Rare correlation of somatic PRKACA mutations with pregnancy-associated aldosterone- and cortisol-producing adenomas: a case report and literature review.

BACKGROUND: Somatic mutations have been observed to induce aldosterone-producing adenomas (APAs). These may be accelerated during pregnancy. Somatic PRKACA mutations are common in cortisol-producing adenomas (CPAs). However, their role in APAs, particularly aldosterone- and cortisol-producing adenomas (A/CPAs), is not well understood. This study aims to investigate the association between PRKACA mutations and the accelerated development of A/CPAs during pregnancy. CASE PRESENTATION: A patient with primary aldosteronism (PA) associated with severe Cushing's syndrome (CS) underwent surgical resection of an adrenal tumor one year after delivery. Pathologic examination revealed an adrenocortical adenoma characterized primarily by zona glomerulosa hyperplasia. Somatic mutation analysis revealed the presence of the somatic PRKACA mutation, which was validated as a deleterious mutation by various computational databases. Immunohistochemical results showed positive staining for cytochrome P450 family 11 subfamily B member 1 (CYP11B1), cytochrome P450 family 11 subfamily B member 2 (CYP11B2), and luteinizing hormone/chorionic gonadotropin receptor (LHCGR). Our study included a review of 20 previously documented cases of aldosterone- and cortisol-producing adenomas (A/CPAs), two of which were concurrently positive for both CYP11B1 and CYP11B2, consistent with our findings. CONCLUSION: Somatic mutations in PRKACA may correlate with the upregulation of LHCGR, which synergistically drives the accelerated growth of co-secretion tumors during pregnancy, thereby exacerbating disease progression.

Deep learning for intracranial aneurysm segmentation using CT angiography.

OBJECTIVE: This study aimed to employ a two-stage deep learning method to accurately detect small aneurysms (4-10 mm in size) in computed tomography angiography (CTA) images. Methods: This study included 956 patients from 6 hospitals and a public dataset obtained with 6 CT scanners from different manufacturers. The proposed method consists of two components: a lightweight and fast head region selection (HRS) algorithm and an adaptive 3D nnU-Net network, which is used as the main architecture for segmenting aneurysms. Segments generated by the deep neural network were compared with expert-generated manual segmentation results and assessed using Dice scores. Results: The area under the curve (AUC) exceeded 79% across all datasets. In particular, the precision and AUC reached 85.2% and 87.6%, respectively, on certain datasets. The experimental results demonstrated the promising performance of this approach, which reduced the inference time by more than 50% compared to direct inference without HRS. Conclusion: Compared with a model without HRS, the deep learning approach we developed can accurately segment aneurysms by automatically localizing brain regions and can accelerate aneurysm inference by more than 50%. Keywords: Deep Learning, CT Angiography, Aneurisms.

Accurate Whole-Brain Image Enhancement for Low-Dose Integrated PET/MR Imaging Through Spatial Brain Transformation.

Positron emission tomography/magnetic resonance imaging (PET/MRI) systems can provide precise anatomical and functional information with exceptional sensitivity and accuracy for neurological disorder detection. Nevertheless, the radiation exposure risks and economic costs of radiopharmaceuticals may pose significant burdens on patients. To mitigate image quality degradation during low-dose PET imaging, we proposed a novel 3D network equipped with a spatial brain transform (SBF) module for low-dose whole-brain PET and MR images to synthesize high-quality PET images. The FreeSurfer toolkit was applied to derive the spatial brain anatomical alignment information, which was then fused with low-dose PET and MR features through the SBF module. Moreover, several deep learning methods were employed as comparison measures to evaluate the model performance, with the peak signal-to-noise ratio (PSNR), structural similarity (SSIM) and Pearson correlation coefficient (PCC) serving as quantitative metrics. Both the visual results and quantitative results illustrated the effectiveness of our approach. The obtained PSNR and SSIM were 41.96 ±4.91 dB (p<0.01) and 0.9654 ±0.0215 (p<0.01), which achieved a 19% and 20% improvement, respectively, compared to the original low-dose brain PET images. The volume of interest (VOI) analysis of brain regions such as the left thalamus (PCC = 0.959) also showed that the proposed method could achieve a more accurate standardized uptake value (SUV) distribution while preserving the details of brain structures. In future works, we hope to apply our method to other multimodal systems, such as PET/CT, to assist clinical brain disease diagnosis and treatment.

