Bulk lysis procedures alter target cell population counts.

To achieve high-sensitivity cell measurements (<1 in 105 cells) by flow cytometry (FCM), the minimum number of acquired cells must be considered and conventional immunophenotyping protocols fall short of these numbers. The bulk lysis (BL) assay is a standardized erythrocyte lysing approach that allows the analysis of the millions of cells required for high-sensitivity measurable residual disease (MRD) detection. However, this approach has been associated with significant cell loss, along with potential over or underestimates of rare cells when using this method. The aim of this study was to evaluate bulk lysis protocols and compare them with minimal sample perturbation (MSP) protocols, which are reported to better preserve the native cellular state and avoid significant cell loss due to washing steps. To achieve this purpose, we first generated an MRD model by spiking fresh peripheral blood with K562 cells, stably expressing EGFP, at known percentages of EGFP positive cells to leukocytes. Samples were then prepared with BL and MSP protocols and analyzed using FCM. For all percentages of K562 cells established and evaluated, a significant decrease of this population was detected in BL samples compared with MSP samples, even at low K562 cell percentages. Significant decreases for non-necrotic cells were also observed in BL samples relative to MSP samples. In conclusion, the evaluation of the potential effects of BL protocols in obtaining the final count is of great interest, especially for over- or under-estimation of target cells, as in the case of measurable residual disease. Since conventional flow cytometry or minimal sample perturbation assays fall short in obtaining the minimum numbers required to reach high sensitivity measurements, significant efforts may be needed to improve bulk lysis solution reagents.

Multiparameter persistent homology landscapes identify immune cell spatial patterns in tumors.

Highly resolved spatial data of complex systems encode rich and nonlinear information. Quantification of heterogeneous and noisy data-often with outliers, artifacts, and mislabeled points-such as those from tissues, remains a challenge. The mathematical field that extracts information from the shape of data, topological data analysis (TDA), has expanded its capability for analyzing real-world datasets in recent years by extending theory, statistics, and computation. An extension to the standard theory to handle heterogeneous data is multiparameter persistent homology (MPH). Here we provide an application of MPH landscapes, a statistical tool with theoretical underpinnings. MPH landscapes, computed for (noisy) data from agent-based model simulations of immune cells infiltrating into a spheroid, are shown to surpass existing spatial statistics and one-parameter persistent homology. We then apply MPH landscapes to study immune cell location in digital histology images from head and neck cancer. We quantify intratumoral immune cells and find that infiltrating regulatory T cells have more prominent voids in their spatial patterns than macrophages. Finally, we consider how TDA can integrate and interrogate data of different types and scales, e.g., immune cell locations and regions with differing levels of oxygenation. This work highlights the power of MPH landscapes for quantifying, characterizing, and comparing features within the tumor microenvironment in synthetic and real datasets.

Exploring the sources of variation of electrical conductivity and total and differential somatic cell count in Italian Mediterranean buffaloes.

In the buffalo dairy sector, a huge effort is still needed to improve mastitis prevention, detection, and management. Electrical conductivity (EC) and total somatic cell count (SCC) are well-known indirect indicators of mastitis. Differential somatic cell count (DSCC), which represents the proportion of neutrophils and lymphocytes on the total SCC, is instead a novel phenotype collected in the dairy cattle sector in the last lustrum. As little is known about this novel trait in dairy buffalo, in the present study we explored the nongenetic factors affecting DSCC, as well as EC and total somatic cell score (SCS), in the Italian Mediterranean buffalo. The data set used for the analysis included 14,571 test-day (TD) records of 1,501 animals from 6 herds, and climatic information of the sampling locations. The original data were filtered to exclude animals with less than 3 TD per lactation and, for the investigated traits, outliers beyond 4 standard deviations. In the statistical model we included the fixed effects of herd (6 classes), days in milk (DIM; 10 classes of 30 d, with the last being an open class until 360 d), parity (6 classes, from 1 to 6+), year-season of calving (11 classes, from summer 2019 to winter 2021/2022), year-season of sampling (9 classes, from spring 2020 to spring 2022), production level (4 classes based on quartiles of average milk yield by herd), and temperature-humidity index (THI; 4 classes based on quartiles, calculated using the average temperature and relative humidity of the 5 d before sampling). Average EC, SCS, and DSCC vary across herds. Considering DIM, greater EC values were observed at the beginning and the end of lactation; SCS was slightly lower, but DSCC was greater around the lactation peak. Increased EC, SCS, and DSCC levels with increasing parity were reported. Year-season calving and year-season sampling only slightly affected the variation of the investigated traits. Milk of high-producing buffaloes was characterized by lower EC and SCS mean values, nevertheless it had slightly greater DSCC percentages. Buffaloes grouped in the highest THI classes (classes 3 and 4) showed, on average, greater EC, SCS, and DSCC in comparison to the lower classes, especially to class 2. Results of the present study represent a preliminary as well as necessary step for the possible future inclusion of EC, SCS, or DSCC in breeding programs aimed to improve mastitis resistance in dairy buffaloes.

