Explore the vast range of titles available.

As “the island at the center of the world,” Manhattan has inspired countless writers and has served as a spatial archetype in science fiction’s world-building. From the interdisciplinary perspective of literature and economics, this article discusses the crisis imagination of the “bubble metropolis” in five contemporary Manhattan-related science fiction novels including Cities in Flight (1970), The Blister (1975), Terminal World (2010), Zone One (2011), and New York 2140 (2017). The spatial variety of Manhattan Island in these science fiction novels is closely combined with its economic condition. The characters, plots, and spatial imagery of these novels gather to reflect the different stages of the operation of a bubble economy, illustrating a historical cycle of capitalism that can never be escaped. Manhattan Island has long been the symbol of the world’s rush for wealth. The fear of economic recession, environmental degradation, and class conflict have formed the special geographical features of the island in the future. The crisis imagination of the “bubble metropolis” also seeks to stimulate critical thinking on economic ethics, urban design, and high technology, calling for social justice and public welfare.

Primary large B-cell lymphoma of immune-privileged sites (IP-LBCL) encompasses a spectrum of relatively rare aggressive B-cell lymphomas, such as primary central nervous system lymphoma (PCNSL), primary testicular large B-cell lymphoma (PTL), and primary vitreoretinal large B-cell lymphoma (PVRL). Macroscopically, the development of IPI-LBCL may be associated with the dysfunction of meningeal lymphatic vessels (mLVs) and the perivascular channel system formed by astrocytes. Microscopically, mutation in MYD88 and CD79B genes plays a pivotal role in the pathogenesis of IP-LBCL. Pathological examination remains the cornerstone for establishing a diagnosis of IP-LBCL. Moreover, traditional imaging is now supplemented by a suite of advanced diagnostic methods, including cytological, genetic, immunological, multiple omics, and molecular biological, which collectively enhance the diagnostic accuracy of IP-LBCL. Despite these advancements, the high recurrence rates and attendant high mortality rates pose significant challenges to achieving long-term survival in IP-LBCL patients. However, the emergence of novel therapeutic agents, such as Bruton’s tyrosine kinase inhibitors (BTKi), immune checkpoint inhibitors, immunomodulators, and anti-CD19 chimeric antigen receptor T (CAR-T) cell therapy, has offered promising new avenues for the treatment of IP-LBCL, demonstrating remarkable anti-tumor efficacy in recent years. This review delves into the epidemiology, pathogenesis mechanisms, diagnosis approaches, therapeutic strategies, and prognosis factors associated with IP-LBCL. It meticulously examines the parallels and divergences between the National Comprehensive Cancer Network (NCCN) and European Society for Medical Oncology (ESMO) guidelines, enhancing the professional comprehension of the complexities inherent to IP-LBCL.

Background Among hypertensive cohorts across different nations, the relationship between the triglyceride-glucose index (TyG) and its conjunction with obesity metrics in relation to cardiovascular disease (CVD) incidence and mortality remains to be elucidated. Methods This study enrolled 9,283, 164,357, and 5,334 hypertensives from the National Health and Nutrition Examination Survey (NHANES), UK Biobank (UKBB), and Shanghai Pudong cohort. The related outcomes for CVD were defined by multivariate Cox proportional hazards models, Generalized Additive Models and Mendelian randomization analysis. Mediation analysis explored the mediating role of inflammatory markers in the above relationships. Results Five measures of insulin resistance were linked to CVD and related death in a U-shaped pattern, with the highest group having different risk increases. Higher glucose triglyceride-waist height ratio (TyG-WHTR) was linked to higher all-cause mortality (UKBB: HR 1.21, 95%CI 1.16–1.26, NHANES: HR 1.17, 95%CI 1.00–1.36), CVD mortality (UKBB: HR 1.36, 95%CI 1.23–1.49, NHANES: HR 1.32, 95%CI 1.00–1.72) risks. In the China Pudong cohort, higher triglyceride/high-density lipoprotein-cholesterol (TG/HDL_C) ratio was associated with higher risks of CVD and stroke (HR 1.31, 95%CI 1.00–1.73 and 1.67, 1.06–2.63). Inflammation markers like systemic inflammatory response index (SIRI) and C-reactive protein (CRP) partially explained these links, with CRP having a stronger effect. Genetically predicted TyG was also linked to stroke (OR 1.26, 95%CI 1.10–1.45) risk. Conclusions An elevated TyG index and its related indices are significantly correlated with an increased risk of CVD and related mortality across three national cohorts. These indices are anticipated to serve as valid predictors of incident CVD and mortality in individuals with hypertension. Graphical abstract