MMCA-NET: A Multimodal Cross Attention Transformer Network for Nasopharyngeal Carcinoma Tumor Segmentation Based on a Total-Body PET/CT System.

Nasopharyngeal carcinoma (NPC) is a malignant tumor primarily treated by radiotherapy. Accurate delineation of the target tumor is essential for improving the effectiveness of radiotherapy. However, the segmentation performance of current models is unsatisfactory due to poor boundaries, large-scale tumor volume variation, and the labor-intensive nature of manual delineation for radiotherapy. In this paper, MMCA-Net, a novel segmentation network for NPC using PET/CT images that incorporates an innovative multimodal cross attention transformer (MCA-Transformer) and a modified U-Net architecture, is introduced to enhance modal fusion by leveraging cross-attention mechanisms between CT and PET data. Our method, tested against ten algorithms via fivefold cross-validation on samples from Sun Yat-sen University Cancer Center and the public HECKTOR dataset, consistently topped all four evaluation metrics with average Dice similarity coefficients of 0.815 and 0.7944, respectively. Furthermore, ablation experiments were conducted to demonstrate the superiority of our method over multiple baseline and variant techniques. The proposed method has promising potential for application in other tasks.

Pulsatile gonadotropin releasing hormone therapy for spermatogenesis in congenital hypogonadotropic hypogonadism patients who had poor response to combined gonadotropin therapy.

Objective: Both pulsatile gonadotropin-releasing hormone (GnRH) and combined gonadotropin therapy are effective to induce spermatogenesis in men with congenital hypogonadotropic hypogonadism (CHH). This study aimed to evaluate the effect of pulsatile GnRH therapy on spermatogenesis in male patients with CHH who had poor response to combined gonadotropin therapy. Materials and methods: Patients who had poor response to combined gonadotropin therapy ≥ 6 months were recruited and shifted to pulsatile GnRH therapy. The rate of successful spermatogenesis, the median time to achieve spermatogenesis, serum gonadotropins, testosterone, and testicular volume were used for data analysis. Results: A total of 28 CHH patients who had poor response to combined gonadotropin (HCG/HMG) therapy for 12.5 (6.0, 17.75) months were recruited and switched to pulsatile GnRH therapy for 10.0 (7.25, 16.0) months. Sperm was detected in 17/28 patients (60.7%). The mean time for the appearance of sperm in semen was 12.0 (7.5, 17.5) months. Compared to those who could not achieve spermatogenesis during pulsatile GnRH therapy, the successful group had a higher level of LH60min (4.32 vs. 1.10 IU/L, P = 0.043) and FSH60min (4.28 vs. 1.90 IU/L, P = 0.021). Testicular size increased during pulsatile GnRH therapy, compared to previous HCG/ HMG therapy (P < 0.05). Conclusion: For CHH patients with prior poor response to one year of HCG/ HMG therapy, switching to pulsatile GnRH therapy may induce spermatogenesis.

WTAP-induced N6-methyladenosine of PD-L1 blocked T-cell-mediated antitumor activity under hypoxia in colorectal cancer.

N6-Methyladenosine (m6A) is a important process regulating gene expression post-transcriptionally. Programmed death ligand 1 (PD-L1) is a major immune inhibitive checkpoint that facilitates immune evasion and is expressed in tumor cells. In this research we discovered that Wilms' tumor 1-associated protein (WTAP) degradation caused by ubiquitin-mediated cleavage in cancer cells (colorectal cancer, CRC) under hypoxia was inhibited by Pumilio homolog 1 (PUM1) directly bound to WTAP. WTAP enhanced PD-L1 expression in a way that was m6A-dependent. m6A "reader," Insulin-like growth factor 2 mRNA-binding protein 2 (IGF2BP2) identified methylated PD-L1 transcripts and subsequently fixed its mRNA. Additionally, we found that T-cell proliferation and its cancer cell-killing effects were prevented by overexpression of WTAP in vitro and in vivo. Overexpression prevented T cells from proliferating and killing CRC by maintaining the expression of PD-L1. Further evidence supporting the WTAP-PD-L1 regulatory axis was found in human CRC and organoid tissues. Tumors with high WTAP levels appeared more responsive to anti-PD1 immunotherapy, when analyzing samples from patients undergoing treatment. Overall, our findings demonstrated a novel PD-L1 regulatory mechanism by WTAP-induced mRNA epigenetic regulation and the possible application of targeting WTAP as immunotherapy for tumor hypoxia.

