Molecular insight into the specific enzymatic properties of TREX1 revealing the diverse functions in processing RNA and DNA/RNA hybrids.

In various autoimmune diseases, dysfunctional TREX1 (Three prime Repair Exonuclease 1) leads to accumulation of endogenous single-stranded DNA (ssDNA), double-stranded DNA (dsDNA) and DNA/RNA hybrids in the cytoplasm and triggers immune activation through the cGAS-STING pathway. Although inhibition of TREX1 could be a useful strategy for cancer immunotherapy, profiling cellular functions in terms of its potential substrates is a key step. Particularly important is the functionality of processing DNA/RNA hybrids and RNA substrates. The exonuclease activity measurements conducted here establish that TREX1 can digest both ssRNA and DNA/RNA hybrids but not dsRNA. The newly solved structures of TREX1-RNA product and TREX1-nucleotide complexes show that 2'-OH does not impose steric hindrance or specific interactions for the recognition of RNA. Through all-atom molecular dynamics simulations, we illustrate that the 2'-OH-mediated intra-chain hydrogen bonding in RNA would affect the binding with TREX1 and thereby reduce the exonuclease activity. This notion of higher conformational rigidity in RNA leading TREX1 to exhibit weaker catalytic cleavage is further validated by the binding affinity measurements with various synthetic DNA-RNA junctions. The results of this work thus provide new insights into the mechanism by which TREX1 processes RNA and DNA/RNA hybrids and contribute to the molecular-level understanding of the complex cellular functions of TREX1 as an exonuclease.

Associations between the artificial intelligence scoring system and live birth outcomes in preimplantation genetic testing for aneuploidy cycles.

BACKGROUND: Several studies have demonstrated that iDAScore is more accurate in predicting pregnancy outcomes in cycles without preimplantation genetic testing for aneuploidy (PGT-A) compared to KIDScore and the Gardner criteria. However, the effectiveness of iDAScore in cycles with PGT-A has not been thoroughly investigated. Therefore, this study aims to assess the association between artificial intelligence (AI)-based iDAScore (version 1.0) and pregnancy outcomes in single-embryo transfer (SET) cycles with PGT-A. METHODS: This retrospective study was approved by the Institutional Review Board of Chung Sun Medical University, Taichung, Taiwan. Patients undergoing SET cycles (n = 482) following PGT-A at a single reproductive center between January 2017 and June 2021. The blastocyst morphology and morphokinetics of all embryos were evaluated using a time-lapse system. The blastocysts were ranked based on the scores generated by iDAScore, which were defined as AI scores, or by KIDScore D5 (version 3.2) following the manufacturer's protocols. A single blastocyst without aneuploidy was transferred after examining the embryonic ploidy status using a next-generation sequencing-based PGT-A platform. Logistic regression analysis with generalized estimating equations was conducted to assess whether AI scores are associated with the probability of live birth (LB) while considering confounding factors. RESULTS: Logistic regression analysis revealed that AI score was significantly associated with LB probability (adjusted odds ratio [OR] = 2.037, 95% confidence interval [CI]: 1.632-2.542) when pulsatility index (PI) level and types of chromosomal abnormalities were controlled. Blastocysts were divided into quartiles in accordance with their AI score (group 1: 3.0-7.8; group 2: 7.9-8.6; group 3: 8.7-8.9; and group 4: 9.0-9.5). Group 1 had a lower LB rate (34.6% vs. 59.8-72.3%) and a higher rate of pregnancy loss (26% vs. 4.7-8.9%) compared with the other groups (p < 0.05). The receiver operating characteristic curve analysis verified that the iDAScore had a significant but limited ability to predict LB (area under the curve [AUC] = 0.64); this ability was significantly weaker than that of the combination of iDAScore, type of chromosomal abnormalities, and PI level (AUC = 0.67). In the comparison of the LB groups with the non-LB groups, the AI scores were significantly lower in the non-LB groups, both for euploid (median: 8.6 vs. 8.8) and mosaic (median: 8.0 vs. 8.6) SETs. CONCLUSIONS: Although its predictive ability can be further enhanced, the AI score was significantly associated with LB probability in SET cycles. Euploid or mosaic blastocysts with low AI scores (≤ 7.8) were associated with a lower LB rate, indicating the potential of this annotation-free AI system as a decision-support tool for deselecting embryos with poor pregnancy outcomes following PGT-A.

