World Psychiatry. 2023 Feb;22(1):43-45. doi: 10.1002/wps.21039.
NO ABSTRACT
PMID:36640399 | DOI:10.1002/wps.21039
Category: Nevin Manimala
J Assist Reprod Genet. 2023 Jan 14. doi: 10.1007/s10815-022-02707-6. Online ahead of print.
ABSTRACT
PURPOSE: To determine if creating voting ensembles combining convolutional neural networks (CNN), support vector machine (SVM), and multi-layer neural networks (NN) alongside clinical parameters improves the accuracy of artificial intelligence (AI) as a non-invasive method for predicting aneuploidy.
METHODS: A cohort of 699 day 5 PGT-A tested blastocysts was used to train, validate, and test a CNN to classify embryos as euploid/aneuploid. All embryos were analyzed using a modified FAST-SeqS next-generation sequencing method. Patient characteristics such as maternal age, AMH level, paternal sperm quality, and total number of normally fertilized (2PN) embryos were processed using SVM and NN. To improve model performance, we created voting ensembles using CNN, SVM, and NN to combine our imaging data with clinical parameter variations. Statistical significance was evaluated with a one-sample t-test with 2 degrees of freedom.
RESULTS: When assessing blastocyst images alone, the CNN test accuracy was 61.2% (± 1.32% SEM, n = 3 models) in correctly classifying euploid/aneuploid embryos (n = 140 embryos). When the best CNN model was assessed as a voting ensemble, the test accuracy improved to 65.0% (AMH; p = 0.1), 66.4% (maternal age; p = 0.06), 65.7% (maternal age, AMH; p = 0.08), 66.4% (maternal age, AMH, number of 2PNs; p = 0.06), and 71.4% (maternal age, AMH, number of 2PNs, sperm quality; p = 0.02) (n = 140 embryos).
CONCLUSIONS: By combining CNNs with patient characteristics, voting ensembles can be created to improve the accuracy of classifying embryos as euploid/aneuploid from CNN alone, allowing for AI to serve as a potential non-invasive method to aid in karyotype screening and selection of embryos.
PMID:36640251 | DOI:10.1007/s10815-022-02707-6
Environ Sci Pollut Res Int. 2023 Jan 14. doi: 10.1007/s11356-023-25194-3. Online ahead of print.
ABSTRACT
In recent years, traditional energy sources have caused a variety of negative impacts on the environment, and reducing carbon emissions is a top priority. The development of renewable energy technology is the key to transform the energy structure. Renewable energy represented by wind energy and photovoltaics has abundant reserves so they are connected to the grid system on a large scale. However, because of natural energy’s randomness, renewable energy power generation poses potential risks to energy production and grid security. By making short-term forecasts of renewable energy generation power, the uncertainty of energy generation can be reduced, and it is crucial to study renewable energy forecasting techniques. This paper proposes an integrated forecasting system for renewable energy sources. Firstly, ensemble empirical mode decomposition is used for data preprocessing, and stationarity analysis is used for modal identification; then, support vector regression optimized by sparrow search algorithm and statistical methods are combined to make forecast according to different characteristics of the series respectively; finally, the feasibility of this method in renewable energy time series prediction is verified by experiments. The experiments prove that the proposed model effectively improves the accuracy and prediction performance on ultra-short-term renewable energy forecasting; and it has good applicability and competitiveness with different forecasting scenarios and characteristics, which satisfy the actual forecasting requirements in terms of operational efficiency and accuracy, thus providing a technical basis for the effective utilization of renewable energy.
PMID:36640232 | DOI:10.1007/s11356-023-25194-3
Funct Integr Genomics. 2023 Jan 14;23(1):38. doi: 10.1007/s10142-023-00963-y.
