Zinc finger protein ZBTB17 controls cellular senescence via interacting with nuclear receptor RXRA and its downstream calcium signaling.

Cellular senescence is broadly known as a stable cell cycle arrest accompanied by a senescence-associated secretory phenotype (SASP). In the past decades, calcium signaling has emerged as a key mediator of cellular senescence. However, the transcriptional regulation of calcium signaling during cellular senescence remains partially understood. We have previously identified the nuclear receptor RXRA as a key senescence repressor through inhibiting the endoplasmic reticulum (ER) calcium release channel inositol 1,4,5-trisphosphate receptor, type 2 (ITPR2) mediated intracellular calcium signaling. Nevertheless, as a transcriptional recruiter, the mechanism by which RXRA inhibits ITPR2 during cellular senescence remains unclear. Here we identified the zinc finger protein ZBTB17 can interact with RXRA. Interestingly, knockdown of ZBTB17 induces a cascade of RXRA-dependent intracellular calcium signaling, mitochondrial membrane potential (MMP), reactive oxygen species (ROS) accumulation, DNA damages, and ultimately cellular senescence. Moreover, the signaling and senescence phenotype induced by knocking down of ZBTB17 can also be abolished after silencing ITPR2. Altogether, our work provides a new mechanism controlling intracellular calcium signaling and cellular senescence and unveils novel insight toward the role of zinc finger proteins.

Novel ratio-expressions of genes enables estimation of wound age in contused skeletal muscle.

Given that combination with multiple biomarkers may well raise the predictive value of wound age, it appears critically essential to identify new features under the limited cost. For this purpose, the present study explored whether the gene expression ratios provide unique time information as an additional indicator for wound age estimation not requiring the detection of new biomarkers and allowing full use of the available data. The expression levels of four wound-healing genes (Arid5a, Ier3, Stom, and Lcp1) were detected by real-time polymerase chain reaction, and a total of six expression ratios were calculated among these four genes. The results showed that the expression levels of four genes and six ratios of expression changed time-dependent during wound repair. The six expression ratios provided additional temporal information, distinct from the four genes analyzed separately by principal component analysis. The overall performance metrics for cross-validation and external validation of four typical prediction models were improved when six ratios of expression were added as additional input variables. Overall, expression ratios among genes provide temporal information and have excellent potential as predictive markers for wound age estimation. Combining the expression levels of genes with ratio-expression of genes may allow for more accurate estimates of the time of injury.

A qualitative study on inner experience of self-management behavior among elderly patients with type 2 diabetes in rural areas.

BACKGROUND: As a chronic metabolic disease, diabetes poses a serious threat to human health and has become a major public health problem in China and worldwide. In 2020, 30% of Chinese people (aged ≥ 60 years) reported having diabetes mellitus. Moreover, individuals with diabetes living in rural areas face a significantly higher mortality risk compared to those in urban areas. In this study, we explored the inner experience of self-management behaviors in elderly patients with type 2 diabetes in rural areas to inform targeted interventions. METHODS: A phenomenological research design was used to explore the inner experience of self-management in rural elderly diabetes. Ten elderly diabetic patients were sampled from December 2022 to March 2023 in rural areas of Yangcheng County, Jincheng City, ShanXi Province, China. The seven-step Colaizzi phenomenological was used to analyze the interview data and generate themes. RESULTS: Four themes emerged: "Insufficient self-management cognition", "Negative self-management attitude", "Slack self-management behavior", and "No time for self-management". CONCLUSION: The level of self-management among elderly patients with type 2 diabetes in rural areas is low. Healthcare professionals should develop targeted interventions aimed at enhancing their cognitive levels, modifying their coping styles, and improving their self-management abilities to improve their quality of life.

Pathological Characteristics and Classification of Unstable Coronary Atherosclerotic Plaques.