Novel insights into the associations between immune cell population distribution in mammary glands and milk minerals in Holstein cows.

Udder health has a crucial role in sustainable milk production, and various reports have pointed out that changes in udder condition seem to affect milk mineral content. The somatic cell count (SCC) is the most recognized indicator for the determination of udder health status. Recently, a new parameter, the differential somatic cell count (DSCC), has been proposed for a more detailed evaluation of intramammary infection patterns. Specifically, the DSCC is the combined proportions of polymorphonuclear neutrophils and lymphocytes (PMN-LYM) on the total SCC, with macrophages (MAC) representing the remainder proportion. In this study, we evaluated the association between DSCC in combination with SCC on a detailed milk mineral profile in 1,013 Holstein-Friesian cows reared in 5 herds. An inductively coupled plasma-optical emission spectrometry was used to quantify 32 milk mineral elements. Two different linear mixed models were fitted to explore the associations between the milk mineral elements and first, the DSCC combined with SCC, and second, DSCC expressed as the PMN-LYM and MAC counts, obtained by multiplying the proportion of PMN-LYM and MAC by SCC. We observed a significant positive association between SCC and milk Na, S, and Fe levels. Differential somatic cell count showed an opposite behavior to the one displayed by SCC, with a negative association with Na and positive association with K milk concentrations. When considering DSCC as count, Na and K showed contrasting behavior when associated with PMN-LYM or MAC counts, with decreasing of Na content and increasing K when associated with increasing PMN-LYM counts, and increasing Na and decreasing K when associated with increasing MAC count. These findings confirmed that an increase in SCC is associated with altered milk Na and K amounts. Moreover, MAC count seemed to mirror SCC patterns, with the worsening of inflammation. Differently, PMN-LYM count exhibited patterns of associations with milk Na and K contents attributable more to LYM than PMN, given the nonpathological condition of the majority of the investigated population. An interesting association was observed for milk S content, which increased with increasing of inflammatory conditions (i.e., increased SCC and MAC count) probably attributable to its relationship with milk proteins, especially whey proteins. Moreover, milk Fe content showed positive associations with the PMN-LYM population, highlighting its role in immune regulation during inflammation. Further studies including individuals with clinical condition are needed to achieve a comprehensive view of milk mineral behavior during udder health impairment.

Quality Control in the Corneal Bank with Artificial Intelligence: Comparison of a New Deep Learning-based Approach with Conventional Endothelial Cell Counting by the "Rhine-Tec Endothelial Analysis System". / Qualitätskontrolle in der Hornhautbank mit künstlicher Intelligenz: Vergleich eines neuen Deep-Learning-basierten Ansatzes mit der konventionellen Endothelzelldichtenbestimmung durch das "Rhine-Tec Endothelial Analysis System".

