Verification of different methods used for isolating Salmonella enterica serovar Dublin from cattle feces.

Salmonella enterica serovar Dublin is a cattle-adapted serovar, and some infected cattle can become asymptomatic carriers. Identification of carrier animals is important for preventing the spread of infection within a farm, but low diagnostic sensitivity of the fecal culture method is problematic. In this study, we investigated isolation methods of four S. enterica Dublin strains. Selective enrichment using the tetrathionate broth showed better performance than Rappaport-Vassiliadis R10 broth, but one of the strains was not detectable. Since isolation of such strains by selective enrichment can be difficult, we designed a method using immuno-plates that concentrates S. enterica Dublin by antigen-antibody reaction. Our method is able to detect approximately 200 clony-forming units of S. enterica Dublin in 0.1 g of cattle feces. If S. enterica Dublin was isolated from cattle with clinical signs, the method to identify carriers in the farm should be based on the growth kinetics of the target S. enterica Dublin strain.

Is AI essential? Examining the need for deep learning in image-activated sorting of Saccharomyces cerevisiae.

Artificial intelligence (AI) has become a focal point across a multitude of societal sectors, with science not being an exception. Particularly in the life sciences, imaging flow cytometry has increasingly integrated AI for automated management and categorization of extensive cell image data. However, the necessity of AI over traditional classification methods when extending imaging flow cytometry to include cell sorting remains uncertain, primarily due to the time constraints between image acquisition and sorting actuation. AI-enabled image-activated cell sorting (IACS) methods remain substantially limited, even as recent advancements in IACS have found success while largely relying on traditional feature gating strategies. Here we assess the necessity of AI for image classification in IACS by contrasting the performance of feature gating, classical machine learning (ML), and deep learning (DL) with convolutional neural networks (CNNs) in the differentiation of Saccharomyces cerevisiae mutant images. We show that classical ML could only yield a 2.8-fold enhancement in target enrichment capability, albeit at the cost of a 13.7-fold increase in processing time. Conversely, a CNN could offer an 11.0-fold improvement in enrichment capability at an 11.5-fold increase in processing time. We further executed IACS on mixed mutant populations and quantified target strain enrichment via downstream DNA sequencing to substantiate the applicability of DL for the proposed study. Our findings validate the feasibility and value of employing DL in IACS for morphology-based genetic screening of S. cerevisiae, encouraging its incorporation in future advancements of similar technologies.

Blood Eosinophil Count as a Predictive Biomarker of Chronic Obstructive Pulmonary Disease Exacerbation in a Real-World Setting.

Introduction: Chronic obstructive pulmonary disease (COPD) is the third leading cause of death, and COPD exacerbation worsens the prognosis. Eosinophilic airway inflammation is a COPD phenotype that causes COPD exacerbation and is correlated with peripheral blood eosinophil count. We analyzed real-world data of COPD patients to assess the risk factors of COPD exacerbation focusing on blood eosinophils. Materials and Methods: Patients with COPD who visited our hospital between January 1, 2018, and December 31, 2018, were recruited, and their background information, spirometry data, laboratory test results, and moderate-to-severe exacerbation events during the one-year follow-up period were collected from the electronic medical records and analyzed. The COPD exacerbation risk factors were assessed using univariate and multivariate logistic regression analyses. Results: Twenty-two of 271 (8.1%) patients experienced moderate-to-severe exacerbation. Patients with exacerbation showed worse pulmonary function, and we found that a high blood eosinophil count (≥350 cells/µL; p=0.014), low % FEV1 (<50%; p=0.002), increase in white blood cell (≥9000 cells/µL; p=0.039), and use of home oxygen therapy (p=0.005) were risk factors for future exacerbations. We also found a strong correlation between eosinophil count cut-offs and exacerbation risk (r = 0.89, p < 0.001). On the other hand, there was no relation between exacerbation risk and inhalation therapy for COPD. Conclusion: In a real-world setting, peripheral blood eosinophil count could be a predictor of future COPD exacerbation.

Intelligent sort-timing prediction for image-activated cell sorting.

