Direct asymmetric synthesis of β-branched aromatic α-amino acids using engineered phenylalanine ammonia lyases.

β-Branched aromatic α-amino acids are valuable building blocks in natural products and pharmaceutically active compounds. However, their chemical or enzymatic synthesis is challenging due to the presence of two stereocenters. We design phenylalanine ammonia lyases (PAL) variants for the direct asymmetric synthesis of β-branched aromatic α-amino acids.

Catalytic N-Formylation of CO by Atomically Precise AuPd(DPPF) Clusters into a Two-Dimensional Metal-Organic Framework.

By highly efficient ligand-exchange strategy, atomically precise AuPd(PPh) (PPh=triphenylphosphine) cluster can be transformed into a AuPd(DPPF) (DPPF=1,1'-bis(diphenylphosphino)ferrocene) cluster that can maintain the atomic-packing structure but overcome the lability of AuPd(PPh) . Catalytic evaluation for the CO hydrogenation coupled with o-phenylenediamine demonstrates that the AuPd(DPPF) catalyst can remarkably enhance both activity and stability compared to the AuPd(PPh) catalyst. More notably, the direct construction of a two-dimensional metal-organic framework (2D MOF) can be elaborately accomplished in the formylation process of o-phenylenediamine, CO and H with zinc nitrate enabled by the AuPd(DPPF) catalyst.

LncRNA495810 Promotes Proliferation and Migration of Hepatocellular Carcinoma Cells by Interacting with FABP5.

Hepatocellular carcinoma (HCC) is one of the malignant tumors with high morbidity and mortality. Long non-coding RNAs (lncRNAs) are frequently dysregulated in human cancers and play an important role in the initiation and progression of HCC. Here, we investigated the expression of a new reported lncRNA495810 in our previous study by analyzing the publicly available datasets and using RT-qPCR assay.

The role of cholesterol-modified prognostic nutritional index in nutritional status assessment and predicting survival after liver resection for hepatocellular carcinoma.

Malnutrition, which is often underestimated in patients with hepatocellular carcinoma (HCC), has a proven adverse effect on survival rates. The purpose of this study was to verify the effectiveness of the cholesterol-modified prognostic nutritional index (CPNI) in determining the nutritional status and predicting overall survival (OS) and recurrence-free survival (RFS) in patients with HCC by comparing it with several other nutritional indicators. This retrospective single-center study enrolled 1450 consecutive HCC patients who underwent curative liver resection from January 2015 to November 2019.

Quantifying dose uncertainties resulting from cardiorespiratory motion in intensity-modulated proton therapy for cardiac stereotactic body radiotherapy.

Background: Cardiac stereotactic body radiotherapy (CSBRT) with photons efficaciously and safely treats cardiovascular arrhythmias. Proton therapy, with its unique physical and radiobiological properties, can offer advantages over traditional photon-based therapies in certain clinical scenarios, particularly pediatric tumors and those in anatomically challenging areas. However, dose uncertainties induced by cardiorespiratory motion are unknown.

Composite hydrogels with antioxidant and robust adhesive properties for the prevention of radiation-induced dermatitis.

Radiotherapy is a pivotal means of cancer treatment, but it often leads to radiation dermatitis, a skin injury caused by radiation-induced excess reactive oxygen species (ROS). Scavenging free radicals in the course of radiation therapy will be an effective means to prevent radiation dermatitis. This study demonstrates a novel double network hydrogel doped with MoS nanosheets for the prevention of radiation-induced dermatitis.

Neural Network Model Based on Branch Architecture for the Quality Assurance of Volumetric Modulated Arc Therapy.

Radiation therapy relies on quality assurance (QA) to verify dose delivery accuracy. However, current QA methods suffer from operation lag as well as inaccurate performance. Hence, to address these shortcomings, this paper proposes a QA neural network model based on branch architecture, which is based on the analysis of the category features of the QA complexity metrics.

An unusual aromatase/cyclase programs the formation of the phenyldimethylanthrone framework in anthrabenzoxocinones and fasamycin.

Aromatic polyketides are renowned for their wide-ranging pharmaceutical activities. Their structural diversity is mainly produced via modification of limited types of basic frameworks. In this study, we characterized the biosynthesis of a unique basic aromatic framework, phenyldimethylanthrone (PDA) found in (+)/(-)-anthrabenzoxocinones (ABXs) and fasamycin (FAS).

A gln-tRNA-based CRISPR/Cas9 knockout system enables the functional characterization of genes in the genetically recalcitrant brassica anthracnose fungus Colletotrichum higginsianum.

Colletotrichum higginsianum causes anthracnose disease in brassicas. The availability of the C. higginsianum genome has paved the way for the genome-wide exploration of genes associated with virulence/pathogenicity.

Application of Semiconductor Metal Oxide in Chemiresistive Methane Gas Sensor: Recent Developments and Future Perspectives.

The application of semiconductor metal oxides in chemiresistive methane gas sensors has seen significant progress in recent years, driven by their promising sensitivity, miniaturization potential, and cost-effectiveness. This paper presents a comprehensive review of recent developments and future perspectives in this field. The main findings highlight the advancements in material science, sensor fabrication techniques, and integration methods that have led to enhanced methane-sensing capabilities.

Clinical evaluation on automatic segmentation results of convolutional neural networks in rectal cancer radiotherapy.

Purpose: Image segmentation can be time-consuming and lacks consistency between different oncologists, which is essential in conformal radiotherapy techniques. We aimed to evaluate automatic delineation results generated by convolutional neural networks (CNNs) from geometry and dosimetry perspectives and explore the reliability of these segmentation tools in rectal cancer.

