Development of an artificial intelligence model for predicting the likelihood of human embryo euploidy based on blastocyst images from multiple imaging systems during IVF.

STUDY QUESTION: Can an artificial intelligence (AI) model predict human embryo ploidy status using static images captured by optical light microscopy? SUMMARY ANSWER: Results demonstrated predictive accuracy for embryo euploidy and showed a significant correlation between AI score and euploidy rate, based on assessment of images of blastocysts at Day 5 after IVF. WHAT IS KNOWN ALREADY: Euploid embryos displaying the normal human chromosomal complement of 46 chromosomes are preferentially selected for transfer over aneuploid embryos (abnormal complement), as they are associated with improved clinical outcomes. Currently, evaluation of embryo genetic status is most commonly performed by preimplantation genetic testing for aneuploidy (PGT-A), which involves embryo biopsy and genetic testing. The potential for embryo damage during biopsy, and the non-uniform nature of aneuploid cells in mosaic embryos, has prompted investigation of additional, non-invasive, whole embryo methods for evaluation of embryo genetic status. STUDY DESIGN, SIZE, DURATION: A total of 15 192 blastocyst-stage embryo images with associated clinical outcomes were provided by 10 different IVF clinics in the USA, India, Spain and Malaysia. The majority of data were retrospective, with two additional prospectively collected blind datasets provided by IVF clinics using the genetics AI model in clinical practice. Of these images, a total of 5050 images of embryos on Day 5 of in vitro culture were used for the development of the AI model. These Day 5 images were provided for 2438 consecutively treated women who had undergone IVF procedures in the USA between 2011 and 2020. The remaining images were used for evaluation of performance in different settings, or otherwise excluded for not matching the inclusion criteria. PARTICIPANTS/MATERIALS, SETTING, METHODS: The genetics AI model was trained using static 2-dimensional optical light microscope images of Day 5 blastocysts with linked genetic metadata obtained from PGT-A. The endpoint was ploidy status (euploid or aneuploid) based on PGT-A results. Predictive accuracy was determined by evaluating sensitivity (correct prediction of euploid), specificity (correct prediction of aneuploid) and overall accuracy. The Matthew correlation coefficient and receiver-operating characteristic curves and precision-recall curves (including AUC values), were also determined. Performance was also evaluated using correlation analyses and simulated cohort studies to evaluate ranking ability for euploid enrichment. MAIN RESULTS AND THE ROLE OF CHANCE: Overall accuracy for the prediction of euploidy on a blind test dataset was 65.3%, with a sensitivity of 74.6%. When the blind test dataset was cleansed of poor quality and mislabeled images, overall accuracy increased to 77.4%. This performance may be relevant to clinical situations where confounding factors, such as variability in PGT-A testing, have been accounted for. There was a significant positive correlation between AI score and the proportion of euploid embryos, with very high scoring embryos (9.0-10.0) twice as likely to be euploid than the lowest-scoring embryos (0.0-2.4). When using the genetics AI model to rank embryos in a cohort, the probability of the top-ranked embryo being euploid was 82.4%, which was 26.4% more effective than using random ranking, and ∼13-19% more effective than using the Gardner score. The probability increased to 97.0% when considering the likelihood of one of the top two ranked embryos being euploid, and the probability of both top two ranked embryos being euploid was 66.4%. Additional analyses showed that the AI model generalized well to different patient demographics and could also be used for the evaluation of Day 6 embryos and for images taken using multiple time-lapse systems. Results suggested that the AI model could potentially be used to differentiate mosaic embryos based on the level of mosaicism. LIMITATIONS, REASONS FOR CAUTION: While the current investigation was performed using both retrospectively and prospectively collected data, it will be important to continue to evaluate real-world use of the genetics AI model. The endpoint described was euploidy based on the clinical outcome of PGT-A results only, so predictive accuracy for genetic status in utero or at birth was not evaluated. Rebiopsy studies of embryos using a range of PGT-A methods indicated a degree of variability in PGT-A results, which must be considered when interpreting the performance of the AI model. WIDER IMPLICATIONS OF THE FINDINGS: These findings collectively support the use of this genetics AI model for the evaluation of embryo ploidy status in a clinical setting. Results can be used to aid in prioritizing and enriching for embryos that are likely to be euploid for multiple clinical purposes, including selection for transfer in the absence of alternative genetic testing methods, selection for cryopreservation for future use or selection for further confirmatory PGT-A testing, as required. STUDY FUNDING/COMPETING INTEREST(S): Life Whisperer Diagnostics is a wholly owned subsidiary of the parent company, Presagen Holdings Pty Ltd. Funding for the study was provided by Presagen with grant funding received from the South Australian Government: Research, Commercialisation, and Startup Fund (RCSF). 'In kind' support and embryology expertise to guide algorithm development were provided by Ovation Fertility. 'In kind' support in terms of computational resources provided through the Amazon Web Services (AWS) Activate Program. J.M.M.H., D.P. and M.P. are co-owners of Life Whisperer and Presagen. S.M.D., M.A.D. and T.V.N. are employees or former employees of Life Whisperer. S.M.D, J.M.M.H, M.A.D, T.V.N., D.P. and M.P. are listed as inventors of patents relating to this work, and also have stock options in the parent company Presagen. M.V. sits on the advisory board for the global distributor of the technology described in this study and also received support for attending meetings. TRIAL REGISTRATION NUMBER: N/A.

