Multiparametric MRI-based radiomic nomogram for predicting HER-2 2+ status of breast cancer.

Objective: To explore the application of multiparametric MRI-based radiomic nomogram for assessing HER-2 2+ status of breast cancer (BC). Methods: Patients with pathology-proven HER-2 2+ invasive BC, who underwent preoperative MRI were divided into training (72 patients, 21 HER-2-positive and 51 HER-2-negative) and validation (32 patients, 9 HER-2-positive and 23 HER-2-negative) sets by randomization. All were classified as HER-2 2+ FISH-positive (HER-2-positive) or -negative (HER-2-negative) according to IHC and FISH. The 3D VOI was drawn on MR images by two radiologists. ADC, T2WI, and DCE images were analyzed separately to extract features (n = 1906). L1 regularization, F-test, and other methods were used to reduce dimensionality. Binary radiomics prediction models using features from single or combined imaging sequences were constructed using logistic regression (LR) classifier then and validated on a validation dataset. To build a radiomics nomogram, multivariate LR analysis was conducted to identify independent indicators. An evaluation of the model's predictive efficacy was made using AUC. Results: On the basis of combined ADC, T2WI, and DCE images, ten radiomic features were extracted following feature dimensionality reduction. There was superior diagnostic efficiency of radiomic signature using all three sequences compared to either one or two sequences (AUC for training group: 0.883; AUC for validation group: 0.816). Based on multivariate LR analysis, radiomic signature and peritumoral edema were independent predictors for identifying HER-2 2 +. In both training and validation datasets, nomograms combining peritumoral edema and radiomics signature demonstrated an effective discrimination (AUCs were respectively 0.966 and 0. 884). Conclusion: The nomogram that incorporated peritumoral edema and multiparametric MRI-based radiomic signature can be used to effectively predict the HER-2 2+ status of BC.

Association between biological aging and the risk of mortality in individuals with non-alcoholic fatty liver disease: A prospective cohort study.

BACKGROUND: The biological process of aging plays an important role in nonalcoholic fatty liver disease (NAFLD) development. However, epidemiological evidence about the association of biological aging with mortality risk among people with NAFLD is limited. METHODS: A total of 2199 participants with NAFLD from the National Health and Nutrition Examination Surveys (NHANES) III were included. The outcomes were all-cause and cause-specific (cardiovascular disease [CVD], cancer, and diabetes) mortality. We computed three BA measures, the Klemera-Doubal method (KDM) age, Phenotypic age, and homeostatic dysregulation (HD), by using 18 age-associated clinical biomarkers, and assessed their associations with mortality risk using Cox proportional hazards (CPH) models. RESULTS: After a median follow-up of 16 years, a total of 1077 deaths occurred. People with NAFLD who died during follow-up period exhibited higher baseline biological age (BA) and biological age accelerations (BAAs). The multivariate-adjusted CPH suggested that a one-standard deviation (SD) increase in KDM age acceleration, Phenotypic age acceleration, or HD was associated with a 3 %, 7 %, or 39 % elevated risk of all-cause mortality, respectively. The results of age-varying HRs showed that the associations of KDM age accelerations (AAs) and Phenotypic AAs with all-cause mortality appeared to be stronger in people with NAFLD younger than 45 years. CONCLUSIONS: Biological aging was positively associated with both all-cause and cause-specific mortality among people with NAFLD, particularly among younger individuals.

Prevalence of nonalcoholic fatty liver disease and liver cirrhosis in Chinese adults with type 2 diabetes mellitus.

