A novel near infrared spectroscopy analytical strategy for soil nutrients detection based on the DBO-SVR method.

Soil is the basis of agricultural production and accessing accurate information on soil nutrients is essential. Traditional methods of soil composition detection, which are based on chemical analysis, are characterized by being costly and polluting. Spectroscopic analysis has proven to be a rapid, non-destructive and effective technique for predicting soil properties in general and potassium, phosphorus and organic matter in particular. However, previous research on soils has rarely combined optimization algorithms with machine learning techniques, which has led to suboptimal model accuracy and convergence speed. In this study, a total of 184 soil samples were collected from three cities of Linhai, Yueqing and Longyou County, Zhejiang Province, China. After measuring pH values, alkali-hydrolyzable nitrogen (SAN), available phosphorus (SAP), available potassium (SAK) and soil organic matter (SOM) contents, along with their corresponding spectroscopic measurements, nine pretreatment methods and their combinations are adopted. A novel assessment model, integrating support vector machine and dung beetle optimization algorithm (DBO-SVR), is proposed to predict pH values and SAN, SAP, SAK, SOM content. Meanwhile, the DBO algorithm is compared with three mainstream optimization algorithms (particle swarm optimization (PSO), whale optimization algorithm (WOA) and grey wolf optimizer (GWO)). Results showed that the DBO-SVR model was shown best performance with Rp, RMSEP and RPD of 0.9842, 0.1306, 5.6485 respectively for prediction of pH value, with Rp, RMSEP and RPD of 0.8802, 15.0574 mg/kg and 2.0508, respectively for assessment of SAN content, with Rp, RMSEP and RPD of 0.9790, 12.8298 mg/kg, and 4.5132, respectively for assessment of SAP content, with Rp, RMSEP and RPD of 0.8677, 22.5107 mg/kg, and 1.9546, respectively for assessment of SAK content, and with Rp, RMSEP and RPD of 0.9273, 2.6427g/kg , and 2.1821, respectively for assessment of SOM content. This study demonstrates that the combination of near-infrared (NIR) spectroscopy and the DBO-SVR algorithm is capable of predicting soil nutrient composition with greater accuracy and efficiency.

Construction and optimization of a polygenic risk model for venous thromboembolism in the Chinese population.

BACKGROUND: Venous thromboembolism (VTE) has both environmental and genetic risk factors. It is regulated by polygenes and multisites. The polygenic risk score (PRS) has been widely used because any single genetic biomarker failed to accurately predict the genetic risk of VTE. However, no polygenic risk model has been proposed for VTE in the Chinese population. Thus, we aimed to construct a PRS model for the first episode of VTE in the Chinese population. METHODS: First, single nucleotide polymorphisms (SNPs) associated with VTE in genome-wide association studies, meta-analyses, and candidate gene studies were screened as variables for the PRS. The logarithm of the odds ratio was used to weight the variables. Second, a training set with simulated data from 1000 cases of VTE and 1000 controls was created with different genotypes and frequencies. Finally, we calculated the area under the receiver operating characteristic curve (AUC) to evaluate the discriminatory ability of the PRS model. RESULTS: We screened 53 SNPs potentially associated with the first episode of VTE in the Chinese population. The AUC of the PRS-53 model (containing 53 SNPs) was 0.748 (95% confidence interval, 0.727-0.770) in the training set. From the largest weight to the smallest weight, SNPs were incrementally added to the model to calculate the AUC for model optimization. The AUC of the PRS-10 model (containing 10 SNPs) was 0.718 (95% confidence interval, 0.696-0.740), with no statistically significant difference from the AUC for the PRS-53 model. CONCLUSIONS: The PRS-10 and PRS-53 models showed similar predictive abilities and satisfactory discriminatory power and can be used to predict the genetic risk of the first episode of VTE in the Chinese population. The simplified PRS-10 model is more efficient in clinical practice.

