A bibliometric study on the impact of gut microbiota on the efficacy of immune checkpoint inhibitors in cancer patients: analysis of the top 100 cited articles

BackgroundImmune checkpoint inhibitors (ICIs) have transformed oncological treatment by modulating immune responses against tumors. However, their efficacy is subject to inter-patient variability and is associated with immune-related adverse events (irAEs). The human gut microbiota, a complex microbial ecosystem, is increasingly implicated in modulating responses to ICIs. This bibliometric analysis examines the 100 most-cited articles to elucidate trends and advancements in research concerning the gut microbiota’s impact on ICI efficacy.MethodsA systematic literature retrieval was conducted within the Web of Science Core Collection (WoSCC), focusing on the 100 most-cited articles. VOSviewer and CiteSpace were utilized for bibliometric analysis, examining collaborative patterns and keyword co-occurrences. The relationship between citing and cited entities was analyzed, and burst ranking identified research hotspots based on citation frequency.ResultsThe 100 most-cited publications encompassed a range of disciplines, with a predominance of oncological research. The United States and China were leading in publication volume, with France and Canada also contributing significantly. French institutions, particularly INSERM and Université Paris Cite, were prolific. Routy, Bertrand and Zitvogel, Laurence were prominent among high-impact authors. Dominant keywords included “gut microbiota,” “immunotherapy,” “efficacy,” and “cancer.” The article by Routy et al. (2018) was the most frequently cited.ConclusionsThis study highlights the significant role of the gut microbiota in ICI development and efficacy, emphasizing the necessity for international and interdisciplinary collaboration. The research is progressively focusing on managing immunotherapy side effects and optimizing treatment strategies. Challenges, including individual variability in gut microbiota composition, persist. Further research is imperative to exploit the potential of the gut microbiota in cancer therapy, advocating for personalized approaches and a more profound comprehension of the underlying mechanisms

The Tianlin Mission: a 6m UV/Opt/IR space telescope to explore the habitable worlds and the universe

[Abridged] It is expected that the ongoing and future space-borne planet survey missions including TESS, PLATO, and Earth 2.0 will detect thousands of small to medium-sized planets via the transit technique, including over a hundred habitable terrestrial rocky planets. To conduct a detailed study of these terrestrial planets, particularly the cool ones with wide orbits, the exoplanet community has proposed various follow-up missions. The currently proposed ESA mission ARIEL is capable of characterization of planets down to warm super-Earths mainly using transmission spectroscopy. The NASA 6m UV/Opt/NIR mission proposed in the Astro2020 Decadal Survey may further tackle down to habitable rocky planets, and is expected to launch around 2045. In the meanwhile, China is funding a concept study of a 6-m class space telescope named Tianlin (A UV/Opt/NIR Large Aperture Space Telescope) that aims to start its operation within the next 10-15 years and last for 5+ years. Tianlin will be primarily aimed to the discovery and characterization of rocky planets in the habitable zones (HZ) around nearby stars and to search for potential biosignatures mainly using the direct imaging method. Transmission and emission spectroscopy at moderate to high resolution will be carried out as well on a population of exoplanets to strengthen the understanding of the formation and evolution of exoplanets. It will also carry out in-depth studies of the cosmic web and early galaxies, and constrain the nature of the dark matter and dark energy. We describe briefly the primary scientific motivations and main technical considerations based on our preliminary simulation results. We find that a monolithic off-axis space telescope with a primary mirror diameter larger than 6m equipped with a high contrast chronograph can identify water in the atmosphere of a habitable-zone Earth-like planet around a Sun-like star.Comment: 15 pages, 5 figures, accepted for publication in RAA and is available onlin

Ischemic colitis presenting as a colonic mass: a case report and diagnostic challenges

Ischemic colitis (IC) is a multifaceted condition that often manifests with nonspecific symptoms such as abdominal pain and bloody diarrhea, particularly in older adults with vascular risk factors. Diagnosis is supported by elevated levels of white blood cells, lactate, and C-reactive protein (CRP). Computed tomography (CT) imaging typically reveals wall thickening and fat stranding in watershed areas. Colonoscopy may demonstrate mucosal erythema, ulceration, or necrosis. IC can be differentiated from inflammatory bowel disease (IBD), diverticulitis, and colorectal cancer based on symptom patterns and imaging findings. The absence of specific biomarkers can complicate diagnosis, potentially causing delays. Illustrating these challenges is the case of a 53-year-old male patient who arrived at the hospital exhibiting abdominal pain and diarrhea. Enhanced CT scans and colonoscopy identified a mass in the ileocecal region of the colon, and subsequent tissue biopsy revealed ischemic lesions in the submucosa. Initially diagnosed with IC, the patient’s symptoms gradually improved with conservative treatment, which included antibiotics, fluid resuscitation, and bowel rest. Follow-up endoscopy showed significant lesion improvement, and no recurrence was detected during subsequent follow-ups. This case illustrates the healing process of IC as manifested by colon mass under endoscopy. Also, it highlights the critical importance of timely diagnosis and personalized treatment strategies in atypical presentations to improve patient outcomes

Evaluating the effect of SARS-CoV-2 spike mutations with a linear doubly robust learner

