Glucocorticoid receptor and specificity protein 1 (Sp1) or Sp3, but not the antibiotic Mithramycin A, stimulates human alphaherpesvirus 1 (HSV-1) replication.

Following acute human alphaherpesvirus 1 (HSV-1) infection of oral-facial mucosal surfaces, sensory neurons in trigeminal ganglia (TG) are important sites for life-long latency. Neurons in the central nervous system, including brainstem, also harbor viral genomes during latency. Periodically, certain cellular stressors trigger reactivation from latency, which can lead to recurrent HSV-1 disease: herpes labialis, herpes stromal keratitis, and encephalitis for example. Activation of the glucocorticoid receptor (GR) by stressful stimuli enhances HSV-1 gene expression, replication, and explant-induced reactivation. GR and certain stress-induced Krüppel like factors (KLF) cooperatively transactivate cis-regulatory modules (CRM) that drive expression of viral transcriptional regulatory proteins (ICP0, ICP4, and ICP27). These CRMs lack GR response elements (GRE); however, specificity protein 1 (Sp1) binding sites are crucial for GR and KLF15 or KLF4 mediated transactivation. Hence, we tested whether Sp1 or Sp3 regulate viral replication and transactivation of the ICP0 promoter. During early stages of explant-induced reactivation from latency, the number of Sp3+ TG neurons were significantly higher relative to TG from latently infected mice. Conversely, Sp1+ TG neurons were only increased in females, but not male mice, during explant-induced reactivation. Sp1 siRNA significantly reduced HSV-1 replication in cultured mouse (Neuro-2A) and monkey (CV-1) cells. Mithramycin A, an antibiotic that has anti-tumor activity preferentially interacts with GC-rich DNA, including Sp1 binding sites, significantly reduced HSV-1 replication indicating it has antiviral activity. GR and Sp1 or Sp3 transactivated the HSV-1 ICP0 promoter in Neuro-2A and CV-1 cells confirming these transcription factors enhance viral replication and gene expression.

Manual versus deep learning measurements to evaluate cumulus expansion of bovine oocytes and its relationship with embryo development in vitro.

Cumulus expansion is an important indicator of oocyte maturation and has been suggested to be indicative of greater oocyte developmental capacity. Although multiple methods have been described to assess cumulus expansion, none of them is considered a gold standard. Additionally, these methods are subjective and time-consuming. In this manuscript, the reliability of three cumulus expansion measurement methods was assessed, and a deep learning model was created to automatically perform the measurement. Cumulus expansion of 232 cumulus-oocyte complexes was evaluated by three independent observers using three methods: (1) measurement of the cumulus area, (2) measurement of three distances between the zona pellucida and outer cumulus, and (3) scoring cumulus expansion on a 5-point Likert scale. The reliability of the methods was calculated in terms of intraclass-correlation coefficients (ICC) for both inter- and intra-observer agreements. The area method resulted in the best overall inter-observer agreement with an ICC of 0.89 versus 0.54 and 0.30 for the 3-distance and scoring methods, respectively. Therefore, the area method served as the base to create a deep learning model, AI-xpansion, which reaches a human-level performance in terms of average rank, bias and variance. To evaluate the accuracy of the methods, the results of cumulus expansion calculations were linked to embryonic development. Cumulus expansion had increased significantly in oocytes that achieved successful embryo development when measured by AI-xpansion, the area- or 3-distance method, while this was not the case for the scoring method. Measuring the area is the most reliable method to manually evaluate cumulus expansion, whilst deep learning automatically performs the calculation with human-level precision and high accuracy and could therefore be a valuable prospective tool for embryologists.

Evidence that elevation of maternal somatic cell count could lead to production of offspring with inferior reproductive and productive performance in dairy cows during the first lactation period.

Although the effect of mastitis on reproduction and production of lactating dairy cows has been vastly studied, little information is available about the association of maternal udder health status with offspring reproduction and production. Therefore, the present research was conducted to study the association between maternal average monthly somatic cell count (SCC) with reproduction, anti-Müllerian hormone (AMH) concentration, udder health status and milk production in the offspring. Based on maternal average monthly SCC (MSCC), offspring were classified into five categories including MSCC1 (SCC <200,000; n = 3005), MSCC2 (200,000 ≤ SCC <400,000; n = 252), MSCC3 (400,000 ≤ SCC <600,000; n = 103), MSCC4 (600,000 ≤ SCC <800,000; n = 40) and MSCC5 (SCC ≥800,000; n = 61). Data associated with reproduction, production and udder health status of offspring were retrieved from the herd database. In addition, blood samples were collected from a subset of offspring (n = 136) for measurement of serum AMH, as a reliable marker of ovarian reserves. Offspring in MSCC5 category had more services per conception and longer calving to conception interval than offspring in MSCC1 and MSCC2 categories (P < 0.05). The average number of SCC and risk of clinical mastitis in the offspring were not associated with MSCC (P > 0.05). But offspring in MSCC5 category produced less milk, fat and protein than offspring in MSCC1 category (P < 0.05). In addition, AMH concentration was lower in MSCC5 than MSCC1 category (P < 0.05). In conclusion, the present study showed that elevated maternal average monthly SCC could culminate in birth of offspring with inferior reproductive performance, smaller size of ovarian reserves and lower level of milk production during the first lactation period.

Oocyte developmental capacity is influenced by intrinsic ovarian factors in a bovine model for individual embryo production.

