Fluorescent hydrogen-bonded organic framework act as a multifunctional platform for Fe3+ and F- sensing, and for information encryption.

Due to their exceptional optical properties and adjustable functional characteristics, hydrogen-bonded organic frameworks (HOFs) demonstrate significant potential in applications such as sensing, information encryption. However, studies on the synthesis of HOFs designed to construct multifunctional platforms are scant. In this work, we report the synthesis of a new fluorescent HOF by assembling melem and isophthalic acid (IPA), designated as HOF-IPA. HOF-IPA exhibited good selectivity and sensitivity towards Fe3+, making it suitable as a fluorescent sensor for Fe3+ detection. The sensor achieved satisfactory recoveries ranging from 97.79 % to106.42 % for Fe3+ sensing, with a low relative standard deviation (RSD) of less than 3.33 %, indicating significant application potential for HOF-IPA. Due to the ability of F- to mask the electrostatic action on the surface of Fe3+ and inhibit the photoelectron transfer (PET) of HOF-IPA, the HOF-IPA - Fe3+ system can be utilized as a fluorescent "off-on" sensor for F- detection. Additionally, owing to the colorless, transparent property of HOF-IPA in aqueous solution under sunlight and its blue fluorescence property under UV light (color) or microplate reader (fluorescence intensity), HOF-IPA based ink can be used for various types of information encryption, and all yielding favorable outcomes.

Anion-binding-induced selective aggregation and self-degradation: Influence of positional isomerism on the anion selectivity and mode of binding of an imine-based receptor.

Imine based positional isomers (8E)-N-(4-((E)-(perfluorophenylimino)methyl)benzylidene)-2,3,4,5,6-pentafluorobenzenamine, L and (10E)-N-(3-(E-Perfluorophenylimino)methyl)benzylidene)-2,3,4,5,6-pentafluorobenzenamine, L1 have been designed, and synthesized by functionalizing two electron deficient aromatic moieties at the para-para'/ortho-ortho' positions in the phenyl core of the L and L1 respectively. The responses of L and L1 towards various anionic species are examined. The positional isomers L and L1 differs not only by showing distinguishable color change upon addition of anions but also differentiates themselves by the way of self-assembling together upon binding with cyanide anion. The naked-eye colorimetric experiments, UV-Vis, Nuclear Magnetic Resonance, and Infra-Red spectroscopic analyses reveal that the isomer L binds fluoride anion through 2:1 stoichiometry ratio. Unlike fluoride complex, the isomer L form aggregates while binding with cyanide ion. On the other hand, isomer L1 does not show any instant color change upon additions of any anion. Interestingly, after thirty minutes, only the color of the cyanide complex is turned into dark brown. While analyzing the spectroscopic results of cyanide complex of L1, it is found that the cyanide complex begins to decompose and finally it is completely decomposed within 30 min. This unprecedented phenomenon about the colorimetric sensing of cyanide and destruction of cyanide complex with respect to time has not been reported in the literature yet. To the best of our knowledge this is the first example of study of sensing controlling the selectivity, mode of binding, self-aggregating and degradation properties of anionic complexes under the influence of positional isomeric effects. This present investigation provides simple and effective strategy to construct the sensor molecules with tunable binding properties in terms of easy to prepare as well as easy to use as a colorimetric sensor. _____________________________________________________________________________________________________.

Effect of structure on sensing performance of nitro explosives with high sensitivity and mechanism of two Tb(III) coordination polymers.

The use of a conjugate N-containing ligand resulted in the decreasing of structural dimensions from 2D network of [Tb(2-pyia)(Ac)(H2O)] (CP1) to 1D chain [Tb(2-pyia)(Ac)(IDP)] (CP2) (2-H2pyia = 5-(pyridin-2-ylmethoxy) isophthalic acid and IDP=imidazo[4,5-f]-[1,10] phenanthroline). Both of them exhibit the characteristic luminescence of Tb ions and could have high fluorescence sensing properties for cefixime and fluridine. The different sensing properties for nitro explosives are manifested as CP1 for nitrobenzene and CP2 for 4-nitrophenol due to the difference in structure. Furthermore, CP2 exhibits the ratiometric fluorescence sensing for Fe3+ ion with a low detection limit of 0.405 µM. The fluorescence sensing mechanism of the two Tb complexes for different analytes was investigated using experimental methods and theoretical calculations. CP1 was used for the detection of Flu residues in the actual system and better results were obtained. The work shows the introduction of the chelated ligand might affect the structural and sensing performance changes of coordination polymers.

