Factors affecting timing of hypothyroidism following radioactive iodine therapy (RAIT) for patients with Graves' disease: A 12-month observational study.

BACKGROUND: This retrospective study analyzed factors influencing hypothyroidism development after radioactive iodine therapy for Graves' disease. PATIENTS AND METHODS: Three hundred and three patients with Graves' disease treated with radioactive iodine (RAI) from 2013 to 2022 at two Egyptian hospitals were included. Data collected included demographics, lab values, thyroid imaging, RAI doses, and outcomes. Patients were followed for ≥1 year to assess hypothyroidism onset. RESULTS: At the end of 1 year, around 79.5% of the individuals developed hypothyroidism while 12.5% continued to experience hyperthyroidism. The onset of hypothyroidism occurred earlier in those with thyroid volume (≤75.5 cm 3 ), lower thyroid weight (≤84.7 g), thyroid uptake (≤18.8%), and higher RAI dose/volume (≥0.1022 mCi/ml) ( P  < 0.001). Additionally, there was a correlation between anti-thyroid peroxidase (anti-TPO) antibodies and faster development of hypothyroidism compared to those who were negative for antibodies (2.9 vs 8.9 months, P  = 0.001). When considering factors in analysis it was found that anti-TPO antibodies were the only independent predictor, for developing hypothyroidism (hazard risk 30.47, P  < 0.001). Additionally, thyroid volume and uptake independently predicted successful treatment outcomes ( P  < 0.05). CONCLUSION: Positive anti-TPO antibodies strongly predict hypothyroidism risk after RAI therapy for Graves' disease. Smaller thyroid size, lower uptake, and higher RAI dose/volume correlate with earlier hypothyroidism onset but are less significant predictors than anti-TPO status. Findings can guide RAI therapy personalization to optimize outcomes.

Optimizing classification of diseases through language model analysis of symptoms.

This paper investigated the use of language models and deep learning techniques for automating disease prediction from symptoms. Specifically, we explored the use of two Medical Concept Normalization-Bidirectional Encoder Representations from Transformers (MCN-BERT) models and a Bidirectional Long Short-Term Memory (BiLSTM) model, each optimized with a different hyperparameter optimization method, to predict diseases from symptom descriptions. In this paper, we utilized two distinct dataset called Dataset-1, and Dataset-2. Dataset-1 consists of 1,200 data points, with each point representing a unique combination of disease labels and symptom descriptions. While, Dataset-2 is designed to identify Adverse Drug Reactions (ADRs) from Twitter data, comprising 23,516 rows categorized as ADR (1) or Non-ADR (0) tweets. The results indicate that the MCN-BERT model optimized with AdamP achieved 99.58% accuracy for Dataset-1 and 96.15% accuracy for Dataset-2. The MCN-BERT model optimized with AdamW performed well with 98.33% accuracy for Dataset-1 and 95.15% for Dataset-2, while the BiLSTM model optimized with Hyperopt achieved 97.08% accuracy for Dataset-1 and 94.15% for Dataset-2. Our findings suggest that language models and deep learning techniques have promise for supporting earlier detection and more prompt treatment of diseases, as well as expanding remote diagnostic capabilities. The MCN-BERT and BiLSTM models demonstrated robust performance in accurately predicting diseases from symptoms, indicating the potential for further related research.

Improved prostate cancer diagnosis using a modified ResNet50-based deep learning architecture.

Prostate cancer, the most common cancer in men, is influenced by age, family history, genetics, and lifestyle factors. Early detection of prostate cancer using screening methods improves outcomes, but the balance between overdiagnosis and early detection remains debated. Using Deep Learning (DL) algorithms for prostate cancer detection offers a promising solution for accurate and efficient diagnosis, particularly in cases where prostate imaging is challenging. In this paper, we propose a Prostate Cancer Detection Model (PCDM) model for the automatic diagnosis of prostate cancer. It proves its clinical applicability to aid in the early detection and management of prostate cancer in real-world healthcare environments. The PCDM model is a modified ResNet50-based architecture that integrates faster R-CNN and dual optimizers to improve the performance of the detection process. The model is trained on a large dataset of annotated medical images, and the experimental results show that the proposed model outperforms both ResNet50 and VGG19 architectures. Specifically, the proposed model achieves high sensitivity, specificity, precision, and accuracy rates of 97.40%, 97.09%, 97.56%, and 95.24%, respectively.

Coronary Artery Dissection and Myocarditis Caused by Eosinophilic Granulomatosis with Polyangiitis (EGPA): A Case Report.

