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China's southwestern karst landscapes support remarkable cavefish diversity, especially within , the world's largest cavefish genus. Using integrative taxonomic methods, we describe sp. nov., found in a subterranean river in Guizhou Province. This species lacks horn-like cranial structures; its eyes are either reduced to a dark spot or absent. It possesses a pronounced nuchal hump and a forward-protruding, duckbill-shaped head. Morphometric analysis of 28 individuals from six species shows clear separation from related taxa. Nano-CT imaging reveals distinct vertebral and cranial features. Phylogenetic analyses of mitochondrial and genes place within group as sister to , with p-distances of 1.7% () and 0.7% (), consistent with sister-species patterns within the genus. is differentiated from by its eyeless or degenerate-eye condition and lack of bifurcated horns. It differs from , its morphologically closest species, in having degenerate or absent eyes, shorter maxillary barbels, and pelvic fins that reach the anus. The combination of morphological and molecular evidence supports its recognition as a distinct species. Accurate documentation of such endemic and narrowly distributed taxa is important for conservation and for understanding speciation in cave habitats.
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http://dx.doi.org/10.3390/ani15152216 | DOI Listing |
Microb Genom
September 2025
School of Animal and Veterinary Sciences, The University of Adelaide, Roseworthy, South Australia 5371, Australia.
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Sleep is essential for maintaining human health and quality of life. Analyzing physiological signals during sleep is critical in assessing sleep quality and diagnosing sleep disorders. However, manual diagnoses by clinicians are time-intensive and subjective.
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August 2025
School of Computer Science, Xi'an Polytechnic University, 710048, Xi'an, China.
Cancer, with its inherent heterogeneity, is commonly categorized into distinct subtypes based on unique traits, cellular origins, and molecular markers specific to each type. However, current studies primarily rely on complete multi-omics datasets for predicting cancer subtypes, often overlooking predictive performance in cases where some omics data may be missing and neglecting implicit relationships across multiple layers of omics data integration. This paper introduces Multi-Layer Matrix Factorization (MLMF), a novel approach for cancer subtyping that employs multi-omics data clustering.
View Article and Find Full Text PDFEnviron Monit Assess
September 2025
Indira Gandhi Conservation Monitoring Centre, World Wide Fund-India, New Delhi, 110003, India.
Understanding the intricate relationship between land use/land cover (LULC) transformations and land surface temperature (LST) is critical for sustainable urban planning. This study investigates the spatiotemporal dynamics of LULC and LST across Delhi, India, using thermal data from Landsat 7 (2001), Landsat 5 (2011) and Landsat 8 (2021) resampled to 30-m spatial resolution, during the peak summer month of May. The study aims to target three significant aspects: (i) to analyse and present LULC-LST dynamics across Delhi, (ii) to evaluate the implications of LST effects at the district level and (iii) to predict seasonal LST trends in 2041 for North Delhi district using the seasonal auto-regressive integrated moving average (SARIMA) time series model.
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