Adrenal pheochromocytoma impacts three main pathways: cysteine-methionine, pyrimidine, and tyrosine metabolism. / è‚¾ä¸Šè ºå—œé“¬ç»†èƒžç˜¤å½±å“ä¸‰æ¡ä¸»è¦ä»£è°¢é€šè·¯ï¼šåŠèƒ±æ°¨é ¸-è›‹æ°¨é ¸ä»£è°¢ã€å˜§å•¶ä»£è°¢å’Œé ªæ°¨é ¸ä»£è°¢é€šè·¯.

Pheochromocytomas and paragangliomas (PPGLs) cause symptoms by altering the circulation levels of catecholamines and peptide hormones. Currently, the diagnosis of PPGLs relies on diagnostic imaging and the detection of catecholamines. In this study, we used ultra-performance liquid chromatography (UPLC)/quadrupole time-of-flight mass spectrometry (Q-TOF MS) analysis to identify and measure the perioperative differential metabolites in the plasma of adrenal pheochromocytoma patients. We identified differentially expressed genes by comparing the transcriptomic data of pheochromocytoma with the normal adrenal medulla. Through conducting two steps of metabolomics analysis, we identified 111 differential metabolites between the healthy group and the patient group, among which 53 metabolites were validated. By integrating the information of differential metabolites and differentially expressed genes, we inferred that the cysteine-methionine, pyrimidine, and tyrosine metabolism pathways were the three main metabolic pathways altered by the neoplasm. The analysis of transcription levels revealed that the tyrosine and cysteine-methionine metabolism pathways were downregulated in pheochromocytoma, whereas the pyrimidine pathway showed no significant difference. Finally, we developed an optimized diagnostic model of two metabolites, L-dihydroorotic acid and vanylglycol. Our results for these metabolites suggest that they may serve as potential clinical biomarkers and can be used to supplement and improve the diagnosis of pheochromocytoma.

Adrenal pheochromocytoma impacts three main pathways: cysteine-methionine, pyrimidine, and tyrosine metabolism. / è‚¾ä¸Šè ºå—œé“¬ç»†èƒžç˜¤å½±å“ä¸‰æ¡ä¸»è¦ä»£è°¢é€šè·¯ï¼šåŠèƒ±æ°¨é ¸-è›‹æ°¨é ¸ä»£è°¢ã€å˜§å•¶ä»£è°¢å’Œé ªæ°¨é ¸ä»£è°¢é€šè·¯.

Pheochromocytomas and paragangliomas (PPGLs) cause symptoms by altering the circulation levels of catecholamines and peptide hormones. Currently, the diagnosis of PPGLs relies on diagnostic imaging and the detection of catecholamines. In this study, we used ultra-performance liquid chromatography (UPLC)/quadrupole time-of-flight mass spectrometry (Q-TOF MS) analysis to identify and measure the perioperative differential metabolites in the plasma of adrenal pheochromocytoma patients. We identified differentially expressed genes by comparing the transcriptomic data of pheochromocytoma with the normal adrenal medulla. Through conducting two steps of metabolomics analysis, we identified 111 differential metabolites between the healthy group and the patient group, among which 53 metabolites were validated. By integrating the information of differential metabolites and differentially expressed genes, we inferred that the cysteine-methionine, pyrimidine, and tyrosine metabolism pathways were the three main metabolic pathways altered by the neoplasm. The analysis of transcription levels revealed that the tyrosine and cysteine-methionine metabolism pathways were downregulated in pheochromocytoma, whereas the pyrimidine pathway showed no significant difference. Finally, we developed an optimized diagnostic model of two metabolites, L-dihydroorotic acid and vanylglycol. Our results for these metabolites suggest that they may serve as potential clinical biomarkers and can be used to supplement and improve the diagnosis of pheochromocytoma.

Progranulin Facilitates Corneal Repair Through Dual Mechanisms of Inflammation Suppression and Regeneration Promotion.

