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\"Within these pages you'll find myriad approaches to Alice, from horror to historical, taking us from nightmarish reaches of the imagination to tales that will shock, surprise, and tug on the heart-strings. So it's time now to go down the rabbit hole, or through the looking-glass or ... But no, wait. By picking up this book and starting to read it you're already there, can't you see?\"--Provided by publisher.

Field campaigns are instrumental in providing ground truth for understanding and modeling global ocean biogeochemical budgets. A survey however can only inspect a fraction of the global oceans, typically a region hundreds of kilometers wide for a temporal window of the order of (at most) several weeks. This spatiotemporal domain is also the one in which the mesoscale activity induces through horizontal stirring a strong variability in the biogeochemical tracers, with ephemeral, local contrasts which can easily mask the regional and seasonal gradients. Therefore, whenever local in situ measures are used to infer larger-scale budgets, one faces the challenge of identifying the mesoscale structuring effect, if not simply to filter it out. In the case of the KEOPS2 investigation of biogeochemical responses to natural iron fertilization, this problem was tackled by designing an adaptive sampling strategy based on regionally optimized multisatellite products analyzed in real time by specifically designed Lagrangian diagnostics. This strategy identified the different mesoscale and stirring structures present in the region and tracked the dynamical frontiers among them. It also enabled back trajectories for the ship-sampled stations to be estimated, providing important insights into the timing and pathways of iron supply, which were explored further using a model based on first-order iron removal. This context was essential for the interpretation of the field results. The mesoscale circulation-based strategy was also validated post-cruise by comparing the Lagrangian maps derived from satellites with the patterns of more than one hundred drifters, including some adaptively released during KEOPS2 and a subsequent research voyage. The KEOPS2 strategy was adapted to the specific biogeochemical characteristics of the region, but its principles are general and will be useful for future in situ biogeochemical surveys.

An accurate knowledge of the ocean mean dynamic topography (MDT) is mandatory for the optimal use of altimetric data, including their assimilation into operational ocean forecasting systems. A new global 1/4° resolution MDT was computed for the 1993–1999 time period with improved data and methodology compared to the previous RIO05 MDT field. First, a large‐scale MDT is obtained from the CLS01 altimetric Mean Sea Surface and a recent geoid model computed from 4.5 years of GRACE (Gravity Recovery and Climate Experiment) data. Altimetric sea level anomalies and in situ measurements are then combined to compute synthetic estimates of the MDT and the corresponding mean currents. While the RIO05 MDT was based on 10 years of in situ dynamic heights and drifting buoy velocities, the new field benefits from an enlarged data set of in situ measurements ranging from 1993 to 2008 and includes all hydrological profiles from the Argo array. Moreover, the processing of the in situ data has been updated. A new Ekman model was developed to extract the geostrophic velocity component from the drifting buoy measurements. The handling of hydrologic measurements has also been revisited. Compared to the previous RIO05 solution, the new global MDT resolves much stronger gradients in western boundary currents, with mean velocities being doubled in some places. Moreover, in comparison to several other recent MDT estimates, we find that the new CNES‐CLS09 MDT is in better agreement with independent in situ observations. Key Points Computation of a new mean dynamic topography Development of a new Ekman model Optimal filtering of MSS‐Geoid

Bacterial virulence factors facilitate host colonization and set the stage for the evolution of parasitic and mutualistic interactions. The Sodalis-allied clade of bacteria exhibit striking diversity in the range of both plant and animal feeding insects they inhabit, suggesting the appropriation of universal molecular mechanisms that facilitate establishment. Here, we report on the infection of the tsetse fly by free-living Sodalis praecaptivus, a close relative of many Sodalis-allied symbionts. Key genes involved in quorum sensing, including the homoserine lactone synthase (ypeI) and response regulators (yenR and ypeR) are integral for the benign colonization of S. praecaptivus. Mutants lacking ypeI, yenR and ypeR compromised tsetse survival as a consequence of their inability to repress virulence. Genes under quorum sensing, including homologs of the binary insecticidal toxin PirAB and a putative symbiosis-promoting factor CpmAJ, demonstrated negative and positive impacts, respectively, on tsetse survival. Taken together with results obtained from experiments involving weevils, this work shows that quorum sensing virulence suppression plays an integral role in facilitating the establishment of Sodalis-allied symbionts in diverse insect hosts. This knowledge contributes to the understanding of the early evolutionary steps involved in the formation of insect-bacterial symbiosis. Further, despite having no established history of interaction with tsetse, S. praecaptivus can infect reproductive tissues, enabling vertical transmission through adenotrophic viviparity within a single host generation. This creates an option for the use of S. praecaptivus in the biocontrol of insect disease vectors via paratransgenesis.

Artificial intelligence has been widely used in the field of dentistry in recent years. The present study highlights current advances and limitations in integrating artificial intelligence, machine learning, and deep learning in subfields of dentistry including periodontology, endodontics, orthodontics, restorative dentistry, and oral pathology. This article aims to provide a systematic review of current clinical applications of artificial intelligence within different fields of dentistry. The preferred reporting items for systematic reviews (PRISMA) statement was used as a formal guideline for data collection. Data was obtained from research studies for 2009–2022. The analysis included a total of 55 papers from Google Scholar, IEEE, PubMed, and Scopus databases. Results show that artificial intelligence has the potential to improve dental care, disease diagnosis and prognosis, treatment planning, and risk assessment. Finally, this study highlights the limitations of the analyzed studies and provides future directions to improve dental care.

