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Abstract The precise extraction of winter wheat planting structure holds significant importance for food security risk assessment, agricultural resource management, and governmental decision-making. This study proposed a method for extracting the winter wheat planting structure by taking into account the growth phenology of winter wheat. Utilizing the fitting effect index, the optimal Savitzky–Golay (S–G) filtering parameter combination was determined automatically to achieve automated filtering and reconstruction of NDVI time series data. The phenological phases of winter wheat growth was identified automatically using a threshold method, and subsequently, a model for extracting the winter wheat planting structure was constructed based on three key phenological stages, including seeding, heading, and harvesting, with the combination of hierarchical classification principles. A priori sample library was constructed using historical data on winter wheat distribution to verify the accuracy of the extracted results. The validation of fitting effect on different surfaces demonstrated that the optimal filtering parameters for S–G filtering could be obtained automatically by using the fitting effect index. The extracted winter wheat phenological phases showed good consistency with ground-based observational results and MOD12Q2 phenological products. Validation against statistical yearbook data and the proposed priori knowledge base exhibited high statistical accuracy and spatial precision, with an extracting accuracy of 94.92%, a spatial positioning accuracy of 93.26%, and a kappa coefficient of 0.9228. The results indicated that the proposed method for winter wheat planting structure extracting can identify winter wheat areas rapidly and significantly. Furthermore, this method does not require training samples or manual experience, and exhibits strong transferability.

Abstract The dominant bacteria in the hindgut of calves play an important role in their growth and health, which could even lead to lifelong consequences. However, the identification of core probiotics in the hindgut and its mechanism regulating host growth remain unclear. Here, a total of 1045 fecal samples were analyzed by 16S rRNA gene sequencing from the 408 Holstein dairy calves at the age of 0, 14, 28, 42, 56, and 70 days to characterize the dynamic changes of core taxa. Moreover, the mechanisms of nutrient metabolism of calf growth regulated by core bacteria were investigated using multi-omics analyses. Finally, fecal microbiota transplantation (FMT) in mice were conducted to illustrate the potential beneficial effects of core bacteria. Four calf enterotypes were identified and enterotypes dominated by Bifidobacterium and Oscillospiraceae_UCG-005 were representative. The frequency of enterotype conversion shifted from variable to stable. The close relationship observed between phenotype and enterotype, revealing a potential pro-growth effect of Bifidobacterium, might be implemented by promoting the use of carbohydrate, activating the synthesis of volatile fatty acids, amino acids and vitamin B6, and inhibiting methane production in the hindgut. The FMT results indicated the beneficial effect of Bifidobacterium on host growth and hindgut development. These results support the notion that the Bifidobacterium-dominated fecal microbiome would be an important driving force for promoting the host growth in the early life. Our findings provide new insights into the potential probiotic mining and application strategies to promote the growth of young animals or improve their growth retardation.

Abstract Background Oncology nurses are considered the group with the highest risk for moral distress, compassion fatigue and burnout. Mindful self-care may help oncology nurses improve their well-being and solve psychological problems. However, the investigation and in-depth analysis of mindful self-care among oncology nurses in China is lacking. Objectives To identify heterogeneity groups of oncology nurses on mindful self-care ability and examine the sociodemographic correlation to these profiles. Design Cross-sectional descriptive study. Participants The study was carried out among oncology nurses in two affiliated comprehensive hospitals and one affiliated oncology hospital. A total of 839 oncology nurses were enrolled in this survey. Methods From January to May 2023, a cross-sectional study was carried out among oncology nurses using convenient sampling. The subjects were given the brief Mindful Self-Care Scale (B-MSCS) and the General Demographic Information Questionnaire. Latent profile analysis using the Mplus 7.4 program was used to separate oncology nurses’ mindful self-care into a variety of subgroups. The SPSS 25.0 statistical program was used to analyze the data. One-way ANOVA and the chi-square test were performed to compare the score of B-MSCS in each class and the difference in sociodemographic characteristics among the subgroups. Multinomial logistic regression was used to examine the influence of the sociodemographic variables on each class. Results The total score of the B-MSCS was 76.40 ± 13.19. The support structure dimension had the highest score, with an average mean value of 3.60, and physical care had the lowest score at 2.57. The findings of the latent profile analysis showed that respondents were divided into three classes, moderate mindful self-care(51.2%), low-low mindful relaxation(14.8%), and high-high mindfulness self-awareness(34.0%). Across scale scores and dimensions, three groups demonstrated statistically significant differences (p

