Liver proteomics identifies a disconnect between proteins associated with de novo lipogenesis and triglyceride storage.

De novo lipogenesis (DNL) has been implicated in the development and progression of liver steatosis. Hepatic DNL is strongly influenced by dietary macronutrient composition with diets high in carbohydrate increasing DNL and while diets high in fat decrease DNL. The enzymes in the core DNL pathway have been well characterised, however less is known about other liver proteins that play accessory or regulatory roles. In the current study, we associate measured rates of hepatic DNL and fat content with liver proteomic analysis in mice to identify known and unknown proteins that may have a role in DNL. Male mice were fed either a standard chow diet, a semi-purified high starch or high fat diet. Both semi-purified diets resulted in increased body weight, fat mass and liver triglyceride content compared to chow controls and hepatic DNL was increased in the high starch and decreased in high fat fed mice. Proteomic analysis identified novel proteins associated with DNL that are involved in taurine metabolism, suggesting a link between these pathways. There was no relationship between proteins that associated with DNL and those associated with liver triglyceride content. Further analysis identified proteins that are differentially regulated when comparing a non-purified chow diet to either of the semi-purified diets which provide a set of proteins that are influenced by dietary complexity. Finally, we compared the liver proteome between 4- and 30-week diet-fed mice and found remarkable similarity suggesting metabolic remodelling of the liver occurs rapidly in response to differing dietary components.

Predictors of Participation in a Perinatal Text Message Screening Protocol for Maternal Depression and Anxiety: Prospective Cohort Study.

BACKGROUND: Universal screening for depression and anxiety in pregnancy has been recommended by several leading medical organizations, but the implementation of such screening protocols may overburden health care systems lacking relevant resources. Text message screening may provide a low-cost, accessible alternative to in-person screening assessments. However, it is critical to understand who is likely to participate in text message-based screening protocols before such approaches can be implemented at the population level. OBJECTIVE: This study aimed to examine sources of selection bias in a texting-based screening protocol that assessed symptoms of depression and anxiety across pregnancy and into the postpartum period. METHODS: Participants from the Montreal Antenatal Well-Being Study (n=1130) provided detailed sociodemographic information and completed questionnaires assessing symptoms of depression (Edinburgh Postnatal Depression Scale [EPDS]) and anxiety (State component of the State-Trait Anxiety Inventory [STAI-S]) at baseline between 8 and 20 weeks of gestation (mean 14.5, SD 3.8 weeks of gestation). Brief screening questionnaires, more suitable for delivery via text message, assessing depression (Whooley Questions) and anxiety symptoms (Generalized Anxiety Disorder 2-Item questionnaire) were also collected at baseline and then via text message at 14-day intervals. Two-tailed t tests and Fisher tests were used to identify maternal characteristics that differed between participants who responded to the text message screening questions and those who did not. Hurdle regression models were used to test if individuals with a greater burden of depression and anxiety at baseline responded to fewer text messages across the study period. RESULTS: Participants who responded to the text messages (n=933) were more likely than nonrespondents (n=114) to self-identify as White (587/907, 64.7% vs 39/96, 40.6%; P<.001), report higher educational attainment (postgraduate: 268/909, 29.5% vs 15/94, 16%; P=.005), and report higher income levels (CAD $150,000 [a currency exchange rate of CAD $1=US $0.76 is applicable] or more: 176/832, 21.2% vs 10/84, 11.9%; P<.001). There were no significant differences in symptoms of depression and anxiety between the 2 groups at baseline or postpartum. However, baseline depression (EPDS) or anxiety (STAI-S) symptoms did predict the total number of text message time points answered by participants, corresponding to a decrease of 1% (eß=0.99; P<.001) and 0.3% (eß=0.997; P<.001) in the number of text message time points answered per point increase in EPDS or STAI-S score, respectively. CONCLUSIONS: Findings from this study highlight the feasibility of text message-based screening protocols with high participation rates. However, our findings also highlight how screening and service delivery via digital technology could exacerbate disparities in mental health between certain patient groups.

Region-based analyses of existing genome-wide association studies identifies novel potential genetic susceptibility regions for glioma.

