The Identification of Bee Comb Cell Contents Using Semiconductor Gas Sensors.

Beekeeping is an extremely difficult field of agriculture. It requires efficient management of the bee nest so that the bee colony can develop efficiently and produce as much honey and other bee products as possible. The beekeeper, therefore, must constantly monitor the contents of the bee comb. At the University of Warmia and Mazury in Olsztyn, research is being carried out to develop methods for efficient management of the apiary. One of our research goals was to test whether a gas detector (MCA-8) based on six semiconductor sensors-TGS823, TGS826, TGS832, TGS2600, TGS2602, and TGS2603 from the company FIGARO-is able to recognize the contents of bee comb cells. For this purpose, polystyrene and wooden test chambers were created, in which fragments of bee comb with different contents were placed. Gas samples were analyzed from an empty comb, a comb with sealed brood, a comb with open brood, a comb with carbohydrate food in the form of sugar syrup, and a comb with bee bread. In addition, a sample of gas from an empty chamber was tested. The results in two variants were analyzed: (1) Variant 1, the value of 270 s of sensor readings from the sample measurement (exposure phase), and (2) Variant 2, the value of 270 s of sensor readings from the sample measurement (measurement phase) with baseline correction by subtracting the last 600 s of surrounding air measurements (flushing phase). A five-time cross-validation 2 (5xCV2) test and the Monte Carlo cross-validation 25 (trained and tested 25 times) were performed. Fourteen classifiers were tested. The naive Bayes classifier (NB) proved to be the most effective method for distinguishing individual classes from others. The MCA-8 device brilliantly differentiates an empty comb from a comb with contents. It differentiates better between an empty comb and a comb with brood, with results of more than 83%. Lower class accuracy was obtained when distinguishing an empty comb from a comb with food and a comb with bee bread, with results of less than 73%. The matrix of six TGS sensors in the device shows promising versatility in distinguishing between various types of brood and food found in bee comb cells. This capability, though still developing, positions the MCA-8 device as a potentially invaluable tool for enhancing the efficiency and effectiveness of beekeepers in the future.

IGSF1 Deficiency Leads to Reduced TSH Production Independent of Alterations in Thyroid Hormone Action in Male Mice.

Loss of function mutations in IGSF1/Igsf1 cause central hypothyroidism. Igsf1 knockout mice have reduced pituitary thyrotropin-releasing hormone receptor, Trhr, expression, perhaps contributing to the phenotype. Because thyroid hormones negatively regulate Trhr, we hypothesized that IGSF1 might affect thyroid hormone availability in pituitary thyrotropes. Consistent with this idea, IGSF1 coimmunoprecipitated with the thyroid hormone transporter monocarboxylate transporter 8 (MCT8) in transfected cells. This association was impaired with IGSF1 bearing patient-derived mutations. Wild-type IGSF1 did not, however, alter MCT8-mediated thyroid hormone import into heterologous cells. IGSF1 and MCT8 are both expressed in the apical membrane of the choroid plexus. However, MCT8 protein levels and localization in the choroid plexus were unaltered in Igsf1 knockout mice, ruling out a necessary chaperone function for IGSF1. MCT8 expression was low in the pituitary and was similarly unaffected in Igsf1 knockouts. We next assessed whether IGSF1 affects thyroid hormone transport or action, by MCT8 or otherwise, in vivo. To this end, we treated hypothyroid wild-type and Igsf1 knockout mice with exogenous thyroid hormones. T4 and T3 inhibited TSH release and regulated pituitary and forebrain gene expression similarly in both genotypes. Interestingly, pituitary TSH beta subunit (Tshb) expression was consistently reduced in Igsf1 knockouts relative to wild-type regardless of experimental condition, whereas Trhr was more variably affected. Although IGSF1 and MCT8 can interact in heterologous cells, the physiological relevance of their association is not clear. Nevertheless, the results suggest that IGSF1 loss can impair TSH production independently of alterations in TRHR levels or thyroid hormone action.

In-Field Detection of American Foulbrood (AFB) by Electric Nose Using Classical Classification Techniques and Sequential Neural Networks.

