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Abstract The study of evolutionary rates and patterns is the key to understand how natural selection shaped the current and past diversity of phenotypes. Phylogenetic comparative methods offer an array of solutions to undertake this challenging task, and help understanding phenotypic variation in full in most circumstances. However, complex, three-dimensional structures such as the skull and the brain serve disparate goals, and different portions of these phenotypes often fulfil different functions, making it hard to understand which parts truly were recruited by natural selection. In the recent past, we developed tools apt to chart evolutionary rate and patterns directly on three-dimensional shapes, according to their magnitude and direction. Here, we present further developments of these tools, which now allow to restitute the mapping of rates and patterns with full biological realism. The tools are condensed in a new R software package.

Abstract The global biodiversity crisis is generated by the combined effects of human-induced climate change and land conversion. Madagascar is one of the World’s most renewed hotspots of biodiversity. Yet, its rich variety of plant and animal species is threatened by deforestation and climate change. Predicting the future of Madagascar’s chameleons, in particular, is complicated by their ecological rarity, making it hard to tell which factor is the most menacing to their survival. By applying an extension of the ENphylo species distribution model algorithm to work with extremely rare species, we find that Madagascar chameleons will face intense species loss in the north-western sector of the island. Land conversion by humans will drive most of the loss, and will intersect in a complex, nonlinear manner with climate change. We find that some 30% of the Madagascar’s chameleons may lose in the future nearly all their habitats, critically jeopardizing their chance for survival.

Abstract Taphonomic deformation, whether it be brittle or plastic, is possibly the most influential process hindering the correct understanding of fossil species morphology. This is especially true if the deformation affects type specimens or applies to or obscures taxonomically diagnostic or functionally significant traits. Target Deformation, a recently developed virtual manipulation protocol, was implemented to address this issue by applying landmark-guided restoration of the original, deformed fossils, using undeformed specimens (or parts thereof) of the same species as a reference. The enigmatic Early Pleistocene canid Canis arnensis provides a typical example of a fossil species in dire need of virtual restoration. Its lectotype specimen is heavily deformed and none of the few known skulls are well preserved, obscuring the recognition of its systematic and phylogenetic position. Our results indicate that the algorithm effectively countered the lectotype skull’s laterolateral compression and its concomitant rostrocaudal elongation. Morphometrically, comparison of the retrodeformed cranium (IGF 867_W) with other specimens of the same species, and to other fossil and extant canid material, confirms IGF 867_W consistently clusters within C. arnensis variability. Overall, the evidence presented here confirms that Target Deformation provides a powerful tool to better characterize complex taxa like C. arnensis, whose knowledge is severely affected by the state of preservation of its fossil material.

Abstract The use of light as a catalytic prompt for the synthesis of industrial relevant compounds is widely explored in the past years, with a special consideration over the hydrogen evolution reaction (HER). However, semiconductors for heterogeneous photocatalysis suffer from fast charge recombination and, consequently, low solar‐to‐hydrogen efficiency. These drawbacks can be mitigated by coupling photocatalysts with an external circuit that can physically separate the photogenerated charge carriers (electrons and holes). For this reason, photoelectrochemical (PEC) production of hydrogen is under the spotlight as promising green and sustainable technique and widely investigated in numerous publications. However, considering that a significant fraction of the hydrogen produced is used for reduction processes, the development of PEC devices for direct in situ hydrogenation can address the challenges associated with hydrogen storage and distribution. This Perspective aims at highlighting the fundamental aspects of HER from PEC systems, and how these can be harnessed toward the implementation of suitable settings for the hydrogenation of organic compounds of industrial value.

Abstract In recent years, research focused on the multifaceted landscape and functions of cancer-associated fibroblasts (CAFs) aimed to reveal their heterogeneity and identify commonalities across diverse tumors for more effective therapeutic targeting of pro-tumoral stromal microenvironment. However, a unified functional categorization of CAF subsets remains elusive, posing challenges for the development of targeted CAF therapies in clinical settings. The CAF phenotype arises from a complex interplay of signals within the tumor microenvironment, where transcription factors serve as central mediators of various cellular pathways. Recent advances in single-cell RNA sequencing technology have emphasized the role of transcription factors in the conversion of normal fibroblasts to distinct CAF subtypes across various cancer types. This review provides a comprehensive overview of the specific roles of transcription factor networks in shaping CAF heterogeneity, plasticity, and functionality. Beginning with their influence on fibroblast homeostasis and reprogramming during wound healing and fibrosis, it delves into the emerging insights into transcription factor regulatory networks. Understanding these mechanisms not only enables a more precise characterization of CAF subsets but also sheds light on the early regulatory processes governing CAF heterogeneity and functionality. Ultimately, this knowledge may unveil novel therapeutic targets for cancer treatment, addressing the existing challenges of stromal-targeted therapies.