Development of an artificial intelligence-based assessment model for prediction of embryo viability using static images captured by optical light microscopy during IVF.

STUDY QUESTION: Can an artificial intelligence (AI)-based model predict human embryo viability using images captured by optical light microscopy? SUMMARY ANSWER: We have combined computer vision image processing methods and deep learning techniques to create the non-invasive Life Whisperer AI model for robust prediction of embryo viability, as measured by clinical pregnancy outcome, using single static images of Day 5 blastocysts obtained from standard optical light microscope systems. WHAT IS KNOWN ALREADY: Embryo selection following IVF is a critical factor in determining the success of ensuing pregnancy. Traditional morphokinetic grading by trained embryologists can be subjective and variable, and other complementary techniques, such as time-lapse imaging, require costly equipment and have not reliably demonstrated predictive ability for the endpoint of clinical pregnancy. AI methods are being investigated as a promising means for improving embryo selection and predicting implantation and pregnancy outcomes. STUDY DESIGN, SIZE, DURATION: These studies involved analysis of retrospectively collected data including standard optical light microscope images and clinical outcomes of 8886 embryos from 11 different IVF clinics, across three different countries, between 2011 and 2018. PARTICIPANTS/MATERIALS, SETTING, METHODS: The AI-based model was trained using static two-dimensional optical light microscope images with known clinical pregnancy outcome as measured by fetal heartbeat to provide a confidence score for prediction of pregnancy. Predictive accuracy was determined by evaluating sensitivity, specificity and overall weighted accuracy, and was visualized using histograms of the distributions of predictions. Comparison to embryologists' predictive accuracy was performed using a binary classification approach and a 5-band ranking comparison. MAIN RESULTS AND THE ROLE OF CHANCE: The Life Whisperer AI model showed a sensitivity of 70.1% for viable embryos while maintaining a specificity of 60.5% for non-viable embryos across three independent blind test sets from different clinics. The weighted overall accuracy in each blind test set was >63%, with a combined accuracy of 64.3% across both viable and non-viable embryos, demonstrating model robustness and generalizability beyond the result expected from chance. Distributions of predictions showed clear separation of correctly and incorrectly classified embryos. Binary comparison of viable/non-viable embryo classification demonstrated an improvement of 24.7% over embryologists' accuracy (P = 0.047, n = 2, Student's t test), and 5-band ranking comparison demonstrated an improvement of 42.0% over embryologists (P = 0.028, n = 2, Student's t test). LIMITATIONS, REASONS FOR CAUTION: The AI model developed here is limited to analysis of Day 5 embryos; therefore, further evaluation or modification of the model is needed to incorporate information from different time points. The endpoint described is clinical pregnancy as measured by fetal heartbeat, and this does not indicate the probability of live birth. The current investigation was performed with retrospectively collected data, and hence it will be of importance to collect data prospectively to assess real-world use of the AI model. WIDER IMPLICATIONS OF THE FINDINGS: These studies demonstrated an improved predictive ability for evaluation of embryo viability when compared with embryologists' traditional morphokinetic grading methods. The superior accuracy of the Life Whisperer AI model could lead to improved pregnancy success rates in IVF when used in a clinical setting. It could also potentially assist in standardization of embryo selection methods across multiple clinical environments, while eliminating the need for complex time-lapse imaging equipment. Finally, the cloud-based software application used to apply the Life Whisperer AI model in clinical practice makes it broadly applicable and globally scalable to IVF clinics worldwide. STUDY FUNDING/COMPETING INTEREST(S): Life Whisperer Diagnostics, Pty Ltd is a wholly owned subsidiary of the parent company, Presagen Pty Ltd. Funding for the study was provided by Presagen with grant funding received from the South Australian Government: Research, Commercialisation and Startup Fund (RCSF). 'In kind' support and embryology expertise to guide algorithm development were provided by Ovation Fertility. J.M.M.H., D.P. and M.P. are co-owners of Life Whisperer and Presagen. Presagen has filed a provisional patent for the technology described in this manuscript (52985P pending). A.P.M. owns stock in Life Whisperer, and S.M.D., A.J., T.N. and A.P.M. are employees of Life Whisperer.

