Microscopic Cell Counts Research Articles

L. plantarum UBLP-40 Versus the Combined Formula of L. rhamnosus UBLP-58 and B. longum UBBL-64 in Excisional Wound Healing: A Cellular Perspective

Introduction: The utilization of probiotics in enhancing the active healing of skin wounds represents a burgeoning trend in contemporary medicine. Previous research has extensively explored wound healing mechanisms involving the strains of Lactiplantibacillus plantarum, Lacticaseibacillus rhamnosus, and Bifidobacterium longum. This study seeks to compare and interpret cellular findings derived from immunohistochemical and pathological applications. Methods: Three groups (the control, Lactiplantibacillus plantarum (RO1) group, and Lacticaseibacillus rhamnosus and Bifidobacterium longum (PRO2) group) underwent histological analysis, and microscopic cell counting were employed, offering insights into dynamic changes among neutrophils, lymphocytes, plasmacytes, mast cells, fibroblasts, and newly formed vessels across distinct treatment groups and temporal intervals. Results: The neutrophil count was found to be elevated in PRO2 on day 2, while the same group resulted in the highest decline on day 15. The number of fibroblasts peaked on day 4 for the PRO1 group, compared to the other two groups, which peaked on day 8. The lymphocyte count was the highest in the control group, while they peaked on day 4 in PRO2. The mast cells and plasmacytes were variable and sparse among all groups and time frames. Neovascularization was promoted by PRO1 and PRO2 groups on day 4 and remained high on day 8 for PRO2. Conclusions: Probiotic strains can be beneficial to the human population and in assisting skin wound healing, each strain working differently and more effectively in different healing phases. Thus, a combined formula containing different probiotics to modulate various healing phases is desirable.

A novel ensemble approach with deep transfer learning for accurate identification of foodborne bacteria from hyperspectral microscopy

The detection of foodborne bacteria is critical in ensuring both consumer safety and food safety. If these pathogens are not properly identified, it can lead to dangerous cross-contamination. One of the most common methods for classifying bacteria is through the examination of Hyperspectral microscope imaging (HMI). A widely used technique for measuring microbial growth is microscopic cell counting. HMI is a laborious and expensive process, producing voluminous data and needing specialized equipment, which might not be widely available. Machine learning (ML) methods are now frequently utilized to automatically interpret data from hyperspectral microscopy. The objective of our study is to devise a technique that employs deep transfer learning to address the challenge of limited data and utilizes four base classifiers - InceptionResNetV2, MobileNet, ResNet101V2, and Xception - to create an ensemble-based classification model for distinguishing live and dead bacterial cells of six pathogenic strains. In order to determine the optimal weights for the base classifiers, a Powell's optimization method was utilized in conjunction with a weighted average ensemble (WAVE) technique. We carried out an extensive experimental study to verify the efficiency of our proposed ensemble model on live and dead cell images of six different foodborne bacteria. In order to gain a better understanding of the regions, we performed a Grad-CAM analysis to explain the predictions made by our model. Through a series of experiments, our proposed framework has proven its capacity to effectively and precisely detect numerous bacterial pathogens. Specifically, it achieved a perfect identification rate of 100 % for Escherichia coli (EC), Listeria innocua (LI), and Salmonella Enteritidis (SE), while achieving rates of 96.30 % for Salmonella Typhimurium (ST), 87.13 % for Staphylococcus aureus (SA), and 94.12 % for Salmonella Heidelberg (SH). As a result, it can be considered as an effective tool for the identification of foodborne pathogens, due to its high level of efficiency.

A Bayesian Approach Toward Robust Multidimensional Ellipsoid-Specific Fitting.