PURPOSE: Glioma is a rare and debilitating brain cancer with one of the lowest cancer survival rates. Genome-wide association studies have identified 34 genetic susceptibility regions. We sought to discover novel susceptibility regions using approaches which test groups of contiguous genetic markers simultaneously. PATIENTS AND METHODS: We analyzed data from three independent glioma studies of European ancestry, GliomaScan (1,316 cases/1,293 controls), AGOG (560 cases/2,237 controls), and GICC (4,000 cases/2,411 controls), using the machine-learning algorithm DEPTH and a region-based regression method based on the generalized Berk-Jones (GBJ) statistic, to assess the association of glioma with genomic regions by glioma type and sex. Summary statistics from the UCSF/Mayo Clinic study were used for independent validation. We conducted a meta-analysis using GliomaScan, AGOG, GICC and UCSF/Mayo. RESULTS: We identified 11 novel candidate genomic regions for glioma risk common to multiple studies. Two of the 11 regions, 16p13.3 containing RBFOX1 and 1p36.21 containing PRDM2, were significantly associated with female and male glioma risk respectively, based on results of the meta-analysis. Both regions have been previously linked to glioma tumor progression. Three of the 11 regions contain neurotransmitter receptor genes (7q31.33 GRM8, 5q35.2 DRD1, 15q13.3 CHRNA7). CONCLUSIONS: Our region-based approach identified 11 genomic regions that suggest association with glioma risk of which two regions, 16p13.3 and 1p36.21, warrant further investigation as genetic susceptibility regions for female and male risk respectively. Our analyses suggest that genetic susceptibility to glioma may differ by sex and highlights the possibility that synapse-related genes play a role in glioma susceptibility.

FedDSS: A data-similarity approach for client selection in horizontal federated learning.

BACKGROUND AND OBJECTIVE: Federated learning (FL) is an emerging distributed learning framework allowing multiple clients (hospitals, institutions, smart devices, etc.) to collaboratively train a centralized machine learning model without disclosing personal data. It has the potential to address several healthcare challenges, including a lack of training data, data privacy, and security concerns. However, model learning under FL is affected by non-i.i.d. data, leading to severe model divergence and reduced performance due to the varying client's data distributions. To address this problem, we propose FedDSS, Federated Data Similarity Selection, a framework that uses a data-similarity approach to select clients, without compromising client data privacy. METHODS: FedDSS comprises a statistical-based data similarity metric, a N-similar-neighbor network, and a network-based selection strategy. We assessed FedDSS' performance against FedAvg's in i.i.d. and non-i.i.d. settings with two public pediatric sepsis datasets (PICD and MIMICIII). Selection fairness was measured using entropy. Simulations were repeated five times to evaluate average loss, true positive rate (TPR), and entropy. RESULTS: In i.i.d setting on PICD, FedDSS achieved a higher TPR starting from the 9th round and surpassing 0.6 three rounds earlier than FedAvg. On MIMICIII, FedDSS's loss decreases significantly from the 13th round, with TPR > 0.8 by the 2nd round, two rounds ahead of FedAvg (at the 4th round). In the non-i.i.d. setting, FedDSS achieved TPR > 0.7 by the 4th and > 0.8 by the 7th round, earlier than FedAvg (at the 5th and 11th rounds). In both settings, FedDSS showed reasonable fairness (entropy of 2.2 and 2.1). CONCLUSION: We demonstrated that FedDSS contributes to improved learning in FL by achieving faster convergence, reaching the desired TPR with fewer communication rounds, and potentially enhancing sepsis prediction (TPR) over FedAvg.

A consultation and work-up diagnosis protocol for a multicancer early detection test: a case series study.

The emergence of multicancer early detection (MCED) tests holds promise for improving early cancer detection and public health outcomes. However, positive MCED test results require confirmation through recommended cancer diagnostic imaging modalities. To address these challenges, we have developed a consultation and work-up protocol for definitive diagnostic results post MCED testing, named SPOT-MAS. Developed through circulating tumor DNA (ctDNA) analysis and in line with professional guidelines and advisory board consensus, this protocol standardizes information to aid general practitioners in accessing, interpreting and managing SPOT-MAS results. Clinical effectiveness is demonstrated through a series of identified cancer cases. Our research indicates that the protocol could empower healthcare professionals to confidently interpret circulating tumor DNA test results for 5 common types of cancer, thereby facilitating the clinical integration of MCED tests.