BACKGROUND: Nonalcoholic fatty liver disease (NAFLD) and liver cirrhosis are significant clinical concerns, especially among individuals with type 2 diabetes mellitus (T2DM). However, in China, there is a paucity of reliable evidence detailing the characteristics of NAFLD and liver cirrhosis in T2DM. Furthermore, the relationship between blood glucose levels and NAFLD prevalence remains unclear. METHODS: Data from the Shanghai Suburban Adult Cohort and Biobank were analyzed, including 6621 participants with T2DM. NAFLD was diagnosed by ultrasonography and liver cirrhosis was performed according to the health information systems. Logistic regression and restricted cubic spline analysis were used to explore the potential risk factors for NAFLD and liver cirrhosis. RESULTS: The prevalence of NAFLD was 59.36%, and liver cirrhosis was 1.43% among T2DM patients. In these patients, factors like age, being female, marital status, and obesity significantly increased the risk of NAFLD. Specifically, obesity had a strong positive association with NAFLD (odds ratio [OR] = 4.70, 95% confidence interval [CI]: 4.13-5.34). The higher glycated hemoglobin (HbA1c) quartile was associated with a heightened NAFLD risk compared to the lowest quartile (all p < .001). The HbA1c-NAFLD relationship displayed a linear that mimicked an inverted L-shaped pattern. A significant positive association existed between HbA1c levels and NAFLD for HbA1c <8.00% (OR = 1.59, 95% CI: 1.44-1.75), but this was not observed for HbA1c >8.00% (OR = 1.03, 95% CI: 0.92-1.15). CONCLUSION: Systematic screening for NAFLD is essential in T2DM patients, especially with poor glucose control and obesity in female.

Electroacupuncture can Modify Stress, Low-Grade Inflammation in the Duodenum, and Damage to the Intestinal Barrier in Rats with Functional Dyspepsia through the CRF Signaling Pathway

BACKGROUND: In the domain of functional gastrointestinal disorders, Functional Dyspepsia (FD) stands out due to its widespread occurrence internationally. Historically, electroacupuncture (EA) has been employed as a therapeutic modality for FD, demonstrating notable clinical efficacy. OBJECTIVES: This research aimed to delve into the impact of EA on stress responses, minor duodenal inflammatory processes, and the integrity of the intestinal barrier within FD-affected rodent models while also elucidating the underlying mechanisms. METHODS: Thirty-six male Wistar rats were evenly distributed into three cohorts: a normal, a modeled FD, and an EA treatment group. The FD condition in the rats, barring those in the normal, was induced through a series of multifactorial procedures. For the EA cohort, the rats received electroacupuncture at the acupoints RN12 (Zhongwan) and ST36 (Zusanli) for 20 minutes daily over a span of one week. The gastric residue rate (GRR), intestinal propulsion rate (IPR), and changes in emotional state were measured in each group of rats. Additionally, serum levels of corticotropin-releasing hormone (CRH), adrenocorticotropic hormone (ACTH), and corticosterone (CORT) were detected, and the duodenal inflammatory condition and intestinal mucosal barrier status were observed through staining and fluorescence. The expression levels of Claudin-1, Junctional Adhesion Molecule 1 (JAM-1), Corticotropin-Releasing Factor (CRF), and Corticotropin-Releasing Factor Receptor 1 (CRF-R1) were also detected. RESULTS: The study demonstrated that EA had a positive effect on body weight and food intake, GRR, and IPR in FD rats. Additionally, the EA group showed a decrease in serum levels of CRH, ACTH, and CORT, as well as a decrease in the number of duodenal mast cells and tryptase content. Furthermore, the expression of tight junction proteins Claudin-1 and JAM-1 was increased in the EA group compared to the model group. EA also reduced the levels of CRF and CRF-R1 in the hypothalamus and duodenum. CONCLUSION: EA has been shown to improve the stress state of FD rats, inhibit the activation of mast cells in the duodenum, and reduce low-grade inflammatory response and damage to the intestinal mucosal barrier. It is believed that EA achieves these effects by modulating the expression of CRF and its receptors in the brain-gut interaction pathway through the CRF signaling pathway. This provides a new approach to treating FD.

COVID-19-induced acute loss of consciousness in Marchiafava-Bignami disease: a case report.