Eosinophilic granulomatosis with polyangiitis (EGPA) also referred to as Churg-Strauss syndrome is a rare vasculitis of the small to medium vessels. We present a rare case of acute coronary artery dissection brought on by EGPA, which generally has a poor prognosis. A 41-year-old male with history of bronchial asthma presented to the emergency room with a 2-week history of dyspnea, cough with clear phlegm, and fever. For the past eight months he had experienced episodes with similar symptoms relieved by steroids. CT chest showed bilateral upper lobe patchy opacities with extensive workup for infectious etiology being negative. He had peripheral eosinophilia with sinusitis. He had acute coronary syndrome and Coronary angiogram showed Right coronary artery dissection. After making a diagnosis of EGPA based on American college of Rheumatology criteria, he was successfully treated with high dose immunosuppression. Coronary artery dissection is a fatal and uncommon complication of EGPA which is usually diagnosed postmortem. Early recognition of this condition ante mortem and aggressive treatment can be lifesaving as demonstrated in our case.

Early stent fractures in superficial femoral artery resulting multiple pseudoaneurysm formation within one year: a case report.

BACKGROUND: Though fracture is known complication of stenting, pseudoaneurysm asscoiated with stent fracture is an extremely rare complication. This has previoulsy been described to occur at least one or more years following initial stent placement. Here we present a case of multi-site stent fracture leading to two separate SFA pseudoaneurysms within one year of placement, successfully treated with covered stents. CASE PRESENTATION: A 72-year-old male presented with severe claudication of his left lower extremity (Rutherford 3), found to have long segment SFA chronic total occlusion (CTO). Patient successfully underwent endovascular revascularization. Follow-up duplex ultrasound (US) at one year demonstrated a focus of severe in-stent restenosis (ISR). During repeat angiogram for treatment of the stenosis, stent fracture and pseudoaneurysm was seen in the distal SFA, which was treated successfully with a self-expanding covered stent. Additional stent fractures and pseudoanerusyms were subseuqently identified on follow-up, necessitating a third angiogram, and these were successfully repaired using overlapping covered stents, without further recurrence. CONCLUSIONS: Superficial femoral artery stent fractures leading to pseudoaneurysms are extremely rare, particularly within first year of stent placement. Endovascular repair with covered stents has proven to be an effective treatment option with decreased procedural morbidity compared to surgical repair.

A Case of Herpes Simplex Virus Meningitis in an Immunocompromised Individual: Avoiding Common Diagnostic Pitfalls.

Herpes simplex virus meningoencephalitis (HSV ME) is a severe viral infection that affects the brain and surrounding tissues. It is caused primarily by HSV type 1 (HSV-1) virus. This condition requires prompt recognition and treatment due to its potential for significant morbidity and mortality. We aim to highlight the importance of avoiding common diagnostic pitfalls in identifying HSV meningoencephalitis, especially in immunocompromised individuals. We present a case of a 34-year-old immunocompromised patient with HSV meningoencephalitis, emphasizing key clinical features and diagnostic strategies that helped us reach an accurate diagnosis. By sharing this case, we aim to enhance awareness and improve the management of HSV meningoencephalitis in similar patient populations, leading to better outcomes.

Biosynthesis approach of copper nanoparticles, physicochemical characterization, cefixime wastewater treatment, and antibacterial activities.

The aim of this paper is the green synthesis of copper nanoparticles (Cu NPs) via Quinoa seed extract. X-ray diffraction (XRD) results confirmed the production of the pure crystalline face center cubic system of the Cu NPs with an average crystallite size of 8.41 nm. Infrared spectroscopy (FT-IR) analysis confirmed the capping and stabilization of the Cu NPs bioreduction process. UV visible spectroscopy (UV-Vis). surface plasmon resonance revealed the absorption peak at 324 nm with an energy bandgap of 3.47 eV. Electrical conductivity was conducted assuring the semiconductor nature of the biosynthesized Cu NPs. Morphological analysis was investigated confirming the nano-characteristic properties of the Cu NPs as polycrystalline cubic agglomerated shapes in scanning electron microscopy (SEM) analysis. Transmission electron microscopy (TEM) analysis also was used to assess the cubic shapes at a particle size of 15.1 ± 8.3 nm and a crystallinity index about equal to 2.0. Energy dispersive spectroscopy (EDX) was conducted to investigate the elemental composition of the Cu NPs. As a potential utility of the biosynthesized Cu NPs as nano adsorbents to the removal of the Cefixime (Xim) from the pharmaceutical wastewater; adsorption studies and process parameters were being investigated. The following strategic methodology for maximum Xim removal was conducted to be solution pH 4, Cu NPs dosage 30 mg, Xim concentration 100 mg/L, and absolute temperature 313 K. The maximum monolayer adsorption capacity was 122.9 mg/g according to the Langmuir isothermal model, and the kinetic mechanism was pseudo-second-order. Thermodynamic parameters also were derived as spontaneous chemisorption endothermic processes. Antibacterial activity of the Xim and Xim@Cu NPs was investigated confirming they are highly potent against each Gram-negative and Gram-positive bacterium.

