Rapid and Complete Digestion of Refractory Geological Samples Using Ultrafine Powder for Accurate Analyses of Trace Elements.

Complete sample digestion is a prerequisite for acquiring high-quality analytical results for geological samples. Closed-vessel acid digestion (bomb) has typically been used for the total digestion of refractory geological samples. However, the long digestion time (4-5 days) and insoluble fluoride complexes still pose challenges for digesting refractory geological samples using this approach. In this study, an efficient and simplified digestion technique combining ultrafine powders from planetary ball milling with bomb digestion was developed for trace element analysis of refractory geological samples: peridotite and granitoid. The method shows two significant improvements compared with previous approaches. (1) By performing dry planetary ultrafine milling, the initial 200 mesh peridotite (<74 µm) could be reduced to 800 mesh (<20 µm) in 6 min at a ball-to-powder mass ratio of approximately 15 using 3 mm tungsten carbide milling balls. (2) Complete peridotite and granitoid dissolution were achieved in approximately 2 h, 60 times faster than what is achievable using previous methods (2 h vs 120 h). Moreover, ultrafine powders effectively suppressed insoluble fluoride formation during bomb digestion. A suite of peridotite and granitoid reference materials were measured to evaluate the stability of this method. This efficient, simple, and reliable sample digestion method could benefit geological, food, environmental, and other fields requiring solid sample decomposition via wet acid, fusion, combustion, or dry ashing.

Individualized driver amplitude in liver MR elastography: a linear regression study.

BACKGROUND: Current liver magnetic resonance elastography (MRE) scans often require adjustments to driver amplitude to produce acceptable images. This could lead to time wastage and the potential loss of an opportunity to capture a high-quality image. PURPOSE: To construct a linear regression model of individualized driver amplitude to improve liver MRE image quality. MATERIAL AND METHODS: Data from 95 liver MRE scans of 61 participants, including abdominal missing volume ratio (AMVR), breath-holding status, the distance from the passive driver on the skin surface to the liver edge (Dd-l), body mass index (BMI), and lateral deflection of the passive driver with respect to the human sagittal plane (Angle α), were continuously collected. The Spearman correlation analysis and lasso regression were conducted to screen the independent variables. Multiple linear regression equations were developed to determine the optimal amplitude prediction model. RESULTS: The optimal formula for linear regression models: driver amplitude (%) = -16.80 + 78.59 × AMVR - 11.12 × breath-holding (end of expiration = 1, end of inspiration = 0) + 3.16 × Dd-l + 1.94 × BMI + 0.34 × angle α, with the model passing the F test (F = 22.455, P <0.001) and R2 value of 0.558. CONCLUSION: The individualized amplitude prediction model based on AMVR, breath-holding status, Dd-l, BMI, and angle α is a valuable tool in liver MRE examination.

Nomogram-based risk assessment for emergency cervical cerclage failure in patients with cervical insufficiency.

Background: Cervical insufficiency can lead to preterm birth and neonatal mortality. Emergency cervical cerclage is a surgical intervention aimed at preventing preterm birth in patients with cervical insufficiency. However, some patients may experience cerclage failure. This study aimed to identify the risk factors associated with cerclage failure and develop a predictive nomogram model for patients with cervical insufficiency undergoing emergency cervical cerclage. Methods: Data of 200 patients who underwent emergency cervical cerclage for cervical insufficiency were retrospectively analyzed. Patients were categorized into successful and failed groups based on their ability to take the infant home. Univariate and multivariate logistic regression analyses were performed to identify risk factors for cerclage failure. A nomogram model was developed based on multivariate logistic regression results, and its performance was assessed using receiver operating characteristic curves, calibration plots, and decision curve analysis (DCA). Results: Univariate logistic regression analysis identified 11 potential risk factors for cerclage failure, including the presence of polycystic ovary syndrome (PCOS), vaginitis, cervical dilation, preoperative C-reactive protein, routine vaginal lavage after cervical cerclage, delivery, gestational age, extended days, chorioamnionitis, intrauterine infection, cervical laceration, and premature rupture of membranes. Multivariate logistic regression analysis revealed that PCOS, cervical dilation after cervical cerclage were independent risk factors for cerclage failure while routine vaginal lavage was a protective factor against failure. The nomogram predictive model demonstrated an area under the curve value of 0.975, indicating excellent discriminatory ability. The calibration plot showed good consistency between the nomogram predictions and actual observations. DCA demonstrated the strong clinical applicability of the nomogram. Conclusions: This study successfully identified risk factors associated with emergency cervical cerclage failure in patients with cervical insufficiency and developed a predictive nomogram model. This model can assist clinicians in making informed decisions and accurately predicting the risk of cerclage failure in these patients.

Isolated ipsilateral ptosis associated with ventral midbrain infarction: a case report and literature review.