American foulbrood is a dangerous bee disease that attacks the sealed brood. It quickly leads to the death of bee colonies. Efficient diagnosis of this disease is essential. As specific odours are produced when larvae rot, it was investigated whether an electronic nose can distinguish between colonies affected by American foulbrood and healthy ones. The experiment was conducted in an apiary with 18 bee families, 9 of which showed symptoms of the disease confirmed by laboratory diagnostics. Three units of the Beesensor V.2 device based on an array of six semiconductor TGS gas sensors, manufactured by Figaro, were tested. Each copy of the device was tested in all bee colonies: sick and healthy. The measurement session per bee colony lasted 40 min and yielded results from four 10 min measurements. One 10-min measurement consisted of a 5 min regeneration phase and a 5 min object-measurement phase. For the experiments, we used both classical classification methods such as k-nearest neighbour, Naive Bayes, Support Vector Machine, discretized logistic regression, random forests, and committee of classifiers, that is, methods based on extracted representative data fragments. We also used methods based on the entire 600 s series, in this study of sequential neural networks. We considered, in this study, six options for data preparation as part of the transformation of data series into representative results. Among others, we used single stabilised sensor readings as well as average values from stable areas. For verifying the quality of the classical classifiers, we used the 25-fold train-and-test method. The effectiveness of the tested methods reached a threshold of 75 per cent, with results stable between 65 and 70 per cent. As an element to confirm the possibility of class separation using an artificial nose, we used applied visualisations of classes. It is clear from the experiments conducted that the artificial nose tested has practical potential. Our experiments show that the approach to the problem under study by sequential network learning on a sequence of data is comparable to the best classical methods based on discrete data samples. The results of the experiment showed that the Beesensor V.2 along with properly selected classification techniques can become a tool to facilitate rapid diagnosis of American foulbrood under field conditions.

Recording the Presence of Peanibacillus larvae larvae Colonies on MYPGP Substrates Using a Multi-Sensor Array Based on Solid-State Gas Sensors.

American foulbrood is a dangerous disease of bee broods found worldwide, caused by the Paenibacillus larvae larvae L. bacterium. In an experiment, the possibility of detecting colonies of this bacterium on MYPGP substrates (which contains yeast extract, Mueller-Hinton broth, glucose, K2HPO4, sodium pyruvate, and agar) was tested using a prototype of a multi-sensor recorder of the MCA-8 sensor signal with a matrix of six semiconductors: TGS 823, TGS 826, TGS 832, TGS 2600, TGS 2602, and TGS 2603 from Figaro. Two twin prototypes of the MCA-8 measurement device, M1 and M2, were used in the study. Each prototype was attached to two laboratory test chambers: a wooden one and a polystyrene one. For the experiment, the strain used was P. l. larvae ATCC 9545, ERIC I. On MYPGP medium, often used for laboratory diagnosis of American foulbrood, this bacterium produces small, transparent, smooth, and shiny colonies. Gas samples from over culture media of one- and two-day-old foulbrood P. l. larvae (with no colonies visible to the naked eye) and from over culture media older than 2 days (with visible bacterial colonies) were examined. In addition, the air from empty chambers was tested. The measurement time was 20 min, including a 10-min testing exposure phase and a 10-min sensor regeneration phase. The results were analyzed in two variants: without baseline correction and with baseline correction. We tested 14 classifiers and found that a prototype of a multi-sensor recorder of the MCA-8 sensor signal was capable of detecting colonies of P. l. larvae on MYPGP substrate with a 97% efficiency and could distinguish between MYPGP substrates with 1-2 days of culture, and substrates with older cultures. The efficacy of copies of the prototypes M1 and M2 was shown to differ slightly. The weighted method with Canberra metrics (Canberra.811) and kNN with Canberra and Manhattan metrics (Canberra. 1nn and manhattan.1nn) proved to be the most effective classifiers.

Diagnosis of Varroosis Based on Bee Brood Samples Testing with Use of Semiconductor Gas Sensors.

