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Abstract Background Observational studies have suggested an association between birth weight and type 2 diabetes mellitus, but the causality between them has not been established. We aimed to obtain the causal relationship between birth weight with T2DM and quantify the mediating effects of potential modifiable risk factors. Methods Two-step, two-sample Mendelian randomization (MR) techniques were applied using SNPs as genetic instruments for exposure and mediators. Summary data from genome-wide association studies (GWAS) for birth weight, T2DM, and a series of fatty acids traits and their ratios were leveraged. The inverse variance weighted (IVW) method was the main analysis approach. In addition, the heterogeneity test, horizontal pleiotropy test, Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) test, and leave-one-out analysis were carried out to assess the robustness. Results The IVW method showed that lower birth weight raised the risk of T2DM (β: −1.113, 95% CI: −1.573 ∼ −0.652). Two-step MR identified 4 of 17 candidate mediators partially mediating the effect of lower birth weight on T2DM, including ratio of polyunsaturated fatty acids to monounsaturated fatty acids (proportion mediated: 7.9%), ratio of polyunsaturated fatty acids to total fatty acids (7.2%), ratio of omega-6 fatty acids to total fatty acids (8.1%) and ratio of linoleic acid to total fatty acids ratio (6.0%). Conclusions Our findings supported a potentially causal effect of birth weight against T2DM with considerable mediation by modifiable risk factors. Interventions that target these factors have the potential to reduce the burden of T2DM attributable to low birth weight.

The conventional real-time screening in organs-on-chips is limited to optical tracking of pre-tagged cells and biological agents. This work introduces an efficient biofabrication protocol to integrate tunable hydrogel electrodes into 3D bioprinted-on-chips. We established our method of fabricating cell-laden hydrogel-based microfluidic chips through digital light processing-based 3D bioprinting. Our conductive ink includes poly-(3,4-ethylene-dioxythiophene)-polystyrene sulfonate (PEDOT: PSS) microparticles doped in polyethylene glycol diacrylate (PEGDA). We optimized the manufacturing process of PEDOT: PSS microparticles characterized our conductive ink for different 3D bioprinting parameters, geometries, and materials conditions. While the literature is limited to 0.5% w/v for PEDOT: PSS microparticle concentration, we increased their concentration to 5% w/v with superior biological responses. We measured the conductivity in the 3–15 m/m for a range of 0.5%–5% w/v microparticles, and we showed the effectiveness of 3D-printed electrodes for predicting cell responses when encapsulated in gelatin-methacryloyl (GelMA). Interestingly, a higher cellular activity was observed in the case of 5% w/v microparticles compared to 0.5% w/v microparticles. Electrochemical impedance spectroscopy measurements indicated significant differences in cell densities and spheroid sizes embedded in GelMA microtissues.

Abstract Developing high‐efficiency and stable bifunctional electrocatalysts for water splitting remains a great challenge. Herein, NiMoO4 nanowires as sacrificial templates to synthesize Mo‐doped NiFe Prussian blue analogs are employed, which can be easily phosphorized to Mo‐doped Fe2xNi2(1‐x)P nanotubes (Mo‐FeNiP NTs). This synthesis method enables the controlled etching of NiMoO4 nanowires that results in a unique hollow nanotube architecture. As a bifunctional catalyst, the Mo‐FeNiP NTs present lower overpotential and Tafel slope of 151.3 (232.6) mV at 100 mA cm−2 and 76.2 (64.7) mV dec−1 for HER (OER), respectively. Additionally, it only requires an ultralow cell voltage of 1.47 V to achieve 10 mA cm−2 for overall water splitting and can steadily operate for 200 h at 100 mA cm−2. First‐principles calculations demonstrate that Mo doping can effectively adjust the electron redistribution of the Ni hollow sites to optimize the hydrogen adsorption‐free energy for HER. Besides, in situ Raman characterization reveals the dissolving of doped Mo can promote a rapid surface reconstruction on Mo‐FeNiP NTs to dynamically stable (Fe)Ni‐oxyhydroxide layers, serving as the actual active species for OER. The work proposes a rational approach addressed by electron manipulation and surface reconstruction of bimetallic phosphides to regulate both the HER and OER activity.