Intrahepatic cholangiocarcinoma (ICC) typically exhibits poor responsiveness to immune checkpoint inhibitors (ICIs) due to its microsatellite-stable (MSS) status and low tumor mutational burden (TMB). Conventional biomarkers like PD-L1 expression show limited predictive value, creating an urgent need for novel therapeutic targets in this aggressive malignancy. We describe a stage IV ICC patient with PD-L1 positivity and a somatic KMT2D mutation (p.R5303C) who attained sustained complete remission after pembrolizumab treatment, despite developing severe multi-organ immune-related adverse events (irAEs) including hepatitis, pneumonitis, and thrombocytopenia. Mechanistic analysis revealed that KMT2D deficiency potentially remodeled the tumor immune microenvironment through epigenetic reprogramming, characterized by enhanced CD8+ T-cell infiltration. Our findings advocate for combinatorial biomarker strategies incorporating epigenetic markers (KMT2D status) with PD-L1 expression to optimize ICI patient selection, while highlighting the need for vigilant toxicity monitoring in this subset.

Coronavirus disease (COVID-19) has affected more than 200 countries and territories worldwide. This disease poses an extraordinary challenge for public health systems because screening and surveillance capacity is often severely limited, especially during the beginning of the outbreak; this can fuel the outbreak, as many patients can unknowingly infect other people. The aim of this study was to collect and analyze posts related to COVID-19 on Weibo, a popular Twitter-like social media site in China. To our knowledge, this infoveillance study employs the largest, most comprehensive, and most fine-grained social media data to date to predict COVID-19 case counts in mainland China. We built a Weibo user pool of 250 million people, approximately half the entire monthly active Weibo user population. Using a comprehensive list of 167 keywords, we retrieved and analyzed around 15 million COVID-19-related posts from our user pool from November 1, 2019 to March 31, 2020. We developed a machine learning classifier to identify \"sick posts,\" in which users report their own or other people's symptoms and diagnoses related to COVID-19. Using officially reported case counts as the outcome, we then estimated the Granger causality of sick posts and other COVID-19 posts on daily case counts. For a subset of geotagged posts (3.10% of all retrieved posts), we also ran separate predictive models for Hubei province, the epicenter of the initial outbreak, and the rest of mainland China. We found that reports of symptoms and diagnosis of COVID-19 significantly predicted daily case counts up to 14 days ahead of official statistics, whereas other COVID-19 posts did not have similar predictive power. For the subset of geotagged posts, we found that the predictive pattern held true for both Hubei province and the rest of mainland China regardless of the unequal distribution of health care resources and the outbreak timeline. Public social media data can be usefully harnessed to predict infection cases and inform timely responses. Researchers and disease control agencies should pay close attention to the social media infosphere regarding COVID-19. In addition to monitoring overall search and posting activities, leveraging machine learning approaches and theoretical understanding of information sharing behaviors is a promising approach to identify true disease signals and improve the effectiveness of infoveillance.