Among the various manifestations of COVID-19, the neurological implications of SARS-CoV-2 infection are of significant concern. Marchiafava-Bignami disease (MBD), a neurodegenerative disorder, exhibits a clinical spectrum ranging from mild progressive dementia in its chronic form to states of acute coma and varied mortality rates. Acute MBD primarily occurs in chronic alcoholics and malnourished individuals and is characterized by sudden loss of consciousness, seizures, confusion, and psychosis. We herein report a case of MBD presenting as acute loss of consciousness after the development of COVID-19. The patient presented with a history of fever and upper respiratory infection and was diagnosed with SARS-CoV-2 infection. He developed a neurological syndrome characterized by altered consciousness and convulsions, and brain magnetic resonance imaging revealed abnormal signals in the corpus callosum and frontoparietal lobes. Considering his alcohol intake history and the absence of other differential diagnoses, we diagnosed him with acute MBD triggered by COVID-19. After high-dose vitamin B1 and corticosteroid therapy, his clinical symptoms improved. In this case, we observed a temporal sequence between the development of COVID-19 and acute exacerbation of MBD. This case adds to the mounting evidence suggesting the potential effect of SARS-CoV-2 on the neurological system.

Establishment of a mild cognitive impairment risk model in middle-aged and older adults: a longitudinal study.

BACKGROUND: Early identification individuals at high risk of mild cognitive impairment (MCI) is essential for prevention and intervention strategies of dementia, such as Alzheimer's disease. MCI prediction considering the interdependence of predictors in longitudinal data needs to be further explored. We aimed to employ machine learning (ML) to develop and verify a prediction model of MCI. METHODS: In a longitudinal population-based cohort of China Health and Retirement Longitudinal Study (CHARLS), 8390 non-MCI participants were enrolled. The diagnosis of MCI was based on the aging-associated cognitive decline (AACD), and 13 factors (gender, education, marital status, residence, diabetes, hypertension, depression, hearing impairment, social isolation, physical activity, drinking status, body mass index and expenditure) were finally selected as predictors. We implemented a long short-term memory (LSTM) to predict the MCI risks in middle-aged and older adults within 7 years. The Receiver Operating Characteristic curve (ROC) and calibration curve were used to evaluate the performance of the model. RESULTS: Through 7 years of follow-up, 1925 participants developed MCI. The model for all incident MCI achieved an AUC of 0.774, and its deployment to the participants followed 2, 4, and 7 years achieved results of 0.739, 0.747, and 0.750, respectively. The model was well-calibrated with predicted probabilities plotted against the observed proportions of cognitive impairment. Education level, gender, marital status, and depression contributed most to the prediction of MCI. CONCLUSIONS: This model could be widely applied to medical institutions, even in the community, to identify middle-aged and older adults at high risk of MCI.

Machine learning-based plasma metabolomic profiles for predicting long-term complications of cirrhosis.

BACKGROUND AND AIMS: The liver cirrhosis complications occur after long asymptomatic stages of progressive fibrosis and are generally diagnosed late. We aimed to develop a plasma metabolomic-based score tool to predict these events. APPROACH AND RESULTS: We enrolled 64,005 UK biobank participants with metabolomic profile. Participants were randomly divided into the training (n=43,734) and validation cohorts (n=20,271). Liver cirrhosis complications were defined as hospitalization for liver cirrhosis or presentation with hepatocellular carcinoma. Interpretable machine learning framework was applied to learn the metabolomic states extracted from 168 circulating metabolites in the training cohort. An integrated nomogram was developed and compared to conventional and genetic risk scores. We created three groups: low-risk, middle-risk, and high-risk through selected cut-offs of the nomogram. The predictive performance was validated through area under time-dependent receiver operating characteristic curve (time-dependent AUC), calibration curves, and decision curve analysis. The metabolomic state model could accurately predict 10-year risk of liver cirrhosis complications in the training cohort (time-dependent AUC 0.84 [95% CI 0.82-0.86]), and outperform the fibrosis-4 index (time-dependent AUC difference 0.06 [0.03-0.10]) and polygenic risk score (0.25 [0.21-0.29]). The nomogram, integrating metabolomic state, aspartate aminotransferase, platelet count, waist/hip ratio, and smoking status, showed a time-dependent AUC of 0.930 at 3 years, 0.889 at 5 years, and 0.861 at 10 years in the validation cohort, respectively. The hazard ratio in the high-risk group was 43.58 (95% CI 27.08-70.12) compared with the low-risk group. CONCLUSIONS: We developed a metabolomic state-integrated nomogram, which enables risk stratification and personalized administration of liver-related events.

