Assessing progress towards sustainable development over space and time.

To address global challenges1-4, 193 countries have committed to the 17 United Nations Sustainable Development Goals (SDGs)5. Quantifying progress towards achieving the SDGs is essential to track global efforts towards sustainable development and guide policy development and implementation. However, systematic methods for assessing spatio-temporal progress towards achieving the SDGs are lacking. Here we develop and test systematic methods to quantify progress towards the 17 SDGs at national and subnational levels in China. Our analyses indicate that China's SDG Index score (an aggregate score representing the overall performance towards achieving all 17 SDGs) increased at the national level from 2000 to 2015. Every province also increased its SDG Index score over this period. There were large spatio-temporal variations across regions. For example, eastern China had a higher SDG Index score than western China in the 2000s, and southern China had a higher SDG Index score than northern China in 2015. At the national level, the scores of 13 of the 17 SDGs improved over time, but the scores of four SDGs declined. This study suggests the need to track the spatio-temporal dynamics of progress towards SDGs at the global level and in other nations.

Deciphering recursive polyploidization in Lamiales and reconstructing their chromosome evolutionary trajectories.

Lamiales is an order of core eudicots with abundant diversity, and many Lamiales plants have important medicinal and ornamental values. Here, we comparatively reanalyzed 11 Lamiales species with well-assembled genome sequences and found evidence that Lamiales plants, in addition to a hexaploidization or whole-genome triplication (WGT) shared by core eudicots, experienced further polyploidization events, establishing new groups in the order. Notably, we identified a whole-genome duplication (WGD) occurred just before the split of Scrophulariaceae from the other Lamiales families, such as Acanthaceae, Bignoniaceae, and Lamiaceae, suggesting its likely being the causal reason for the establishment and fast divergence of these families. We also found that a WGT occurred ∼68 to 78 million years ago (Mya), near the split of Oleaceae from the other Lamiales families, implying that it may have caused their fast divergence and the establishment of the Oleaceae family. Then, by exploring and distinguishing intra- and intergenomic chromosomal homology due to recursive polyploidization and speciation, respectively, we inferred that the Lamiales ancestral cell karyotype had 11 proto-chromosomes. We reconstructed the evolutionary trajectories from these proto-chromosomes to form the extant chromosomes in each Lamiales plant under study. We must note that most of the inferred 11 proto-chromosomes, duplicated during a WGD thereafter, have been well preserved in jacaranda (Jacaranda mimosifolia) genome, showing the credibility of the present inference implementing a telomere-centric chromosome repatterning model. These efforts are important to understand genome repatterning after recursive polyploidization, especially shedding light on the origin of new plant groups and angiosperm cell karyotype evolution.

Fiber Bragg gratings fabricated in fibers with different geometries by femtosecond laser written through the coating and their applications in strain sensing and fiber laser.

Applications of the type-I fiber Bragg gratings (FBGs) written through the coating (TTC) in strain sensing and tunable distributed Bragg reflector (DBR) fiber lasers were demonstrated. We reported the principle of selecting the distance between the fiber and the phase mask when writing type-I TTC FBGs. Type-I TTC FBGs written in commercially available acrylate-coated fibers with various geometries and their strain responses were demonstrated. Results showed that the strain sensitivity of FBGs increases as the core-diameter decreases, probably due to the waveguide effect. In addition, a continuously tunable DBR fiber laser based on TTC FBGs was achieved with a wavelength tuning range of 19.934 nm around 1080 nm, by applying a strain of 0-21265.8 µÉ› to the laser resonant cavity. The wavelength tuning range was limited by the splice point between the gain fiber and the passive fiber for transmitting pump and signal lasers. When the pump power was 100 mW, the relative intensity noises were -97.334 dB/Hz at the relaxation oscillation peak of 880 kHz and -128 dB/Hz at frequencies greater than 3 MHz. The results open a potential scheme to design and implement continuously tunable fiber lasers and fiber laser sensors for strain sensing with a higher resolution.

POLR3G promotes EMT via PI3K/AKT signaling pathway in bladder cancer.