Endothelial cell density (ECD) is a crucial parameter for the release of corneal grafts for transplantation. The Lions Eye Bank of Baden-Württemberg uses the "Rhine-Tec Endothelial Analysis System" for ECD quantification, which is based on a fixed counting frame method considering only a small sample of 15 to 40 endothelial cells. The measurement result therefore depends on the frame placement and manual correction of the cells counted within the frame. To increase the sample size and create higher objectivity, we developed a new method based on "deep learning" that automatically detects all visible endothelial cells in the image. This study aims to compare this new method with the conventional Rhine-Tec system. 9375 archived phase-contrast microscopic images of consecutive grafts from the Lions Eye Bank were evaluated with the deep learning method and compared with the corresponding archived analyses of the Rhine-Tec system. Means, Bland-Altman and correlation analyses were compared. Comparable results were obtained for both methods. The mean difference between the Rhine-Tec system and the deep learning method was only - 23 cells/mm2 (95% confidence interval - 29 to - 17). There was a statistically significant positive correlation between the two methods, with a correlation coefficient of 0.748. What was striking in the Bland-Altman analysis were clustered deviations in the cell density range between 2000 and 2500 cells/mm2 - with higher values in the Rhine-Tec system. The comparable results for cell density measurement values underline the validity of the deep learning-based method. The deviations around the formal threshold for graft release of 2000 cells/mm2 are most likely explained by the higher objectivity of the deep learning method and the fact that measurement frames and manual corrections were specifically selected to reach the formal threshold of 2000 cells/mm2 when the full area endothelial quality was good. This full area assessment of the graft endothelium cannot currently be replaced by deep learning methods and remains the most important basis for graft release for keratoplasty.

Intradevice Repeatability and Interdevice Comparison of Two Specular Microscopy Devices in a Real-Life Setting: Tomey EM-4000 and Nidek CEM-530.

Background and Objectives: The purpose of this study was to compare two commercially available specular microscopes (Tomey EM-4000 and Nidek CEM-530) in a real-life clinical setting in terms of intra- and interdevice variability. The study was conducted on all patients seen in a clinical practice specializing in anterior segment pathologies, regardless of the purpose of their visit. Materials and Methods: In total, 112 eyes of 56 patients (age 23-85 years old) were included in the study. Each eye was measured three times with each device (for a total of six measurements), and results for central corneal thickness (CCT) and corneal endothelial cell density (ECD) were recorded. The results were then evaluated with the D'Agostino-Pearson normality test and compared with a Wilcoxon signed-rank test, t-test, ANOVA or Mann-Whitney test for intra- and interdevice variability. Results: Both specular microscopes produced very reliable reproducible intradevice results: The Tomey EM-4000 measured an ECD of 2390 ± 49.57 cells/mm2 (mean ± standard error of mean); the range was 799-3010 cells/mm2. The determined CCT was 546 ± 5.104 µm (mean ± standard error of mean [SEM]); the range was 425-615 µm. The measurements with the Nidek CEM-530 revealed an ECD of 2417 ± 0.09 cells/mm2 (mean ± SEM); the range was 505-3461 cells/mm2 (mean ± SEM). The mean CCT detected was 546.3 ± 4.937 µm (mean ± SEM); the range was 431-621 µm. The interdevice differences were statistically significant for both parameters, ECD (p = 0.0175) and CCT (p = 0.0125) (p < 0.05). Conclusions: The Nidek CEM-530 and the Tomey EM-4000 both produced reliable and reproducible results in terms of ECD and CCT. The absolute measurements were statistically significantly different for CCT and ECD for both devices; the Nidek produces slightly higher values.

SNP-based quantitative deconvolution of biological mixtures: application to the detection of cows with subclinical mastitis by whole-genome sequencing of tank milk.

Biological products of importance in food (e.g., milk) and medical (e.g., donor blood-derived products) sciences often correspond to mixtures of samples contributed by multiple individuals. Identifying which individuals contributed to the mixture and in what proportions may be of interest in several circumstances. We herein present a method that allows to do this by shallow whole-genome sequencing of the DNA in mixed samples from hundreds of donors. We show the efficacy of the approach for the detection of cows with subclinical mastitis by analysis of farms' tank mixtures containing milk from as many as 500 cows.

The purine nucleoside phosphorylase pnp-1 regulates epithelial cell resistance to infection in C. elegans.

