undefined protocol for the implementation. The most reported outcomes were knowledge acquisition (n = 38, 78%) and students' satisfaction or attitudes toward TBL (n = 34, 69%). Despite some differences in their results, the studies found that implementing TBL is associated with increased knowledge acquisition (n = 19, 39%), student engagement (n = 6, 12%), and student satisfaction (n = 31, 63%). CONCLUSIONS: Most of the studies reported positive results in students' satisfaction and students' engagement, whilst the results on knowledge acquisition and retention were more contradictory. In most of the studies, TBL was implemented in a modified form and diverse comparators were used. The methodological quality also varied. Thus, no unequivocal conclusions could be drawn regarding the value of implementing TBL in clinical disciplines. More studies with rigorous methodologies are needed in this field.

Exploring the dynamics of situational interest in team-based learning in undergraduate medical education.

BACKGROUND: Team-based learning (TBL) is a widely recognized instructional approach in medical education blending direct instruction with active-cooperative learning in small groups. While TBL is known to enhance knowledge acquisition, its impact on student motivation, particularly through situational interest, remains underexplored. This study aimed to investigate the development of situational interest across the distinct phases of TBL, focusing on how each phase (individual readiness assurance test; iRAT, team readiness assurance test; tRAT, and application exercise; AE) influences students' situational interest. The study sought to provide insights into the motivational dynamics underpinning TBL in a medical education setting. METHODS: A total of 88 medical students participated in a TBL session on "Bleeding during Pregnancy." Situational interest was measured after each TBL phase. A one-way repeated-measures analysis of variance (ANOVA) was conducted to assess the fluctuation of situational interest throughout the session. RESULTS: The analysis revealed significant variations in situational interest across different TBL stages. There was a significant increase in situational interest following the tRAT (p = .001). Post-tRAT, situational interest significantly decreased after the AE (p = .007), returning to levels observed at the session's start. Post hoc correlation analysis suggested a negative association between tRAT performance and situational interest, indicating heightened interest in response to awareness of knowledge gaps during the tRAT. CONCLUSIONS: The findings of this study may challenge the traditional view of TBL, suggesting a more integrated and dynamic interplay between knowledge acquisition and application phases. The results highlight the importance of the AE phase in clinical education and suggest that situational interest is one key driver in the learning process within TBL. Future research should focus on replicating these findings and comparing situational interest development between pre-clinical and clinical student cohorts to further understand the effects of situational interest on TBL in medical education.

Giant urinary bladder stone: A rare case report.

INTRODUCTION: Giant urinary bladder stones are rare phenomenon which is associated with chronic urinary infections, intravesical foreign bodies, urethral strictures, bladder diverticula etc. CASE REPORT: A 52-year-old man presented with complaints of severe dysuria, urgency, frequency, suprapubic pain, and pollakuria for the last ten years. Physical examination revealed a palpable suprapubic mass with no obvious flank masses. Ultrasonography of the abdomen and pelvis revealed right-sided gross hydroureteronephrosis and thinning of renal parenchyma along with a hyperechoic structure with posterior acoustic shadowing was noted in the region of the urinary bladder, suggesting a vesical calculus. Plain CT of the kidneys, ureters, and bladder (KUB) confirmed right nephrolithiasis in lower poly calyx and a large vesical calculus (10.6 cm × 8.6 cm x8.8 cm, +1110 HU). Open cystolithotomy with a right-sided double-J "DJ" stent insertion was performed. Post-operative period went uneventful. DISCUSSION: Giant bladder stones are extremely rare, often resulting from neglected symptoms in otherwise normal individuals. They typically develop over several years and present with symptoms like severe dysuria, urgency, frequency, supra-pubic pain, and hematuria. Diagnosis is made by cystoscopy, ultrasonography and CT-KUB. Treatment includes intracorporeal cystolithotripsy using a laser, ultrasonic lithotripter, or pneumatic lithotripter, depending on availability. Endourologic procedures have been safer and more cost-effective for bladder stones, however, open removal is the treatment of choice for giant bladder stones. CONCLUSION: Open cystolithotomy can be performed to remove giant bladder stone with near 100 % stone removal rate.

Towards ultrafast quantitative phase imaging via differentiable microscopy [Invited].

