Self-Catalyzed Growth of Co4N and N-Doped Carbon Nanotubes toward Bifunctional Cathode for Highly Safe and Flexible Li-Air Batteries.

The practical application of high-energy density lithium-oxygen (Li-O2) batteries is severely impeded by the notorious cycling stability and safety, which mainly comes from slow kinetics of oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) at cathodes, causing inferior redox overpotentials and reactive lithium metal in flammable liquid electrolyte. Herein, a bifunctional electrode, a safe gel polymer electrolyte (GPE), and a robust lithium anode are proposed to alleviate above problems. The bifunctional electrode is composed of N-doped carbon nanotubes (N-CNTs) and Co4N by in situ chemical vapor deposition self-catalyzed growth on carbon cloth (N-CNTs@Co4N@CC). The self-supporting, binder-free N-CNTs@Co4N@CC electrode has a strong and stable three-dimensional (3D) interconnected conductive structure, which provides interconnectivity between the active sites and the electrode to promote the transfer of electrons. Furthermore, the N-CNT-intertwined Co4N ensures efficient catalytic activity. Hence, the electrode demonstrates improved electrochemical properties even under a large current density (2000 mA g-1) and long cycling operation (250 cycles). Moreover, a highly safe and flexible rechargeable cell using the 3D N-CNTs@Co4N@CC electrode, GPE, and robust lithium anode design has been explored. The open circuit voltage is stable at ∼3.0 V even after 9800 cycles, which proves the mechanical durability of the integrated GPE cell. The stable cable-type Li-air battery was demonstrated to stably drive the light-emitting diodes (LEDs), highlighting the reliability for practical use.

Advantages of transformer and its application for medical image segmentation: a survey.

PURPOSE: Convolution operator-based neural networks have shown great success in medical image segmentation over the past decade. The U-shaped network with a codec structure is one of the most widely used models. Transformer, a technology used in natural language processing, can capture long-distance dependencies and has been applied in Vision Transformer to achieve state-of-the-art performance on image classification tasks. Recently, researchers have extended transformer to medical image segmentation tasks, resulting in good models. METHODS: This review comprises publications selected through a Web of Science search. We focused on papers published since 2018 that applied the transformer architecture to medical image segmentation. We conducted a systematic analysis of these studies and summarized the results. RESULTS: To better comprehend the benefits of convolutional neural networks and transformers, the construction of the codec and transformer modules is first explained. Second, the medical image segmentation model based on transformer is summarized. The typically used assessment markers for medical image segmentation tasks are then listed. Finally, a large number of medical segmentation datasets are described. CONCLUSION: Even if there is a pure transformer model without any convolution operator, the sample size of medical picture segmentation still restricts the growth of the transformer, even though it can be relieved by a pretraining model. More often than not, researchers are still designing models using transformer and convolution operators.

Characteristics of Oil-in-Oil Emulsions under AC Electric Fields.

Emulsions have been applied in a number of industries such as pharmaceutics, cosmetics, and food, which are also of great scientific interest. Although aqueous emulsions are commonly used in our daily life, oil-in-oil (o/o) emulsions also play an irreplaceable role in view of their unique physics and complementary applications. In this paper, we investigate typical behaviors of organic droplets surrounded by organic medium (o/o emulsions) with different functional groups controlled by the AC electric field. Droplet behaviors can be catalogued into five types: namely, "no effect", "movement", "deformation", "interface rupture", and "disorder". We identify the key dimensionless number Wee·Ca, combined with the channel geometry, for characterizing the typical behaviors in silicon oil/1,6-hexanediol diacrylate and mineral oil/1,6-hexanediol diacrylate emulsions. Unlike aqueous emulsion, the Maxwell-Wagner relaxation inhibits the electric effect and leads to an effective frequency, ranging from 0.5 to 3 kHz. The increasing viscosity of the droplet facilitates the escalation by promoting the shearing effect under the same flow conditions. Ethylene glycol droplets primarily show the efficient coalescence even at a low Wee·Ca, which is attributed to the attraction of free charges induced by the increasing conductivity. In 1,6-hexanediol diacrylate/silicon oil emulsion, the droplet tends to form a liquid film that expands into the entire channel due to the affinity of the droplet to the channel wall. A variety of elongated columns are observed to oscillate between the electrodes at high voltages. These findings can contribute to understanding the electrohydrodynamic physics in o/o emulsion and controlling droplet behaviors in a fast response, programmable, and high-throughput way. We expect that this droplet manipulation technology can be widely adopted in a broad range of chemical synthesis and biological and material science.