Association between red cell distribution width-to-albumin ratio and prognostic outcomes in pediatric intensive care unit patients: a retrospective cohort study.

Objective: This study aimed to assess the association between Red Cell Distribution Width-to-Albumin Ratio (RAR) and the clinical outcomes in Pediatric Intensive Care Unit (PICU) patients. Design: This is a retrospective cohort study. Methods: We conducted a retrospective cohort study based on the Pediatric Intensive Care database. The primary outcome was the 28-day mortality rate. Secondary outcomes included the 90-day mortality rate, in-hospital mortality rate, and length of hospital stay. We explored the relationship between RAR and the prognosis of patients in the PICU using multivariate regression and subgroup analysis. Results: A total of 7,075 participants were included in this study. The mean age of the participants was 3.4 ± 3.8 years. Kaplan-Meier survival curves demonstrated that patients with a higher RAR had a higher mortality rate. After adjusting for potential confounding factors, we found that for each unit increase in RAR, the 28-day mortality rate increased by 6% (HR = 1.06, 95% CI: 1.01-1.11, P = 0.015). The high-RAR group (RAR ≥ 4.0) had a significantly increased 28-day mortality rate compared to the low-RAR group (RAR ≤ 3.36) (HR = 1.7, 95% CI: 1.23-2.37, P < 0.001). Similar results were observed for the 90-day and in-hospital mortality rate. No significant interactions were observed in the subgroup analysis. Conclusion: Our study suggests a significant association between RAR and adverse outcomes in PICU patients. A higher RAR is associated with higher 28-day, 90-day, and in-hospital mortality rates.

METTL14-mediated lncRNA XIST silencing alleviates GDM progression by facilitating trophoblast cell proliferation and migration via the miR-497-5p/FOXO1 axis.

Gestational diabetes mellitus (GDM), a prevalent complication during the gestation period, has been linked to impaired proliferation and migration of trophoblasts causing placental maldevelopment. We previously found that lncRNA X-inactive specific transcript (XIST) played an essential role in GDM progression. Here, we investigated the precise biological functions as well as the upstream and downstream regulatory mechanisms of XIST in GDM. We found that XIST and forkhead box O1 (FOXO1) were conspicuously upregulated and miR-497-5p and methyltransferase-like 14 (METTL14) were downregulated in the placentas of GDM patients. XIST silencing facilitated proliferation and migration and inhibited cell apoptosis and cell cycle arrest in HG-cultured HTR8/SVneo cells. METTL14 inhibited XIST expression through m6A methylation modification. XIST overexpression abrogated the positive effect of METTL14 overexpression on HG-cultured HTR8/SVneo cell progression. MiR-497-5p and FOXO1 are downstream regulatory genes of XIST in HTR8/SVneo cells. Reverse experiments illustrated that XIST mediated HTR8/SVneo cell functions by regulating the miR-497-5p/FOXO1 axis. Additionally, XIST silencing augmented glucose tolerance and alleviated fetal detrimental changes in GDM rats. To conclude, METTL14-mediated XIST silencing facilitated proliferation and migration and inhibited cell apoptosis and cell cycle arrest in HG-cultured HTR8/SVneo cells via the miR-497-5p/FOXO1 axis, thereby alleviating GDM progression in rats.

A numerical model of the MICP multi-process considering the scale size.

As an environmentally friendly and controllable technology, Microbially induced carbonate precipitation (MICP) has broad applications in geotechnical and environmental fields. However, the longitudinal dispersivity in MICP multi-process varies with the scale size. Ignoring the effect of the scale size of the research object on the dispersivity leads to the inaccuracy between the numerical model and the experiment data. Thus, this paper has established the relationship between the scale size and the dispersivity initially, and optimized the theoretical system of MICP multi-process reaction. When scale size increases logarithmically from 10-2 m to 105 m, longitudinal dispersivity shows a trend of increasing from 10-3 m to 104 m. The distribution of calcium carbonate is closer to the experimentally measured value when the size effect is considered. After considering the scale size, the suspended bacteria and attached bacteria are higher than the cased without considering the size effect, which leads to a higher calcium carbonate content. Scale has little effect on the penetration law of the suspended bacteria. The maximum carbonate content increases with the increase of the initial porosity, and the average carbonate shows a significant increasing trend with the increase of the bacterial injecting rate. In the simulation of the microbial mineralization kinetic model, it is recommended to consider the influence of the scale size on the MICP multi-process.