The cornea serves as a vital protective barrier for the eye; however, it is prone to injury and damage that can disrupt corneal epithelium and nerves, triggering inflammation. Therefore, understanding the biological effects and molecular mechanisms involved in corneal wound healing and identifying drugs targeting these pathways is crucial for researchers in this field. This study aimed to investigate the therapeutic potential of progranulin (PGRN) in treating corneal injuries. Our findings demonstrated that PGRN significantly enhanced corneal wound repair by accelerating corneal re-epithelialization and re-innervation. In vitro experiments with cultured epithelial cells and trigeminal ganglion cells further revealed that PGRN stimulated corneal epithelial cell proliferation and promoted axon growth in trigeminal ganglion cells. Through RNA-sequencing (RNA-seq) analysis and other experimental techniques, we discovered that PGRN exerted its healing effects modulating Wnt signaling pathway, which played a critical role in repairing epithelial cells and promoting axon regeneration in trigeminal neurons. Importantly, our study highlighted the anti-inflammatory properties of PGRN by inhibiting the NF-κB signaling pathway, leading to decreased infiltration of macrophages. In conclusion, our findings underscored the potential of PGRN in facilitating corneal wound healing by promoting corneal epithelial cell proliferation, trigeminal ganglion cell axon regeneration, and suppressing ocular inflammation. These results suggest that PGRN could potentially expedite the healing process and improve visual outcomes in patients with corneal injuries.

A case of primary aldosteronism with rhabdomyolysis in which the first symptoms were thyrotoxicosis and peripheral paralysis and literature review.

Background: Primary aldosteronism (PA) is one of the main causes of secondary endocrine hypertension, especially refractory hypertension. Increased autonomous secretion leads to increased blood pressure and proinflammatory effects on different organ systems, including the cardiovascular system. However, because of its diverse clinical manifestations or the combination of other conditions, it sometimes causes problems for correct diagnosis. Therefore, we report and review the characteristics of some atypical and uncommon special case cases related to proaldosterone to provide clinical ideas for correct diagnosis and decision-making of proaldosterone. Case Description: A 38-year-old male patient with fatigue and bilateral lower extremity pain came to the clinic and was found to have abnormal thyroid function, low blood potassium, elevated blood pressure, and also combined with rhabdomyolysis (RM) after further improvement of functional tests and imaging tests was diagnosed with an adrenal cortical adenoma (aldosteronism), hypertension secondary to PA, hypokalemia secondary to PA, RM, and subacute thyroiditis. After laparoscopic resection of a unilateral adrenal adenoma, the patient's blood pressure and blood potassium gradually returned to normal, and thyroid function returned to normal without additional intervention. Conclusions: Early screening should be performed for the high-risk population of PA to prevent the occurrence of RM and other serious complications caused by the progression of the disease. For patients with RM, the primary disease should be approached radically and should be based on symptomatic treatment. For RM syndrome associated with thyroid dysfunction, the etiology of the thyroid dysfunction should be actively identified to guide appropriate clinical management.

The cGAS-STING pathway-dependent sensing of mitochondrial DNA mediates ocular surface inflammation.

The innate immune response is the main pathophysiological process of ocular surface diseases exposed to multiple environmental stresses. The epithelium is central to the innate immune response, but whether and how innate immunity is initiated by ocular epithelial cells in response to various environmental stresses in ocular surface diseases, such as dry eye, is still unclear. By utilizing two classic experimental dry eye models-a mouse ocular surface treated with benzalkonium chloride (BAC) and a mouse model with surgically removed extraorbital lachrymal glands, as well as dry eye patient samples-along with human corneal epithelial cells (HCE) exposed to hyperosmolarity, we have discovered a novel innate immune pathway in ocular surface epithelial cells. Under stress, mitochondrial DNA (mtDNA) was released into the cytoplasm through the mitochondrial permeability transition pore (mPTP) and further activated the cyclic GMP-AMP synthase (cGAS)-stimulator of interferon genes (STING) pathway, aggravating downstream inflammatory responses and ocular surface damage. Genetic deletion or pharmacological suppression of STING and inhibition of mtDNA release reduced inflammatory responses, whereas mtDNA transfection supported cytoplasmic mtDNA-induced inflammatory responses by activating the cGAS-STING pathway. Our study clarified the cGAS-STING pathway-dependent sensing of mitochondrial DNA-mediated ocular surface inflammation, which elucidated a new mechanism of ocular surface diseases in response to multiple environmental stresses.