Summary: Background: Tertiary Lymphoid Structures (TLS) correlate with positive outcomes in patients with NSCLC and the efficacy of immune checkpoint blockade (ICB) in cancer. The actin regulatory protein hMENA undergoes tissue-specific splicing, producing the epithelial hMENA11a linked to favorable prognosis in early NSCLC, and the mesenchymal hMENAΔv6 found in invasive cancer cells and pro-tumoral cancer-associated fibroblasts (CAFs). This study investigates how hMENA isoforms in tumor cells and CAFs relate to TLS presence, localization and impact on patient outcomes and ICB response. Methods: Methods involved RNA-SEQ on NSCLC cells with depleted hMENA isoforms. A retrospective observational study assessed tissues from surgically treated N0 patients with NSCLC, using immunohistochemistry for tumoral and stromal hMENA isoforms, fibronectin, and TLS presence. ICB-treated patient tumors were analyzed using Nanostring nCounter and GeoMx spatial transcriptomics. Multiparametric flow cytometry characterized B cells and tissue-resident memory T cells (TRM). Survival and ICB response were estimated in the cohort and validated using bioinformatics pipelines in different datasets. Findings: Findings indicate that hMENA11a in NSCLC cells upregulates the TLS regulator LTβR, decreases fibronectin, and favors CXCL13 production by TRM. Conversely, hMENAΔv6 in CAFs inhibits LTβR-related NF-kB pathway, reduces CXCL13 secretion, and promotes fibronectin production. These patterns are validated in N0 NSCLC tumors, where hMENA11ahigh expression, CAF hMENAΔv6low, and stromal fibronectinlow are associated with intratumoral TLS, linked to memory B cells and predictive of longer survival. The hMENA isoform pattern, fibronectin, and LTβR expression broadly predict ICB response in tumors where TLS indicates an anti-tumor immune response. Interpretation: This study uncovers hMENA alternative splicing as an unexplored contributor to TLS-related Tumor Immune Microenvironment (TIME) and a promising biomarker for clinical outcomes and likely ICB responsiveness in N0 patients with NSCLC. Funding: This work is supported by AIRC (IG 19822), ACC (RCR-2019-23669120), CAL.HUB.RIA Ministero Salute PNRR-POS T4, “Ricerca Corrente” granted by the Italian Ministry of Health.

Abstract Species distribution models (SDMs) are a useful mean to understand how environmental variation influences species geographical distribution. SDMs are implemented by several different algorithms. Unfortunately, these algorithms consistently lose accuracy exactly when they are needed the most, that is with rare species, originating the so‐called rare‐species modelling paradox. Although approaches exist to tackle this problem, most notably by performing and then averaging a number of bivariate models, they are usually computationally intensive and were never shown to apply successfully to the rarest species (i.e. with less than 20 geographical occurrences). Here, we present a new algorithm, ENphylo, embedded in the readily‐available R package RRdtn, which couples Environmental Niche Factor Analysis (ENFA) and phylogenetic imputation to model the distribution of rare species. Using the fossil record of 31 species of large mammals that lived during the late Pleistocene as the source data to sample from, we demonstrate ENphylo provides good SDM evaluation scores, with area under the curve and Sørensen Index both consistently above 0.75, True Skills Statistics above 0.4 and Boyce Index above 0.5 in most cases, when just 10 fossil occurrences are randomly drawn from their respective fossil records. ENphylo proved significantly more accurate than ENFA and the ensemble of bivariate models using Maxent, Generalized Linear Model and Random Forest algorithms. Intriguingly, we found that randomly drawing as little as 10 occurrence data points per species allows ENphylo to perform equally well as Maxent run using the entire fossil record of these same species and data. ENphylo provides a fast and accurate solution to perform species distribution modelling with rare species, which will help predicting their distribution in the light of climate change, and to delineate how rare extinct species reacted to past climatic variation.

Abstract The manipulation of carbon nitride (CN) structures is one main avenue to enhance the activity of CN‐based photocatalysts. Increasing the efficiency of photocatalytic heterogeneous materials is a critical step toward the realistic implementation of sustainable schemes for organic synthesis. However, limited knowledge of the structure/activity relationship in relation to subtle structural variations prevents a fully rational design of new photocatalytic materials, limiting practical applications. Here, the CN structure is engineered by means of a microwave treatment, and the structure of the material is shaped around its suitable functionality for Ni dual photocatalysis, with a resulting boosting of the reaction efficiency toward many CX (X = N, S, O) couplings. The combination of advanced characterization techniques and first‐principle simulations reveals that this enhanced reactivity is due to the formation of carbon vacancies that evolve into triazole and imine N species able to suitably bind Ni complexes and harness highly efficient dual catalysis. The cost‐effective microwave treatment proposed here appears as a versatile and sustainable approach to the design of CN‐based photocatalysts for a wide range of industrially relevant organic synthetic reactions.