Varroosis is a dangerous and difficult to diagnose disease decimating bee colonies. The studies conducted sought answers on whether the electronic nose could become an effective tool for the efficient detection of this disease by examining sealed brood samples. The prototype of a multi-sensor recorder of gaseous sensor signals with a matrix of six semiconductor gas sensors TGS 823, TGS 826, TGS 832, TGS 2600, TGS 2602, and TGS 2603 from FIGARO was tested in this area. There were 42 objects belonging to 3 classes tested: 1st class-empty chamber (13 objects), 2nd class-fragments of combs containing brood sick with varroosis (19 objects), and 3rd class-fragments of combs containing healthy sealed brood (10 objects). The examination of a single object lasted 20 min, consisting of the exposure phase (10 min) and the sensor regeneration phase (10 min). The k-th nearest neighbors algorithm (kNN)-with default settings in RSES tool-was successfully used as the basic classifier. The basis of the analysis was the sensor reading value in 270 s with baseline correction. The multi-sensor MCA-8 gas sensor signal recorder has proved to be an effective tool in distinguishing between brood suffering from varroosis and healthy brood. The five-time cross-validation 2 test (5 × CV2 test) showed a global accuracy of 0.832 and a balanced accuracy of 0.834. Positive rate of the sick brood class was 0.92. In order to check the overall effectiveness of baseline correction in the examined context, we have carried out additional series of experiments-in multiple Monte Carlo Cross Validation model-using a set of classifiers with different metrics. We have tested a few variants of the kNN method, the Naïve Bayes classifier, and the weighted voting classifier. We have verified with statistical tests the thesis that the baseline correction significantly improves the level of classification. We also confirmed that it is enough to use the TGS2603 sensor in the examined context.

The Effectiveness of Varroa destructor Infestation Classification Using an E-Nose Depending on the Time of Day.

Honey bees are subject to a number of stressors. In recent years, there has been a worldwide decline in the population of these insects. Losses raise a serious concern, because bees have an indispensable role in the food supply of humankind. This work is focused on the method of assessment of honey bee colony infestation by Varroa destructor. The approach allows to detect several categories of infestation: "Low", "Medium" and "High". The method of detection consists of two components: (1) the measurements of beehive air using a gas sensor array and (2) classification, which is based on the measurement data. In this work, we indicate the sensitivity of the bee colony infestation assessment to the timing of measurement data collection. It was observed that the semiconductor gas sensor responses to the atmosphere of a defined beehive, collected during 24 h, displayed temporal variation. We demonstrated that the success rate of the bee colony infestation assessment also altered depending on the time of day when the gas sensor array measurement was done. Moreover, it was found that different times of day were the most favorable to detect the particular infestation category. This result could indicate that the representation of the disease in the beehive air may be confounded during the day, due to some interferences. More studies are needed to explain this fact and determine the best measurement periods. The problem addressed in this work is very important for scheduling the beekeeping practices aimed at Varroa destructor infestation assessment, using the proposed method.

Detecting varroosis using a gas sensor system as a way to face the environmental threat.

Colony Collapse Disorder (CCD) is an environmental threat on a global scale due to the irreplaceable role of bees in crop pollination. Varroa destructor (V.d.), a parasite that attacks honeybee colonies, is one of the primary causes of honey bee population decline and the most serious threat to the beekeeping sector. This work demonstrates the possibility of quantitatively determining bee colony infestation by V.d. using gas sensing. The results are based on analysing the experimental data acquired for eighteen bee colonies in field conditions. Their infestation rate was in the 0 to 24.76% range. The experimental data consisted of measurements of beehive air with a semiconductor gas sensor array and the results of bee colony V.d. infestation assessment using a flotation method. The two kinds of data were collected in parallel. Partial Least Square regression was applied to identify the relationship between the highly multivariate measurement data provided by the gas sensor array and the V.d. infestation rate. The quality of the developed quantitative models was very high, as demonstrated by the coefficient of determination exceeding R2 = 0.99. Moreover, the prediction error was <0.6% for V.d. infestation rate predictions based on the measurement data that was unknown to the model. The presented work has considerable novelty. To our knowledge, the ability to determine the V.d. infestation rate of bee colony quantitatively based on beehive air measurements using a semiconductor gas sensor array has not been previously demonstrated.

Classifying the Biological Status of Honeybee Workers Using Gas Sensors.

Honeybee workers have a specific smell depending on the age of workers and the biological status of the colony. Laboratory tests were carried out at the Department of Apiculture at UWM Olsztyn, using gas sensors installed in two twin prototype multi-sensor detectors. The study aimed to compare the responses of sensors to the odor of old worker bees (3-6 weeks old), young ones (0-1 days old), and those from long-term queenless colonies. From the experimental colonies, 10 samples of 100 workers were taken for each group and placed successively in the research chambers for the duration of the study. Old workers came from outer nest combs, young workers from hatching out brood in an incubator, and laying worker bees from long-term queenless colonies from brood combs (with laying worker bee's eggs, humped brood, and drones). Each probe was measured for 10 min, and then immediately for another 10 min ambient air was given to regenerate sensors. The results were analyzed using 10 different classifiers. Research has shown that the devices can distinguish between the biological status of bees. The effectiveness of distinguishing between classes, determined by the parameters of accuracy balanced and true positive rate, of 0.763 and 0.742 in the case of the best euclidean.1nn classifier, may be satisfactory in the context of practical beekeeping. Depending on the environment accompanying the tested objects (a type of insert in the test chamber), the introduction of other classifiers as well as baseline correction methods may be considered, while the selection of the appropriate classifier for the task may be of great importance for the effectiveness of the classification.