This work presents a novel and effective method for fitting multidimensional ellipsoids (i.e., ellipsoids embedded in [Formula: see text]) to scattered data in the contamination of noise and outliers. Unlike conventional algebraic or geometric fitting paradigms that assume each measurement point is a noisy version of its nearest point on the ellipsoid, we approach the problem as a Bayesian parameter estimate process and maximize the posterior probability of a certain ellipsoidal solution given the data. We establish a more robust correlation between these points based on the predictive distribution within the Bayesian framework, i.e., considering each model point as a potential source for generating each measurement. Concretely, we incorporate a uniform prior distribution to constrain the search for primitive parameters within an ellipsoidal domain, ensuring ellipsoid-specific results regardless of inputs. We then establish the connection between measurement point and model data via Bayes' rule to enhance the method's robustness against noise. Due to independent of spatial dimensions, the proposed method not only delivers high-quality fittings to challenging elongated ellipsoids but also generalizes well to multidimensional spaces. To address outlier disturbances, often overlooked by previous approaches, we further introduce a uniform distribution on top of the predictive distribution to significantly enhance the algorithm's robustness against outliers. Thanks to the uniform prior, our maximum a posterior probability coincides with a more tractable maximum likelihood estimation problem, which is subsequently solved by a numerically stable Expectation Maximization (EM) framework. Moreover, we introduce an ε-accelerated technique to expedite the convergence of EM considerably. We also investigate the relationship between our algorithm and conventional least-squares-based ones, during which we theoretically prove our method's superior robustness. To the best of our knowledge, this is the first comprehensive method capable of performing multidimensional ellipsoid-specific fitting within the Bayesian optimization paradigm under diverse disturbances. We evaluate it across lower and higher dimensional spaces in the presence of heavy noise, outliers, and substantial variations in axis ratios. Also, we apply it to a wide range of practical applications such as microscopy cell counting, 3D reconstruction, geometric shape approximation, and magnetometer calibration tasks. In all these test contexts, our method consistently delivers flexible, robust, ellipsoid-specific performance, and achieves the state-of-the-art results.

Water column properties associated with massive algal bloom of green Noctiluca scintillans in the Arabian Sea

An algal bloom of Noctiluca scintillans (NS) was monitored for 20 days in the Arabian Sea during February 2017. The stations under the influence of NS had low temperature and high salinity compared to outside indicating influence of convective mixing. The microscopic cell count of NS reached a value of 52,600 cells l−1. The surface variability in oxygen and pCO2 measured alongside showed a strong disconnect. Modest supersaturation of surface waters (ΔpCO2 = 3–75 μatm) was observed around the NS bloom compared to outside. However, as these stations were under the influence of convective mixing, the observed change in pCO2 due to subsurface ventilation cannot be ruled out. From the viewpoint of climate change and its influence on oceanic processes, constant monitoring of this bloom becomes essential due to its survival strategy in nutrient-depleted conditions and light of the present observations.

Preferential dreissenid mussel grazing on small plankton can favor cyanobacteria: Experimental evidence from western Lake Erie

Abstract Herein we provide experimental evidence for the effects invasive mussels (Dreissena) grazing can exert on a natural assemblage of plankton that included both hetero- and photo-trophic components in western Lake Erie. Five mussel feeding experiments were performed seasonally in 2018 (May, June, July August, October). Pre- and post-grazing samples were collected from seven 20-L mesocosms (3 control, 4 mussel), and analyzed using microscope cell counts. Results from our experiments showed that Dreissena were active grazers of plankton on all dates, with significant correspondence between mussel clearance rates measured using microscopy versus size-specific chlorophyll and FluoroProbe based estimates (Spearman rank correlation, r = 0.45, and r = 0.48, respectively, p < 0.05). Clearance rates (ml mg-1 h-1) were variable among taxonomic groups and seemed to track the abundance of ambient plankton assemblage (range 1.70 to 25.00, mean ± SE 11.70 ± 1.33). Dreissena grazed consistently on nano-sized hetero- and phototrophic plankton that constituted key trophic linkages in the Lake Erie foodweb. The most actively grazed plankton were phototrophic cryptophytes (Rhodomonas minuta, Cryptomonas spp.), centric diatoms (Cyclotella sp. and Discotella spp.), and non-pigmented chrysomonads (Chromulina sp., Ochromonas sp.). Conversely, clearance rates were low for cyanobacteria (e.g. Microcystis), dinoflagellates (Gymnodinium varians), and some colonial chlorophytes (Desmodesmus, Pediastrum); these plankton groups occurred during specific temporal windows (one-way ANOVA, p < 0.05). Our results indicate the potential mussel grazing can suppress typical, non-harmful plankton species in the nanoplankton size range, thereby favoring the occurrence of less-edible, larger cyanobacteria and chlorophyte species in western Lake Erie.

