External validation of anti-Müllerian hormone based prediction of live birth in assisted conception

<p>Background - Chronological age and oocyte yield are independent determinants of live birth in assisted conception. Anti-Müllerian hormone (AMH) is strongly associated with oocyte yield after controlled ovarian stimulation. We have previously assessed the ability of AMH and age to independently predict live birth in an Italian assisted conception cohort. Herein we report the external validation of the nomogram in 822 UK first in vitro fertilization (IVF) cycles.</p> <p>Methods - Retrospective cohort consisting of 822 patients undergoing their first IVF treatment cycle at Glasgow Centre for Reproductive Medicine. Analyses were restricted to women aged between 25 and 42 years of age. All women had an AMH measured prior to commencing their first IVF cycle. The performance of the model was assessed; discrimination by the area under the receiver operator curve (ROCAUC) and model calibration by the predicted probability versus observed probability.</p> <p>Results - Live births occurred in 29.4% of the cohort. The observed and predicted outcomes showed no evidence of miscalibration (p = 0.188). The ROCAUC was 0.64 (95% CI: 0.60, 0.68), suggesting moderate and similar discrimination to the original model. The ROCAUC for a continuous model of age and AMH was 0.65 (95% CI 0.61, 0.69), suggesting that the original categories of AMH were appropriate.</p> <p>Conclusions - We confirm by external validation that AMH and age are independent predictors of live birth. Although the confidence intervals for each category are wide, our results support the assessment of AMH in larger cohorts with detailed baseline phenotyping for live birth prediction.</p&gt

Robotic Surgery and Deep Infiltrating Endometriosis Treatment: The State of Art

Objective: Surgical treatment of endometriosis, when indicated, has demonstrated to be effective in reducing painful symptoms and improve quality of life of patients affected with endometriosis. The minimally invasive approach via laparoscopy is the preferred method when compared with laparotomy but in the last two decades another minimally invasive approach has become available, the robotically assisted laparoscopic surgery. Robotic technology is widely used in different surgical branches, such as general surgery and urology. Moreover, the use of robotic surgery is already accepted for different gynecological procedures either for benign and for oncological diseases. The advantages of robotic surgery such as improve dexterity of movements, avoided tremor, increased magnification of 3-dimensional vision seem strategic in the context of a complex surgery as is deep endometriosis eradication. However, to date there is no unanimous consensus on whether robotically assisted procedures are a valid and safe alternative to laparoscopy in the treatment of endometriosis. Mechanism: In this narrative review we analyze the available literature assessesing the robotic treatment of all types of endometriosis and specifically deep infiltrating endometriosis, compared to the outcomes of conventional laparoscopy. Findings in Brief: Indeed, the evidence of safety and effectiveness of robotically assisted laparoscopy in endometriosis treatment is strong and almost unanimous. There is no clear superiority of one approach to the other but robotic-related advantages and future prospective are promising to be able to improve operative outcomes, reduce surgeon’s fatigue and provide a technology easy to implement with a fast learning curve. Conclusions: Robotic technology applied to laparoscopy in the treatment of endometriosis could be seen as an effective and safe alternative to the conventional laparoscopic treatment

Biological responses to trauma and the development of intrusive memories: An analog study with the trauma film paradigm.

Evidence suggests that previous trauma reduces the cortisol response to subsequent stressors. We examined the relation of this response to intrusive memory, and the potential moderating roles of sympathetic reactions. Pre-existing trauma-related factors and the cardiac defense response were assessed before 58 healthy participants viewed a trauma film. Salivary cortisol and alpha-amylase (sAA) were collected pre-, peri- and post-film. Intrusive memories about the film were recorded for a week. Cortisol increased whereas sAA decreased after the film. Those with more recent traumatic experiences and greater subclinical PTSD symptoms had lower cortisol concentration post-film. Lower cortisol levels predicted greater vividness of intrusions. Positive correlations between cortisol and the frequency of intrusion were only present among individuals with more sympathetic activations. These findings suggest the contribution of insufficient cortisol secretion to over-consolidation of traumatic memory, and highlight the variation attributable to individual differences and different memory characteristics

Cardiovascular and psychological responses to voluntary recall of trauma in posttraumatic stress disorder

