OBJECTIVE: Manual detection and scoring of Ki67 hotspots is difficult and prone to variability, limiting its clinical utility. Automated hotspot detection and scoring by digital image analysis (DIA) could improve the assessment of the Ki67 hotspot proliferation index (PI). This study compared the clinical performance of Ki67 hotspot detection and scoring DIA algorithms based on virtual dual staining (VDS) and deep learning (DL) with manual Ki67 hotspot PI assessment.
METHODS: Tissue sections of 135 consecutive invasive breast carcinomas were immunohistochemically stained for Ki67. Two DIA algorithms, based on VDS and DL, automatically determined the Ki67 hotspot PI. For manual assessment; two independent observers detected hotspots and calculated scores using a validated scoring protocol.
RESULTS: Automated hotspot detection and assessment by VDS and DL could be performed in 73% and 100% of the cases, respectively. Automated hotspot detection by VDS and DL led to higher Ki67 hotspot PIs (mean 39.6% and 38.3%, respectively) compared to manual consensus Ki67 PIs (mean 28.8%). Comparing manual consensus Ki67 PIs with VDS Ki67 PIs revealed substantial correlation (r = 0.90), while manual consensus versus DL Ki67 PIs demonstrated high correlation (r = 0.95).
CONCLUSIONS: Automated Ki67 hotspot detection and analysis correlated strongly with manual Ki67 assessment and provided higher PIs compared to manual assessment. The DL-based algorithm outperformed the VDS-based algorithm in clinical applicability, because it did not depend on virtual alignment of slides and correlated stronger with manual scores. Use of a DL-based algorithm may allow clearer Ki67 PI cutoff values, thereby improving the clinical usability of Ki67.

Biogeographers have often been puzzled by several unusual features in the Juan Fernández Islands (JFI) biota. These include the very high endemism density, multiple endemics that are older than the current islands, close biogeographic affinities with the central and West Pacific, and affinities with the diverse Coast Range of central Chile. We review aspects of biogeography in the JFI and the Coast Range in light of recent geological studies. These have examined the mantle below the East Pacific and South America, and have produced radical, new ideas on tectonic history. A long-lived, intraoceanic archipelago ~9000 km long is now thought to have existed in the East Pacific (passing between the JFI hotspot and mainland Chile) until the mid-Cretaceous. At this time, South America, which was moving westward with the opening of the Atlantic, collided with the archipelago. The assumption that the JFI biota is no older than its current islands is questionable, as taxa would have survived on prior islands produced at the JFI hotspot. We propose a new interpretation of evolution in the region based on tectonics rather than on island age and incorporating the following factors: the newly described East Pacific Archipelago; a long history for the JFI hotspot; metapopulation dynamics, including metapopulation vicariance; and formation of the Humboldt Current in the Cretaceous. The model accounts for many distinctive features of the JFI and Coast Range biota.

UNASSIGNED: A child is a nation\'s supreme asset and future. India homes 444 million children, aged between 0 and 18 years, contributing to 19% of the world\'s children. Crime against children is detrimental to their mental and physical health and affects their growth and development. The National Crime Record Bureau recently reported that a crime targeting children happens every 4 minutes. There is a paucity of literature regarding the burden of crime against children. To understand the magnitude and spatial distribution of crime against children, a retrospective surveillance study was conducted in the state of Tamil Nadu, India, from 2017 to 2021.
UNASSIGNED: This is a cross-sectional analytical type of study conducted in KIMSRC, Chengalpattu, Tamil Nadu. The data from the yearly crime review bulletin of Tamil Nadu from 2017 to 2021 were cleaned, transformed, and analyzed using Python v3.8 and subjected to geospatial auto-correlation and hotspot analysis using the Getis-Ord Gi* in ArcGIS Pro v3.1. The endemicity pattern was studied through cluster analysis with Hierarchical Density Based Scanning in Python and visualization in ArcGIS pro v3.1 in the study area.
UNASSIGNED: In Tamil Nadu, only one hotspot district in 2017 [Tiruppattur (95% confidence, P < 0.05)] and one hotspot in 2020 [Villupuram (90% confidence, P < 0.1)] were identified, with others being insignificant. The districts which show very high prevalence of crimes against children are Chennai, Ranipet, Chengalpattu, Viluppuram, Tiruvannamalai, Vellore, Tiruppattur, Krishnagiri, Dharmapuri, Salem, Cuddalore, Thanjavur, Tiruchirappalli, Karur, Tiruppur, Coimbatore, Dindigul, Pudukkottai, Sivaganga, Tenkasi, Thoothukkudi, Tirunelveli, and Kanniyakumari.
UNASSIGNED: This study identifies key areas within the state of Tamil Nadu which have a high prevalence of crimes against children and also areas that are hotspots for such crimes. Greater resources and measures can now be targeted toward these areas by stakeholders, which can help in the reduction of crimes against children.