Comparison of advanced methodologies for diatom identification within dynamic coastal communities

AbstractDiatom community composition has a critical influence on global ocean health and ecological processes. Developing accurate and efficient methods for diatom identification under dynamic environmental conditions is essential to understanding the implications of diatom community changes. Two developing methods for identifying and enumerating phytoplankton, cell imaging and molecular sequencing, are experiencing rapid advancements. This study aims to compare diatom taxonomic composition results within natural assemblages derived from rapidly advancing methods, FlowCam imaging and metabarcoding of the V4 region of the 18S rRNA gene, with traditional light microscopy cell counting techniques. All three methods were implemented in tandem to analyze changes in dynamic diatom assemblages within simulated upwelling experiments conducted in the California upwelling zone. The results of this study indicate that, summed across all samples, DNA sequencing detected four times as many genera as morphology‐based methods, thus supporting previous findings that DNA sequencing is the most powerful method for analyzing species richness. Results indicate that all three methods returned comparable relative abundance for the most abundant genera. However, the three methods did not return comparable absolute abundance, primarily due to barriers in deriving quantities in equal units. Overall, this study indicates that at the semi‐quantitative level of relative abundance measurements, FlowCam imaging and metabarcoding of the V4 region of the 18S rRNA gene yield comparable results with light microscopy but at the qualitative and quantitative levels, enumeration metrics diverge, and thus method selection and cross‐method comparison should be performed with caution.

Using optimal transport theory to optimize a deep convolutional neural network microscopic cell counting method.

Medical image processing has become increasingly important in recent years, particularly in the field of microscopic cell imaging. However, accurately counting the number of cells in an image can be a challenging task due to the significant variations in cell size and shape. To tackle this problem, many existing methods rely on deep learning techniques, such as convolutional neural networks (CNNs), to count cells in an image or use regression counting methods to learn the similarities between an input image and a predicted cell image density map. In this paper, we propose a novel approach to monitor the cell counting process by optimizing the loss function using the optimal transport method, a rigorous measure to calculate the difference between the predicted count map and the dot annotation map generated by the CNN. We evaluated our algorithm on three publicly available cell count benchmarks: the synthetic fluorescence microscopy (VGG) dataset, the modified bone marrow (MBM) dataset, and the human subcutaneous adipose tissue (ADI) dataset. Our method outperforms other state-of-the-art methods, achieving a mean absolute error (MAE) of 2.3, 4.8, and 13.1 on the VGG, MBM, and ADI datasets, respectively, with smaller standard deviations. By using the optimal transport method, our approach provides a more accurate and reliable cell counting method for medical image processing.

Protistan community structure and the influence of a branch of Kuroshio in the northeastern East China Sea during the late spring

The northeastern East China Sea is an ecologically important marine ecosystem influenced by warm water derived from the Kuroshio Current. However, relatively little is known about the spatial variation of protist communities and their regulating factors from this region’s ecosystem during the spring season. Here, we investigated protistan community structures using a complementary approach combining 18S rRNA gene amplicon sequencing and light microscopy cell counts at nine stations from the northeastern East China Sea to the west of Jeju Island. The vertical profiles of physicochemical properties revealed that the Jeju Warm Current water mass, flowing from the southeast towards the northwest, created a thermohaline front dividing the region in two. These two regions had similar planktonic biomass, but the protistan communities differed significantly: dinoflagellates accounted for higher proportions of the protistan communities in the warm and saline waters, particularly at stations E35, E44, and E45, while the relative abundances of diatoms and picochlorophytes were higher in the low-density water of the western stations (E32 and E42). Furthermore, higher species richness and Shannon Diversity Index values in the warm and saline waters suggests that the Jeju Warm Current, a branch of the Kuroshio, increases protistan taxonomic diversity in the northeastern East China Sea during the late spring. Seed populations of harmful algal bloom-causing species were discovered in the warm and saline water originating from the Kuroshio, which is particularly important as it indicates that these waters could introduce harmful species that may spread to the Yellow Sea and Korea Strait. Taken together, the study suggests that potential changes to the current systems in the region could dramatically alter the structure of its protistan community.