Prognostic factors for competing risk in patients with AIDS-related Kaposi's sarcoma: A SEER population-based study.

OBJECTIVES: Despite the improved survival of patients with AIDS and Kaposi's sarcoma (KS), competing events are a non-negligible issue affecting the survival of such patients. In this study, we explored the prognostic factors of KS-specific and non-KS-specific mortality in patients with AIDS-related KS (AIDS-KS), accounting for competing risk. METHODS: We identified 17 103 patients with AIDS-KS aged 18-65 years between 1980 and 2016 from the Surveillance, Epidemiology, and End Results (SEER) 18 registry database. Prognostic factors for KS-specific and non-KS-specific mortality were determined by the Fine and Grey proportional subdistribution hazard model. We built competing risk nomograms and assessed their predictive performance based on the identified prognostic factors. RESULTS: In total, 12 943 (75.68%) patients died, 1965 (15.50%) of whom died from competing events. The KS-specific mortality rate was 14 835 per 100 000 person-years, and the non-KS specific mortality rate was 2719 per 100 000 person-years. Specifically, age >44 years was associated with an 11% decrease in the subdistribution hazard of KS-specific mortality compared with age <43 years but a 50% increase in the subdistribution hazard of non-KS-specific mortality. Being male was associated with a 26% increase in the subdistribution hazard of KS-specific mortality compared with being female but a 32% decrease in the subdistribution hazard of non-KS-specific mortality. Notably, being in the antiretroviral therapy (ART) era consistently showed a decrease in the subdistribution hazard of both KS-specific and non-KS-specific mortality than being in the pre-ART era. CONCLUSIONS: Competing events commonly occurred among patients with AIDS-KS, which deserves further attention to improve the prognosis of these patients.

Relationship between initial red cell distribution width and ΔRDW and mortality in cardiac arrest patients.

AIMS: There has been a lack of research examining the relationship between red cell distribution width (RDW) and the prognosis of cardiac arrest (CA) patients. The prognostic value of the changes in RDW during intensive care unit (ICU) hospitalization for CA patients has not been investigated. This study aims to investigate the correlation between RDW measures at ICU admission and RDW changes during ICU hospitalization and the prognosis of CA patients and then develop a nomogram that predicts the risk of mortality of these patients. METHODS AND RESULTS: A retrospective cohort study is used to collect clinical characteristics of CA patients (>18 years) that are on their first admission to ICU with RDW data measured from the Medical Information Mart for Intensive Care IV Version 2.0 database. Patients are randomly divided into a development cohort (75%) and a validation cohort (25%). The primary outcome is 30 and 360 day all-cause mortality. ΔRDW is defined as the RDW on ICU discharge minus RDW on ICU admission. A multivariate Cox regression model is applied to test whether the RDW represents an independent risk factor that affects the all-cause mortality of these patients. Meanwhile, the dose-response relationship between the RDW and the mortality is described by restricted cubic spine (RCS). A prediction model is constructed using a nomogram, which is then assessed using receiver operating characteristic curves, calibration curves, and decision curve analysis (DCA). A total of 1278 adult CA patients are included in this study. We found that non-survivors have a higher level of RDW and ΔRDW compared with survivors, and the mortality rate is higher in the high RDW group than in the normal RDW group. The Kaplan-Meier survival curve indicates that patients in the normal RDW group had a higher cumulative survival rate at 30 and 360 days than those in the high RDW group (log-rank test, χ2  = 36.710, χ2  = 54.960, both P values <0.05). The multivariate Cox regression analysis shows that elevated RDW at ICU admission (>15.50%) is an independent predictor of 30 [hazard ratio = 1.451, 95% confidence interval (CI) = 1.181-1.782, P < 0.001] and 360 day (hazard ratio = 1.393, 95% CI = 1.160-1.671, P < 0.001) all-cause mortality among CA patients, and an increase in RDW during ICU hospitalization (ΔRDW ≥ 0.4%) can serve as an independent predictor of mortality among these patients. A non-linear relationship between the RDW measured at ICU admission and the increased risk of mortality rate of these patients is shown by the RCS. This study established and validated a nomogram based on six variables, anion gap, first-day Sequential Organ Failure Assessment score, cerebrovascular disease, malignant tumour, norepinephrine use, and RDW, to predict mortality risk in CA patients. The consistency indices of 30 and 360 day mortality of CA patients in the validation cohort are 0.721 and 0.725, respectively. The nomogram proved to be well calibrated in the validation cohort. DCA curves indicated that the nomogram provided a higher net benefit over a wide, reasonable range of threshold probabilities for predicting mortality in CA patients and could be adapted for clinical decision-making. CONCLUSIONS: Elevated RDW levels on ICU admission and rising RDW during ICU hospitalization are powerful predictors of all-cause mortality for CA patients at 30 and 360 days, and they can be used as potential clinical biomarkers to predict the bad prognosis of these patients. The newly developed nomogram, which includes RDW, demonstrates high efficacy in predicting the mortality of CA patients.