Abstract Non-dissociative chemisorption solid-state storage of hydrogen molecules in host materials is promising to achieve both high hydrogen capacity and uptake rate, but there is the lack of non-dissociative hydrogen storage theories that can guide the rational design of the materials. Herein, we establish generalized design principle to design such materials via the first-principles calculations, theoretical analysis and focused experimental verifications of a series of heteroatom-doped-graphene-supported Ca single-atom carbon nanomaterials as efficient non-dissociative solid-state hydrogen storage materials. An intrinsic descriptor has been proposed to correlate the inherent properties of dopants with the hydrogen storage capability of the carbon-based host materials. The generalized design principle and the intrinsic descriptor have the predictive ability to screen out the best dual-doped-graphene-supported Ca single-atom hydrogen storage materials. The dual-doped materials have much higher hydrogen storage capability than the sole-doped ones, and exceed the current best carbon-based hydrogen storage materials.

Abstract Background The Begonia species are common shade plants that are mostly found in southwest China. They have not been well studied despite their medicinal and decorative uses because gene penetration, decreased adaptability, and restricted availability are all caused by frequent interspecific hybridization. Result To understand the patterns of mutation in the chloroplast genomes of different species of Begonia, as well as their evolutionary relationships, we collected seven Begonia species in China and sequenced their chloroplast genomes. Begonia species exhibit a quadripartite structure of chloroplast genomes (157,634 − 169,694 bp), consisting of two pairs of inverted repeats (IR: 26,529 − 37,674 bp), a large single copy (LSC: 75,477 − 86,500 bp), and a small single copy (SSC: 17,861 − 18,367 bp). 128–143 genes (comprising 82–93 protein-coding genes, 8 ribosomal RNAs, and 36–43 transfer RNAs) are found in the chloroplast genomes. Based on comparative analyses, this taxon has a relatively similar genome structure. A total of six substantially divergent DNA regions (trnT-UGU-trnL-UAA, atpF-atpH, ycf4-cemA, psbC-trnS-UGA, rpl32-trnL-UAG, and ccsA-ndhD) are found in the seventeen chloroplast genomes. These regions are suitable for species identification and phylogeographic analysis. Phylogenetic analysis shows that Begonia species that were suited to comparable environments grouped in a small clade and that all Begonia species formed one big clade in the phylogenetic tree, supporting the genus’ monophyly. In addition, positive selection sites were discovered in eight genes (rpoC1, rpoB, psbE, psbK, petA, rps12, rpl2, and rpl22), the majority of which are involved in protein production and photosynthesis. Conclusion Using these genome resources, we can resolve deep-level phylogenetic relationships between Begonia species and their families, leading to a better understanding of evolutionary processes. In addition to enhancing species identification and phylogenetic resolution, these results demonstrate the utility of complete chloroplast genomes in phylogenetically and taxonomically challenging plant groupings.

Abstract With high spatio‐temporal resolution geostationary hyperspectral infrared sounder (GeoHIS) observations, monitoring, and predicting rapidly changing weather events are expected to be improved with continuous information of 3D weather cube. However, due to the nature of radiation, clouds prevent an adequate retrieval of atmospheric thermodynamic information under clear‐sky conditions due to large uncertainties in the current radiative transfer model. Removing cloud effects from GeoHIS sub‐footprint is an alternative approach for enhancing clear radiance generation. Such cloud removal can be achieved through the optimal cloud‐clearing (OCC) method, which usually relies on the assumption of atmospheric spatial homogeneity. With high temporal resolution observations from GeoHIS, cloud removal can also be achieved through OCC but using the assumption of temporal homogeneity. This concept was demonstrated using 15‐min Geostationary Interferometric Infrared Sounder (GIIRS) observations. The longwave GIIRS clear radiances under partially cloud cover can be effectively produced with observation errors less than 0.02 ± 0.86 K and 0.04 ± 0.77 K for 11 and 12 μm, respectively.