Abstract Background Temperature extremes are anticipated to become more frequent and more intense under the context of climate change. While current evidence on health effects of compound extreme temperature event is scarce. Methods This nationwide cross-sectional study collected daily data on weather and mortality for 161 Chinese districts/counties during 2007-2013. A quasi-Poisson generalized linear model was first applied to assess effects of daytime-only, nighttime-only and compound daytime-nighttime heat wave (and cold spell) on cause-specific mortality. Then a random-effect meta-analysis was used to produce pooled estimates at national level. Stratification analyses were performed by relative humidity, individual and regional characteristics. Results Here we show that mortality risks of compound daytime-nighttime temperature extremes are much higher than those occurring only in the daytime or nighttime. Humid weather further exaggerates the mortality risk during heat waves, while dry air enhances the risk during cold weather. People who are elderly, illiterate, and those with ischemic heart disease and respiratory disease are particularly vulnerable to extreme temperature. At the community-level, population size, urbanization rate, proportion of elderly and PM2.5 are positively associated with increased risks associated with heat waves. Temperature, humidity and normalized difference vegetation index are positively associated with the effects of cold weather, with an opposite trend for latitude and diurnal temperature range. Conclusions This nationwide study highlights the importance of incorporating compound daytime-nighttime extreme temperature events and humid conditions into early warning systems and urban design/planning.

Abstract Background All the scoring methods for the DLQI miss the moderate impact of the disease on patients, which may underestimate the impact of psoriasis on patients’ quality of life. To improve the accuracy of the assessment of the Dermatology Life Quality Index score (DLQI) for patients with psoriasis, this study proposed and validated a new scoring method, the DLQI-NS, which includes the moderate impact option in the self-assessment of each item in psoriasis patients. Methods A cross-sectional study was conducted in which patients with psoriasis were enrolled. A total of 425 participants completed the DLQI, DLQI-NS and Skindex-16 questionnaires. Reliability, validity, ceiling and floor effects were evaluated of both DLQI and DLQI-NS questionnaires. Results About 14.4-32.5% of the patients reported a moderate impact on quality of life. The DLQI-NS allowed 17 more patients (4.0%) to achieve severe disease. The Cronbach’s alpha coefficient of the DLQI-NS was 0.90, and that of the DLQI was 0.89. The KMO test results for the DLQI-NS and DLQI were 0.927 and 0.916, respectively. One factor was identified for each questionnaire. The items of the DLQI-NS showed an item-total correlation from 0.52 to 0.82, and the DLQI questionnaire’s item-total correlation ranged from 0.47 to 0.83. The DLQI-NS, DLQI total score and Skindex-16 had Spearman’s rank correlation coefficients of 0.89 and 0.84, respectively. Both the DLQI-NS and DLQI showed significant moderate correlations with the BSA (0.51 vs. 0.50) and PASI (0.47 vs. 0.46). No ceiling effects were observed for any of the items of both questionnaires. Conclusion The validity and reliability of the DLQI-NS and DLQI were good, but the DLQI-NS was superior to the DLQI. The DLQI-NS is an effective self-assessment tool for assessing quality of life in psoriasis patients.

Abstract Manganese (Mn) is widely recognized owing to its low cost, non-toxic nature, and versatile oxidation states, leading to the emergence of various Mn-based nanomaterials with applications across diverse fields, particularly in tumor diagnosis and therapy. Systematic reviews specifically addressing the tumor diagnosis and therapy aspects of Mn-derived biomaterials are lacking. This review comprehensively explores the physicochemical characteristics and synthesis methods of Mn-derived biomaterials, emphasizing their role in tumor diagnostics, including magnetic resonance imaging, photoacoustic and photothermal imaging, ultrasound imaging, multimodal imaging, and biodetection. Moreover, the advantages of Mn-based materials in tumor treatment applications are discussed, including drug delivery, tumor microenvironment regulation, synergistic photothermal, photodynamic, and chemodynamic therapies, tumor immunotherapy, and imaging-guided therapy. The review concludes by providing insights into the current landscape and future directions for Mn-driven advancements in the field, serving as a comprehensive resource for researchers and clinicians.

This study investigated the effects of β-alanine (β-Ala) on rumen fermentation, nutrient digestibility, nitrogen (N) metabolism, plasma biochemical parameters, and rumen bacterial communities in beef steers. Six steers with initial liveweight of 252.8 ± 5.2 kg and 3 treatments of supplementing with 0, 30, or 60 g β-Ala per day to basal diet were allocated in a replicated 3 × 3 Latin square design. Each experimental period was 20 d, of which the first 15 d were for adaptation and the subsequent 5 d were for sampling. The results showed that β-Ala linearly increased the ruminal concentration of microbial crude protein (MCP) (P = 0.005), but it did not affect the ruminal concentrations of ammonia N and total volatile fatty acids (P > 0.10). β-Ala also linearly increased the dry matter (DM) (P = 0.009), organic matter (OM) (P = 0.017) and crude protein (CP) (P = 0.043) digestibility, tended to decrease the acid detergent fiber digestibility (P = 0.077), but it did not affect the neutral detergent fiber digestibility (P = 0.641). β-Ala quadratically increased the relative abundance of ruminal Bacteroidota (P = 0.021) at the phylum level, and increased Prevotella (P = 0.028) and Prevotellaceae_UCG-003 (P = 0.014), and decreased the relative abundance of NK4A214_group (P = 0.009) at the genus level. Feeding steers with β-Ala linearly increased the urinary N (P = 0.006), urea excretions (P = 0.002) and the N retention (P = 0.004), but it did not affect the N utilization efficiency (P = 0.120). β-Ala quadratically increased the plasma concentration of the total antioxidant capacity (P = 0.011) and linearly increased the plasma concentration of insulin-like growth factor-1 (P