Intestinal epithelial cells are subject to attack by a diverse array of microbes, including intracellular as well as extracellular pathogens. While defense in epithelial cells can be triggered by pattern recognition receptor-mediated detection of microbe-associated molecular patterns, there is much to be learned about how they sense infection via perturbations of host physiology, which often occur during infection. A recently described host defense response in the nematode C. elegans called the Intracellular Pathogen Response (IPR) can be triggered by infection with diverse natural intracellular pathogens, as well as by perturbations to protein homeostasis. From a forward genetic screen, we identified the C. elegans ortholog of purine nucleoside phosphorylase pnp-1 as a negative regulator of IPR gene expression, as well as a negative regulator of genes induced by extracellular pathogens. Accordingly, pnp-1 mutants have resistance to both intracellular and extracellular pathogens. Metabolomics analysis indicates that C. elegans pnp-1 likely has enzymatic activity similar to its human ortholog, serving to convert purine nucleosides into free bases. Classic genetic studies have shown how mutations in human purine nucleoside phosphorylase cause immunodeficiency due to T-cell dysfunction. Here we show that C. elegans pnp-1 acts in intestinal epithelial cells to regulate defense. Altogether, these results indicate that perturbations in purine metabolism are likely monitored as a cue to promote defense against epithelial infection in the nematode C. elegans.

A sample-preparation-free, point-of-care testing system for in situ detection of bovine mastitis.

We present a highly integrated point-of-care testing (POCT) device capable of immediately and accurately screening bovine mastitis infection based on somatic cell counting (SCC). The system primarily consists of a homemade cell-counting chamber and a miniature fluorescent microscope. The cell-counting chamber is pre-embedded with acridine orange (AO) in advance, which is simple and practical. And then SCC is directly identified by microscopic imaging analysis to evaluate the bovine mastitis infection. Only 4 µL of raw bovine milk is required for a simple sample testing and accurate SCC. The entire assay process from sampling to result in presentation is completed quickly within 6 min, enabling instant "sample-in and answer-out." Under laboratory conditions, we mixed bovine leukocyte suspension with whole milk and achieved a detection limit as low as 2.12 × 104 cells/mL on the system, which is capable of screening various types of clinical standards of bovine milk. The fitting degrees of the proposed POCT system with manual fluorescence microscopy were generally consistent (R2 > 0.99). As a proof of concept, four fresh milk samples were used in the test. The average accuracy of somatic cell counts was 98.0%, which was able to successfully differentiate diseased cows from healthy ones. The POCT system is user-friendly and low-cost, making it a potential tool for on-site diagnosis of bovine mastitis in resource-limited areas.

Heritability and genetic correlations of total and differential somatic cell count with milk yield and composition traits in Italian Simmental cows.

Costs of production have deeply increased each year in the last decades, breeders are continuously looking for more cost effective and more efficient ways to produce milk. Despite the major signs of progress in productivity, it is fundamental to optimize rather than maximize the performances of the dairy cows. Mastitis is still a highly prevalent disease in the dairy sector which causes several economic losses and environmental effect. Its accurate and early diagnosis is crucial to improve profitability of dairy cows and contribute to a more sustainable dairy industry. Among mastitis reduction strategies, there is the urgent need to implement breeding objectives to select cows displaying mastitis resistance by investigating the genetic mechanisms at the base of the inflammatory response. Therefore, in this study we aimed to further understand the genetic background of the differential somatic cell count (DSCC), which provides thorough insights on the actual inflammatory status of the mammary glands. The objectives of this study were to estimate on a cohort of 20,215 Italian Simmental cows over a 3-yr period: (1) the heritability and repeatability values of somatic cell score (SCS) and DSCC, (2) the genetic and phenotypic correlations between these 2 traits and milk production and milk composition traits, (3) the heritability and repeatability values of SCS and DSCC within class of udder health status. Heritability was low both for SCS (0.06) and DSCC (0.08), whereas the repeatability values for these traits were 0.43 and 0.36, suggesting that the magnitude of cow permanent environmental effect for these traits is remarkable. The genetic and phenotypic correlation of SCS with DSCC was 0.612 and 0.605, respectively. Because both significantly differed from the unit, we must consider those traits as different ones. This latter aspect corroborates the need to consider the DSCC as a further indicator of inflammatory status which might be implemented in the Simmental breed genetic evaluation. It is worthy to mention that heritability estimates for SCS and DSCC were the highest in healthy cows compared with the other udder health classes. This implies that when the udder health status changes, it is most likely due to environmental factors rather than aspects related to the animal's genetics. In contrast, the highest additive genetic variance and heritability found for SCS and DSCC in the healthy group might reveal the potential to further implement breeding strategies to select for healthier animals.