New tests can now screen for multiple types of cancer early, offering hope for better health outcomes. If one of these tests shows a positive result, doctors need to confirm it with imaging tests. We have developed a guide to help doctors understand and confirm these results. This guide could help healthcare professionals interpret results for five common types of cancer, making it easier to use these tests in regular medical practice.

Med-MGF: multi-level graph-based framework for handling medical data imbalance and representation.

BACKGROUND: Modeling patient data, particularly electronic health records (EHR), is one of the major focuses of machine learning studies in healthcare, as these records provide clinicians with valuable information that can potentially assist them in disease diagnosis and decision-making. METHODS: In this study, we present a multi-level graph-based framework called MedMGF, which models both patient medical profiles extracted from EHR data and their relationship network of health profiles in a single architecture. The medical profiles consist of several layers of data embedding derived from interval records obtained during hospitalization, and the patient-patient network is created by measuring the similarities between these profiles. We also propose a modification to the Focal Loss (FL) function to improve classification performance in imbalanced datasets without the need to imputate the data. MedMGF's performance was evaluated against several Graphical Convolutional Network (GCN) baseline models implemented with Binary Cross Entropy (BCE), FL, class balancing parameter α , and Synthetic Minority Oversampling Technique (SMOTE). RESULTS: Our proposed framework achieved high classification performance (AUC: 0.8098, ACC: 0.7503, SEN: 0.8750, SPE: 0.7445, NPV: 0.9923, PPV: 0.1367) on an extreme imbalanced pediatric sepsis dataset (n=3,014, imbalance ratio of 0.047). It yielded a classification improvement of 3.81% for AUC, 15% for SEN compared to the baseline GCN+ α FL (AUC: 0.7717, ACC: 0.8144, SEN: 0.7250, SPE: 0.8185, PPV: 0.1559, NPV: 0.9847), and an improvement of 5.88% in AUC and 22.5% compared to GCN+FL+SMOTE (AUC: 0.7510, ACC: 0.8431, SEN: 0.6500, SPE: 0.8520, PPV: 0.1688, NPV: 0.9814). It also showed a classification improvement of 3.86% for AUC, 15% for SEN compared to the baseline GCN+ α BCE (AUC: 0.7712, ACC: 0.8133, SEN: 0.7250, SPE: 0.8173, PPV: 0.1551, NPV: 0.9847), and an improvement of 14.33% in AUC and 27.5% in comparison to GCN+BCE+SMOTE (AUC: 0.6665, ACC: 0.7271, SEN: 0.6000, SPE: 0.7329, PPV: 0.0941, NPV: 0.9754). CONCLUSION: When compared to all baseline models, MedMGF achieved the highest SEN and AUC results, demonstrating the potential for several healthcare applications.

Multiple Transcriptomic Analyses Explore Potential Synaptic Biomarker Rabphilin-3A for Alzheimer's Disease.

Alzheimer's disease (AD) is a prevalent neurodegenerative disorder afflicting the elderly population worldwide. The identification of potential gene candidates for AD holds promises for diagnostic biomarkers and therapeutic targets. Employing a comprehensive strategy, this study integrated transcriptomic data from diverse data sources, including microarray and single-cell datasets from blood and tissue samples, enabling a detailed exploration of gene expression dynamics. Through this thorough investigation, 19 notable candidate genes were found with consistent expression changes across both blood and tissue datasets, suggesting their potential as biomarkers for AD. In addition, single cell sequencing analysis further highlighted their specific expression in excitatory and inhibitory neurons, the primary functional units in the brain, underscoring their relevance to AD pathology. Moreover, the functional enrichment analysis revealed that three of the candidate genes were downregulated in synaptic signaling pathway. Further validation experiments significantly showed reduced levels of rabphilin-3A (RPH3A) in 3xTg-AD model mice, implying its role in disease pathogenesis. Given its role in neurotransmitter exocytosis and synaptic function, further investigation into RPH3A and its interactions with neurotrophic proteins may provide valuable insights into the complex molecular mechanisms underlying synaptic dysfunction in AD.