Electroacupuncture Improves Insulin Resistance in Type 2 Diabetes Mice by Regulating Intestinal Flora and Bile Acid.

Introduction: Adjusting internal organs and dredging channel electroacupuncture has a definite effect on type 2 diabetes, but the specific mechanism still needs to be further clarified. This study aims to investigate the effects of electroacupuncture on the gut microbiota and bile acids in db/db mice after the intervention of "adjusting internal organs and dredging channel" and further explore its mechanism of action in treating T2DM. Methods: We used db/db mice as the animal model and db/m mice from the same litter as the blank control group, a total of 4 weeks of intervention were conducted. We evaluated the effectiveness of the "adjusting internal organs and dredging channel" treatment by detecting indicators related to glucose and lipid- metabolism. Detect changes in the gut microbiota of mice in each group using 16SrDNA sequencing technology. The content of bile acids in mouse feces was determined using liquid chromatography mass spectrometry, and the correlation analysis between different bile acids and differential bacterial communities was performed. The expression levels of TGR5 and GLP-1 proteins were measured using the Western blot method. Results: Adjusting internal organs and dredging channel electroacupuncture can improve blood glucose levels in db/db mice, increase the abundance of Firmicutes and Actinobacteria, and increase the content of fecal bile acid pool heavy CA and UDCA. At the same time, it also increased the content of TGR5/GLP1 in the small intestine. Conclusion: Adjusting internal organs and dredging channel electroacupuncture can improve the disorder of glucose and lipid metabolism in db/db mice, regulate the abundance and colony composition of intestinal microbiota in mice, and regulate bile acid metabolism in mice. The interaction between bile acid and intestinal microbiota can also be observed; Mutual influence may play a role in regulating blood sugar together.

Global epidemiology of early-onset liver cancer attributable to specific aetiologies and risk factors from 2010 to 2019.

Background: Considering its emergence as a public health concern worldwide, with potential spatial-temporal heterogeneities, we aimed to determine the global burden of early-onset liver cancer attributable to aetiologies and concomitant risk factors. Methods: We used data from the Global Burden of Diseases Study 2019 to determine age-standardised disability-adjusted life-year (DALY) rates for early-onset liver cancer by aetiologies and the population DALYs attributable to concomitant risk factors between 2010 and 2019. We also calculated estimated annual percentage changes (EAPCs) to measure temporal trends. Results: There were 2.9 million DALYs related to early-onset liver cancer globally in 2019. East Asia contributed over half of DALYs, which increased annually by 1.23% (95% confidence interval (CI) = 0.71, 1.76) between 2010 and 2019. Non-alcoholic steatohepatitis was the only growing aetiology. The proportion of DALYs attributed to metabolic risks increased by 22.50% (95% CI = 14.33, 38.13), while behavioral risks remained stable. Obesity surpassed smoking as the most prevalent nondeterministic aetiological risk factor from 2010 to 2019, while the population DALY attributable to hepatitis B combined with obesity increased by 29.93% (95% CI = 8.49, 60.77) in the same period, making it the principal joint contributor. Conclusions: Early-onset liver cancer poses considerable disability and continues to increase in many regions, especially in East Asia. Metabolic risk factors, particularly when hepatitis B and obesity coexist, are the fastest-growing contributors to this type of cancer. More targeted interventions are imperative to curb the growing burden of early-onset liver cancer due to metabolic risks.