Evaluation of test-day milk somatic cell count to predict intramammary infection in late lactation grazing dairy cows.

Use of selective dry cow antimicrobial therapy requires to precisely differentiate cows with an intramammary infection (IMI) from uninfected cows close to drying-off to enable treatment allocation. Milk somatic cell count (SCC) is an indicator of an inflammatory response in the mammary gland and is usually associated with IMI. However, SCC can also be influenced by cow-level variables such as milk yield, lactation number and stage of lactation. In recent years, predictive algorithms have been developed to differentiate cows with IMI from cows without IMI based on SCC data. The objective of this observational study was to explore the association between SCC and subclinical IMI, taking cognizance of cow-level predictors on Irish seasonal spring calving, pasture-based systems. Additionally, the optimal test-day SCC cut-point (maximized sensitivity and specificity) for IMI diagnosis was determined. A total of 2,074 cows, across 21 spring calving dairy herds with an average monthly milk weighted bulk tank SCC of ≤200,000 cells/mL were enrolled in the study. Quarter-level milk sampling was carried out on all cows in late lactation (interquartile range = 240-261 d in milk) for bacteriological culturing. Bacteriological results were used to define cows with IMI, when ≥1 quarter sample resulted in bacterial growth. Cow-level test-day SCC records were provided by the herd owners. The ability of the average, maximum and last test-day SCC to predict infection were compared using receiver operator curves. Predictive logistic regression models tested included parity (primiparous or multiparous), yield at last test-day and a standardized count of high SCC test-days. In total, 18.7% of cows were classified as having an IMI, with first parity cows having a higher proportion of IMI (29.3%) compared with multiparous cows (16.1%). Staphylococcus aureus accounted for the majority of these infections. The last test-day SCC was the best predictor of infection with the highest area under the curve. The inclusions of parity, yield at last test-day, and a standardized count of high SCC test-days as predictors did not significantly improve the ability of last test-day SCC to predict IMI. The cut-point for last test-day SCC which maximized sensitivity and specificity was 64,975 cells/mL. This study indicates that in Irish seasonal pasture-based dairy herds, with low bulk tank SCC control programs, the last test-day SCC (interquartile range days in milk = 221-240) is the best predictor of IMI in late lactation.

Transcription phenotype of circulating tumor cells in non-metastatic breast cancer.

The presented research is relevant, as breast cancer is the most commonly diagnosed cancer in the female population worldwide, with the exception of skin cancer. The aim of this article is to study the transcription phenotype of circulating tumor cells in non-metastatic breast cancer. The transcriptional phenotype of circulating tumor cells (CTCs) was studied using real-time polymerase chain reaction (PCR). Three-year OS was 79.2, and 90.8 without the expression with p Log-Rank = 0.04. Independent prognostic factors for the recurrence of disease include the presence of CTCs expressing BIRC5 genes and ABC transporter genes in the peripheral blood before the start of special treatment for resectable breast cancer, as well as the preservation of CTCs per se after completion of special anticancer therapy. In patients with breast cancer stage I-IIIC, circulating tumor cells before special treatment have significant heterogeneity, manifested by a different transcriptional phenotype, including both actively growing and stem tumor cells, and cells at the epithelial-to-mesenchymal transition.

Combination therapy with novel androgen receptor antagonists and statin for castration-resistant prostate cancer.