The most well-known criterion for POC devices is ASSURED, and affordability, i.e., using low-cost instrumentation, is the most challenging one. This manuscript provides a pathway for transitioning ESSENCE, an impedance-based biosensor platform, from using an expensive benchtop analyzer—KeySight 4294A (~$50k)—to using a significantly portable and cheaper USB oscilloscope—Analog Discovery 2 (~$200) —with similar sensitivity (around 100 times price difference). To achieve this, we carried out a fundamental study of the interplay between an electrolyte like potassium chloride (KCl), and an electrolyte buffer like phosphate buffered saline (PBS) in the presence and absence of a redox buffer like ferro/ferricyanide system and ([Ru(bpy)3]2+). Redox molecules in the electrolyte caused a significant change in the Nyquist curve of the impedance depending on the redox molecule type. The redox species and the background electrolyte have their own RC semicircles in the Nyquist curve, whose overlap depends on the redox concentration and electrolyte ionic strength. We found that by increasing the electrolyte ionic strength or the redox concentration, the RC semicircle moves to higher frequencies and vice versa. Importantly, the use of the buffer electrolyte, instead of KCl, led to a lower standard deviation and overall signal (lesser sensitivity). However, to achieve the best results from the biorecognition signal, we chose a buffered electrolyte like PBS with high ionic strength and lowered the redox probe concentrations to minimize the standard deviation and reduce any noise from migrating to the low-cost analyzer. Comparing the two analyzers shows similar results, with a lowered detection limit from the low-cost analyzer.

Abstract Geostationary (GEO) imager Infrared (IR) bands are often intercalibrated with hyperspectral IR sounders onboard low earth orbit (LEO) satellites. Due to viewing geometry and time differences between GEO and LEO, the inter‐calibration is limited to certain viewing angles and times. When a GEO hyperspectral IR sounder and GEO imager are on the same platform, the inter‐calibration can be conducted from all angles and at all times. In this study, the Geostationary Interferometric Infrared Sounder (GIIRS) is used to inter‐calibrate the Advanced Geosynchronous Radiation Imager (AGRI), both onboard FengYun‐4A. Radiance inter‐comparisons between GIIRS and AGRI under homogeneous scenes, including both clear and cloudy situations, indicate that the differences are within 1 K. The differences have obvious dependence on scene radiance, less dependence on the cloudy situation, and the local zenith angle when it is less than 70°. However, they exhibit significant diurnal characteristics.

BackgroundIncreasing studies have found that PM2.5 has large adverse effects on stroke mortality. We want to investigate the long-term trends in the mortality of stroke attributable to ambient particulate matter pollution and household air pollution to provide evidence facilitating the design of policy.MethodsThe deaths data of stroke and its subtypes attributable to PM2.5 were obtained from the Global Burden of Disease (GBD) 2019, analyzed by Joinpoint regression software and the age-period-cohort (APC) method to assess the magnitude of the trends in mortality and the temporal trends in the mortality rate by age, period, and cohort.ResultsFrom 1990 to 2019, the age-standardized mortality rate (ASMR) attributable to PM2.5 exposure trended downwards, but the trends of ambient particulate matter pollution and household air pollution were opposite. The trends varied among subtypes, the AAPC of intracerebral hemorrhage, ischemic stroke, and subarachnoid hemorrhage attributable to PM2.5 were 0.7, 2.5, and−3.3%, respectively. The longitudinal age curve of the APC model showed that the mortality rates due to PM2.5 exposure increased with age. The period RRs of ischemic stroke due to ambient particulate matter pollution increased significantly. The cohort RRs of ambient particulate matter pollution increased among those born from 1905 to 1990. The net drifts of all subtypes attributable to PM2.5 were below 0, but owing to the increase of ambient particulate matter pollution, the range of the decline was small. Males had higher net drift values, compared with females.ConclusionsAmbient particulate matter pollution has become the main type of PM2.5 leading to stroke in China. PM2.5 exposure is more harmful to ischemic stroke, males, and elderly. Chinese government should pay attention to the long-term impact of ambient air pollution on stroke and take effective public health policies and interventions.

