Cristian Salinas

Bio: Cristian Salinas is an academic researcher from Edith Cowan University. The author has contributed to research in topics: Blue carbon & Seagrass. The author has an hindex of 3, co-authored 10 publications receiving 1440 citations. Previous affiliations of Cristian Salinas include University of Los Andes.

Australian vegetated coastal ecosystems as global hotspots for climate change mitigation

Abstract: Policies aiming to preserve vegetated coastal ecosystems (VCE; tidal marshes, mangroves and seagrasses) to mitigate greenhouse gas emissions require national assessments of blue carbon resources. Here, we present organic carbon (C) storage in VCE across Australian climate regions and estimate potential annual CO2 emission benefits of VCE conservation and restoration. Australia contributes 5–11% of the C stored in VCE globally (70–185 Tg C in aboveground biomass, and 1,055–1,540 Tg C in the upper 1 m of soils). Potential CO2 emissions from current VCE losses are estimated at 2.1–3.1 Tg CO2-e yr-1, increasing annual CO2 emissions from land use change in Australia by 12–21%. This assessment, the most comprehensive for any nation to-date, demonstrates the potential of conservation and restoration of VCE to underpin national policy development for reducing greenhouse gas emissions. Policies aiming to preserve vegetated coastal ecosystems (VCE) to mitigate greenhouse gas emissions require national assessments of blue carbon resources. Here the authors assessed organic carbon storage in VCE across Australian and the potential annual CO2 emission benefits of VCE conservation and find that Australia contributes substantially the carbon stored in VCE globally.

Seagrass losses since mid-20th century fuelled CO2 emissions from soil carbon stocks.

Abstract: Seagrass meadows store globally significant organic carbon (C-org) stocks which, if disturbed, can lead to CO2 emissions, contributing to climate change. Eutrophication and thermal stress continue to be a major cause of seagrass decline worldwide, but the associated CO2 emissions remain poorly understood. This study presents comprehensive estimates of seagrass soil C-org erosion following eutrophication-driven seagrass loss in Cockburn Sound (23 km(2) between 1960s and 1990s) and identifies the main drivers. We estimate that shallow seagrass meadows ( 5 m), however, soil C-org stocks in seagrass and bare but previously vegetated areas were not significantly different (2.6 +/- 0.3 and 3.0 +/- 0.6 kg C-org/m(2), respectively), The soil C-org sequestration capacity prevailed in shallow and deep vegetated areas (55 +/- 11 and 21 +/- 7 g C-org m(-2) year(-1), respectively), but was lost in bare areas. We identified that seagrass canopy loss alone does not necessarily drive changes in soil C-org but, when combined with high hydrodynamic energy, significant erosion occurred. Our estimates point at similar to 0.20 m/s as the critical shear velocity threshold causing soil C-org erosion. We estimate, from field studies and satellite imagery, that soil C-org erosion (within the top 50 cm) following seagrass loss likely resulted in cumulative emissions of 0.06-0.14 Tg CO2-eq over the last 40 years in Cockburn Sound. We estimated that indirect impacts (i.e. eutrophication, thermal stress and light stress) causing the loss of similar to 161,150 ha of seagrasses in Australia, likely resulted in the release of 11-21 Tg CO2-eq since the 1950s, increasing cumulative CO2 emissions from land-use change in Australia by 1.1%-2.3% per annum. The patterns described serve as a baseline to estimate potential CO2 emissions following disturbance of seagrass meadows.

Factors determining seagrass Blue Carbon across bioregions and geomorphologies

Abstract: Seagrass meadows rank among the most significant organic carbon (C) sinks on earth. We examined the variability in seagrass soil C stocks and composition across Australia and identified the main drivers of variability, applying a spatially hierarchical approach that incorporates bioregions and geomorphic settings. Top 30 cm soil C stocks were similar across bioregions and geomorphic settings (min-max: 20–26 Mg C ha), but meadows formed by large species (i.e., Amphibolis spp. and Posidonia spp.) showed higher stocks (24–29 Mg C ha) than those formed by smaller species (e.g., Halodule, Halophila, Ruppia, Zostera, Cymodocea, and Syringodium; 12–21 Mg C ha). In temperate coastal meadows dominated by large species, soil C stocks mainly derived from seagrass C (72 ± 2%), while allochthonous C dominated soil C stocks in meadows formed by small species in temperate and tropical estuarine meadows (64 ± 5%). In temperate coastal meadows, soil C stocks were enhanced by low hydrodynamic exposure associated with high mud and seagrass C contents. In temperate estuarine meadows, soil C stocks were enhanced by high contributions of seagrass C, low to moderate solar radiation, and low human pressure. In tropical estuarine meadows formed by small species, large soil C stocks were mainly associated with low hydrodynamic energy, low rainfall, and high solar radiation. These results showcase that bioregion and geomorphic setting are not necessarily good predictors of soil C stocks and that site-specific estimates based on local environmental factors are needed for Blue Carbon projects and greenhouse gases accounting purposes.