Multi-domain feature joint optimization based on multi-view learning for improving the EEG decoding.

Background: Brain-computer interface (BCI) systems based on motor imagery (MI) have been widely used in neurorehabilitation. Feature extraction applied by the common spatial pattern (CSP) is very popular in MI classification. The effectiveness of CSP is highly affected by the frequency band and time window of electroencephalogram (EEG) segments and channels selected. Objective: In this study, the multi-domain feature joint optimization (MDFJO) based on the multi-view learning method is proposed, which aims to select the discriminative features enhancing the classification performance. Method: The channel patterns are divided using the Fisher discriminant criterion (FDC). Furthermore, the raw EEG is intercepted for multiple sub-bands and time interval signals. The high-dimensional features are constructed by extracting features from CSP on each EEG segment. Specifically, the multi-view learning method is used to select the optimal features, and the proposed feature sparsification strategy on the time level is proposed to further refine the optimal features. Results: Two public EEG datasets are employed to validate the proposed MDFJO method. The average classification accuracy of the MDFJO in Data 1 and Data 2 is 88.29 and 87.21%, respectively. The classification result of MDFJO was significantly better than MSO (p < 0.05), FBCSP32 (p < 0.01), and other competing methods (p < 0.001). Conclusion: Compared with the CSP, sparse filter band common spatial pattern (SFBCSP), and filter bank common spatial pattern (FBCSP) methods with channel numbers 16, 32 and all channels as well as MSO, the MDFJO significantly improves the test accuracy. The feature sparsification strategy proposed in this article can effectively enhance classification accuracy. The proposed method could improve the practicability and effectiveness of the BCI system.

Pan-genome Analysis of WOX Gene Family and Function Exploration of CsWOX9 in Cucumber.

Cucumber is an economically important vegetable crop, and the warts (composed of spines and Tubercules) of cucumber fruit are an important quality trait that influences its commercial value. WOX transcription factors are known to have pivotal roles in regulating various aspects of plant growth and development, but their studies in cucumber are limited. Here, genome-wide identification of cucumber WOX genes was performed using the pan-genome analysis of 12 cucumber varieties. Our findings revealed diverse CsWOX genes in different cucumber varieties, with variations observed in protein sequences and lengths, gene structure, and conserved protein domains, possibly resulting from the divergent evolution of CsWOX genes as they adapt to diverse cultivation and environmental conditions. Expression profiles of the CsWOX genes demonstrated that CsWOX9 was significantly expressed in unexpanded ovaries, especially in the epidermis. Additionally, analysis of the CsWOX9 promoter revealed two binding sites for the C2H2 zinc finger protein. We successfully executed a yeast one-hybrid assay (Y1H) and a dual-luciferase (LUC) transaction assay to demonstrate that CsWOX9 can be transcriptionally activated by the C2H2 zinc finger protein Tu, which is crucial for fruit Tubercule formation in cucumber. Overall, our results indicated that CsWOX9 is a key component of the molecular network that regulates wart formation in cucumber fruits, and provide further insight into the function of CsWOX genes in cucumber.

Expanding the chemical space of enol silyl ethers: catalytic dicarbofunctionalization enabled by iron catalysis.