Important forensic diagnostic indicators of sudden death in coronary atherosclerotic heart disease, such as acute or chronic myocardial ischemic changes, sometimes make it difficult to locate the ischemic site due to the short death process, the lack of tissue reaction time. In some cases, the deceased died of sudden death on the first-episode, resulting in difficulty for medical examiners to make an accurate diagnosis. However, clinical studies on coronary instability plaque revealed the key role of coronary spasm and thrombosis caused by their lesions in sudden coronary death process. This paper mainly summarizes the pathological characteristics of unstable coronary plaque based on clinical medical research, including plaque rupture, plaque erosion and calcified nodules, as well as the influencing factors leading to plaque instability, and briefly describes the research progress and technique of the atherosclerotic plaques, in order to improve the study on the mechanism of sudden coronary death and improve the accuracy of the forensic diagnosis of sudden coronary death by diagnosing different pathologic states of coronary atherosclerotic plaques.

A novel method for determining postmortem interval based on the metabolomics of multiple organs combined with ensemble learning techniques.

Determining postmortem interval (PMI) is one of the most challenging and essential endeavors in forensic science. Developments in PMI estimation can take advantage of machine learning techniques. Currently, applying an algorithm to obtain information on multiple organs and conducting joint analysis to accurately estimate PMI are still in the early stages. This study aimed to establish a multi-organ stacking model that estimates PMI by analyzing differential compounds of four organs in rats. In a total of 140 rats, skeletal muscle, liver, lung, and kidney tissue samples were collected at each time point after death. Ultra-performance liquid chromatography coupled with high-resolution mass spectrometry was used to determine the compound profiles of the samples. The original data were preprocessed using multivariate statistical analysis to determine discriminant compounds. In addition, three interrelated and increasingly complex patterns (single organ optimal model, single organ stacking model, multi-organ stacking model) were established to estimate PMI. The accuracy and generalized area under the receiver operating characteristic curve of the multi-organ stacking model were the highest at 93% and 0.96, respectively. Only 1 of the 14 external validation samples was misclassified by the multi-organ stacking model. The results demonstrate that the application of the multi-organ combination to the stacking algorithm is a potential forensic tool for the accurate estimation of PMI.

Forensic identification of sudden cardiac death: a new approach combining metabolomics and machine learning.

The determination of sudden cardiac death (SCD) is one of the difficult tasks in the forensic practice, especially in the absence of specific morphological changes in the autopsies and histological investigations. In this study, we combined the metabolic characteristics from corpse specimens of cardiac blood and cardiac muscle to predict SCD. Firstly, ultra-high performance liquid chromatography coupled with high-resolution mass spectrometry (UPLC-HRMS)-based untargeted metabolomics was applied to obtain the metabolomic profiles of the specimens, and 18 and 16 differential metabolites were identified in the cardiac blood and cardiac muscle from the corpses of those who died of SCD, respectively. Several possible metabolic pathways were proposed to explain these metabolic alterations, including the metabolism of energy, amino acids, and lipids. Then, we validated the capability of these combinations of differential metabolites to distinguish between SCD and non-SCD through multiple machine learning algorithms. The results showed that stacking model integrated differential metabolites featured from the specimens showed the best performance with 92.31% accuracy, 93.08% precision, 92.31% recall, 91.96% F1 score, and 0.92 AUC. Our results revealed that the SCD metabolic signature identified by metabolomics and ensemble learning in cardiac blood and cardiac muscle has potential in SCD post-mortem diagnosis and metabolic mechanism investigations.

Prevalence and risk factors of frailty in older patients with chronic heart failure: a systematic review and meta-analysis.

AIM: To provide a summary of the available evidence concerning prevalence and risk factors of frailty in elderly patients with CHF. METHODS: PubMed, Embase, Web of Science, CINAHL, The Cochrane Library, China National Knowledge Infrastructure Database (CNKI), Chinese Biomedical Database (Sinomed), Weipu Database (VIP), and Wanfang database were searched from inception to July 2023. This study strictly followed the PRISMA guidelines. The quality of the included studies was rated by the Agency for Healthcare and Research and Quality and the Newcastle-Ottawa Scale. RESULTS: A total of 21 original studies were included, involving 4,797 patients. Meta-analysis results showed that the prevalence of frailty in older patients with heart failure was 38% (95%CI: 0.32-0.44). Age, cardiac function grading, left atrial diameter, left ventricular ejection fraction, hemoglobin, polypharmacy, BNP, nutritional risk, and hospitalization day are the influential factors of frailty in older patients with CHF. CONCLUSION: The prevalence of frailty in older patients with CHF is high, and clinical medical personnel should identify and intervene early to reduce or delay the frailty in older patients with CHF as much as possible.

