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Discrimination slope is the slope of a linear regression of predicted probabilities on the binary outcome variable, which is much influenced by the calibration [4]. Discrimination and calibration are the two most important aspects of a prediction model: the former focuses on the ranking of individuals from (relatively) low to high risk, whereas the latter focuses on absolute probability of having an event. [...]they request different levels of information [3]: linear predictor (LP) (prognostic index, risk score) or predicted probability. For logistic models, if intercept was included in LP calculation, predicted probability can be derived by using logistic transformation; however, for Cox models, baseline survival will be needed to calculate predicted survival probability (Fig. 1, information needed). Because discrimination only depends on the ranking rather than absolute probability, having LP is sufficient to calculate discrimination performance measure, for both logistic and Cox models.

Background Long non-coding RNAs (lncRNAs) possess significant regulatory functions in multiple biological and pathological processes, especially in cancer. Dysregulated lncRNAs in hepatocellular carcinoma (HCC) and their therapeutic applications remain unclear. Methods Differentially expressed lncRNA profile in HCC was constructed using TCGA data. LINC00958 expression level was examined in HCC cell lines and tissues. Univariate and multivariate analyses were performed to demonstrate the prognostic value of LINC00958. Loss-of-function and gain-of-function experiments were used to assess the effects of LINC00958 on cell proliferation, motility, and lipogenesis. Patient-derived xenograft model was established for in vivo experiments. RNA immunoprecipitation, dual luciferase reporter, biotin-labeled miRNA pull-down, fluorescence in situ hybridization, and RNA sequencing assays were performed to elucidate the underlying molecular mechanisms. We developed a PLGA-based nanoplatform encapsulating LINC00958 siRNA and evaluated its superiority for systemic administration. Results We identified a lipogenesis-related lncRNA, LINC00958, whose expression was upregulated in HCC cell lines and tissues. High LINC00958 level independently predicted poor overall survival. Functional assays showed that LINC00958 aggravated HCC malignant phenotypes in vitro and in vivo. Mechanistically, LINC00958 sponged miR-3619-5p to upregulate hepatoma-derived growth factor (HDGF) expression, thereby facilitating HCC lipogenesis and progression. METTL3-mediated N 6 -methyladenosine modification led to LINC00958 upregulation through stabilizing its RNA transcript. A PLGA-based nanoplatform loaded with si-LINC00958 was developed for HCC systemic administration. This novel drug delivery system was controlled release, tumor targeting, safe, and presented satisfactory antitumor efficacy. Conclusions Our results delineate the clinical significance of LINC00958 in HCC and the regulatory mechanisms involved in HCC lipogenesis and progression, providing a novel prognostic indicator and promising nanotherapeutic target.

Single-photon emitters (SPEs) play an important role in a number of quantum information tasks such as quantum key distributions. In these protocols, telecom wavelength photons are desired due to their low transmission loss in optical fibers. In this paper, we present a study of bright single-photon emitters in cubic silicon carbide (3C-SiC) emitting in the telecom range. We find that these emitters are photostable and bright at room temperature with a count rate of ~ MHz. Altogether with the fact that SiC is a growth and fabrication-friendly material, our result may be relevant for future applications in quantum communication technology. Room-temperature solid-state single photon emitters in the telecom range are suitable for quantum communication. Here, the authors observe defects in high-purity 3C-SiC epitaxy layers grown on a silicon substrate, with good characteristics in terms of brightness, emission’s polarization and photostability.