Leukocyte-associated immunoglobulin-like receptor 1 (LAIR1) is reduced with preeclampsia and small for gestational aged fetuses.

Leukocyte-associated immunoglobulin-like receptor 1 (LAIR1) is an inhibitory receptor expressed on immune cells. We evaluated LAIR1 in placentas from preeclamptic or small for gestational age (SGA) pregnancies, and placental explant model (1 % O2, IL6 and TNFα, or control). LAIR1 mRNA was reduced in placentas from preeclamptic (p < 0.0001, n = 78) and SGA (p < 0.0001, n = 32) pregnancies. LAIR1 protein expression was reduced in placentas from preeclampsia (p < 0.0001, n = 43) and SGA (p = 0.009, n = 10) pregnancies. Hypoxia (1 % O2) reduced LAIR1 mRNA expression in placental explants (p = 0.008). These findings suggest hypoxia modulates LAIR1 expression in the placenta.

A study on the antioxidant, anti-inflammatory, and xanthine oxidase inhibitory activity of the Artemisia vulgaris L. extract and its fractions.

ETHNOPHARMACOLOGICAL RELEVANCE: Vietnamese people use mugwort (Artemisia vulgaris L.) to treat arthritis and gout. Our previous research shows that mugwort contains flavonoids, and its extract possesses antibacterial and anti-inflammatory activities. However, no publications have been on the xanthine oxidase inhibitory activity of mugwort and acute anti-inflammatory activity in vivo. AIM OF THE STUDY: The study aimed to verify the antioxidant, xanthine oxidase inhibitory, and anti-inflammatory capabilities of mugwort extract in vitro and in vivo, isolate phyto-compounds from potential bioactive fractions, and then evaluate their potential in inhibiting xanthine oxidase. METHODS: According to established methods, the extract and the active flavonoids were obtained using different chromatographic techniques. DPPH, ABTS, reducing power, and H2O2 elimination were used to evaluate antioxidant activity. The model of LPS-induced RAW264.7 cells was used to measure the inhibition of NO production. The carrageenan-induced paw oedema model was used to assess acute inflammation in mice. In vitro, xanthine oxidase inhibition assay was applied to investigate the effects of extract/compounds on uric acid production. Chemical structures were identified by spectral analysis. RESULTS: The assessment of the acute inflammatory model in mice revealed that both the 96% ethanol and the 50% ethanol extracts significantly decreased oedema in the mice's feet following carrageenan-induced inflammation. 96% ethanol extract exhibited a better reduction in oedema at the low dose. The analysis revealed that the ethyl acetate fraction had the highest levels of total polyphenols and flavonoids. Additionally, this fraction demonstrated significant antioxidant activity in various assays, such as DPPH, ABTS, reducing power, and H2O2 removal. Furthermore, it displayed the most potent inhibition of xanthine oxidase, an anti-inflammatory activity. Five phytochemicals were isolated and determined from the active fraction such as luteolin (1), rutin (2), apigenin (3), myricetin (4), and quercetin (5). Except for rutin, the other compounds demonstrated the ability to inhibit effective xanthine oxidase compared to standard (allopurinol). Moreover, quercetin (5) inhibited NO production (IC50 21.87 µM). CONCLUSION: The results indicate that extracts from A. vulgaris effectively suppressed the activity of xanthine oxidase and exhibited antioxidant and anti-inflammatory properties, potentially leading to a reduction in the production of uric acid in the body and eliminating ROS. The study identified mugwort extract and bioactive compounds derived from Artemisia vulgaris, specifically luteolin, apigenin, and quercetin, as promising xanthine oxidase inhibitors. These findings suggest that further development of these compounds is warranted. At the same time, the above results also strengthen the use of mugwort to treat gout disease in Vietnam.

Beyond black-box models: explainable AI for embryo ploidy prediction and patient-centric consultation.