BACKGROUND: One of the growth mechanisms of castration-resistant prostate cancer (CRPC) is de novo androgen synthesis from intracellular cholesterol, and statins may be able to inhibit this mechanism. In addition, statins have been reported to suppress the expression of androgen receptors (ARs) in prostate cancer cell lines. In this study, we investigated a combination therapy of novel AR antagonists and statin, simvastatin, for CRPC. METHODS: LNCaP, 22Rv1, and PC-3 human prostate cancer cell lines were used. We developed androgen-independent LNCaP cells (LNCaP-LA). Microarray analysis was performed, followed by pathway analysis, and mRNA and protein expression was evaluated by quantitative real-time polymerase chain reaction and Western blot analysis, respectively. Cell viability was determined by MTS assay and cell counts. All evaluations were performed on cells treated with simvastatin and with or without AR antagonists (enzalutamide, apalutamide, and darolutamide). RESULTS: The combination of darolutamide and simvastatin most significantly suppressed proliferation in LNCaP-LA and 22Rv1 cells. In a 22Rv1-derived mouse xenograft model, the combination of darolutamide and simvastatin enhanced the inhibition of cell proliferation. In LNCaP-LA cells, the combination of darolutamide and simvastatin led to reduction in the mRNA expression of the androgen-stimulated genes, KLK2 and PSA; however, this reduction in expression did not occur in 22Rv1 cells. The microarray data and pathway analyses showed that the number of differentially expressed genes in the darolutamide and simvastatin-treated 22Rv1 cells was the highest in the pathway termed "role of cell cycle." Consequently, we focused our efforts on the cell cycle regulator polo-like kinase 1 (PLK1), cyclin-dependent kinase 2 (CDK2), and cell cycle division 25C (CDC25C). In 22Rv1 cells, the combination of darolutamide and simvastatin suppressed the mRNA and protein expression of these three genes. In addition, in PC-3 cells (which lack AR expression), the combination of simvastatin and darolutamide enhanced the suppression of cell proliferation and expression of these genes. CONCLUSIONS: Simvastatin alters the expression of many genes involved in the cell cycle in CRPC cells. Thus, the combination of novel AR antagonists (darolutamide) and simvastatin can potentially affect CRPC growth through both androgen-dependent and androgen-independent mechanisms.

Uterine CD56+ cell density and euploid miscarriage in women with a history of recurrent miscarriage: A clinical descriptive study.

In women with a history of recurrent miscarriage, the uterine CD56+ cell density in subjects with subsequent euploid miscarriage was significantly higher than those with subsequent aneuploid miscarriage. Both endometrial and embryonic factors should be investigated when interpreting uterine CD56+ cell density results relating to recurrent miscarriage.

Circulating tumor cell detection: A prospective comparison between CellSearch® and RareCyte® platforms in patients with progressive metastatic breast cancer.

PURPOSE: Circulating tumor cells (CTCs) are prognostic in patients with breast cancer. Several technical platforms exist for their enumeration and characterization. Comparative studies between these platforms are scarce. The RareCyte CTC detection is theoretically more sensitive than the established CellSearch platform, which identifies only CTCs that express EpCAM and cytokeratin. This study prospectively compares CTC enumeration in patients with breast cancer in a paired analysis using these two platforms. It investigates survival outcomes in groups defined by a CTC count threshold. DESIGN: CTC enumeration was performed on 100 samples obtained from 86 patients with progressive metastatic breast cancer (MBC) in two independent laboratories each blinded to the clinical data and the results from the other platform. RESULTS: One hundred paired samples were collected and CTC counts were determined using the CellSearch and RareCyte CTC platforms. In total, 65% and 75% of samples had at least one detectable CTC in 7.5 mL blood with the CellSearch and the RareCyte systems, respectively. CTC counts with the CellSearch system ranged from 0 to 2289 with a median of 3 CTCs, the RareCyte CTC counts ranged from 0 to 1676 with a median of 3 CTCs. The number of samples with 5 or more CTCs in 7.5 mL of blood (the poor prognosis cut-off validated with the CellSearch system) blood was 45% with the CellSearch test and 48% with the RareCyte test. CTC counts quantified with the CellSearch and the RareCyte systems were strongly correlated (Spearman's r = 0.8235 (0.7450-0.8795) p < 0.001). 86 patients were included for Kaplan-Meier survival analysis. An increased mortality risk in patients with CellSearch of 5 CTCs or more per 7.5 mL blood, with a log-rank hazard ratio of 5.164 (2.579-10.34) (p < 0.001) was confirmed. The survival analysis with RareCyte CTC counts with the identical cut-off showed a significantly impaired survival with a hazard ratio of 4.213 (2.153-8.244) (p < 0.001). CONCLUSION: Our data demonstrate the analytical and prognostic equivalence of CellSearch and RareCyte CTC enumeration platforms in patients with MBC using the CellSearch cut-off. This is the first demonstration of prognostic significance using the RareCyte platform.