Intelligent image-activated cell sorting (iIACS) has enabled high-throughput image-based sorting of single cells with artificial intelligence (AI) algorithms. This AI-on-a-chip technology combines fluorescence microscopy, AI-based image processing, sort-timing prediction, and cell sorting. Sort-timing prediction is particularly essential due to the latency on the order of milliseconds between image acquisition and sort actuation, during which image processing is performed. The long latency amplifies the effects of the fluctuations in the flow speed of cells, leading to fluctuation and uncertainty in the arrival time of cells at the sort point on the microfluidic chip. To compensate for this fluctuation, iIACS measures the flow speed of each cell upstream, predicts the arrival timing of the cell at the sort point, and activates the actuation of the cell sorter appropriately. Here, we propose and demonstrate a machine learning technique to increase the accuracy of the sort-timing prediction that would allow for the improvement of sort event rate, yield, and purity. Specifically, we trained an algorithm to predict the sort timing for morphologically heterogeneous budding yeast cells. The algorithm we developed used cell morphology, position, and flow speed as inputs for prediction and achieved 41.5% lower prediction error compared to the previously employed method based solely on flow speed. As a result, our technique would allow for an increase in the sort event rate of iIACS by a factor of ~2.

The Role of miR-217-5p in the Puromycin Aminonucleoside-Induced Morphological Change of Podocytes.

Podocytes, alternatively called glomerular epithelial cells, are terminally differentiated cells that wrap around glomerular capillaries and function as a part of the glomerular filtration barrier in the kidney. Therefore, podocyte injury with morphological alteration and detachment from glomerular capillaries leads to severe proteinuria and subsequent renal failure through glomerulosclerosis. Previous RNA sequencing analysis of primary rat podocytes exposed to puromycin aminonucleoside (PAN), a well-known experimental model of injured podocytes, identified several transcripts as being aberrantly expressed. However, how the expression of these transcripts is regulated remains unclear. MicroRNAs (miRNAs) are small noncoding RNAs that posttranscriptionally inhibit the expression of their target transcripts. In this study, using small RNA sequencing analysis, miR-217-5p was identified as the most upregulated transcript in PAN-treated rat podocytes. MiR-217-5p overexpression in E11 podocyte cells led to shrunken cells with abnormal actin cytoskeletons. Consistent with these changes in cell morphology, gene ontology (GO) enrichment analysis showed that interactive GO terms related to cell morphogenesis were enriched with the predicted targets of miR-217-5p. Of the predicted targets highly downregulated by PAN, Myosin 1d (Myo1d) is a nonmuscle myosin predicted to be involved in actin filament organization and thought to play a role in podocyte morphogenesis and injury. We demonstrated that miR-217-5p targets Myo1d by luciferase assays, qRT-PCR, and Western blotting. Furthermore, we showed that miR-217-5p was present in urine from PAN- but not saline-administrated rats. Taken together, our data suggest that miR-217-5p may serve as a therapeutic target and a biomarker for podocyte injury.

Multimodal imaging analysis of macular dystrophy in patient with maternally inherited diabetes and deafness (MIDD) with m.3243A>G mutation.

Purpose: Maternally inherited diabetes and deafness (MIDD) is caused by a heteroplasmic m.3243A>G mutation in the mitochondrial DNA. The main ocular feature in MIDD is macular dystrophy. The purpose of this study was to identify the phenotypical characteristics of a patient with MIDD by multimodal high-resolution imaging analyses.Methods: A detailed history and ophthalmic examination were performed on a 39-year-old patient with MIDD. Multi-modal imaging included fundus photography, fundus autofluorescence imaging, fluorescein angiography, spectral-domain optical coherence tomography, OCT-angiography, and adaptive optics imaging. The PCR-invader and whole exome sequencing (WES) methods were performed on the DNA of the patient.Results: A 39-year-old woman with sensorineural hearing loss, diabetes mellitus presented with atrophic perifoveal changes and MIDD was suspected. The PCR-invader and WES methods showed that the patient had a m.3243A>G mutation in the mitochondrial DNA with 29% and 16.7% of the heteroplasmy in the peripheral blood, respectively. Morphological analyses revealed that the areas of photoreceptor degeneration and chorioretinal atrophy were present mainly in the perifoveal region. Multifocal ERGs showed that the perifoveal responses were reduced. Goldmann visual field was significant for a cecocentral scotoma in the right eye and an enlarged blind spot in the left eye. The central isopter was constricted bilaterally. The results of high-resolution retinal imaging by AO revealed that the densities of the cone photoreceptor were significantly reduced in the fovea where no obvious atrophy of the RPE and choroid was observed.Conclusions: Our findings indicate that WES analysis can be used to detect the m.3243A>G mutation in the mtDNA. The results of multimodal imaging analyses indicated that the primary dysfunction of the photoreceptors in the fovea might precede the dysfunction of the RPE in patient with MIDD.