ABSTRACT
Breast cancer is the most common tumor and the leading cause of cancer death in women. Cuproptosis is a new type of cell death, which can induce proteotoxic stress and eventually lead to cell death. Therefore, regulating copper metabolism in tumor cells is a new therapeutic approach. Long non-coding RNAs play an important regulatory role in immune response. At present, cuproptosis-related lncRNAs in breast cancer have not been reported. Breast cancer RNA sequencing, genomic mutations, and clinical data were downloaded from The Cancer Genome Atlas (TCGA). Patients with breast cancer were randomly assigned to the train group or the test group. Co-expression network analysis, Cox regression method, and least absolute shrinkage and selection operator (LASSO) method were used to identify cuproptosis-related lncRNAs and to construct a risk prognostic model. The prediction performance of the model is verified and recognized. In addition, the nomogram was used to predict the prognosis of breast cancer patients. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and immunoassay were used to detect the differences in biological function. Tumor mutation burden (TMB) was used to measure immunotherapy response. A total of 19 cuproptosis genes were obtained and a prognostic model based on 10 cuproptosis-related lncRNAs was constructed. Kaplan-Meier survival curves showed statistically significant overall survival (OS) between the high-risk and low-risk groups. Receiver operating characteristic curve (ROC) and principal component analysis (PCA) show that the model has accurate prediction ability. Compared with other clinical features, cuproptosis-related lncRNAs model has higher diagnostic efficiency. Univariate and multivariate Cox regression analysis showed that risk score was an independent prognostic factor for breast cancer patients. In addition, the nomogram model analysis showed that the tumor mutation burden was significantly different between the high-risk and low-risk groups. Of note, the additive effect of patients in the high-risk group and patients with high TMB resulted in reduced survival in breast cancer patients. Our study identified 10 cuproptosis-related lncRNAs, which may be promising biomarkers for predicting the survival prognosis of breast cancer.
PMID:36640225 | DOI:10.1007/s10142-023-00963-y
Environ Monit Assess. 2023 Jan 14;195(2):299. doi: 10.1007/s10661-023-10922-6.
ABSTRACT
Use of medicinal herbs is now gaining popularity especially among the low-income people because it is cheap, readily available and its “seeming” lack of side effects. However, environmental pollution is a potential threat to its continued use. This study examines the effect of air pollution on the soil and consequently on the medicinal herbs grown on such soils. Soil and four medicinal herbs, Chromolaena odorata, Vernonia amygdalina, Carica papaya and Ocimum gratissimum, commonly used in the south western part of Nigeria either as purely medicinal herbs, soup vegetables or both were carefully harvested from Fasina, a polluted area, and Moro, a relatively unpolluted area, all in Ile-Ife, Nigeria. Samples were prepared following standard practice and analysed for nickel, chromium, cadmium and lead using atomic absorption spectroscopy (AAS). The results showed that elemental concentrations at the two locations were within the permissible limit for both soil and herbs, the statistical test also established no significant difference between the two locations. However, toxic metals concentrations (chromium, cadmium and lead) were found higher at the polluted site while that of the essential metal, nickel, was higher at the unpolluted site. Of the four metals, cadmium has the highest transfer ratio (0.39 and 0.34) while lead has the least (0.21 and 0.25) for Moro and Fasina sites respectively. Similarly, Chromolaena odorata has the highest transfer ratio (0.34) while Carica papaya has the least (0.28). In conclusion, gradual build-up of the toxic metals at the polluted site is evident and may eventually contaminate the herbs.
PMID:36640219 | DOI:10.1007/s10661-023-10922-6
J Med Syst. 2023 Jan 14;47(1):9. doi: 10.1007/s10916-023-01907-6.
ABSTRACT
Cancer centres rely on electronic information in oncology information systems (OIS) to guide patient care. We investigated the completeness and accuracy of routinely collected head and neck cancer (HNC) data sourced from an OIS for suitability in prognostic modelling and other research. Three hundred and fifty-three adults diagnosed from 2000 to 2017 with head and neck squamous cell carcinoma, treated with radiotherapy, were eligible. Thirteen clinically relevant variables in HNC prognosis were extracted from a single-centre OIS and compared to that compiled separately in a research dataset. These two datasets were compared for agreement using Cohen’s kappa coefficient for categorical variables, and intraclass correlation coefficients for continuous variables. Research data was 96% complete compared to 84% for OIS data. Agreement was perfect for gender (κ = 1.000), high for age (κ = 0.993), site (κ = 0.992), T (κ = 0.851) and N (κ = 0.812) stage, radiotherapy dose (κ = 0.889), fractions (κ = 0.856), and duration (κ = 0.818), and chemotherapy treatment (κ = 0.871), substantial for overall stage (κ = 0.791) and vital status (κ = 0.689), moderate for grade (κ = 0.547), and poor for performance status (κ = 0.110). Thirty-one other variables were poorly captured and could not be statistically compared. Documentation of clinical information within the OIS for HNC patients is routine practice; however, OIS data was less correct and complete than data collected for research purposes. Substandard collection of routine data may hinder advancements in patient care. Improved data entry, integration with clinical activities and workflows, system usability, data dictionaries, and training are necessary for OIS data to generate robust research. Data mining from clinical documents may supplement structured data collection.
