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Neuropeptides are a group of neuronal signaling molecules that regulate physiological and behavioral processes in animals. Here, we used in silico mining to predict the polypeptide composition of available transcriptomic data of Turbinaria peltata. In total, 118 transcripts encoding putative peptide precursors were discovered. One neuropeptide Y/F-like peptide, named TpNPY, was identified and selected for in silico structural, in silico binding, and pharmacological studies. In our study, the anti-inflammation effect of TpNPY was evaluated using an LPS-stimulated C8-D1A astrocyte cell model. Our results demonstrated that TpNPY, at 0.75–3 μM, inhibited LPS-induced NO production and reduced the expression of iNOS in a dose-dependent manner. Furthermore, TpNPY reduced the secretion of proinflammatory cytokines. Additionally, treatment with TpNPY reduced LPS-mediated elevation of ROS production and the intracellular calcium concentration. Further investigation revealed that TpNPY downregulated the IKK/IκB/NF-κB signaling pathway and inhibited expression of the NLRP3 inflammasome. Through molecular docking and using an NPY receptor antagonist, TpNPY was shown to have the ability to interact with the NPY Y1 receptor. On the basis of these findings, we concluded that TpNPY might prevent LPS-induced injury in astrocytes through activation of the NPY-Y1R.

Ligand peptides that have high affinity for ion channels are critical for regulating ion flux across the plasma membrane. These peptides are now being considered as potential drug candidates for many diseases, such as cardiovascular disease and cancers. In this work, we developed Multi-Branch-CNN, a CNN method with multiple input branches for identifying three types of ion channel peptide binders (sodium, potassium, and calcium) from intra- and inter-feature types. As for its real-world applications, prediction models that are able to recognize novel sequences having high or low similarities to training sequences are required. To this end, we tested our models on two test sets: a general test set including sequences spanning different similarity levels to those of the training set, and a novel-test set consisting of only sequences that bear little resemblance to sequences from the training set. Our experiments showed that the Multi-Branch-CNN method performs better than thirteen traditional ML algorithms (TML13), yielding an improvement in accuracy of 3.2%, 1.2%, and 2.3% on the test sets as well as 8.8%, 14.3%, and 14.6% on the novel-test sets for sodium, potassium, and calcium ion channels, respectively. We confirmed the effectiveness of Multi-Branch-CNN by comparing it to the standard CNN method with one input branch (Single-Branch-CNN) and an ensemble method (TML13-Stack). The data sets, script files to reproduce the experiments, and the final predictive models are freely available at https://github.com/jieluyan/Multi-Branch-CNN.

Despite the levels of air pollution in Macao continuing to improve over recent years, there are still days with high-pollution episodes that cause great health concerns to the local community. Therefore, it is very important to accurately forecast air quality in Macao. Machine learning methods such as random forest (RF), gradient boosting (GB), support vector regression (SVR), and multiple linear regression (MLR) were applied to predict the levels of particulate matter (PM10 and PM2.5) concentrations in Macao. The forecast models were built and trained using the meteorological and air quality data from 2013 to 2018, and the air quality data from 2019 to 2021 were used for validation. Our results show that there is no significant difference between the performance of the four methods in predicting the air quality data for 2019 (before the COVID-19 pandemic) and 2021 (the new normal period). However, RF performed significantly better than the other methods for 2020 (amid the pandemic) with a higher coefficient of determination (R2) and lower RMSE, MAE, and BIAS. The reduced performance of the statistical MLR and other ML models was presumably due to the unprecedented low levels of PM10 and PM2.5 concentrations in 2020. Therefore, this study suggests that RF is the most reliable prediction method for pollutant concentrations, especially in the event of drastic air quality changes due to unexpected circumstances, such as a lockdown caused by a widespread infectious disease.