Investigating developmental characteristics of biopsied blastocysts stratified by mitochondrial copy numbers using time-lapse monitoring.

BACKGROUND: For in vitro fertilization (IVF), mitochondrial DNA (mtDNA) levels in the trophectodermal (TE) cells of biopsied blastocysts have been suggested to be associated with the cells' developmental potential. However, scholars have reached differing opinions regarding the use of mtDNA levels as a reliable biomarker for predicting IVF outcomes. Therefore, this study aims to assess the association of mitochondrial copy number measured by mitoscore associated with embryonic developmental characteristics and ploidy. METHODS: This retrospective study analyzed the developmental characteristics of embryos and mtDNA levels in biopsied trophectodermal cells. The analysis was carried out using time-lapse monitoring and next-generation sequencing from September 2021 to September 2022. Five hundred and fifteen blastocysts were biopsied from 88 patients undergoing IVF who met the inclusion criteria. Embryonic morphokinetics and morphology were evaluated at 118 h after insemination using all recorded images. Blastocysts with appropriate morphology on day 5 or 6 underwent TE biopsy and preimplantation genetic testing for aneuploidy (PGT-A). Statistical analysis involved generalized estimating equations, Pearson's chi-squared test, Fisher's exact test, and Kruskal-Wallis test, with a significance level set at P < 0.05. RESULTS: To examine differences in embryonic characteristics between blastocysts with low versus high mitoscores, the blastocysts were divided into quartiles based on their mitoscore. Regarding morphokinetic characteristics, no significant differences in most developmental kinetics and observed cleavage dysmorphisms were discovered. However, blastocysts in mitoscore group 1 had a longer time for reaching 3-cell stage after tPNf (t3; median: 14.4 h) than did those in mitoscore group 2 (median: 13.8 h) and a longer second cell cycle (CC2; median: 11.7 h) than did blastocysts in mitoscore groups 2 (median: 11.3 h) and 4 (median: 11.4 h; P < 0.05). Moreover, blastocysts in mitoscore group 4 had a lower euploid rate (22.6%) and a higher aneuploid rate (59.1%) than did those in the other mitoscore groups (39.6-49.3% and 30.3-43.2%; P < 0.05). The rate of whole-chromosomal alterations in mitoscore group 4 (63.4%) was higher than that in mitoscore groups 1 (47.3%) and 2 (40.1%; P < 0.05). A multivariate logistic regression model was used to analyze associations between the mitoscore and euploidy of elective blastocysts. After accounting for factors that could potentially affect the outcome, the mitoscore still exhibited a negative association with the likelihood of euploidy (adjusted OR = 0.581, 95% CI: 0.396-0.854; P = 0.006). CONCLUSIONS: Blastocysts with varying levels of mitochondrial DNA, identified through biopsies, displayed similar characteristics in their early preimplantation development as observed through time-lapse imaging. However, the mitochondrial DNA level determined by the mitoscore can be used as a standalone predictor of euploidy.

TIAM2S-positive microglia enhance inflammation and neurotoxicity through soluble ICAM-1-mediated immune priming.

TIAM Rac1-associated GEF 2 short form (TIAM2S) as an oncoprotein alters the immunity of peripheral immune cells to construct an inflammatory tumor microenvironment. However, its role in the activation of microglia, the primary innate immune cells of the brain, and neuroinflammation remains unknown. This study investigated the mechanism underlying TIAM2S shapes immune properties of microglia to facilitate neuron damage. Human microglial clone 3 cell line (HMC3) and human brain samples were applied to determine the presence of TIAM2S in microglia by western blots and double immunostaining. Furthermore, TIAM2S transgenic mice combined with multiple reconstituted primary neuron-glial culture systems and a cytokine array were performed to explore how TIAM2S shaped immune priming of microglia and participated in lipopolysaccharide (LPS)-induced neuron damage. TIAM2S protein was detectable in HMC3 cells and presented in a small portion (~11.1%) of microglia in human brains referred to as TIAM2S-positive microglia. With the property of secreted soluble factor-mediated immune priming, TIAM2S-positive microglia enhanced LPS-induced neuroinflammation and neural damage in vivo and in vitro. The gain- and loss-of-function experiments showed soluble intercellular adhesion molecule-1 (sICAM-1) participated in neurotoxic immune priming of TIAM2S+ microglia. Together, this study demonstrated a novel TIAM2S-positive microglia subpopulation enhances inflammation and neurotoxicity through sICAM-1-mediated immune priming.