Postmortem Interval Estimation Using Protein Chip Technology Combined with Multivariate Analysis Methods.

OBJECTIVES: To estimate postmortem interval (PMI) by analyzing the protein changes in skeletal muscle tissues with the protein chip technology combined with multivariate analysis methods. METHODS: Rats were sacrificed for cervical dislocation and placed at 16 ℃. Water-soluble proteins in skeletal muscles were extracted at 10 time points (0 d, 1 d, 2 d, 3 d, 4 d, 5 d, 6 d, 7 d, 8 d and 9 d) after death. Protein expression profile data with relative molecular mass of 14 000-230 000 were obtained. Principal component analysis (PCA) and orthogonal partial least squares (OPLS) were used for data analysis. Fisher discriminant model and back propagation (BP) neural network model were constructed to classify and preliminarily estimate the PMI. In addition, the protein expression profiles data of human skeletal muscles at different time points after death were collected, and the relationship between them and PMI was analyzed by heat map and cluster analysis. RESULTS: The protein peak of rat skeletal muscle changed with PMI. The result of PCA combined with OPLS discriminant analysis showed statistical significance in groups with different time points (P<0.05) except 6 d, 7 d and 8 d after death. By Fisher discriminant analysis, the accuracy of internal cross-validation was 71.4% and the accuracy of external validation was 66.7%. The BP neural network model classification and preliminary estimation results showed the accuracy of internal cross-validation was 98.2%, and the accuracy of external validation was 95.8%. There was a significant difference in protein expression between 4 d and 25 h after death by the cluster analysis of the human skeletal muscle samples. CONCLUSIONS: The protein chip technology can quickly, accurately and repeatedly obtain water-soluble protein expression profiles in rats' and human skeletal muscles with the relative molecular mass of 14 000-230 000 at different time points postmortem. The establishment of multiple PMI estimation models based on multivariate analysis can provide a new idea and method for PMI estimation.

Estimating the time of skeletal muscle contusion based on the spatial distribution of neutrophils: a practical approach to forensic problems.

The study aimed to explore the neutrophil's spatial distributions used to estimate the histological age of contused skeletal muscle, and assessed the accuracy of various indicators, such as the proportion of neutrophils, "neutrophil mean distance," and distribution of neutrophils in areas of "contiguous contour lines." Fifty-five Sprague-Dawley rats were divided randomly into a control group and contusion groups at 1, 1.5, 2, 3, 4, and 6 h, as well as 1, 3, 5, and 15 days, post-injury (n = 5 per group). Nuclei and neutrophils were detected by hematoxylin and eosin (HE) staining and immunohistochemical (IHC) staining. At 0-24 h after injury, the distribution of neutrophils at distances of 100, 200, 300, 400, 500, and 600 µm from adjacent blood vessels was determined, and the best samples were screened to estimate wound age. To estimate wound age as accurately as possible, Fisher discriminant analysis (FDA) of the proportion of neutrophils, neutrophil mean distance, and distribution of neutrophils was performed, and 100.0% and 95.0% of the original and cross-validated cases were correctly classified, respectively. The spatial distribution of neutrophils at different distances from adjacent blood vessels showed a strong correlation with the histological age of contusion skeletal muscle, and the combination of the proportion of neutrophils, neutrophil mean distance, and distribution of neutrophils could be used to accurately estimate wound age.

Evaluation of droplet digital PCR rapid detection method and precise diagnosis and treatment for suspected sepsis (PROGRESS): a study protocol for a multi-center pragmatic randomized controlled trial.

