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Throughout the United States, cancer remains the second leading cause of death. Traditional treatments induce significant medical toxic effects and unpleasant adverse reactions, making them inappropriate for long-term use. Consequently, anticancer-drug resistance and relapse are frequent in certain situations. Thus, there is an urgent necessity to find effective antitumor medications that are specific and have few adverse consequences. Curcumin is a polyphenol derivative found in the turmeric plant (Curcuma longa L.), and provides chemopreventive, antitumor, chemo-, and radio-sensitizing properties. In this paper, we summarize the new nano-based formulations of polyphenolic curcumin because of the growing interest in its application against cancers and tumors. According to recent studies, the use of nanoparticles can overcome the hydrophobic nature of curcumin, as well as improving its stability and cellular bioavailability in vitro and in vivo. Several strategies for nanocurcumin production have been developed, each with its own set of advantages and unique features. Because the majority of the curcumin-based nanoformulation evidence is still in the conceptual stage, there are still numerous issues impeding the provision of nanocurcumin as a possible therapeutic option. To support the science, further work is necessary to develop curcumin as a viable anti-cancer adjuvant. In this review, we cover the various curcumin nanoformulations and nanocurcumin implications for therapeutic uses for cancer, as well as the current state of clinical studies and patents. We further address the knowledge gaps and future research orientations required to develop curcumin as a feasible treatment candidate.

Background Principal Component Analysis (PCA) is widely used in population genetics to visualize genetic relationships and population structures. In ancient genomics, genotype information may in parts remain unresolved due to the low abundance and degraded quality of ancient DNA. While methods like SmartPCA allow the projection of ancient samples despite missing data, they do not quantify projection uncertainty. The reliability of PCA projections for often very sparse ancient genotype samples is not well understood. Ignoring this uncertainty may lead to overconfident conclusions about the observed genetic relationships and population structure. Results This study systematically investigates the impact of missing loci on PCA projections using both simulated and real ancient human genotype data. Through extensive simulations with high-coverage ancient samples, we demonstrate that increasing levels of missing data can lead to less accurate SmartPCA projections, highlighting the importance of considering uncertainty when interpreting PCA results from ancient samples. To address this, we developed a probabilistic framework to quantify the uncertainty in PCA projections due to missing data. By applying our methodology to modern and ancient West Eurasian genotype samples from the Allen Ancient DNA Resource database, we could show a high concordance between our predicted projection and empirically derived distributions. Applying this framework to real-world data, we demonstrate its utility in predicting and visualizing embedding uncertainties for ancient samples of varying SNP coverages. Conclusion Our results emphasize the importance of accounting for projection uncertainty in ancient population studies. We therefore make our probabilistic model available through TrustPCA, a user-friendly web tool that provides researchers with uncertainty estimates alongside PCA projections, facilitating data exploration in ancient human genomic studies and enhancing transparency in data quality reporting.

Artificial intelligence (AI) in medicine and digital assistance systems such as chatbots will play an increasingly important role in future doctor - patient communication. To benefit from the potential of this technical innovation and ensure optimal patient care, future physicians should be equipped with the appropriate skills. Accordingly, a suitable place for the management and adaptation of digital assistance systems must be found in the medical education curriculum. To determine the existing levels of knowledge of medical students about AI chatbots in particular in the healthcare setting, this study surveyed medical students of the University of Luebeck and the University Hospital of Tuebingen. Using standardized quantitative questionnaires and qualitative analysis of group discussions, the attitudes of medical students toward AI and chatbots in medicine were investigated. From this, relevant requirements for the future integration of AI into the medical curriculum could be identified. The aim was to establish a basic understanding of the opportunities, limitations, and risks, as well as potential areas of application of the technology. The participants (N = 12) were able to develop an understanding of how AI and chatbots will affect their future daily work. Although basic attitudes toward the use of AI were positive, the students also expressed concerns. There were high levels of agreement regarding the use of AI in administrative settings (83.3%) and research with health-related data (91.7%). However, participants expressed concerns that data protection may be insufficiently guaranteed (33.3%) and that they might be increasingly monitored at work in the future (58.3%). The evaluations indicated that future physicians want to engage more intensively with AI in medicine. In view of future developments, AI and data competencies should be taught in a structured way during the medical curriculum and integrated into curricular teaching.