Cancer cell population growth kinetics at low densities deviate from the exponential growth model and suggest an Allee effect.

Most models of cancer cell population expansion assume exponential growth kinetics at low cell densities, with deviations to account for observed slowing of growth rate only at higher densities due to limited resources such as space and nutrients. However, recent preclinical and clinical observations of tumor initiation or recurrence indicate the presence of tumor growth kinetics in which growth rates scale positively with cell numbers. These observations are analogous to the cooperative behavior of species in an ecosystem described by the ecological principle of the Allee effect. In preclinical and clinical models, however, tumor growth data are limited by the lower limit of detection (i.e., a measurable lesion) and confounding variables, such as tumor microenvironment, and immune responses may cause and mask deviations from exponential growth models. In this work, we present alternative growth models to investigate the presence of an Allee effect in cancer cells seeded at low cell densities in a controlled in vitro setting. We propose a stochastic modeling framework to disentangle expected deviations due to small population size stochastic effects from cooperative growth and use the moment approach for stochastic parameter estimation to calibrate the observed growth trajectories. We validate the framework on simulated data and apply this approach to longitudinal cell proliferation data of BT-474 luminal B breast cancer cells. We find that cell population growth kinetics are best described by a model structure that considers the Allee effect, in that the birth rate of tumor cells increases with cell number in the regime of small population size. This indicates a potentially critical role of cooperative behavior among tumor cells at low cell densities with relevance to early stage growth patterns of emerging and relapsed tumors.

Chandelier Cartridge Density Is Reduced in the Prefrontal Cortex in Autism.

An alteration in the balance of excitation-inhibition has been proposed as a common characteristic of the cerebral cortex in autism, which may be due to an alteration in the number and/or function of the excitatory and/or inhibitory cells that form the cortical circuitry. We previously found a decreased number of the parvalbumin (PV)+ interneuron known as Chandelier (Ch) cell in the prefrontal cortex in autism. This decrease could result from a decreased number of Ch cells, but also from decreased PV protein expression by Ch cells. To further determine if Ch cell number is altered in autism, we quantified the number of Ch cells following a different approach and different patient cohort than in our previous studies. We quantified the number of Ch cell cartridges-rather than Ch cell somata-that expressed GAT1-rather than PV. Specifically, we quantified GAT1+ cartridges in prefrontal areas BA9, BA46, and BA47 of 11 cases with autism and 11 control cases. We found that the density of GAT1+ cartridges was decreased in autism in all areas and layers. Whether this alteration is cause or effect remains unclear but could result from alterations that take place during cortical prenatal and/or postnatal development.

Microstructure of Human Corpus Callosum across the Lifespan: Regional Variations in Axon Caliber, Density, and Myelin Content.

The myeloarchitecture of the corpus callosum (CC) is characterized as a mosaic of distinct differences in fiber density of small- and large-diameter axons along the anterior-posterior axis; however, regional and age differences across the lifespan are not fully understood. Using multiecho T2 magnetic resonance imaging combined with multi-T2 fitting, the myelin water fraction (MWF) and geometric-mean of the intra-/extracellular water T2 (geomT2IEW) in 395 individuals (7-85 years; 41% males) were examined. The approach was validated where regional patterns along the CC closely resembled the histology; MWF matched mean axon diameter and geomT2IEW mirrored the density of large-caliber axons. Across the lifespan, MWF exhibited a quadratic association with age in all 10 CC regions with evidence of a positive linear MWF-age relationship among younger participants and minimal age differences in the remainder of the lifespan. Regarding geomT2IEW, a significant linear age × region interaction reflected positive linear age dependence mostly prominent in the regions with the highest density of small-caliber fibers-genu and splenium. In all, these two indicators characterize distinct attributes that are consistent with histology, which is a first. In addition, these results conform to rapid developmental progression of CC myelination leveling in middle age as well as age-related degradation of axon sheaths in older adults.

