A review of the ecological value of Cusuco National Park an urgent call forconservation action in a highly threatened Mesoamerican cloud forest

Cloud forests are amongst the most biologically unique, yet threatened, ecosystems in Mesoamerica. We summarize the ecological value and conservation status of a well-studied cloud forest site: Cusuco National Park (CNP), a 23,440 ha protected area in the Merendón mountains, northwest Honduras. We show CNP to have exceptional biodiversity; of 966 taxa identified to a species-level to date, 362 (37.5%) are Mesoamerican endemics, 67 are red-listed by the IUCN, and at least 49 are micro-endemics known only from the Merendón range. CNP also provides key ecosystem services including provision of drinking water and downstream flood mitigation, as well as carbon sequestration, with an estimated stock of 3.5 million megagrams of carbon in 2000. Despite its ecological importance, CNP faces multiple environmental threats and associated stresses, including deforestation (1,759 ha since 2000 equating to 7% of total forest area), poaching (7% loss of mammal relative abundance per year), amphibian declines due to chytridiomycosis (70% of species threatened or near-threatened), and climate change (a mean 2.6 °C increase in temperature and 112 mm decrease in rainfall by 2100). Despite conservation actions, including community ranger patrols, captive-breeding programmes, and ecotourism initiatives, environmental degradation of CNP continues. Further action is urgently required, including reinforcement and expansion of ranger programmes, greater stakeholder engagement, community education programmes, development of alternative livelihood projects, and legislative enforcement and prosecution. Without a thorough and rapid response to understand and mitigate illegal activities, the extirpation and extinction of species and the loss of vital ecosystem services are inevitable in the coming decades

Discovery of drug-omics associations in type 2 diabetes with generative deep-learning models.

The application of multiple omics technologies in biomedical cohorts has the potential to reveal patient-level disease characteristics and individualized response to treatment. However, the scale and heterogeneous nature of multi-modal data makes integration and inference a non-trivial task. We developed a deep-learning-based framework, multi-omics variational autoencoders (MOVE), to integrate such data and applied it to a cohort of 789 people with newly diagnosed type 2 diabetes with deep multi-omics phenotyping from the DIRECT consortium. Using in silico perturbations, we identified drug-omics associations across the multi-modal datasets for the 20 most prevalent drugs given to people with type 2 diabetes with substantially higher sensitivity than univariate statistical tests. From these, we among others, identified novel associations between metformin and the gut microbiota as well as opposite molecular responses for the two statins, simvastatin and atorvastatin. We used the associations to quantify drug-drug similarities, assess the degree of polypharmacy and conclude that drug effects are distributed across the multi-omics modalities. [Abstract copyright: © 2023. The Author(s).

Genomic analysis of two phlebotomine sand fly vectors of Leishmania from the New and Old World.

Phlebotomine sand flies are of global significance as important vectors of human disease, transmitting bacterial, viral, and protozoan pathogens, including the kinetoplastid parasites of the genus Leishmania, the causative agents of devastating diseases collectively termed leishmaniasis. More than 40 pathogenic Leishmania species are transmitted to humans by approximately 35 sand fly species in 98 countries with hundreds of millions of people at risk around the world. No approved efficacious vaccine exists for leishmaniasis and available therapeutic drugs are either toxic and/or expensive, or the parasites are becoming resistant to the more recently developed drugs. Therefore, sand fly and/or reservoir control are currently the most effective strategies to break transmission. To better understand the biology of sand flies, including the mechanisms involved in their vectorial capacity, insecticide resistance, and population structures we sequenced the genomes of two geographically widespread and important sand fly vector species: Phlebotomus papatasi, a vector of Leishmania parasites that cause cutaneous leishmaniasis, (distributed in Europe, the Middle East and North Africa) and Lutzomyia longipalpis, a vector of Leishmania parasites that cause visceral leishmaniasis (distributed across Central and South America). We categorized and curated genes involved in processes important to their roles as disease vectors, including chemosensation, blood feeding, circadian rhythm, immunity, and detoxification, as well as mobile genetic elements. We also defined gene orthology and observed micro-synteny among the genomes. Finally, we present the genetic diversity and population structure of these species in their respective geographical areas. These genomes will be a foundation on which to base future efforts to prevent vector-borne transmission of Leishmania parasites

Assessment of plasma chitotriosidase activity, CCL18/PARC concentration and NP-C suspicion index in the diagnosis of Niemann-Pick disease type C: A prospective observational study