Anticancer drug-loaded mesenchymal stem cells for targeted cancer therapy.

Mesenchymal stem cells (MSCs) have a tumor-homing ability-they accumulate inside tumors after systemic injection, and may thus be useful as carriers for tumor-targeting therapy. To use MSCs effectively as an anti-cancer therapy, they must first be functionalized with a large amount of anti-cancer drugs without causing any significant changes to their tumor-tropism. In the present study, we attempted to modify the cell surface of MSCs with doxorubicin-loaded liposomes (DOX-Lips), using the avidin-biotin complex method, and evaluated delivery efficiency and anti-tumor efficacy of DOX-Lip-modified MSCs. The amount of DOX in DOX-Lip-modified C3H10T1/2 cells, a murine mesenchymal stem cell line, was approximately 21.5 pg per cell, with no significant changes to the tumor-tropism of C3H10T1/2 cells. Notably, DOX-Lip-modified C3H10T1/2 cells significantly suppressed the proliferation of firefly luciferase-expressing murine colon adenocarcinoma colon26/fluc cells, compared to DOX-Lips alone. Fluorescent DOX accumulated at the cell contact surface and inside green fluorescence protein-expressing colon26 (colon26/GFP) in co-cultures of DOX-Lip-modified C3H10T1/2 and colon26/GFP cells. This localized distribution was not observed when only DOX-Lips was added to colon26/GFP cells. These results suggest that DOX-Lips are efficiently delivered from DOX-Lip-modified C3H10T1/2 cells to the neighboring colon26 cells. Furthermore, DOX-Lip-modified C3H10T1/2 cells suppressed tumor growth in subcutaneous tumor-bearing mice, and in a lung metastasis mouse model. Taken together, these results indicate that the intercellular delivery of DOX may be enhanced using DOX-Lip-modified MSCs as an efficient carrier system for targeted tumor therapy.

High-resolution photoreceptor imaging analysis of patients with autosomal dominant retinitis pigmentosa (adRP) caused by HK1 mutation.

PURPOSE: The hexokinase 1 (HK1) gene encodes one of the four human hexokinases that play essential roles in glucose metabolism. Recently, several cases of E847K mutation in the HK1 gene were reported to cause inherited retinal dystrophy. The purpose of this study was to identify the phenotypical characteristics of patients with a recurrent E847K mutation in the HK1 gene. METHODS: Three generations of one family with autosomal dominant retinitis pigmentosa were examined. Whole exome sequencing was performed on the DNA. Fundus imaging by an adaptive optics fundus camera was used to obtain high-resolution photoreceptor images. RESULTS: Fundus examination of the proband showed degeneration of the mid-peripheral retina, and SD-OCT images showed an absence of the ellipsoid zone (EZ) and interdigitation zone (IZ) in the parafovea and more peripherally. SD-OCT images of the mother of the proband showed an absence of the EZ and IZ, and fundus autofluorescence images showed hypo-autofluorescence surrounding the macular region. One daughter of the proband had only mild night blindness, however, the density of the cone photoreceptors was reduced in the parafoveal region. Whole exome sequencing identified a heterozygous variant, E847K, in the HK1 gene. This variant was found to co-segregate with the disease in three family members. CONCLUSIONS: Although the systemic phenotypes were found to be associated with the HK1 mutations, only the E847K mutation can cause a non-syndromic photoreceptor degeneration. Our study strengthened the hypothesis that the amino acid E847 might play a critical role in the maintenance of the morphology and function of the photoreceptors.