Structural and functional characterization of TesB from Yersinia pestis reveals a unique octameric arrangement of hotdog domains.

Acyl-CoA thioesterases catalyse the hydrolysis of the thioester bonds present within a wide range of acyl-CoA substrates, releasing free CoASH and the corresponding fatty-acyl conjugate. The TesB-type thioesterases are members of the TE4 thioesterase family, one of 25 thioesterase enzyme families characterized to date, and contain two fused hotdog domains in both prokaryote and eukaryote homologues. Only two structures have been elucidated within this enzyme family, and much of the current understanding of the TesB thioesterases has been based on the Escherichia coli structure. Yersinia pestis, a highly virulent bacterium, encodes only one TesB-type thioesterase in its genome; here, the structural and functional characterization of this enzyme are reported, revealing unique elements both within the protomer and quaternary arrangements of the hotdog domains which have not been reported previously in any thioesterase family. The quaternary structure, confirmed using a range of structural and biophysical techniques including crystallography, small-angle X-ray scattering, analytical ultracentrifugation and size-exclusion chromatography, exhibits a unique octameric arrangement of hotdog domains. Interestingly, the same biological unit appears to be present in both TesB structures solved to date, and is likely to be a conserved and distinguishing feature of TesB-type thioesterases. Analysis of the Y. pestis TesB thioesterase activity revealed a strong preference for octanoyl-CoA and this is supported by structural analysis of the active site. Overall, the results provide novel insights into the structure of TesB thioesterases which are likely to be conserved and distinguishing features of the TE4 thioesterase family.

Structural and dynamic requirements for optimal activity of the essential bacterial enzyme dihydrodipicolinate synthase.