Multiple gamma rhythms carry distinct spatial frequency information in primary visual cortex.

Gamma rhythms in many brain regions, including the primary visual cortex (V1), are thought to play a role in information processing. Here, we report a surprising finding of 3 narrowband gamma rhythms in V1 that processed distinct spatial frequency (SF) signals and had different neural origins. The low gamma (LG; 25 to 40 Hz) rhythm was generated at the V1 superficial layer and preferred a higher SF compared with spike activity, whereas both the medium gamma (MG; 40 to 65 Hz), generated at the cortical level, and the high gamma HG; (65 to 85 Hz), originated precortically, preferred lower SF information. Furthermore, compared with the rates of spike activity, the powers of the 3 gammas had better performance in discriminating the edge and surface of simple objects. These findings suggest that gamma rhythms reflect the neural dynamics of neural circuitries that process different SF information in the visual system, which may be crucial for multiplexing SF information and synchronizing different features of an object.

Two-Step Machine Learning Approach for Charge-Transfer Coupling with Structurally Diverse Data.

Electronic coupling is important in determining charge-transfer rates and dynamics. Coupling strength is sensitive to both intermolecular, e.g., orientation or distance, and intramolecular degrees of freedom. Hence, it is challenging to build an accurate machine learning model to predict electronic coupling of molecular pairs, especially for those derived from the amorphous phase, for which intermolecular configurations are much more diverse than those derived from crystals. In this work, we devise a new prediction algorithm that employs two consecutive KRR models. The first model predicts molecular orbitals (MOs) from structural variation for each fragment, and coupling is further predicted by using the overlap integral included in a second model. With our two-step procedure, we achieved mean absolute errors of 0.27 meV for an ethylene dimer and 1.99 meV for a naphthalene pair, much improved accuracy amounting to 14-fold and 3-fold error reductions, respectively. In addition, MOs from the first model can also be the starting point to obtain other quantum chemical properties from atomistic structures. This approach is also compatible with a MO predictor with sufficient accuracy.

Distilling coarse-grained representations of molecular electronic structure with continuously gated message passing.

Bottom-up methods for coarse-grained (CG) molecular modeling are critically needed to establish rigorous links between atomistic reference data and reduced molecular representations. For a target molecule, the ideal reduced CG representation is a function of both the conformational ensemble of the system and the target physical observable(s) to be reproduced at the CG resolution. However, there is an absence of algorithms for selecting CG representations of molecules from which complex properties, including molecular electronic structure, can be accurately modeled. We introduce continuously gated message passing (CGMP), a graph neural network (GNN) method for atomically decomposing molecular electronic structure sampled over conformational ensembles. CGMP integrates 3D-invariant GNNs and a novel gated message passing system to continuously reduce the atomic degrees of freedom accessible for electronic predictions, resulting in a one-shot importance ranking of atoms contributing to a target molecular property. Moreover, CGMP provides the first approach by which to quantify the degeneracy of "good" CG representations conditioned on specific prediction targets, facilitating the development of more transferable CG representations. We further show how CGMP can be used to highlight multiatom correlations, illuminating a path to developing CG electronic Hamiltonians in terms of interpretable collective variables for arbitrarily complex molecules.

WISE: whole-scenario embryo identification using self-supervised learning encoder in IVF.

PURPOSE: To study the effectiveness of whole-scenario embryo identification using a self-supervised learning encoder (WISE) in in vitro fertilization (IVF) on time-lapse, cross-device, and cryo-thawed scenarios. METHODS: WISE was based on the vision transformer (ViT) architecture and masked autoencoders (MAE), a self-supervised learning (SSL) method. To train WISE, we prepared three datasets including the SSL pre-training dataset, the time-lapse identification dataset, and the cross-device identification dataset. To identify whether pairs of images were from the same embryos in different scenarios in the downstream identification tasks, embryo images including time-lapse and microscope images were first pre-processed through object detection, cropping, padding, and resizing, and then fed into WISE to get predictions. RESULTS: WISE could accurately identify embryos in the three scenarios. The accuracy was 99.89% on the time-lapse identification dataset, and 83.55% on the cross-device identification dataset. Besides, we subdivided a cryo-thawed evaluation set from the cross-device test set to have a better estimation of how WISE performs in the real-world, and it reached an accuracy of 82.22%. There were approximately 10% improvements in cross-device and cryo-thawed identification tasks after the SSL method was applied. Besides, WISE demonstrated improvements in the accuracy of 9.5%, 12%, and 18% over embryologists in the three scenarios. CONCLUSION: SSL methods can improve embryo identification accuracy even when dealing with cross-device and cryo-thawed paired images. The study is the first to apply SSL in embryo identification, and the results show the promise of WISE for future application in embryo witnessing.