AI on a chip.

Artificial intelligence (AI) has dramatically changed the landscape of science, industry, defence, and medicine in the last several years. Supported by considerably enhanced computational power and cloud storage, the field of AI has shifted from mostly theoretical studies in the discipline of computer science to diverse real-life applications such as drug design, material discovery, speech recognition, self-driving cars, advertising, finance, medical imaging, and astronomical observation, where AI-produced outcomes have been proven to be comparable or even superior to the performance of human experts. In these applications, what is essentially important for the development of AI is the data needed for machine learning. Despite its prominent importance, the very first process of the AI development, namely data collection and data preparation, is typically the most laborious task and is often a limiting factor of constructing functional AI algorithms. Lab-on-a-chip technology, in particular microfluidics, is a powerful platform for both the construction and implementation of AI in a large-scale, cost-effective, high-throughput, automated, and multiplexed manner, thereby overcoming the above bottleneck. On this platform, high-throughput imaging is a critical tool as it can generate high-content information (e.g., size, shape, structure, composition, interaction) of objects on a large scale. High-throughput imaging can also be paired with sorting and DNA/RNA sequencing to conduct a massive survey of phenotype-genotype relations whose data is too complex to analyze with traditional computational tools, but is analyzable with the power of AI. In addition to its function as a data provider, lab-on-a-chip technology can also be employed to implement the developed AI for accurate identification, characterization, classification, and prediction of objects in mixed, heterogeneous, or unknown samples. In this review article, motivated by the excellent synergy between AI and lab-on-a-chip technology, we outline fundamental elements, recent advances, future challenges, and emerging opportunities of AI with lab-on-a-chip technology or "AI on a chip" for short.

Metabolomics for improved treatment monitoring of phenylketonuria: urinary biomarkers for non-invasive assessment of dietary adherence and nutritional deficiencies.

Management of phenylketonuria (PKU) requires lifelong restriction of phenylalanine (Phe) intake using specialized medical foods to prevent neurocognitive impairment in affected patients. However, dietary adherence is challenging to maintain while ensuring adequate nutrition, which can lead to sub-optimal clinical outcomes. Metabolomics offers a systematic approach to identify new biomarkers of disease progression in PKU when using urine as a surrogate for blood specimens that is more accurate than self-reported diet records. Herein, the plasma and urine metabolome of a cohort of classic PKU patients (median age = 11 years; n = 22) mainly prescribed (78%) a Phe-restricted diet were characterized using multisegment injection-capillary electrophoresis-mass spectrometry (MSI-CE-MS). Overall, there was good mutual agreement between plasma Phe and tyrosine (Tyr) concentrations measured from PKU patients when using an amino acid analyzer based on UPLC-UV as compared to MSI-CE-MS with a mean bias of 12% (n = 82). Longitudinal measurements of recently diagnosed PKU infants (n = 3) revealed good long-term regulation of blood Phe with dietary management, and only occasional episodes exceeding the recommended therapeutic range (>360 µM) unlike older PKU patients. Plasma metabolomic studies demonstrated that non-adherent PKU patients had lower circulating concentrations of Tyr, arginine, 2-aminobutyric acid, and propionylcarnitine (q < 0.05, FDR) that were inversely correlated to Phe (r ≈ -0.600 to -0.830). Nontargeted metabolite profiling also revealed urinary biomarkers associated with poor dietary adherence among PKU patients, including elevated concentrations of catabolites indicative of Phe intoxication (e.g., phenylpyruvic acid, phenylacetylglutamine, hydroxyphenylacetic acid). Additionally, PKU patients with poor blood Phe control had lower excretion of urinary compounds derived from co-metabolism of Tyr due to microbiota activity (e.g., cresol sulfate, phenylsulfate), as well as several metabolites associated with inadequate nutrient intake, including low carnitine and B vitamin status (e.g., folic acid, vitamin B12). Interestingly, an unknown urinary metabolite was strongly correlated with Phe excretion in PKU patients (r = 0.861), which was subsequently identified as imidazole lactic acid when using high resolution MS/MS. Overall, urine profiling offers a non-invasive approach for better treatment monitoring of individual PKU patients, which can also guide the design of novel therapies that improve adherence to Phe-restricted diets without acquired nutritional deficiencies.