The characteristics of information flow, as represented by the Baidu index, reflect the pattern of tourism flows between different cities. This paper is based on the Baidu index and applies the seasonal concentration index and social network analysis (SNA) methods to study the spatial structure characteristics of tourism flows in China. The results reveal that: (1) both the search volume of the Baidu index in different cities and the online attention to different scenic areas exhibit obvious spatial heterogeneity and seasonal differences; (2) regions with strong tourism flow connections mainly occur in the areas between metropolises or among the inner cities of urban agglomerations, which are largely distributed on the southeast side of the Heihe–Tengchong Line; (3) the development of the whole tourism flow network in China is low, with an unbalanced development between tourism supply and demand, indicating that tourism resources are concentrated in a few cities and that most of the information interaction among cities occurs in core areas, while a weak interaction is observed in peripheral areas; (4) cities like Beijing and Wuhan attain obvious advantages in regard to their tourism resources, whereas other cities, including Beijing, Shanghai, Shenzhen and Guangzhou, exhibit a high demand for tourism. Moreover, tourism information flow networks are concentrated in several cities with an important role in the Chinese urban system, such as Beijing, Wuhan, and Chengdu, because they contain abundant tourism resources, well-developed transportation systems and advanced economic and societal development levels. (5) Cities such as Beijing, Lhasa, Wuhan, and Zhengzhou possess numerous advantages due to structural holes, and they thus occur at an advantageous position in the tourism flow network.

This study aimed to evaluate the methodological quality of existing meta-analyses (MA) and the quality of evidence for outcome indicators to provide an updated overview of the evidence concerning the therapeutic efficacy of the Mediterranean diet (MD) for various types of CVD. We conducted comprehensive searches of PubMed, Cochrane Library, and Embase databases. The quality of the MA was assessed using the A Measurement Tool to Assess Systematic Reviews 2 (AMSTAR 2) checklist, while the Grading of Recommendations Assessment, Development and Evaluation (GRADE) evidence evaluation system was employed to evaluate the quality of evidence for significant outcomes. The CVD remains a significant contributor to global mortality. Multiple MA have consistently demonstrated the efficacy of medical interventions in managing CVD. However, due to variations in the scope, quality and outcomes of these reviews, definitive conclusions are yet to be established. This study included five randomized trials and twelve non-randomized studies, with a combined participant population of 716 318. The AMSTAR 2 checklist revealed that 54·55 % of the studies demonstrated high quality, while 9·09 % exhibited low quality, and 36·36 % were deemed critically low quality. Additionally, there was moderate evidence supporting a positive correlation between MD and CHD/acute myocardial infarction, stroke, heart failure, cardiovascular events, coronary events and major adverse cardiovascular events. This study indicates that although recognizing the potential efficacy of MD in managing CVD, the quality of the methodology and the evidence for the outcome indicators remain unsatisfactory.

Background Breast cancer is the most prevalent cancer among women. In triple-negative breast cancer (TNBC) cells, a novel quinone derivative, coenzyme Q 0 (CoQ 0 ), promotes apoptosis and cell-cycle arrest. This study explored the anti-epithelial–mesenchymal transition (EMT) and antimetastatic attributes of CoQ 0 in TNBC (MDA-MB-231). Methods Invasion, as well as MTT assays were conducted. Lipofectamine RNAiMAX was used to transfect cells with β-catenin siRNA. Through Western blotting and RT-PCR, the major signaling pathways’ protein expressions were examined, and the biopsied tumor tissues underwent immunohistochemical and hematoxylin and eosin staining as well as Western blotting. Results CoQ 0 (0.5–2 μM) hindered tumor migration, invasion, and progression. Additionally, it caused MMP-2/− 9, uPA, uPAR, and VEGF downregulation. Furthermore, in highly metastatic MDA-MB-231 cells, TIMP-1/2 expression was subsequently upregulated and MMP-9 expression was downregulated. In addition, CoQ 0 inhibited metastasis and EMT in TGF-β/TNF-α-stimulated non-tumorigenic MCF-10A cells. Bioluminescence imaging of MDA-MB-231 luciferase–injected live mice demonstrated that CoQ 0 significantly inhibited metastasis of the breast cancer to the lungs and inhibited the development of tumors in MDA-MB-231 xenografted nude mice. Silencing of β-catenin with siRNA stimulated CoQ 0 -inhibited EMT. Western blotting as well as histological analysis established that CoQ0 reduced xenografted tumor development because apoptosis induction, cell-cycle inhibition, E-cadherin upregulation, β-catenin downregulation, and metastasis and EMT regulatory protein modulation were observed. Conclusions CoQ 0 inhibited the progression of metastasis as well as EMT (in vitro and in vivo). The described approach has potential in treating human breast cancer metastasis.