Dihydrodipicolinate synthase (DHDPS) is an essential enzyme involved in the lysine biosynthesis pathway. DHDPS from E. coli is a homotetramer consisting of a 'dimer of dimers', with the catalytic residues found at the tight-dimer interface. Crystallographic and biophysical evidence suggest that the dimers associate to stabilise the active site configuration, and mutation of a central dimer-dimer interface residue destabilises the tetramer, thus increasing the flexibility and reducing catalytic efficiency and substrate specificity. This has led to the hypothesis that the tetramer evolved to optimise the dynamics within the tight-dimer. In order to gain insights into DHDPS flexibility and its relationship to quaternary structure and function, we performed comparative Molecular Dynamics simulation studies of native tetrameric and dimeric forms of DHDPS from E. coli and also the native dimeric form from methicillin-resistant Staphylococcus aureus (MRSA). These reveal a striking contrast between the dynamics of tetrameric and dimeric forms. Whereas the E. coli DHDPS tetramer is relatively rigid, both the E. coli and MRSA DHDPS dimers display high flexibility, resulting in monomer reorientation within the dimer and increased flexibility at the tight-dimer interface. The mutant E. coli DHDPS dimer exhibits disorder within its active site with deformation of critical catalytic residues and removal of key hydrogen bonds that render it inactive, whereas the similarly flexible MRSA DHDPS dimer maintains its catalytic geometry and is thus fully functional. Our data support the hypothesis that in both bacterial species optimal activity is achieved by fine tuning protein dynamics in different ways: E. coli DHDPS buttresses together two dimers, whereas MRSA dampens the motion using an extended tight-dimer interface.

Efficient automated error detection in medical data using deep-learning and label-clustering.

Medical datasets inherently contain errors from subjective or inaccurate test results, or from confounding biological complexities. It is difficult for medical experts to detect these elusive errors manually, due to lack of contextual information, limiting data privacy regulations, and the sheer scale of data to be reviewed. Current methods for training robust artificial intelligence (AI) models on data containing mislabeled examples generally fall into one of several categories-attempting to improve the robustness of the model architecture, the regularization techniques used, the loss function used during training, or selecting a subset of data that contains cleaner labels. This last category requires the ability to efficiently detect errors either prior to or during training, either relabeling them or removing them completely. More recent progress in error detection has focused on using multi-network learning to minimize deleterious effects of errors on training, however, using many neural networks to reach a consensus on which data should be removed can be computationally intensive and inefficient. In this work, a deep-learning based algorithm was used in conjunction with a label-clustering approach to automate error detection. For dataset with synthetic label flips added, these errors were identified with an accuracy of up to 85%, while requiring up to 93% less computing resources to complete compared to a previous model consensus approach developed previously. The resulting trained AI models exhibited greater training stability and up to a 45% improvement in accuracy, from 69 to over 99% compared to the consensus approach, at least 10% improvement on using noise-robust loss functions in a binary classification problem, and a 51% improvement for multi-class classification. These results indicate that practical, automated a priori detection of errors in medical data is possible, without human oversight.

A novel decentralized federated learning approach to train on globally distributed, poor quality, and protected private medical data.

Training on multiple diverse data sources is critical to ensure unbiased and generalizable AI. In healthcare, data privacy laws prohibit data from being moved outside the country of origin, preventing global medical datasets being centralized for AI training. Data-centric, cross-silo federated learning represents a pathway forward for training on distributed medical datasets. Existing approaches typically require updates to a training model to be transferred to a central server, potentially breaching data privacy laws unless the updates are sufficiently disguised or abstracted to prevent reconstruction of the dataset. Here we present a completely decentralized federated learning approach, using knowledge distillation, ensuring data privacy and protection. Each node operates independently without needing to access external data. AI accuracy using this approach is found to be comparable to centralized training, and when nodes comprise poor-quality data, which is common in healthcare, AI accuracy can exceed the performance of traditional centralized training.

Impact of the reduction of environmental and equipment contamination on vancomycin-resistant enterococcus rates.