IGSF1 Deficiency Results in Human and Murine Somatotrope Neurosecretory Hyperfunction.

CONTEXT: The X-linked immunoglobulin superfamily, member 1 (IGSF1), gene is highly expressed in the hypothalamus and in pituitary cells of the POU1F1 lineage. Human loss-of-function mutations in IGSF1 cause central hypothyroidism, hypoprolactinemia, and macroorchidism. Additionally, most affected adults exhibit higher than average IGF-1 levels and anecdotal reports describe acromegaloid features in older subjects. However, somatotrope function has not yet been formally evaluated in this condition. OBJECTIVE: We aimed to evaluate the role of IGSF1 in human and murine somatotrope function. PATIENTS, DESIGN, AND SETTING: We evaluated 21 adult males harboring hemizygous IGSF1 loss-of-function mutations for features of GH excess, in an academic clinical setting. MAIN OUTCOME MEASURES: We compared biochemical and tissue markers of GH excess in patients and controls, including 24-hour GH profile studies in 7 patients. Parallel studies were undertaken in male Igsf1-deficient mice and wild-type littermates. RESULTS: IGSF1-deficient adult male patients demonstrated acromegaloid facial features with increased head circumference as well as increased finger soft-tissue thickness. Median serum IGF-1 concentrations were elevated, and 24-hour GH profile studies confirmed 2- to 3-fold increased median basal, pulsatile, and total GH secretion. Male Igsf1-deficient mice also demonstrated features of GH excess with increased lean mass, organ size, and skeletal dimensions and elevated mean circulating IGF-1 and pituitary GH levels. CONCLUSIONS: We demonstrate somatotrope neurosecretory hyperfunction in IGSF1-deficient humans and mice. These observations define a hitherto uncharacterized role for IGSF1 in somatotropes and indicate that patients with IGSF1 mutations should be evaluated for long-term consequences of increased GH exposure.

Gas Sensor Array and Classifiers as a Means of Varroosis Detection.

The study focused on a method of detection for bee colony infestation with the Varroa destructor mite, based on the measurements of the chemical properties of beehive air. The efficient detection of varroosis was demonstrated. This method of detection is based on a semiconductor gas sensor array and classification module. The efficiency of detection was characterized by the true positive rate (TPR) and true negative rate (TNR). Several factors influencing the performance of the method were determined. They were: (1) the number and kind of sensors, (2) the classifier, (3) the group of bee colonies, and (4) the balance of the classification data set. Gas sensor array outperformed single sensors. It should include at least four sensors. Better results of detection were attained with a support vector machine (SVM) as compared with the k-nearest neighbors (k-NN) algorithm. The selection of bee colonies was important. TPR and TNR differed by several percent for the two examined groups of colonies. The balance of the classification data was crucial. The average classification results were, for the balanced data set: TPR = 0.93 and TNR = 0.95, and for the imbalanced data set: TP = 0.95 and FP = 0.53. The selection of bee colonies and the balance of classification data set have to be controlled in order to attain high performance of the proposed detection method.

The short mRNA isoform of the immunoglobulin superfamily, member 1 gene encodes an intracellular glycoprotein.

Mutations in the immunoglobulin superfamily, member 1 gene (IGSF1/Igsf1) cause an X-linked form of central hypothyroidism. The canonical form of IGSF1 is a transmembrane glycoprotein with 12 immunoglobulin (Ig) loops. The protein is co-translationally cleaved into two sub-domains. The carboxyl-terminal domain (CTD), which contains the last 7 Ig loops, is trafficked to the plasma membrane. Most pathogenic mutations in IGSF1 map to the portion of the gene encoding the CTD. IGSF1/Igsf1 encodes a variety of transcripts. A little studied, but abundant splice variant encodes a truncated form of the protein, predicted to contain the first 2 Ig loops of the full-length IGSF1. The protein (hereafter referred to as IGSF1 isoform 2 or IGSF1-2) is likely retained in most individuals with IGSF1 mutations. Here, we characterized basic biochemical properties of the protein as a foray into understanding its potential function. IGSF1-2, like the IGSF1-CTD, is a glycoprotein. In both mouse and rat, the protein is N-glycosylated at a single asparagine residue in the first Ig loop. Contrary to earlier predictions, neither the murine nor rat IGSF1-2 is secreted from heterologous or homologous cells. In addition, neither protein associates with the plasma membrane. Rather, IGSF1-2 appears to be retained in the endoplasmic reticulum. Whether the protein plays intracellular functions or is trafficked through the secretory pathway under certain physiologic or pathophysiologic conditions has yet to be determined.