Synergistic toxic effects of high-strength ammonia and ZnO nanoparticles on biological nitrogen removal systems and role of exogenous C10-HSL regulation.

The inhibitory effects of zinc oxide nanoparticles (ZnO NPs) and impacts of N-acyl-homoserine lactone (AHL)-based quorum sensing (QS) on biological nitrogen removal (BNR) performance have been well-investigated. However, the effects of ammonia nitrogen (NH4+-N) concentrations on NP toxicity and AHL regulation have seldom been addressed yet. This study consulted on the impacts of ZnO NPs on BNR systems when high NH4+-N concentration was available. The synergistic toxic effects of high-strength NH4+-N (200 mg/L) and ZnO NPs resulted in decreased ammonia oxidation rates and dropped the nitrogen removal efficiencies by 17.5% ± 0.2%. The increased extracellular polymeric substances (EPS) production was observed in response to the high NH4+-N and ZnO NP stress, which indicated the defense mechanism against the toxic effects in the BNR systems was stimulated. Furthermore, the regulatory effects of exogenous N-decanoyl-homoserine lactone (C10-HSL)-mediated QS system on NP-stressed BNR systems were revealed to improve the BNR performance under different NH4+-N concentrations. The C10-HSL regulated the intracellular reactive oxygen species levels, denitrification functional enzyme activities, and antioxidant enzyme activities, respectively. This probably synergistically enhanced the defense mechanism against NP toxicity. However, compared to the low NH4+-N concentration of 60 mg/L, the efficacy of C10-HSL was inhibited at high NH4+-N levels of 200 mg/L. The findings provided the significant application potential of QS system for BNR when facing toxic compound shock threats.

Establishment and verification of anthropogenic speciated VOCs emission inventory of Central China.

Improving the accuracy of anthropogenic volatile organic compounds (VOCs) emission inventory is crucial for reducing atmospheric pollution and formulating control policy of air pollution. In this study, an anthropogenic speciated VOCs emission inventory was established for Central China represented by Henan Province at a 3 km × 3 km spatial resolution based on the emission factor method. The 2019 VOCs emission in Henan Province was 1003.5 Gg, while industrial process source (33.7%) was the highest emission source, Zhengzhou (17.9%) was the city with highest emission and April and August were the months with the more emissions. High VOCs emission regions were concentrated in downtown areas and industrial parks. Alkanes and aromatic hydrocarbons were the main VOCs contribution groups. The species composition, source contribution and spatial distribution were verified and evaluated through tracer ratio method (TR), Positive Matrix Factorization Model (PMF) and remote sensing inversion (RSI). Results show that both the emission results by emission inventory (EI) (15.7 Gg) and by TR method (13.6 Gg) and source contribution by EI and PMF are familiar. The spatial distribution of HCHO primary emission based on RSI is basically consistent with that of HCHO emission based on EI with a R-value of 0.73. The verification results show that the VOCs emission inventory and speciated emission inventory established in this study are relatively reliable.

The phytopathogen Xanthomonas campestris senses and effluxes salicylic acid via a sensor HepR and an RND family efflux pump to promote virulence in host plants.