PMID:36640212 | DOI:10.1007/s10916-023-01907-6
Clin Transl Oncol. 2023 Jan 14. doi: 10.1007/s12094-022-03068-3. Online ahead of print.
ABSTRACT
BACKGROUND: The chemosensitivity of osteosarcoma patients to MTX is closely related to prognosis. There is currently a lack of advance prediction methods for MTX sensitivity.
OBJECTIVE: We proposed novel peri-osteosarcoma fat parameters based on computed tomography (CT) to evaluate the chemotherapy response preoperatively and calculate the correlation between image characteristics and methotrexate (MTX) blood concentration and systemic inflammation.
MATERIALS AND METHODS: Pediatric patients with osteosarcoma (OS) who were treated with high-dose MTX were retrospectively studied and grouped according to postoperative Huvos classification. Clinical data were collected and reviewed. Image characteristics including peri-osteosarcoma fat volume and fat attenuation index were measured using the threshold method based on CT images. Statistical significance, correlation and prediction performance were performed.
RESULTS: Eighteen patients (good response (GR) group/poor response (PR) group: 10/8) was enrolled. MTX peak value at 6 h differed significantly between the two groups which was significantly higher in GR group (745.1 μmol/L vs 529.0 μmol/L p = 0.001). Peri-osteosarcoma fat attenuation index was significantly lower in GR group compared with that in PR group (- 104.90 vs. – 97.19, p < 0.0001). MTX blood concentration at 6 h negatively correlated with peri-osteosarcoma fat attenuation index (R = – 0.519, p = 0.027). In addition, 6 h MTX blood concentration (OR 0.974; 95% CI 0.951-0.998, p = 0.037) and FAI (OR 2.108; 95% CI 1.047-4.243, p = 0.037) were, respectively, independently related to good response to chemotherapy. The prediction performance on chemotherapy response of peri-osteosarcoma fat attenuation index and 6 h MTX blood concentration were both good with the comparable area under the ROC curve (0.950, 95% CI 0.856-1.000 and 0.963, 95% CI 0.878-1.00).
CONCLUSIONS: Peri-osteosarcoma fat parameters based on CT were associated with the chemotherapy response and the MTX blood concentration, but not with the systemic inflammation. Combined with the requirement of current clinical practice, peri-osteosarcoma fat parameters may have the potential to be valuable image characteristics for monitoring chemotherapy response in OS pediatric patients.
PMID:36640208 | DOI:10.1007/s12094-022-03068-3
J Neurol. 2023 Jan 14. doi: 10.1007/s00415-023-11562-z. Online ahead of print.
ABSTRACT
Abnormal sensory discriminatory processing has been implicated as an endophenotypic marker of isolated dystonia. However, the extent of alterations across the different sensory domains and their commonality in different forms of dystonia are unclear. Based on the previous findings of abnormal temporal but not spatial discrimination in patients with laryngeal dystonia, we investigated sensory processing in the auditory and olfactory domains as potentially additional contributors to the disorder pathophysiology. We tested auditory temporal discrimination and olfactory function, including odor identification, threshold, and discrimination, in 102 laryngeal dystonia patients and 44 healthy controls, using dichotically presented pure tones and the extended Sniffin’ Sticks smell test protocol, respectively. Statistical significance was assessed using analysis of variance with non-parametric bootstrapping. Patients had a lower mean auditory temporal discrimination threshold, with abnormal values found in three patients. Hyposmia was found in 64 patients and anosmia in 2 patients. However, there were no statistically significant differences in either auditory temporal discrimination threshold or olfactory identification, threshold, and discrimination between the groups. A significant positive relationship was found between olfactory threshold and disorder severity based on the Burke-Fahn-Marsden dystonia rating scale. Our findings demonstrate that, contrary to altered visual temporal discrimination, auditory temporal discrimination and olfactory function are likely not candidate endophenotypic markers of laryngeal dystonia.