Paraboea (Gesneriaceae) distributed in the karst areas of South and Southwest China and Southeast Asia, is an ideal genus to study the phylogeny and adaptive evolution of karst plants. In this study, the complete chloroplast genomes of twelve Paraboea species were sequenced and analyzed. Twelve chloroplast genomes ranged in size from 153166 to 154245 bp. Each chloroplast genome had a typical quartile structure, and relatively conserved type and number of gene components, including 131 genes which are composed of 87 protein coding genes, 36 transfer RNAs and 8 ribosomal RNAs. A total of 600 simple sequence repeats and 389 non-overlapped sequence repeats were obtained from the twelve Paraboea chloroplast genomes. We found ten divergent regions (trnH-GUG-psbA, trnM-CAU, trnC-GCA, atpF-atpH, ycf1, trnK-UUU-rps16, rps15, petL, trnS-GCU-trnR-UCU and psaJ-rpl33) among the 12 Paraboea species to be potential molecular markers. In the phylogenetic tree of 31 Gesneriaceae plants including twelve Paraboea species, all Paraboea species clustered in a clade and confirmed the monophyly of Paraboea. Nine genes with positive selection sites were detected, most of which were related to photosynthesis and protein synthesis, and might played crucial roles in the adaptability of Paraboea to diverse karst environments. These findings are valuable for further study of the phylogeny and karst adaptability of Gesneriaceae plants.

Infrared (IR) land surface emissivity (LSE) plays an important role in numerical weather prediction (NWP) models through the satellite radiance assimilation. However, due to the large uncertainties in LSE over the desert, many land-surface sensitive channels of satellite IR sensors are not assimilated. This calls for further assessments of the quality of satellite-retrieved LSE in these desert regions. A set of LSE observations were made from field experiments conducted on 16–18 October 2013 along a south/north desert road in the Taklimakan Desert (TD), China. The observed LSEs (EOBS) are thus used in this study as the reference values to evaluate the quality of Combined ASTER MODIS Emissivity over Land (CAMEL) data. Analysis of these data shows four main results. First, the CAMEL datasets appear to sufficiently capture the spatial variations in LSE from the oasis to the hinterland of the TD (this is especially the case in the quartz reststrahlen band). From site 1 at the southern edge of the Taklimakan Desert to site 10 at the northern edge, the measured LSE and the corresponding CAMEL observation in the quartz reststrahlen band first decrease and reach their minimum around sites 4–6 in the hinterland of the Taklimakan Desert. Then, the LSE increases gradually and finally reaches its maximum at site 10, which has a clay ground surface, showing that the LSE is higher at the edges of the desert and lower in the center. Second, the CAMEL values at 11.3 μm have a zonal distribution characterized by a northeast–southwest strike, though such an artifact might have been introduced by ASTER LSE data during the merging process that created the CAMEL dataset. Third, the unrealistic variation of the original EOBS can be filtered out with useful signals, as identified by the first six principal components of the PCA conducted on the laboratory-measured hyperspectral emissivity spectra (ELAB). Fourth, the CAMEL results correlate well with the measured LSE at the 10 observation sites, with the observed LSE being slightly smaller than the CAMEL values in general.