Salicylic acid (SA) plays an essential role in plant defense against biotrophic and semi-biotrophic pathogens. Following pathogen recognition, SA biosynthesis dramatically increases at the infection site of the host plant. The manner in which pathogens sense and tolerate the onslaught of SA stress to survive in the plant following infection remains to be understood. The objective of this work was to determine how the model phytopathogen Xanthomonas campestris pv. campestris (Xcc) senses and effluxes SA during infection inside host plants. First, RNA-Seq analysis identified an SA-responsive operon Xcc4167-Xcc4171, encoding a MarR family transcription factor HepR and an RND (resistance-nodulation-cell division) family efflux pump HepABCD in Xcc. Electrophoretic mobility shift assays and DNase I footprint analysis revealed that HepR negatively regulated hepABCD expression by specifically binding to an AT-rich region of the promoter of the hepRABCD operon, Phep. Second, isothermal titration calorimetry and further genetic analysis suggest that HepR is a novel SA sensor. SA binding released HepR from its cognate promoter Phep and then induced the expression of hepABCD. Third, the RND family efflux pump HepABCD was responsible for SA efflux. The hepRABCD cluster was also involved in the regulation of culture pH and quorum sensing signal diffusible signaling factor turnover. Finally, the hepRABCD cluster was transcribed during the XC1 infection of Chinese radish and was required for the full virulence of Xcc in Chinese radish and cabbage. These findings suggest that the ability of Xcc to co-opt the plant defense signal SA to activate the multidrug efflux pump may have evolved to ensure Xcc survival and virulence in susceptible host plants.

Discovery of ß-nitrostyrene derivatives as potential quorum sensing inhibitors for biofilm inhibition and antivirulence factor therapeutics against Serratia marcescens.

Quorum sensing (QS) inhibition has emerged as a promising target for directed drug design, providing an appealing strategy for developing antimicrobials, particularly against infections caused by drug-resistant pathogens. In this study, we designed and synthesized a total of 33 ß-nitrostyrene derivatives using 1-nitro-2-phenylethane (NPe) as the lead compound, to target the facultative anaerobic bacterial pathogen Serratia marcescens. The QS-inhibitory effects of these compounds were evaluated using S. marcescens NJ01 and the reporter strain Chromobacterium violaceum CV026. Among the 33 new ß-nitrostyrene derivatives, (E)-1-methyl-4-(2-nitrovinyl)benzene (m-NPe, compound 28) was proven to be a potent inhibitor that reduced biofilm formation of S. marcescens NJ01 by 79%. Scanning electron microscopy (SEM) and confocal laser scanning microscopy (CLSM) results revealed that treatment with m-NPe (50 µg/ml) not only enhanced the susceptibility of the formed biofilms but also disrupted the architecture of biofilms by 84%. m-NPe (50 µg/ml) decreased virulence factors in S. marcescens NJ01, reducing the activity of protease, prodigiosin, and extracellular polysaccharide (EPS) by 36%, 72%, and 52%, respectively. In S. marcescens 4547, the activities of hemolysin and EPS were reduced by 28% and 40%, respectively, outperforming the positive control, vanillic acid (VAN). The study also found that the expression levels of QS- and biofilm-related genes (flhD, fimA, fimC, sodB, bsmB, pigA, pigC, and shlA) were downregulated by 1.21- to 2.32-fold. Molecular dynamics analysis showed that m-NPe could bind stably to SmaR, RhlI, RhlR, LasR, and CviR proteins in a 0.1 M sodium chloride solution. Importantly, a microscale thermophoresis (MST) test revealed that SmaR could be a target protein for the screening of a quorum sensing inhibitor (QSI) against S. marcescens. Overall, this study highlights the efficacy of m-NPe in suppressing the virulence factors of S. marcescens, identifying it as a new potential QSI and antibiofilm agent capable of restoring or improving antimicrobial drug sensitivity.

Metabolic activities of marine ammonia-oxidizing archaea orchestrated by quorum sensing.

Ammonia-oxidizing archaea (AOA) play crucial roles in marine carbon and nitrogen cycles by fixing inorganic carbon and performing the initial step of nitrification. Evaluation of carbon and nitrogen metabolism popularly relies on functional genes such as amoA and accA. Increasing studies suggest that quorum sensing (QS) mainly studied in biofilms for bacteria may serve as a universal communication and regulatory mechanism among prokaryotes; however, this has yet to be demonstrated in marine planktonic archaea. To bridge this knowledge gap, we employed a combination of metabolic activity markers (amoA, accA, and grs) to elucidate the regulation of AOA-mediated nitrogen, carbon processes, and their interactions with the surrounding heterotrophic population. Through co-transcription investigations linking metabolic markers to potential key QS genes, we discovered that QS molecules could regulate AOA's carbon, nitrogen, and lipid metabolisms under different conditions. Interestingly, specific AOA ecotypes showed a preference for employing distinct QS systems and a distinct QS circuit involving a typical population. Overall, our data demonstrate that QS orchestrates nitrogen and carbon metabolism, including the exchange of organic metabolites between AOA and surrounding heterotrophic bacteria, which has been previously overlooked in marine AOA research.