Evaluation of total leukocytes count by flow cytometry with Beckman Coulter® DXH900 in the presence of platelet aggregates

The Beckman Coulter® DXH900 uses the impedance method to measure the total leukocytes count. In presence of platelet aggregates, the device identifies the structural changes and associates an alarm with the leukocytes result. The aim of this study was to evaluate the influence of platelet aggregates using the principle of flow cytometry as a second assessment of the white blood cell count. Total leukocytes count was evaluated in 49 specimens with presence of platelet aggregates and 32 without anomaly. The differences between total leukocyte count by the two automatic methods (impedance and flow cytometry) and the microscopic method were compared. Without platelet aggregates, the median values were 5.6 (microscopic cell count), 5.4 (impedance) and 5.4 (flow cytometry) and no discordance was observed. In presence of platelet aggregates, the median values were 5.6, 6.4 and 5.1 respectively. The graphical analysis with the allowable total error range of ± 25.7% showed substantial analytical discrepancies (15/49) using impedance method while the flow cytometry method revealed minor disagreements (3/49). Analytical discordances versus WBC reference ranges showed 88% agreement and a substantial Kappa coefficient of 0.70 by impedance, while the flow cytometry method had 94% agreement and a perfect Kappa coefficient of 0.83. The formation of platelet aggregates increased the total leukocyte count performed DXH900 impedance method. Our study has shown that DXH 900 flow cytometry method may be an alternative to exclude the presence of pseudoleukocytosis. In case flags are generated, the microscopic method may be needed for the confirmation of WBC count.

A study of the seasonal and interannual variability of phytoplankton and zooplankton assemblages in a significant marine ecosystem

The eastern Great Australian Bight (GAB) is a significant marine ecosystem, featuring a range of marine mammals and large pelagic fish including blue whales, sharks and tuna. Previous research has classified the region as generally oligotrophic, apart from late austral summer months when seasonal upwelling triggers phytoplankton blooms in the region. Based on multi-year field observations, this study analysed the interannual and interdecadal variability of the plankton community structure in this region. Pigment data indicate that nano- and pico-phytoplankton generally dominated the phytoplankton community structure with averages of 39% and 30% of the total biomass, including a relatively large proportion of nanophytoplankton (cryptophytes, haptophytes and prasinophytes) with cell sizes <5 µm, not resolved in microscopic cell counts. Nano- and pico-phytoplankton alone contributed ∼0.3 mg/m3 to the chlorophyll-a signal and therefore sustained an overall mesotrophic environment year-round. Distinct diatom blooms developed during the upwelling season within concentrated subsurface layers where chlorophyll-a concentrations increased to >1 mg/m3, characterising eutrophic conditions. The biomass of diatoms increased from <10% to ∼30% of total biomass. Diatom blooms coincided with relatively high abundances of three dominant zooplankton species (Oithona similis, Penilia avirostris and Microsetella norvegica) and/or the dinophyta Noctiluca scintillans, but events of high zooplankton abundance also occurred outside the upwelling season. The observational findings also show the occurrence of significant subsurface phytoplankton blooms in late spring, not reported before, that may also contribute to the ecosystem functioning of the region.

