Intravenous metastasis of unexpected uterine sarcoma in the context of uterine fibroids: case report and literature review.

Objective: Endometrial stromal tumors are rare and complex mesenchymal tumors that often present with clinical symptoms similar to uterine leiomyomas. Due to their atypical nature, they are prone to be misdiagnosed or overlooked by healthcare professionals. This study presents a case report of an incidentally discovered endometrial stromal sarcoma with venous metastasis, which was initially misdiagnosed as a uterine leiomyoma.

Induction Chemotherapy Followed by Radiotherapy vs Chemoradiotherapy in Nasopharyngeal Carcinoma: A Randomized Clinical Trial.

Importance: Induction chemotherapy plus concurrent chemoradiotherapy is recommended for locoregionally advanced nasopharyngeal carcinoma but is associated with higher rates of acute toxic effects and low compliance. Evidence on de-escalating treatment intensity after induction chemotherapy is limited.

Objective: To assess if radiotherapy was noninferior to chemoradiotherapy after induction chemotherapy for locoregionally advanced nasopharyngeal carcinoma.

Targeted Delivery of Peptide Nucleic Acid by Biomimetic Nanoparticles Based on Extracellular Vesicle-coated Mesoporous Silica Nanoparticles.

Background: Peptide nucleic acid (PNA) plays an important role in antimicrobial activity, but its cellular permeability is poor. To overcome this limitation, we constructed biomimetic nanoparticles by using extracellular vesicle (EV)-coated mesoporous silicon nanoparticles (MSNs) to deliver PNA to Staphylococcus aureus (S. aureus) and improve its antisense therapeutic effect.

Apatinib combined with camrelizumab in the treatment of recurrent/metastatic nasopharyngeal carcinoma: a prospective multicenter phase II study.

Background: Preclinical studies demonstrated that immune checkpoint inhibitors combined with antiangiogenic drugs have a synergistic anti-tumor effect. This present phase II trial aimed to evaluate the efficacy and safety of apatinib combined with camrelizumab in patients with recurrent/metastatic nasopharyngeal carcinoma (RM-NPC).

Methods: Patients with RM-NPC were administered with apatinib at 250 mg orally once every day and with camrelizumab at 200 mg intravenous infusion every 2 weeks until the disease progressed or toxicity became unacceptable.

Deep learning at the edge enables real-time streaming ptychographic imaging.

Coherent imaging techniques provide an unparalleled multi-scale view of materials across scientific and technological fields, from structural materials to quantum devices, from integrated circuits to biological cells. Driven by the construction of brighter sources and high-rate detectors, coherent imaging methods like ptychography are poised to revolutionize nanoscale materials characterization. However, these advancements are accompanied by significant increase in data and compute needs, which precludes real-time imaging, feedback and decision-making capabilities with conventional approaches.

Novel chimeric antigen receptor T cell-based immunotherapy: a perspective for triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is highly aggressive and does not express estrogen receptor (ER), progesterone (PR), or human epidermal growth factor receptor 2 (HER2). It has a poor prognosis, and traditional endocrine and anti-HER2 targeted therapies have low efficacy against it. In contrast, surgery, radiotherapy, and/or systemic chemotherapy are relatively effective at controlling TNBC.

Three-Dimensional Electrochemical Sensors for Food Safety Applications.

Considering the increasing concern for food safety, electrochemical methods for detecting specific ingredients in the food are currently the most efficient method due to their low cost, fast response signal, high sensitivity, and ease of use. The detection efficiency of electrochemical sensors is determined by the electrode materials' electrochemical characteristics. Among them, three-dimensional (3D) electrodes have unique advantages in electronic transfer, adsorption capacity and exposure of active sites for energy storage, novel materials, and electrochemical sensing.

Advances in Portable Heavy Metal Ion Sensors.

Heavy metal ions, one of the major pollutants in the environment, exhibit non-degradable and bio-chain accumulation characteristics, seriously damage the environment, and threaten human health. Traditional heavy metal ion detection methods often require complex and expensive instruments, professional operation, tedious sample preparation, high requirements for laboratory conditions, and operator professionalism, and they cannot be widely used in the field for real-time and rapid detection. Therefore, developing portable, highly sensitive, selective, and economical sensors is necessary for the detection of toxic metal ions in the field.

FAIR principles for AI models with a practical application for accelerated high energy diffraction microscopy.

A concise and measurable set of FAIR (Findable, Accessible, Interoperable and Reusable) principles for scientific data is transforming the state-of-practice for data management and stewardship, supporting and enabling discovery and innovation. Learning from this initiative, and acknowledging the impact of artificial intelligence (AI) in the practice of science and engineering, we introduce a set of practical, concise, and measurable FAIR principles for AI models. We showcase how to create and share FAIR data and AI models within a unified computational framework combining the following elements: the Advanced Photon Source at Argonne National Laboratory, the Materials Data Facility, the Data and Learning Hub for Science, and funcX, and the Argonne Leadership Computing Facility (ALCF), in particular the ThetaGPU supercomputer and the SambaNova DataScale system at the ALCF AI Testbed.

Linking scientific instruments and computation: Patterns, technologies, and experiences.

Powerful detectors at modern experimental facilities routinely collect data at multiple GB/s. Online analysis methods are needed to enable the collection of only interesting subsets of such massive data streams, such as by explicitly discarding some data elements or by directing instruments to relevant areas of experimental space. Thus, methods are required for configuring and running distributed computing pipelines-what we call flows-that link instruments, computers (e.

DPP-Cu Complexes Gated Mesoporous Silica Nanoparticles For pH and Redox Dual Stimuli-Responsive Drug Delivery.