PURPOSE: To determine if an explainable artificial intelligence (XAI) model enhances the accuracy and transparency of predicting embryo ploidy status based on embryonic characteristics and clinical data. METHODS: This retrospective study utilized a dataset of 1908 blastocyst embryos. The dataset includes ploidy status, morphokinetic features, morphology grades, and 11 clinical variables. Six machine learning (ML) models including Random Forest (RF), Linear Discriminant Analysis (LDA), Logistic Regression (LR), Support Vector Machine (SVM), AdaBoost (ADA), and Light Gradient-Boosting Machine (LGBM) were trained to predict ploidy status probabilities across three distinct datasets: high-grade embryos (HGE, n = 1107), low-grade embryos (LGE, n = 364), and all-grade embryos (AGE, n = 1471). The model's performance was interpreted using XAI, including SHapley Additive exPlanations (SHAP) and Local Interpretable Model-agnostic Explanations (LIME) techniques. RESULTS: The mean maternal age was 38.5 ± 3.85 years. The Random Forest (RF) model exhibited superior performance compared to the other five ML models, achieving an accuracy of 0.749 and an AUC of 0.808 for AGE. In the external test set, the RF model achieved an accuracy of 0.714 and an AUC of 0.750 (95% CI, 0.702-0.796). SHAP's feature impact analysis highlighted that maternal age, paternal age, time to blastocyst (tB), and day 5 morphology grade significantly impacted the predictive model. In addition, LIME offered specific case-ploidy prediction probabilities, revealing the model's assigned values for each variable within a finite range. CONCLUSION: The model highlights the potential of using XAI algorithms to enhance ploidy prediction, optimize embryo selection as patient-centric consultation, and provides reliability and transparent insights into the decision-making process.

Initiator cell death event induced by SARS-CoV-2 in the human airway epithelium.

Virus-induced cell death is a key contributor to COVID-19 pathology. Cell death induced by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is well studied in myeloid cells but less in its primary host cell type, angiotensin-converting enzyme 2 (ACE2)-expressing human airway epithelia (HAE). SARS-CoV-2 induces apoptosis, necroptosis, and pyroptosis in HAE organotypic cultures. Single-cell and limiting-dilution analysis revealed that necroptosis is the primary cell death event in infected cells, whereas uninfected bystanders undergo apoptosis, and pyroptosis occurs later during infection. Mechanistically, necroptosis is induced by viral Z-RNA binding to Z-DNA-binding protein 1 (ZBP1) in HAE and lung tissues from patients with COVID-19. The Delta (B.1.617.2) variant, which causes more severe disease than Omicron (B1.1.529) in humans, is associated with orders of magnitude-greater Z-RNA/ZBP1 interactions, necroptosis, and disease severity in animal models. Thus, Delta induces robust ZBP1-mediated necroptosis and more disease severity.

Trophoblast Side-Population Markers are Dysregulated in Preeclampsia and Fetal Growth Restriction.

Dysregulated progenitor cell populations may contribute to poor placental development and placental insufficiency pathogenesis. Side-population cells possess progenitor properties. Recent human trophoblast side-population isolation identified enrichment of 8 specific genes (CXCL8, ELL2, GATA6, HK2, HLA-DPB1, INTS6, SERPINE3 and UPP1) (Gamage et al. 2020, Stem Cell Rev Rep). We characterised these trophoblast side-population markers in human placenta and in placental insufficiency disorders: preeclampsia and fetal growth restriction (FGR). Trophoblast side-population markers localised to mononuclear trophoblasts lining the placental villous basement membrane in preterm control, preeclamptic and FGR placental sections (n = 3, panel of 3 markers/serial section). Analysis of single-cell transcriptomics of an organoid human trophoblast stem cell (hTSC) to extravillous trophoblast (EVT) differentiation model (Shannon et al. 2022, Development) identified that all side-population genes were enriched in mononuclear trophoblast and trophoblasts committed to differentiation under hTSC culture conditions. In vitro validation via 96 h time course hTSC differentiation to EVTs or syncytiotrophoblasts (n = 5) demonstrated ELL2 and HK2 increased with differentiation (p < 0.0024, p < 0.0039 respectively). CXCL8 and HLA-DPB1 were downregulated (p < 0.030, p < 0.011 respectively). GATA6 and INTS6 increased with EVT differentiation only, and UPP1 reduced with syncytialisation. SERPINE3 was undetectable. Trophoblast side-population marker mRNA was measured in human placentas (< 34-weeks' gestation; n = 78 preeclampsia, n = 30 FGR, and n = 18 gestation-matched controls). ELL2, HK2 and CXCL8 were elevated in preeclamptic (p = 0.0006, p < 0.0001, p = 0.0335 respectively) and FGR placentas (p = 0.0065, p < 0.0001, p = 0.0001 respectively) versus controls. Placental GATA6 was reduced in pregnancies with preeclampsia and FGR (p = 0.0014, p = 0.0146 respectively). Placental INTS6 was reduced with FGR only (p < 0.0001). This study identified the localisation of a unique trophoblast subset enriched for side-population markers. Aberrant expression of some side-population markers may indicate disruptions to unique trophoblast subtypes in placental insufficiency.