RNA Polymerase III Subunit G (POLR3G) promotes tumorigenesis, metastasis, cancer stemness, and chemoresistance of breast cancer and lung cancer; however, its biological function in bladder cancer (BLCA) remains unclear. Through bioinformatic analyses, we found that POLR3G expression was significantly elevated in BLCA tumor tissues and was associated with decreased survival. Multivariate Cox analysis indicated that POLR3G could serve as an independent prognostic risk factor. Our functional investigations revealed that POLR3G deficiency resulted in reduced migration and invasion of BLCA cells both in vitro and in vivo. Additionally, the expressions of EMT-related mesenchymal markers were also downregulated in POLR3G knockdown cells. Mechanistically, we showed that POLR3G could activate the PI3K/AKT signaling pathway. Inhibition of this pathway with LY294002 reduced the enhanced migration and invasion of BLCA cells induced by POLR3G overexpression, whereas the activation of this pathway using 740Y-P restored the abilities that were inhibited by POLR3G knockdown. Taken together, our findings suggested that POLR3G is a prognostic predictor for BLCA and promotes EMT of BLCA through activation of the PI3K/AKT signaling pathway.

Engineering the Relatively Conserved Residues in Active Site Architecture of Thermophilic Chitinase SsChi18A Enhanced Catalytic Activity.

Chitinase plays a vital role in the efficient biotransformation of the chitin substrate. This study aimed to modify and elucidate the contribution of the relatively conserved residues in the active site architecture of a thermophilic chitinase SsChi18A from Streptomyces sp. F-3 in processive catalysis. The enzymatic activity on colloidal chitin increased to 151%, 135%, and 129% in variants Y286W, E287A, and K186A compared with the wild type (WT). Also, the apparent processive parameter G2/G1 was lower in the variants compared to the WT, indicating the essential role of Tyr-286, Glu-287, and Lys-186 in processive catalysis. Additionally, the enzymatic activity on the crystalline chitin of F48W and double mutants F48W/Y209F and F48W/Y286W increased by 35%, 16%, and 36% compared with that for WT. Molecular dynamics simulations revealed that the driving force of processive catalysis might be related to the changes in interaction energy. This study provided a rational design strategy targeting relatively conserved residues to enhance the catalytic activity of GH18 processive chitinases.

Obscured Contribution of Oxygenated Intermediate-Volatility Organic Compounds to Secondary Organic Aerosol Formation from Gasoline Vehicle Emissions.

Secondary organic aerosol (SOA) formation from gasoline vehicles spanning a wide range of emission types was investigated using an oxidation flow reactor (OFR) by conducting chassis dynamometer tests. Aided by advanced mass spectrometric techniques, SOA precursors, including volatile organic compounds (VOCs) and intermediate/semivolatile organic compounds (I/SVOCs), were comprehensively characterized. The reconstructed SOA produced from the speciated VOCs and I/SVOCs can explain 69% of the SOA measured downstream of an OFR upon 0.5-3 days' OH exposure. While VOCs can only explain 10% of total SOA production, the contribution from I/SVOCs is 59%, with oxygenated I/SVOCs (O-I/SVOCs) taking up 20% of that contribution. O-I/SVOCs (e.g., benzylic or aliphatic aldehydes and ketones), as an obscured source, account for 16% of total nonmethane organic gas (NMOG) emission. More importantly, with the improvement in emission standards, the NMOG is effectively mitigated by 35% from China 4 to China 6, which is predominantly attributed to the decrease of VOCs. Real-time measurements of different NMOG components as well as SOA production further reveal that the current emission control measures, such as advances in engine and three-way catalytic converter (TWC) techniques, are effective in reducing the "light" SOA precursors (i.e., single-ring aromatics) but not for the I/SVOC emissions. Our results also highlight greater effects of O-I/SVOCs to SOA formation than previously observed and the urgent need for further investigation into their origins, i.e., incomplete combustion, lubricating oil, etc., which requires improvements in real-time molecular-level characterization of I/SVOC molecules and in turn will benefit the future design of control measures.

Manipulating the charge transport via incorporating a cobalt bridge into a single-molecule junction.