Microbial and hydrothermal venting activities on the seafloor are important for the formation of sediment-hosted stratiform sulfide (SHSS) deposits. Fe isotopic compositions are sensitive to both microbial and hydrothermal activities and may be used to investigate the formation of these deposits. However, to the best of our knowledge, no Fe isotopic studies have been conducted on SHSS deposits. In the Devonian Dajiangping SHSS-type pyrite deposit (389 Ma), South China, laminated pyrite ores were precipitated from exhalative hydrothermal fluids, whereas black shales were deposited during intervals with no exhalation. Pyrite grains from black shales mostly display positive δ56Fe-py (0.01–0.73‰), higher than marine sediments (ca. 0‰), due to pyrite deriving Fe from basinal shuttled Fe(III) (hydr-)oxides and slowly crystallizing in pores of sediments with equilibrium fractionation, except for negative δ56Fe-py (−0.17‰ to −0.24‰) of two samples caused by mixing of Fe from underlain laminated ores. The positive δ34S-py (3.50–24.5‰) of black shales reflect that sulfur of pyrite originated from quantitative reduction of sulfate in closed pores of sediments. In contrast, pyrite grains of laminated ores have negative δ56Fe-py (−0.60‰ to −0.21‰), which were not only inherited from the negative δ56Fe of hydrothermal fluids but also caused by kinetic fractionation during rapid precipitation of a pyrite precursor (FeS) in hydrothermal plumes. These ores have negative δ34S-py (−28.7‰ to −1.82‰), because H2S for pyrite mineralization was produced by bacterial sulfate reduction (BSR) in a sulfate-rich seawater column or shallow sediments. The δ56Fe-py values of laminated ores co-vary positively with δ34S-py and δ13C-carbonate along the ore stratigraphy, with δ13C-carbonate values ranging from −12.0‰ to −2.50‰. However, they correlate negatively with aluminum-normalized total organic carbon (TOC/Al2O3). Organic carbon is thus considered to enhance the production of H2S by BSR activities, increase pyrite precipitation rates and promote the expression of kinetic fractionation of Fe isotopes. Intriguingly, in the ore units with vigorous hydrothermal venting activities, δ56Fe-py, δ34S-py and δ13C-carbonate values display a consistently increasing trend. Such results suggest that venting hydrothermal fluids significantly inhibited the H2S production of BSR, which then reduced the pyrite crystallization rate and decreased the kinetic fractionation of Fe isotopes. Our study reveals that the formation of SHSS deposits relies on H2S from microbial activities and metals from hydrothermal exhalation on the seafloor, but that vigorous exhalation can inhibit microbial activities and thus sulfide precipitation rates. The integrated use of Fe, S, and C isotopes can effectively elucidate these dynamic interactions between hydrothermal venting and microbial activities during the formation of SHSS deposits.

The Qiyugou gold deposit, located in the Xiong’ ershan area of the North China Craton, contains abundant bismuth-sulfosalts that are closely associated with gold mineralization. Pyrite is the dominant Au-hosted mineral, and has been formed in three generations (Py1, Py2, and Py3). Py1 grains, generally intergrown with milky quartz, are coarse (>1 mm), euhedral in shape, and Au-depleted in composition. In contrast, subhedral Py2 grains, associated with light gray quartz, are medium to coarse (0.2–3 mm) and are enriched in gold that is both invisible and visible. Py3 grains (0.1–0.5 mm), intergrown with abundant sulfide minerals, are relatively fine and Au-depleted. The time-resolved LA-ICP-MS depth profiles of the Py2 grains indicate that invisible gold occurs as either solid solution or nano-particles of native gold and electrum. Visible gold occurs as small blebs in the Py2 grains where inclusions of native bismuth, galenobismutite, lillianite homologs, tetradymite, and galena are also present. In addition, it is common that electrum in microfracture infillings or along grain boundaries of the Py1 and Py2, are intergrown with bismuthinite derivatives, Bi-Cu sulfosalts, emplectite, tetradymite, chalcopyrite, galena, and Py3. Based on textural relationships and mineral assemblages, calculation of physicochemical conditions show that gold was formed in conditions of fTe2 = ~10−11 and fS2 = ~10−11 to 10−12 for Py2, and fTe2 = ~10−9 to 10-11and fS2 = ~10−10 to 10−11 for Py3. We thus proposed that such physicochemical conditions may have triggered the precipitation of Bi melt, and sulfidation driven by cooling or increase in sulfur content results in the transformation of the Au-Bi liquid into a stable assemblage of native gold and bismuthinite. These bismuth minerals are associated with native gold/Au-bearing minerals, indicating that the Au mineralization of the Qiyugou gold deposit might be genetically associated with Bi melt. The present study highlights the role of Bi as important gold scavengers in arsenic-deficient ore-forming fluid.

Seafloor massive sulfide (SMS) deposits are important deep-sea mineral resources expected to occur predominantly on slow- and ultraslow-spreading mid-ocean ridges. Resource estimates are already available for some of the largest SMS deposits on slow-spreading ridges but not on ultraslow-spreading ridges. Based on geological mapping and sampling, this study investigates the distribution and content of sulfide-rich deposits in the Yuhuang-1 hydrothermal field (YHF), located on the ultraslow-spreading Southwest Indian Ridge. The sulfide-rich deposits in the YHF are composed of two areas ∼500 m apart: the southwest sulfide area (SWS) and the northeast sulfide area (NES). We calculated the volume of sulfide-rich mounds in the YHF and arrived at a total accumulation of ∼10.6 × 106 tons, including at least ∼7.5 × 105 tons of copper and zinc and ∼18 tons of gold. Furthermore, considering the coverage of layered hydrothermal sediment mixed with sulfide-rich breccias, which may have underlying massive sulfide deposits, the maximum total mass was estimated at ∼45.1 × 106 tons. This suggests that the YHF is one of the largest SMS deposits worldwide and confirm that ultraslow-spreading ridges have the greatest potential to form large-scale SMS deposits.