Background Telemedicine has experienced rapid growth in recent years, aiming to enhance medical efficiency and reduce the workload of healthcare professionals. During the COVID-19 pandemic in 2019, it became especially crucial, enabling remote screenings and access to healthcare services while maintaining social distancing. Online consultation platforms have emerged, but the demand has strained the availability of medical professionals, directly leading to research and development in automated medical consultation. Specifically, there is a need for efficient and accurate medical dialogue summarization algorithms to condense lengthy conversations into shorter versions focused on relevant medical facts. The success of large language models like generative pre-trained transformer (GPT)-3 has recently prompted a paradigm shift in natural language processing (NLP) research. In this paper, we will explore its impact on medical dialogue summarization. Methods We present the performance and evaluation results of two approaches on a medical dialogue dataset. The first approach is based on fine-tuned pre-trained language models, such as bert-based summarization (BERTSUM) and bidirectional auto-regressive Transformers (BART). The second approach utilizes a large language models (LLMs) GPT-3.5 with inter-context learning (ICL). Evaluation is conducted using automated metrics such as ROUGE and BERTScore. Results In comparison to the BART and ChatGPT models, the summaries generated by the BERTSUM model not only exhibit significantly lower ROUGE and BERTScore values but also fail to pass the testing for any of the metrics in manual evaluation. On the other hand, the BART model achieved the highest ROUGE and BERTScore values among all evaluated models, surpassing ChatGPT. Its ROUGE-1, ROUGE-2, ROUGE-L, and BERTScore values were 14.94%, 53.48%, 32.84%, and 6.73% higher respectively than ChatGPT’s best results. However, in the manual evaluation by medical experts, the summaries generated by the BART model exhibit satisfactory performance only in the “Readability” metric, with less than 30% passing the manual evaluation in other metrics. When compared to the BERTSUM and BART models, the ChatGPT model was evidently more favored by human medical experts. Conclusion On one hand, the GPT-3.5 model can manipulate the style and outcomes of medical dialogue summaries through various prompts. The generated content is not only better received than results from certain human experts but also more comprehensible, making it a promising avenue for automated medical dialogue summarization. On the other hand, automated evaluation mechanisms like ROUGE and BERTScore fall short in fully assessing the outputs of large language models like GPT-3.5. Therefore, it is necessary to research more appropriate evaluation criteria.

In this paper, a novel algorithm is presented for warhead recognition in the defense of ballistic missiles. The range profiles from the warheads of interest in typical illumination directions form a dataset. First, each range profile in the dataset is compared to the range profile of the target under observation, and the most similar range profile is found. Then, the observed target is considered as a warhead if the deviation of its range profile from the most similar range profile is less than or equal to a threshold. The threshold is chosen such that the detection rate is a constant. The simulation results verify the effectiveness of the proposed algorithm. Since the threshold is automatically calculated according to the detection rate, this algorithm has a larger applicability than the current methods based on range-profile matching.

Tumor‐associated macrophages (TAMs), one of the most common cell components in the tumor microenvironment, have been reported as key contributors to cancer‐related inflammation and enhanced metastatic progression of tumors. To explore the underlying mechanism of TAM‐induced tumor progression, TAMs were isolated from colorectal cancer patients, and the functional interaction with colorectal cancer cells was analyzed. Our study found that coculture of TAMs contributed to a glycolytic state in colorectal cancer, which promoted the stem‐like phenotypes and invasion of tumor cells. TAMs produced the cytokine transforming growth factor‐β to support hypoxia‐inducible factor 1α (HIF1α) expression, thereby upregulating Tribbles pseudokinase 3 (TRIB3) in tumor cells. Elevated expression of TRIB3 resulted in activation of the β‐catenin/Wnt signaling pathway, which eventually enhanced the stem‐like phenotypes and cell invasion in colorectal cancer. Our findings provided evidence that TAMs promoted colorectal cancer progression in a HIF1α/TRIB3‐dependent manner, and blockade of HIF1α signals efficiently improved the outcome of chemotherapy, describing an innovative approach for colorectal cancer treatment. Our findings provided evidence that tumor‐associated macrophages promoted colorectal progression in a HIF1α/TRIB3‐dependent manner, and blockade of HIF1α signals efficiently improved the outcome of chemotherapy, describing an innovative approach for colorectal cancer treatment.