More than 1,500 perirectal swab cultures and 552 environmental and equipment cultures were collected during the study period. Enterococcus faecium was the most frequent species isolated, being responsible for 71% of the positive cultures. Fifty infections were documented, with bloodstream infections (18, 36%) being the most frequent, followed by urinary tract infection (15, 30%). An educational intervention was given to 136 healthcare workers (HCWs), and a questionnaire regarding vancomycin-resistant enterococcus (VRE) transmission was also performed pre- and post-intervention. Overall, 858 opportunities of patient care were evaluated. The compliance with contact precautions did not improve; however, in general, the proportion of correct answers regarding VRE increased significantly when comparing pre- and post-intervention periods (p < 0.05). On the other hand, the proportion of environmental and equipment contaminated by VRE decreased significantly from pre- (23.2%) to post-intervention (8.2%) (p < 0.001) and was associated with a significant decrease in VRE infection from 7.7 to 1.9 when comparing the pre- and post-intervention periods. The use of vancomycin (defined daily dose [DDD]) did not change significantly over the study period (p = 0.970), and the use of teicoplanin increased (p < 0.001). Seventy-six percent of E. faecium belong to type and subtype A by pulsed-field gel electrophoresis (PFGE). This predominant type was found in the environment and caused colonization and infection. In conclusion, the present study showed that reduction of the proportion of environmental and equipment contamination was associated with a decrease of colonization and infection due to VRE, and that the strategy to control VRE dissemination should be based on local problems.

Automated detection of poor-quality data: case studies in healthcare.

The detection and removal of poor-quality data in a training set is crucial to achieve high-performing AI models. In healthcare, data can be inherently poor-quality due to uncertainty or subjectivity, but as is often the case, the requirement for data privacy restricts AI practitioners from accessing raw training data, meaning manual visual verification of private patient data is not possible. Here we describe a novel method for automated identification of poor-quality data, called Untrainable Data Cleansing. This method is shown to have numerous benefits including protection of private patient data; improvement in AI generalizability; reduction in time, cost, and data needed for training; all while offering a truer reporting of AI performance itself. Additionally, results show that Untrainable Data Cleansing could be useful as a triage tool to identify difficult clinical cases that may warrant in-depth evaluation or additional testing to support a diagnosis.

Characterisation of dihydrodipicolinate synthase (DHDPS) from Bacillus anthracis.

Bacillus anthracis is a Gram-positive spore-forming bacterium that is the causative agent of anthrax disease. The use of anthrax as a bioweapon has increased pressure for the development of an effective treatment. Dihydrodipicolinate synthase (DHDPS) catalyses the first committed step in the biosynthetic pathway yielding two essential bacterial metabolites, meso-diaminopimelate (DAP) and (S)-lysine. DHDPS is therefore a potential antibiotic target, as microbes require either lysine or DAP as a component of the cell wall. This paper is the first biochemical description of DHDPS from B. anthracis. Enzyme kinetic analyses, isothermal titration calorimetry (ITC), mass spectrometry and differential scanning fluorimetry (DSF) were used to characterise B. anthracis DHDPS and compare it with the well characterised Escherichia coli enzyme. B. anthracis DHDPS exhibited different kinetic behaviour compared with E. coli DHDPS, in particular, substrate inhibition by (S)-aspartate semi-aldehyde was observed for the B. anthracis enzyme (K(si(ASA))=5.4+/-0.5 mM), but not for the E. coli enzyme. As predicted from a comparison of the X-ray crystal structures, the B. anthracis enzyme was not inhibited by lysine. The B. anthracis enzyme was thermally stabilised by the first substrate, pyruvate, to a greater extent than its E. coli counterpart, but has a weaker affinity for pyruvate based on enzyme kinetics and ITC studies. This characterisation will provide useful information for the design of inhibitors as new antibiotics targeting B. anthracis.

Toxicological assessment and developmental abnormalities induced by butylparaben and ethylparaben exposure in zebrafish early-life stages.