Objective: A simple pH and redox dual stimuli-responsive diketopyrrolopyrrole (DPP)-Cu complexes gated mesoporous silica nanoparticles (MSN) were prepared for precise drug delivery and controlled drug release.

Method: MSN was prepared by sol-gel method and then laminated. Carboxylic acid (CA)-Pyrrolo[3,4-c] pyrrole-1,4-dione, 2,5-dihydro-3,6-di-2-pyridinyl (PyDPP) was grafted onto the surface of amino-functionalized MSN (MSN-NH) through a simple amide reaction and then complexed with Cu to form gated molecules after doxorubicin (DOX) loading.

Multiple amplification-based fluorometric aptasensor for highly sensitive detection of Staphylococcus aureus.

Rapid and accurate detection and identification of Staphylococcus aureus (S. aureus) are of great significance for food safety, environmental monitoring, early clinical diagnosis, and prevention of the spread of drug-resistant bacteria. Herein, we design a fluorometric aptasensor for ultra-sensitive, specific, and rapid detection of S.

Recent Advances in Aptasensors For Rapid and Sensitive Detection of .

The infection of and the spread of drug-resistant bacteria pose a serious threat to global public health. Therefore, timely, rapid and accurate detection of is of great significance for food safety, environmental monitoring, clinical diagnosis and treatment, and prevention of drug-resistant bacteria dissemination. Traditional detection methods such as culture identification, ELISA, PCR, MALDI-TOF-MS and sequencing, etc.

: fast X-ray Bragg peak analysis using deep learning.

X-ray diffraction based microscopy techniques such as high-energy diffraction microscopy (HEDM) rely on knowledge of the position of diffraction peaks with high precision. These positions are typically computed by fitting the observed intensities in detector data to a theoretical peak shape such as pseudo-Voigt. As experiments become more complex and detector technologies evolve, the computational cost of such peak-shape fitting becomes the biggest hurdle to the rapid analysis required for real-time feedback in experiments.

Application strategies of peptide nucleic acids toward electrochemical nucleic acid sensors.

Peptide nucleic acids (PNAs) have attracted tremendous interest in the fabrication of highly sensitive electrochemical nucleic acid biosensors due to their higher stability and increased sensitivity than common DNA probes. The neutral pseudopeptide backbone of PNAs not only makes the PNA/DNA duplexes more stable but also provides many opportunities to construct ultrasensitive nucleic acid sensors. This review presents the details of various protocols for the construction of PNA-based electrochemical nucleic acid sensors.

Identification of a tumor microenvironment-associated prognostic gene signature in bladder cancer by integrated bioinformatic analysis.

Bladder cancer is a common malignancy in the urinary system. Stromal and immune cells in tumor microenvironments, including those in the bladder cancer microenvironment, can serve as prognostic markers. However, the complex processes of bladder cancer necessitate large-scale evaluation to better understand the underlying mechanisms and identify biomarkers for diagnosis and treatment.

Water-Soluble Elastomeric Carboxymethyl Chitosan as an Efficient Binder for Si Anodes of Lithium Ion Batteries.

The binder acts a pivotal part in determining the mechanical and electrochemical performances of lithium-ion battery electrodes. Herein, a series of water-soluble Si anode binders based on carboxymethyl chitosan (C-Cs) and styrene-butadiene rubber (SBR) is developed. Water-soluble C-Cs and aqueous emulsion SBR solution are mixed to form C-Cs/SBR binders.

Estimation of Winter Wheat Yield in Arid and Semiarid Regions Based on Assimilated Multi-Source Sentinel Data and the CERES-Wheat Model.

The farmland area in arid and semiarid regions accounts for about 40% of the total area of farmland in the world, and it continues to increase. It is critical for global food security to predict the crop yield in arid and semiarid regions. To improve the prediction of crop yields in arid and semiarid regions, we explored data assimilation-crop modeling strategies for estimating the yield of winter wheat under different water stress conditions across different growing areas.

Identification of Four Immune Subtypes in Bladder Cancer Based on Immune Gene Sets.

Molecular classification of bladder cancer is becoming increasingly important for its clinical management. And, the current classifications are primarily based on gene expression profiles. We identified four immunotypes of bladder cancer (referred to as C1-C4) based on gene expression profiles performed by immune-related gene sets in three independent data sets, and proved that this classification is effective and reproducible.

Development and validation of a novel stem cell subtype for bladder cancer based on stem genomic profiling.

Background: Bladder cancer (BLCA) is the fifth most common type of cancer worldwide, with high recurrence and progression rates. Although considerable progress has been made in the treatment of BLCA through accurate typing of molecular characteristics, little is known regarding the various genetic and epigenetic changes that have evolved in stem and progenitor cells. To address this issue, we have developed a novel stem cell typing method.

Automatic In Situ Synthesis System for Polypeptide Biochip Based on Microfluidic Mixer.

Biochips have become a sophisticated analytical device in the fields of biochemical sensing and genetic analysis. However, the cumbersome preparation process and the high production cost limit the versatility of its application. Herein, we have developed an automated synthesis system for in situ preparation of biochip with peptide backbone based on the microfluidic mixer and micro reaction chamber.

Identification of a prognostic signature of nine metabolism-related genes for hepatocellular carcinoma.

Background: Hepatocellular carcinoma (HCC) is the fifth most common cancer. Since changes in liver metabolism contribute to liver disease development, it is necessary to build a metabolism-related prognostic model for HCC.

Methods: We constructed a metabolism-related-gene (MRG) signature comprising nine genes, which segregated HCC patients into high- and low-risk groups.