Impact of somatic cell count combined with differential somatic cell count on milk protein fractions in Holstein cattle.

Udder health in dairy herds is a very important issue given its implications for animal welfare and the production of high-quality milk. Somatic cell count (SCC) is the most widely used means of assessing udder health status. However, differential somatic cell count (DSCC) has recently been proposed as a new and more effective means of evaluating intramammary infection dynamics. Differential SCC represents the combined percentage of polymorphonuclear neutrophils and lymphocytes (PMN-LYM) in the total SCC, with macrophages (MAC) accounting for the remaining proportion. The aim of this study was to evaluate the association between SCC and DSCC and the detailed milk protein profile in a population of 1,482 Holstein cows. A validated reversed-phase HPLC method was used to quantify 4 caseins (CN), namely αS1-CN, αS2-CN, κ-CN, and ß-CN, and 3 whey protein fractions, namely ß-lactoglobulin, α-lactalbumin, and lactoferrin, which were expressed both quantitatively (g/L) and qualitatively (as a percentage of the total milk nitrogen content, %N). A linear mixed model was fitted to explore the associations between somatic cell score (SCS) combined with DSCC and the protein fractions expressed quantitatively and qualitatively. We ran an additional model that included DSCC expressed as PMN-LYM and MAC counts, obtained by multiplying the percentages of PMN-LYM and MAC by SCC for each cow in the data set. When the protein fractions were expressed as grams per liter, SCS was significantly negatively associated with almost all the casein fractions and positively associated with the whey protein α-lactalbumin, while DSCC was significantly associated with αS1-CN, ß-CN, and α-lactalbumin, but in the opposite direction to SCS. We observed the same pattern with the qualitative data (i.e., %N), confirming opposite effects of SCS and DSCC on milk protein fractions. The PMN-LYM count was only slightly associated with the traits of concern, although the pattern observed was the same as when both SCS and DSCC were included in the model. The MAC count, however, generally had a greater impact on many casein fractions, in particular decreasing both ß-CN content (g/L) and proportion (%N), and exhibited the opposite pattern to the PMN-LYM count. Our results show that information obtained from both SCS and DSCC may be useful in assessing milk quality and protein fractions. They also demonstrate the potential of MAC count as a novel udder health trait.

Direct labeling of milk cells without centrifugation for counting total and differential somatic cells using flow cytometry.

Somatic cell count (SCC) in milk is an essential indicator for defining and managing udder health. However, analyzing differential SCC (dSCC) can be helpful in determining the type or evolution stage of mastitis. A high abundance of polymorphonuclear cells (PMN) is associated with acute mastitis; however, the status of a chronic disease is less well characterized. A method capable of analyzing SCC and dSCC can prove to be a helpful tool for monitoring the status of evolution of mastitis disease in a better way. Therefore, a new direct-flow cytometry method was developed to count and differentiate somatic cells in milk without the steps of centrifugation or washing, avoiding variabilities that occur due to enrichment or loss of specific cell types. In this new method, SCC is analyzed using the method of DNA staining with Hoechst stain, whereas dSCC are analyzed using specific antibodies targeting 2 main cell types associated with mastitis: PMN cells and antigen-presenting cells, which are associated with innate and adaptive immunity. Equivalent SCC values were obtained between the new method and the routine ISO 13366-2 method in a comparison of 240 raw milk samples. Furthermore, dSCC results were confirmed by microscopy after May-Gründwald-Giemsa staining in 165 quarter milk samples from healthy and diseased cows. The method was verified with fluorescence microscopy on the 2 targeted cell types and in raw milk samples. The newly developed method is independent of any instrument and can be further designed to differentiate other cell types and animal species by selecting appropriate antibodies.