With the rapid development of high-throughput RNA-seq technologies, the transcriptome of prokaryotes can now be studied in unprecedented detail. Transcription start site (TSS) identification provides critical insights into transcriptional regulation. Still, current command-line tools for the prediction of TSS remain challenging with respect to their usability and lack of integrated exploration features. We introduce TSSpredator-Web, an interactive web application that enhances the usability of the established yet unpublished tool, TSSpredator. TSSpredator-Web facilitates TSS prediction from non-enriched and enriched RNA-seq data, classifies TSS relative to annotated genes, and allows users to explore results through dynamic visualizations and interactive tables. For the visualizations, we provide an UpSet plot summarizing the TSS distribution across experiments or classes, and a genome viewer that integrates transcriptomic and genomic data, which contextualizes the insights of the TSS predictions. To illustrate the usage of TSSpredator-Web, we provide a use case with Cappable-seq data from Escherichia coli. TSSpredator-Web is available on the TueVis visualization web-server at https://tsspredator-tuevis.cs.uni-tuebingen.de/. By combining user-friendly accessibility with interactive data exploration, TSSpredator-Web significantly facilitates genome-wide TSS analysis and interpretation in prokaryotes, empowering a broader range of researchers to generate biological insights from transcriptomic data.

Three 1,000-year-old mycobacterial genomes from Peruvian human skeletons reveal that a member of the Mycobacterium tuberculosis complex derived from seals caused human disease before contact in the Americas. Tuberculosis in the Americas Mycobacterium tuberculosis has a long history as a human pathogen, but how and when this unfortunate relationship began is not clear. Although the strains found in the Americas today are closely related to those in Europe, archaeological evidence suggests that the disease was present in the New World before contact with Europeans. Johannes Krause and colleagues sequenced three approximately 1,000-year-old M. tuberculosis genomes from human remains in Peru, proving that the pathogen caused human disease in the pre-contact New World. The ancient DNA is most closely related to that found in strains adapted to seals and sea lions. The authors hypothesize that these sea mammals may have contracted the disease from an African host species and carried it across the oceans where exploitation of marine resources by coastal peoples of South America allowed zoonotic transfer. This strain of tuberculosis may have then adapted to humans before being replaced by European strains introduced post-contact. Modern strains of Mycobacterium tuberculosis from the Americas are closely related to those from Europe, supporting the assumption that human tuberculosis was introduced post-contact 1 . This notion, however, is incompatible with archaeological evidence of pre-contact tuberculosis in the New World 2 . Comparative genomics of modern isolates suggests that M. tuberculosis attained its worldwide distribution following human dispersals out of Africa during the Pleistocene epoch 3 , although this has yet to be confirmed with ancient calibration points. Here we present three 1,000-year-old mycobacterial genomes from Peruvian human skeletons, revealing that a member of the M. tuberculosis complex caused human disease before contact. The ancient strains are distinct from known human-adapted forms and are most closely related to those adapted to seals and sea lions. Two independent dating approaches suggest a most recent common ancestor for the M. tuberculosis complex less than 6,000 years ago, which supports a Holocene dispersal of the disease. Our results implicate sea mammals as having played a role in transmitting the disease to humans across the ocean.