Pigments of fungal origin have aroused increasing interest in the food dye and cosmetic industries since the global demand for natural dyes has grown. Endophytic microorganisms are a source of bioactive compounds, and Amazonian plant species can harbor fungi with a wide range of biotechnological applications. Popularly known in Brazil as crajiru, Fridericia chica is a medicinal plant that produces a red pigment. In this study, a total of 121 fungi were isolated in potato dextrose agar from three plants. We identified nine pigment-producing endophytic fungi isolated from branches and leaves of F. chica. The isolates that showed pigment production in solid media were molecularly identified via multilocus analysis as Aspergillus welwitschiae, A. sydowii, Curvularia sp., Diaporthe cerradensis (two strains), Hypoxylon investiens, Neoscytalidium sp. (two strains) and Penicillium rubens. These isolates were subjected to submerged fermentation in two culture media to obtain metabolic extracts. The extracts obtained were analyzed in terms of their absorbance between 400 and 700 nm. The pigmented extract produced by H. investiens in medium containing yeast extract showed maximum absorbance in the red absorption range (UA700 = 0.550) and significant antioxidant and antimicrobial activity. This isolate can thus be considered a new source of extracellular pigment.

Polyelectrolytes can electrophoretically be driven through nanopores in order to be detected. The respective translocation events are often very fast and the process needs to be controlled to promote efficient detection. To this end, we attempt to control the translocation dynamics by coating the inner surface of a nanopore. For this, different charge distributions are chosen that result in substantial variations of the pore–polymer interactions. In addition and in view of the existing detection modalities, experimental settings, and nanopore materials, different types of sensors inside the nanopore have been considered to probe the translocation process and its temporal spread. The respective transport of polyelectrolytes through the coated nanopores is modeled through a multi-physics computational scheme that incorporates a mesoscopic/electrokinetic description for the solvent and particle-based scheme for the polymer. This investigation could underline the interplay between sensing modality, nanopore material, and detection accuracy. The electro-osmotic flow and electrophoretic motion in a pore are analyzed together with the polymeric temporal and spatial fluctuations unraveling their correlations and pathways to optimize the translocation speed and dynamics. Accordingly, this work sketches pathways in order to tune the pore–polymer interactions in order to control the translocation dynamics and, in the long run, errors in their measurements. [ABSTRACT FROM AUTHOR]

Cecropia sp. (Urticaceae) are commonly used in traditional medicine in South American countries for the treatment of different diseases. To date, the species Cecropia concolor Willd, of Amazonian occurrence, has not been investigated for its pharmacological potential. In this study, we described the chemical profile and the antileishmanial, antioxidant and cytotoxic activities of extracts of the leaves of C. concolor. The ethanolic extract and its partition phases (hexane, ethyl acetate and hydroethanolic) were analyzed for their chemical classes and phenolic content. Antileishmanial activity was assessed against Leishmania (L.) amazonensis. The antioxidant activity was evaluated using the DPPH method and in MRC-5 human fibroblast cells. Toxicity was tested against Artemia salina and in human cells (fibroblasts and cancer lines). The leaves of C. concolor have phenolic substances, such as flavonoids, as well as terpenes, steroids and alkaloids. Chlorogenic acid, caffeic acid, schaftoside and vicenin 2 were identified. The hydroethanolic phase showed a high concentration of phenolic compounds and pronounced antioxidant activity. The antileishmanial activity was observed in the ethanolic extract, with a promising effect of the hexane phase. The C. concolor ethanolic extract and its phases are non-toxic, which makes this species of interest in pharmaceutical and cosmetics applications. [ABSTRACT FROM AUTHOR]

The demand for biodiesel worldwide is skyrocketing as the need to replace fossil diesel with renewable energy sources becomes increasingly pressing. In this context, biocatalysis is emerging as an environmentally friendly and highly efficient alternative to chemical catalysis. When combined with the utilization of waste materials, it has the potential to make the process of biodiesel production sustainable. In the study, the potential of an extract rich in lipase produced by an Amazonian endophytic fungus as a biocatalyst in the transesterification of waste cooking oil for biodiesel production has been systematically investigated. The fungus Endomelanconiopsis endophytica exhibited an enzyme production of 11,262 U/mL after 120 h of cultivation. The lipolytic extract demonstrated its highest catalytic activity at 40 °C and a pH of 5.5. Using soybean oil and frying residue as raw materials, biodiesel was produced through biocatalytic transesterification, and yields of 91% and 89% (wt.), respectively, were achieved. By evaluating the process parameters, a maximum biodiesel yield of 90% was achieved using ethanol at a ratio of 3:1 ratio within 120 min. The experimental results demonstrate the feasibility and sustainability of applying a fungal enzymatic extract as a biocatalyst in the production of ethyl esters using waste cooking oil as a raw material.