Research on planting planning of Glycyrrhiza uralensis in Naiman Banner based on MaxEnt model and remote sensing technology.

Benefits of Glycyrrhiza uralensis include removing heat, detoxifying, and moistening the lungs, easing coughs, refueling the spleen, and balancing medications. In addition to providing theoretical guidance for the development of the G. uralensis industry and rural revitalization plan, it is anticipated that this paper will also provide basic data for the formulation of production layout of the G. uralensis industry at the county level, the control of cultivation industry direction, the establishment of high-quality G. uralensis cultivation technology system. The Maximum Entropy (MaxEnt) model was used to simulate the potential distribution of G. uralensis, a Chinese medicine resource, in Naiman Banner. By conducting a field inquiry and a broad assessment of the available Chinese medicine resources, the distribution information was acquired. The random forest technique was used to classify G. uralensis. The phenological cycle and development mode of vegetation, which exhibits diverse temporal traits and aids in identification, were elucidated through long-term series analysis. The random forest classification algorithm based on multiple features showed high accuracy in remote sensing (RS) recognition of G. uralensis. Comparative analysis of the MaxEnt and RS results showed that the planting area of G. uralensis was smaller than that of its potential distribution. The expansion to high-suitability areas planting should be prioritized. Based on the dual analysis of regional and remote sensing, it not only proved the great potential of using geographic information to predict the distribution of G. uralensis, but also verified the great potential of extracting the distribution of G. uralensis from GF-6 images. These results will guide the planting and development of G. uralensis in Naiman Banner and a scientific basis for the development of G. uralensis economy, conducive to optimizing the ecological environment and promoting rural revitalization programs.

Luminescence properties of Sr2Ga2GeO7:Bi3+ phosphors and temperature sensing characteristics of co-doped Sm3.

As one of the fundamental physical quantities, temperature is extremely important in various fields. In order to study the temperature sensing characteristics of dual-emitting center phosphors, Bi3+-doped and Bi3+/Sm3+-doped Sr2Ga2GeO7 phosphors were synthesized by high-temperature solid-phase method. Under 312 nm excitation, the Sr2Ga2GeO7:Bi3+ phosphor exhibits a blue broadband emission corresponding to the 3P1 → 1S0 transition of Bi3+ ions. By testing the temperature change spectrum of phosphors, it was found that Bi3+ exhibited strong thermal sensitivity. However, due to the fact that single ion doped phosphors are easily affected by other factors when applied to the field of temperature sensing, based on the thermal sensitivity of Bi3+, Sm3+ with low temperature sensitivity was selected as the co-doped ion, and it was found that the two ions had different thermal quenching characteristics when the temperature change spectrum was tested. Using the temperature detection method based on the fluorescence intensity ratio (FIR) of the dual emission centers, it was found that the best absolute sensitivity Sa was 3.125% K-1 and the maximum relative sensitivity Sr was 1.275% K-1 in the range of 303-423 K. These results show that Sr2Ga2GeO7:Bi3+/Sm3+ phosphors have broad application prospects in the field of optical temperature sensing.

Dual-Responsive MnO2-Loaded Carbonaceous Nanobottle Motors Fabricated by Interfacial Superassembly for On-The-Fly MicroRNA Sensing.