Magnetic resonance is essential in revealing the structure and dynamics of biomolecules. However, measuring the magnetic resonance spectrum of single biomolecules has remained an elusive goal. We demonstrate the detection of the electron spin resonance signal from a single spin-labeled protein under ambient conditions. As a sensor, we use a single nitrogen vacancy center in bulk diamond in close proximity to the protein. We measure the orientation of the spin label at the protein and detect the impact of protein motion on the spin label dynamics. In addition, we coherently drive the spin at the protein, which is a prerequisite for studies involving polarization of nuclear spins of the protein or detailed structure analysis of the protein itself.

Electrocatalysts are extensively employed to suppress the shuttling effect in lithium-sulfur (Li-S) batteries. However, it remains challenging to probe the sulfur redox reactions and mechanism at the electrocatalyst/LiPS interface after the active sites are covered by the solid discharge products Li 2 S/Li 2 S 2 . Here, we demonstrate the intrinsic autocatalytic activity of the Li 2 S (100) plane towards lithium polysulfides on single-atom nickel (SANi) electrocatalysts. Guided by theoretical models and experimental data, it is concluded that LiPS dissociates into Li 2 S 2 and short-chain LiPS on the Li 2 S (100) plane. Subsequently, Li 2 S 2 undergoes further lithiation to Li 2 S on the Li 2 S (100) surface, generating a new Li 2 S (100) layer, thus enabling the autocatalytic formation of a new Li 2 S (100) surface. Benefiting from the autocatalytic growth of Li 2 S, the concentration of LiPS in the electrolyte remains at a lower level, enabling Li-S batteries under high loading and low electrolyte conditions to exhibit superior electrochemical performance. This study reveals the autocatalytic growth of Li 2 S crystals at the solid-liquid interface in lithium-sulfur batteries enabling good electrochemical performance under high loading and low electrolyte conditions.

The intrinsic antiferromagnetic topological insulator MnBi 2 Te 4 provides an ideal platform for exploring exotic topological quantum phenomena. Recently, the Chern insulator and axion insulator phases have been realized in few-layer MnBi 2 Te 4 devices at low magnetic field regime. However, the fate of MnBi 2 Te 4 in high magnetic field has never been explored in experiment. In this work, we report transport studies of exfoliated MnBi 2 Te 4 flakes in pulsed magnetic fields up to 61.5 T. In the high-field limit, the Chern insulator phase with Chern number C  = −1 evolves into a robust zero Hall resistance plateau state. Nonlocal transport measurements and theoretical calculations demonstrate that the charge transport in the zero Hall plateau state is conducted by two counter-propagating edge states that arise from the combined effects of Landau levels and large Zeeman effect in strong magnetic fields. Our result demonstrates the intricate interplay among intrinsic magnetic order, external magnetic field, and nontrivial band topology in MnBi 2 Te 4 . The antiferromagnetic topological insulator MnBi 2 Te 4 exhibits Chern and axion insulator phases at low magnetic field; however, its behaviour in high magnetic field has remained unexplored. Here, using transport measurements at high magnetic field, the authors report a zero Hall plateau composed of two counter-propagating edge channels.

Plant derived extracellular vesicles (EVs) are nano-sized membranous vesicles released by plant cells, which contain lipids, proteins, nucleic acids and specific pharmacologically active substances. They are safe, widely available and expediently extractive. They have gratifyingly biological activity against inflammation, cancer, bacteria and oxidative aging, especially for the prevention or treatment of colitis, cancer, alcoholic liver, and COVID-19. In addition, as natural drug carriers, plant derived EVs have the potential to target the delivery of small molecule drugs and nucleic acid through oral, transdermal, injection. With the above advantages, plant derived EVs are expected to have excellent strong competitiveness in clinical application or preventive health care products in the future. We comprehensively reviewed the latest separation methods and physical characterization techniques of plant derived EVs, summarized the application of them in disease prevention or treatment and as a new drug carrier, and analyzed the clinical application prospect of plant derived EVs as a new drug carrier in the future. Finally, the problems hindering the development of plant derived EVs at present and consideration of the standardized application of them are discussed.