Cobalt-bridged organometallic molecular wires (p-Co-p, p-Co-m and m-Co-m) are synthesized, and their charge transport properties are studied. The experimental results show that the quantum interference (QI) effects of cobalt-bridged organometallic wires are determined by the anchoring group. Interestingly, the cobalt-bridge reduces the conductance of the junctions and tunes the QI effect of the wires. These results demonstrate the unique property of metal-bridged organometallic molecular wires and their potential applications in molecular electronics.

Interactions between inhalable aged microplastics and lung surfactant: Potential pulmonary health risks.

The relationship between microplastics (MPs) and human respiratory health has garnered significant attention since inhalation constitutes the primary pathway for atmospheric MP exposure. While recent studies have revealed respiratory risks associated with MPs, virgin MPs used as plastic surrogates in these experiments did not represent the MPs that occur naturally and that undergo aging effects. Thus, the effects of aged MPs on respiratory health remain unknown. We herein analyzed the interaction between inhalable aged MPs with lung surfactant (LS) extracted from porcine lungs vis-à-vis interfacial chemistry employing in-vitro experiments, and explored oxidative damage induced by aged MPs in simulated lung fluid (SLF) and the underlying mechanisms of action. Our results showed that aged MPs significantly increased the surface tension of the LS, accompanied by a diminution in its foaming ability. The stronger adsorptive capacity of the aged MPs toward the phospholipids of LS appeared to produce increased surface tension, while the change in foaming ability might have resulted from a variation in the protein secondary structure and the adsorption of proteins onto MPs. The adsorption of phospholipid and protein components then led to the aggregation of MPs in SLF, where the aged MPs exhibited smaller hydrodynamic diameters in comparison with the unaged MPs, likely interacting with biomolecules in bodily fluids to exacerbate health hazards. Persistent free radicals were also formed on aged MPs, inducing the formation of reactive oxygen species such as superoxide radicals (O2•-), hydrogen peroxide (HOOH), and hydroxyl radicals (•OH); this would lead to LS lipid peroxidation and protein damage and increase the risk of respiratory disease. Our investigation was the first-ever to reveal a potential toxic effect of aged MPs and their actions on the human respiratory system, of great significance in understanding the risk of inhaled MPs on lung health.

Lightweight Tunnel Obstacle Detection Based on Improved YOLOv5.

Considering the high incidence of accidents at tunnel construction sites, using robots to replace humans in hazardous tasks can effectively safeguard their lives. However, most robots currently used in this field require manual control and lack autonomous obstacle avoidance capability. To address these issues, we propose a lightweight model based on an improved version of YOLOv5 for obstacle detection. Firstly, to enhance detection speed and reduce computational load, we modify the backbone network to the lightweight Shufflenet v2. Secondly, we introduce a coordinate attention mechanism to enhance the network's ability to learn feature representations. Subsequently, we replace the neck convolution block with GSConv to improve the model's efficiency. Finally, we modify the model's upsampling method to further enhance detection accuracy. Through comparative experiments on the model, the results demonstrate that our approach achieves an approximately 37% increase in detection speed with a minimal accuracy reduction of 1.5%. The frame rate has improved by about 54%, the parameter count has decreased by approximately 74%, and the model size has decreased by 2.5 MB. The experimental results indicate that our method can reduce hardware requirements for the model, striking a balance between detection speed and accuracy.

Digestive system deep infiltrating endometriosis: What do we know.

Digestive system infiltrating endometriosis (DSIE) is an uncommon form of endometriosis in the digestive system. DSIE often occurs in the intestines (especially the sigmoid rectum), liver, gallbladder and pancreas. Clinically, DSIE presents with the same symptoms as endometriosis, including cyclic pain, bleeding and infertility, in addition to specific biliary/intestinal obstruction and gastrointestinal bleeding. Compared to general endometriosis, DSIE has unique biological behaviour and pathophysiological mechanisms. Most DSIEs are deep invasive endometrioses, characterized by metastasis to the lymph nodes and lymphatic vessels, angiogenesis, peripheral nerve recruitment, fibrosis and invasion of surrounding tissues. DSIE-related peripheral angiogenesis is divided into three patterns: angiogenesis, vasculogenesis and inosculation. These patterns are regulated by interactions between multiple hypoxia-hormone cytokines. The nerve growth factors regulate the extensive neurofibril recruitment in DSIE lesions, which accounts for severe symptoms of deep pain. They are also associated with fibrosis and the aggressiveness of DSIE. Cyclic changes in DSIE lesions, recurrent inflammation and oxidative stress promote repeated tissue injury and repair (ReTIAR) mechanisms in the lesions, accelerating fibril formation and cancer-related mutations. Similar to malignant tumours, DSIE can also exhibit aggressiveness derived from collective cell migration mediated by E-cadherin and N-cadherin. This often makes DSIE misdiagnosed as a malignant tumour of the digestive system in clinical practice. In addition to surgery, novel treatments are urgently required to effectively eradicate this lesion.