Leveraging federated learning for boosting data privacy and performance in IVF embryo selection.

PURPOSE: To study the effectiveness of federated learning in in vitro fertilization on embryo evaluation tasks. METHODS: This is a retrospective cohort analysis. Two datasets were used in this study. The ploidy status dataset consisted of 10,065 embryo records, 3760 treatments, and 2479 infertile couples from 5 hospitals. The clinical pregnancy dataset consisted of 4495 embryo records, 4495 treatments, and 3704 infertile couples from 4 hospitals. Federated learning and the gradient boosting decision tree algorithm were utilized for modeling. RESULTS: On the ploidy status dataset, the areas under the receiver operating characteristic curves of our model trained with federated learning were 71.78%, 73.10%, 69.39%, 69.72%, and 73.46% for 5 hospitals respectively, showing an average increase of 2.5% compared to those of our model trained without federated learning. On the clinical pregnancy dataset, the areas under the receiver operating characteristic curves of our model trained with federated learning were 72.03%, 56.77%, 61.63%, and 58.58% for 4 hospitals respectively, showing an average increase of 3.08%. CONCLUSIONS: Federated learning can improve data privacy and data security and meanwhile improve the performance of embryo selection tasks by leveraging data from multiple sources. This study demonstrates the effectiveness of federated learning in embryo evaluation, and the results show the promise for future application.

Association between Serum Glycated Hemoglobin Levels and Female Infertility: A Cross-Sectional Survey and Genetic Approach.

Female infertility affects a significant portion of the population, and recent studies suggest a potential link between glycemic control and reproductive health. This study investigates the association between serum glycated hemoglobin (HbA1c) levels and female infertility, utilizing data from the NHANES 2017-2020 and Mendelian randomization (MR) analysis. A cross-sectional study was conducted with 1578 women aged 20-45 who attempted pregnancy for at least one year. Serum HbA1c levels were analyzed in relation to infertility status, with multivariable logistic regression models adjusting for covariates such as age, body mass index, race/ethnicity, education, marital status, hypertension, and hyperlipidemia. Higher HbA1c levels were significantly associated with increased infertility risk. Each 1% increase in HbA1c was linked to higher odds of infertility (adjusted OR: 1.40, 95% CI: 1.15-1.69, p = 0.003). HbA1c levels ≥ 6.5% showed the strongest association. MR analysis employed single-nucleotide polymorphisms as instrumental variables to assess the causal relationship between HbA1c and infertility, confirming a causal relationship between higher genetically predicted HbA1c levels and infertility (OR: 1.82, 95% CI: 1.33-2.49, p = 0.00018). Sensitivity analyses supported the robustness of these findings. Elevated HbA1c levels are associated with an increased risk of female infertility, suggesting the importance of glycemic control in reproductive health management.

Zfra Overrides WWOX in Suppressing the Progression of Neurodegeneration.

We reported that a 31-amino-acid Zfra protein (zinc finger-like protein that regulates apoptosis) blocks neurodegeneration and cancer growth. Zfra binds WW domain-containing oxidoreductase (WWOX) to both N- and C-termini, which leads to accelerated WWOX degradation. WWOX limits the progression of neurodegeneration such as Alzheimer's disease (AD) by binding tau and tau-hyperphosphorylating enzymes. Similarly, Zfra binds many protein targets and accelerates their degradation independently of ubiquitination. Furthermore, Zfra4-10 peptide strongly prevents the progression of AD-like symptoms in triple-transgenic (3xTg) mice during aging. Zfra4-10 peptide restores memory loss in 9-month-old 3xTg mice by blocking the aggregation of a protein cascade, including TPC6AΔ, TIAF1, and SH3GLB2, by causing aggregation of tau and amyloid ß. Zfra4-10 also suppresses inflammatory NF-κB activation. Zfra-activated Hyal-2+ CD3- CD19- Z cells in the spleen, via Hyal-2/WWOX/Smad4 signaling, are potent in cancer suppression. In this perspective review, we provide mechanistic insights regarding how Zfra overrides WWOX to induce cancer suppression and retard AD progression via Z cells.