Enol silyl ethers are versatile, robust, and readily accessible substrates widely used in chemical synthesis. However, the conventional reactivity of these motifs has been limited to classical two electron (2-e) enolate-type chemistry with electrophilic partners or as radical acceptors in one electron (1-e) reactivity leading, in both cases, to exclusive α-monofunctionalization of carbonyls. Herein we describe a mild, fast, and operationally simple one-step protocol that combines readily available fluoroalkyl halides, silyl enol ethers, and, for the first time, hetero(aryl) Grignard reagents to promote selective dicarbofunctionalization of enol silyl ethers. From a broader perspective, this work expands the synthetic utility of enol silyl ethers and establishes bisphosphine-iron catalysis as enabling technology capable of orchestrating selective C-C bond formations with short-lived α-silyloxy radicals with practical implications towards sustainable chemical synthesis.

Effect of acupuncture for patients with knee osteoarthritis: study protocol for a double-dummy randomized controlled trial.

BACKGROUND: Acupuncture has been used to relieve chronic pain in patients with knee osteoarthritis (KOA), but the evidence is contradictory. Therefore, we carefully designed a double-dummy randomized controlled trial (RCT) to explore the therapeutic effect of acupuncture for KOA. METHODS/DESIGN: A total of 138 eligible participants with KOA who consent to participate will be randomly divided into Groups A, B, and C in a ratio of 1:1:1. Participants in Group A will receive verum acupuncture and placebo gel, while those in Groups B and C will be treated with diclofenac diethylammon gel and sham acupuncture, sham acupuncture and placebo gel, respectively. The patients will receive 4 weeks of treatment, five times a week, including acupuncture treatment once a day for 30 min and gel treatment three times a day. The primary outcome will be the change of Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) at week 4. The secondary outcomes will include visual analog scale (VAS), Arthritis Quality of Life Measurement Scale Simplified Scale (AIMS2-SF), Beck Anxiety Inventory (BAI), Beck Depression Inventory (BDI) and Credibility/Expectancy Questionnaire. The evaluation will be performed at baseline, week 4, 8, and 12 after randomization. DISCUSSION: This double-dummy RCT used diclofenac diethylammon gel as a positive control, and the completion of this trial will provide detailed and accurate evidence of the efficacy and safety of acupuncture for KOA. TRIAL REGISTRATION: China Clinical Trials Registry No.ChiCTR2100043947. Registered on September 24, 2020. https://www.chictr.org.cn/showproj.html?proj=122536 .

Compound Droplet Impact on a Thin Hydrophobic Cylinder.

The impact of compound droplets on solid surfaces is a ubiquitous phenomenon that pervades both the natural and technological fields. A comprehensive understanding of the dynamics of the droplet impact on solid surfaces is therefore of paramount importance for a broad range of applications. In this study, we investigate the impact of a water-in-oil compound droplet on a thin hydrophobic cylindrical surface, with regard to the Weber number and cylinder dimensions. Owing to the prewetting effect of the oil, the droplet completely engulfs the cylinder during impact. The ensuing breakups of oil and water engender various unique impact outcomes, which are depicted via a phase map. The phase boundaries are described by analyzing the gravitational and drag forces exerted by the cylinder. A threshold value of the Weber number is found beyond which its effect on the azimuthal spreading process becomes less obvious. The distinctive axial spreading processes of oil and water are illustrated through high-speed imaging from both front and side perspectives, revealing that droplet oscillation is critically influenced by the Weber number. Our work elucidates the impact dynamics of compound droplets on curved surfaces, providing pivotal insights into related thermal management, droplet printing, and coating fabrication applications.

Clinical-functional brain connectivity signature predicts longitudinal symptom improvement after acupuncture treatment in patients with functional dyspepsia.