Nitrogen isotope pattern in Mongolian larch stands at the southern Eurasian boreal forest boundary.

In the last decades a drastic increase in air temperature but a stable precipitation regime in Mongolia has led to gradual drying conditions. Thus, we evaluated the effect of spatial and climatic characteristics on the soil-plant nitrogen dynamics in three representative larch stands (Larix sibirica) with different geographical and climatic conditions using stable nitrogen isotopes. The results showed significant differences in the soil inorganic N content among sites and consequently a different isotopic composition in the plant-soil system. Litter, bark and wood had the lowest δ15N values for all sites, slightly higher δ15N values for needles, while the highest δ15N values were observed for roots and soil. These differences could be the result of the larch stands age themselves, but were in agreement with the spatial and climatic characteristics of the sites. Based on the δ15N value a higher reliance on ectomycorrhizal fungi (ECMF) was observed in the warmest and driest site, while lower dependency was shown in the cooler northern site with higher soil inorganic N content. In both sites, the rate of air temperature increase has been similar in the last decades; however, their soil-plant N dynamics showed different characteristics.

Evaluation of the effect of the 2011 Tsunami on coastal forests by means of multiple isotopic analyses of tree-rings.

The March 2011 Mega-Tsunami in eastern Japan damaged at different degrees the black pine (Pinus thunbergii) forests along the coast. In order to evaluate the recovery of black pine four years later, tree-ring samples from 9 trees for the period 2002-2014 were analyzed for ring growth and stable isotopes (δ13C, δ15N and δ18O). The results showed that annual tree-ring width decreased approximately 70 % from the year 2011 to 2014 compared to the period previous to the tsunami (2002-2010). The multiple isotopic analyses showed that the reduction in growth was caused by soil salinity that prompted stomatal closure and an abrupt increase of tree-ring δ13C. Sea water deposition in the soil did not affect tree-ring δ18O values. Two years after the tsunami, decreasing tree-ring δ13C values caused by apparently photosynthetic recovery did not translate into radial tree-growth, indicating a possible shift in carbon allocation to foliage and mainly roots as a defense mechanism to sodium toxicity. The dual δ13C-δ18O model explains neither the limited growth nor the subsequent recovery in δ13C. Similarly tree-ring δ15N indicated that there was no difference in nitrogen availability before and after the tsunami, suggesting that nutrients were not a limitation but rather soil salinity.

Long-term drug modification to the surface of mesenchymal stem cells by the avidin-biotin complex method.

Mesenchymal stem cells (MSCs) have various functions, making a significant contribution to tissue repair. On the other hand, the viability and function of MSCs are not lasting after an in vivo transplant, and the therapeutic effects of MSCs are limited. Although various chemical modification methods have been applied to MSCs to improve their viability and function, most of conventional drug modification methods are short-term and unstable and cause cytotoxicity. In this study, we developed a method for long-term drug modification to C3H10T1/2 cells, murine mesenchymal stem cells, without any damage, using the avidin-biotin complex method (ABC method). The modification of NanoLuc luciferase (Nluc), a reporter protein, to C3H10T1/2 cells by the ABC method lasted for at least 14 days in vitro without major effects on the cellular characteristics (cell viability, cell proliferation, migration ability, and differentiation ability). Moreover, in vivo, the surface Nluc modification to C3H10T1/2 cells by the ABC method lasted for at least 7 days. Therefore, these results indicate that the ABC method may be useful for long-term surface modification of drugs and for effective MSC-based therapy.

Reconstitution of active mycobacterial binuclear iron monooxygenase complex in Escherichia coli.

