Rhipicephalus microplus poses a substantial threat to livestock health and agricultural economies worldwide. Its remarkable adaptability to diverse environments and hosts is a testament to its extensive genetic diversity. This review delves into the genetic diversity of R. microplus, employing three pivotal genetic markers: the cytochrome c oxidase I (COX1) gene, ribosomal genes, and microsatellites. The COX1 gene, a crucial tool for genetic characterization and phylogenetic clustering, provides insights into the adaptability of ticks. Ribosomal genes, such as internal transcribed spacer regions (ITS-1 and2) as well as 18S and 28S, are routinely utilized for species differentiation. However, their use is limited due to indels (insertions and deletions). Microsatellites and minisatellites, known for their high polymorphism, have been successfully employed to study populations and genetic diversity across various tick species. Despite their effectiveness, challenges such as null alleles and marker variations warrant careful consideration. Bm86, a well-studied vaccine candidate, exhibits substantial genetic diversity. This diversity directly influences vaccine efficacy, posing challenges for developing a universally effective Bm86-based vaccine. Moreover, the review emphasizes the prevalence of genes associated with synthetic pyrethroid resistance. Identifying single nucleotide polymorphisms in the acaricide-resistant genes of R. microplus has facilitated the development of molecular markers for detecting and monitoring resistance against synthetic pyrethroids. However, mutations in sodium channels, the target site for synthetic pyrethroid, correlate well with the resistance status of R. microplus, which is not the case with other acaricide target genes. This study underscores the importance of understanding genetic diversity in developing effective tick management strategies. The choice of genetic marker should be tailored based on the level of taxonomic resolution and the group of ticks under investigation. A holistic approach combining multiple markers and integrating additional molecular and morphological data may offer a more comprehensive understanding of tick diversity and relationships. This research has far-reaching implications in formulating breeding programs and the development of vaccine against ticks and tick-borne diseases (TTBDs) as well as strategies for the management of resistant ticks.

BACKGROUND: The indications for sentinel lymph node biopsy (SLNB) for thin melanoma are still unclear. This meta-analysis aims to determine the positive rate of SLNB in thin melanoma and to summarize the predictive value of different high-risk features for positive results of SLNB.
METHODS: Four databases were searched for literature on SLNB performed in patients with thin melanoma published between January 2000 and December 2020. The overall positive rate and positive rate of each high-risk feature were calculated and obtained with 95% confidence intervals (CIs). Both unadjusted odds ratios (ORs) and adjusted ORs (AORs) of high-risk features were analyzed. Pooled effects were estimated using random-effects model meta-analyses.
RESULTS: Sixty-six studies reporting 38,844 patients with thin melanoma who underwent SLNB met the inclusion criteria. The pooled positive rate of SLNB was 5.1% [95% confidence interval (CI) 4.9%-5.3%]. Features significantly predicted a positive result of SLNB were thickness≥0.8 mm [AOR 1.94 (95%CI 1.28-2.95); positive rate 7.0% (95%CI 6.0-8.0%)]; ulceration [AOR 3.09 (95%CI 1.75-5.44); positive rate 4.2% (95%CI 1.8-7.2%)]; mitosis rate >0/mm2 [AOR 1.63 (95%CI 1.13-2.36); positive rate 7.7% (95%CI 6.3-9.1%)]; microsatellites [OR 3.8 (95%CI 1.38-10.47); positive rate 16.6% (95%CI 2.4-36.6%)]; and vertical growth phase [OR 2.76 (95%CI 1.72-4.43); positive rate 8.1% (95%CI 6.3-10.1%)].
CONCLUSIONS: The overall positive rate of SLNB in thin melanoma was 5.1%. The strongest predictor for SLN positivity identified was microsatellites on unadjusted analysis and ulceration on adjusted analysis. Breslow thickness ≥0.8 mm and mitosis rate >0/mm2 both predict SLN positivity in adjusted analysis and increase the positive rate to 7.0% and 7.7%. We suggest patients with thin melanoma with the above high-risk features should be considered for giving an SLNB.

The grey wolf (Canis lupus) is an iconic large carnivore that has increasingly been recognized as an apex predator with intrinsic value and a keystone species. However, wolves have also long represented a primary source of human-carnivore conflict, which has led to long-term persecution of wolves, resulting in a significant decrease in their numbers, genetic diversity and gene flow between populations. For more effective protection and management of wolf populations in Europe, robust scientific evidence is crucial. This review serves as an analytical summary of the main findings from wolf population genetic studies in Europe, covering major studies from the \'pre-genomic era\' and the first insights of the \'genomics era\'. We analyse, summarize and discuss findings derived from analyses of three compartments of the mammalian genome with different inheritance modes: maternal (mitochondrial DNA), paternal (Y chromosome) and biparental [autosomal microsatellites and single nucleotide polymorphisms (SNPs)]. To describe large-scale trends and patterns of genetic variation in European wolf populations, we conducted a meta-analysis based on the results of previous microsatellite studies and also included new data, covering all 19 European countries for which wolf genetic information is available: Norway, Sweden, Finland, Estonia, Latvia, Lithuania, Poland, Czech Republic, Slovakia, Germany, Belarus, Russia, Italy, Croatia, Bulgaria, Bosnia and Herzegovina, Greece, Spain and Portugal. We compared different indices of genetic diversity in wolf populations and found a significant spatial trend in heterozygosity across Europe from south-west (lowest genetic diversity) to north-east (highest). The range of spatial autocorrelation calculated on the basis of three characteristics of genetic diversity was 650-850 km, suggesting that the genetic diversity of a given wolf population can be influenced by populations up to 850 km away. As an important outcome of this synthesis, we discuss the most pressing issues threatening wolf populations in Europe, highlight important gaps in current knowledge, suggest solutions to overcome these limitations, and provide recommendations for science-based wolf conservation and management at regional and Europe-wide scales.