Volatile fatty acids production from kitchen waste slurry using anaerobic membrane bioreactor via alkaline fermentation with high salinity: Evaluation on process performance and microbial succession.

In this study, a pilot-scale anaerobic membrane bioreactor (AnMBR) was developed to continuously produce volatile fatty acids (VFAs) from kitchen waste slurry under an alkaline condition. The alkaline fermentation effectively suppressed methanogenesis, thus achieving high VFAs production of 60.3 g/L. Acetic acid, propionic acid, and butyric acid accounted for over 95.0 % of the total VFAs. The VFAs yield, productivity, and chemical oxygen demand (COD) recovery efficiency reached 0.5 g/g-CODinfluent, 6.0 kg/m3/d, and 62.8 %, respectively. Moreover, the CODVFAs/CODeffluent ratio exceeded 96.0 %, and the CODVFAs/NH3-N ratio through ammonia distillation reached up to 192.5. The microbial community was reshaped during the alkaline fermentation with increasing salinity. The membrane fouling of the AnMBR was alleviated by chemical cleaning and sludge discharge, and membrane modules displayed a sustained filtration performance. In conclusion, this study demonstrated that high-quality VFAs could be efficiently produced from kitchen waste slurry using an AnMBR process via alkaline fermentation.

In-situ methane enrichment in anaerobic digestion of food waste slurry by nano zero-valent iron: Long-term performance and microbial community succession.

In this work, nano zero-valent iron (nZVI) was added to a lab-scale continuous stirring tank reactor (CSTR) for food waste slurry treatment, and the effect of dosing rate and dosage of nZVI were attempted to be changed. The results showed that anaerobic digestion (AD) efficiency and biomethanation stability were optimum under the daily dosing and dosage of 0.48 g/gTCOD. The average daily methane (CH4) yield reached 495.38 mL/gTCOD, which was 43.65% higher than that at control stage, and the maximum CH4 content reached 95%. However, under single dosing rate conditions, high nZVI concentrations caused microbial cell rupture and loosely bound extracellular polymeric substances (LB-EPS) precipitation degradation. The daily dosing rate promoted the hydrogenotrophic methanogenesis pathway, and the activity of coenzyme F420 increased by 400.29%. The microbial analysis indicated that daily addition of nZVI could promote the growth of acid-producing bacteria (Firmicutes and Bacteroidetes) and methanogens (Methanothrix).

Learning CT-free attenuation-corrected total-body PET images through deep learning.

OBJECTIVES: Total-body PET/CT scanners with long axial fields of view have enabled unprecedented image quality and quantitative accuracy. However, the ionizing radiation from CT is a major issue in PET imaging, which is more evident with reduced radiopharmaceutical doses in total-body PET/CT. Therefore, we attempted to generate CT-free attenuation-corrected (CTF-AC) total-body PET images through deep learning. METHODS: Based on total-body PET data from 122 subjects (29 females and 93 males), a well-established cycle-consistent generative adversarial network (Cycle-GAN) was employed to generate CTF-AC total-body PET images directly while introducing site structures as prior information. Statistical analyses, including Pearson correlation coefficient (PCC) and t-tests, were utilized for the correlation measurements. RESULTS: The generated CTF-AC total-body PET images closely resembled real AC PET images, showing reduced noise and good contrast in different tissue structures. The obtained peak signal-to-noise ratio and structural similarity index measure values were 36.92 ± 5.49 dB (p < 0.01) and 0.980 ± 0.041 (p < 0.01), respectively. Furthermore, the standardized uptake value (SUV) distribution was consistent with that of real AC PET images. CONCLUSION: Our approach could directly generate CTF-AC total-body PET images, greatly reducing the radiation risk to patients from redundant anatomical examinations. Moreover, the model was validated based on a multidose-level NAC-AC PET dataset, demonstrating the potential of our method for low-dose PET attenuation correction. In future work, we will attempt to validate the proposed method with total-body PET/CT systems in more clinical practices. CLINICAL RELEVANCE STATEMENT: The ionizing radiation from CT is a major issue in PET imaging, which is more evident with reduced radiopharmaceutical doses in total-body PET/CT. Our CT-free PET attenuation correction method would be beneficial for a wide range of patient populations, especially for pediatric examinations and patients who need multiple scans or who require long-term follow-up. KEY POINTS: • CT is the main source of radiation in PET/CT imaging, especially for total-body PET/CT devices, and reduced radiopharmaceutical doses make the radiation burden from CT more obvious. • The CT-free PET attenuation correction method would be beneficial for patients who need multiple scans or long-term follow-up by reducing additional radiation from redundant anatomical examinations. • The proposed method could directly generate CT-free attenuation-corrected (CTF-AC) total-body PET images, which is beneficial for PET/MRI or PET-only devices lacking CT image poses.