Pulmonary rehabilitation assessment in COPD based on the ICF brief core set: a latent profile analysis.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is the most burdened chronic respiratory disease in the world, resulting in a reduced quality of life and limited physical activity for patients. Pulmonary rehabilitation (PR) is an effective therapy for COPD. Effective PR relies on an accurate pulmonary rehabilitation program. An adequate pre-rehabilitation assessment helps healthcare professionals to develop an accurate pulmonary rehabilitation program. However, pre-rehabilitation assessment strategies lack specific selection criteria and an assessment of the patient's overall functioning. METHODS: This study explored the functional characteristics of COPD patients before pulmonary rehabilitation and collected COPD patients from October 2019 to March 2022. A cross-sectional survey of 237 patients was conducted using the ICF brief core set as the study tool. Latent profile analysis identified subgroups of patients with different rehabilitation needs based on body function and activity participation. RESULTS: Four subgroups of functional dysfunction were identified: 5.42%, 21.03%, 29.44%, and 34.11% in the high dysfunction group, the moderate dysfunction group, the lower-middle dysfunction but high mobility impairment group, and the low dysfunction group, respectively. Patients in the high dysfunction group were older, had a higher proportion of widowed spouses, and experienced more exacerbation. Most patients in the low-dysfunction group did not use inhaled medication and had a lower participation rate in oxygen therapy. Patients with a more severe disease classification and symptom burden mostly belonged to the high dysfunction group. CONCLUSIONS: COPD patients require an adequate assessment before implementing a pulmonary rehabilitation program to determine their rehabilitation needs. The four subgroups were heterogeneous in terms of the degree of functional impairment in body function and activity participation. Patients in the high dysfunction group can improve basic cardiorespiratory fitness; patients in the moderate dysfunction group should focus on improving cardiorespiratory endurance and muscle fitness, patients in the lower-middle-dysfunction but high mobility impairment group should focus on improving mobility and patients in the low functional disability group should focus more on preventive measures. Healthcare providers can tailor rehabilitation programs to the functional impairments of patients with different characteristics. TRIAL REGISTRATION: This study has been registered in the Chinese Clinical Trials Registry (ChiCTR2000040723).

Matrix reconstruction with reliable neighbors for predicting potential MiRNA-disease associations.

Numerous experimental studies have indicated that alteration and dysregulation in mircroRNAs (miRNAs) are associated with serious diseases. Identifying disease-related miRNAs is therefore an essential and challenging task in bioinformatics research. Computational methods are an efficient and economical alternative to conventional biomedical studies and can reveal underlying miRNA-disease associations for subsequent experimental confirmation with reasonable confidence. Despite the success of existing computational approaches, most of them only rely on the known miRNA-disease associations to predict associations without adding other data to increase the prediction accuracy, and they are affected by issues of data sparsity. In this paper, we present MRRN, a model that combines matrix reconstruction with node reliability to predict probable miRNA-disease associations. In MRRN, the most reliable neighbors of miRNA and disease are used to update the original miRNA-disease association matrix, which significantly reduces data sparsity. Unknown miRNA-disease associations are reconstructed by aggregating the most reliable first-order neighbors to increase prediction accuracy by representing the local and global structure of the heterogeneous network. Five-fold cross-validation of MRRN produced an area under the curve (AUC) of 0.9355 and area under the precision-recall curve (AUPR) of 0.2646, values that were greater than those produced by comparable models. Two different types of case studies using three diseases were conducted to demonstrate the accuracy of MRRN, and all top 30 predicted miRNAs were verified.

Oxidative Stress Amelioration of Novel Peptides Extracted from Enzymatic Hydrolysates of Chinese Pecan Cake.

Pecan (Carya cathayensis) is an important economic crop, and its hydrolyzed peptides have been evidenced to reduce the effect of oxidative stress due to their antioxidant capacity. Hence, the protocols of ultrafiltration and gel filtration chromatography were established to obtain bioactive peptides from by-products of C. cathayensis (pecan cake). As measured by DPPH/ABTS radical scavenging, the peptides with less molecular weight (MW) possess higher antioxidant capacity. PCPH-III (MW < 3 kDa) presented higher radical scavenging capacity than PCPH-II (3 kDa < MW < 10 kDa) and PCPH-I (MW > 10 kDa) measured by DPPH (IC50: 111.0 µg/ mL) and measured by ABTs (IC50: 402.9 µg/mL). The secondary structure and amino acid composition varied by their MW, in which PCPH-II contained more α-helices (26.71%) and ß-sheets (36.96%), PCPH-III contained higher ratios of ß-turns (36.87%), while the composition of different secondary of PCPH-I was even 25 ± 5.76%. The variation trend of α-helix and random experienced slightly varied from PCPH-I to PCPH-II, while significantly decreased from PCPH-II to PCPH-III. The increasing antioxidant capacity is followed by the content of proline, and PCPH-III had the highest composition (8.03%). With regard to the six peptides identified by LC-MS/MS, two of them (VYGYADK and VLFSNY) showed stronger antioxidant capacity than others. In silico molecular docking demonstrated their combining abilities with a transcription factor Kelch-like ECH-associated protein 1 (Keap1) and speculated that they inhibit oxidative stress through activating the Keap1-Nrf2-ARE pathway. Meanwhile, increased activity of SOD and CAT­antioxidant markers­were found in H2O2-induced cells. The residue of tyrosine was demonstrated to contribute the most antioxidant capacity of VYGYADK and its position affected less. This study provided a novel peptide screening and by-product utilization process that can be applied in natural product developments.

Clinical Study of Clopidogrel Combined with Huoxue Tongluo Prescription in Improving Transient Ischemic Attack and the Effect on MMP-9, Hcy, and CRP.