High-throughput and specific detection of microorganisms by intelligent modular fluorescent photoelectric microbe detector.

Food safety has emerged as a major global issue. Detecting foodborne pathogenic microorganisms and controlling them is vital to guard against foodborne diseases caused by microorganisms. However, the current detection methods need to meet the demand for real-time detection on the spot after a simple operation. Considering unresolved challenges, we developed an Intelligent Modular Fluorescent Photoelectric Microbe (IMFP) system containing a special detection reagent. This IMFP system can automatically monitor microbial growth in which the photoelectric detection, temperature control, fluorescent probe, and bioinformatics screen are integrated into one platform and employed to detect pathogenic microorganisms. Moreover, a specific culture medium was also developed, which matched the system platform for Coliform bacteria and Salmonella typhi. The developed IMFP system could attain a limit of detection (LOD) of about 1 CFU/mL for both bacteria, while the selectivity could reach 99%. In addition, the IMFP system was applied to detect 256 bacterial samples simultaneously. This platform reflects the high-throughput needs of fields for microbial identification and related requirements, such as the development of pathogenic microbial diagnostic reagents, antibacterial sterilization performance tests, and microbial growth kinetics. The IMFP system also confirmed the other merits, such as high sensitivity, high-throughput, and operation simplicity compared to conventional methods, and it has a high potential as a tool for application in the health and food security fields.

An Efficient Deep Learning-Based High-Definition Image Compressed Sensing Framework for Large-Scene Construction Site Monitoring.

High-definition images covering entire large-scene construction sites are increasingly used for monitoring management. However, the transmission of high-definition images is a huge challenge for construction sites with harsh network conditions and scarce computing resources. Thus, an effective compressed sensing and reconstruction method for high-definition monitoring images is urgently needed. Although current deep learning-based image compressed sensing methods exhibit superior performance in recovering images from a reduced number of measurements, they still face difficulties in achieving efficient and accurate high-definition image compressed sensing with less memory usage and computational cost at large-scene construction sites. This paper investigated an efficient deep learning-based high-definition image compressed sensing framework (EHDCS-Net) for large-scene construction site monitoring, which consists of four parts, namely the sampling, initial recovery, deep recovery body, and recovery head subnets. This framework was exquisitely designed by rational organization of the convolutional, downsampling, and pixelshuffle layers based on the procedures of block-based compressed sensing. To effectively reduce memory occupation and computational cost, the framework utilized nonlinear transformations on downscaled feature maps in reconstructing images. Moreover, the efficient channel attention (ECA) module was introduced to further increase the nonlinear reconstruction capability on downscaled feature maps. The framework was tested on large-scene monitoring images from a real hydraulic engineering megaproject. Extensive experiments showed that the proposed EHDCS-Net framework not only used less memory and floating point operations (FLOPs), but it also achieved better reconstruction accuracy with faster recovery speed than other state-of-the-art deep learning-based image compressed sensing methods.

Fluorescent Probe Combined with Photoelectric Analysis Technology for Detection of Escherichia coli.

