Antimony release and volatilization from rice paddy soils: Field and microcosm study

The fate of antimony (Sb) in submerged soils and the impact of common agricultural practices (e.g., manuring) on Sb release and volatilization is understudied. We investigated porewater Sb release and volatilization in the field and laboratory for three rice paddy soils. In the field study, the porewater Sb concentration (up to 107.1 μg L^-1) was associated with iron (Fe) at two sites, and with pH, Fe, manganese (Mn), and sulfate (SO₄^2-) at one site. The surface water Sb concentrations (up to 495.3 ± 113.7 μg L^-1) were up to 99 times higher than the regulatory values indicating a potential risk to aquaculture and rice agriculture. For the first time, volatile Sb was detected in rice paddy fields using a validated quantitative method (18.1 ± 5.2 to 217.9 ± 160.7 mg ha^-1 y^-1). We also investigated the influence of two common rice agriculture practices (flooding and manuring) on Sb release and volatilization in a 56-day microcosm experiment using the same soils from the field campaign. Flooding induced an immediate, but temporary, Sb release into the porewater that declined with SO₄^2-, indicating that SO₄^2- reduction may reduce porewater Sb concentrations. A secondary Sb release, corresponding to Fe reduction in the porewater, was observed in some of the microcosms. Our results suggest flooding-induced Sb release into rice paddy porewaters is temporary but relevant. Manuring the soils did not impact the porewater Sb concentration but did enhance Sb volatilization. Volatile Sb (159.6 ± 108.4 to 2237.5 ± 679.7 ng kg^-1 y^-1) was detected in most of the treatments and was correlated with the surface water Sb concentration. Our study indicates that Sb volatilization could be occurring at the soil-water interface or directly in the surface water and highlights that future works should investigate this potentially relevant mechanism.

[Clinical efficacy of split liver transplantation in the treatment of children with biliary atresia]

Objective: To compare the clinical efficacy of split liver transplantation (SLT) and living donor liver transplantation(LDLT) in the treatment of children with biliary atresia. Methods: The clinical data of 64 children with biliary atresia who underwent SLT and 44 children who underwent LDLT from June 2017 to May 2022 at Liver Surgery & Liver Transplantation Center,the Third Affiliated Hospital of Sun Yat-sen University were retrospectively analyzed. Among the children who received SLT, there were 40 males and 24 females. The median age at transplantation was 8 months (range:4 to 168 months). Among the patients who received LDLT, there were 24 males and 20 females. The age at transplantation ranged from 4 to 24 months,with a median age of 7 months. Sixty-four children with biliary atresia were divided into two groups according to the SLT operation time: 32 cases in the early SLT group(June 2017 to January 2019) and 32 cases in the technically mature SLT group (February 2019 to May 2022). Rank sum test or t test was used to compare the recovery of liver function between the LDLT group and the SLT group,and between the early SLT group and the technically mature SLT group. The incidence of postoperative complications was compared by χ² test or Fisher exact probability method. Kaplan-Meier method and Log-rank test were used for survival analysis. Results: The cold ischemia time(M (IQR)) (218 (65) minutes), intraoperative blood loss(175 (100) ml) and graft-to-recipient body weight ratio (3.0±0.7) in the LDLT group were lower than those in the SLT group(500 (130) minutes, 200 (250) ml, 3.4±0.8) (Z=-8.064,Z=-2.969, t=-2.048, all P<0.05). The cold ischemia time(457(158)minutes) and total hospital stay ((37.4±22.4)days) in the technically mature SLT group were lower than those in the early SLT group(510(60)minutes, (53.0±39.0)days).The differences were statistically significant (Z=-2.132, t=1.934, both P<0.05).The liver function indexes of LDLT group and SLT group showed unimodal changes within 1 week after operation. The peak values of ALT, AST, prothrombin time, activeated partial thromboplasting time, international normalized ratio, fibrinogen and creatinine all appeared at 1 day after operation, and the peak value of prothrombin activity appeared at 3 days after operation. All indicators returned to normal at 7 days after operation. The 1-,2-,and 3-year overall survival rates were 95.5% in LDLT group and 93.5% in the technically mature SLT group, and the difference was not statistically significant. The 1-,2-,and 3-year overall survival rates were 90.2% in the early SLT group and 93.5% in the technically mature SLT group, and there was no significant difference between the two groups(P>0.05). The main complications of the early SLT group were surgery-related complications(28.1%,9/32), and the main complications of the technically mature SLT group were non-surgery-related complications(21.9%,7/32). There were 5 deaths in the SLT group,including 4 in the early SLT group and 1 in the technically mature SLT group. Conclusion: The survival rate of SLT in the treatment of biliary atresia is comparable to that of LDLT.