Whilst acupuncture has been shown to be an effective treatment for functional dyspepsia (FD), its efficacy varies significantly among patients. Knowing beforehand how each patient responds to acupuncture treatment will facilitate the ability to produce personalized prescriptions, therefore, improving acupuncture efficacy. The objective of this study was to construct the prediction model, based on the clinical-neuroimaging signature, to forecast the individual symptom improvement of FD patients following a 4-week acupuncture treatment and to identify the critical predictive features that could potentially serve as biomarkers for predicting the efficacy of acupuncture for FD. Clinical-functional brain connectivity signatures were extracted from samples in the training-test set (100 FD patients) and independent validation set (60 FD patients). Based on these signatures and support vector machine algorithms, prediction models were developed in the training test set, followed by model performance evaluation and predictive features extraction. Subsequently, the external robustness of the extracted predictive features in predicting acupuncture efficacy was evaluated by the independent validation set. The developed prediction models possessed an accuracy of 88% in predicting acupuncture responders, as well as an R2 of 0.453 in forecasting symptom relief. Factors that contributed significantly to stronger responsiveness of patients to acupuncture therapy included higher resting-state functional connectivity associated with the orbitofrontal gyrus, caudate, hippocampus, and anterior insula, as well as higher baseline scores of the Symptom Index of Dyspepsia and shorter durations of the condition. Furthermore, the robustness of these features in predicting the efficacy of acupuncture for FD was verified through various machine learning algorithms and independent samples and remained stable in univariate and multivariate analyses. These findings suggest that it is both feasible and reliable to predict the efficacy of acupuncture for FD based on the pre-treatment clinical-neuroimaging signature. The established prediction framework will promote the identification of suitable candidates for acupuncture treatment, thereby improving the efficacy and reducing the cost of acupuncture for FD.

EVs-mediated delivery of CB2 receptor agonist for Alzheimer's disease therapy.

Alzheimer's disease (AD) is a typical neurodegenerative disease that leads to irreversible neuronal degeneration, and effective treatment remains elusive due to the unclear mechanism. We utilized biocompatible mesenchymal stem cell-derived extracellular vesicles as carriers loaded with the CB2 target medicine AM1241 (EVs-AM1241) to protect against neurodegenerative progression and neuronal function in AD model mice. According to the results, EVs-AM1241 were successfully constructed and exhibited better bioavailability and therapeutic effects than bare AM1241. The Morris water maze (MWM) and fear conditioning tests revealed that the learning and memory of EVs-AM1241-treated model mice were significantly improved. In vivo electrophysiological recording of CA1 neurons indicated enhanced response to an auditory conditioned stimulus following fear learning. Immunostaining and Western blot analysis showed that amyloid plaque deposition and amyloid ß (Aß)-induced neuronal apoptosis were significantly suppressed by EVs-AM1241. Moreover, EVs-AM1241 increased the number of neurons and restored the neuronal cytoskeleton, indicating that they enhanced neuronal regeneration. RNA sequencing revealed that EVs-AM1241 facilitated Aß phagocytosis, promoted neurogenesis and ultimately improved learning and memory through the calcium-Erk signaling pathway. Our study showed that EVs-AM1241 efficiently reversed neurodegenerative pathology and enhanced neurogenesis in model mice, indicating that they are very promising particles for treating AD.

Unresolved Excess Accumulation of Myelin-Derived Cholesterol Contributes to Scar Formation after Spinal Cord Injury.

Spinal cord injury triggers complex pathological cascades, resulting in destructive tissue damage and incomplete tissue repair. Scar formation is generally considered a barrier for regeneration in the central nervous system. However, the intrinsic mechanism of scar formation after spinal cord injury has not been fully elucidated. Here, we report that excess cholesterol accumulates in phagocytes and is inefficiently removed from spinal cord lesions in young adult mice. Interestingly, we observed that excessive cholesterol also accumulates in injured peripheral nerves but is subsequently removed by reverse cholesterol transport. Meanwhile, preventing reverse cholesterol transport leads to macrophage accumulation and fibrosis in injured peripheral nerves. Furthermore, the neonatal mouse spinal cord lesions are devoid of myelin-derived lipids and can heal without excess cholesterol accumulation. We found that transplantation of myelin into neonatal lesions disrupts healing with excessive cholesterol accumulation, persistent macrophage activation, and fibrosis. Myelin internalization suppresses macrophage apoptosis mediated by CD5L expression, indicating that myelin-derived cholesterol plays a critical role in impaired wound healing. Taken together, our data suggest that the central nervous system lacks an efficient approach for cholesterol clearance, resulting in excessive accumulation of myelin-derived cholesterol, thereby inducing scar formation after injury.