Diverse nanomotors with advanced motion manipulation have been proposed to revolutionize the way problems in many fields are solved. However, rational and controllable synthetic methods of multifunctional nanomotor are still limited. Herein, dual-responsive MnO2-loaded carbonaceous nanobottle motors (MnO2 NBMs) are developed through an interfacial superassembly strategy. Asymmetric carbonaceous nanobottles are first synthesized, and the reductive carbonaceous shell induces an oxidation-reduction reaction with KMnO4 for in-situ growth of MnO2 nanosheets, which enables the nanomotor to perform either self-diffusiophoretic or self-thermophoretic motion in response to H2O2 and near-infrared light, respectively. Inspired by bioaffinity sensing, the nanomotors are sequentially assembled with functional nanoparticles and hairpin DNA to construct swimming functional MnO2 NBMs (MnO2 FNBMs) probes. The probes can move around complex samples to improve target miRNA transport and accelerate receptor-target interaction. Coupling with the photocurrent-signal amplification, the self-assembly of photoelectrochemical (PEC) biosensors has been achieved for sensitive microRNA detection. Trace amounts of miRNA-155 can be quickly detected with a wide detection range (100 fM to 100 nM). Moreover, the direct detection of microRNA in tumor cell lysates by the biosensor is demonstrated. Given the merits of automation and miniaturization, the proposed strategy provides a promising method for fast and effective self-assembly of biosensors.

Synergistic Effect Between 0D CQDs and 2D MXene to Enhance the Photothermal Conversion of Hydrogel Evaporators for Efficient Solar Water Evaporation, Photothermal Sensing and Electricity Generation.

Solar-powered interfacial water evaporation is a promising technique for alleviating freshwater stress. However, the evaporation performance of solar evaporators is still constrained by low photothermal conversion efficiency and high water evaporation enthalpy. Herein, 0D carbon quantum dots (CQDs) are combined with 2D MXene to serve as a hybrid photothermal material to enhance the light absorption and photothermal conversion ability, meanwhile sodium carboxymethyl cellulose (CMC)/polyacrylamide (PAM) hydrogels are used as a substrate material for water transport to reduce the enthalpy of water evaporation. The synergistic effect in 0D CQDs/2D MXene hybrid photothermal materials accelerate the carrier transfer, inducing efficient localized surface plasmon resonance (LSPR) effect. This results in the enhanced photothermal conversion efficiency. The integrated hydrogel evaporators demonstrate a high evaporation rate (1.93 and 2.86 kg m-2 h-1 under 1 and 2 sunlights, respectively) and low evaporation enthalpy (1485 J g-1). In addition, the hydrogel evaporators are applied for photothermal sensing and temperature difference power generation (TEG). The TEG device presents an efficient output power density (230.7 mW m-2) under 1 sunlight. This work provides a feasible approach for regulating and controlling the evaporation performances of hydrogel evaporators, and gives a proof-of-concept for the design of multipurpose solar evaporation systems.

Jasmonates Regulate Auxin-Mediated Root Growth Inhibition in Response to Rhizospheric pH in Arabidopsis thaliana.

Rhizospheric pH, an important environmental cue, severely impacts plant growth and fitness, therefore, has emerged as a major determinant of crop productivity. Despite numerous attempts, the key questions related to plants response against rhizospheric pH remains largely elusive. The present study provides a mechanistic framework for rhizospheric pH-mediated root growth inhibition (RGI). Utilizing various genetic resources combined with pharmacological agents and high-resolution confocal microscopy, the study provides direct evidence for the involvement of jasmonates and auxin in rhizospheric pH-mediated RGI. We show that auxin maxima at root tip is tightly regulated by the rhizospheric pH. In contrast, jasmonates (JAs) abundance inversely correlates with rhizospheric pH. Furthermore, JA-mediated regulation of auxin maxima through GRETCHEN HAGEN 3 (GH3) family genes explains the pattern of RGI observed over the range of rhizospheric pH. Our findings revealed auxin as the key regulator of RGI during severe pH conditions, while JAs antagonistically regulate auxin response against rhizospheric pH.

Anatomic-Based Technique for Sensing Lead Placement in Hypoglossal Stimulator Implantation.

Placement of the sensing lead can be challenging in obese and Down syndrome patients. This article presents an alteration in technique for its placement for these patient populations. Laryngoscope, 2024.

Spatial ecology, biodiversity, and abiotic determinants of Congo's bai ecosystem.