Documented cases of ipsilateral ptosis caused by midbrain infarction remain rare. Herein, we present a patient with isolated ipsilateral ptosis that was initially considered to be a consequence of myasthenia gravis but was subsequently attributed to ventral midbrain infarction. We also discuss the possible underlying mechanisms; ipsilateral ptosis in our patient was attributed to selective damage of the levator palpebral muscle branch of the oculomotor nerve. The patient was started on aspirin (200 mg once daily) and atorvastatin (40 mg once daily). Improvement in ptosis occurred from day 5 of admission, and the patient was subsequently discharged. Ptosis disappeared 1 month after onset. This report describes an extremely rare case of ventral midbrain infarction presenting with isolated ipsilateral ptosis. Careful examination, including magnetic resonance imaging, is essential in such patients, especially in those with multiple cerebrovascular risk factors.

The causal relationship between gut microbiota and alopecia areata: a Mendelian randomization analysis.

Background: Increasing evidence suggests a robust correlation between the gut microbiome and alopecia areata. In light of the extensive diversity of gut microbiota, this study aims to utilize state-of-the-art and comprehensive data to explore the causative association between gut microbiota and alopecia areata. Objective: We conducted a Mendelian randomization (MR)-based two-sample study to elucidate the causal relationship between gut microbiota and alopecia areata. Method: Summary information on Ncase = 767 and Ncontrol = 394,105 cases of alopecia areata was obtained from the FinnGen study. A total of 473 gut microbial taxa were summarized from the genome-wide association study (GWAS) catalog. The study comprised a forward Mendelian randomization (MR) analysis with the gut microbiome as the exposure factor and alopecia areata as the outcome, as well as a reverse MR analysis with alopecia areata as the exposure factor and the gut microbiome as the outcome. Various analytical methods including inverse variance weighting (IVW), Weighted Median, MR-Egger, Weighted Mode, and Simple Mode were employed. Subsequently, sensitivity analysis was conducted to ensure the robustness of our research findings. Result: This study has established a causal relationship between gut microbiota and alopecia areata. Forward causal analysis revealed causality relationships between 16 gut microbial taxa and alopecia areata, while reverse causal analysis found that there may be a causal relationship between alopecia areata and 16 gut microbial taxa (not statistically significant). Conclusion: Our study findings suggest a causal relationship between gut microbiota and alopecia areata, providing potential guidance for future clinical trials.

The value of machine learning based on CT radiomics in the preoperative identification of peripheral nerve invasion in colorectal cancer: a two-center study.

BACKGROUND: We aimed to explore the application value of various machine learning (ML) algorithms based on multicenter CT radiomics in identifying peripheral nerve invasion (PNI) of colorectal cancer (CRC). METHODS: A total of 268 patients with colorectal cancer who underwent CT examination in two hospitals from January 2016 to December 2022 were considered. Imaging and clinicopathological data were collected through the Picture Archiving and Communication System (PACS). The Feature Explorer software (FAE) was used to identify the peripheral nerve invasion of colorectal patients in center 1, and the best feature selection and classification channels were selected. Finally, the best feature selection and classifier pipeline were verified in center 2. RESULTS: The six-feature models using RFE feature selection and GP classifier had the highest AUC values, which were 0.610, 0.699, and 0.640, respectively. FAE generated a more concise model based on one feature (wavelet-HLL-glszm-LargeAreaHighGrayLevelEmphasis) and achieved AUC values of 0.614 and 0.663 on the validation and test sets, respectively, using the "one standard error" rule. Using ANOVA feature selection, the GP classifier had the best AUC value in a one-feature model, with AUC values of 0.611, 0.663, and 0.643 on the validation, internal test, and external test sets, respectively. Similarly, when using the "one standard error" rule, the model based on one feature (wave-let-HLL-glszm-LargeAreaHighGrayLevelEmphasis) achieved AUC values of 0.614 and 0.663 on the validation and test sets, respectively. CONCLUSIONS: Combining artificial intelligence and radiomics features is a promising approach for identifying peripheral nerve invasion in colorectal cancer. This innovative technique holds significant potential for clinical medicine, offering broader application prospects in the field. CRITICAL RELEVANCE STATEMENT: The multi-channel ML method based on CT radiomics has a simple operation process and can be used to assist in the clinical screening of patients with CRC accompanied by PNI. KEY POINTS: • Multi-channel ML in the identification of peripheral nerve invasion in CRC. • Multi-channel ML method based on CT-radiomics can detect the PNI of CRC. • Early preoperative identification of PNI in CRC is helpful to improve the formulation of treatment strategies and the prognosis of patients.

Hemodynamic predictors of early neurological deterioration and clinical outcome after endovascular treatment in large artery occlusion.