AC-electric-field-controlled multi-component droplet coalescence at microscale.

Droplet coalescence with fast response, high controllability and monodispersity has been widely investigated in industrial production and bioengineering. Especially for droplets with multiple components, programmable manipulation of such droplets is crucial for practical applications. However, precise control of the dynamics can be challenging, owing to the complex boundaries and the interfacial and fluidic properties. AC electric fields, with their fast response and high flexibility, have attracted our interest. We design and fabricate an improved flow-focusing microchannel configuration together with a non-contact type of electrode featuring asymmetric geometries, based on which we conduct systematic investigations of the AC-electric-field-controlled coalescence of multi-component droplets at the microscale. Parameters such as flow rates, component ratio, surface tension, electric permittivity and conductivity were given our attention. The results show that droplet coalescence in different flow parameters can be achieved in milliseconds by adjusting the electrical conditions, which shows high controllability. Specifically, both the coalescence region and reaction time can be adjusted by a combination of applied voltage and frequency, and unique merging phenomena have appeared. One is contact coalescence with the approach of paired droplets, while the other is squeezing coalescence, which occurs in the start position and promotes the merging process. The fluid properties, such as the electric permittivity, conductivity and surface tension, present a significant influence on merging behavior. The increasing relative dielectric constant leads to a dramatic reduction of the start merging voltage from the original 250 V to 30 V. The range of effective voltage for coalescence decreases with the addition of surfactant, offering a stricter and yet higher selectivity on electrical conditions, about 1500 V. The conductivity presents a negative correlation with the start merging voltage due to the reduction of the dielectric stress, from 400 V to 1500 V. Finally, we achieve the precise fabrication process of the Janus droplet via implementation of the proposed method, where the components of the droplets and the coalescence conditions are well controlled. Our results can serve as a potent methodology to decipher the physics of multi-component droplet electro-coalescence and contribute to applications in chemical synthesis, bioassay and material synthesis.

Irrigation Scheduling for Maize under Different Hydrological Years in Heilongjiang Province, China.

Appropriate irrigation schedules could minimize the existing imbalance between agricultural water supply and crop water requirements (ETc), which is severely impacted by climate change. In this study, different hydrological years (a wet year, normal year, dry year, and an extremely dry year) in Heilongjiang Province were calculated by hydrological frequency methods. Then, the single crop coefficient method was used to calculate the maize ETc, based on the daily meteorological data of 26 meteorological stations in Heilongjiang Province from 1960 to 2020. Afterward, the CROPWAT model was used to calculate the effective precipitation (Pe) and irrigation water requirement (Ir), and formulate the irrigation schedules of maize in Heilongjiang Province under different hydrological years. The results showed that ETc and Ir decreased first and then increased from west to east. The Pe and crop water surplus deficit index increased first and then decreased from west to east in Heilongjiang Province. Meanwhile, the average values of the Ir in were 171.14 mm, 232.79 mm, 279.08 mm, and 334.47 mm in the wet year, normal year, dry year, and extremely dry year, respectively. Heilongjiang Province was divided into four irrigation zones according to the Ir of different hydrological years. Last, the irrigation quotas for the wet year, normal year, dry year, and extremely dry year were 0~180 mm, 20~240 mm, 60~300 mm, and 80~430 mm, respectively. This study provides reliable support for maize irrigation practices in Heilongjiang Province, China.

Target Density Effects on Charge Transfer of Laser-Accelerated Carbon Ions in Dense Plasma.