PSI-18 Effect of Heat Processing Methods on Carbohydrate Subfractions and Degradation in Relation to Carbohydrate Molecular Spectral Profile of Barley Grain Using Advanced Molecular Spectroscopy in Ruminants

To our knowledge, there are few studies on the association between carbohydrate molecular structure spectral profiles of barley grain and ruminant-relevant nutritional characteristics. This study aimed to study associate processing-induced changes in carbohydrate molecular structure with changes in ruminant-relevant carbohydrate nutritional profiles. The heat processing methods included: dry roasting, autoclaving, and microwave irradiation. The ruminant-relevant carbohydrate nutritional profiles were determined which included carbohydrate chemical profiles, carbohydrate subfractions, ruminant-relevant carbohydrate digestion. The molecular structure spectral profiles were determined using vibrational molecular spectroscopy (ATR-FT/IR). The results showed that heat related processing significantly induced carbohydrate molecular spectral profiles. The heat related processing also significantly changed ruminant-relevant nutritional characteristics. There was an association between processing induced carbohydrate molecular structure changes and ruminant-relevant carbohydrate nutritional profiles. The advanced vibrational molecular spectroscopic technique (ATR-FTIR) shows the great potential as a fast analytical tool to predict ruminant-relevant carbohydrate nutritional characteristics.

Robust analysis of cancer heterogeneity for high-dimensional data

Cancer heterogeneity plays an important role in the understanding of tumor etiology, progression, and response to treatment. To accommodate heterogeneity, cancer subgroup analysis has been extensively conducted. However, most of the existing studies share the limitation that they cannot accommodate heavy-tailed or contaminated outcomes and also high dimensional covariates, both of which are not uncommon in biomedical research. In this study, we propose a robust subgroup identification approach based on M-estimators together with concave and pairwise fusion penalties, which advances from existing studies by effectively accommodating high-dimensional data containing some outliers. The penalties are applied on both latent heterogeneity factors and covariates, where the estimation is expected to achieve subgroup identification and variable selection simultaneously, with the number of subgroups being apriori unknown. We innovatively develop an algorithm based on parallel computing strategy, with a significant advantage of capable of processing large-scale data. The convergence property of the proposed algorithm, oracle property of the penalized M-estimators, and selection consistency of the proposed BIC criterion are carefully established. Simulation and analysis of TCGA breast cancer data demonstrate that the proposed approach is promising to efficiently identify underlying subgroups in high-dimensional data.

Heritability estimation for a linear combination of phenotypes via ridge regression

MOTIVATION

The joint analysis of multiple phenotypes is important in many biological studies, such as plant and animal breeding. The heritability estimation for a linear combination of phenotypes is designed to account for correlation information. Existing methods for estimating heritability mainly focus on single phenotypes under random-effect models. These methods also require some stringent conditions, which calls for a more flexible and interpretable method for estimating heritability. Fixed-effect models emerge as a useful alternative.

RESULTS

In this paper, we propose a novel heritability estimator based on multivariate ridge regression for linear combinations of phenotypes, yielding accurate estimates in both sparse and dense cases. Under mild conditions in the high-dimensional setting, the proposed estimator appears to be consistent and asymptotically normally distributed. Simulation studies show that the proposed estimator is promising under different scenarios. Compared with independently combined heritability estimates in the case of multiple phenotypes, the proposed method significantly improves the performance by considering correlations among those phenotypes. We further demonstrate its application in heritability estimation and correlation analysis for the Oryza sativa rice dataset.