Enhanced Deep Learning Model for Classification of Retinal Optical Coherence Tomography Images.

Retinal optical coherence tomography (OCT) imaging is a valuable tool for assessing the condition of the back part of the eye. The condition has a great effect on the specificity of diagnosis, the monitoring of many physiological and pathological procedures, and the response and evaluation of therapeutic effectiveness in various fields of clinical practices, including primary eye diseases and systemic diseases such as diabetes. Therefore, precise diagnosis, classification, and automated image analysis models are crucial. In this paper, we propose an enhanced optical coherence tomography (EOCT) model to classify retinal OCT based on modified ResNet (50) and random forest algorithms, which are used in the proposed study's training strategy to enhance performance. The Adam optimizer is applied during the training process to increase the efficiency of the ResNet (50) model compared with the common pre-trained models, such as spatial separable convolutions and visual geometry group (VGG) (16). The experimentation results show that the sensitivity, specificity, precision, negative predictive value, false discovery rate, false negative rate accuracy, and Matthew's correlation coefficient are 0.9836, 0.9615, 0.9740, 0.9756, 0.0385, 0.0260, 0.0164, 0.9747, 0.9788, and 0.9474, respectively.

COVID-19-associated MRSA infective endocarditis and mitral valve perforation: a case report.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has emerged as a global pandemic, leading to significant morbidity and mortality. The interplay between COVID-19 and other medical conditions can complicate diagnosis and management, necessitating further exploration. CASE PRESENTATION: This case report presents a patient with COVID-19 who developed infective endocarditis (IE) and mitral valve perforation caused by methicillin-resistant Staphylococcus aureus on a native mitral valve. Notably, the patient did not exhibit typical IE risk factors, such as intravenous drug use. However, he did possess risk factors for bacteremia, including a history of diabetes mellitus and recent steroid use due to the COVID-19 infection. The diagnosis of IE was crucially facilitated by transesophageal echocardiography. CONCLUSIONS: This case highlights the potential association between COVID-19 and the development of infective endocarditis. Prompt evaluation using transesophageal echocardiography is vital when there is a high suspicion of IE in COVID-19 patients. Further research is required to elucidate the precise relationship between COVID-19 and IE.

Quality Improvement Initiative in a Community Hospital to Reduce Central Line Device Utilization Rate.

Background The intensive care unit (ICU) in a community hospital in southwest Minnesota saw a steady increase in central line-associated bloodstream infections (CLABSI) and an increase in the utilization of central lines. The baseline CLABSI rate was 11.36 at the start of the project, which was the highest in the last five years. The corresponding device utilization rate (DUR) was 64%, which increased from a pre-COVID pandemic rate of 45%. Aim The aim of this project was to decrease the ICU DUR by 37.5% from a baseline of 64% to 40% within six months without adversely impacting staff satisfaction. Methods A multidisciplinary team using the define, measure, analyze, improve, and control (DMAIC) methodology reviewed the potential causes of the increased use of central lines in the ICU. The team identified the following major causal themes: process, communication, education, and closed-loop feedback. Once the root causes were determined, suitable countermeasures were identified and implemented to address these barriers. These included reviewing current guidelines, enhanced care team rounding, staff education, and the creation of a vascular access indication algorithm. The team met biweekly to study the current state, determine the future state, evaluate feedback, and guide implementation. Results The pandemic saw a surge in the number of severely ill patients in the ICU, which may have caused an increase in the DUR. The project heightened the awareness of the increased DUR and its impact on the CLABSI rate. The initiation of discussion around this project led to an immediate decline in DUR via increased awareness and focus. As interventions were introduced and implemented, the DUR continued to decrease at a steady rate. Post implementation, the DUR met the project goal of less than 40%. The team continued to track progress and monitor feedback. The DUR continued to meet the goal for three months post implementation. Since the start of the project, there have been no CLABSI events reported. This effort has positively impacted safety and patient outcomes. Conclusions Through a defined process, the central line utilization rate in our ICU was decreased to 37.5% to meet the target goal and has been sustained.