Soil Carbon Stocks Vary Across Geomorphic Settings in Australian Temperate Tidal Marsh Ecosystems

Abstract: Tidal marshes rank among the ecosystems with the highest capacity to sequester and store organic carbon (Corg) on earth To inform conservation of coastal vegetated ecosystems for climate change mitigation, this study investigated the factors driving variability in carbon storage We estimated soil Corg stocks in tidal marshes across temperate Western Australia and assessed differences among geomorphic settings (marine and fluvial deltas, and mid-estuary) and vegetation type (Sarcocornia quinqueflora and Juncus kraussii) linked to soil biogeochemistry Soil Corg stocks within fluvial and mid-estuary settings were significantly higher (209 ± 14 and 211 ± 20 Mg Corg ha−1, respectively; 1-m-thick soils) than in marine counterparts (156 ± 12 Mg Corg ha−1), which can be partially explained by higher preservation of soil Corg in fluvial and mid-estuary settings rich in fine-grained (< 0063 mm) sediments (49 ± 3% and 47 ± 4%, respectively) compared to marine settings (23 ± 4%) Soil Corg stocks were not significantly different between S quinqueflora and J kraussii marshes (185 ± 13 and 202 ± 13 Mg Corg ha−1, respectively) The higher contribution of tidal marsh plus supratidal vegetation in fluvial (80%) and intermediate (76%) compared to marine (57%) settings further explains differences in soil Corg stocks The estimated soil Corg stocks in temperate Western Australia’s tidal marshes (57 Tg Corg within ~ 3000 km2 extent) correspond to about 2% of worldwide tidal marsh soil Corg stocks The results obtained identify global drivers of soil Corg storage in tidal marshes and can be used to target hot spots for climate change mitigation based on tidal marsh conservation

"Pig in a poke (gato por liebre)": the "mota" (Calophysus macropterus) fishery, molecular evidence of commercialization in Colombia and toxicological analyses.

Abstract: Overfishing has affected the population abundance trends of many commercial fish species. In the Amazon, the fishery of a catfish commonly known as “mota” or “piracatinga” (Calophysus macropterus) has become an important economic activity in the region as this species has replaced a number of other overexploited great catfish species in the markets. Due to this high exploitation, ways in which to increase captures have been identified. One strategy is to use decomposing animal carcasses as bait. Such strategy has increased the hunting pressure on endangered species such as caimans and river dolphins. We investigated which catfish species are currently commercialized in Colombian fish markets using DNA barcoding, and measured mercury concentration in the tissues of fish molecularly identified as C. macropterus. We collected 86 fish samples in markets of four Colombian cities. Sixty-eight of these were identified molecularly as C.macropterus. The mercury concentration of 29 such samples was analyzed. Samples presented total Hg concentrations higher than the limit for human consumption established by the WHO (0.5 μg/g). These results are worrisome and suggest that (1) C. macropterus is a widely used fish species for human consumption in Colombia and (2) C. macropterus has high concentrations of total Hg, making its consumption a public health risk. Results presented here suggest that C. macropterus has replaced capaz in most Colombian markets. This fishery threatens wild species of river dolphins and caimans, and is also a public health risk given the high mercury levels we found in a subsample of these fishes.

Advances in oligonucleotide drug delivery

Abstract: Oligonucleotides can be used to modulate gene expression via a range of processes including RNAi, target degradation by RNase H-mediated cleavage, splicing modulation, non-coding RNA inhibition, gene activation and programmed gene editing. As such, these molecules have potential therapeutic applications for myriad indications, with several oligonucleotide drugs recently gaining approval. However, despite recent technological advances, achieving efficient oligonucleotide delivery, particularly to extrahepatic tissues, remains a major translational limitation. Here, we provide an overview of oligonucleotide-based drug platforms, focusing on key approaches - including chemical modification, bioconjugation and the use of nanocarriers - which aim to address the delivery challenge.

Genetics of diabetes mellitus and diabetes complications.