The widespread W-(Mo)-Sn-Nb-Ta polymetallic mineralization in Southeast (SE) China is genetically associated with Mesozoic highly fractionated granitic rocks. Such rocks have enigmatic mineralogical and geochemical features, making its petrogenesis an intensely debated topic. To better understand the underlying magma evolution processes, petrography, garnet chemistry and whole-rock major and trace element data are reported for Jurassic highly fractionated granitic rocks and associated microgranite and aplitepegmatite dikes from Macao and compared with coeval similar granitic rocks from nearby areas in SE China. Despite the fact that the most evolved rocks in Macao are garnet-bearing aplite-pegmatite dikes, the existence of coeval two-mica and garnet-bearing biotite and muscovite granites displaying more evolved compositions (e.g, lower Zr/Hf ratios) indicates that the differentiation sequence reached higher degrees of fractionation at a regional scale. Although crystal fractionation played an important role, late-stage fluid/melt interactions, involving F-rich fluids, imparted specific geochemical characteristics to Macao and SE China highly fractionated granitic rocks such as the non-CHARAC (CHArge-and-RAdius-Controlled) behavior of trace elements, leading, for example, to non-chondritic Zr/Hf ratios, Rare Earth Elements (REE) tetrad effects and Nb-Ta enrichment and fractionation. Such process contributed to the late-stage crystallization of accessory phases only found in these highly evolved facies. Among the latter, two populations of garnet were identified in MGI (Macao Group I) highly fractionated granitic rocks: small grossular-poor euhedral grains and large grossular-rich skeletal garnet grains with quartz inclusions. The first group was mainly formed through precipitation from highly evolved Mn-rich slightly peraluminous melts under low-pressure and relatively low temperature (∼700 °C) conditions. Assimilation of upper crust metasedimentary materials may have contributed as a source of Mn and Al to the formation of garnet. The second group has a metasomatic origin related to the interaction of magmatic fluids with previously crystallized mineral phases and, possibly, with assimilated metasedimentary enclaves or surrounding metasedimentary strata. The highly fractionated granitic rocks in Macao represent the first stage in the development of granite-related W-(Mo)-Sn-Nb-Ta mineralization associated with coeval more evolved lithotypes in SE China.

A 1:12,000 geological map of the Macao Special Administrative Region has been produced through detailed field work supported by petrographic, mineralogical, geochronological and geochemical data obtained in previous studies. This map aims to represent a reliable tool to understand the geological evolution of the region and for management of the territory. The geology of Macao is dominated by two groups of Jurassic granitic rocks belonging to an intrusive suite located along the coast of Southeast China: Macao Group I (MGI: 164.5 ± 0.6 to 162.9 ± 0.7 Ma) and Macao Group II (MGII: 156.6 ± 0.2 to 155.5 ± 0.8 Ma), including the associated microgranite, aplite and pegmatite dikes and quartz veins. Remnants of the metasedimentary wall-rock are present as Devonian xenoliths enclosed within the granites. Younger Jurassic to Cretaceous andesite to dacite dikes (150.6 ± 0.6 to <120 Ma) intrude the granitic rocks. Additionally, Quaternary sedimentary deposits cover the older lithologies.

Macao ( 30 Km2) is a territory characterized by small granitic intrusions, located along the coastal region of Southeast China (Cathaysia Block). Granitoids occur as different facies, including microgranite dykes, with distinct textural, mineralogical and geochemical features, for which a middle-upper Jurassic age ( 164 Ma) has been proposed. New data suggest that these granitoids are mostly high-K calc-alkaline metaluminous (A/CNK = 0.8 - 1.1) biotite granites, consistent with total absence of primary muscovite. They show variable amounts of SiO2 (67-77%), reflecting different degrees of magmatic evolution. There is also variability in terms of trace elements, particularly Rare Earth Elements (REEs), evidenced by decreasing (La/Sm)N, (Gd/Lu)N, (Ce/Yb)N and (Eu/Eu*)N towards the more evolved samples, which can be partly attributed to fractional crystallization processes. Most of the granitoids are characterized by (La/Yb)N = 3 - 10.8, showing negative Ba, Nb, Sr, Zr, P, Ti and Eu anomalies. On the other hand, microgranite dykes, along with a few more evolved granites, show an opposite tendency, being usually enriched in HREEs relatively to LREEs with (La/Yb)N = 0.4 - 1.1. Our data suggests intermediate genetic affinities between I-type and A-type granites. Although these granitoids are mostly metaluminous (characteristic of I-types), Ga/Al ratios, usually used to identify A-types, are close to the accepted boundary between A-type and other granite types. The affinities with A-type granites are more marked for the more evolved facies, which depict higher values of FeOt/MgO (14 - 60) and K2O/MgO (60 - 250). Their trace element characteristics are also transitional between WPG (Within-plate granites) and Syn-COLG (Collision Granites). We interpret those transitional characteristics (A/I and WPG/Syn-COLG) of Macao granitoids as reflecting an origin by melting of infracrustal sources over a period of high heat transfer from mantle to crust during an extensional tectonic setting probably contemporaneous with the subduction of the paleo-Pacific plate beneath the Eurasia, whose paleo-suture is thought to be located in the east flank of the Central Range, Taiwan.