Bacterial binuclear iron monooxygenases play numerous physiological roles in oxidative metabolism. Monooxygenases of this type found in actinomycetes also catalyze various useful reactions and have attracted much attention as oxidation biocatalysts. However, difficulties in expressing these multicomponent monooxygenases in heterologous hosts, particularly in Escherichia coli, have hampered the development of engineered oxidation biocatalysts. Here, we describe a strategy to functionally express the mycobacterial binuclear iron monooxygenase MimABCD in Escherichia coli. Sodium dodecyl sulfate-polyacrylamide gel electrophoretic analysis of the mimABCD gene expression in E. coli revealed that the oxygenase components MimA and MimC were insoluble. Furthermore, although the reductase MimB was expressed at a low level in the soluble fraction of E. coli cells, a band corresponding to the coupling protein MimD was not evident. This situation rendered the transformed E. coli cells inactive. We found that the following factors are important for functional expression of MimABCD in E. coli: coexpression of the specific chaperonin MimG, which caused MimA and MimC to be soluble in E. coli cells, and the optimization of the mimD nucleotide sequence, which led to efficient expression of this gene product. These two remedies enabled this multicomponent monooxygenase to be actively expressed in E. coli. The strategy described here should be generally applicable to the E. coli expression of other actinomycetous binuclear iron monooxygenases and related enzymes and will accelerate the development of engineered oxidation biocatalysts for industrial processes.

The mycobacterial binuclear iron monooxygenases require a specific chaperonin-like protein for functional expression in a heterologous host.

The mimABCD gene clusters in Mycobacterium smegmatis strain mc(2) 155 and Mycobacterium goodii strain 12523 encode binuclear iron monooxygenases that oxidize propane and phenol. In this study, we attempted to express each mimABCD gene cluster in a heterologous host. The actinomycetous strain Rhodococcus opacus B-4, which is phylogenetically close to Mycobacterium, was selected as the host. Each mimABCD gene cluster was cloned into the Rhodococcus-Escherichia coli shuttle vector, pTip-QC2, and then introduced into R. opacus cells. Although whole-cell assays were performed with phenol as a substrate, the transformed R. opacus cells did not oxidize this substrate. SDS/PAGE analysis revealed that the oxygenase large subunit MimA was expressed in the insoluble fraction of R. opacus cells. We found that a gene designated mimG, which lies downstream of mimABCD, exhibits similarity in the amino acid sequence of its product with the products of genes encoding the chaperonin GroEL. When the mimG gene was cloned and coexpressed with each mimABCD gene cluster in R. opacus strain B-4, this host successfully acquired oxidation activity towards phenol. SDS/PAGE and western blotting analyses demonstrated that MimA was clearly soluble when in the presence of MimG. These results indicated that MimG played essential roles in the productive folding of MimA, and that the resulting soluble MimA protein led to the active expression of MimABCD.

Dienogest increases the progesterone receptor isoform B/A ratio in patients with ovarian endometriosis.

BACKGROUND: The resistance of endometriotic tissue to progesterone can be explained by alterations in the distribution of progesterone receptor (PR) and estrogen receptor (ER) isoforms. The aims of this study were to examine the expressions of PR-A, PR-B, ERα and ERß in endometrioma and assess whether these expressions are affected by dienogest or leuprolide acetate (LA) treatment. METHODS: We enrolled 60 females, including 43 patients with endometriosis (14 who received no medical treatment, 13 who received dienogest and 16 who received LA before undergoing laparoscopic surgery) and 17 patients with leiomyoma. The expression levels of PR and ER isoforms in eutopic and ectopic endometrium were assayed with quantitative real-time PCR, and confirmed with immunohistochemistry. RESULTS: A decreased PR-B/PR-A ratio and an increased ERß/ERα ratio were demonstrated in ectopic endometrium derived from females with endometriosis compared with the ratios observed in eutopic endometrium obtained from females without endometriosis. Although LA treatment did not affect the PR-B/PR-A and ERß/ERα ratios, dienogest treatment increased the PR-B/PR-A ratio and decreased the ERß/ERα ratio in patients with endometriomas. CONCLUSIONS: Dienogest may improve progesterone resistance in endometriotic tissue by increasing the relative expressions of PR-B and PR-A, and decreasing the relative expressions of ERß and ERα.