AVAILABILITY AND IMPLEMENTATION

An R package implementing the proposed method is available at https://github.com/xg-SUFE1/MultiRidgeVar, where covariance estimates are also given together with heritability estimates.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Whole genome and transcriptome analysis enhances precision cancer treatment options

BACKGROUND

Recent advances are enabling delivery of precision genomic medicine to cancer clinics. While the majority of approaches profile panels of selected genes or hotspot regions, comprehensive data provided by whole genome and transcriptome sequencing and analysis (WGTA) presents an opportunity to align a much larger proportion of patients to therapies.

PATIENTS AND METHODS

Samples from 570 patients with advanced or metastatic cancer of diverse types enrolled in the Personalized OncoGenomics (POG) program underwent WGTA. DNA-based data, including mutations, copy number, and mutation signatures, were combined with RNA-based data, including gene expression and fusions, to generate comprehensive WGTA profiles. A multidisciplinary molecular tumour board used WGTA profiles to identify and prioritize clinically actionable alterations and inform therapy. Patient responses to WGTA-informed therapies were collected.

RESULTS

Clinically actionable targets were identified for 83% of patients, 37% of whom received WGTA-informed treatments. RNA expression data were particularly informative, contributing to 67% of WGTA-informed treatments; 25% of treatments were informed by RNA expression alone. Of a total 248 WGTA-informed treatments, 46% resulted in clinical benefit. RNA expression data were comparable to DNA-based mutation and copy number data in aligning to clinically beneficial treatments. Genome signatures also guided therapeutics including platinum, PARP inhibitors, and immunotherapies. Patients accessed WGTA-informed treatments through clinical trials (19%), off-label use (35%), and as standard therapies (46%) including those which would not otherwise have been the next choice of therapy, demonstrating the utility of genomic information to direct use of chemotherapies as well as targeted therapies.

CONCLUSIONS

Integrating RNA expression and genome data illuminated treatment options that resulted in 46% of treated patients experiencing positive clinical benefit, supporting the use of comprehensive WGTA profiling in clinical cancer care.

CLINICAL TRIAL NUMBER

NCT02155621.

Broadband and high-efficiency photonic spin-Hall effect with all-metallic metasurfaces

In this paper, all-metallic reflective metasurfaces comprising S-shape streamline structures are proposed to achieve the photonic spin-Hall effect with average cross-polarization conversion efficiency exceeding ∼84% in the range of 8-14 µm. By comparing with all-metallic nanobricks, it is demonstrated that the electric field coupling could be enhanced by constructing a similar split ring resonator between adjacent unit elements to further improve its efficiency and bandwidth. As a proof of concept, the photonic spin Hall effect and spin-to-orbit angular momentum conversion could be observed by two metadevices with the maximum diffraction efficiency of ∼95.7%. Such an all-metallic configuration may provide a platform for various high-efficiency electromagnetic components, catenary optics, and practical applications.

Improved tenderness of beef from bulls supplemented with active dry yeast is related to matrix metalloproteinases and reduced oxidative stress

Supplementing diets with active dry yeast (ADY, Saccharomyces cerevisiae) improves the carcass quality grade of beef cattle and the tenderness of beef. The relevant mechanisms have not been fully elucidated, but may be related to the effect of ADY on oxidative stress and the activity of matrix metalloproteinases (MMPs). To provide further insight into these mechanisms, this study evaluated the influence of ADY supplementation on growth performance, carcass traits, meat quality, concentrations of MMPs in serum (MMP-2, MMP-9 and MMP-13), oxidative stress indices and antioxidant capacity indices in beef cattle. Forty-six crossbred Simmental × Yanbian bulls (∼18 months of age, BW 436 ± 35 kg) participated in a 145-day finishing trial. ADY supplementation significantly improved marbling deposition, intramuscular fat content, and beef tenderness (P < 0.05); altered individual fatty acid proportions in the beef and increased saturated fatty acids while decreasing polyunsaturated fatty acids (P < 0.05); significantly decreased the abundance of reactive oxygen species in serum and meat; significantly increased the level of superoxide dismutase in meat (P < 0.05); tended to increase the level of catalase (P = 0.075) in serum and glutathione reductase (P = 0.066) in meat; and increased the secretion of MMPs. The improvement of beef tenderness following ADY supplementation of finishing bulls is related to the effects of ADY on the secretion of MMPs and the lowering of oxidative stress.