Toxicological effects of butylparaben (BuP) and ethylparaben (EtP) on zebrafish (Danio rerio) early-life stages are not well established. The present study evaluated, using zebrafish embryos and larvae, the toxicity of BuP and EtP through benchmark dose (BMD) approach. BuP was more toxic than EtP to zebrafish larvae. In fact, Lethal Concentration 50 (LC50) values at 96 h post-fertilization (hpf) for BuP and EtP were 2.34 mg/L and 20.86 mg/L, respectively. Indeed, BMD confidence interval (lower bound (BMDL) - upper bound (BMDU) was 0.91-1.92 mg/L for BuP and 10.8-17.4 mg/L for EtP. Zebrafish embryos exposed to 1 mg/L, 2.5 mg/L of BuP and 5 mg/L, 10 mg/L, 20 mg/L, 30 mg/L of EtP showed several developmental abnormalities and teratological effects compared to negative control. Exposed zebrafish developed reduced heartbeat, reduction in blood circulation, blood stasis, pericardial edema, deformed notochord and misshaped yolk sac. Embryos exposed to the highest concentrations of the chemicals (2.5 mg/L of BuP, 10 mg/L, 20 mg/L and 30 mg/L of EtP) showed the developmental abnormalities at 48 hpf while those treated with 1 mg/L of BuP and 10 mg/L of EtP reported behavioral changes at 72 hpf, including trembling of head, pectoral fins and spinal cord. This research identified the lethal and sublethal effects of BuP and EtP in zebrafish early-life stages and could be helpful to elucidate the developmental pathways of toxicity of parabens.

Embryotoxicity of methylparaben to zebrafish (Danio rerio) early-life stages.

Methylparaben (MeP) is widely used as preservative in personal care products, food commodities and pharmaceuticals due to its antimicrobial properties. Its widespread use resulted in the contamination of aquatic environment and raised concerns about the potential adverse effects on human health, especially in the developing organisms. The aim of the present study was to evaluate the embryotoxicity of MeP in zebrafish early-life stages applying the benchmark-dose (BMD) methodology to Fish embryo acute toxicity (FET) tests-OECD guideline 236. Toxic effects were studied by daily evaluation of lethal endpoints, hatching rate and sublethal alterations. Zebrafish fertilized eggs were exposed until 96 h post fertilization (hpf) to five concentrations of MeP: 1 mg/L, 10 mg/L, 30 mg/L, 60 mg/L and 80 mg/L. The lethal concentration 50 (LC 50) was 72.67 mg/L. Indeed, BMD confidence interval (lower bound, BMDL-upper bound, BMDU) was 40.8-57.4 mg/L for lethal endpoints and 16-26.5 mg/L for toxicity index, that includes both lethal and sublethal alterations. Zebrafish embryos exposed to MeP developed sublethal alterations including pericardial edema, yolk edema, blood stasis, reduction in blood circulation, reduced heartbeat and notochord curvature. The number of embryos exposed to the highest concentrations of MeP that reported sublethal alterations increased between 24hpf and 48 hpf-72 hpf-96 hpf. Only zebrafish larvae treated with 30 mg/L of MeP showed behavioural changes. This study highlighted the detrimental effects of MeP on zebrafish early-life stages with attention to its developmental toxicity.

Quantitative analysis of oxysterols in zebrafish embryos by HPLC-MS/MS.

Zebrafish is an in vivo model used in toxicology to estimate the effects of xenobiotics and their teratogenic consequences. The knowledge of the oxysterols profile in zebrafish, during early embryonic stages, provides important information on the role and biological function of these molecules. This work reports the development and validation of a LC-MS/MS method for the determination of 7 different oxysterols in zebrafish embryos. Sample was treated with a combination of liquid/liquid extraction (LLE) followed by micro solid phase extraction (µSPE) clean-up in order to remove matrix interference and obtain a suitable enrichment factor of the analytes. The method was validated on 2 different embryos growing stages, 3-4 and 24 h post fertilization (hpf), as slight differences in terms of recovery and matrix effect were shown. The validation results provided good accuracy (bias ≤17%; 20% at LOQ) and repeatability (≤15%; ≤19% at LOQ), with low LOQs in the range 22 and 65 pg on 100 embryos sample, without any analyte derivatization, demonstrating the suitability of this analytical method as a useful tool to understand the correlation between oxysterols profile and developmental abnormalities induced by xenobiotic exposure.