The potential causal association between systemic lupus erythematosus and endocrine and metabolic disorders in the East Asian population: A bidirectional two-sample Mendelian randomization study.

OBJECTIVES: Observational studies indicate a significant correlation between systemic lupus erythematosus (SLE) and endocrine and metabolic disorders, but the causal association between SLE and endocrine and metabolic disorders remains unclear due to the reverse causality and confounding biases commonly presented in conventional observational research. This study endeavors to uncover the causal association between SLE and three common endocrine and metabolic disorders, including Graves' disease (GD), type 2 diabetes mellitus (T2DM), and osteoporosis (OP). METHODS: We used genome-wide association study data for SLE and three endocrine and metabolic disorders in an East Asian population, employing bidirectional two-sample Mendelian randomization (MR) analysis and sensitivity analysis to ascertain the causal association between SLE and endocrine and metabolic disorders. RESULTS: A multiplicative random-effect inverse-variance weighted approach revealed a significant positive correlation between SLE and an elevated risk of GD with an odds ratio (OR) of 1.12 (95% CI: 1.04-1.22, p < .01), and inverse-variance weighted (IVW) analysis also indicated that SLE increased the risk of OP with an OR of 1.035 (95% CI: 1.003-1.068, p < .05). Additionally, GD causally affected SLE in an IVW analysis after Bonferroni correction, with an OR of 1.33 (95% CI: 1.19-1.49, p < .05/3), but the application of multivariable MR analysis resulted in the absence of a causal association of GD on SLE (OR 1.047, 95% CI: 0.952-1.151, p > .05). Lastly, the robustness and validity of the findings were verified through a sensitivity analysis. CONCLUSIONS: We confirmed that SLE has a causal effect on GD as well as OP, but no evidence exists to substantiate a causal link between SLE and T2DM. Our study offers valuable contributions for uncovering the etiology of SLE and endocrine and metabolic disorders and furthering disease risk research while providing potential targets for disease monitoring and therapeutic intervention.

Few-shot segmentation framework for lung nodules via an optimized active contour model.

BACKGROUND: Accurate segmentation of lung nodules is crucial for the early diagnosis and treatment of lung cancer in clinical practice. However, the similarity between lung nodules and surrounding tissues has made their segmentation a longstanding challenge. PURPOSE: Existing deep learning and active contour models each have their limitations. This paper aims to integrate the strengths of both approaches while mitigating their respective shortcomings. METHODS: In this paper, we propose a few-shot segmentation framework that combines a deep neural network with an active contour model. We introduce heat kernel convolutions and high-order total variation into the active contour model and solve the challenging nonsmooth optimization problem using the alternating direction method of multipliers. Additionally, we use the presegmentation results obtained from training a deep neural network on a small sample set as the initial contours for our optimized active contour model, addressing the difficulty of manually setting the initial contours. RESULTS: We compared our proposed method with state-of-the-art methods for segmentation effectiveness using clinical computed tomography (CT) images acquired from two different hospitals and the publicly available LIDC dataset. The results demonstrate that our proposed method achieved outstanding segmentation performance according to both visual and quantitative indicators. CONCLUSION: Our approach utilizes the output of few-shot network training as prior information, avoiding the need to select the initial contour in the active contour model. Additionally, it provides mathematical interpretability to the deep learning, reducing its dependency on the quantity of training samples.

An interactive nuclei segmentation framework with Voronoi diagrams and weighted convex difference for cervical cancer pathology images.