Mammographic Texture versus Conventional Cumulus Measure of Density in Breast Cancer Risk Prediction: A Literature Review.

Mammographic textures show promise as breast cancer risk predictors, distinct from mammographic density. Yet, there is a lack of comprehensive evidence to determine the relative strengths as risk predictor of textures and density and the reliability of texture-based measures. We searched the PubMed database for research published up to November 2023, which assessed breast cancer risk associations [odds ratios (OR)] with texture-based measures and percent mammographic density (PMD), and their discrimination [area under the receiver operating characteristics curve (AUC)], using same datasets. Of 11 publications, for textures, six found stronger associations (P < 0.05) with 11% to 508% increases on the log scale by study, and four found weaker associations (P < 0.05) with 14% to 100% decreases, compared with PMD. Risk associations remained significant when fitting textures and PMD together. Eleven of 17 publications found greater AUCs for textures than PMD (P < 0.05); increases were 0.04 to 0.25 by study. Discrimination from PMD and these textures jointly was significantly higher than from PMD alone (P < 0.05). Therefore, different textures could capture distinct breast cancer risk information, partially independent of mammographic density, suggesting their joint role in breast cancer risk prediction. Some textures could outperform mammographic density for predicting breast cancer risk. However, obtaining reliable texture-based measures necessitates addressing various issues. Collaboration of researchers from diverse fields could be beneficial for advancing this complex field.

Prognostic value of exercise longitudinal right ventricular free wall strain in patients with sickle cell disease.

Longitudinal right ventricular free wall strain (RVFWS) has been identified as an independent prognostic marker in patients with pulmonary hypertension. Little is known however about the prognostic value of RVFWS in patients with sickle cell (SC) disease, particularly during exercise. We therefore examined the prognostic significance of RVFWS both at rest and with exercise in patients with SC disease and normal resting systolic pulmonary artery pressure (SPAP). Consecutive patients with SC disease referred for bicycle ergometer stress echocardiography (SE) were enrolled ftom July 2019 to January 2021. All patients had measurable tricuspid regurgitation velocity (TRV). Conventional echocardiography parameters, left ventricular global longitudinal strain (LVGLS), RVFWS, and ventriculoarterial coupling indices (TAPSE/SPAP and RVFWS/SPAP) were assessed at rest and peak exercise. Repeat SE was performed at a median follow-up of 2 years. The cohort consisted of 87 patients (mean age was 31 ± 11 years, 66% females). All patients had normal resting TRV < 2.8 m/s, RVFWS and LVGLS at baseline. There were 23 (26%) patients who had peak stress RVFWS < 20%. They had higher resting and peak stress TRV and SPAP, but lower resting and peak stress TAPSE/SPAP, RVFWS/SPAP, and LVGLS as well as lower peak stress cardiac output when compared to patients with peak stress RVFWS ≥ 20% (p < 0.05). Patients with baseline peak stress RVFWS < 20% had a significant decrease in exercise performance at follow-up (7.5 ± 2.7 min at baseline vs. 5.5 ± 2.8 min at follow-up, p < 0.001). In the multivariate analysis, baseline peak stress RVFWS was the only independent predictor of poorer exercise performance at follow-up [odds ratio 8.2 (1.2, 56.0), p = 0.033]. Among patients with SC disease who underwent bicycle ergometer SE, a decreased baseline value of RVFWS at peak stress predicted poorer exercise time at follow-up.

