What sperm parameters effect blastocyst formation and quality during ICSI with severe male infertility.

Sperm-derived genetic material contributes half of the genome to the embryo, hence it's crucial to investigate which sperm parameter influences blastocyst formation in the intracytoplasmic sperm injection (ICSI) cycles with severe male infertility. The retrospective study analyzed 296 ICSI cycles with severe oligoasthenoteratozoospermia (OAT) and 99 ICSI cycles with preimplantation genetic testing for aneuploidy (PGT-A). Following the correlation analysis, data stratifications were performed in the OAT ICSI subgroup. The results showed that the matching blastocyst in the OAT ICSI cycles had inferior sperm parameters. DFI and sperm morphology had an influence on the blastocyst formation rate and the high-quality blastocysts formation rate on Day6, but no significant effect on the blastocyst development on Day 5. The high-quality blastocysts formation rate and ratio of high-quality blastocyst on Day 6 were demonstrably better in the subgroup of the teratozoospermic morphology when DFI was within the normal range. In the case of the normal sperm morphology, no statistically significant difference was found in blastocyst development, although there were numerical differences within different DFI subgroups. It was concluded that the blastocyst quality and development declined with the decreased sperm qualities.

Oxidation Behavior of Pre-Strained Polycrystalline Ni3Al-Based Superalloy.

The harsh service environment of aeroengine hot-end components requires superalloys possessing excellent antioxidant properties. This study investigated the effect of pre-strain on the oxidation behavior of polycrystalline Ni3Al-based superalloys. The growth behaviors of oxidation products were analyzed by scanning electron microscope, transmission electron microscope, X-ray Photoelectron Spectroscopy and Raman spectroscopy. The results indicated that the 5% pre-strained alloys exhibited lower mass gain, shallower oxidation depth and more compact oxide film structures compared to the original alloy. This is mainly attributed to the formation of rapid diffusion paths for Al atoms diffusing to the surface under 5% pre-strain, which promotes the faster formation of protective Al2O3 film while continuing to increase the pre-strain to 25% results in less protective transient oxidation behavior being aggravated due to the increase in dislocation density within the alloy, which prevents the timely formation of the protective Al2O3 film, resulting in uneven oxidation behavior on the alloy.

Exploring the diagnostic value of ultrasound radiomics for neonatal respiratory distress syndrome.

BACKGROUND: Neonatal respiratory distress syndrome (NRDS) is a prevalent cause of respiratory failure and death among newborns, and prompt diagnosis is imperative. Historically, diagnosis of NRDS relied mostly on typical clinical manifestations, chest X-rays, and CT scans. However, recently, ultrasound has emerged as a valuable and preferred tool for aiding NRDS diagnosis. Nevertheless, evaluating lung ultrasound imagery necessitates rigorous training and may be subject to operator-dependent bias, limiting its widespread use. As a result, it is essential to investigate a new, reliable, and operator-independent diagnostic approach that does not require subjective factors or operator expertise. This article aims to explore the diagnostic potential of ultrasound-based radiomics in differentiating NRDS from other non-NRDS lung disease. METHODS: A total of 150 neonatal lung disease cases were consecutively collected from the department of neonatal intensive care unit of the Quanzhou Maternity and Children's Hospital, Fujian Province, from September 2021 to October 2022. Of these patients, 60 were diagnosed with NRDS, whereas 30 were diagnosed with neonatal pneumonia, meconium aspiration syndrome (MAS), and transient tachypnea (TTN). Two ultrasound images with characteristic manifestations of each lung disease were acquired and divided into training (n = 120) and validation cohorts (n = 30) based on the examination date using an 8:2 ratio. The imaging texture features were extracted using PyRadiomics and, after the screening, machine learning models such as random forest (RF), logistic regression (LR), K-nearest neighbors (KNN), support vector machine (SVM), and multilayer perceptron (MLP) were developed to construct an imaging-based diagnostic model. The diagnostic efficacy of each model was analyzed. Lastly, we randomly selected 282 lung ultrasound images and evaluated the diagnostic efficacy disparities between the optimal model and doctors across differing levels of expertise. RESULTS: Twenty-two imaging-based features with the highest weights were selected to construct a predictive model for neonatal respiratory distress syndrome. All models exhibited favorable diagnostic performances. Analysis of the Youden index demonstrated that the RF model had the highest score in both the training (0.99) and validation (0.90) cohorts. Additionally, the calibration curve indicated that the RF model had the best calibration (P = 0.98). When compared to the diagnostic performance of experienced and junior physicians, the RF model had an area under the curve (AUC) of 0.99; however, the values for experienced and junior physicians were 0.98 and 0.85, respectively. The difference in diagnostic efficacy between the RF model and experienced physicians was not statistically significant (P = 0.24), whereas that between the RF model and junior physicians was statistically significant (P < 0.0001). CONCLUSION: The RF model exhibited excellent diagnostic performance in the analysis of texture features based on ultrasound radiomics for diagnosing NRDS.