Plasmon-induced hot carriers are a promising \"active\" energy source, attracting increasing attention for their potential applications in photocatalysis and photodetection. Here, we hybridize plasmonic Au spherical nanoparticles (SNPs) with catalytically active Pt nanocrystals to form Au@Pt core-satellite nanoparticles (CSNPs), which act as both an efficient catalyst for plasmon-promoted decarboxylation reaction and a robust surface-enhanced Raman scattering (SERS) substrate for plasmon-enhanced molecular spectroscopic detection. By regulating the coverage of Pt nanocrystals on the Au SNPs, we modulated the \"hotspot\" structures of the Au@Pt CSNPs to optimize the SERS detecting capability and catalytic decarboxylation performance. The coupling functionalities enable us with unique opportunities to in-situ SERS monitor universal reactions catalyzed by active catalysts (e.g. Pt, Pd) in the chemical industry in real-time. The decarboxylation rate of 4-mercaptophenylacetic acid was dynamically controlled by the surface catalytic decarboxylation step, following first-order overall reaction kinetics. Moreover, the reaction rate exhibited a strong correlation with the local field enhancement |E/E0|4 of the hotspot structure. This work provides spectroscopic insights into the molecule-plasmon interface under the plasmon-promoted catalytic reactions, guiding the rational design of the plasmonic interface of nanocatalysts to achieve desired functionalities.

BRAF is one of multiple RAF proteins responsible for the activation of the MAPK cell signalling cascade involved in cell growth, differentiation, and survival. A hotspot BRAFV600E mutation, in exon 15, was determined to be a driver in 100% hairy cell leukaemias, 50%-60% of human melanomas, 30%-50% of human thyroid carcinomas and 10%-20% of human colorectal carcinomas. The orthologous BRAFV595E mutation was seen in 67% and 80% of canine bladder transitional cell carcinomas and prostatic adenocarcinomas, respectively. Since veterinary and human cancers exploit similar pathways and BRAF is highly conserved across species, BRAF can be expected to be a driver in a feline cancer. Primers were developed to amplify exon 15 of feline BRAF. One hundred ninety-six feline tumours were analysed. Sanger sequencing of the 211 bp PCR amplicon was done. A BRAF mutation was found in one tumour, a cutaneous melanoma. The mutation was a BRAFV597E mutation, orthologous to the canine and human hotspot mutations. A common synonymous variant, BRAFT586T, was seen in 23% (47/196) of tumours. This variant was suspected to be a single nucleotide polymorphism. BRAF was not frequently mutated in common feline tumours or in tumour types that frequently harbour BRAF mutations in human and canine cancers. As is seen in canine cancer genomics, the mutational profile in feline tumours may not parallel the histologic equivalent in human oncology.

Lampedusa, a picturesque Italian island in the Mediterranean, serves as a gateway for migrants from Africa and Asia to Europe. Despite populist rhetoric portraying migrants as carriers of disease, epidemiological data reveal very low levels of communicable diseases among migrants, challenging false narratives and xenophobic sentiments propagated by populist governments.