Exploring the effects of pandemics on transportation through correlations and deep learning techniques.

The COVID-19 pandemic has had a significant impact on human migration worldwide, affecting transportation patterns in cities. Many cities have issued "stay-at-home" orders during the outbreak, causing commuters to change their usual modes of transportation. For example, some transit/bus passengers have switched to driving or car-sharing. As a result, urban traffic congestion patterns have changed dramatically, and understanding these changes is crucial for effective emergency traffic management and control efforts. While previous studies have focused on natural disasters or major accidents, only a few have examined pandemic-related traffic congestion patterns. This paper uses correlations and machine learning techniques to analyze the relationship between COVID-19 and transportation. The authors simulated traffic models for five different networks and proposed a Traffic Prediction Technique (TPT), which includes an Impact Calculation Methodology that uses Pearson's Correlation Coefficient and Linear Regression, as well as a Traffic Prediction Module (TPM). The paper's main contribution is the introduction of the TPM, which uses Convolutional Neural Network to predict the impact of COVID-19 on transportation. The results indicate a strong correlation between the spread of COVID-19 and transportation patterns, and the CNN has a high accuracy rate in predicting these impacts.

An Unusual Case of Escherichia Coli Meningitis in an Immunocompetent Adult.

Spontaneous meningitis caused by Gram-negative bacilli is rare in adults. It typically occurs after a neurosurgical procedure or head injury but may also be related to the presence of a neurosurgical device, cerebrospinal fluid (CSF) leak syndrome, or seen in immunosuppressed patients. Escherichia coli (E. coli) is the leading cause of Gram-negative bacilli meningitis. We describe the case of a 47-year-old man who was hospitalized for spontaneous, community-acquired E. coli meningitis, which is unusual to see in an immunocompetent adult. CSF analysis was consistent with bacterial meningitis; his blood culture was positive for E. coli. Within 24 hours of initiation of antibiotics, his status improved.

Case Report of Acute Q Fever with Hepatitis Progressing to Chronic Q Fever with Endocarditis.

A 35-year-old male greenhouse worker presented with myalgia, fatigue, and fever. Initially, he was thought to have an unspecified viral infection and was treated with conservative therapy. However, the patient's symptoms persisted, and he reported additional symptoms of mild abdominal pain and headaches. Laboratory evaluation was significant for elevated liver enzymes. Due to concern for acute hepatitis and persistent fever the patient was hospitalized. During his hospital course, no infectious etiology was found to explain his symptoms. After discharge from the hospital, additional testing showed positive serology for Q fever IgG phase II antibody (1:8192) and phase II antibody IgM (>1:2048). He was treated with doxycycline and had a good clinical response. Upon follow-up, he had worsening Phase I IgG serologies. Transesophageal echo demonstrated vegetations consistent with endocarditis.

The effect of choosing optimizer algorithms to improve computer vision tasks: a comparative study.

Optimization algorithms are used to improve model accuracy. The optimization process undergoes multiple cycles until convergence. A variety of optimization strategies have been developed to overcome the obstacles involved in the learning process. Some of these strategies have been considered in this study to learn more about their complexities. It is crucial to analyse and summarise optimization techniques methodically from a machine learning standpoint since this can provide direction for future work in both machine learning and optimization. The approaches under consideration include the Stochastic Gradient Descent (SGD), Stochastic Optimization Descent with Momentum, Rung Kutta, Adaptive Learning Rate, Root Mean Square Propagation, Adaptive Moment Estimation, Deep Ensembles, Feedback Alignment, Direct Feedback Alignment, Adfactor, AMSGrad, and Gravity. prove the ability of each optimizer applied to machine learning models. Firstly, tests on a skin cancer using the ISIC standard dataset for skin cancer detection were applied using three common optimizers (Adaptive Moment, SGD, and Root Mean Square Propagation) to explore the effect of the algorithms on the skin images. The optimal training results from the analysis indicate that the performance values are enhanced using the Adam optimizer, which achieved 97.30% accuracy. The second dataset is COVIDx CT images, and the results achieved are 99.07% accuracy based on the Adam optimizer. The result indicated that the utilisation of optimizers such as SGD and Adam improved the accuracy in training, testing, and validation stages.