[Pituicytoma: a clinicopathological analysis of twenty-one cases]

Objective: To investigate the clinicopathological features and treatment strategies of pituicytoma. Methods: Twenty-one cases of pituicytoma were collected at the First Affiliated Hospital of Nanjing Medical University and Jinling Hospital, Nanjing, China from 2009 to 2020. The clinical data of 21 pituicytoma patients was retrospectively analyzed, and the relevant literature was reviewed. Results: Twenty-one patients aged 4 to 68 years, including 8 males and 13 females. All patients underwent surgical treatment. Histologically, the tumor was consisted almost entirely of elongate, bipolar spindle cells arranged in a fascicular or storiform pattern. Mitotic figures were rare. Immunohistochemically, tumor cells were diffusely positive for S-100 protein (21/21), vimentin (15/15) and TTF1 (14/14), while they were weakly or focally positive for GFAP (13/16) and EMA (6/12). CKpan was negative in all cases and Ki-67 proliferation index was low (<5%). Among the 18 patients with follow-up, all survived and 2 relapsed after surgery. Conclusions: Pituicytoma is a rare low-grade glioma of the sellar area. It is easily confused with other sellar tumors. Preoperative diagnosis is difficult. It needs to be confirmed by histopathology and immunohistochemistry. Microsurgery is the main treatment method at present.

Automated 3D Fetal Brain Segmentation Using an Optimized Deep Learning Approach

BACKGROUND AND PURPOSE

MR imaging provides critical information about fetal brain growth and development. Currently, morphologic analysis primarily relies on manual segmentation, which is time-intensive and has limited repeatability. This work aimed to develop a deep learning-based automatic fetal brain segmentation method that provides improved accuracy and robustness compared with atlas-based methods.

MATERIALS AND METHODS

A total of 106 fetal MR imaging studies were acquired prospectively from fetuses between 23 and 39 weeks of gestation. We trained a deep learning model on the MR imaging scans of 65 healthy fetuses and compared its performance with a 4D atlas-based segmentation method using the Wilcoxon signed-rank test. The trained model was also evaluated on data from 41 fetuses diagnosed with congenital heart disease.

RESULTS

The proposed method showed high consistency with the manual segmentation, with an average Dice score of 0.897. It also demonstrated significantly improved performance (P < .001) based on the Dice score and 95% Hausdorff distance in all brain regions compared with the atlas-based method. The performance of the proposed method was consistent across gestational ages. The segmentations of the brains of fetuses with high-risk congenital heart disease were also highly consistent with the manual segmentation, though the Dice score was 7% lower than that of healthy fetuses.

CONCLUSIONS

The proposed deep learning method provides an efficient and reliable approach for fetal brain segmentation, which outperformed segmentation based on a 4D atlas and has been used in clinical and research settings.

Experimental Evidence of Intrinsic Current Generation by Turbulence in Stationary Tokamak Plasmas

High-β_{θe} (a ratio of the electron thermal pressure to the poloidal magnetic pressure) steady-state long-pulse plasmas with steep central electron temperature gradient are achieved in the Experimental Advanced Superconducting Tokamak. An intrinsic current is observed to be modulated by turbulence driven by the electron temperature gradient. This turbulent current is generated in the countercurrent direction and can reach a maximum ratio of 25% of the bootstrap current. Gyrokinetic simulations and experimental observations indicate that the turbulence is the electron temperature gradient mode (ETG). The dominant mechanism for the turbulent current generation is due to the divergence of ETG-driven residual flux of current. Good agreement has been found between experiments and theory for the critical value of the electron temperature gradient triggering ETG and for the level of the turbulent current. The maximum values of turbulent current and electron temperature gradient lead to the destabilization of an m/n=1/1 kink mode, which by counteraction reduces the turbulence level (m and n are the poloidal and toroidal mode number, respectively). These observations suggest that the self-regulation system including turbulence, turbulent current, and kink mode is a contributing mechanism for sustaining the steady-state long-pulse high-β_{θe} regime.