High-throughput sequencing and marker pigment analysis of freshwater phytoplankton: A direct comparison with microscopic count data in the tropical crater lakes of Western Uganda

High-throughput DNA sequencing (HTS) and photosynthetic marker-pigment analysis can provide cost-and time-efficient alternatives for morphology-based microscopic identification and counting of lacustrine phytoplankton. However, application of particularly HTS in tropical lakes is still uncommon. We analyzed the community composition of cyanobacterial and eukaryotic phytoplankton in relation to trophic status and other environmental factors in 15 tropical crater lakes in western Uganda, using both high-performance liquid chromatography (HPLC) of photosynthetic marker pigments and HTS of 16 S and 18 S small subunit rRNA genes. We then compared the results with phytoplankton composition data based on microscopic identification and cell counting to evaluate whether the two former methods can be alternative or complementary approaches to analyze these lakes’ phytoplankton communities. HTS recorded 105 operational taxonomic units (OTUs) of cyanobacteria, and 197 OTUs of autotrophic eukaryotes mainly from dinoflagellates, cryptophytes and green algae. Ochrophyta (chrysophytes and diatoms) were present in low abundances only, and the few remaining sequences belonged to Streptophyta and Haptophyta. Marker pigment distribution among samples reflected the widespread and often dominant presence of cyanobacteria (primarily zeaxanthin, myxoxanthophyll and echinenone), followed by green algae (chlorophyll b, lutein, antheraxanthin, neoxanthin) and diatoms (fucoxanthin, diato-diadinoxanthin), and with cryptophyta (alloxanthin) important in some of the lakes. Direct and indirect ordinations of the OTUs and marker pigments revealed that, similar to patterns observed in cell counts, phytoplankton community composition differed between deep oligotrophic lakes and shallower more productive lakes, even though the distribution of cyanobacterial OTUs was more related to lake water conductivity and season than to trophic status. Procrustes analyses of the composition of green algae and Ochrophyta, the two dominant eukaryotic groups, based on HTS data showed patterns significantly similar to composition data based on cell counts, but no significant correlations were found between the complete eukaryotic or cyanobacterial HTS data and cell count data. While the latter discrepancies can be attributed to method-related biases in both HTS and microscopy, in contrast to the microscopic approach HTS failed to identify trophic indicator species and did not assign all lakes to the correct trophic category. Composition data based on marker pigments clustered the 15 lakes according to their trophic level only when pigment abundances were expressed as absolute concentrations, not when expressed as fractional abundances. We attribute this lower discriminating power partly to the wide distribution of cyanobacteria in these tropical crater lakes, besides the pigments’ low taxonomic resolution. Nevertheless, as the compositional patterns in relation to environmental variation observed in marker pigments and OTUs of the dominant eukaryotic phytoplankton groups are similar to those in cell count data, both methods hold potential for ecosystem-level monitoring of tropical crater lakes. However, the high-resolution HTS approach is handicapped by non-uniform amplification of gene sequences, while the low-resolution marker-pigment approach is handicapped by the widespread dominance of cyanobacteria in these systems irrespective of their trophic status.

Comparison of California mastitis test and Draminski mastitis detector as on-farm methods for monitoring udder health in lactating buffalo

This study was conducted to compare the performance of the California Mastitis Test (CMT) and Draminski Mastitis Detector (DMD) for monitoring udder health in lactating buffalo. A total of 647 milk samples collected from 145 apparently healthy lactating buffalo cows during the first three months of the lactation period were used in this study. Both DMD and CMT were performed on-farm directly after sampling of the milk. The diagnostic accuracy of CMT and DMD was evaluated by estimating the area under the Receiver-Operating Characteristic curve (AUC) based on a value of 200,000 somatic cells per mL as a cut-point value for an infected quarter detected by direct microscopic somatic cell count. Data analysis showed that 63.76% of CMT results were “Trace” and 99% of DMD readings were greater than 300. The accuracy of CMT and DMD was close to each other; the AUC was 80.1% and 81.4% for CMT and DMD, respectively. The optimal cut-point value for CMT was Trace (T), and 515 for DMD. In conclusion, both CMT and DMD are practical on-farm tests for identifying infected udder in buffalo cows, and the suggested cut-point value for DMD is 515 for buffalo’s milk testing instead of the 300 that was assigned by the manufacturer for cow’s milk.