BACKGROUND: Sepsis is still a major public health concern and a medical emergency due to its high morbidity and mortality. Accurate and timely etiology diagnosis is crucial for sepsis management. As an emerging rapid and sensitive pathogen detection tool, digital droplet PCR (ddPCR) has shown promising potential in rapid identification of pathogens and antimicrobial resistance genes. However, the diagnostic value and clinical impact of ddPCR tests remains to be studied in patients with suspected sepsis. PROGRESS trial is aimed to evaluate the clinical effectiveness of a novel ddPCR assay compared with standard practice. METHODS: PROGRESS is a multicenter, open-label, pragmatic randomized controlled trial (pRCT) set in ten hospitals, including departments of infectious disease and intensive care units. In this study, a total of 2292 patients with suspected sepsis will be randomly assigned to two arms: the ddPCR group and the control group with a ratio of 3:1. The primary outcome is the diagnostic efficacy, that is, the sensitivity and specificity of the ddPCR assay compared with the synchronous blood culture. Secondary outcomes include the mortality rates and the mean Sequential Organ Failure Assessment (SOFA) score at follow-up time points, the length of stay in the hospital, the time to directed antimicrobial therapy, duration of broad-spectrum antibiotic use, and the EQ-5D-5L score on day 90. DISCUSSION: It is the first multicenter pragmatic RCT to explore the diagnostic efficacy and clinical impact of the ddPCR assay in patients with suspected sepsis, taking advantage of both RCT's ability to establish causality and the feasibility of pragmatic approaches in real-world studies (RWS). This trial will help us to get a comprehensive view of the assay's capacity for precise diagnosis and treatment of sepsis. It has the potential to monitor the pathogen load change and to guide the antimicrobial therapy, making a beneficial impact on the prognosis of sepsis patients. TRIAL REGISTRATION: ClinicalTrial.gov, NCT05190861. Registered January 13, 2022-'Retrospectively registered', https://clinicaltrials.gov/ct2/show/NCT05190861 .

Application of Linear Regression Model of Gpnmb Gene in Rat Injury Time Estimation.

OBJECTIVES: To investigate the effects of injury time, postmortem interval (PMI) and postmortem storage temperature on mRNA expression of glycoprotein non-metastatic melanoma protein B (Gpnmb), and to establish a linear regression model between Gpnmb mRNA expression and injury time, to provide aimed at providing potential indexes for injury time estimation. METHODS: Test group SD rats were anesthetized and subjected to blunt contusion and randomly divided into 0 h, 4 h, 8 h, 12 h, 16 h, 20 h and 24 h groups after injury, with 18 rats in each group. After cervical dislocation, 6 rats in each group were collected and stored at 0 ℃, 16 ℃ and 26 ℃, respectively. The muscle tissue samples of quadriceps femoris injury were collected at 0 h, 12 h and 24 h postmortem at the same temperature. The grouping method and treatment method of the rats in the validation group were the same as above. The expression of Gpnmb mRNA in rat skeletal muscle was detected by RT-qPCR. The Pearson correlation coefficient was used to evaluate the correlation between Gpnmb mRNA expression and injury time, PMI, and postmortem storage temperature. SPSS 25.0 software was used to construct a linear regression model, and the validation group data was used for the back-substitution test. RESULTS: The expression of Gpnmb mRNA continued to increase with the prolongation of injury time, and the expression level was highly correlated with injury time (P<0.05), but had little correlation with PMI and postmortem storage temperature (P>0.05). The linear regression equation between injury time (y) and Gpnmb mRNA relative expression (x) was y=0.611 x+4.489. The back-substitution test proved that the prediction of the model was accurate. CONCLUSIONS: The expression of Gpnmb mRNA is almost not affected by the PMI and postmortem storage temperature, but is mainly related to the time of injury. Therefore, a linear regression model can be established to infer the time of injury.

The biological function of IGF2BPs and their role in tumorigenesis.