Pituitary Suppression with Gonadotropin-Releasing Hormone Agonist Prior to Artificial Endometrial Preparation in Frozen-Thawed Embryo Transfer Cycles: A Systematic Review and Meta-Analysis of Different Protocols and Infertile Populations.

This study investigates the effect of GnRHa pretreatment on pregnancy outcomes in artificial endometrial preparation for frozen-thawed embryo transfer (AC-FET) cycles. A systematic review of English language studies published before 1 September 2022, was conducted, excluding conference papers and preprints. Forty-one studies involving 43,021 participants were analyzed using meta-analysis, with a sensitivity analysis ensuring result robustness. The study found that GnRHa pretreatment generally improved the clinical pregnancy rate (CPR), implantation rate (IR), and live birth rate (LBR). However, discrepancies existed between randomized controlled trials (RCTs) and observational studies; RCTs showed no significant differences in outcomes for GnRHa-treated cycles. Depot GnRHa protocols outperformed daily regimens in LBR. Extended GnRHa pretreatment (two to five cycles) significantly improved CPR and IR compared to shorter treatment. Women with polycystic ovary syndrome (PCOS) saw substantial benefits from GnRHa pretreatment, including improved CPR and LBR and reduced miscarriage rates. In contrast, no significant benefits were observed in women with regular menstruation. More rigorous research is needed to solidify these findings.

Association of breast cancer with quantitative mammographic density measures for women receiving contrast-enhanced mammography.

Women with high mammographic density have an increased risk of breast cancer. They may be offered contrast-enhanced mammography to improve breast cancer screening performance. Using a cohort of women receiving contrast-enhanced mammography, we evaluated whether conventional and modified mammographic density measures were associated with breast cancer. Sixty-six patients with newly diagnosed unilateral breast cancer were frequency matched on the basis of age to 133 cancer-free control individuals. On low-energy craniocaudal contrast-enhanced mammograms (equivalent to standard mammograms), we measured quantitative mammographic density using CUMULUS software at the conventional intensity threshold ("Cumulus") and higher-than-conventional thresholds ("Altocumulus," "Cirrocumulus"). The measures were standardized to enable estimation of odds ratio per adjusted standard deviation (OPERA). In multivariable logistic regression of case-control status, only the highest-intensity measure (Cirrocumulus) was statistically significantly associated with breast cancer (OPERA = 1.40, 95% confidence interval = 1.04 to 1.89). Conventional Cumulus did not contribute to model fit. For women receiving contrast-enhanced mammography, Cirrocumulus mammographic density may better predict breast cancer than conventional quantitative mammographic density.

The impacts of telemedicine on assisted reproduction: a systematic review and meta-analysis.

Telemedicine is being applied in assisted reproduction technology (ART) to provide remote consultations, monitoring and support for patients. This study aimed to evaluate the potential advantages of telemedicine in ART treatment in the form of virtual consultations. Studies in which patients were using telemedicine during ART treatment were identified from four scientific databases (PudMed, EMBASE, Scopus, Web of Science). The success of fertility treatments was compared between telemedicine and in-office care, and patient satisfaction with ART through telemedicine was assessed. Eleven studies, comprising 4697 patients, were identified. Quality assessment (Joanna Briggs Institute Critical Appraisal and revised Cochrane risk-of-bias tools) revealed an acceptable risk of bias for both randomized controlled trials and observational studies. Using a fixed-effects model, telemedicine was comparable to in-person care regarding the pregnancy rate achieved (odds ratio 1.02, 95% confidence intervals 0.83-1.26, P = 0.83). A Q-test suggested that all the included studies were homogeneous. Patients who received telemedicine during fertility treatment reported a high level of satisfaction (91%, 95% confidence intervals 80-96%). Egger's test confirmed that no publication bias was found. Telemedicine could serve as a complementary tool during fertility treatment to facilitate patients' satisfaction and overcome some practical problems without compromising treatment outcomes. Future studies should continue exploring the potential applications of telemedicine in assisted reproduction.

Causation and familial confounding as explanations for the associations of polygenic risk scores with breast cancer: Evidence from innovative ICE FALCON and ICE CRISTAL analyses.