Objective: Half of the patients with acute large artery occlusion (LAO) have poor outcomes after endovascular treatment (EVT). Early complications such as cerebral edema and symptomatic intracranial hemorrhage (sICH) can lead to early neurological deterioration (END), which correlates with hemodynamics. This study aimed to identify the hemodynamic predictors of END and outcomes in LAO patients after EVT. Methods: A total of 76 patients with anterior circulation LAO who underwent EVT and received transcranial Doppler (TCD) monitoring were included. Bilateral middle cerebral artery (MCA) blood flow velocities (BFVs) were measured repeatedly within 1 week. Mean flow velocities (MFV) and MFV index (ipsilateral MFV/contralateral MFV) were calculated. The primary outcome was the incidence of END within 72 h. The secondary outcome was the functional outcome at 90 days-a good outcome was defined as a modified Rankin scale (mRS) score of 0-2, while a poor outcome was defined as an mRS score of 3-6. Results: A total of 13 patients (17.1 %) experienced END within 72 h, including 5 (38.5 %) with cerebral edema, 5 (38.5 %) with sICH, and 3 (23.0 %) with infarct progression. Multivariable logistic regression analysis showed that a higher 24 h MFV index was independently associated with END (aOR 10.5; 95 % CI 2.28-48.30, p = 0.003) and a poor 90-day outcome (aOR 5.10; 95 % CI 1.38-18.78, p = 0.014). The area under the receiver operating characteristic (ROC) curve (AUC) of the 24 h MFV index for predicting END was 0.807 (95 % CI 0.700-0.915, p = 0.0005), the sensitivity was 84.6 %, and the specificity was 66.7 %. At the 1-week TCD follow-up, patients who had poor 90-day outcomes showed significantly higher 1-week iMFV [73.5 (58.4-99.0) vs. 57.7 (45.3-76.3), p = 0.004] and MFV index [1.24 (0.98-1.57) vs.1.0 (0.87-1.15) p = 0.007]. A persistent high MFV index (PHMI) was independently associated with a poor outcome (aOR 7.77, 95 % CI 1.81-33.3, p = 0.006). Conclusion: TCD monitoring within 24 h after EVT in LAO patients can help predict END, while dynamic follow-up within 1 week is valuable in predicting clinical outcomes.

Complete mitochondrial genome of Angelica dahurica and its implications on evolutionary analysis of complex mitochondrial genome architecture in Apiaceae.

Angelica dahurica is a kind of Chinese traditional herbs with economic and ornament value, widely distributed in China. Despite its significance, there have been limited comprehensive investigations on the genome of A. dahurica, particularly regarding mitochondrial genomes. To investigate the conversion between mitochondrial genome and chloroplast genome, a complete and circular mitochondrial genome was assembled using Oxford Nanopore Technologies (ONT) long reads. The mitochondrial genome of A. dahurica had a length of 228,315 base pairs (bp) with 45.06% GC content. The mitochondrial genome encodes 56 genes, including 34 protein-coding genes, 19 tRNA genes and 3 rRNA genes. Moreover, we discovered that 9 homologous large fragments between chloroplast genome and mitochondrial genome based on sequence similarity. This is the first report for A. dahurica mitochondrial genome, which could provide an insight for communication between plastid genome, and also give a reference genome for medicinal plants within the Angelica family.

Ruthenium Complex Suppresses Proliferation of Residual Hepatocellular Carcinoma after Incomplete Radiofrequency Ablation Therapy.

BACKGROUND: Radiofrequency ablation (RFA) is an effective therapy for hepatocellular carcinoma (HCC). However, incomplete radiofrequency ablation (IRFA) can promote the progression of residual cancer cells, which is a serious problem in the clinical application of RFA. Therefore, it is of great significance to explore the mechanism and countermeasures of the progression of residual tumors after IRFA. Our previous study confirmed that IRFA can activate the hypoxia/ autophagy pathway of residual tumors in mice and then induce the proliferation of residual tumor cells. Additionally, we found a metal ruthenium complex [Ru(bpy)2(ipad)](ClO4)2 (Ru, where bpy = 2,2'-bipyridine and ipad = 2-(anthracene-9,10-dione-2-yl)imidazo[4,5-f][1,10]phenanthroline) can effectively inhibit hypoxia-inducible factor (HIF-1α) and has good anti-tumor effect in a hypoxic environment; however, whether Ru could suppress the proliferation of residual tumor cells after IRFA is unknown. OBJECTIVE: This study intends to evaluate the effect of Ru in suppressing the proliferation of residual hepatocellular carcinoma after IRFA in a mice model. METHODS: The Hepa1-6 xenograft mouse model was established in C57BL/6 mice to simulate clinical IRFA. H&E staining was used to evaluate the biosafety of major organs in the treated mice. TUNEL assay was employed to assess the antitumor effect. Immunohistochemically and immunofluorescence staining was performed to detect the expression of HIF-1α and autophagy-related proteins. The ELISA assay was used to examine the cytokines of interferon-gamma (IFN-γ) and interleukin 10 (IL-10). RESULTS: Our findings revealed that the residual tumor relapsed via the HIF-1α/LC3B/P62 autophagy- related pathway after IRFA, while Ru could suppress this process. In addition, it was demonstrated that Ru could effectively activate the immune system of the mice and reverse the tumor immune suppression microenvironment after IRFA. CONCLUSION: The ruthenium complex Ru could suppress the proliferation of residual hepatocellular carcinoma cells after IRFA in the mice model. This study introduces a novel approach that combines the use of ruthenium complexes with IRFA, offering a potential solution to address the reoccurrence of residual liver cancer following IRFA in clinical settings.