Fine mapping of qAHPS07 and functional studies of AhRUVBL2 controlling pod size in peanut (Arachis hypogaea L.).

Cultivated peanut (Arachis hypogaea L.) is an important oil and cash crop. Pod size is one of the major traits determining yield and commodity characteristic of peanut. Fine mapping of quantitative trait locus (QTL) and identification of candidate genes associated with pod size are essential for genetic improvement and molecular breeding of peanut varieties. In this study, a major QTL related to pod size, qAHPS07, was fine mapped to a 36.46 kb interval on chromosome A07 using F2 , recombinant inbred line (RIL) and secondary F2 populations. qAHPS07 explained 38.6%, 23.35%, 37.48%, 25.94% of the phenotypic variation for single pod weight (SPW), pod length (PL), pod width (PW) and pod shell thickness (PST), respectively. Whole genome resequencing and gene expression analysis revealed that a RuvB-like 2 protein coding gene AhRUVBL2 was the most likely candidate for qAHPS07. Overexpression of AhRUVBL2 in Arabidopsis led to larger seeds and plants than the wild type. AhRUVBL2-silenced peanut seedlings represented small leaves and shorter main stems. Three haplotypes were identified according to three SNPs in the promoter of AhRUVBL2 among 119 peanut accessions. Among them, SPW, PW and PST of accessions carrying Hap_ATT represent 17.6%, 11.2% and 26.3% higher than those carrying Hap_GAC，respectively. In addition, a functional marker of AhRUVBL2 was developed. Taken together, our study identified a key functional gene of peanut pod size, which provides new insights into peanut pod size regulation mechanism and offers practicable markers for the genetic improvement of pod size-related traits in peanut breeding.

Identification of HPV oncogene and host cell differentiation associated cellular heterogeneity in cervical cancer via single-cell transcriptomic analysis.

Human Papillomaviruses (HPVs) are associated with around 5%-10% of human cancer, notably nearly 99% of cervical cancer. The mechanisms HPV interacts with stratified epithelium (differentiated layers) during the viral life cycle, and oncogenesis remain unclear. In this study, we used single-cell transcriptome analysis to study viral gene and host cell differentiation-associated heterogeneity of HPV-positive cervical cancer tissue. We examined the HPV16 genes-E1, E6, and E7, and found they expressed differently across nine epithelial clusters. We found that three epithelial clusters had the highest proportion of HPV-positive cells (33.6%, 37.5%, and 32.4%, respectively), while two exhibited the lowest proportions (7.21% and 5.63%, respectively). Notably, the cluster with the most HPV-positive cells deviated significantly from normal epithelial layer markers, exhibiting functional heterogeneity and altered epithelial structuring, indicating that significant molecular heterogeneity existed in cancer tissues and that these cells exhibited unique/different gene signatures compared with normal epithelial cells. These HPV-positive cells, compared to HPV-negative, showed different gene expressions related to the extracellular matrix, cell adhesion, proliferation, and apoptosis. Further, the viral oncogenes E6 and E7 appeared to modify epithelial function via distinct pathways, thus contributing to cervical cancer progression. We investigated the HPV and host transcripts from a novel viewpoint focusing on layer heterogeneity. Our results indicated varied HPV expression across epithelial clusters and epithelial heterogeneity associated with viral oncogenes, contributing biological insights to this critical field of study.