We report on charge state measurements of laser-accelerated carbon ions in the energy range of several MeV penetrating a dense partially ionized plasma. The plasma was generated by irradiation of a foam target with laser-induced hohlraum radiation in the soft x-ray regime. We use the tricellulose acetate (C_{9}H_{16}O_{8}) foam of 2 mg/cm^{3} density and 1 mm interaction length as target material. This kind of plasma is advantageous for high-precision measurements, due to good uniformity and long lifetime compared to the ion pulse length and the interaction duration. We diagnose the plasma parameters to be T_{e}=17 eV and n_{e}=4×10^{20} cm^{-3}. We observe the average charge states passing through the plasma to be higher than those predicted by the commonly used semiempirical formula. Through solving the rate equations, we attribute the enhancement to the target density effects, which will increase the ionization rates on one hand and reduce the electron capture rates on the other hand. The underlying physics is actually the balancing of the lifetime of excited states versus the collisional frequency. In previous measurement with partially ionized plasma from gas discharge and z pinch to laser direct irradiation, no target density effects were ever demonstrated. For the first time, we are able to experimentally prove that target density effects start to play a significant role in plasma near the critical density of Nd-glass laser radiation. The finding is important for heavy ion beam driven high-energy-density physics and fast ignitions. The method provides a new approach to precisely address the beam-plasma interaction issues with high-intensity short-pulse lasers in dense plasma regimes.

Genome-wide profiling of rice Double-stranded RNA-Binding Protein 1-associated RNAs by targeted RNA editing.

RNA-binding proteins (RBPs) play essential roles in regulating gene expression. However, the RNA ligands of RBPs are poorly understood in plants, not least due to the lack of efficient tools for genome-wide identification of RBP-bound RNAs. An RBP-fused adenosine deaminase acting on RNA (ADAR) can edit RBP-bound RNAs, which allows efficient identification of RNA ligands of RBPs in vivo. Here, we report the RNA editing activities of the ADAR deaminase domain (ADARdd) in plants. Protoplast experiments indicated that RBP-ADARdd fusions efficiently edited adenosines within 41 nucleotides (nt) of their binding sites. We then engineered ADARdd to profile the RNA ligands of rice (Oryza sativa) Double-stranded RNA-Binding Protein 1 (OsDRB1). Overexpressing the OsDRB1-ADARdd fusion protein in rice introduced thousands of A-to-G and T-to-C RNA‒DNA variants (RDVs). We developed a stringent bioinformatic approach to identify A-to-I RNA edits from RDVs, which removed 99.7% to 100% of background single-nucleotide variants in RNA-seq data. This pipeline identified a total of 1,798 high-confidence RNA editing (HiCE) sites, which marked 799 transcripts as OsDRB1-binding RNAs, from the leaf and root samples of OsDRB1-ADARdd-overexpressing plants. These HiCE sites were predominantly located in repetitive elements, 3'-UTRs, and introns. Small RNA sequencing also identified 191 A-to-I RNA edits in miRNAs and other sRNAs, confirming that OsDRB1 is involved in sRNA biogenesis or function. Our study presents a valuable tool for genome-wide profiling of RNA ligands of RBPs in plants and provides a global view of OsDRB1-binding RNAs.

A hybrid multi-objective optimization of functional ink composition for aerosol jet 3D printing via mixture design and response surface methodology.

The limited electrical performance of microelectronic devices caused by low inter-particle connectivity and inferior printing quality is still the greatest hurdle to overcome for Aerosol jet printing (AJP) technology. Despite the incorporation of carbon nanotubes (CNTs) and specified solvents into functional inks can improve inter-particle connectivity and ink printability respectively, it is still challenging to consider multiple conflicting properties in mixture design simultaneously. This research proposes a novel hybrid multi-objective optimization method to determine the optimal functional ink composition to achieve low electrical resistivity and high printed line quality. In the proposed approach, silver ink, CNTs ink and ethanol are blended according to mixture design, and two response surface models (ReSMs) are developed based on the Analysis of Variance. Then a desirability function method is employed to identify a 2D optimal operating material window to balance the conflicting responses. Following that, the conflicting objectives are optimized in a more robust manner in the 3D mixture design space through the integration of a non-dominated sorting genetic algorithm III (NSGA-III) with the developed ReSMs and the corresponding statistical uncertainty. Experiments are conducted to validate the effectiveness of the proposed approach, which extends the methodology of designing materials with multi-component and multi-property in AJP technology.

Onchidium struma polysaccharides exhibit hypoglycemic activity and modulate the gut microbiota in mice with type 2 diabetes mellitus.

