The Recent Development of Organofluorine Chemistry in China: Asymmetric Construction of Stereogenic Trifluoromethyl-substituted Carbon Centers

The stereospecific incorporation of the trifluoromethyl group into an organic compound has attracted considerable attention and significant progress has been achieved in the past decade. Scholars from China have also contributed greatly to this field, which is the subject of the current review

Graph Analysis in Decentralized Online Social Networks with Fine-Grained Privacy Protection

Graph analysts cannot directly obtain the global structure in decentralized social networks, and analyzing such a network requires collecting local views of the social graph from individual users. Since the edges between users may reveal sensitive social interactions in the local view, applying differential privacy in the data collection process is often desirable, which provides strong and rigorous privacy guarantees. In practical decentralized social graphs, different edges have different privacy requirements due to the distinct sensitivity levels. However, the existing differentially private analysis of social graphs provide the same protection for all edges. To address this issue, this work proposes a fine-grained privacy notion as well as novel algorithms for private graph analysis. We first design a fine-grained relationship differential privacy (FGR-DP) notion for social graph analysis, which enforces different protections for the edges with distinct privacy requirements. Then, we design algorithms for triangle counting and k-stars counting, respectively, which can accurately estimate subgraph counts given fine-grained protection for social edges. We also analyze upper bounds on the estimation error, including k-stars and triangle counts, and show their superior performance compared with the state-of-the-arts. Finally, we perform extensive experiments on two real social graph datasets and demonstrate that the proposed mechanisms satisfying FGR-DP have better utility than the state-of-the-art mechanisms due to the finer-grained protection

Major depressive disorder plays a vital role in the pathway from gastroesophageal reflux disease to chronic obstructive pulmonary disease: a Mendelian randomization study

Background: Observational studies have shown a bidirectional association between chronic obstructive pulmonary disease (COPD) and gastroesophageal reflux disease (GERD), but it is not clear whether this association is causal. In our previous study, we found that depression was a hot topic of research in the association between COPD and GERD. Is major depressive disorder (MDD) a mediator of the association between COPD and GERD? Here, we evaluated the causal association between COPD, MDD, and GERD using Mendelian randomization (MR) study.Methods: Based on the FinnGen, United Kingdom Biobank, and Psychiatric Genomics Consortium (PGC) databases, we obtained genome-wide association study (GWAS) summary statistics for the three phenotypes from 315,123 European participants (22,867 GERD cases and 292,256 controls), 462,933 European participants (1,605 COPD cases and 461,328 controls), and 173,005 European participants (59,851 MDD cases and 113,154 controls), respectively. To obtain more instrumental variables to reduce bias, we extracted relevant single-nucleotide polymorphisms (SNPs) for the three phenotypes from published meta-analysis studies. Bidirectional MR and expression quantitative trait loci (eQTL)-MR were performed using the inverse variance weighting method to assess the causal association between GERD, MDD, and COPD.Results: There was no evidence of a causal effect between GERD and COPD in the bidirectional MR analysis [forward MR for GERD on COPD: odds ratios (OR) = 1.001, p = 0.270; reverse MR for COPD on GERD: OR = 1.021, p = 0.303]. The causal effect between GERD and MDD appeared to be bidirectional (forward MR for GERD on MDD: OR = 1.309, p = 0.006; reverse MR for MDD on GERD: OR = 1.530, p < 0.001), while the causal effect between MDD and COPD was unidirectional (forward MR for MDD on COPD: OR = 1.004, p < 0.001; reverse MR for COPD on MDD: OR = 1.002, p = 0.925). MDD mediated the effect of GERD on COPD in a unidirectional manner (OR = 1.001). The results of the eQTL-MR were consistent with those of the bidirectional MR.Conclusion: MDD appears to play a vital role in the effect of GERD on COPD. However, we have no evidence of a direct causal association between GERD and COPD. There is a bidirectional causal association between MDD and GERD, which may accelerate the progression from GERD to COPD

Paragraph-to-Image Generation with Information-Enriched Diffusion Model

Text-to-image (T2I) models have recently experienced rapid development, achieving astonishing performance in terms of fidelity and textual alignment capabilities. However, given a long paragraph (up to 512 words), these generation models still struggle to achieve strong alignment and are unable to generate images depicting complex scenes. In this paper, we introduce an information-enriched diffusion model for paragraph-to-image generation task, termed ParaDiffusion, which delves into the transference of the extensive semantic comprehension capabilities of large language models to the task of image generation. At its core is using a large language model (e.g., Llama V2) to encode long-form text, followed by fine-tuning with LORA to alignthe text-image feature spaces in the generation task. To facilitate the training of long-text semantic alignment, we also curated a high-quality paragraph-image pair dataset, namely ParaImage. This dataset contains a small amount of high-quality, meticulously annotated data, and a large-scale synthetic dataset with long text descriptions being generated using a vision-language model. Experiments demonstrate that ParaDiffusion outperforms state-of-the-art models (SD XL, DeepFloyd IF) on ViLG-300 and ParaPrompts, achieving up to 15% and 45% human voting rate improvements for visual appeal and text faithfulness, respectively. The code and dataset will be released to foster community research on long-text alignment.Comment: The project website is at: https://weijiawu.github.io/ParaDiffusionPage/. Code: https://github.com/weijiawu/ParaDiffusio