Ultra-high-temperature sensing using fiber grating sensor and demodulation method based on support vector regression optimized by a genetic algorithm.

We propose an ultra-high-temperature sensing method using a fiber Bragg grating (FBG) and demodulation technique based on support vector regression optimized by a genetic algorithm (GA-SVR). A type-I FBG inscribed by a femtosecond laser in a silica fiber was packaged with a tube and used as a temperature sensor. The external ambient temperature was retrieved from the transient FBG wavelength and its increase rate in reaching thermal equilibrium of the FBG with the external environment using GA-SVR. The temperature sensing in the range of 400 to 1000 °C was realized with an accuracy of 4.8 °C. The highest sensing temperature exceeded the FBG resisting temperature of 700 °C. The demodulation time was decreased to approximately 15 s, only 3.14% of the FBG sensor time constant. The proposed method could realize the external ambient temperature determination before the FBG temperature reached the thermal equilibrium state, which enables to attain a demodulation time shorter than the time constant of the FBG sensor and a sensing temperature higher than the FBG resisting temperature. This method could be potentially applied in temperature inspection of combustion and other fields.

Control of Grain Size and Weight by the GSK2-LARGE1/OML4 Pathway in Rice.

Regulation of grain size is crucial for improving crop yield and is also a basic aspect in developmental biology. However, the genetic and molecular mechanisms underlying grain size control in crops remain largely unknown despite their central importance. Here, we report that the MEI2-LIKE PROTEIN4 (OML4) encoded by the LARGE1 gene is phosphorylated by GLYCOGEN SYNTHASE KINASE2 (GSK2) and negatively controls grain size and weight in rice (Oryza sativa). Loss of function of OML4 leads to large and heavy grains, while overexpression of OML4 causes small and light grains. OML4 regulates grain size by restricting cell expansion in the spikelet hull. OML4 is expressed in developing panicles and grains, and the GFP-OML4 fusion protein is localized in the nuclei. Biochemical analyses show that the GSK2 physically interacts with OML4 and phosphorylates it, thereby possibly influencing the stability of OML4. Genetic analyses support that GSK2 and OML4 act, at least in part, in a common pathway to control grain size in rice. These results reveal the genetic and molecular mechanism of a GSK2-OML4 regulatory module in grain size control, suggesting that this pathway is a suitable target for improving seed size and weight in crops.

Effects of interlayer reflection and interpixel interaction in diffractive optical neural networks.

Multilayer diffractive optical neural networks (DONNs) can perform machine learning (ML) tasks at the speed of light with low energy consumption. Decreasing the number of diffractive layers can reduce inevitable material and diffraction losses to improve system performance, and incorporating compact devices can reduce the system footprint. However, current analytical DONN models cannot accurately describe such physical systems. Here we show the ever-ignored effects of interlayer reflection and interpixel interaction on the deployment performance of DONNs through full-wave electromagnetic simulations and terahertz (THz) experiments. We demonstrate that the drop of handwritten digit classification accuracy due to reflection is negligible with conventional low-index THz polymer materials, while it can be substantial with high-index materials. We further show that one- and few-layer DONN systems can achieve high classification accuracy, but there is a trade-off between accuracy and model-system matching rate because of the fast-varying spatial distribution of optical responses in diffractive masks. Deep DONNs can break down such a trade-off because of reduced mask spatial complexity. Our results suggest that new accurate and trainable DONN models are needed to advance the development and deployment of compact DONN systems for sophisticated ML tasks.

Clinicopathologic features in childhood-onset lupus nephritis with antineutrophil cytoplasmic antibody positivity--a multi-center retrospective study.

BACKGROUND: Positive antineutrophil cytoplasmic antibody (ANCA) serology in adult-onset lupus nephritis (LN) is associated with more active disease and distinct renal pathology, but data with respect to childhood-onset LN remain scarce. Here, we aimed to determine the impact of positive ANCA serology on clinical and histopathologic features and renal outcomes in children with LN from multiple centers. METHODS: Clinical and histopathologic data of 61 ANCA-positive and 330 ANCA-negative LN children (1

Purinergic signaling: a potential therapeutic target for ischemic stroke.