Egypt, located on the isthmus of Africa, is an ideal region to study historical population dynamics due to its geographic location and documented interactions with ancient civilizations in Africa, Asia and Europe. Particularly, in the first millennium BCE Egypt endured foreign domination leading to growing numbers of foreigners living within its borders possibly contributing genetically to the local population. Here we present 90 mitochondrial genomes as well as genome-wide data sets from three individuals obtained from Egyptian mummies. The samples recovered from Middle Egypt span around 1,300 years of ancient Egyptian history from the New Kingdom to the Roman Period. Our analyses reveal that ancient Egyptians shared more ancestry with Near Easterners than present-day Egyptians, who received additional sub-Saharan admixture in more recent times. This analysis establishes ancient Egyptian mummies as a genetic source to study ancient human history and offers the perspective of deciphering Egypt’s past at a genome-wide level. Archaeological and historical records had shown ancient Egypt before and after Ptolemaic and Roman periods to be a hub of human migration and exchange. Here, Schuenemann and colleagues analyse ancient mitochondrial and nuclear DNA to investigate the genetic history of Egypt.

Mycobacterium lepromatosis is an uncultured human pathogen associated with diffuse lepromatous leprosy and a reactional state known as Lucio's phenomenon. By using deep sequencing with and without DNA enrichment, we obtained the near-complete genome sequence of M. lepromatosis present in a skin biopsy from a Mexican patient, and compared it with that of Mycobacterium leprae , which has undergone extensive reductive evolution. The genomes display extensive synteny and are similar in size (∼3.27 Mb). Protein-coding genes share 93% nucleotide sequence identity, whereas pseudogenes are only 82% identical. The events that led to pseudogenization of 50% of the genome likely occurred before divergence from their most recent common ancestor (MRCA), and both M. lepromatosis and M. leprae have since accumulated new pseudogenes or acquired specific deletions. Functional comparisons suggest that M. lepromatosis has lost several enzymes required for amino acid synthesis whereas M. leprae has a defective heme pathway. M. lepromatosis has retained all functions required to infect the Schwann cells of the peripheral nervous system and therefore may also be neuropathogenic. A phylogeographic survey of 227 leprosy biopsies by differential PCR revealed that 221 contained M. leprae whereas only six, all from Mexico, harbored M. lepromatosis . Phylogenetic comparisons indicate that M. lepromatosis is closer than M. leprae to the MRCA, and a Bayesian dating analysis suggests that they diverged from their MRCA approximately 13.9 Mya. Thus, despite their ancient separation, the two leprosy bacilli are remarkably conserved and still cause similar pathologic conditions. Significance Leprosy was thought to be exclusively caused by infection of humans by Mycobacterium leprae . In 2008, Han et al. proposed that Mycobacterium lepromatosis , a separate unculturable species, might be responsible for a rare yet severe form of the disease called diffuse lepromatous leprosy. Here, by using comparative genomics, we show that the two species are very closely related and derived from a common ancestor that underwent genome downsizing and gene decay. Since their separation 13.9 Mya, the two species have continued to lose genes, but from different regions of the genome, and M. leprae appears to be more recent. In a phylogeographic survey, by using differential PCR, we found that M. lepromatosis was scarce and restricted to patients from Mexico.

Campylobacter jejuni is currently the leading cause of bacterial gastroenteritis in humans. Comparison of multiple Campylobacter strains revealed a high genetic and phenotypic diversity. However, little is known about differences in transcriptome organization, gene expression, and small RNA (sRNA) repertoires. Here we present the first comparative primary transcriptome analysis based on the differential RNA-seq (dRNA-seq) of four C. jejuni isolates. Our approach includes a novel, generic method for the automated annotation of transcriptional start sites (TSS), which allowed us to provide genome-wide promoter maps in the analyzed strains. These global TSS maps are refined through the integration of a SuperGenome approach that allows for a comparative TSS annotation by mapping RNA-seq data of multiple strains into a common coordinate system derived from a whole-genome alignment. Considering the steadily increasing amount of RNA-seq studies, our automated TSS annotation will not only facilitate transcriptome annotation for a wider range of pro- and eukaryotes but can also be adapted for the analysis among different growth or stress conditions. Our comparative dRNA-seq analysis revealed conservation of most TSS, but also single-nucleotide-polymorphisms (SNP) in promoter regions, which lead to strain-specific transcriptional output. Furthermore, we identified strain-specific sRNA repertoires that could contribute to differential gene regulation among strains. In addition, we identified a novel minimal CRISPR-system in Campylobacter of the type-II CRISPR subtype, which relies on the host factor RNase III and a trans-encoded sRNA for maturation of crRNAs. This minimal system of Campylobacter, which seems active in only some strains, employs a unique maturation pathway, since the crRNAs are transcribed from individual promoters in the upstream repeats and thereby minimize the requirements for the maturation machinery. Overall, our study provides new insights into strain-specific transcriptome organization and sRNAs, and reveals genes that could modulate phenotypic variation among strains despite high conservation at the DNA level.