Vaccinia virus anti-apoptotic F1L is a novel Bcl-2-like domain-swapped dimer that binds a highly selective subset of BH3-containing death ligands.

Apoptosis is an important part of the host's defense mechanism for eliminating invading pathogens. Some viruses express proteins homologous in sequence and function to mammalian pro-survival Bcl-2 proteins. Anti-apoptotic F1L expressed by vaccinia virus is essential for survival of infected cells, but it bears no discernable sequence homology to proteins other than its immediate orthologues in related pox viruses. Here we report that the crystal structure of F1L reveals a Bcl-2-like fold with an unusual N-terminal extension. The protein forms a novel domain-swapped dimer in which the alpha1 helix is the exchanged domain. Binding studies reveal an atypical BH3-binding profile, with sub-micromolar affinity only for the BH3 peptide of pro-apoptotic Bim and low micromolar affinity for the BH3 peptides of Bak and Bax. This binding interaction is sensitive to F1L mutations within the predicted canonical BH3-binding groove, suggesting parallels between how vaccinia virus F1L and myxoma virus M11L bind BH3 domains. Structural comparison of F1L with other Bcl-2 family members reveals a novel sequence signature that redefines the BH4 domain as a structural motif present in both pro- and anti-apoptotic Bcl-2 members, including viral Bcl-2-like proteins.

Mutants of pertussis toxin suitable for vaccine development.

Immunization with chemically detoxified pertussis toxin can prevent severe whooping cough with an efficacy similar to that of the cellular pertussis vaccine, which normally gives unwanted side effects. To avoid the reversion to toxicity and the loss of immunogenicity that may follow chemical treatment of pertussis toxin, inactive toxins were constructed by genetic manipulation. A number of genetically engineered alleles of the pertussis toxin genes, constructed by replacing either one or two key amino acids within the enzymatically active S1 subunit, were introduced into the chromosome of strains of Bordetella pertussis, B. parapertussis, and B. bronchiseptica. These strains produce mutant pertussis toxin molecules that are nontoxic and immunogenic and that protect mice from the intracerebral challenge with virulent Bordetella pertussis. Such molecules are ideal for the development of new and safer vaccines against whooping cough.

Frontal sinus fractures: a review of 132 cases.

BACKGROUND: Frontal sinus fractures peculiarity is that a wrong treatment not only could it encompass functional or aesthetical problems but also more dangerous complications: the proximity of the frontal bone to the brain, on a side, and to the nasolacrimal duct, on the other side, and therefore to the nasal cavity, lead the traumatisms occurring within this region to be at high risk of infections. MATERIALS AND METHODS: We report our experience on 132 cases of frontal sinus fracture treated from 1989 to 2005 and to present the surgical techniques performed as well as to compare the complications they reported over time to the International Literature data. 101 patients (76.5%) were treated in order to reduce and contain the isolated fractures involving the frontal sinus anterior wall, the patients presenting associated fractures of the frontal sinus anterior and posterior wall were 28 (21.2%), while the cases reporting isolated fractures of the nasolacrimal duct were 3. RESULTS: Our patients underwent follow-ups from 1 to 16 years long. We subdivided the complications found in our group into infectious and functional so that the incidence of the complications related to the sites and the treatment performed according to the specific case could be better assessed. In conclusion, the infectious and functional complications found were treated with a multidisciplinary study considering the approach to the craniofacial traumatized person is subordinated to the co-existence of general and neurological conditions requiring for their resolution different approaches and times.

Polycyclic aromatic hydrocarbons in farmed rainbow trout (Oncorhynchus mykiss) processed by traditional flue gas smoking and by liquid smoke flavourings.