Canopy gaps are foundational features of rainforest biodiversity and successional processes. The bais of Central Africa are among the world's largest natural forest clearings and thought to be critically important islands of open-canopy habitat in an ocean of closed-canopy rainforest. However, while frequently denoted as a conservation priority, there are no published studies on the abundance or distribution of bais across the landscape, nor on their biodiversity patterns, limiting our understanding of their ecological contribution to Congolese rainforests. We combined remote sensing and field surveys to quantify the abundance, spatial distribution, shape, size, biodiversity, and soil properties of bais in Odzala-Kokoua National Park (OKNP), Republic of the Congo (hereafter, Congo). We related bai spatial distribution to variation in hydrology and topography, compared plant community composition and 3D structure between bais and other open ecosystems, quantified animal diversity from camera traps, and measured soil moisture content in different bai types. We found bais to be more numerous than previously thought (we mapped 2176 bais in OKNP), but their predominantly small size (80.7% of bais were <1 ha), highly clustered distribution, and restriction to areas of low topographic position make them a rare riparian habitat type. We documented low plant community and structural similarity between bai types and with other open ecosystems, and identified significant differences in soil moisture between bai and open ecosystem types. Our results demonstrate that two distinct bai types can be differentiated based on their plant and animal communities, soil properties, and vegetation structure. Taken together, our findings provide insights into how bais relate to other types of forest clearings and on their overall importance to Congolese rainforest ecosystems.

π-Conjugated Porous Polymer Nanosheets for Explosive Sensing: Investigation on the Role of H-Bonding.

Nitroaromatic explosive sensing plays a critical role in ensuring public security and environmental protection. Herein, we report 2-pyridyl-thiazolothiazole (pyTTz) integrated blue-fluorescent π-conjugated porous polymer nanosheets, NTzCMP and TzCMP for selective sensing of picric acid (PA) among nitrophenol explosives. Acid-base interactions between PA and pyTTz of CMP lead to H-bonding interactions, where the hydroxy group of PA engaged in weak H-bonding interactions with pyridine and TTz of pyTTz moiety. This led to a strong fluorescence quenching of CMPs-such formation of ground state complex was supported by linear Stern-Volmer quenching plots, unaltered excited state lifetimes, and detailed FTIR analysis of PA exposed CMPs. Interestingly, both CMPs exhibited an excellent response to smaller analytes such as o-nitrotoluene compared to electron-deficient 2,4-dinitrotoluene. Both NTzCMP and TzCMP CMPs exhibited high KSV values of 9×103 and 2.1×103 M-1 for PA and the corresponding limit of detection values were found to be 0.46 and 1.6 ppm, respectively.

Recent progress of chiral metal-organic frameworks in enantioselective separation and detection.

Chiral compounds are abundantly distributed in both the natural world and biological systems. It is crucial to identify and detect chiral compounds in living systems or to separate and determine them in the natural environment. Many researchers have developed a range of chiral materials with different functionalizations to separate and detect chiral substances. Chiral metal-organic frameworks (CMOFs) have the potential to be used in enantioselective separation and detection due to their large surface areas, regulated framework topologies, particular substrate interactions, and accessible chiral sites. CMOFs contribute significantly to the development of enantiomer separation and detection in medicine, agriculture, food, environment, and other fields. This review focuses on four synthesis methods of CMOFs and their applications in chiral separation and chiral sensing in the past five years, mainly including chromatographic separation, membrane separation, optical sensing, electrochemical sensing, and other sensing methods. Finally, the challenges and potential growth direction of CMOFs in enantiomer separation and detection are discussed and prospected.

Self-supervised in-domain representation learning for remote sensing image scene classification.