Objective.Nuclei segmentation is crucial for pathologists to accurately classify and grade cancer. However, this process faces significant challenges, such as the complex background structures in pathological images, the high-density distribution of nuclei, and cell adhesion.Approach.In this paper, we present an interactive nuclei segmentation framework that increases the precision of nuclei segmentation. Our framework incorporates expert monitoring to gather as much prior information as possible and accurately segment complex nucleus images through limited pathologist interaction, where only a small portion of the nucleus locations in each image are labeled. The initial contour is determined by the Voronoi diagram generated from the labeled points, which is then input into an optimized weighted convex difference model to regularize partition boundaries in an image. Specifically, we provide theoretical proof of the mathematical model, stating that the objective function monotonically decreases. Furthermore, we explore a postprocessing stage that incorporates histograms, which are simple and easy to handle and prevent arbitrariness and subjectivity in individual choices.Main results.To evaluate our approach, we conduct experiments on both a cervical cancer dataset and a nasopharyngeal cancer dataset. The experimental results demonstrate that our approach achieves competitive performance compared to other methods.Significance.The Voronoi diagram in the paper serves as prior information for the active contour, providing positional information for individual cells. Moreover, the active contour model achieves precise segmentation results while offering mathematical interpretability.

OIF-Net: An Optical Flow Registration-Based PET/MR Cross-Modal Interactive Fusion Network for Low-Count Brain PET Image Denoising.

The short frames of low-count positron emission tomography (PET) images generally cause high levels of statistical noise. Thus, improving the quality of low-count images by using image postprocessing algorithms to achieve better clinical diagnoses has attracted widespread attention in the medical imaging community. Most existing deep learning-based low-count PET image enhancement methods have achieved satisfying results, however, few of them focus on denoising low-count PET images with the magnetic resonance (MR) image modality as guidance. The prior context features contained in MR images can provide abundant and complementary information for single low-count PET image denoising, especially in ultralow-count (2.5%) cases. To this end, we propose a novel two-stream dual PET/MR cross-modal interactive fusion network with an optical flow pre-alignment module, namely, OIF-Net. Specifically, the learnable optical flow registration module enables the spatial manipulation of MR imaging inputs within the network without any extra training supervision. Registered MR images fundamentally solve the problem of feature misalignment in the multimodal fusion stage, which greatly benefits the subsequent denoising process. In addition, we design a spatial-channel feature enhancement module (SC-FEM) that considers the interactive impacts of multiple modalities and provides additional information flexibility in both the spatial and channel dimensions. Furthermore, instead of simply concatenating two extracted features from these two modalities as an intermediate fusion method, the proposed cross-modal feature fusion module (CM-FFM) adopts cross-attention at multiple feature levels and greatly improves the two modalities' feature fusion procedure. Extensive experimental assessments conducted on real clinical datasets, as well as an independent clinical testing dataset, demonstrate that the proposed OIF-Net outperforms the state-of-the-art methods.

The mystery of transient pregnancy-induced cushing's syndrome: a case report and literature review highlighting GNAS somatic mutations and LHCGR overexpression.

PURPOSE: Transient pregnancy-induced Cushing's syndrome is a rare condition characterized by the manifestation of symptoms solely during pregnancy, which typically resolve spontaneously following delivery or miscarriage. While it has been established that GNAS is associated with adrenal tumors, its specific role in the pathogenesis of pregnancy-induced Cushing's syndrome remains uncertain.This work aims to examine the association between GNAS mutation and pregnancy-induced Cushing's syndrome. METHODS: DNA was extracted from patients' peripheral blood and tumor tissues for whole-exome sequencing (WES) and Sanger sequencing. We used AlphaFold to predict the protein structure of wild-type and mutant GNAS and to make functional predictions, and immunohistochemistry was used to detect disease-associated protein expression. A review and summary of reported cases of transient pregnancy-induced Cushing's syndrome induced by pregnancy was conducted. RESULTS: Using WES, we identified a somatic mutation in GNAS (NM_000516, c.C601T, p.R201C) that was predicted to have a deleterious effect using computational methods, such as AlphaFold. Human chorionic gonadotropin (hCG) stimulation tests had weakly positive results, and immunohistochemical staining of adrenal adenoma tissue also revealed positivity for luteinizing hormone/chorionic gonadotropin receptor (LHCGR) and cytochrome P450 family 11 subfamily B member 1 (CYP11B1). We reviewed 15 published cases of transient Cushing's syndrome induced by pregnancy. Among these cases, immunohistochemical staining of the adrenal gland showed positive LHCGR expression in 3 case reports, similar to our findings. CONCLUSION: Transient pregnancy-induced Cushing's syndrome may be associated with somatic GNAS mutations and altered adrenal pathology due to abnormal activation of LHCGR.