A storm tracking and nowcasting model was developed for the contiguous US (CONUS) by combining observations from the advanced baseline imager (ABI) and numerical weather prediction (NWP) short-range forecast data, along with the precipitation rate from CMORPH (the Climate Prediction Center morphing technique). A random forest based model was adopted by using the maximum precipitation rate as the benchmark for convection intensity, with the location and time of storms optimized by using optical flow (OF) and continuous tracking. Comparative evaluations showed that the optimized models had higher accuracy for severe storms with areas equal to or larger than 5000 km2 over smaller samples, and loweraccuracy for cases smaller than 1000 km2, while models with sample-balancing applied showed higher possibilities of detection (PODs). A typical convective event from August 2019 was presented to illustrate the application of the nowcasting model on local severe storm (LSS) identification and warnings in the pre-convection stage; the model successfully provided warnings with a lead time of 1–2 h before heavy rainfall. Importance score analysis showed that the overall impact from ABI observations was much higher than that from NWP, with the brightness temperature difference between 6.2 and 10.3 microns ranking at the top in terms of feature importance.

This review paper presents the recent developments in spectroelectrochemical (SEC) technologies. The coupling of spectroscopy and electrochemistry enables SEC to do a detailed and comprehensive study of the electron transfer kinetics and vibrational spectroscopic fingerprint of analytes during electrochemical reactions. Though SEC is a promising technique, the usage of SEC techniques is still limited. Therefore, enough publicity for SEC is required, considering the promising potential in the analysis fields. Unlike previously published review papers primarily focused on the relatively frequently used SEC techniques (ultraviolet-visible SEC and surface-enhanced Raman spectroscopy SEC), the two not-frequently used but promising techniques (nuclear magnetic resonance SEC and dark-field microscopy SEC) have also been studied in detail. This review paper not only focuses on the applications of each SEC method but also details their primary working mechanism. In short, this paper summarizes each SEC technique’s working principles, current applications, challenges encountered, and future development directions. In addition, each SEC technique’s applicative research directions are detailed and compared in this review work. Furthermore, integrating SEC techniques into microfluidics is becoming a trend in minimized analysis devices. Therefore, the usage of SEC techniques in microfluidics is discussed.

Meta-heuristic algorithms have successfully solved many real-world problems in recent years. Inspired by different natural phenomena, the algorithms with special search mechanisms can be good at tackling certain problems. However, they may fail to solve other problems. Among the various approaches, hybridizing meta-heuristic algorithms may possibly help to enrich their search behaviors while promoting the search adaptability. Accordingly, an efficient hybrid population-based optimization framework, namely the HYPO, is proposed in this study in which two meta-heuristic algorithms with different search ideas are connected by a dynamic contribution-based state transition scheme. Specifically, the dynamic transition scheme determines the directions of information transitions after considering the current contribution and system state at each iteration so that useful information can be shared and learnt between the concerned meta-heuristic algorithms throughout the search process. To carefully examine the effectiveness of the dynamic transition scheme, the proposed HYPO framework is compared against various well-known meta-heuristic algorithms on a set of large-scale benchmark functions and portfolio management problems of different scales in which the HYPO attains outstanding performances on the problems with complex features. Last but not least, the hybrid framework sheds lights on many possible directions for further improvements and investigations.

With the rapid growth of emerging point-of-use (POU)/point-of-care (POC) detection technologies, miniaturized sensors for the real-time detection of gases and airborne pathogens have become essential to fight pollution, emerging contaminants, and pandemics. However, the low-cost development of miniaturized gas sensors without compromising selectivity, sensitivity, and response time remains challenging. Microfluidics is a promising technology that has been exploited for decades to overcome such limitations, making it an excellent candidate for POU/POC. However, microfluidic-based gas sensors remain a nascent field. In this review, the evolution of microfluidic gas sensors from basic electronic techniques to more advanced optical techniques such as surface-enhanced Raman spectroscopy to detect analytes is documented in detail. This paper focuses on the various detection methodologies used in microfluidic-based devices for detecting gases and airborne pathogens. Non-continuous microfluidic devices such as bubble/droplet-based microfluidics technology that have been employed to detect gases and airborne pathogens are also discussed. The selectivity, sensitivity, advantages/disadvantages vis-a-vis response time, and fabrication costs for all the microfluidic sensors are tabulated. The microfluidic sensors are grouped based on the target moiety, such as air pollutants such as carbon monoxide and nitrogen oxides, and airborne pathogens such as E. coli and SARS-CoV-2. The possible application scenarios for the various microfluidic devices are critically examined.