The insulin-like growth factor-2 mRNA-binding proteins (IGF2BPs) pertain to a highly conservative RNA-binding family that works as a post-transcriptional fine-tuner for target transcripts. Emerging evidence suggests that IGF2BPs regulate RNA processing and metabolism, including stability, translation, and localization, and are involved in various cellular functions and pathophysiologies. In this review, we summarize the roles and molecular mechanisms of IGF2BPs in cancer development and progression. We mainly discuss the functional relevance of IGF2BPs in embryo development, neurogenesis, metabolism, RNA processing, and tumorigenesis. Understanding IGF2BPs role in tumor progression will provide new insight into cancer pathophysiology.

The Molecular Genetics of Marfan Syndrome.

Marfan syndrome (MFS) is a complex connective tissue disease that is primarily characterized by cardiovascular, ocular and skeletal systems disorders. Despite its rarity, MFS severely impacts the quality of life of the patients. It has been shown that molecular genetic factors serve critical roles in the pathogenesis of MFS. FBN1 is associated with MFS and the other genes such as FBN2, transforming growth factor beta (TGF-ß) receptors (TGFBR1 and TGFBR2), latent TGF-ß-binding protein 2 (LTBP2) and SKI, amongst others also have their associated syndromes, however high overlap may exist between these syndromes and MFS. Abnormalities in the TGF-ß signaling pathway also contribute to the development of aneurysms in patients with MFS, although the detailed molecular mechanism remains unclear. Mutant FBN1 protein may cause unstableness in elastic structures, thereby perturbing the TGF-ß signaling pathway, which regulates several processes in cells. Additionally, DNA methylation of FBN1 and histone acetylation in an MFS mouse model demonstrated that epigenetic factors play a regulatory role in MFS. The purpose of the present review is to provide an up-to-date understanding of MFS-related genes and relevant assessment technologies, with the aim of laying a foundation for the early diagnosis, consultation and treatment of MFS.

Somatic Mutation Profiling of Papillary Thyroid Carcinomas by Whole-exome Sequencing and Its Relationship with Clinical Characteristics.

The incidence of papillary thyroid carcinomas (PTCs) has increased rapidly during the past several decades. Until now, the mechanisms underlying the tumorigenesis of PTCs have remained largely unknown. Next-generation-sequencing (NGS) provides new ways to investigate the molecular pathogenesis of PTCs. To characterize the somatic alterations associated with PTCs, we performed whole-exome sequencing (WES) of PTCs from 23 Chinese patients. This study revealed somatic mutations in genes with relevant functions for tumorigenesis, such as BRAF, BCR, CREB3L2, DNMT1, IRS2, MSH6, and TP53. We also identified novel somatic gene alterations which may be potentially involved in PTC progression. Gene set enrichment analysis revealed that the cellular response to hormone stimulus, epigenetic modifications, such as protein/histone methylation and protein alkylation, as well as MAPK, PI3K-AKT, and FoxO/mTOR signaling pathways, were significantly altered in the PTCs studied here. Moreover, Protein-Protein Interaction (PPI) network analysis of our mutated gene selection highlighted EP300, KRAS, PTEN, and TP53 as major core genes. The correlation between gene mutations and clinicopathologic features of the PTCs defined by conventional ultrasonography (US) and contrast-enhanced ultrasonography (CEUS) were assessed. These analyses established significant associations between subgroups of mutations and respectively taller-than-wide, calcified, and peak time iso- or hypo-enhanced and metastatic PTCs. In conclusion, our study supplements the genomic landscape of PTCs and identifies new actionable target candidates and clinicopathology-associated mutations. Extension of this study to larger cohorts will help define comprehensive genomic aberrations in PTCs and validate target candidates. These new targets may open methods of individualized treatments adapted to the clinicopathologic specifics of the patients.

Estimating Postmortem Interval Using Intestinal Microbiota Diversity Based on 16S rRNA High-throughput Sequencing Technology. / 基于16S rRNAé«˜é€šé‡æµ‹åºæŠ€æœ¯çš„è‚ é“èŒç¾¤å¤šæ ·æ€§æŽ¨æ–­æ­»äº¡æ—¶é—´.