Predicting the medium-temperature thermal stability of impact-strengthened medium-thick plate aluminum alloy using a back propagation artificial neural network.

A normalized medium-thick plate of aluminum alloy (4038) was impact-strengthened using a free-fall method at room temperature (approximately 20 °C). Specimens were then aged at 450 °C, 550 °C and 650 °C for 10, 20, 30 and 40 min respectively. Micro-hardness of each sample was tested. Micro-structure of samples annealed at 650 °C for different durations was characterized. A three-layer back propagation artificial neural network (BPANN) was trained using actual state parameters of the prepared samples. Results reveal that medium-temperature thermal stability of the prepared plate can be predicted through the BPANN model. Deviation of predicted values from the experimental ones is within 6 %, with a prediction accuracy exceeding 94 %. Variation trend of the predicted and the experimental thermal stability is consistent, but the predicted values are all higher than the measurements. Prediction accuracy of BPANN can be improved by increasing convergence rate of the error function. By adding relevant parameters of the micro-structure from samples aged at 650 °C to the input layer, BPANN model further improve its output and approach the real state of samples. The findings of this study can help researchers reduce the number and cost of experiments. The aim of this work was to predict the medium-temperature thermal stability of impact-strengthened normalized medium-thick plate of aluminum alloy annealed at different temperatures, and it also can be used as reference for other similar experiments.

A study of brain networks associated with Freezing of gait in Parkinson's disease using transfer entropy analysis.

BACKGROUND: Parkinson's disease (PD) is a common neurodegenerative disease in the elderly. Freezing of Gait (FOG) is one of the common motor symptoms of PD, but the potential mechanism remains unclear. This study aimed to investigate the changes of brain functional network topology in PD patients with FOG. METHODS: The resting electroencephalogram (EEG) were acquired from15 PD patients with FOG (PD-FOG), 13 PD patients without FOG (PD-nFOG), and 16 healthy control (HC). Cognitive and motor functions were assessed using subjective scales. The whole-brain functional networks were constructed based on transfer entropy. Transfer entropy was used to analyse the information flow and causality in the network and the network connectivity was analyzed by graph theory. The characteristics of PD-FOG and PD-nFOG were compared by receiver operator characteristic (ROC) curve analysis. RESULTS: The θ bands brain network of PD-FOG, PD-nFOG and HC group was significantly different (P < 0.05). The average characteristic path length of the θ bands brain network was positively correlated with FOG Questionnaire (FOGQ). PD-FOG and PD-nFOG get high classification accuracy according to this feature. The information inflow in the frontal and occipital lobes and information outflow in the temporal lobe of PD-FOG patients in the θ bands increased significantly. CONCLUSIONS: The whole-brain functional network characteristics of PD-FOG in the θ bands can serve as potential biomarkers for early diagnosis of PD-FOG. Abnormal information flow of the frontal, occipital, and temporal lobes in the θ bands may be an important factor leading to FOG.

Acupuncture is an effective therapy for macular damage: A case report.