Abstract: Diabetes is one of the fastest growing diseases worldwide, projected to affect 693 million adults by 2045. Devastating macrovascular complications (cardiovascular disease) and microvascular complications (such as diabetic kidney disease, diabetic retinopathy and neuropathy) lead to increased mortality, blindness, kidney failure and an overall decreased quality of life in individuals with diabetes. Clinical risk factors and glycaemic control alone cannot predict the development of vascular complications; numerous genetic studies have demonstrated a clear genetic component to both diabetes and its complications. Early research aimed at identifying genetic determinants of diabetes complications relied on familial linkage analysis suited to strong-effect loci, candidate gene studies prone to false positives, and underpowered genome-wide association studies limited by sample size. The explosion of new genomic datasets, both in terms of biobanks and aggregation of worldwide cohorts, has more than doubled the number of genetic discoveries for both diabetes and diabetes complications. We focus herein on genetic discoveries for diabetes and diabetes complications, empowered primarily through genome-wide association studies, and emphasize the gaps in research for taking genomic discovery to the next level.

Hybrid threshold adaptable quantum secret sharing scheme with reverse Huffman-Fibonacci-tree coding

Abstract: With prevalent attacks in communication, sharing a secret between communicating parties is an ongoing challenge. Moreover, it is important to integrate quantum solutions with classical secret sharing schemes with low computational cost for the real world use. This paper proposes a novel hybrid threshold adaptable quantum secret sharing scheme, using an m-bonacci orbital angular momentum (OAM) pump, Lagrange interpolation polynomials, and reverse Huffman-Fibonacci-tree coding. To be exact, we employ entangled states prepared by m -bonacci sequences to detect eavesdropping. Meanwhile, we encode m -bonacci sequences in Lagrange interpolation polynomials to generate the shares of a secret with reverse Huffman-Fibonacci-tree coding. The advantages of the proposed scheme is that it can detect eavesdropping without joint quantum operations, and permits secret sharing for an arbitrary but no less than threshold-value number of classical participants with much lower bandwidth. Also, in comparison with existing quantum secret sharing schemes, it still works when there are dynamic changes, such as the unavailability of some quantum channel, the arrival of new participants and the departure of participants. Finally, we provide security analysis of the new hybrid quantum secret sharing scheme and discuss its useful features for modern applications.

Tunable nanophotonics enabled by chalcogenide phase-change materials

Abstract: Nanophotonics has garnered intensive attention due to its unique capabilities in molding the flow of light in the subwavelength regime. Metasurfaces (MSs) and photonic integrated circuits (PICs) enable the realization of mass-producible, cost-effective, and highly efficient flat optical components for imaging, sensing, and communications. In order to enable nanophotonics with multi-purpose functionalities, chalcogenide phase-change materials (PCMs) have been introduced as a promising platform for tunable and reconfigurable nanophotonic frameworks. Integration of non-volatile chalcogenide PCMs with unique properties such as drastic optical contrasts, fast switching speeds, and long-term stability grants substantial reconfiguration to the more conventional static nanophotonic platforms. In this review, we discuss state-of-the-art developments as well as emerging trends in tunable MSs and PICs using chalcogenide PCMs. We outline the unique material properties, structural transformation, electro-optic, and thermo-optic effects of well-established classes of chalcogenide PCMs. The emerging deep learning-based approaches for the optimization of reconfigurable MSs and the analysis of light-matter interactions are also discussed. The review is concluded by discussing existing challenges in the realization of adjustable nanophotonics and a perspective on the possible developments in this promising area.

Topaz-Denoise: general deep denoising models for cryoEM and cryoET.

Abstract: Cryo-electron microscopy (cryoEM) is becoming the preferred method for resolving protein structures. Low signal-to-noise ratio (SNR) in cryoEM images reduces the confidence and throughput of structure determination during several steps of data processing, resulting in impediments such as missing particle orientations. Denoising cryoEM images can not only improve downstream analysis but also accelerate the time-consuming data collection process by allowing lower electron dose micrographs to be used for analysis. Here, we present Topaz-Denoise, a deep learning method for reliably and rapidly increasing the SNR of cryoEM images and cryoET tomograms. By training on a dataset composed of thousands of micrographs collected across a wide range of imaging conditions, we are able to learn models capturing the complexity of the cryoEM image formation process. The general model we present is able to denoise new datasets without additional training. Denoising with this model improves micrograph interpretability and allows us to solve 3D single particle structures of clustered protocadherin, an elongated particle with previously elusive views. We then show that low dose collection, enabled by Topaz-Denoise, improves downstream analysis in addition to reducing data collection time. We also present a general 3D denoising model for cryoET. Topaz-Denoise and pre-trained general models are now included in Topaz. We expect that Topaz-Denoise will be of broad utility to the cryoEM community for improving micrograph and tomogram interpretability and accelerating analysis. The low signal-to-noise ratio (SNR) in cryoEM images can make the first steps in cryoEM structure determination challenging, particularly for non-globular and small proteins. Here, the authors present Topaz-Denoise, a deep learning based method for micrograph denoising that significantly increases the SNR of cryoEM images and cryoET tomograms, which helps to accelerate the cryoEM pipeline.