Germline PRKACA amplification-associated primary pigmented nodular adrenocortical disease: a case report and literature review

SUMMARY Primary pigmented nodular adrenocortical disease (PPNAD) is a rare adrenocorticotropin hormone (ACTH)-independent Cushing's syndrome (CS). Pediatric patients with PPNAD typically have unusual skin lesions and slow growth with unknown causes. We present a case of a female Chinese patient with PPNAD caused by the germline PRKACA gene copy number gain of chromosome 19. The patient initially presented with kidney stones, short stature, and obesity. After further testing, it was discovered that the patient had diabetes, mild hypertension, low bone mass, a low ACTH level, and hypercortisolemia, and neither the low-dose or high-dose dexamethasone suppression test was able to inhibit hematuric cortisol, which paradoxically increased. PPNAD was pathologically diagnosed after unilateral adrenalectomy. Chromosome microarrays and whole exon sequencing analyses of the peripheral blood, as well as testing of sectioned adrenal tissue, showed a rise in the copy number of the duplication-containing PRKACA gene on chromosome 19p13.13p13.12, a de novo but not heritable gene defect that causes disease. The clinical signs and symptoms supported the diagnosis of Carney complex (CNC). One significant mechanism of CNC pathogenesis may be the rise in germline PRKACA copy number of chromosome 19. When assessing PPNAD patients for CNC, the possibility of PRKACA gene amplification should be considered. The effect of PRKACA gene amplification on the clinical manifestations of CNC needs to be confirmed by more cases.

Pulsatile gonadotropin releasing hormone therapy for spermatogenesis in congenital hypogonadotropic hypogonadism patients who had poor response to combined gonadotropin therapy

ABSTRACT Objective: Both pulsatile gonadotropin-releasing hormone (GnRH) and combined gonadotropin therapy are effective to induce spermatogenesis in men with congenital hypogonadotropic hypogonadism (CHH). This study aimed to evaluate the effect of pulsatile GnRH therapy on spermatogenesis in male patients with CHH who had poor response to combined gonadotropin therapy. Materials and methods: Patients who had poor response to combined gonadotropin therapy ≥ 6 months were recruited and shifted to pulsatile GnRH therapy. The rate of successful spermatogenesis, the median time to achieve spermatogenesis, serum gonadotropins, testosterone, and testicular volume were used for data analysis. Results: A total of 28 CHH patients who had poor response to combined gonadotropin (HCG/HMG) therapy for 12.5 (6.0, 17.75) months were recruited and switched to pulsatile GnRH therapy for 10.0 (7.25, 16.0) months. Sperm was detected in 17/28 patients (60.7%). The mean time for the appearance of sperm in semen was 12.0 (7.5, 17.5) months. Compared to those who could not achieve spermatogenesis during pulsatile GnRH therapy, the successful group had a higher level of LH60min (4.32 vs. 1.10 IU/L, P = 0.043) and FSH60min (4.28 vs. 1.90 IU/L, P = 0.021). Testicular size increased during pulsatile GnRH therapy, compared to previous HCG/HMG therapy (P < 0.05). Conclusion: For CHH patients with prior poor response to one year of HCG/HMG therapy, switching to pulsatile GnRH therapy may induce spermatogenesis.

Germline PRKACA amplification-associated primary pigmented nodular adrenocortical disease: a case report and literature review.

Primary pigmented nodular adrenocortical disease (PPNAD) is a rare adrenocorticotropin hormone (ACTH)-independent Cushing's syndrome (CS). Pediatric patients with PPNAD typically have unusual skin lesions and slow growth with unknown causes. We present a case of a female Chinese patient with PPNAD caused by the germline PRKACA gene copy number gain of chromosome 19. The patient initially presented with kidney stones, short stature, and obesity. After further testing, it was discovered that the patient had diabetes, mild hypertension, low bone mass, a low ACTH level, and hypercortisolemia, and neither the low-dose or high-dose dexamethasone suppression test was able to inhibit hematuric cortisol, which paradoxically increased. PPNAD was pathologically diagnosed after unilateral adrenalectomy. Chromosome microarrays and whole exon sequencing analyses of the peripheral blood, as well as testing of sectioned adrenal tissue, showed a rise in the copy number of the duplication-containing PRKACA gene on chromosome 19p13.13p13.12, a de novo but not heritable gene defect that causes disease. The clinical signs and symptoms supported the diagnosis of Carney complex (CNC). One significant mechanism of CNC pathogenesis may be the rise in germline PRKACA copy number of chromosome 19. When assessing PPNAD patients for CNC, the possibility of PRKACA gene amplification should be considered. The effect of PRKACA gene amplification on the clinical manifestations of CNC needs to be confirmed by more cases.