Transcriptomic Analysis of Vitrified-Warmed vs. Fresh Mouse Blastocysts: Cryo-Induced Physiological Mechanisms and Implantation Impact.

Blastocyst vitrification has significantly improved embryo transfer methods, leading to higher implantation success rates and better pregnancy outcomes in subsequent frozen embryo transfer cycles. This study aimed to simulate the transcriptional changes caused by vitrifying human blastocysts using mouse blastocysts as a model and to further investigate these changes' effects. Utilizing a human vitrification protocol, we implanted both vitrified and fresh embryos into mice. We observed the implantation success rates and performed transcriptomic analysis on the blastocysts. To validate the results from messenger RNA sequencing, we conducted reverse transcriptase-quantitative polymerase chain reaction (RT-qPCR) to measure the expression levels of specific genes. Based on mRNA profiling, we predicted the microRNAs responsible for the regulation and used qPCR basic microRNA assays for validation. Our observations revealed a higher implantation success rate for vitrified embryos than fresh embryos. Transcriptomic analysis showed that vitrified-warmed blastocysts exhibited differentially expressed genes (DEGs) primarily associated with thermogenesis, chemical carcinogenesis-reactive oxygen species, oxidative phosphorylation, immune response, and MAPK-related signaling pathways. RT-qPCR confirmed increased expression of genes such as Cdk6 and Nfat2, and decreased expression of genes such as Dkk3 and Mapk10. Additionally, gene-microRNA interaction predictions and microRNA expression analysis identified twelve microRNAs with expression patterns consistent with the predicted results, suggesting potential roles in uterine epithelial cell adhesion, trophectoderm development, invasive capacity, and immune responses. Our findings suggest that vitrification induces transcriptomic changes in mouse blastocysts, and even small changes in gene expression can enhance implantation success. These results highlight the importance of understanding the molecular mechanisms underlying vitrification to optimize embryo transfer techniques and improve pregnancy outcomes.

MFI2 upregulation promotes malignant progression through EGF/FAK signaling in oral cavity squamous cell carcinoma.

Oral squamous cell carcinoma (OSCC) is the predominant histological type of the head and neck squamous cell carcinoma (HNSCC). By comparing the differentially expressed genes (DEGs) in OSCC-TCGA patients with copy number variations (CNVs) that we identify in OSCC-OncoScan dataset, we herein identified 37 dysregulated candidate genes. Among these potential candidate genes, 26 have been previously reported as dysregulated proteins or genes in HNSCC. Among 11 novel candidates, the overall survival analysis revealed that melanotransferrin (MFI2) is the most significant prognostic molecular in OSCC-TCGA patients. Another independent Taiwanese cohort confirmed that higher MFI2 transcript levels were significantly associated with poor prognosis. Mechanistically, we found that knockdown of MFI2 reduced cell viability, migration and invasion via modulating EGF/FAK signaling in OSCC cells. Collectively, our results support a mechanistic understanding of a novel role for MFI2 in promoting cell invasiveness in OSCC.

Anterior gradient 2 induces resistance to sorafenib via endoplasmic reticulum stress regulation in hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) accounts for almost 80% of all liver cancer cases and is the sixth most common cancer and the second most common cause of cancer-related death worldwide. The survival rate of sorafenib-treated advanced HCC patients is still unsatisfactory. Unfortunately, no useful biomarkers have been verified to predict sorafenib efficacy in HCC. RESULTS: We assessed a sorafenib resistance-related microarray dataset and found that anterior gradient 2 (AGR2) is highly associated with overall and recurrence-free survival and with several clinical parameters in HCC. However, the mechanisms underlying the role of AGR2 in sorafenib resistance and HCC progression remain unknown. We found that sorafenib induces AGR2 secretion via posttranslational modification and that AGR2 plays a critical role in sorafenib-regulated cell viability and endoplasmic reticulum (ER) stress and induces apoptosis in sorafenib-sensitive cells. In sorafenib-sensitive cells, sorafenib downregulates intracellular AGR2 and conversely induces AGR2 secretion, which suppresses its regulation of ER stress and cell survival. In contrast, AGR2 is highly intracellularly expressed in sorafenib-resistant cells, which supports ER homeostasis and cell survival. We suggest that AGR2 regulates ER stress to influence HCC progression and sorafenib resistance. CONCLUSIONS: This is the first study to report that AGR2 can modulate ER homeostasis via the IRE1α-XBP1 cascade to regulate HCC progression and sorafenib resistance. Elucidation of the predictive value of AGR2 and its molecular and cellular mechanisms in sorafenib resistance could provide additional options for HCC treatment.