Voluntary recall of trauma is a key element in exposure-based psychotherapies and can trigger spontaneous dissociative responses such as flashbacks, depersonalisation, and derealisation. In order to examine the associations between cardiovascular and psychological responses to voluntary recollection of trauma, individuals with PTSD recalled a traumatic memory. Heart rate and heart rate variability were recorded continuously and the episodes when different forms of dissociation were experienced during the recall were identified. A significant increase in parasympathetic activity was found during trauma recall, with greater parasympathetic dominance being indicative of greater state depersonalisation/derealisation. Whereas overall decreases in heart rate during trauma recall were associated with increased fear and perceived threat, flashbacks were accompanied by short-term increases in heart rate. These findings demonstrate different types of cardiovascular responses associated with different psychological experiences during trauma recall. Future research directions were discussed

Outcomes after Surgery for Spinal Metastasis of Colorectal Origin: Case Series

Study DesignRetrospective study.PurposeThe aim of this study was to evaluate the clinical management and outcomes of patients who underwent surgical intervention for metastatic colorectal adenocarcinoma of the spine.Overview of LiteratureGastrointestinal (GI) cancer metastasis to the spine are relatively rare and represent later manifestations of the disease. Studies and reports on the outcomes of patients who undergo surgery for spinal metastasis of GI origin are scarce.MethodsA retrospective chart review of all patients who underwent surgery for spinal metastasis of colorectal origin was performed. Four patients were identified. Patient characteristics, outcomes, and survival were analyzed.ResultsTwo patients experienced improvement in pain or myelopathic symptoms. Although the mean survival was 15.3 months, this average included a patient still living at 57.1 months. The mean survival was just 1.3 months for the 3 patients who expired.ConclusionsIn certain cases, symptomatic improvement with prolonged survival is possible after surgery for metastatic spinal lesions of colorectal origin; however, survival is poor in the majority of cases

Heart rate, startle response, and intrusive trauma memories

Abstract The current study adopted the trauma film paradigm to examine potential moderators affecting heart rate (HR) as an indicator of peritraumatic psychological states and as a predictor of intrusive memories. We replicated previous findings that perifilm HR decreases predicted the development of intrusive images and further showed this effect to be specific to images rather than thoughts, and to detail rather than gist recognition memory. Moreover, a group of individuals showing both an atypical sudden reduction in HR after a startle stimulus and higher trait dissociation was identified. Only among these individuals was lower perifilm HR found to indicate higher state dissociation, fear, and anxiety, along with reduced vividness of intrusions. The current findings emphasize how peritraumatic physiological responses relate to emotional reactions and intrusive memory. The moderating role of individual difference in stress defense style was highlighted

Heart rate, startle response, and intrusive trauma memories

The current study adopted the trauma film paradigm to examine potential moderators affecting heart rate (HR) as an indicator of peritraumatic psychological states and as a predictor of intrusive memories. We replicated previous findings that perifilm HR decreases predicted the development of intrusive images and further showed this effect to be specific to images rather than thoughts, and to detail rather than gist recognition memory. Moreover, a group of individuals showing both an atypical sudden reduction in HR after a startle stimulus and higher trait dissociation was identified. Only among these individuals was lower perifilm HR found to indicate higher state dissociation, fear, and anxiety, along with reduced vividness of intrusions. The current findings emphasize how peritraumatic physiological responses relate to emotional reactions and intrusive memory. The moderating role of individual difference in stress defense style was highlighted

Endocannabinoid and steroid analysis in infant and adult nails by LC-MS/MS

A common method to quantify chronic stress is the analysis of stress markers in keratinized matrices such as hair or nail. In this study, we aimed to validate a sensitive liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for the combined quantification of steroid hormones and endocannabinoids (eCBs) in the keratinized matrix nail. Furthermore, we aimed to investigate the suitability of the nail matrix for the detection of these stress markers in a pilot study. An LC-MS/MS method was used for the simultaneous identification and quantification of four eCBs (2-arachidonoylglycerol (2-AG), anandamide (AEA), oleoylethanolamide (OEA), palmitoylethanolamide (PEA)) and five steroid hormones (cortisol, cortisone, androstenedione, progesterone, testosterone) in human nails using a surrogate analyte method for each analyte. The method was validated in terms of selectivity, response factor, linearity, limit of quantification (LOQ), precision, accuracy, matrix effect, recovery, robustness, and autosampler stability. Nail samples were extracted for 1 h with methanol following a clean-up with a fully automated supported liquid extraction (SLE). The influence of nail weight on the quantification was investigated by using 0.5-20 mg of nail sample. As a proof of concept, nail samples (N = 57) were analyzed from a cohort representing newborns (1 month old), children (between 1 and 10 years), and adults (up to 43 years). It could be shown that the established workflow using a 1 hour extraction and clean-up by SLE was very robust and resulted in a short sample preparation time. The LC-MS/MS method was successfully validated. Matrix effects with ion enhancement occurred mainly for 2-AG. Sample weights below 5 mg showed variations in quantification for some analytes. Certain analytes such as PEA and progesterone could be accurately quantified at a sample weight lower than 5 mg. This is the first study where steroids and eCBs could be simultaneously detected and quantified in infant and adult nails. These results show that nails may serve as an alternative keratinized matrix (compared to hair) for the retrospective monitoring of cumulative eCB and steroid hormone levels. The combined assessment of eCBs and steroids from nails could provide a new approach to gain new insights into stress exposure in newborns and adults