Network analysis of emotion regulation and reactivity in adolescents: identifying central components and implications for anxiety and depression interventions.

Difficulties in emotion regulation (DER) and emotion reactivity (ER) are important causes and consequences of psychiatric disorders such as depression and anxiety, and previous research suggests that there are many interactions between them. Understanding the structure of their relationship, and which components may play a key role, will help provide insight into emotion disorders in adolescents and provide guidance for clinical interventions. In this study, we collected data from 483 adolescents and used network analysis methods to explore the relationship between DER and ER, specifically looking for core nodes. The results showed that "limited access to emotion regulation strategies" was the most central node in the network. Furthermore, by adding nodes for depression and anxiety to this network, we found that anxiety had the strongest relationship with ER, while depression had a stronger relationship with DER. Thus, our findings suggest that for anxiety disorders, the strong association with ER highlights a potentially promising area for intervention development, whereas for depression, the association with DER points to the possibility of clarifying emotions and exploring coping strategies, acknowledging the complex interplay between depressive and anxious symptoms.

Acute Thyrotoxic Myopathy Combined with Neck Pain: A Case Report.

INTRODUCTION: Acute thyrotoxic myopathy (ATM) is a rare and potentially lethal complication of thyrotoxicosis. The typical clinical symptoms of ATM are characterized by bulbar paralysis. Reports of the successful treatment of ATM are sporadic due to its low incidence. However, no English literature has reported Chinese patients with ATM and neck pain. Here, we report for the first time a Chinese patient with ATM and neck pain who recovered through large doses of systemic glucocorticoids and one intrathyroidal steroid injection. CASE REPORT: A 23-year-old woman visited our hospital with a two-year history of progressive weakness of her bulbar muscles, hoarseness, cough when swallowing, dysphagia, and a one-month history of recurrent painful swelling of the thyroid gland. She was diagnosed with ATM, chronic thyrotoxic myopathy (CTM), and Graves' ophthalmopathy (GO) due to Graves' disease (GD). After she was treated with a combination of low-dose glucocorticoids, antithyroid drugs (ATDs), propranolol, and ultrasound-guided percutaneous intrathyroidal injection of glucocorticoids, her bulbar paralysis, proximal myopathy, and neck pain simultaneously improved without recurrence during follow-up. To our knowledge, this is the first case report of a patient with ATM, CTM, GD, GO and neck pain treated by administering a combination of low-dose glucocorticoids, one intrathyroidal steroid injection and antithyroid agents. CONCLUSIONS: Clinicians should consider ATM and intervene with aggressive glucocorticoid therapy, and this is the key to reversing the progression of ATM when a patient has bulbar paralysis and thyrotoxic symptoms. Our case report references the clinical diagnosis and treatment of such cases.

Biological Characteristics of Beauveria majiangensis Strain MJ1015 and Optimization of Solid Medium Technology for Sporulation.

The entomopathogenic fungus Beauveria majiangensis strain MJ1015, recently isolated from white grubs on a blueberry farm in Guizhou, China, could be used as a biocontrol agent. As a first step toward determining the effect of different solid culture media, temperature, and pH on colony growth rate and sporulation, we evaluated the optimum solid medium for mycelial growth and conidia production on a commercial scale. Subsequently, we also used single-factor analysis and response surface optimization to optimize the composition of the solid culture medium. On potato dextrose agar (PDA) medium, MJ1015 grew fastest and produced the highest spore yield at 29°C and pH 5. The best solid medium for the growth and sporulation of strain MJ1015 comprised 64.70 g/l of rice, 13.00 g/l of wheat, 0.30 g/l of NaNO3, 0.36 g/l of K2HPO4 · 3H2O, and 1.00 g/l of CaCO3. Rice, NaNO3, and K2HPO4 · 3H2O were the main influencing factors. The predicted value of cultured spores using the optimal medium was 4.56 x 1010 conidia/l. The validation test results showed that the average growth rate of strain MJ1015 on the optimal medium was 85% and 96% faster than that on Sabouraud dextrose agar with yeast extracts medium (SDAY) and PDA, respectively. Sporulation was 43.90 times and 9.65 times of that produced on SDAY and PDA, respectively. Our findings provide a theoretical basis for the commercial production of B. majiangensis to control white grubs.