Food safety is facing great challenges in preventing foodborne diseases caused by pathogenic pollution, especially in resource-limited areas. The rapid detection technique of microorganisms, such as immunological methods and molecular biological methods, plays a crucial key in timely bioanalysis and disease treatment strategies. However, it is difficult for these methods to simultaneously meet the criteria of simple operation, high specificity, and sensitivity, as well as low cost. Coconut water is known as the "water of life" in Hainan. It is a refreshing and nutritious beverage which is widely consumed due to its beneficial properties to health. Coconut water processing is an important pillar industry in Hainan. The detection of pathogenic microorganisms, such as Escherichia coli, in coconut water has become an important factor which has restricted the upgrading and development of this industry. Based on the needs of industrial development, we developed a microbial photoelectric detection system which was composed of a fluorescent probe detection reagent and a photoelectric sensor detection device. This system combined microbial enzyme targets, selective fluorescent substrate metabolism characteristics, and a photoelectric sensor signal transduction mechanism, which produce a strong signal with a high signal-to-noise ratio. The microbial detection system developed here has a simple structure, simple and convenient operation, short detecting time (≥2 h), and high sensitivity (1 CFU/mL). This system may also enable early warning and monitoring programs for other pathogenic microorganisms in order to promote the overall competitiveness of the Hainan coconut water industry.

AES-CSFS: an automatic evaluation system for corneal sodium fluorescein staining based on deep learning.

Background: Corneal fluorescein sodium staining is a valuable diagnostic method for various ocular surface diseases. However, the examination results are highly dependent on the subjective experience of ophthalmologists. Objectives: To develop an artificial intelligence system based on deep learning to provide an accurate quantitative assessment of sodium fluorescein staining score and the size of cornea epithelial patchy defect. Design: A prospective study. Methods: We proposed an artificial intelligence system for automatically evaluating corneal staining scores and accurately measuring patchy corneal epithelial defects based on corneal fluorescein sodium staining images. The design incorporates two segmentation models and a classification model to forecast and assess the stained images. Meanwhile, we compare the evaluation findings from the system with ophthalmologists with varying expertise. Results: For the segmentation task of cornea boundary and cornea epithelial patchy defect area, our proposed method can achieve the performance of dice similarity coefficient (DSC) is 0.98/0.97 and Hausdorff distance (HD) is 3.60/8.39, respectively, when compared with the manually labeled gold standard. This method significantly outperforms the four leading algorithms (Unet, Unet++, Swin-Unet, and TransUnet). For the classification task, our algorithm achieves the best performance in accuracy, recall, and F1-score, which are 91.2%, 78.6%, and 79.2%, respectively. The performance of our developed system exceeds seven different approaches (Inception, ShuffleNet, Xception, EfficientNet_B7, DenseNet, ResNet, and VIT) in classification tasks. In addition, three ophthalmologists were selected to rate corneal staining images. The results showed that the performance of our artificial intelligence system significantly outperformed the junior doctors. Conclusion: The system offers a promising automated assessment method for corneal fluorescein staining, decreasing incorrect evaluations caused by ophthalmologists' subjective variance and limited knowledge.

Visualization and metabolome for the migration and distribution behavior of pesticides residue in after-ripening of banana.

Exploring the behavior of pesticide residues in fruits is important for effectively applying pesticides and minimizing the risk of pesticide exposure to humans. However, most studies do not consider in situ visual analysis of residues and migration patterns in fresh fruit samples. We investigated the migration patterns of thiram, propamocarb, imidacloprid and pyraclostrobin in fresh bananas based on ambient mass spectrometry imaging, metabolome and transcriptome analysis. The systemic pesticides entered via lateral penetration and vertical migration over time, which began to internally migrate to the inner core after 6 h. The non-systemic pesticide thiram did not enter the interior of the bananas, and remained only in the peel. The transportation rate of the pesticides increased with the decrease of water-octanol partition coefficient and the relative molecular mass. Moreover, the pesticide migrated fast with the increase of banana ripeness. The pesticides significantly enhanced pyruvate kinase, NADP-dependent malic enzyme, and malate synthase activities in the banana peels through carbohydrate metabolism. The banana pulp was also protected against the external toxicity of pesticides by the ascorbate-glutathione cycle. These results can provide guidelines for the appropriate application of pesticides and their safety evaluation.

Early prediction of pathological complete response to neoadjuvant chemotherapy combining DCE-MRI and apparent diffusion coefficient values in breast Cancer.