Pathogenesis of ischemic stroke is mainly characterized by thrombosis and neuroinflammation. Purinergic signaling pathway constitutes adenosine triphosphate (ATP), adenosine diphosphate (ADP), adenosine monophosphate (AMP), and adenosine (ADO). ATP is hydrolyzed to ADP and then to AMP by extracellular nucleotidase CD39; AMP is subsequently converted to adenosine by CD73. All these nucleotides and nucleosides act on purinergic receptors protecting against thrombosis and inhibit inflammation. In addition, many physical methods have been found to play a neuroprotective role through purinergic signaling. This review mainly introduces the role and potential mechanism of purinergic signalings in the treatment of ischemic stroke, so as to provide reference for seeking new treatment methods for stroke.

Application of a fiber Bragg grating temperature sensing method based on support vector regression optimized by a genetic algorithm for the decreasing external ambient temperature case.

We studied the application of the fiber Bragg grating (FBG) temperature sensing method based on support vector regression optimized by a genetic algorithm (GA-SVR) for constant and decreasing external ambient temperature cases by simulation. The external ambient temperature could be retrieved from both the transient FBG wavelength and its corresponding change rate using GA-SVR, before the FBG temperature sensor reached the thermal equilibrium state with the external ambient temperature. FBG wavelengths and their corresponding change rates in the cases of FBG sensor temperatures higher and lower than the external ambient temperature were studied and used to construct the training data set. We found that there exist singularity points in the curves of the wavelength change rate when the FBG sensor temperature is higher than the external ambient temperature in some cases, which is different from the case where the FBG sensor temperature is lower than the external ambient temperature. Its application for sensing the constant and decreasing external ambient temperature in real time was demonstrated with an accuracy of 0.32°C in those two cases. It also indicates that for real applications of this temperature sensing method where the external ambient temperature varies randomly, the FBG sensor temperature changes rather than the external ambient temperature changes play the dominant role. What is more, the demodulation time was decreased to 0.002 s, which is approximately 0.05‱ of the time constant of the FBG temperature sensor. In other words, this method makes it possible to realize the external ambient temperature determination using a time smaller than the time constant of the FBG sensor. The high sensing accuracy and fast demodulation speed are crucial for future high-performance real-time FBG temperature sensing.

Aquaporins in Urinary System.

There are at least eight aquaporins (AQPs) expressed in the kidney. Including AQP1 expressed in proximal tubules, thin descending limb of Henle and vasa recta; AQP2, AQP3, AQP4, AQP5, and AQP6 expressed in collecting ducts; AQP7 expressed in proximal tubules; AQP8 expressed in proximal tubules and collecting ducts; and AQP11 expressed in the endoplasmic reticulum of proximal tubular epithelial cells. Over years, researchers have constructed different AQP knockout mice and explored the effect of AQP knockout on kidney function. Thus, the roles of AQPs in renal physiology are revealed, providing very useful information for addressing fundamental questions about transepithelial water transport and the mechanism of near isoosmolar fluid reabsorption. This chapter introduces the localization and function of AQPs in the kidney and their roles in different kidney diseases to reveal the prospects of AQPs in further basic and clinical studies.

Data-driven strategies for the computational design of enzyme thermal stability: trends, perspectives, and prospects.

Thermal stability is one of the most important properties of enzymes, which sustains life and determines the potential for the industrial application of biocatalysts. Although traditional methods such as directed evolution and classical rational design contribute greatly to this field, the enormous sequence space of proteins implies costly and arduous experiments. The development of enzyme engineering focuses on automated and efficient strategies because of the breakthrough of high-throughput DNA sequencing and machine learning models. In this review, we propose a data-driven architecture for enzyme thermostability engineering and summarize some widely adopted datasets, as well as machine learning-driven approaches for designing the thermal stability of enzymes. In addition, we present a series of existing challenges while applying machine learning in enzyme thermostability design, such as the data dilemma, model training, and use of the proposed models. Additionally, a few promising directions for enhancing the performance of the models are discussed. We anticipate that the efficient incorporation of machine learning can provide more insights and solutions for the design of enzyme thermostability in the coming years.