PMID:36640203 | DOI:10.1007/s00415-023-11562-z
Langenbecks Arch Surg. 2023 Jan 14;408(1):28. doi: 10.1007/s00423-022-02740-0.
ABSTRACT
PURPOSE: The detection of pancreatic cystic lesions (PCL) causes uncertainty for physicians and patients, and international guidelines are based on low evidence. The extent and perioperative risk of resections of PCL in Germany needs comparison with these guidelines to highlight controversies and derive recommendations.
METHODS: Clinical data of 1137 patients who underwent surgery for PCL between 2014 and 2019 were retrieved from the German StuDoQ|Pancreas registry. Relevant features for preoperative evaluation and predictive factors for adverse outcomes were statistically identified.
RESULTS: Patients with intraductal papillary mucinous neoplasms (IPMN) represented the largest PCL subgroup (N = 689; 60.6%) while other entities (mucinous cystic neoplasms (MCN), serous cystic neoplasms (SCN), neuroendocrine tumors, pseudocysts) were less frequently resected. Symptoms of pancreatitis were associated with IPMN (OR, 1.8; P = 0.012) and pseudocysts (OR, 4.78; P < 0.001), but likewise lowered the likelihood of MCN (OR, 0.49; P = 0.046) and SCN (OR, 0.15, P = 0.002). A total of 639 (57.2%) patients received endoscopic ultrasound before resection, as recommended by guidelines. Malignancy was histologically confirmed in 137 patients (12.0%), while jaundice (OR, 5.1; P < 0.001) and weight loss (OR, 2.0; P = 0.002) were independent predictors. Most resections were performed by open surgery (N = 847, 74.5%), while distal lesions were in majority treated using minimally invasive approaches (P < 0.001). Severe morbidity was 28.4% (N = 323) and 30d mortality was 2.6% (N = 29). Increased age (P = 0.004), higher BMI (P = 0.002), liver cirrhosis (P < 0.001), and esophageal varices (P = 0.002) were independent risk factors for 30d mortality.
CONCLUSION: With respect to unclear findings frequently present in PCL, diagnostic means recommended in guidelines should always be considered in the preoperative phase. The therapy of PCL should be decided upon in the light of patient-specific factors, and the surgical strategy needs to be adapted accordingly.
PMID:36640188 | DOI:10.1007/s00423-022-02740-0
Phytother Res. 2023 Jan 14. doi: 10.1002/ptr.7729. Online ahead of print.
ABSTRACT
Several preclinical studies have focused on the beneficial effects of garlic on cardiovascular diseases, but the results were inconsistent. We performed a systematic review and meta-analysis on the effect of garlic powder tablets and aged garlic extract (AGE) in CAD patients, mainly focusing on blood pressure, coronary artery calcification, lipid profile, and inflammatory markers. We searched PubMed, Cochrane CENTRAL, and Google Scholar to identify randomized controlled trials which examined garlic’s effect on CAD patients. The standardized mean difference with 95% CI was calculated using fixed-effect or random-effect models. Garlic has shown statistically significant changes of HDL (SMD = 0.18; 95% CI = -0.00 to 0.37; p = .05); LDL (SMD = -0.27; 95% CI = -0.46 to -0.08; p = .004), apolipoprotein-A (SMD = 0.68; 95% CI = 0.24 1.13; p = .002), C-RP (SMD = -0.59; 95% CI = -0.92 to -0.25; p = .0007), IL-6 (SMD = -1.08; 95% CI = -2.17 to 0.01; p = .05), homocysteine (SMD = -0.66; 95% CI = -1.04 to -0.28; p = .0007) and CAC score (SMD = -1.61; 95% CI = -2.66 to -0.57; p = .003). In the case of subgroup analysis, the overall effect was significantly effective in reducing TC, LDL levels and improving HDL levels in CV risk patients. Our study findings provide consistent evidence that intake of garlic reduces CVD risk factors. However, garlic could be considered a safe natural medicine to debilitate inflammation in CAD patients.
PMID:36640154 | DOI:10.1002/ptr.7729