OBJECTIVES: To explore the correlation between intestinal microbiota and postmortem interval(PMI) in rats by using 16S rRNA high-throughput sequencing technology. METHODS: Rats were killed by anesthesia and placed at 16 ℃, and DNA was extracted in caecum at 14 time points of 0, 1, 2, 3, 5, 7, 9, 12, 15, 18, 21, 24, 27 and 30 d after death. The 16S rRNA high-throughput sequencing technology was used to detect intestinal microbiota in rat cecal contents, and the results were used to analyze the rat intestinal microbiota diversity and differences. RESULTS: The total number of intestinal microbial communities did not change significantly within 30 days after death, but the diversity showed an upward trend. A total of 119 bacterial communities were significantly changed at 13 time points after death. The models for PMI estimation were established by using partial least squares (PLS) regression at all time points, before 9 days and after 12 days, reaching an R2 of 0.795, 0.767 and 0.445, respectively; and the root mean square errors (RMSEs) were 6.57, 1.96 and 5.37 d, respectively. CONCLUSIONS: Using 16S rRNA high-throughput sequencing technology, the composition and structure of intestinal microbiota changed significantly within 30 d after death. In addition, the established PLS regression model suggested that the PMI was highly correlated with intestinal microbiota composition, showing a certain time series change.

Loganin alleviates testicular damage and germ cell apoptosis induced by AGEs upon diabetes mellitus by suppressing the RAGE/p38MAPK/NF-κB pathway.

Diabetes mellitus (DM) damages male reproduction at multiple levels, such as endocrine secretion, spermatogenesis and penile erection. We herein investigated the protective effects and mechanism of loganin targeting the advanced glycation end products (AGEs)/receptor for AGEs (RAGE)/p38 mitogen-activated protein kinase (p38MAPK)/NF-κB signalling pathway. Loganin relieved the general DM symptoms and decreased the blood glucose level of KK-Ay DM mice. Haematoxylin-eosin staining demonstrated that loganin ameliorated testicular histology and function and enhanced the activities of testis-specific markers lactate dehydrogenase (LDH), acid phosphatase (ACP) and gamma-glutamyl transferase (γ-GT). Loganin also showed evident anti-oxidative stress, anti-apoptotic and anti-inflammatory effects on DM-induced reproductive damage by restoring glutathione (GSH) level and superoxide dismutase (SOD) activity, as well as reducing reactive oxygen species (ROS) level and Bax/Bcl-2 ratio in vivo and in vitro. Western blotting exhibited that loganin significantly inhibited the AGEs/RAGE/p38MAPK/NF-κB signalling pathway. Acridine orange and ethidium bromide staining (AOEB) and Western blotting showed that loganin in combination with inhibitors of RAGE, p38MAPK and NF-κB exerted stronger anti-apoptotic effects on AGE-induced GC-2 cell damage compared with loganin alone. In conclusion, loganin can protect against DM-induced reproductive damage, probably by suppressing the AGEs/RAGE/p38MAPK/NF-κB pathway.

Research Progress on lncRNA Functions and Mechanisms in Pituitary Adenomas.

Despite being the most common human neuroendocrine tumor, the pathogenesis of pituitary adenomas (PAs) is still unclear. Long non-coding RNA (lncRNA) is involved in a variety of physiological and pathological processes, and has been shown to play a key role in the process of tumor instigation and development by affecting the proliferation, migration, invasiveness, and metastasis of tumor cells. Therefore, lncRNAs may be used as diagnostic and prognostic markers of tumors. In this paper, the effect of lncRNA on the onset and progression of PAs is reviewed so as to provide a profound understanding of its pathogenesis and clinical reference for the early diagnosis of PAs.

Novel insights into wound age estimation: combined with "up, no change, or down" system and cosine similarity in python environment.