Onchidium struma polysaccharides (OsPs) are natural biologically active compounds, and our previous work showed that they can inhibit the activity of α-glucosidase in vitro, showing potential hypoglycemic activity. However, the effects of OsPs on type 2 diabetes mellitus (T2DM) in vivo remain unknown. Thus, the anti-diabetic activity of OsPs was evaluated in the present study in diabetic mice. The results showed that OsPs can significantly ameliorate the features of T2DM in mice by improving the levels of fasting blood glucose (FBG), oral glucose tolerance test (OGTT), and pro-inflammatory factors, and ameliorating insulin resistance. Furthermore, OsPs can significantly improve biochemical indicators, decrease the contents of total cholesterol (TC) and triglyceride (TG), and reduce lipid accumulation in the liver. The possible mechanism of the prevention and treatment of T2DM by OsPs may involve the phosphoinositide 3-kinase (PI3K)/protein kinase B (AKT-1) signaling pathway. OsPs can regulate the dysbiosis of gut microbiota and reverse the abundance of Lactobacillus in mice with T2DM. Moreover, OsPs significantly increased the concentration of short-chain fatty acids (SCFAs) in mice with T2DM. Our results indicate that OsPs can be used as a novel food supplement for the prevention and treatment of T2DM.

Spatiotemporal variation of PM2.5-related preterm birth in China and India during 1990-2019 and implications for emission controls.

Preterm birth is the leading threat to neonatal health. The variation of PM2.5-associated preterm birth in China and India from 1990 through 2019 was estimated in this study. Meanwhile, four mitigation scenarios were proposed, and the corresponding PM2.5-related preterm birth was projected for 2030. Owing to differences in emission control policies and the effects of various factors (e.g., differences in population-control policies), the PM2.5 concentration and PM2.5-associated preterm birth in the two countries presented disparate spatiotemporal characteristics and variation trends during 1990-2019. The 30-year average of annual PM2.5-associated preterm birth in India was 1018 (95% confidence interval, 718-1289) thousand, which was much larger than in China (280 [196-358] thousand). To fight air pollution, China launched several control strategies in the past two decades, and the nationwide maternal exposure risk dramatically decreased after 2010. In contrast, India's air-pollution control measures and policies have not effectively mitigated the nationwide PM2.5 pollution. Under current mitigation measures and policies, the projected decrease in maternal exposure risk by 2030 is greater for China than India, and the scope for controlling air pollutant emissions and reducing maternal exposure risk is much large for India. The results of all four scenarios revealed that the annual PM2.5-associated preterm birth in the two countries is likely to decrease in the future. In particular, if China and India implement more robust emission control strategies than those currently, the number of associated preterm birth is projected to be more than 50% lower in 2030 compared with 2019 rates.

Effect of biomass burning on premature mortality associated with long-term exposure to PM2.5 in Equatorial Asia.

The health burden from exposure to ambient fine particulates (PM2.5) in Equatorial Asia is substantially affected by the peatland fires in Indonesia, but the long-term health effect of the fires on local inhabitants is unclear. In this study, PM2.5-associated excess mortality in Equatorial Asia over the past 30 years (1990-2019) was estimated and then the health effect of biomass burning was identified. The PM2.5-related death in Equatorial Asia almost tripled from 113 (95% confidence interval, 100-125) thousand in 1990 to 337 (300-373) thousand in 2019, with a rate of increase of 6.4 (6.2-6.9) thousand/yr. The intense biomass burning between 1990 and 2019 was estimated to have induced 317 (282-348) thousand excess deaths in the study regions, with excess deaths mainly occurring in the El Niño years, such as in 1997, 2006, 2015 and 2019. Although the remote sensing data and emission inventories both reveal that the effective control measures have reduced biomass burning intensity in Equatorial Asia (especially in Sumatra and Borneo), the corresponding health benefit has been offset by variations in demographic factors, i.e., population and age structure. Over the same period, fossil fuel emissions continued to increase rapidly. Thus, more stringent and ambitious policies are required to reduce the health burden from biomass burning and anthropogenic emissions simultaneously to maximize the health benefits from government measures and policies.