Does advanced-stage endometriosis affect the gene expression of estrogen and progesterone receptors in granulosa cells?

OBJECTIVE: To evaluate how endometriosis affects the expression of estrogen and progesterone receptors mRNA in granulosa cells. DESIGN: Prospective study. SETTING: IVF-ET program at Osaka Medical College. PATIENT(S): Eighteen patients with revised American Fertility Society stage IV endometriosis and 23 patients with tubal infertility without endometriosis. INTERVENTION(S): Granulosa cells obtained from patients with endometriosis were examined for estrogen (ER-ß, ER-α) and progesterone (PR-A, PR-B) receptor mRNA expression ratio against GAPDH. MAIN OUTCOME MEASURE(S): Hormonal environment and clinical outcome were investigated. Expression of ER and PR mRNA were evaluated by StepOne real-time polymerase chain reaction (PCR) analysis. RESULT(S): Total hMG/FSH levels were statistically higher in patients with endometriosis; however, high-quality embryo rates and pregnancy rates were lower in patients with endometriosis than in patients with tubal infertility. Expression of PR-A and ER-α in patients with endometriosis was statistically higher than in patients with tubal infertility. The expression of PRs and ERs in patients with tubal infertility showed a positive correlation; however, it was not identified in the endometriosis group. CONCLUSION(S): The higher PR-A and ER-α gene expression in granulosa cells in patients with endometriosis, compared with patients with tubal infertility, might be a leading cause of ovarian dysfunction due to endometriosis.

Differential contributions of prefrontal and hippocampal dopamine D(1) and D(2) receptors in human cognitive functions.

Dopamine D(1) receptors in the prefrontal cortex (PFC) are important for prefrontal functions, and it is suggested that stimulation of prefrontal D(1) receptors induces an inverted U-shaped response, such that too little or too much D(1) receptor stimulation impairs prefrontal functions. Less is known of the role of D(2) receptors in cognition, but previous studies showed that D(2) receptors in the hippocampus (HPC) might play some roles via HPC-PFC interactions. We measured both D(1) and D(2) receptors in PFC and HPC using positron emission tomography in healthy subjects, with the aim of elucidating how regional D(1) and D(2) receptors are differentially involved in frontal lobe functions and memory. We found an inverted U-shaped relation between prefrontal D(1) receptor binding and Wisconsin Card Sorting Test performance. However, prefrontal D(2) binding has no relation with any neuropsychological measures. Hippocampal D(2) receptor binding showed positive linear correlations not only with memory function but also with frontal lobe functions, but hippocampal D(1) receptor binding had no association with any memory and prefrontal functions. Hippocampal D(2) receptors seem to contribute to local hippocampal functions (long-term memory) and to modulation of brain functions outside HPC ("frontal lobe functions"), which are mainly subserved by PFC, via the HPC-PFC pathway. Our findings suggest that orchestration of prefrontal D(1) receptors and hippocampal D(2) receptors might be necessary for human executive function including working memory.

Enhanced dopamine release by nicotine in cigarette smokers: a double-blind, randomized, placebo-controlled pilot study.

Previous studies of smoking on dopamine release in humans were investigated only in smokers. Using nicotine gum, we examined the effect of nicotine on dopamine release in smokers and non-smokers and its relation to the degree of nicotine dependence. Smokers and non-smokers participated in a double-blind, randomized, placebo-controlled cross-over study. They participated in two PET measurements with [11C]raclopride, in which they received either nicotine or placebo. Changes in [11C]raclopride non-displaceable binding potential (BPND) following nicotine administration were quantified. Smokers showed significant decrease in BP in the striatum following nicotine administration, but non-smokers did not show such a decrease. The BPND difference between the two scanning sessions was correlated with the degree of nicotine dependence. The BPND difference might reflect enhanced dopamine release in smokers and the reinforced effect of nicotine. These data suggest the feasibility of our gum method as well as the importance of the degree of dependence in future studies of the nicotine effect on the dopamine system.