Synovial Fluid Analysis to Identify Osteoarthritis.

Synovial fluid (SF) analysis is important in diagnosing osteoarthritis (OA). Macroscopic and microscopic features, including total and differential white blood cell (WBC) count, help define the non-inflammatory nature of SF, which is a hallmark of OA. In patients with OA, WBC in SF samples usually does not exceed 2000 cells per microliter, and the percentage of inflammatory cells, such as neutrophils, is very low or absent. Calcium crystals are frequent in SF collected from OA patients. Although their role in the pathogenesis of OA remains unclear, they have been associated with a mild inflammatory process and a more severe disease progression. Recently, calcium crystals have been described in both the early and late stages of OA, indicating that they may play a vital role in diagnosing different clinical subsets of OA and pharmacological treatment. The overall goal of SF analysis in OA is two-fold: to ascertain the non-inflammatory degree of SF and to highlight the presence of calcium crystals.

Algicidal activity of Morganella morganii against axenic and environmental strains of Microcystis aeruginosa: Compound combination effects

Cyanobacterial harmful algal blooms (cyanoHABs) are a global problem with serious consequences for public health and many sectors of the economy. The use of algicidal bacteria as natural antagonists to control bloom-forming cyanobacteria is a topic of growing interest. However, there are still unresolved questions that need to be addressed to better understand their mode of action and to implement effective mitigation strategies. In this study, thirteen bacterial strains isolated from both scums and concentrated bloom samples exhibited algicidal activity on three Microcystis aeruginosa strains with different characteristics: the axenic microcystin (MC)-producing strain M. aeruginosa PCC7820 (MaPCC7820), and two environmental (non-axenic) M. aeruginosa strains isolated from two different water bodies in Poland, one MC-producer (MaSU) and another non-MC-producer (MaPN). The bacterial strain SU7S0818 exerted the highest average algicidal effect on the three cyanobacterial strains. This strain was identified as Morganella morganii (99.51% similarity) by the 16S rRNA gene analyses; hence, this is the first study that demonstrates the algicidal properties of these ubiquitous bacteria. Microscopic cell counting and qPCR analyses showed that M. morganii SU7S0818 removed 91%, 96%, and 98.5% of MaPCC7820, MaSU and MaPN cells after 6 days of co-culture, respectively. Interestingly, the ultra-high-performance liquid chromatography-tandem mass spectrometer (UHPLC-MS/MS) analyses showed that this bacterium was involved on the release of several substances with algicidal potential. It was remarkable how the profile of some compounds evolved over time, as in the case of cadaverine, tyramine, cyclo[Pro-Gly] and cyclo[Pro-Val]. These dynamic changes could be attributed to the action of M. morganii SU7S0818 and the presence of associated bacteria with environmental cyanobacterial strains. Therefore, this study sheds light on how algicidal bacteria may adapt their action on cyanobacterial cells by releasing a combination of compounds, which is a crucial insight to exploit them as effective biological tools in the control of cyanoHABs.

A rapid fluorescence approach on differentiation of typical dinoflagellate of East China Sea