Driven by various mutations on the viral Spike protein, diverse variants of SARS-CoV-2 have emerged and prevailed repeatedly, significantly prolonging the pandemic. This phenomenon necessitates the identification of key Spike mutations for fitness enhancement. To address the need, this manuscript formulates a well-defined framework of causal inference methods for evaluating and identifying key Spike mutations to the viral fitness of SARS-CoV-2. In the context of large-scale genomes of SARS-CoV-2, it estimates the statistical contribution of mutations to viral fitness across lineages and therefore identifies important mutations. Further, identified key mutations are validated by computational methods to possess functional effects, including Spike stability, receptor-binding affinity, and potential for immune escape. Based on the effect score of each mutation, individual key fitness-enhancing mutations such as D614G and T478K are identified and studied. From individual mutations to protein domains, this paper recognizes key protein regions on the Spike protein, including the receptor-binding domain and the N-terminal domain. This research even makes further efforts to investigate viral fitness via mutational effect scores, allowing us to compute the fitness score of different SARS-CoV-2 strains and predict their transmission capacity based solely on their viral sequence. This prediction of viral fitness has been validated using BA.2.12.1, which is not used for regression training but well fits the prediction. To the best of our knowledge, this is the first research to apply causal inference models to mutational analysis on large-scale genomes of SARS-CoV-2. Our findings produce innovative and systematic insights into SARS-CoV-2 and promotes functional studies of its key mutations, serving as reliable guidance about mutations of interest

China's new Towns in Controversy: A Literature Review

In the past forty years, more than 3,800 new towns emerged and accommodated over 150 million urban inhabitants in China, which drew much attention since they were reported as “ghost cities” by media in the late 2000s. This literature review examines existing research and synthesizes current discussions through a meta-analysis. It concludes that existing literature, led by environmental scientists and designers, exhibits two polarized debates around the new towns’ uniqueness and the future of ghost cities. Gaps exist in national-scale surveys, criticism of planning methodology, and theories that can explain the current disputes. </jats:p

The application of simultaneous paver liquid cement sprinkling system in the road construction of Yun-Mao Highway

The simultaneous paver liquid cement sprinkling system is the combination of a conventional paver and a simultaneous liquid cement sprinkler. During operation, the cement sprinkler can be installed onto a paver with the use of connectors. When paving the stabilization aggregate mixture, this system sprinkles liquid cement on the working surface. This device can effectively solve the common quality issues such as the formation of cement isolation layer and road pollution, as a result of premature hardening of the pre-sprinkled liquid cement during road construction in high-temperature environments.</jats:p

The application of simultaneous paver liquid cement sprinkling system in the road construction of Yun-Mao Highway

The simultaneous paver liquid cement sprinkling system is the combination of a conventional paver and a simultaneous liquid cement sprinkler. During operation, the cement sprinkler can be installed onto a paver with the use of connectors. When paving the stabilization aggregate mixture, this system sprinkles liquid cement on the working surface. This device can effectively solve the common quality issues such as the formation of cement isolation layer and road pollution, as a result of premature hardening of the pre-sprinkled liquid cement during road construction in high-temperature environments

Swin Transformer-Based Edge Guidance Network for RGB-D Salient Object Detection

Salient object detection (SOD), which is used to identify the most distinctive object in a given scene, plays an important role in computer vision tasks. Most existing RGB-D SOD methods employ a CNN-based network as the backbone to extract features from RGB and depth images; however, the inherent locality of a CNN-based network limits the performance of CNN-based methods. To tackle this issue, we propose a novel Swin Transformer-based edge guidance network (SwinEGNet) for RGB-D SOD in which the Swin Transformer is employed as a powerful feature extractor to capture the global context. An edge-guided cross-modal interaction module is proposed to effectively enhance and fuse features. In particular, we employed the Swin Transformer as the backbone to extract features from RGB images and depth maps. Then, we introduced the edge extraction module (EEM) to extract edge features and the depth enhancement module (DEM) to enhance depth features. Additionally, a cross-modal interaction module (CIM) was used to integrate cross-modal features from global and local contexts. Finally, we employed a cascaded decoder to refine the prediction map in a coarse-to-fine manner. Extensive experiments demonstrated that our SwinEGNet achieved the best performance on the LFSD, NLPR, DES, and NJU2K datasets and achieved comparable performance on the STEREO dataset compared to 14 state-of-the-art methods. Our model achieved better performance compared to SwinNet, with 88.4% parameters and 77.2% FLOPs. Our code will be publicly available

Global Guided Cross-Modal Cross-Scale Network for RGB-D Salient Object Detection

RGB-D saliency detection aims to accurately localize salient regions using the complementary information of a depth map. Global contexts carried by the deep layer are key to salient objection detection, but they are diluted when transferred to shallower layers. Besides, depth maps may contain misleading information due to the depth sensors. To tackle these issues, in this paper, we propose a new cross-modal cross-scale network for RGB-D salient object detection, where the global context information provides global guidance to boost performance in complex scenarios. First, we introduce a global guided cross-modal and cross-scale module named G2CMCSM to realize global guided cross-modal cross-scale fusion. Then, we employ feature refinement modules for progressive refinement in a coarse-to-fine manner. In addition, we adopt a hybrid loss function to supervise the training of G2CMCSNet over different scales. With all these modules working together, G2CMCSNet effectively enhances both salient object details and salient object localization. Extensive experiments on challenging benchmark datasets demonstrate that our G2CMCSNet outperforms existing state-of-the-art methods