RATIONALE: Many factors can contribute to the development of macular injury, which results in vision loss as a result of a disease. Heredity, age, underlying eye illness, internal eye surgery, or eye trauma can all cause it. A safer alternative to current therapies for macular degeneration is urgently needed since they all induce ocular irritation and postoperative recurrence as well as a host of other adverse effects. PATIENT CONCERNS: A 12-year-old girl was the patient. A laser pen burnt her right eye. There was a spot and a shadow in the middle of her right eye's visual field. DIAGNOSES: Macular degeneration. INTERVENTIONS: Given the patient's age, we opted out of medicine and instead used acupuncture as a symptomatic treatment. OUTCOMES: Two months after therapy concluded, optical coherence tomography result report indicate that the macula region of the right eye is better than it was previously. The corrected visual acuity of the right eye recovered from 0.25 to 1.0, and the clinical accompanying symptoms of the right eye disappeared. LESSONS: No additional medication or surgical procedure was employed in this instance. We treated the macular damage with acupuncture, which relieved the patient's clinical symptoms and had no adverse effects. This demonstrates that acupuncture may be beneficial in treating ophthalmopathy in this direction.

Associations of healthy lifestyle and three latent socioeconomic status patterns with physical multimorbidity among middle-aged and older adults in China.

BACKGROUND: Multimorbidity is an emerging global public health concern. However, complex associations of healthy lifestyle and socioeconomic status (SES) with multimorbidity have not been identified. METHODS: This population-based prospective cohort study used data from four waves of the China Health and Retirement Longitudinal Study (CHARLS) to explore these relationships. Physical multimorbidity was measured using 12 non-communicable diseases. Latent class analysis (LCA) was conducted to determine the optimal SES patterns based on annual per-capita household expenditure, occupation, education level, and health insurance. The healthy lifestyle score (0-5) was constructed comprising information on smoking, drinking, physical activity, sleep, and body shape. RESULTS: Of 17,708 participants in the CHARLS, 7776 were eligible for inclusion in our analysis (13.3% with high SES, 26.1% with medium SES, and 60.6% with low SES). Compared with high SES participants, those with low SES had higher risks of incident physical multimorbidity (OR 1.22, 95% CI 1.05, 1.42), which was competitively mediated by lifestyle (mediation proportion, -10.17%, 95% CI -19.12%, -1.23%). Significant interactions were observed between lifestyle factors and SES in patients with incident diabetes. Participants with low SES and no or one healthy lifestyle factor had a higher risk of incident physical multimorbidity than those with high SES and four to five healthy lifestyle factors (OR 2.19, 95% CI 1.57, 3.04). CONCLUSION: Healthy lifestyles competitively mediate a fractional proportion of socioeconomic inequity in incident physical multimorbidity. Furthermore, healthy lifestyles were associated with lower multimorbidity risk in the SES subgroups, supporting the important role of lifestyle in reducing physical multimorbidity burden.

Endoplasmic reticulum stress-related signature predicts prognosis and immune infiltration analysis in acute myeloid leukemia.

OBJECTIVES: To construct an endoplasmic reticulum stress-related prognostic risk score (RS) model to predict prognosis and perform a preliminary analysis of immune infiltration in patients with acute myeloid leukemia (AML). METHODS: The whole-genome expression data for AML and endoplasmic reticulum stress (ER stress)-related genes were downloaded from the GEO and GSEA databases, respectively. The samples were divided into death and survival groups, combined with clinical prognosis information. LASSO regression was used to construct a prognostic RS model. The Kaplan-Meier curve method was used to evaluate the association between different risk groups and actual survival prognosis information. A cox regression analysis was used to screen for independent survival prognostic clinical factors and construct a nomogram. CIBERSORT and ssGSEA was used for immune-related analysis. RESULTS: Eighteen ER-stress related genes were identified and a comprehensive network was constructed. Further, 5 CC, 8 MF, 17 BP, and 2 KEGG pathways were enriched. Ten optimal DEGs were obtained and a prognostic risk model was constructed. Compared to the low RS group, the OS values of the high RS group were significantly lower. A significant correlation between the different risk groups and the actual prognosis was demonstrated. Ten immune cells with significantly different distributions in different risk groups were screened. KEGG enrichment analysis showed that there were 5 signaling pathways in the high-risk group. CONCLUSIONS: The RS model can effectively predict the prognosis and has clinical implications for the prognosis of AML, combined with the correlation between different RS groups and the immune microenvironment.