With the increased demand for safe and sustainable alternatives to growth promoting antibiotics in the livestock industry, oregano essential oils (OEO) and Lactobacillus reuteri (LR) have been examined as alternatives to antibiotics for growth promotion and to improve animal health and performance. However, the mechanism underlying the OEO and LR mediation of sheep growth remains unknown. In this study, 16S rRNA gene sequencing and untargeted metabolomics were used to determine the role of the gut microbiota in the growth improvements observed. The potential modulating roles of intestinal microbial metabolites of OEO and LR to intestinal health were systematically explored as well. It was observed that both OEO and LR had greater average daily gain (ADG) and lower F/G ratio. Furthermore, OEO also appeared to have produced a greater amylase enzyme activity and mucin gene expression in the jejunal mucosa. It was also observed that OEO reduced serum IL-2 and TNF-β as well as mRNA levels of NF-κB p65 , toll-like receptor-4 ( TLR-4 ), and IL-6 in the jejunal mucosa. Moreover, dietary OEO supplementation increased the abundances of Ruminococcus , Bifidobacterium and Enterococcus , while the relative abundances of Succiniclasticum , Marvinbryantia and Streptococcus were enriched in LR group. Spearman’s correlation analysis revealed that the abundances of Bifidobacterium , Ruminococcus and Enterococcus were positively correlated with the mRNA expression of mucins. Moreover, the relative abundance of Enterococcus was positively correlated with amylase activity. Metabolomics analysis indicated that OEO and LR increased the levels of indole acetaldehyde and indole-3-acetic acid through the tryptophan metabolism pathway. It was observed that LR also decreased the inflammatory metabolites including tryptamine and 5-hydroxyindole-3-acetic acid. Collectively, these results suggested that OEO exerted a beneficial effect on growth performance and the mucosal barrier, affected tryptophan metabolism and improved the intestinal microbiota of sheep.

Background: Alzheimer's disease (AD) is a neurodegenerative disease characterized by progressive memory deficits, cognitive decline, and spatial disorientation. Non-pharmacological interventions to treat AD have been reported in many meta-analyses (MAs), but robust conclusions have not been made because of variations in the scope, quality, and findings of these reviews. Objective: This work aimed to review existing MAs to provide an overview of existing evidence on the effects of five non-pharmacological interventions in AD patients on three outcomes: Mini-Mental State Examination (MMSE), activities of daily living (ADL), and Alzheimer's Disease Assessment Scale-cognitive section (ADAS-cog). Methods: The databases PubMed, Cochrane Library, Embase, and Web of Science were searched to collect MAs of non-pharmacological interventions for AD. Two reviewers independently conducted literature screening, data extraction, and quality assessment. We assessed the quality of MAs with the Measurement Tool to Assess Systematic Reviews (AMSTAR) 2 and assessed the evidence quality for significant outcomes using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) system. Results: We found 10 eligible MAs, which included between three (133 patients) and 15 randomized trials (1,217 patients), and five non-pharmacological interventions, namely, acupuncture therapy (40%), exercise intervention (30%), music therapy (10%), cognitive intervention (10%), and repetitive transcranial magnetic stimulation (rTMS) (10%). All the included MAs were critically low to low quality by AMSTAR 2. Acupuncture therapy and exercise intervention showed the preliminary potential to improve ADL and MMSE. rTMS and acupuncture therapy show benefits in decreasing ADAS-cog, and there were some evidence of improved MMSE with cognitive intervention. All these outcomes scored very low quality to moderate quality of evidence on the GRADE system. Conclusions: Non-pharmacological therapy shows promise for the treatment of AD, but there is still a lack of high-quality evidence. In the future, the quality of the original research needs to be improved, and strictly designed MAs should be carried out following methodological requirements.