The accurate knowledge of the ocean's mean dynamic topography (MDT) is a crucial issue for a number of oceanographic applications and, in some areas of the Mediterranean Sea, important limitations have been found pointing to the need of an upgrade. We present a new MDT that was computed for the Mediterranean Sea. It profits from improvements made possible by the use of extended data sets and refined processing. The updated data set spans the 1993–2012 period and consists of drifter velocities, altimetry data, hydrological profiles and model data. The methodology is similar to the previous MDT by Rio et al. (2007). However, in Rio et al. (2007) no hydrological profiles had been taken into account. This required the development of dedicated processing. A number of sensitivity studies have been carried out to obtain the most accurate MDT as possible. The main results from these sensitivity studies are the following: moderate impact to the choice of correlation scales but almost negligible sensitivity to the choice of the first guess (model solution). A systematic external validation to independent data has been made to evaluate the performance of the new MDT. Compared to previous versions, SMDT-MED-2014 (Synthetic Mean Dynamic Topography of the MEDiterranean sea) features shorter-scale structures, which results in an altimeter velocity variance closer to the observed velocity variance and, at the same time, gives better Taylor skills.

Although trefoil factor 1 (TFF1; previously named pS2) is abnormally expressed in about 50% of human breast tumors, its physiopathological role in this disease has been poorly studied. Moreover, controversial data have been reported. TFF1 function in the mammary gland therefore needs to be clarified. In this study, using retroviral vectors, we performed TFF1 gain- or loss-of-function experiments in four human mammary epithelial cell lines: normal immortalized TFF1-negative MCF10A, malignant TFF1-negative MDA-MB-231 and malignant TFF1-positive MCF7 and ZR75.1. The expression of TFF1 stimulated the migration and invasion in the four cell lines. Forced TFF1 expression in MCF10A, MDA-MB-231 and MCF7 cells did not modify anchorage-dependent or -independent cell proliferation. By contrast, TFF1 knockdown in MCF7 enhanced soft-agar colony formation. This increased oncogenic potential of MCF7 cells in the absence of TFF1 was confirmed in vivo in nude mice. Moreover, chemically induced tumorigenesis in TFF1-deficient (TFF1-KO) mice led to higher tumor incidence in the mammary gland and larger tumor size compared with wild-type mice. Similarly, tumor development was increased in the TFF1-KO ovary and lung. Collectively, our results clearly show that TFF1 does not exhibit oncogenic properties, but rather reduces tumor development. This beneficial function of TFF1 is in agreement with many clinical studies reporting a better outcome for patients with TFF1-positive breast primary tumors.

Past failures of monocultures, caused by wind-throw or insect damages, and ongoing climate change currently strongly stimulate research into mixed-species stands. So far, the focus has mainly been on combinations of species with obvious complementary functional traits. However, for any generalization, a broad overview of the mixing reactions of functionally different tree species in different mixing proportions, patterns and under different site conditions is needed, including assemblages of species with rather similar demands on resources such as light. Here, we studied the growth of Scots pine and oak in mixed versus monospecific stands on 36 triplets located along a productivity gradient across Europe, reaching from Sweden to Spain and from France to Georgia. The set-up represents a wide variation in precipitation (456–1250 mm year−1), mean annual temperature (6.7–11.5 °C) and drought index by de Martonne (21–63 mm °C−1). Stand inventories and increment cores of trees stemming from 40- to 132-year-old, fully stocked stands on 0.04–0.94-ha-sized plots provided insight into how species mixing modifies stand growth and structure compared with neighbouring monospecific stands. On average, the standing stem volume was 436 and 360 m3 ha−1 in the monocultures of Scots pine and oak, respectively, and 418 m3 ha−1 in the mixed stands. The corresponding periodical annual volume increment amounted to 10.5 and 9.1 m3 ha−1 year−1 in the monocultures and 10.5 m3 ha−1 year−1 in the mixed stands. Scots pine showed a 10% larger quadratic mean diameter (p < 0.05), a 7% larger dominant diameter (p < 0.01) and a 9% higher growth of basal area and volume in mixed stands compared with neighbouring monocultures. For Scots pine, the productivity advantages of growing in mixture increased with site index (p < 0.01) and water supply (p < 0.01), while for oak they decreased with site index (p < 0.01). In total, the superior productivity of mixed stands compared to monocultures increased with water supply (p < 0.10). Based on 7843 measured crowns, we found that in mixture both species, but especially oak, had significantly wider crowns (p < 0.001) than in monocultures. On average, we found relatively small effects of species mixing on stand growth and structure. Scots pine benefiting on rich, and oak on poor sites, allows for a mixture that is productive and most likely climate resistant all along a wide ecological gradient. We discuss the potential of this mixture in view of climate change.

The Intact Proviral DNA Assay (IPDA) was developed to address the critical need for a scalable method for intact HIV-1 reservoir quantification. This droplet digital PCR-based assay simultaneously targets two HIV-1 regions to distinguish genomically intact proviruses against a large background of defective ones, and its application has yielded insights into HIV-1 persistence. Reports of assay failures however, attributed to HIV-1 polymorphism, have recently emerged. Here, we describe a diverse North American cohort of people with HIV-1 subtype B, where the IPDA yielded a failure rate of 28% due to viral polymorphism. We further demonstrate that within-host HIV-1 diversity can lead the IPDA to underestimate intact reservoir size, and provide examples of how this phenomenon could lead to erroneous interpretation of clinical trial data. While the IPDA represents a major methodological advance, HIV-1 diversity should be addressed before its widespread adoption as a principal readout in HIV-1 remission trials. The intact proviral DNA assay quantifies the genomically intact HIV reservoir, but assay failure due to HIV-1 polymorphism has been observed. Here, the authors report a 28% failure rate in a cohort of people with HIV-1, and note within-host HIV-1 diversity as a further challenge to IPDA accuracy.