Wound age estimation is a complex, multifactorial issue. It is considered to have great practical significance that combining multi-biomarkers and multi-methods for injury time estimation. We optimized our earlier "up, no change, or down" model by adding data on the expression levels of mRNAs encoding ABHD2, MAD2L2, and ARID5A, and we converted the relative quantitative expression levels of seven genes into a vector rather than a color model. We used Python to derive the cosine similarity (CS) between a test set and the vector matrix; the highest similarity most accurately reflected the injury time. For the optimized model, the internal and external verifications were approximately 0.71 and 0.66, respectively. The good double-blinded results indicated that the model was stable and reliable. In summary, we used a vector matrix and cosine similarities derived by Python to mine the levels of genes expressed in contused skeletal muscle. We are the first to combine several biomarkers and methods for wound age estimation.

Temporal expression of wound healing-related genes inform wound age estimation in rats after a skeletal muscle contusion: a multivariate statistical model analysis.

Although many time-dependent parameters involved in wound healing have been exhaustively investigated, establishing an objective and reliable means for estimating wound age remains a challenge. In this study, 78 Sprague-Dawley rats were divided randomly into a control group and contusion groups at 4, 8, 12, 16, 20, 24, 28, 32, 36, 40, 44, and 48 h post-injury (n = 6 per group). The expression of 35 wound healing-related genes was explored in contused skeletal muscle by real-time polymerase chain reaction. Differences between the groups were assessed by partial least squares discriminant analysis (PLS-DA). The results show that the samples were classified into three groups by wound age (4-12, 16-24, and 28-48 h). A Fisher discriminant analysis model of 14 selected genes was constructed, and 94.9% cross-validated grouped cases were correctly classified. A PLS regression analysis using 14 genes showed reasonable internal predictive validity, with a root mean squared error of cross-validation of approximately 8 h. To examine whether the prediction models were capable of analyzing new (ungrouped) cases, an external validation was carried out using the expression data from an additional 30 rats. Approximately 76.7% of ungrouped cases were correctly classified, which was a lower proportion than that for cross-validation. Similarly, the prediction results of the PLS model showed lower relatively external predictive validity (root mean squared error of prediction = 11 h) than internal predictive validity. Although the prediction results were less accurate than expected, the gene expression modeling and multivariate analyses showed great potential for estimating injury time. These multivariate methods may be valuable when devising future wound time estimation strategies.

Evaluation of the thyroid characteristics of patients with growth hormone-secreting adenomas.

BACKGROUND: Acromegaly is highly associated with thyroid disorders. However, the clinical characteristics of thyroid nodules in individuals with acromegaly who present with thyroid diseases have not been completely elucidated. METHODS: Overall, 134 consecutive participants with growth hormone (GH)-secreting adenoma (n = 67) and non-functioning (NF) pituitary adenoma (n = 67) were recruited from the outpatient and inpatient patient department of The First Affiliated Hospital, Jinan University from August 2015 to August 2017. Thyroid ultrasonography was performed using an ultrasound system. The cytopathological results of fine-needle aspiration biopsy were analyzed by a pathologist according to the Bethesda system. Twenty-one patients with GH-secreting adenoma and thyroid disease underwent transsphenoidal pituitary adenoma resection and were followed up for 1 year. RESULTS: The prevalence of thyroid disease increased in the GH-secreting adenoma group compared with that in the NF pituitary adenoma group. The number of hypoechoic, isoechogenic, heterogeneous, and vascular thyroid nodules increased in patients with GH-secreting adenoma plus thyroid disease compared with that in patients with NF pituitary adenoma plus thyroid disease. Finally, we found significant decreases in the morphology of solid nodules and significant increases in the morphology of cystic nodules after surgery compared with those before surgery in the cured group. Moreover, the numbers of heterogeneous and vascular thyroid nodules decreased significantly after surgery compared with those before surgery in the cured group. However, the characteristics of the thyroid nodules did not change after surgery compared with those before surgery in the non-cured group. CONCLUSIONS: The numbers of hypoechoic, isoechoic, heterogeneous, and vascular thyroid nodules increased in patients with GH-secreting adenomas. In these patients, surgery resulted in significant changes from solid to cystic nodules and also reduced the numbers of heterogeneous and vascular thyroid nodules.