Detecting the marine phytoplankton by the means of absorption or fluorescence spectra were successfully deployed in the past decades, however, the differentiation are mainly limited in levels of class, such as bacillariophytas, dinophytas, raphidophytes, chlorophytes, cyanobacteria, etc. which are characterized by their specific composition of photosynthetic pigments. To further differentiate the typical dinoflagellate Prorocentrum donghaiense, Amphidinium carterae, Scrippsiella trochoidea, Karenia mikimotoi out of the common diatom Skeletonema costatum and haptonema Phaeocystis globosa at East China Sea, a rapid 3D-fluorescence method equipped with CHEMTAX model were conducted. Initial fluorescence excitation spectra of each algal species (under variable environmental conditions) were captured by 3D-fluorometer first. Then fingerprints of each algae were characterized by ten-point discrete excitation spectrum with the excitation wavelengths of 405, 420, 435, 470, 490, 505, 535, 555, 570 and 590 nm, which closely reflecting the difference of photosynthetic pigments. By equipping with CHEMTAX model, the standard spectra and norm spectra were constructed for FS-CHEMTAX (Fluorescence spectra-CHEMTAX) model to further identify the algal species and estimate the cell density. The developed method performed a better way of identifying the toxic species Amphidinium carterae, Phaeocystis globosa, and Karenia mikimotoi out of the non-toxic ones, with the identification accuracy rates of 83.3%, 90% and 100%, in monocultures, and 77.8%, 90% and 100%, in the bi-mixed cultures, respectively. Meanwhile, the detection limits for the three toxic species were found as low as 250, 1,400 and 120 cells/mL. The concentrations estimated are in good agreement with the microscopic cell counts for all the algae groups (correlation coefficients (R2) exceed 0.8). The relative error of predict concentration was lowest for small cells, i.e., Phaeocystis globosa (10.0%) and Amphidinium carterae (21.1%), but the highest for big cells, i.e. Karenia mikimotoi (41.8%) when the target algae become the dominant species. The overall concentration detection error was no more than one order of magnitude, indicating that this method could provide an important technical support for monitoring the related harmful algal blooms.

Cultivation and characterization of primary human parathyroid cells from patients with severe secondary hyperparathyroidism

To establish an cell model of hyperparathyroidism by isolation, in vitro culture, and identification of parathyroid cells from patients with secondary hyperparathyroidism (SHPT). The parathyroid gland tissues obtained from 10 patients with SHPT were dissociated by collagenase digestion for primary culture of the parathyroid cells. Morphological changes and growth characteristics of the cells were assessed by microscopic imaging and cell counting. The mRNA and protein expression levels of parathyroid hormone (PTH), calcium-sensing receptor (CaSR), and glial cells missing 2 (GCM2) in the primary and passaged cells were determined by immunofluorescence, qRT-PCR, and Western blotting. Primary cultures of parathyroid cells were successfully obtained. The cells exhibited a high expression of PTH shown by immunofluorescence assay and had a population doubling time of approximately 71.61 h. PTH secretion in the second-passage (P2) cells was significantly lower than that in the primary (P0) and first-passage (P1) cells (P < 0.001). Despite a significant downregulation of CaSR mRNA (P=0.017) and protein (P=0.006) in P1 cells as compared with P0 cells, no significant differences were found in mRNA and protein expressions of PTH or GCM2 between the two cell generations. Primary cultures of parathyroid cells isolated from SHPT patients by collagenase digestion show similar biological properties to the cells in vivo.

Autumn blooms and seasonality of the dinoflagellate Unruhdinium penardii in the Han River (Korea) as tracked by morphological and molecular techniques

Abstract Dinoflagellate blooms mainly occur in marine environments, and also occur in freshwater. This study reported the autumn blooms of the freshwater dinoflagellate Unruhdinium penardii var. robustum from the Paldang Reservoir in the Han River, South Korea. Morphological and molecular methods were used to examine 2 years of water samples collected monthly in 2012 and 2019. Environmental factors such as temperature, dissolved oxygen and nutrients showed similar seasonal patterns in 2-year comparisons. The chlorophyll-a and phytoplankton cell concentrations were higher in 2019 than in 2012. Dinoflagellate cells were abundantly detected in autumn, with a maximum of 5.1 × 106 cells·L−1 in 2012 and 3.1 × 106 cells·L−1 in 2019. Of these, the dinoflagellate U. penardii var. robustum was predominant in October 2019. Quantitative polymerase chain reaction assays targeting 28S rDNA of Unruhdinium detected the highest copy numbers (5.1 × 108 copies·L−1 in November 2012 and 8.6 × 108 copies·L−1 in October 2019) in autumn. These patterns matched well with the microscopic cell counts. Canonical correspondence analysis showed that autumn samples were correlated with 28S rDNA of Unruhdinium. These results suggest autumn blooms and seasonality of the dinoflagellate U. penardii var. robustum in the Paldang Reservoir.