With applications ranging from metabolomics to histopathology, quantitative phase microscopy (QPM) is a powerful label-free imaging modality. Despite significant advances in fast multiplexed imaging sensors and deep-learning-based inverse solvers, the throughput of QPM is currently limited by the pixel-rate of the image sensors. Complementarily, to improve throughput further, here we propose to acquire images in a compressed form so that more information can be transferred beyond the existing hardware bottleneck of the image sensor. To this end, we present a numerical simulation of a learnable optical compression-decompression framework that learns content-specific features. The proposed differentiable quantitative phase microscopy (∂-QPM) first uses learnable optical processors as image compressors. The intensity representations produced by these optical processors are then captured by the imaging sensor. Finally, a reconstruction network running on a computer decompresses the QPM images post aquisition. In numerical experiments, the proposed system achieves compression of × 64 while maintaining the SSIM of ∼0.90 and PSNR of ∼30 dB on cells. The results demonstrated by our experiments open up a new pathway to QPM systems that may provide unprecedented throughput improvements.

CHK1 inhibitor induced PARylation by targeting PARG causes excessive replication and metabolic stress and overcomes chemoresistance in ovarian cancer.

Chemoresistance contributes to the majority of deaths in women with ovarian cancer (OC). Altered DNA repair and metabolic signaling is implicated in mediating therapeutic resistance. DNA damage checkpoint kinase 1 (CHK1) integrates cell cycle and DNA repair in replicating cells, and its inhibition causes replication stress, repair deficiency and cell cycle dysregulation. We observed elevated Poly-ADP-ribosylation (PAR) of proteins (PARylation) and subsequent decrease in cellular NAD+ levels in OC cells treated with the CHK1 inhibitor prexasertib, indicating activation of NAD+ dependent DNA repair enzymes poly-ADP-ribose polymerases (PARP1/2). While multiple PARP inhibitors are in clinical use in treating OC, tumor resistance to these drugs is highly imminent. We reasoned that inhibition of dePARylation by targeting Poly (ADP-ribose) glycohydrolase (PARG) would disrupt metabolic and DNA repair crosstalk to overcome chemoresistance. Although PARG inhibition (PARGi) trapped PARylation of the proteins and activated CHK1, it did not cause any significant OC cell death. However, OC cells deficient in CHK1 were hypersensitive to PARGi, suggesting a role for metabolic and DNA repair crosstalk in protection of OC cells. Correspondingly, OC cells treated with a combination of CHK1 and PARG inhibitors exhibited excessive replication stress-mediated DNA lesions, cell cycle dysregulation, and mitotic catastrophe compared to individual drugs. Interestingly, increased PARylation observed in combination treatment resulted in depletion of NAD+ levels. These decreased NAD+ levels were also paralleled with reduced aldehyde dehydrogenase (ALDH) activity, which requires NAD+ to maintain cancer stem cells. Furthermore, prexasertib and PARGi combinations exhibited synergistic cell death in OC cells, including an isogenic chemoresistant cell line and 3D organoid models of primary patient-derived OC cell lines. Collectively, our data highlight a novel crosstalk between metabolism and DNA repair involving replication stress and NAD+-dependent PARylation, and suggest a novel combination therapy of CHK1 and PARG inhibitors to overcome chemoresistance in OC.

Citalopram exposure of hESCs during neuronal differentiation identifies dysregulated genes involved in neurodevelopment and depression.

Selective serotonin reuptake inhibitors (SSRIs), including citalopram, are widely used antidepressants during pregnancy. However, the effects of prenatal exposure to citalopram on neurodevelopment remain poorly understood. We aimed to investigate the impact of citalopram exposure on early neuronal differentiation of human embryonic stem cells using a multi-omics approach. Citalopram induced time- and dose-dependent effects on gene expression and DNA methylation of genes involved in neurodevelopmental processes or linked to depression, such as BDNF, GDF11, CCL2, STC1, DDIT4 and GAD2. Single-cell RNA-sequencing analysis revealed distinct clusters of stem cells, neuronal progenitors and neuroblasts, where exposure to citalopram subtly influenced progenitor subtypes. Pseudotemporal analysis showed enhanced neuronal differentiation. Our findings suggest that citalopram exposure during early neuronal differentiation influences gene expression patterns associated with neurodevelopment and depression, providing insights into its potential neurodevelopmental impact and highlighting the importance of further research to understand the long-term consequences of prenatal SSRI exposure.

Severe maternal morbidity and mortality associated with COVID-19: The risk should not be downplayed

Nordic countries have a long tradition of collecting health related population data meticulously and reporting them transparently. Such data provide firm grounds for making good decisions and as a result the public health institutions in Scandinavia enjoy the trust of society. The Covid­19 pandemic has, however, resulted in a completely new situation as we are now exploring in uncharted waters. Based on reports from China, Italy, USA and perhaps with the good intention of reducing anxiety among this vulnerable population group, it has been widely publicized that pregnant women are not at increased risk of susceptibility, infectivity and severity of COVID­19 compared to the general population or non­pregnant women, although a systematic review of 108 cases of laboratory confirmed pregnancies with COVID­19 has reported the possibility of increased risk of severe disease among pregnant women.(AU)