APP and DYRK1A regulate axonal and synaptic vesicle protein networks and mediate Alzheimer's pathology in trisomy 21 neurons.

Trisomy 21 (T21) causes Down syndrome and an early-onset form of Alzheimer's disease (AD). Here, we used human induced pluripotent stem cells (hiPSCs) along with CRISPR-Cas9 gene editing to investigate the contribution of chromosome 21 candidate genes to AD-relevant neuronal phenotypes. We utilized a direct neuronal differentiation protocol to bypass neurodevelopmental cell fate phenotypes caused by T21 followed by unbiased proteomics and western blotting to define the proteins dysregulated in T21 postmitotic neurons. We show that normalization of copy number of APP and DYRK1A each rescue elevated tau phosphorylation in T21 neurons, while reductions of RCAN1 and SYNJ1 do not. To determine the T21 alterations relevant to early-onset AD, we identified common pathways altered in familial Alzheimer's disease neurons and determined which of these were rescued by normalization of APP and DYRK1A copy number in T21 neurons. These studies identified disruptions in T21 neurons in both the axonal cytoskeletal network and presynaptic proteins that play critical roles in axonal transport and synaptic vesicle cycling. These alterations in the proteomic profiles have functional consequences: fAD and T21 neurons exhibit dysregulated axonal trafficking and T21 neurons display enhanced synaptic vesicle release. Taken together, our findings provide insights into the initial molecular alterations within neurons that ultimately lead to synaptic loss and axonal degeneration in Down syndrome and early-onset AD.

Machine-learned dynamic disorder of electron transfer coupling.

Electron transfer (ET) is a fundamental process in chemistry and biochemistry, and electronic coupling is an important determinant of the rate of ET. However, the electronic coupling is sensitive to many nuclear degrees of freedom, particularly those involved in intermolecular movements, making its characterization challenging. As a result, dynamic disorder in electron transfer coupling has rarely been investigated, hindering our understanding of charge transport dynamics in complex chemical and biological systems. In this work, we employed molecular dynamic simulations and machine-learning models to study dynamic disorder in the coupling of hole transfer between neighboring ethylene and naphthalene dimer. Our results reveal that low-frequency modes dominate these dynamics, resulting primarily from intermolecular movements such as rotation and translation. Interestingly, we observed an increasing contribution of translational motion as temperature increased. Moreover, we found that coupling is sub-Ohmic in its spectral density character, with cut-off frequencies in the range of 102 cm-1. Machine-learning models allow direct study of dynamics of electronic coupling in charge transport with sufficient ensemble trajectories, providing further new insights into charge transporting dynamics.

Live motile sperm sorting device for enhanced sperm-fertilization competency: comparative analysis with density-gradient centrifugation and microfluidic sperm sorting.

PURPOSE: A live motile sperm sorting device (LensHooke® CA0) developed to prevent the deleterious effects of centrifugation was evaluated comparatively with conventional density-gradient centrifugation (DGC) and microfluidic-based device (Zymot) in sperm selection. METHODS: Semen samples from 239 men were collected. CA0 under different incubation intervals (5, 10, 30, and 60 min) and temperatures (20, 25, and 37℃) was conducted. The sperm quality in CA0-, DGC-, and Zymot-processed samples was then comparatively evaluated. Semen parameters included concentration, motility, morphology, motion kinematics, DNA fragmentation index (DFI), and the rate of acrosome-reacted sperm (AR). RESULTS: Total motility and motile sperm concentration increased in a time- and temperature-dependent manner and the total motility peaked for 30 min at 37℃. In paired analysis, CA0 showed significantly higher total motility (94.0%), progressive motility (90.8%), rapid progressive motility (83.6%), normal morphology (10.3%), and lower DFI (2.4%) and AR (4.7%) than the other two methods in normozoospermic samples (all p < 0.05). For non-normozoospermic samples, CA0 had significantly better results than the other two methods (total motility 89.2%, progressive motility 80.4%, rapid progressive motility 74.2%, normal morphology 8.5%, DFI 4.0%, and AR 4.0%; all p < 0.05). CONCLUSION: CA0 yielded spermatozoa with enhanced sperm fertilization potentials; DFI was minimized in samples processed by CA0. CA0 was effective for both normal and abnormal semen samples due to its consistent selection efficiency.