In this study, an Fe–Cr–Mo–Ni–B coating was prepared using plasma cladding on Cr5 steel substrate. The microstructure, phase evolution and tribological performance of the Fe–Cr–Mo–Ni–B coating were investigated. The microstructure is mainly composed of Mo2FeB2, Fe2B, α-Fe, γ-Fe and MoB. The process of phase evolution in the coating was observed in situ by HT-CLSM. The Mo2FeB2 phase with good thermodynamic stability can exist in the high-temperature liquid phase. It also has a phenomenon of connection and merging and turns into different morphology during the plasma cladding process. The hardness value of coating was much higher than the base metal, and the hardness value of Mo2FeB2 (785.5 HV) was higher than the eutectic matrix (693.2 HV). The wear mechanisms of the cladding under dry sliding were primarily caused by adhesive wear, accompanying slight oxidation wear. The Mo2FeB2 phase has an important effect on the wear resistance property.

A physical retrieval algorithm has been developed for deriving the layered precipitable water vapor (LPWs) product from infrared radiances of the Advanced Geosynchronous Radiation Imager (AGRI) onboard FengYun-4A (FY-4A), the first of the new generation of Chinese geostationary weather satellites (FengYun-4, or FY-4 Series). The FY-4A AGRI LPWs are evaluated with different types of reference datasets based on Quality Control System (QCS), including those from Himawari-8 AHI (Advanced Himawari Imager), MODIS (Moderate Resolution Imaging Spectroradiometer), Radiosonde, ERA5 (European Centre for Medium-Range Weather Forecasts Reanalysis v5), NCEP (National Centers for Environmental Prediction) reanalysis and CMA (China Meteorological Administration) forecast product from global medium range numerical weather prediction (NWP) system. QCS is one of the important components of FY-4A ground segment, which mainly focuses on the satellite products’ evaluation and validation. It is found that the AGRI LPW product has a good agreement with different evaluating sources and the quality is favorable and stable. With the capability of frequent (5-min interval) observations over the East Asia and Western Pacific regions, the AGRI LPW products can be used to investigate the atmospheric temporal and spatial variations in the pre-landfall environment for typhoons. The QCS is a useful tool to monitor, evaluate, and validate the AGRI LPW products.

LiBH4 with high hydrogen storage density, is regarded as one of the most promising hydrogen storage materials. Nevertheless, it suffers from high dehydrogenation temperature and poor reversibility for practical use. Nanoconfinement is effective in achieving low dehydrogenation temperature and favorable reversibility. Besides, graphene can serve as supporting materials for LiBH4 catalysts and also destabilize LiBH4 via interfacial reaction. However, graphene has never been used alone as a frame material for nanoconfining LiBH4. In this study, graphene microflowers with large pore volumes were prepared and used as nanoconfinement framework material for LiBH4, and the nanoconfinement effect of graphene was revealed. After loading 70 wt% of LiBH4 and mechanically compressed at 350 MPa, 8.0 wt% of H2 can be released within 100 min at 320 °C, corresponding to the highest volumetric hydrogen storage density of 94.9 g H2 L-1 ever reported. Thanks to the nanoconfinement of graphene, the rate-limiting step of dehydrogenation of nanoconfined LiBH4 was changed and its apparent activation energy of the dehydrogenation (107.3 kJ moL-1) was 42% lower than that of pure LiBH4. Moreover, the formation of the intermediate Li2B12H12 was effectively inhibited, and the stable nanoconfined structure enhanced the reversibility of LiBH4. This work widens the understanding of graphene's nanoconfinement effect and provides new insights for developing high-density hydrogen storage materials. [ABSTRACT FROM AUTHOR]