Updating the therapeutic role of ginsenosides in breast cancer: a bibliometrics study to an in-depth review

Breast cancer is currently the most common malignancy and has a high mortality rate. Ginsenosides, the primary bioactive constituents of ginseng, have been shown to be highly effective against breast cancer both in vitro and in vivo. This study aims to comprehensively understand the mechanisms underlying the antineoplastic effects of ginsenosides on breast cancer. Through meticulous bibliometric analysis and an exhaustive review of pertinent research, we explore and summarize the mechanism of action of ginsenosides in treating breast cancer, including inducing apoptosis, autophagy, inhibiting epithelial-mesenchymal transition and metastasis, and regulating miRNA and lncRNA. This scholarly endeavor not only provides novel prospects for the application of ginsenosides in the treatment of breast cancer but also suggests future research directions for researchers

Detrimental Effects and Prevention of Acidic Electrolytes on Oxygen Reduction Reaction Catalytic Performance of Heteroatom-Doped Graphene Catalysts

Article describes study in which the density functional theory (DFT) methods were applied to understand the inferior performance of doped graphene in acid

Case Report: Sequential Chemotherapy and Immunotherapy Produce Sustained Response in Osteosarcoma With High Tumor Mutational Burden

BackgroundImmunotherapy has provided an effective method for the treatment of many cancers. However, its efficacy in osteosarcoma is not satisfactory so far.Case PresentationHere, we presented a case of osteosarcoma treated with sequential chemotherapy and immunotherapy and showed promising therapeutic potential. The 29-year-old female patient presented 9th rib osteosarcoma with suspected right lung lower lobe metastasis. Surgery was performed to remove the primary lesion, and a series of chemotherapies were given afterward in consideration of the response and tolerance. The right lung lower lobe metastasis was under control first but progressed (PD) 9 months after the initiation of therapy. The lesion was surgically removed and subsequent chemotherapy was implemented. The patient had good tolerance with chemotherapy and maintained well for approximately 11 months before the discovery of 11th rib and right lung upper lobe metastases. Surgery was then performed on both lesions and achieved complete response. Post-surgical brief chemotherapy and subsequent long-term immunotherapy (pembrolizumab) maintained continuous remission for 33 months. The patient survived for 60 months with well-controlled disease from the time of confirmed diagnosis. Genetic alterations of all primary and metastatic lesions were investigated by whole-exome sequencing (WES). Substantial similarity in mutational landscape between the primary lesion and 11th rib metastasis and between the two lung metastases were revealed, while substantial heterogeneity was found between the rib lesions and lung metastases. The tumor mutational burden (TMB) for the 9th rib primary lesion, the metastatic 11th rib lesion, and the metastatic right upper and lower lobe nodule tissues was 8.02, 2.38, 4.61, and 0.14 mutations/Mb, respectively. The primary lesion exhibited the most diverse copy number variation (CNV) changes among all lesions. Furthermore, pathway enrichment analysis also suggested significant heterogeneity among the lesions.ConclusionsSurgery with sequential chemotherapy and maintenance immunotherapy was shown to have good response for the first time on osteosarcoma patient who had high TMB tumor lesions and good tolerance for chemotherapy and immunotherapy

Modelling underground coal gasification: What to start with

Underground coal gasification (UCG) is widely regarded as a clean coal technology that holds enormous potential to decarbonize the world's coal industry. It converts coal underground into combustible syngas through a set of complex physiochemical events. Experimental and numerical efforts over the past century have contributed to the development of UCG around the world; however, tapping the world's deep-situated coal resources with UCG requires substantial contributions from numerous high-quality researchers. To facilitate effective engagement, this paper will provide a background on where to start if one wishes to undertake UCG modelling. First, a brief description of the fundamental phenomena involved in UCG is given. Then, a succinct introduction of the widely used modelling software is rendered, followed by a description of UCG studies to provide insight how to tune the various software packages for modelling UCG and where their strengths lie. This paper shall serve as guidance to new UCG modellers