INTRODUCTION: Improving the early prediction of neoadjuvant chemotherapy (NAC) efficacy in breast cancer can lead to an improved prediction of the final prognosis of patients, which would be useful for promoting individualized treatment. This study aimed to explore the value of the combination of dynamic contrast-enhanced (DCE)-MRI parameters and apparent diffusion coefficient (ADC) values in the early prediction of pathological complete response (pCR) to NAC for breast cancer. METHODS: A total of 119 (range, 28-69 years) patients with biopsy-proven breast cancer who received two cycles of NAC before breast surgery were retrospectively enrolled from our hospital database. Patients were divided into pCR and non pCR groups according to their pathological responses; a total of 24 patients achieved pCR, while 95 did not. The quantitative (Ktrans; Kep; Ve; IAUC) and semiquantitative parameters (W-in; W-out; TTP) of DCE-MRI that were significantly different between groups were combined with ADC values to explore their value in the early prediction of pCR to NAC for breast cancer. The independent T test was performed to compare the differences in DCE-MRI parameters and ADC values between the two groups. Receiver operating characteristic (ROC) curves were plotted, and the area under the ROC curve (AUC), sensitivity and specificity were calculated to evaluate the performance of the prediction. RESULTS: The Ktrans, Kep, IAUC, ADC, W-in and TTP values were significantly different between the pCR and non pCR groups after NAC. The AUC (0.845) and specificity (95.79%) of the combined Ktrans, Kep, IAUC and ADC values were both higher than those of the individual parameters. The combination of W-in, TTP and ADC values had the highest AUC value (0.886) in predicting pCR, with a sensitivity and specificity of 87.5% and 82.11%, respectively. CONCLUSIONS: The results suggested that the combination of ADC values and quantitative and semiquantitative DCE-MRI parameters, especially the combination of W-in, TTP, and ADC values, may improve the early prediction of pCR in breast cancer.

Germline variants profiling of BRCA1 and BRCA2 in Chinese Hakka breast and ovarian cancer patients.

OBJECTIVE: To investigate the prevalence and spectrum of BRCA1 and BRCA2 mutations in Chinese Hakka patients with breast and ovarian cancer. METHODS: A total of 1,664 breast or ovarian cancer patients were enrolled for genetic testing at our hospital. Germline mutations of the BRCA gene were analysed by next-generation sequencing, including the coding regions and exon intron boundary regions. RESULTS: The 1,664 patients included 1,415 (85.04%) breast cancer patients and 245 (14.72%) ovarian cancer patients, while four (0.24%) patients had both the breast and ovarian cancers. A total of 151 variants, including 71 BRCA1 variants and 80 BRCA2 variants, were detected in the 234 (14.06%) patients. The 151 variants included 58 pathogenic variants, 8 likely pathogenic variants, and 85 variants of unknown significance (VUS). A total of 56.25% (18/32) and 65.38% (17/26) of pathogenic variants (likely pathogenic variants are not included) were distributed in exon 14 of BRCA1 and exon 11 of BRCA2, respectively. The most common pathogenic variants among this Hakka population are c.2635G > T (p.Glu879*) (n = 7) in the BRCA1 gene and c.5164_5165del (p.Ser1722Tyrfs*4) (n = 7) in the BRCA2 gene among the Hakka population. A hotspot mutation in the Chinese population, the BRCA1 c.5470_5477del variant was not found in this Hakka population. The prevalence and spectrum of variants in the BRCA genes in the Hakka patients are different from that in other ethnic groups. CONCLUSIONS: The most common pathogenic variant in this population is c.2635G > T in the BRCA1 gene, and c.5164_5165delAG in the BRCA2 gene in this population. The prevalence and spectrum of variants in the BRCA1 and BRCA2 genes in the Hakka patients from southern China are different from those in other ethnic groups.

Changing Patterns in Clinicopathological Characteristics of Breast Cancer and Prevalence of BRCA Mutations: Analysis in a Rural Area of Southern China.