Is IGSF1 involved in human pituitary tumor formation?

IGSF1 is a membrane glycoprotein highly expressed in the anterior pituitary. Pathogenic mutations in the IGSF1 gene (on Xq26.2) are associated with X-linked central hypothyroidism and testicular enlargement in males. In this study, we tested the hypothesis that IGSF1 is involved in the development of pituitary tumors, especially those that produce growth hormone (GH). IGSF1 was sequenced in 21 patients with gigantism or acromegaly and 92 healthy individuals. Expression studies with a candidate pathogenic IGSF1 variant were carried out in transfected cells and immunohistochemistry for IGSF1 was performed in the sections of GH-producing adenomas, familial somatomammotroph hyperplasia, and in normal pituitary. We identified the sequence variant p.N604T, which in silico analysis suggested could affect IGSF1 function, in two male patients and one female with somatomammotroph hyperplasia from the same family. Of 60 female controls, two carried the same variant and seven were heterozygous for other variants. Immunohistochemistry showed increased IGSF1 staining in the GH-producing tumor from the patient with the IGSF1 p.N604T variant compared with a GH-producing adenoma from a patient negative for any IGSF1 variants and with normal control pituitary tissue. The IGSF1 gene appears polymorphic in the general population. A potentially pathogenic variant identified in the germline of three patients with gigantism from the same family (segregating with the disease) was also detected in two healthy female controls. Variations in IGSF1 expression in pituitary tissue in patients with or without IGSF1 germline mutations point to the need for further studies of IGSF1 action in pituitary adenoma formation.

Three novel IGSF1 mutations in four Japanese patients with X-linked congenital central hypothyroidism.

CONTEXT: Congenital central hypothyroidism (C-CH) is a rare disease. We investigated the molecular basis of unexplained C-CH in 4 Japanese boys. PATIENTS AND METHODS: C-CH was diagnosed by low free T4 and/or T3 and low basal TSH concentrations. We used whole-exome sequencing of one patient with C-CH to identify potential disease-causing mutations. Thereafter, PCR direct sequencing was performed to Identify genetic defects underlying C-CH in 3 more patients. We then assessed the effects of mutations identified in the Ig superfamily, member 1 (IGSF1), gene on protein expression and membrane trafficking. RESULTS: All patients had congenital hypothyroidism, and 2 had definitive prolactin deficiency. Two patients were detected by neonatal screening. The other patients were diagnosed by short stature and failure to thrive. We identified a novel nonsense variant in IGSF1 by whole-exome sequencing in patient 1, which was confirmed by PCR direct sequencing (p.R1189X). PCR direct sequencing identified the identical nonsense mutation in patient 2. Patients 3 and 4 harbored distinct missense (p.V1082E) or nonsense (p.Q645X) mutations in IGSF1. The mothers of patients 1, 3, and 4 were heterozygous for these mutations. The R1189X mutant, which lacks the transmembrane domain, failed to traffic to the plasma membrane. V1082E could be observed at the cell surface, but at greatly diminished levels relative to the wild-type form of the protein. The severely truncated Q645X mutant could not be detected by Western blot. CONCLUSION: Our findings provide additional genetic evidence that loss-of-function mutations in IGSF1 cause an X-linked form of C-CH and variable prolactin deficiency.

Loss-of-function mutations in IGSF1 cause an X-linked syndrome of central hypothyroidism and testicular enlargement.