Gestalt neurons and emergent properties in visual perception: A novel concept for the transformation from local to global processing.

Gestalten in visual perception are defined by emergent properties of the whole, which cannot be predicted from the sum of its parts; rather, they arise by virtue of inherent principles, the Laws of Seeing. This review attempts to assign neurophysiological correlates to select emergent properties in motion and contour perception and proposes parallels to the processing of local versus global attributes by classical versus contextual receptive fields. The aim is to identify Gestalt neurons in the visual system to account for the Laws of Seeing in causal terms and to explain "Why do things look as they do" (Koffka, 1935, p. 76).

SUMO1 and Defective Spermatozoa Correlate with Endogenous Hydrogen Peroxide and Live Birth Outcome in Intrauterine Insemination Cycles for Unexplained Infertility.

This study aimed to investigate the correlation between hydrogen peroxide (H2O2), small ubiquitin-like modifier molecules (SUMO), and pregnancy outcomes in couples with unexplained infertility (UI) undergoing intrauterine insemination (IUI) treatment. We prospectively collected semen samples from 56 couples with UI and divided the spermatozoa into motile and immotile fractions by density gradient centrifugation (DSC). Immunofluorescence staining was used to examine the immunostaining and localization of nuclear pore complex (NPC), SUMO1, and SUMO2/3 in spermatozoa. We detected H2O2 levels by chemiluminescence methods. We found that H2O2 levels correlated with NPC (neck) (r = 0.400) and NPC (tail) (r = 0.473) in motile sperm fractions. In immotile fractions, H2O2 positively correlated with NPC (tail) (r = 0.431) and SUMO1 (neck) (r = 0.282). Furthermore, the positive NPC (tail) group had a significantly lower live birth rate than the negative NPC group (17.9% = 5/28 vs. 42.9% = 12/28). In conclusion, H2O2 positively correlated with SUMO1 (neck) and NPC (tail) in human spermatozoa. The DSC may partially eliminate defective spermatozoa (positive NPC staining); however, if defective spermatozoa remain in the motile fraction, this scenario is associated with a low live birth rate following IUI treatment.

Sleep disturbances, glycaemic control, stress, and coping among diabetic patients: A structural equation modelling approach.

BACKGROUND: Sleep disturbances are more prevalent in diabetic patients than in the general population and may consequently be comorbid with hyperglycaemia. OBJECTIVE: The two study aims were to (1) verify the factors associated with sleep disturbances and glycaemic control and (2) further understand the mediation effects of coping and social support in the relationship among stress, sleep disturbances, and glycaemic control. METHODS: A cross-sectional study design was used. Data were collected at two metabolic clinics in southern Taiwan. The study recruited 210 patients with type II diabetes mellitus who were aged 20 years or above. Demographic information and data on stress, coping, social support, sleep disturbances, and glycaemic control were collected. The Pittsburgh Sleep Quality Index (PSQI) was used to assess sleep quality, and PSQI scores >5 were considered to indicate sleep disturbances. Structural equation modelling (SEM) approaches were employed to analyse the path association for sleep disturbances in diabetic patients. RESULTS: The mean age of the 210 participants was 61.43 (standard deviation, SD 11.41) years old, and 71.9 % reported sleep disturbances. The final path model had acceptable model fit indices. Stress perception was divided into stress perceived positively and negatively. Stress perceived positively was associated with coping (ß = 0.46, p < .01) and social support (ß = 0.31, p < .01), whereas stress perceived negatively was significantly associated with sleep disturbances (ß = 0.40, p < .001). CONCLUSIONS: The study shows that sleep quality is essential to glycaemic control, and stress perceived negatively might play a critical role to sleep quality.