An interpretable machine learning approach to multimodal stress detection in a simulated office environment

Background and objective: Work-related stress affects a large part of today’s workforce and is known to have detrimental effects on physical and mental health. Continuous and unobtrusive stress detection may help prevent and reduce stress by providing personalised feedback and allowing for the development of just-in-time adaptive health interventions for stress management. Previous studies on stress detection in work environments have often struggled to adequately reflect real-world conditions in controlled laboratory experiments. To close this gap, in this paper, we present a machine learning methodology for stress detection based on multimodal data collected from unobtrusive sources in an experiment simulating a realistic group office environment (N=90). Methods: We derive mouse, keyboard and heart rate variability features to detect three levels of perceived stress, valence and arousal with support vector machines, random forests and gradient boosting models using 10-fold cross-validation. We interpret the contributions of features to the model predictions with SHapley Additive exPlanations (SHAP) value plots. Results: The gradient boosting models based on mouse and keyboard features obtained the highest average F1 scores of 0.625, 0.631 and 0.775 for the multiclass prediction of perceived stress, arousal and valence, respectively. Our results indicate that the combination of mouse and keyboard features may be better suited to detect stress in office environments than heart rate variability, despite physiological signal-based stress detection being more established in theory and research. The analysis of SHAP value plots shows that specific mouse movement and typing behaviours may characterise different levels of stress. Conclusions: Our study fills different methodological gaps in the research on the automated detection of stress in office environments, such as approximating real-life conditions in a laboratory and combining physiological and behavioural data sources. Implications for field studies on personalised, interpretable ML-based systems for the real-time detection of stress in real office environments are also discussed

A multi-band AGN-SFG classifier for extragalactic radio surveys using machine learning

Extragalactic radio continuum surveys play an increasingly more important role in galaxy evolution and cosmology studies. While radio galaxies and radio quasars dominate at the bright end, star-forming galaxies (SFGs) and radio-quiet Active Galactic Nuclei (AGNs) are more common at fainter flux densities. Our aim is to develop a machine learning classifier that can efficiently and reliably separate AGNs and SFGs in radio continuum surveys. We perform supervised classification of SFGs vs AGNs using the Light Gradient Boosting Machine (LGBM) on three LOFAR Deep Fields (Lockman Hole, Bootes and ELAIS-N1), which benefit from a wide range of high-quality multi-wavelength data and classification labels derived from extensive spectral energy distribution (SED) analyses. Our trained model has a precision of 0.92(0.01) and a recall of 0.87(0.02) for SFGs. For AGNs, the model has slightly worse performance, with a precision of 0.87(0.02) and recall of 0.78(0.02). These results demonstrate that our trained model can successfully reproduce the classification labels derived from detailed SED analysis. The model performance decreases towards higher redshifts, mainly due to smaller training sample sizes. To make the classifier more adaptable to other radio galaxy surveys, we also investigate how our classifier performs with a poorer multi-wavelength sampling of the SED. In particular, we find that the far-infrared (FIR) and radio bands are of great importance. We also find that higher S/N in some photometric bands leads to a significant boost in the model's performance. In addition to using the 150 MHz radio data, our model can also be used with 1.4 GHz radio data. Converting 1.4 GHz to 150 MHz radio data reduces performance by about 4% in precision and 3% in recall. The final trained model is publicly available at https://github.com/Jesper-Karsten/MBASCComment: 14 pages 9 figures Accepted for publication in A&