Polycyclic aromatic hydrocarbons (PAHs) were determined by high performance liquid chromatography (HPLC) method with fluorescence detection in rainbow trout fillets processed by traditional flue gas smoking and by liquid smoke flavourings, at low temperature (25 degrees C for 3h). Raw fillets were also investigated as control group. The following compounds, anthracene, fluoranthene, pyrene, benz(a)anthracene, chrysene, benzo(b)fluoranthene, benzo(k)fluoranthene and benzo(ghi)perylene were detected in all samples and no significant difference (p>0.05) was found neither between fresh and processed samples nor between the two different smoking techniques, except for chrysene and benzo(b)fluoranthene. The results show that PAHs found in rainbow trout fillets could be considered as a consequence of environmental pollution and the mild smoking process described in the present study did not affect their concentrations.

Influence of mycotoxins on spontaneous contraction in myometrial strips of prepubertal lamb.

The effects of mycotoxin zearalenone and their major metabolites alpha- and beta-zearalenol on spontaneous contractions in isolated lamb uterine smooth muscle were examined. The study was carried out on 20 female prepubertal lambs aged between 45 and 50 days. Myometrial strips were set up in two isolated organ baths (10ml) at 37 degrees C and were exposed to increasing concentrations (10(-11)M-10(-6)M) of these mycoestrogens and results were compared with the effect, at the same concentrations, of natural estrogen 17beta-estradiol. Our findings suggest that mycotoxins and 17beta-estradiol, at nanomolar concentrations, rapidly enhance phasic spontaneous smooth muscle contraction. In particular, zearalenone increases the uterine activity similarly to 17beta-estradiol. On the contrary, its metabolite alpha-zearalenol significantly inhibits myometrial contractility.

A four-gene LincRNA expression signature predicts risk in multiple cohorts of acute myeloid leukemia patients.

Prognostic gene expression signatures have been proposed as clinical tools to clarify therapeutic options in acute myeloid leukemia (AML). However, these signatures rely on measuring large numbers of genes and often perform poorly when applied to independent cohorts or those with older patients. Long intergenic non-coding RNAs (lincRNAs) are emerging as important regulators of cell identity and oncogenesis, but knowledge of their utility as prognostic markers in AML is limited. Here we analyze transcriptomic data from multiple cohorts of clinically annotated AML patients and report that (i) microarrays designed for coding gene expression can be repurposed to yield robust lincRNA expression data, (ii) some lincRNA genes are located in close proximity to hematopoietic coding genes and show strong expression correlations in AML, (iii) lincRNA gene expression patterns distinguish cytogenetic and molecular subtypes of AML, (iv) lincRNA signatures composed of three or four genes are independent predictors of clinical outcome and further dichotomize survival in European Leukemia Net (ELN) risk groups and (v) an analytical tool based on logistic regression analysis of quantitative PCR measurement of four lincRNA genes (LINC4) can be used to determine risk in AML.

CED-4 forms a 2 : 2 heterotetrameric complex with CED-9 until specifically displaced by EGL-1 or CED-13.

The pathway to cell death in Caenorhabditis elegans is well established. In cells undergoing apoptosis, the Bcl-2 homology domain 3 (BH3)-only protein EGL-1 binds to CED-9 at the mitochondrial membrane to cause the release of CED-4, which oligomerises and facilitates the activation of the caspase CED-3. However, despite many studies, the biophysical features of the CED-4/CED-9 complex have not been fully characterised. Here, we report the purification of a soluble and stable 2 : 2 heterotetrameric complex formed by recombinant CED-4 and CED-9 coexpressed in bacteria. Consistent with previous studies, synthetic peptides corresponding to the BH3 domains of worm BH3-only proteins (EGL-1, CED-13) dissociate CED-4 from CED-9, but not from the gain-of-function CED-9 (G169E) mutant. Surprisingly, the ability of worm BH3 domains to dissociate CED-4 was specific since mammalian BH3-only proteins could not do so.