Background: This study aimed to explore the clinical study of clopidogrel combined with Huoxue Tongluo prescription in improving transient ischemic attack (TIA) and the effect on MMP-9, Hcy, and CRP. Methods: A total of 84 patients with TIA admitted to our hospital from December 2019 to February 2021 were selected. The patients were divided into the control group (42 cases: not treated with Huoxue Tongluo prescription) and study group (42 cases: treatment with Huoxue Tongluo prescription). The clinical efficacy, adverse reactions, the levels of blood pressure and lipid, blood rheology and cerebral hemodynamics, neurological function-related indicators, MMP-9, Hcy, and CRP of the two groups were compared. Results: The total effective rate in the study group was higher than the control group. Compared with before treatment, the levels of SBP and DBP in both groups decreased memorably after treatment, and those in the study group decreased more particularly than the control group. The levels of LDL, HDL, TC, and TG in the study group were significantly better than those in the control group. The plasma viscosity, whole blood high shear viscosity, whole blood low shear viscosity, and hematocrit of patients in the study group were lower than those in the control group, and the maximum blood flow velocity, minimum blood flow velocity, average blood flow velocity, and average blood flow were higher than those in the control group. The levels of NSE, MBP, and S100ß in the study group were more memorably lower than those in the control group. After treatment, the levels of MMP-9, Hcy, and CRP in the study group were significantly lower than those in the control group. There was no obvious difference in the incidence of adverse reactions between the study group and control group. Conclusion: Clopidogrel combined with Huoxue Tongluo prescription can significantly improve the therapeutic effect and reduce the levels of MMP-9, Hcy, and CRP in patients with TIA.

Prediction of Short-Term Breast Cancer Risk with Fusion of CC- and MLO-Based Risk Models in Four-View Mammograms.

This study performed and assessed a novel program to improve the accuracy of short-term breast cancer risk prediction by using information from craniocaudal (CC) and mediolateral-oblique (MLO) views of two breasts. An age-matched dataset of 556 patients with at least two sequential full-field digital mammography examinations was applied. In the second examination, 278 cases were diagnosed and pathologically verified as cancer, and 278 were negative, while all cases in the first examination were negative (not recalled). Two generalized linear-model-based risk prediction models were established with global- and local-based bilateral asymmetry features for CC and MLO views first. Then, a new fusion risk model was developed by fusing prediction results of the CC- and MLO-based risk models with an adaptive alpha-integration-based fusion method. The AUC of the fusion risk model was 0.72 ± 0.02, which was significantly higher than the AUC of CC- or MLO-based risk model (P < 0.05). The maximum odds ratio for CC- and MLO-based risk models were 8.09 and 5.25, respectively, and increased to 11.99 for the fusion risk model. For subgroups of patients aged 37-49 years, 50-65 years, and 66-87 years, the AUCs of 0.73, 0.71, and 0.75 for the fusion risk model were higher than AUC for CC- and MLO-based risk models. For the BIRADS 2 and 3 subgroups, the AUC values were 0.72 and 0.71 respectively for the fusion risk model which were higher than the AUC for the CC- and MLO-based risk models. This study demonstrated that the fusion risk model we established could effectively derive and integrate supplementary and useful information extracted from both CC and MLO view images and adaptively fuse them to increase the predictive power of the short-term breast cancer risk assessment model.

To Analyze the Application Value of Perioperative Nursing Care in Patients with Resected Brain Tumor Accompanied with Epileptic Symptoms under Cortical Electrocorticography Monitoring.

OBJECTIVE: To explore the application value of perioperative nursing for patients with brain tumors with epilepsy symptoms under the cortical electrocorticography (EEG) monitoring. METHODS: A total of 86 patients with brain tumor complicated with epilepsy admitted to the department of brain surgery of our hospital from January 2018 to December 2019 were selected as the research objects, and all underwent resection under cortical EEG monitoring. According to different nursing methods, they were divided into the control group and observation group, each with 43 cases. The control group was given perioperative basic nursing, and the observation group was given perioperative comprehensive nursing. The EEG image of the patient during the operation was observed by a portable EEG monitor. Anxiety and depression were assessed by self-rating anxiety scale (SAS) and self-rating depression scale (SDS) scores. The self-made satisfaction questionnaire was used to investigate the nursing satisfaction. A visual analogue (VAS) score is used to assess pain degree. A multiparameter monitor was used to detect the patient's heart rate (HR), systolic blood pressure (SBP), and diastolic blood pressure (DBP). The quality of life was assessed by the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire-Core 30 (EORTC QLQ-30). The complication rate and recurrence rate were also counted. RESULTS: Eighty-six patients with epileptic brain tumor developed spikes in 35 cases, including 7 meningiomas, 22 gliomas, and 6 cholesteatomas; 27 cases of sharp waves, including 14 meningiomas, 12 gliomas, and 1 case of cholesteatomas; and 24 cases of complex wave, including 9 cases of meningioma, 13 cases of glioma, and 2 cases of cholesteatoma. There was no significant difference in the scores of SAS, SDS, VAS, HR, SBP, DBP, and quality of life between the two groups at T0. The VAS score increased at T1 and T2, and the increase in the control group was greater than that in the observation group. At T3 and T4, the SAS, SDS, and VAS scores of the two groups decreased, and the observation group decreased more than the control group. HR, SBP, and DBP of the two groups showed an upward trend at T1 and T2, and the increase in the control group was more significant than that in the observation group. At T3, the three indicators of the two groups decreased, and the observation group decreased more significantly than the control group. At T4, the scores of all indicators of the quality of life of the two groups increased, and the observation group increased more significantly than the control group. The nursing satisfaction of the observation group was higher than that of the control group. The complication rate and recurrence rate in the observation group were decreased compared with the control group. CONCLUSION: Perioperative comprehensive nursing intervention for patients with epileptic brain tumor undergoing resection under cortical EEG monitoring can reduce or even eliminate the recurrence rate of epilepsy, reduce the patient's pain and stress response, and improve the patient's quality of life. It can also reduce the occurrence of complications, improve nursing satisfaction, thereby improving patient compliance, and has a high clinical application value.