Background: Niemann-Pick disease type C (NP-C) is a rare, autosomal recessive neurodegenerative disease caused by mutations in either the NPC1 or NPC2 genes. The diagnosis of NP-C remains challenging due to the non-specific, heterogeneous nature of signs/symptoms. This study assessed the utility of plasma chitotriosidase (ChT) and Chemokine (C-C motif) ligand 18 (CCL18)/pulmonary and activation-regulated chemokine (PARC) in conjunction with the NP-C suspicion index (NP-C SI) for guiding confirmatory laboratory testing in patients with suspected NP-C. Methods: In a prospective observational cohort study, incorporating a retrospective determination of NP-C SI scores, two different diagnostic approaches were applied in two separate groups of unrelated patients from 51 Spanish medical centers (n = 118 in both groups). From Jan 2010 to Apr 2012 (Period 1), patients with =2 clinical signs/symptoms of NP-C were considered ''suspected NP-C'' cases, and NPC1/NPC2 sequencing, plasma chitotriosidase (ChT), CCL18/PARC and sphingomyelinase levels were assessed. Based on findings in Period 1, plasma ChT and CCL18/PARC, and NP-C SI prediction scores were determined in a second group of patients between May 2012 and Apr 2014 (Period 2), and NPC1 and NPC2 were sequenced only in those with elevated ChT and/or elevated CCL18/PARC and/or NP-C SI =70. Filipin staining and 7-ketocholesterol (7-KC) measurements were performed in all patients with NP-C gene mutations, where possible. Results: In total across Periods 1 and 2, 10/236 (4%) patients had a confirmed diagnosis o NP-C based on gene sequencing (5/118 4.2%] in each Period): all of these patients had two causal NPC1 mutations. Single mutant NPC1 alleles were detected in 8/236 (3%) patients, overall. Positive filipin staining results comprised three classical and five variant biochemical phenotypes. No NPC2 mutations were detected. All patients with NPC1 mutations had high ChT activity, high CCL18/PARC concentrations and/or NP-C SI scores =70. Plasma 7-KC was higher than control cut-off values in all patients with two NPC1 mutations, and in the majority of patients with single mutations. Family studies identified three further NP-C patients. Conclusion: This approach may be very useful for laboratories that do not have mass spectrometry facilities and therefore, they cannot use other NP-C biomarkers for diagnosis

Genetic Sharing with Cardiovascular Disease Risk Factors and Diabetes Reveals Novel Bone Mineral Density Loci.

Bone Mineral Density (BMD) is a highly heritable trait, but genome-wide association studies have identified few genetic risk factors. Epidemiological studies suggest associations between BMD and several traits and diseases, but the nature of the suggestive comorbidity is still unknown. We used a novel genetic pleiotropy-informed conditional False Discovery Rate (FDR) method to identify single nucleotide polymorphisms (SNPs) associated with BMD by leveraging cardiovascular disease (CVD) associated disorders and metabolic traits. By conditioning on SNPs associated with the CVD-related phenotypes, type 1 diabetes, type 2 diabetes, systolic blood pressure, diastolic blood pressure, high density lipoprotein, low density lipoprotein, triglycerides and waist hip ratio, we identified 65 novel independent BMD loci (26 with femoral neck BMD and 47 with lumbar spine BMD) at conditional FDR < 0.01. Many of the loci were confirmed in genetic expression studies. Genes validated at the mRNA levels were characteristic for the osteoblast/osteocyte lineage, Wnt signaling pathway and bone metabolism. The results provide new insight into genetic mechanisms of variability in BMD, and a better understanding of the genetic underpinnings of clinical comorbidity

Repositioning of the global epicentre of non-optimal cholesterol

High blood cholesterol is typically considered a feature of wealthy western countries1,2. However, dietary and behavioural determinants of blood cholesterol are changing rapidly throughout the world3 and countries are using lipid-lowering medications at varying rates. These changes can have distinct effects on the levels of high-density lipoprotein (HDL) cholesterol and non-HDL cholesterol, which have different effects on human health4,5. However, the trends of HDL and non-HDL cholesterol levels over time have not been previously reported in a global analysis. Here we pooled 1,127 population-based studies that measured blood lipids in 102.6 million individuals aged 18 years and older to estimate trends from 1980 to 2018 in mean total, non-HDL and HDL cholesterol levels for 200 countries. Globally, there was little change in total or non-HDL cholesterol from 1980 to 2018. This was a net effect of increases in low- and middle-income countries, especially in east and southeast Asia, and decreases in high-income western countries, especially those in northwestern Europe, and in central and eastern Europe. As a result, countries with the highest level of non-HDL cholesterol—which is a marker of cardiovascular risk—changed from those in western Europe such as Belgium, Finland, Greenland, Iceland, Norway, Sweden, Switzerland and Malta in 1980 to those in Asia and the Pacific, such as Tokelau, Malaysia, The Philippines and Thailand. In 2017, high non-HDL cholesterol was responsible for an estimated 3.9 million (95% credible interval 3.7 million–4.2 million) worldwide deaths, half of which occurred in east, southeast and south Asia. The global repositioning of lipid-related risk, with non-optimal cholesterol shifting from a distinct feature of high-income countries in northwestern Europe, north America and Australasia to one that affects countries in east and southeast Asia and Oceania should motivate the use of population-based policies and personal interventions to improve nutrition and enhance access to treatment throughout the world.</p