A polygenic risk score (PRS) combines the associations of multiple genetic variants that could be due to direct causal effects, indirect genetic effects, or other sources of familial confounding. We have developed new approaches to assess evidence for and against causation by using family data for pairs of relatives (Inference about Causation from Examination of FAmiliaL CONfounding [ICE FALCON]) or measures of family history (Inference about Causation from Examining Changes in Regression coefficients and Innovative STatistical AnaLyses [ICE CRISTAL]). Inference is made from the changes in regression coefficients of relatives' PRSs or PRS and family history before and after adjusting for each other. We applied these approaches to two breast cancer PRSs and multiple studies and found that (a) for breast cancer diagnosed at a young age, for example, <50 years, there was no evidence that the PRSs were causal, while (b) for breast cancer diagnosed at later ages, there was consistent evidence for causation explaining increasing amounts of the PRS-disease association. The genetic variants in the PRS might be in linkage disequilibrium with truly causal variants and not causal themselves. These PRSs cause minimal heritability of breast cancer at younger ages. There is also evidence for nongenetic factors shared by first-degree relatives that explain breast cancer familial aggregation. Familial associations are not necessarily due to genes, and genetic associations are not necessarily causal.

Breast and bowel cancers diagnosed in people 'too young to have cancer': A blueprint for research using family and twin studies.

Young breast and bowel cancers (e.g., those diagnosed before age 40 or 50 years) have far greater morbidity and mortality in terms of years of life lost, and are increasing in incidence, but have been less studied. For breast and bowel cancers, the familial relative risks, and therefore the familial variances in age-specific log(incidence), are much greater at younger ages, but little of these familial variances has been explained. Studies of families and twins can address questions not easily answered by studies of unrelated individuals alone. We describe existing and emerging family and twin data that can provide special opportunities for discovery. We present designs and statistical analyses, including novel ideas such as the VALID (Variance in Age-specific Log Incidence Decomposition) model for causes of variation in risk, the DEPTH (DEPendency of association on the number of Top Hits) and other approaches to analyse genome-wide association study data, and the within-pair, ICE FALCON (Inference about Causation from Examining FAmiliaL CONfounding) and ICE CRISTAL (Inference about Causation from Examining Changes in Regression coefficients and Innovative STatistical AnaLysis) approaches to causation and familial confounding. Example applications to breast and colorectal cancer are presented. Motivated by the availability of the resources of the Breast and Colon Cancer Family Registries, we also present some ideas for future studies that could be applied to, and compared with, cancers diagnosed at older ages and address the challenges posed by young breast and bowel cancers.

In Vivo Fluticasone Absorption in Surgical Patients.

BACKGROUND: Intranasal corticosteroids (INCS) are a treatment mainstay of chronic rhinosinusitis and allergic rhinitis. Current computational models demonstrate that >90% of INCS drug deposition occurs on the head of the inferior turbinate and nasal valve, rather than the actual sinuses. These models do not consider mucociliary clearance which propels mucus posteriorly, nor do they consider the absorption of the drug. The purpose of this study is to better understand the exact anatomical location where INCS are absorbed. METHODS: Patients with chronic rhinosinusitis and allergic rhinitis taking fluticasone pre-operatively who were scheduled for functional endoscopic sinus surgery and inferior turbinate reduction, respectively, were recruited. Intra-operative tissue samples were obtained from predetermined locations within the sinonasal cavity. Mass spectrometry was then used to quantify the amount of absorption in each specific anatomic location to determine the largest amount of absorption. RESULTS: Eighteen patients were included in our study. The greatest fluticasone absorption levels across the sinonasal anatomy were at the anterior inferior turbinate (5.7 ngl/mL), ethmoid sinus, (4.4 ng/mL), posterior inferior turbinate (3.7 ng/mL), maxillary sinus (1.3 ng/mL), and the sphenoethmoidal recess (0.72 ng/mL) respectively. Absorption was significantly higher in revision surgery compared to surgically naïve patients. CONCLUSIONS: Computation fluid dynamic models of the nasal passage are useful models to help predict intranasal particle flow. However, these models do not incorporate or consider the important mucociliary clearance system, leading to absorption of fluticasone throughout the sinonasal cavity far beyond that predicted by these models. LEVEL OF EVIDENCE: 2 Laryngoscope, 134:1551-1555, 2024.