UNASSIGNED: Bibliometric analysis is commonly used to visualize the knowledge foundation, trends, and patterns in a specific scientific field by performing a quantitative evaluation of the relevant literature. The purpose of this study was to perform a bibliometric analysis of recent studies in the field of orthopedic biofilm research and identify its current trends and hotspots.
UNASSIGNED: Research studies were retrieved from the Web of Science Core Collection and Scopus databases and analyzed in bibliometrix with R package (4.2.2).
UNASSIGNED: A total of 2426 literature were included in the study. Journal of orthopaedic research and Clinical orthopaedics and related research ranked first in terms of productivity and impact, with 57 published articles and 32 h-index, respectively. Trampuz A, Ohio State Univ and the United States ranked as the most productive authors, institutions, and countries. Biofilm formation, role of sonication, biomaterial mechanism and antibiotic loading have been investigated as the trend and hotspots in the field of orthopedic biofilm research.
UNASSIGNED: This study provides a thorough overview of the state of the art of current orthopedic biofilm research and offers valuable insights into recent trends and hotspots in this field.

[This corrects the article DOI: 10.3389/fpubh.2023.1136939.].

Freshwater environments are primary receiving systems of wastewater and effluents, which carry low concentrations of antibiotics and antimicrobial-resistant (AMR) bacteria and genes. Aquatic microbial communities are thus exposed to environmentally relevant concentrations of antibiotics (ERCA) that presumably influence the acquisition and spread of environmental AMR. Here, we analyzed ERCA exposure with and without the additional presence of municipal wastewater treatment plant effluent (W) and swine manure run-off (M) on aquatic biofilm resistomes. Microscopic analyses revealed decreased taxonomic diversity and biofilm structural integrity, while metagenomic analysis revealed an increased abundance of resistance, virulence, and mobile element-related genes at the highest ERCA exposure levels, with less notable impacts observed when solely exposed to W or M effluents. Microbial function predictions indicated increased gene abundance associated with energy and cell membrane metabolism and heavy metal resistance under ERCA conditions. In silico predictions of increased resistance mechanisms did not correlate with observed phenotypic resistance patterns when whole communities were exposed to antimicrobial susceptibility testing. This reveals important insight into the complexity of whole-community coordination of physical and genetic responses to selective pressures. Lastly, the environmental AMR risk assessment of metagenomic data revealed a higher risk score for biofilms grown at sub-MIC antibiotic conditions.

OBJECTIVE: To analyze the hotspots and trends in artificial intelligence (AI) research in the field of cataracts.
METHODS: The Science Citation Index Expanded of the Web of Science Core Collection was used to collect the research literature related to AI in the field of cataracts, which was analyzed for valuable information such as years, countries/regions, journals, institutions, citations, and keywords. Visualized co-occurrence network graphs were generated through the library online analysis platform, VOSviewer, and CiteSpace tools.
RESULTS: A total of 222 relevant research articles from 41 countries were selected. Since 2019, the number of related articles has increased significantly every year. China (n = 82, 24.92%), the United States (n = 55, 16.72%) and India (n = 26, 7.90%) were the three countries with the most publications, accounting for 49.54% of the total. The Journal of Cataract and Refractive Surgery (n = 13, 5.86%) and Translational Vision Science & Technology (n = 10, 4.50%) had the most publications. Sun Yat-sen University (n = 25, 11.26%), the Chinese Academy of Sciences (n = 17, 7.66%), and Capital Medical University (n = 16, 7.21%) are the three institutions with the highest number of publications. We discovered through keyword analysis that cataract, diagnosis, imaging, classification, intraocular lens, and formula are the main topics of current study.
CONCLUSIONS: This study revealed the hot spots and potential trends of AI in terms of cataract diagnosis and intraocular lens power calculation. AI will become more prevalent in the field of ophthalmology in the future.