Metabolomics of Vitis davidii Foëx. grapes from southern China: Flavonoids and volatiles reveal the flavor profiles of five spine grape varieties.

The spine grapes (Vitis davidii Foëx.) are wild grape species that grow in southern China, and can be used for table grapes, juicing and winemaking. To systematically investigate the flavor profiles of spine grapes, flavonoids and volatile compounds were detected in five spine grape varieties (Seputao, Ziqiu, Miputao, Tianputao and Baiputao) using HPLC-QqQ-MS/MS and GC-MS. The content of flavonoids highly depended on the variety, such as the total concentrations of anthocyanins (91.43-328.85 mg/kg FW) and flavonols (33.90 to 83.16 mg/kg FW). The volatile compounds with higher odor active value were selected to describe the aroma of spine grapes. Hexanal, (E)-2-hexenal and (E, Z)-2,6-nonadienal contributed to the higher herbaceous flavor to Baiputao and Ziqiu. ß-Damascenone and (E)-2-nonenal gave Baiputao a flavor with more floral, fruity and earthy. Their characteristic flavor compounds were subsequently revealed using multivariate statistical analysis. The results helped producers to further develop and utilize the spine grapes.

Phar-LSTM: a pharmacological representation-based LSTM network for drug-drug interaction extraction.

Pharmacological drug interactions are among the most common causes of medication errors. Many different methods have been proposed to extract drug-drug interactions from the literature to reduce medication errors over the last few years. However, the performance of these methods can be further improved. In this paper, we present a Pharmacological representation-based Long Short-Term Memory (LSTM) network named Phar-LSTM. In this method, a novel embedding strategy is proposed to extract pharmacological representations from the biomedical literature, and the information related to the target drug is considered. Then, an LSTM-based multi-task learning scheme is introduced to extract features from the different but related tasks according to their corresponding pharmacological representations. Finally, the extracted features are fed to the SoftMax classifier of the corresponding task. Experimental results on the DDIExtraction 2011 and DDIExtraction 2013 corpuses show that the performance of Phar-LSTM is competitive compared with other state-of-the-art methods. Our Python implementation and the corresponding data of Phar-LSTM are available by using the DOI 10.5281/zenodo.8249384.

A neural network-based framework to understand the type 2 diabetes-related alteration of the human gut microbiome.

The identification of microbial markers adequate to delineate the disease-related microbiome alterations from the complex human gut microbiota is of great interest. Here, we develop a framework combining neural network (NN) and random forest, resulting in 40 marker species and 90 marker genes identified from the metagenomic data set (185 healthy and 183 type 2 diabetes [T2D] samples), respectively. In terms of these markers, the NN model obtained higher accuracy in classifying the T2D-related samples than other methods; the interaction network analyses identified the key species and functional modules; the regression analysis determined that fasting blood glucose is the most significant factor (p < 0.05) in the T2D-related alteration of the human gut microbiome. We also observed that those marker species varied little across the case and control samples greatly shift in the different stages of the T2D development, suggestive of their important roles in the T2D-related microbiome alteration. Our study provides a new way of identifying the disease-related biomarkers and analyzing the role they may play in the development of the disease.

Determination of orcinol glucoside by LC-MS in Curculigo orchioides and its application to a pharmacokinetic study

ABSTRACT This study was designed to explore the pharmacokinetic regularity of the plasma concentration, tissue distribution and excretion of orcinol glucoside from aqueous extracts of raw and processed Curculigo orchioides Gaertn., Hypoxidaceae. The experiment first used an ultrahigh-performance liquid chromatography-tandem mass spectrometry approach with multiple reaction monitoring and a positive mode to separate orcinol glucoside from naringin to obtain the plasma concentration curves, bar graph of tissue distribution and excretion curves. These results might be beneficial for reasonable clinical application of C. orchioides and for further development of its wine and salt-processing mechanism.