The ovary and its hormones may have major effects on the in vitro developmental capacity of the oocytes it contains. We related intrinsic ovarian factors namely the presence of corpus luteum (CL) and/or dominant follicle (>8 mm) and the follicular count to cumulus expansion (CE), embryo development, and blastocyst quality in a bovine model. Cumulus-oocyte-complexes (COCs) were aspirated from follicles between 4 and 8 mm in diameter. In vitro embryo production was performed in a fully individual production system. The follicular fluid from which COCs were collected was pooled (per ovary) to evaluate the estrogen, progesterone, and insulin-like growth factor-1 (IGF-1) concentrations. Cumulus oocyte complexes collected from ovaries without a CL presented a greater CE than COCs derived from ovaries bearing CL. The absence of ovarian structures increased the blastocyst rate when compared to oocytes derived from ovaries with a CL, a dominant follicle, or both. Blastocysts derived from ovaries without a dominant follicle presented higher total cell numbers and a lower proportion of apoptosis than blastocysts derived from ovaries containing a dominant follicle. Cumulus oocyte complexes collected from ovaries with high follicular count resulted in higher cleavage than from ovaries with low follicular count, but the blastocyst rate was similar between groups. Ovaries bearing a CL had greater progesterone and IGF-1 follicular fluid concentrations in neighboring follicles than ovaries without a CL. Selection for bovine ovaries without CL or dominant follicle can have positive effects on CE, embryo development, and blastocyst quality in an individual embryo production system set-up.

Lycopene supplementation to serum-free embryo culture medium and its effect on development and quality of bovine blastocysts produced in vitro.

Selenium is commonly used as an antioxidant in a serum-free culture medium setting. However, lycopene has emerged as a potent antioxidant being twice as efficient as ß-carotene and 10 times as efficient as α-tocopherol with beneficial effects when supplemented in a serum-free maturation medium. Here, we aimed to evaluate the effect of lycopene supplementation in a serum-free culture medium on blastocyst development and quality. After in vitro maturation and fertilization, presumed zygotes were cultured in groups of 25 in 50 µl droplets of synthetic oviductal fluid. Culture medium supplementation was done using four experimental groups: insulin, transferrin, selenium (ITS, control); ITS + DMSO (diluent control); ITS + DMSO-lycopene 0.1 µM (ITSL); and IT + DMSO-lycopene 0.1 µM (ITL). DMSO was used as a diluent for lycopene. Blastocyst development among experimental groups was fitted in mixed-effects models, and blastocyst quality parameters (assessed via differential apoptotic staining) were evaluated in mixed linear regression models. The cleavage (85.3 ± 2.4, 82.6 ± 2.7, 86 ± 2.3 and 86.4 ± 2.3% for control, diluent control, ITSL and ITL, respectively) and day 8 blastocyst rates (37.4 ± 3.3, 36.9 ± 3.4, 39.7 ± 3.3 and 46.2 ± 3.4% for control, diluent control, ITSL and ITL, respectively) were not different (p > .1) among experimental groups. Embryos produced in the ITL group resulted in blastocysts with higher total cell numbers (TCN; 141 ± 19.2), inner cell mass (ICM; 65.3 ± 11.6) and trophectoderm cells (TE; 75.2 ± 8.8) compared with the control (129 ± 19.2, 56.3 ± 11.6 and 72.7 ± 8.8, for TCN, ICM and TE; p < .01, respectively). Lycopene-supplemented groups (ITSL and ITL) resulted in blastocysts with similar TCN, ICM and TE (p > .2). The number of apoptotic cells was not different among experimental groups (p > .1). Lycopene supplementation to the culture medium only produced a numerical increase in the blastocyst rate but replacing selenium with lycopene in a serum-free culture medium resulted in blastocysts with more cells.

Validation of a deep learning-based image analysis system to diagnose subclinical endometritis in dairy cows.

The assessment of polymorphonuclear leukocyte (PMN) proportions (%) of endometrial samples is the hallmark for subclinical endometritis (SCE) diagnosis. Yet, a non-biased, automated diagnostic method for assessing PMN% in endometrial cytology slides has not been validated so far. We aimed to validate a computer vision software based on deep machine learning to quantify the PMN% in endometrial cytology slides. Uterine cytobrush samples were collected from 116 postpartum Holstein cows. After sampling, each cytobrush was rolled onto three different slides. One slide was stained using Diff-Quick, while a second was stained using Naphthol (golden standard to stain PMN). One single observer evaluated the slides twice at different days under light microscopy. The last slide was stained with a fluorescent dye, and the PMN% were assessed twice by using a fluorescence microscope connected to a smartphone. Fluorescent images were analyzed via the Oculyze Monitoring Uterine Health (MUH) system, which uses a deep learning-based algorithm to identify PMN. Substantial intra-method repeatabilities (via Spearman correlation) were found for Diff-Quick, Naphthol, and Oculyze MUH (r = 0.67 to 0.76). The intra-method agreements (via Kappa value) at ≥1% PMN (κ = 0.44 to 0.47) were lower than at >5 (κ = 0.69 to 0.78) or >10% (κ = 0.67 to 0.85) PMN cut-offs. The inter-method repeatabilities (via Lin's correlation) were also substantial, and values between Diff-Quick and Oculyze MUH, Naphthol and Diff-Quick, and Naphthol and Oculyze MUH were 0.68, 0.69, and 0.77, respectively. The agreements among evaluation methods at ≥1% PMN were weak (κ = 0.06 to 0.28), while it increased at >5 (κ = 0.48 to 0.81) or >10% (κ = 0.50 to 0.65) PMN cut-offs. To conclude, deep learning-based algorithms in endometrial cytology are reliable and useful for simplifying and reducing the diagnosis bias of SCE in dairy cows.