Distribution of HPV 16 E6 gene variants in screening women and its associations with cervical lesions progression.

The aim of this study is to investigate distribution of human papillomavirus (HPV) 16 variants in screening healthy women and the potential association between HPV 16 variants and progression of cervical lesions. For this study a total of 2000 healthy women in Tianjin urban area and 212 patients who were HPV 16 positive and underwent colposcopy were analyzed for HPV 16 variants by pyrosequencing. The results show that the HPV 16 was the most prevalent genotype in Tianjin healthy women and five HPV 16 variant types were detected. The HPV 16 variants were determined by sequencing parital E6 region and the detected variants were European prototype E-T350 (E-p), E-G350, E-C109 G, Asian (As) and Asian-American (AA), among which the E-p variant was the most prevalent (82.76%) followed by As variant. Interestingly, in patients with suspected cervical lesions the most prevalent variant was As variant (54.9%) by increasing significance with severity of cervical diseases (OR 4.337; 95% CI 1.248-15.067; P = 0.021), and followed by HPV 16 E-p variant while E-G350 variant only appeared in HSIL and cervical cancer. Our results show that HPV 16 E-p variant was more prevalent than As in Tianjin healthy screening women while As variant was the most frequently type in HSIL and cervical cancer. It is suggested that the mutation of HPV 16 Asian variants, comparing with HPV 16 E-p variants, might contribute to the transformation from HPV 16 persistent infection to cervical cancer.

Assessment of global and local region-based bilateral mammographic feature asymmetry to predict short-term breast cancer risk.

This study aims to develop and test a new imaging marker-based short-term breast cancer risk prediction model. An age-matched dataset of 566 screening mammography cases was used. All 'prior' images acquired in the two screening series were negative, while in the 'current' screening images, 283 cases were positive for cancer and 283 cases remained negative. For each case, two bilateral cranio-caudal view mammograms acquired from the 'prior' negative screenings were selected and processed by a computer-aided image processing scheme, which segmented the entire breast area into nine strip-based local regions, extracted the element regions using difference of Gaussian filters, and computed both global- and local-based bilateral asymmetrical image features. An initial feature pool included 190 features related to the spatial distribution and structural similarity of grayscale values, as well as of the magnitude and phase responses of multidirectional Gabor filters. Next, a short-term breast cancer risk prediction model based on a generalized linear model was built using an embedded stepwise regression analysis method to select features and a leave-one-case-out cross-validation method to predict the likelihood of each woman having image-detectable cancer in the next sequential mammography screening. The area under the receiver operating characteristic curve (AUC) values significantly increased from 0.5863 ± 0.0237 to 0.6870 ± 0.0220 when the model trained by the image features extracted from the global regions and by the features extracted from both the global and the matched local regions (p = 0.0001). The odds ratio values monotonically increased from 1.00-8.11 with a significantly increasing trend in slope (p = 0.0028) as the model-generated risk score increased. In addition, the AUC values were 0.6555 ± 0.0437, 0.6958 ± 0.0290, and 0.7054 ± 0.0529 for the three age groups of 37-49, 50-65, and 66-87 years old, respectively. AUC values of 0.6529 ± 0.1100, 0.6820 ± 0.0353, 0.6836 ± 0.0302 and 0.8043 ± 0.1067 were yielded for the four mammography density sub-groups (BIRADS from 1-4), respectively. This study demonstrated that bilateral asymmetry features extracted from local regions combined with the global region in bilateral negative mammograms could be used as a new imaging marker to assist in the prediction of short-term breast cancer risk.