Overlap of diabetic ketoacidosis and hyperosmolar hyperglycemic state.

Diabetic ketoacidosis (DKA) and hyperosmolar hyperglycemia state (HHS) are two life-threatening metabolic complications of diabetes that significantly increase mortality and morbidity. Despite major advances, reaching a uniform consensus regarding the diagnostic criteria and treatment of both conditions has been challenging. A significant overlap between these two extremes of the hyperglycemic crisis spectrum poses an additional hurdle. It has well been noted that a complete biochemical and clinical patient evaluation with timely diagnosis and treatment is vital for symptom resolution. Worldwide, there is a lack of large-scale studies that help define how hyperglycemic crises should be managed. This article will provide a comprehensive review of the pathophysiology, diagnosis, and management of DKA-HHS overlap.

Climate change-related knowledge and attitudes among a sample of the general population in Egypt.

Introduction: Identifying the public awareness and risk perception regarding climate change, are fundamental preliminary steps in determining gaps and paving the way for awareness campaigns that address climate change causes and counteraction mitigation measures. However, few studies were conducted in Egypt; thus, the researchers conducted the current cross-sectional study among a sample of the Egyptian population to identify general knowledge and perception about climate change and its effects, as well as attitudes toward mitigation measures. Methods: An exploratory population-based electronic-open survey, was conducted among 527 members of the general population between January and April 2022, using a convenience sampling technique. A pre-tested 2-page (screen) electronic included three sections: sociodemographic characteristics, global warming/climate change-related knowledge, and attitude toward climate change mitigation. Results: The average global warming knowledge score was 12 ± 3. More than 70% (71.1%) of the participants were knowledgeable (percentage score >70%). Approximately half of the enrolled participants (48.2%) agreed that everyone is vulnerable to the effects of global warming/climate change. More than three-quarters (78.3%) of the participants agreed that carbon emissions from vehicles and industrial methane emissions were the first factors that contributed to climate change, followed by the ozone holes (731%). Global warming/climate change-related knowledge was statistically higher in participants aged of >30 years, married participants, urban residents, highly educated individuals, and employed individuals (p-value ≤ 0.05). Approximately 80% of the participants agreed that responding to the questionnaire drew their attention to the topic of climate change and its effects. More than two-thirds of those polled agreed that increasing public transportation use could help mitigate the effects of climate change/global warming, followed by the materials used and the direction of construction. Conclusion: More than two-thirds of the participants were knowledgeable regarding climate change. Social media and the internet were the main sources of information. However, participants need to get the information in a different way that could help in changing their attitude positively toward the issue of climate change mitigation. The current study recommends the need for various initiatives that work should be launched.

Cardiovascular Complications of Obstructive Sleep Apnea in the Intensive Care Unit and Beyond.

Obstructive sleep apnea (OSA) is a common disease with a high degree of association with and possible etiological factor for several cardiovascular diseases. Patients who are admitted to the Intensive Care Unit (ICU) are incredibly sick, have multiple co-morbidities, and are at substantial risk for mortality. A study of cardiovascular manifestations and disease processes in patients with OSA admitted to the ICU is very intriguing, and its impact is likely significant. Although much is known about these cardiovascular complications associated with OSA, there is still a paucity of high-quality evidence trying to establish causality between the two. Studies exploring the potential impact of therapeutic interventions, such as positive airway pressure therapy (PAP), on cardiovascular complications in ICU patients are also needed and should be encouraged. This study reviewed the literature currently available on this topic and potential future research directions of this clinically significant relationship between OSA and cardiovascular disease processes in the ICU and beyond.

Characterization of plasmid-mediated quinolone resistance genes and extended-spectrum beta-lactamases in non-typhoidal Salmonella enterica isolated from broiler chickens.