Congenital central hypothyroidism occurs either in isolation or in conjunction with other pituitary hormone deficits. Using exome and candidate gene sequencing, we identified 8 distinct mutations and 2 deletions in IGSF1 in males from 11 unrelated families with central hypothyroidism, testicular enlargement and variably low prolactin concentrations. IGSF1 is a membrane glycoprotein that is highly expressed in the anterior pituitary gland, and the identified mutations impair its trafficking to the cell surface in heterologous cells. Igsf1-deficient male mice show diminished pituitary and serum thyroid-stimulating hormone (TSH) concentrations, reduced pituitary thyrotropin-releasing hormone (TRH) receptor expression, decreased triiodothyronine concentrations and increased body mass. Collectively, our observations delineate a new X-linked disorder in which loss-of-function mutations in IGSF1 cause central hypothyroidism, likely secondary to an associated impairment in pituitary TRH signaling.

Activins regulate 17beta-hydroxysteroid dehydrogenase type I transcription in murine gonadotrope cells.

Activins are pleiotropic members of the TGFbeta superfamily and were initially characterized based on their abilities to stimulate FSH synthesis and secretion by gonadotrope cells of the anterior pituitary gland. Here, we identified the gene encoding the steroidogenic enzyme, 17beta-hydroxysteroid dehydrogenase type I (17beta-HSD1; Hsd17b1), as an activin-responsive gene in immortalized gonadotrope cells, LbetaT2. 17beta-HSD1 catalyzes the conversion of estrone to the more active 17beta-estradiol, and activin A stimulated an increase in this enzymatic activity in these cells. We demonstrated that activins signaled via the type I receptor, activin receptor-like kinase (ALK4), and the intracellular signaling protein, SMAD2, to regulate Hsd17b1 transcription in immediate-early fashion. Critical cis-elements, including a minimal SMAD-binding element, were mapped to within 100 bp of the start of transcription. Activin/ALK4 signaling also regulated Hsd17b1 transcription in both immortalized and primary cultured murine granulosa cells. The promoter regions mediating basal and activin/ALK4-regulated promoter activity were generally conserved across the different cell types. The data show that activin A rapidly regulates Hsd17b1 transcription in gonadotrope and granulosa cells and may thereby regulate local 17beta-estradiol synthesis.

An internal signal sequence directs intramembrane proteolysis of a cellular immunoglobulin domain protein.

Precursor proteolysis is a crucial mechanism for regulating protein structure and function. Signal peptidase (SP) is an enzyme with a well defined role in cleaving N-terminal signal sequences but no demonstrated function in the proteolysis of cellular precursor proteins. We provide evidence that SP mediates intraprotein cleavage of IgSF1, a large cellular Ig domain protein that is processed into two separate Ig domain proteins. In addition, our results suggest the involvement of signal peptide peptidase (SPP), an intramembrane protease, which acts on substrates that have been previously cleaved by SP. We show that IgSF1 is processed through sequential proteolysis by SP and SPP. Cleavage is directed by an internal signal sequence and generates two separate Ig domain proteins from a polytopic precursor. Our findings suggest that SP and SPP function are not restricted to N-terminal signal sequence cleavage but also contribute to the processing of cellular transmembrane proteins.

Phospho-STAT5 expression pattern with the MPL W515L mutation is similar to that seen in chronic myeloproliferative disorders with JAK2 V617F.

Abnormal nuclear megakaryocytic staining for phospho-STAT5 (pSTAT5) correlates with JAK2 V617F mutational status in non-chronic myelogenous leukemia chronic myeloproliferative disorders. However, a proportion of wild-type JAK2 non-chronic myelogenous leukemia chronic myeloproliferative disorders cases also demonstrate this abnormal pSTAT5 expression pattern. We report a patient with a JAK2 V617F-negative myeloproliferative/myelodysplastic syndrome who had abnormal megakaryocytic pSTAT5 expression and a MPL W515L mutation. The patient was a 71-year-old man with anemia and thrombocythemia on laboratory examination. His peripheral blood smear demonstrated occasional dysplastic neutrophils. Bone marrow biopsy revealed hypercellular marrow with features consistent with myeloproliferative/myelodysplastic syndrome. Immunohistochemistry for pSTAT5 showed abnormal nuclear megakaryocyte positivity. Cytogenetic analysis revealed a normal karyotype, fluorescence in situ hybridization for BCR-ABL was negative, and JAK2 genotyping demonstrated wild-type JAK2. However, MPL genotyping showed a MPL W515L mutation. Abnormal nuclear megakaryocytic staining for pSTAT5 expression, previously associated with the JAK2 V617F mutation, is also associated with MPL W515L, likely reflecting activation of the JAK-STAT signaling pathway.