Transferring the ImageNet pre-trained weights to the various remote sensing tasks has produced acceptable results and reduced the need for labeled samples. However, the domain differences between ground imageries and remote sensing images cause the performance of such transfer learning to be limited. The difficulty of annotating remote sensing images is well-known as it requires domain experts and more time, whereas unlabeled data is readily available. Recently, self-supervised learning, which is a subset of unsupervised learning, emerged and significantly improved representation learning. Recent research has demonstrated that self-supervised learning methods capture visual features that are more discriminative and transferable than the supervised ImageNet weights. We are motivated by these facts to pre-train the in-domain representations of remote sensing imagery using contrastive self-supervised learning and transfer the learned features to other related remote sensing datasets. Specifically, we used the SimSiam algorithm to pre-train the in-domain knowledge of remote sensing datasets and then transferred the obtained weights to the other scene classification datasets. Thus, we have obtained state-of-the-art results on five land cover classification datasets with varying numbers of classes and spatial resolutions. In addition, by conducting appropriate experiments, including feature pre-training using datasets with different attributes, we have identified the most influential factors that make a dataset a good choice for obtaining in-domain features. We have transferred the features obtained by pre-training SimSiam on remote sensing datasets to various downstream tasks and used them as initial weights for fine-tuning. Moreover, we have linearly evaluated the obtained representations in cases where the number of samples per class is limited. Our experiments have demonstrated that using a higher-resolution dataset during the self-supervised pre-training stage results in learning more discriminative and general representations.

Genetic modifications of EGLN1 reactivate HbF production in ß0-thalassemia/HbE.

Reactivation of fetal hemoglobin (HbF, α2γ2) potentially alleviates clinical presentation in ß-thalassemia. Prolyl hydroxylase domain enzymes (PHDs) play roles in the canonical oxygen-sensing pathway and maintain the stability of cellular hypoxia-inducible factor α (HIF-α) in response to low oxygen levels or hypoxia. Pharmacological inhibition of PHDs has been shown to increase HbF production in erythroid progenitors derived from healthy donors. Here, we demonstrated the relationship between PHD2, the main PHD isoform, and clinical phenotypes in ß0-thalassemia/HbE disease. Although the targeted sequencing annotated several common variants within EGLN1, the gene encoding PHD2, none of these variants were located in the functional domains of PHD2 and were irrelevant to the clinical phenotypes. CRISPR-mediated EGLN1 modifications at the functional regions; however, led to significantly reduce PHD2 expression and increase HbF expression levels in severe ß-thalassemia erythroblasts. Moreover, these beneficial phenotypes were independent to the two well-known HbF regulators including BCL11A and GATA1. Our findings introduce an additional mechanism for HbF regulation in ß-thalassemia and propose that targeting the canonical oxygen-sensing pathway, particularly PHD2 functional domains, might offer a promising therapeutic strategy to ß-thalassemia diseases.

Spectro-environmental factors integrated ensemble learning for urban river network water quality remote sensing.

Remote sensing water quality monitoring technology can effectively supplement the shortcomings of traditional water quality monitoring methods in spatiotemporal dynamic monitoring capabilities. At present, although the spectral feature-based remote sensing water quality inversion models have achieved many successes, there could still be a problem of insufficient generalization ability in monitoring the water quality of complex river networks in large cities. In this paper, we propose a spectro-environmental factors integrated ensemble learning model for urban river network water quality inversion. We analyzed the correlation between water quality parameters, spectral reflectance, and environmental factors based on an in-situ dataset collected in the northern part of Shanghai. Using the Hot Spot Analysis (Getis-Ord Gi*), we found that river network water quality parameters have different patterns in different urban functional zones. Furthermore, daily average temperature, total rainfall within the seven days, and several band combinations were also selected as the environmental and spectral features using factor analysis and Pearson correlation coefficient analysis. After the feature analysis, the spectro-environmental factors integrated ensemble learning model was trained. Compared with the spectral-based machine learning inversion models, the coefficients of determination R2 increased by about 0.50. Our model was also tested in three different test areas within and outside the in-situ sampling areas in Shanghai based on low-altitude multispectral remote sensing images. The R2 results for total phosphorus (TP), ammonia nitrogen (NH3-N), and chemical oxygen demand (COD) within the in-situ sampling areas were 0.52, 0.58, and 0.56 respectively. The mean absolute percentage error (MAPE) results were 53.36%, 63.95%, and 22.46% respectively. After adding the area outside the in-situ sampling areas, the R2 results for TP, NH3-N, and COD were 0.47, 0.47, and 0.53. The MAPE were 49.38%, 74.46%, and 20.49%. Our research provided a new remote sensing water quality inversion method to be utilized in complex urban river networks which exhibited solid accuracy and generalization ability.