Methods: Forty-seven rectal cancer cases treated from February 2018 to April 2019 were randomly collected retrospectively in our cancer center.

Neural signals-based respiratory motion tracking: a proof-of-concept study.

Respiratory motion tracking techniques can provide optimal treatment accuracy for thoracoabdominal radiotherapy and robotic surgery. However, conventional imaging-based respiratory motion tracking techniques are time-lagged owing to the system latency of medical linear accelerators and surgical robots. This study aims to investigate the precursor time of respiratory-related neural signals and analyze the potential of neural signals-based respiratory motion tracking.

Application and Challenges of Statistical Process Control in Radiation Therapy Quality Assurance.

Quality assurance (QA) is important for ensuring precision in radiation therapy. The complexity and resource-intensive nature of QA has increased with the continual evolution of equipment and techniques. An effective approach is to improve the process control technology and resource optimization.

Guaranteed performance of individual control chart used in gamma passing rate-based patient-specific quality assurance.

Purpose: To assess the effect of sampling variability on the performance of individual charts (I-charts) for PSQA and provide a robust and reliable method for unknown PSQA processes.

Materials And Methods: A total of 1327 pretreatment PSQAs were analyzed. Different datasets with samples in the range of 20-1000 were used to estimate the lower control limit (LCL).

Engineering the Substrate Specificity of a P450 Dimerase Enables the Collective Biosynthesis of Heterodimeric Tryptophan-Containing Diketopiperazines.

Heterodimeric tryptophan-containing diketopiperazines (HTDKPs) are an important class of bioactive secondary metabolites. Biosynthesis offers a practical opportunity to access their bioactive structural diversity, however, it is restricted by the limited substrate scopes of the HTDKPs-forming P450 dimerases. Herein, by genome mining and investigation of the sequence-product relationships, we unveiled three important residues (F387, F388 and E73) in these P450s that are pivotal for selecting different diketopiperazine (DKP) substrates in the upper binding pocket.

Identification of disease propagation paths in two-layer networks.

To determine the path of disease in different types of networks, a new method based on compressive sensing is proposed for identifying the disease propagation paths in two-layer networks. If a limited amount of data from network nodes is collected, according to the principle of compressive sensing, it is feasible to accurately identify the path of disease propagation in a multilayer network. Experimental results show that the method can be applied to various networks, such as scale-free networks, small-world networks, and random networks.

A Functionalized Heterogeneous Catalyst from Atomically Precise Pd Au Clusters Facilitates Carbon-Carbon Bond Construction.

It has become possible to establish a connection between homogeneous and heterogeneous catalysis with atomically precise metal clusters. Due to their defined coordination geometry, in this work, atomically precise Pd Au (PPh ) clusters are exploited to identify the crucial factor that can impact the catalytic efficiency for the Suzuki-Miyaura cross-coupling process and further gain valuable insight into the exclusive cooperative effect of the central Pd atom and the peripheral Au atoms of the Pd Au (PPh ) cluster on controlling the cross-coupling reaction. Specifically, a heterogeneous catalyst, namely Pd Au @Resin, is designed by exchanging positively charged Pd Au (PPh ) clusters into the porous resin, thereby not only facilitating catalyst recyclability when performed in a batch reactor, but also realizing time-on-stream performance for the Suzuki-Miyaura cross-coupling reaction carried out in a fixed-bed reactor.

Autophagy mediates a direct synergistic interaction during co-transmission of two distinct arboviruses by insect vectors.

Multiple viral infections in insect vectors with synergistic effects are common in nature, but the underlying mechanism remains elusive. Here, we find that rice gall dwarf reovirus (RGDV) facilitates the transmission of rice stripe mosaic rhabdovirus (RSMV) by co-infected leafhopper vectors. RSMV nucleoprotein (N) alone activates complete anti-viral autophagy, while RGDV nonstructural protein Pns11 alone induces pro-viral incomplete autophagy.

Machine learning for predicting accuracy of lung and liver tumor motion tracking using radiomic features.

Background: Internal tumor motion is commonly predicted using external respiratory signals. However, the internal/external correlation is complex and patient-specific. The purpose of this study was to develop various models based on the radiomic features of computed tomography (CT) images to predict the accuracy of tumor motion tracking using external surrogates and to find accurate and reliable tracking algorithms.

Predictive value of magnetic resonance imaging radiomics-based machine learning for disease progression in patients with high-grade glioma.

Background: Accurately predicting the prognosis of patients with high-grade glioma (HGG) is potentially important for treatment. However, the predictive value of images of various magnetic resonance imaging (MRI) sequences for prognosis at different time points is unknown. We established predictive machine learning models of HGG disease progression and recurrence using MRI radiomics and explored the factors influencing prediction accuracy.

[Automatic Delineation of Clinical Target Volume and Organ at Risk by Deep Learning for Prostate Cancer Adaptive Radiotherapy].

Adaptive radiotherapy can modify the treatment plan online based on the clinical target volume (CTV) and organ at risk (OAR) contours on the cone-beam CT (CBCT) before treatment, improving the accuracy of radiotherapy. However, manual delineation of CTV and OAR on CBCT is time-consuming. In this study, a deep neural network-based method based on U-Net was purposed.

Genome-Wide Identification of Transcription Factor in in Response to Cold Stress.

Alfalfa represents one of the most important legume forages, and it is also applied as an organic fertilizer to improve soil quality. However, this perennial plant is native to warmer temperate regions, and its valuable cold-acclimation-related regulatory mechanisms are still less known. In higher plants, the transcription factors play pleiotropic regulatory roles in response to abiotic stresses.