PURPOSE: Although the burden of breast cancer remains especially high in rural China, data on the clinicopathological characteristics and prevalence of the breast cancer susceptibility gene 1/2 (BRCA1/2) mutations in patients with breast cancer remain limited. We investigated the clinicopathological characteristics, changing patterns, and prevalence of BRCA1/2 mutations in patients with breast cancer. PATIENTS AND METHODS: The clinicopathological characteristics of 3712 women with pathologically confirmed primary breast cancer treated at Meizhou People's Hospital between January 2005 and December 2018 were evaluated. The prevalence of BRCA1/2 mutations in 340 patients with breast cancer diagnosed between January 2017 and September 2018 was also evaluated. RESULTS: The median age at diagnosis was 49±10.5 (range, 20-94) years. Positivity for estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) was observed in 59.0%, 52.5%, and 24.9% of patients, respectively. Time trend analysis revealed that an increasing trend was observed for age at diagnosis (p = 0.001), proportion of patients without a reproductive history (p < 0.001), postmenopausal patients (p = 0.001), invasive pathological cancer type (p = 0.008), ER-positive rate (p < 0.001), PR-positive rate (p = 0.008), and HER2-positive rate (p < 0.001). Compared with patients without BRCA1/2 mutations, those with BRCA1/2 mutations were more likely to have a family history of breast or ovarian cancer (p < 0.001) and have triple-negative breast cancer (TNBC) (p < 0.001). Family history of breast or ovarian cancer (odds ratio [OR], 103.58; 95% confidence interval [CI], 20.58-521.45; p < 0.001) and TNBC subtype (OR, 5.97; 95% CI, 1.16-30.90; p = 0.033) were independent predictors for BRCA1/2 mutation. CONCLUSION: The clinicopathological characteristics of patients with breast cancer in this rural area have changed during the past decade. BRCA1/2 testing should be performed in patients with breast cancer with a family history of breast or ovarian cancer and TNBC.

Identification and validation of a novel zinc finger protein-related gene-based prognostic model for breast cancer.

BACKGROUND: Breast invasive carcinoma (BRCA) is a commonly occurring malignant tumor. Zinc finger proteins (ZNFs) constitute the largest transcription factor family in the human genome and play a mechanistic role in many cancers' development. The prognostic value of ZNFs has yet to be approached systematically for BRCA. METHODS: We analyzed the data of a training set from The Cancer Genome Atlas (TCGA) database and two validation cohort from GSE20685 and METABRIC datasets, composed of 3,231 BRCA patients. After screening the differentially expressed ZNFs, univariate Cox regression, LASSO, and multiple Cox regression analysis were performed to construct a risk-based predictive model. ESTIMATE algorithm, single-sample gene set enrichment analysis (ssGSEA), and gene set enrichment analyses (GSEA) were utilized to assess the potential relations among the tumor immune microenvironment and ZNFs in BRCA. RESULTS: In this study, we profiled ZNF expression in TCGA based BRCA cohort and developed a novel prognostic model based on 14 genes with ZNF relations. This model was composed of high and low-score groups for BRCA classification. Based upon Kaplan-Meier survival curves, risk-status-based prognosis illustrated significant differences. We integrated the 14 ZNF-gene signature with patient clinicopathological data for nomogram construction with accurate 1-, 3-, and 5-overall survival predictive capabilities. We then accessed the Genomics of Drug Sensitivity in Cancer database for therapeutic drug response prediction of signature-defined BRCA patient groupings for our selected TCGA population. The signature also predicts sensitivity to chemotherapeutic and molecular-targeted agents in high- and low-risk patients afflicted with BRCA. Functional analysis suggested JAK STAT, VEGF, MAPK, NOTCH TOLL-like receptor, NOD-like receptor signaling pathways, apoptosis, and cancer-based pathways could be key for ZNF-related BRCA development. Interestingly, based on the results of ESTIMATE, ssGSEA, and GSEA analysis, we elucidated that our ZNF-gene signature had pivotal regulatory effects on the tumor immune microenvironment for BRCA. CONCLUSION: Our findings shed light on the potential contribution of ZNFs to the pathogenesis of BRCA and may inform clinical practice to guide individualized treatment.