Crystal Violet Staining Alone Is Not Adequate to Assess Synergism or Antagonism in Multi-Species Biofilms of Bacteria Associated With Bacterial Vaginosis

Bacterial Vaginosis (BV) involves the presence of a multi-species biofilm adhered to vaginal epithelial cells, but its in-depth study has been limited due to the complexity of the bacterial community, which makes the design of in vitro models challenging. Perhaps the most common experimental technique to quantify biofilms is the crystal violet (CV) staining method. Despite its widespread utilization, the CV method is not without flaws. While biofilm CV quantification within the same strain in different conditions is normally accepted, assessing multi-species biofilms formation by CV staining might provide significant bias. For BV research, determining possible synergism or antagonism between species is a fundamental step for assessing the roles of individual species in BV development. Herein, we provide our perspective on how CV fails to properly quantify an in vitro triple-species biofilm composed of Gardnerella vaginalis, Fannyhessea (Atopobium) vaginae, and Prevotella bivia, three common BV-associated bacteria thought to play key roles in incident BV pathogenesis. We compared the CV method with total colony forming units (CFU) and fluorescence microscopy cell count methods. Not surprisingly, when comparing single-species biofilms, the relationship between biofilm biomass, total number of cells, and total cultivable cells was very different between each tested method, and also varied with the time of incubation. Thus, despite its wide utilization for single-species biofilm quantification, the CV method should not be considered for accurate quantification of multi-species biofilms in BV pathogenesis research.

Evaluating the usability and user experience of phytoplankton cell counter prototype

Microscopic organisms are tiny life forms, often consisting of a single cell, and are very sensitive to change. With conventional microscopic counting of phytoplankton cells being done in many laboratories, it is observed that the enumeration of these tiny organisms is laborious. Given such observation, this paper presents a cell counter prototype as an improvement to the counting process. Combined digital image processing algorithms capacitate the counting. This computer program was housed in a microcontroller with its camera module attached to the eyepiece of a compound microscope. Subsequently, the prototype was evaluated to determine its usability and acceptability rate. A System Usability Scale (SUS) score of 86.5 indicated that the cell counter prototype was 79.20 percent usable, learnable, and acceptable technology in its early stages. Stakeholders will undoubtedly benefit from its labor-saving feature.

Microscopic differential cell count and specific mastitis pathogens in cow milk from compost-bedded pack barns and cubicle barns

Compost bedded pack barns (compost) as a new free walk housing system favorably influence udder health due to improved animal welfare and lying comfort. On the other hand, unfavorable effects on udder health are possible, due to the open bedded pack and the associated larger bacterial content in moisture. For in-depth farming system comparisons, the present study aimed to evaluate the specific cell fractions and mastitis pathogens in milk from cows kept in compost and in conventional cubical barns (cubicle). For milk sample collection we used a repeated measurement data structure of 2,198 udder quarters from 537 Holstein cows kept in six herds (3 in compost and 3 in cubicle). Differential cell counting was conducted including lymphocytes, macrophages and polymorphonuclear leukocytes (PMN). Specific mastitis pathogens comprised major and minor pathogens. Mixed models were applied to infer environmental and cow associated effects on cell fractions and on prevalences for pathogen infections, with specific focus on system × lactation stage, system × milk yield and system × somatic cell count effects. The interaction between system and lactation stage showed significant differences (P < 0.01) between the systems. A significantly smaller number of bacteriologically positive quarters and lower prevalences for minor pathogens were detected in compost compared to cubicle. Least squares means for pathogen prevalences indicated a quite constant proportion of bacteriologically negative udder quarters across milk yield levels in compost, but a slight increase with increasing milk yield in cubicle. Cell fraction responses in both systems differed in relation to the overall bacteriological infection status and farming system particularities. In conclusion, different cell fractions and specific mastitis pathogens should be considered as an indicator for udder health in different production systems, taking into account cow associated factors (lactation stage, milk yield).