Altitudinal gradients provide valuable information about the effects of environmental variables on changes in species richness and composition as well as the distribution of below ground fungal communities. Since most knowledge in this respect has been gathered on aboveground communities, we focused our study towards the characterization of belowground fungal communities associated with two different ages of Norway spruce (Picea abies) trees along an altitudinal gradient. By sequencing the internal transcribed spacer (ITS) region on the Illumina platform, we investigated the fungal communities in a floristically and geologically relatively well explored forest on the slope of Mt. Iseler of the Bavarian Alps. From fine roots and rhizosphere of a total of 90 of Norway spruce trees from 18 plots we detected 1285 taxa, with a range of 167 to 506 (average 377) taxa per plot. Fungal taxa are distributed over 96 different orders belonging to the phyla Ascomycota, Basidiomycota, Chrytridiomycota, Glomeromycota, and Mucoromycota. Overall the Agaricales (438 taxa) and Tremellales (81 taxa) belonging to the Basidiomycota and the Hypocreales (65 spp.) and Helotiales (61 taxa) belonging to the Ascomycota represented the taxon richest orders. The evaluation of our multivariate generalized mixed models indicate that the altitude has a significant influence on the composition of the fungal communities (p < 0.003) and that tree age determines community diversity (p < 0.05). A total of 47 ecological guilds were detected, of which the ectomycorrhizal and saprophytic guilds were the most taxon-rich. Our ITS amplicon Illumina sequencing approach allowed us to characterize a high fungal community diversity that would not be possible to capture with fruiting body surveys alone. We conclude that it is an invaluable tool for diverse monitoring tasks and inventorying biodiversity, especially in the detection of microorganisms developing very ephemeral and/or inconspicuous fruiting bodies or lacking them all together. Results suggest that the altitude mainly influences the community composition, whereas fungal diversity becomes higher in mature/older trees. Finally, we demonstrate that novel techniques from bacterial microbiome analyses are also useful for studying fungal diversity and community structure in a DNA metabarcoding approach, but that incomplete reference sequence databases so far limit effective identification.

Studying ancient DNA allows us to retrace the evolutionary history of human pathogens, such as Mycobacterium leprae, the main causative agent of leprosy. Leprosy is one of the oldest recorded and most stigmatizing diseases in human history. The disease was prevalent in Europe until the 16th century and is still endemic in many countries with over 200,000 new cases reported annually. Previous worldwide studies on modern and European medieval M. leprae genomes revealed that they cluster into several distinct branches of which two were present in medieval Northwestern Europe. In this study, we analyzed 10 new medieval M. leprae genomes including the so far oldest M. leprae genome from one of the earliest known cases of leprosy in the United Kingdom-a skeleton from the Great Chesterford cemetery with a calibrated age of 415-545 C.E. This dataset provides a genetic time transect of M. leprae diversity in Europe over the past 1500 years. We find M. leprae strains from four distinct branches to be present in the Early Medieval Period, and strains from three different branches were detected within a single cemetery from the High Medieval Period. Altogether these findings suggest a higher genetic diversity of M. leprae strains in medieval Europe at various time points than previously assumed. The resulting more complex picture of the past phylogeography of leprosy in Europe impacts current phylogeographical models of M. leprae dissemination. It suggests alternative models for the past spread of leprosy such as a wide spread prevalence of strains from different branches in Eurasia already in Antiquity or maybe even an origin in Western Eurasia. Furthermore, these results highlight how studying ancient M. leprae strains improves understanding the history of leprosy worldwide.