Background and Aim: Antibiotic-resistant Salmonella is a public health concern. Fluoroquinolones and extended-spectrum beta-lactams are widely used for the treatment of Salmonella infections. This study focused on the detection of plasmid-mediated quinolone resistance (PMQR) and extended-spectrum beta-lactamase (ESBL) genes among multidrug-resistant (MDR) Salmonella enterica isolated from broilers. Materials and Methods: A total of 40 non-typhoidal S. enterica isolates were collected from 28 broiler chicken farms in four Iraqi Governorates. These isolates were examined for their susceptibility to 10 antimicrobial agents by disk-diffusion method followed by polymerase chain reaction assay for the detection of PMQR determinants and ESBLs genes. Results: Salmonella strains revealed high levels of resistance to the following antibiotics: Nalidixic acid 100%, levofloxacin (LEV) 97.5%, amoxicillin-clavulanic acid 95.0%, tetracycline 92.5%, and nitrofurantoin 80.0%. Otherwise, all isolates were susceptible to cefotaxime and ceftriaxone. All isolates were MDR, with 15 different profiles observed. Among 38 amoxicillin/clavulanic acid-resistant Salmonella isolates, 20 (52.6%) had the blaTEM gene, while blaSHV, blaCTX-M, and blaOXA genes were not detected. Only 5 (12.8%) out of 39 LEV-resistant isolates were positive for qnrB, three of which had blaTEM. No qnrC or qnrD, qnrS, aac(6`)-Ib-cr, qunA, and oqxAB genes were found in any of the tested isolates. Conclusion: This study demonstrates that broiler chickens may be considered a potential source for spreading MDR non-typhoidal Salmonella and ESBL traits in poultry production. Therefore, it is important to continuously monitor ESBL and PMQR genes to avoid the spread of resistant strains in the food chain and impact public health.

Abnormal accumulation of OFD1 in endometrial cancer with poor prognosis inhibits ciliogenesis.

The aim of the present study was to examine primary cilia in endometrial tissue during the menstrual cycle and to clarify their morphological changes with different grades of endometrial cancer. Images of fluorescence immunostaining taken by confocal microscopy were used to count the number of primary cilia in normal endometrium and endometrioid carcinoma Grade 1 and Grade 3 specimens. To examine the association between autophagy and ciliogenesis in endometrioid carcinoma, the expression of p62/Sequestosome-1, a selective substrate for autophagy, and oral-facial-digital syndrome 1 protein (OFD1), a protein associated with ciliogenesis, were examined using images of fluorescence immunostaining taken by confocal microscopy. The level of p62 expression was confirmed by western blotting. In proliferative and secretory endometrial stromal cells, the percentage of cells that were ciliated was 7.2 and 32.7% (95% confidence interval=21.61-39.79; P<0.01), and the length of the primary cilia was 1.24 µm and 2.34 µm (0.92-1.26; P<0.01), respectively. In stromal cells of endometrioid carcinoma Grade 1 and Grade 3, the percentage of ciliated cells was 13.5 and 2.9% (7.89-15.05; P<0.001), and the length of the primary cilia was 2.02 and 1.14 µm (0.76-0.99; P<0.001), respectively. In both normal menstrual cycle tissue and endometrial carcinomas, the percentage of primary cilia was lower and their length was shorter in tissues with higher proliferative potential. The expression of OFD1 was significantly higher in Grade 3 compared with Grade 1 as indicated by quantifying the intensity of the fluorescence images (133-12248; P=0.046). To the best of our knowledge, this is the first study concerning the distribution of primary cilia in normal endometrium and endometrial cancer tissues. Overall, fewer ciliated cells in the highly malignant endometrial cancer tissues may be associated not only to the proliferation of cancer cells, but also to the excessive accumulation of OFD1 due to dysfunctional autophagy.

Abnormal ciliogenesis in decidual stromal cells in recurrent miscarriage.

Primary cilia regulate cellular signaling and are involved in both sensing and transducing extracellular stimuli. A recent study of patients with recurrent miscarriage (RM) identified mutations affecting DYNC2H1, which were involved in ciliary biogenesis. However, there has been no study concerning primary cilia in the decidua. We compared the number and the length of primary cilia in the decidua of 15 patients with unexplained RM with those of 7 pregnant controls who underwent an artificial termination of pregnancy. Immunohistochemistry was performed using antibodies against primary cilia, extravillous trophoblasts (EVTs), macrophages, uterine Natural Killer (uNK) cells, decidual stromal cells, and the activation of TGF-ß and CREB signaling in the decidua of early pregnancy was studied. The density of decidual stromal cells, but not EVTs, macrophages or uNK cells, was found to be significantly higher in the decidua of patients compared to controls. The percentage of ciliated decidual stromal cells was significantly decreased in patients. There was no difference in the primary ciliary length. Regarding TGF-ß signaling, p-Smad2 in these cells was diminished significantly in patients, and most of the TGF-ß-activated decidual stromal cells of both patients and controls had primary cilia. No difference in the activation of CREB was found. Abnormal primary cilia on decidual stromal cells may be one of the explanatory factors for unknown RM. The inactivation of TGF-ß signaling may lead to abnormal ciliogenesis in the decidua.