ABSTRACT: We investigated the short- and long-term effects of different forage types supplemented in preweaning dairy calves on growth performance, blood metabolites, rumen fermentation, bacterial community, and milk production during first lactation. A total of 60 healthy 30-d-old female Holstein calves were blocked by birth date and body weight and randomly assigned to 1 of 3 groups (n = 20): normal milk and pelleted starter feeding (CON), supplemented with chopped oat hay (OAH; 75.0 g/d per calf [DM basis]), or alfalfa hay (ALF; 75.0 g/d per calf [DM basis]). The forage supplementation started when calves were 30 d old (d 1 of the experimental period) and ended when they were 73 d old (d 44 of the experimental period, when calves were weaned). Milk and feed intakes and fecal consistency scores were recorded daily. Growth performance, rumen fluid, and blood samples were collected biweekly. After weaning, all the calves were integrated with the same barn and diets. After calving, the milk production was recorded daily. During the experimental period, the OAH group had greater solid feed and total DM intakes and greater rumen pH than the CON group (P ≤ 0.04), but had lower forage intake and CP digestibility than the ALF group (P ≤ 0.04). The ALF group had higher rumen pH and blood BHB concentration (P ≤ 0.04), lower fecal score (P = 0.02), and greater ether extract digestibility (P = 0.02) than the CON group. The ALF and OAH groups had lower concentrations of ruminal total VFA (P = 0.01). Still, the ALF group had a greater proportion of acetate and a relative abundance of cellulose degradation-related bacteria (Lachnoclostridium_1 and Oribacterium) and a lower relative abundance of inflammation-related bacteria (Erysipelotrichaceae_UCG-009) in the rumen compared with CON. Interestingly, the average milk production from 6 to 200 DIM was greater in the ALF group (P < 0.01), even though no significant effects were found on the rumen fermentation parameters and blood metabolites at 200 DIM. Generally, alfalfa hay supplementation in preweaning dairy calves had positive effects in the short- and long-term for rumen development, health status, and future milk production.

Abstract Background Aging is a very complex physiological phenomenon, and sEVs are involved in the regulation of this mechanism. Serum samples from healthy individuals under 30 and over 60 years of age were collected to analyze differences in sEVs proteomics. Results Based on PBA analysis, we found that sEVs from the serum of elderly individuals highly express TACSTD2 and identified a subpopulation marked by TACSTD2. Using ELISA, we verified the upregulation of TACSTD2 in serum from elderly human and aged mouse. In addition, we discovered that TACSTD2 was significantly increased in samples from tumor patients and had better diagnostic value than CEA. Specifically, 9 of the 13 tumor groups exhibited elevated TACSTD2, particularly for cervical cancer, colon cancer, esophageal carcinoma, liver cancer and thyroid carcinoma. Moreover, we found that serum sEVs from the elderly (especially those with high TACSTD2 levels) promoted tumor cell (SW480, HuCCT1 and HeLa) proliferation and migration. Conclusion TACSTD2 was upregulated in the serum of elderly individuals and patients with tumors, and could serve as a dual biomarker for aging and tumors.

Osteoarthritis (OA), a common degenerative disease, is characterized by high disability and imposes substantial economic impacts on individuals and society. Current clinical treatments remain inadequate for effectively managing OA. Organoids, miniature 3D tissue structures from directed differentiation of stem or progenitor cells, mimic native organ structures and functions. They are useful for drug testing and serve as active grafts for organ repair. However, organoid construction requires extracellular matrix-like 3D scaffolds for cellular growth. Hydrogel microspheres, with tunable physical and chemical properties, show promise in cartilage tissue engineering by replicating the natural microenvironment. Building on prior work on SF-DNA dual-network hydrogels for cartilage regeneration, we developed a novel RGD-SF-DNA hydrogel microsphere (RSD-MS) via a microfluidic system by integrating photopolymerization with self-assembly techniques and then modified with Pep-RGDfKA. The RSD-MSs exhibited uniform size, porous surface, and optimal swelling and degradation properties. In vitro studies demonstrated that RSD-MSs enhanced bone marrow mesenchymal stem cells (BMSCs) proliferation, adhesion, and chondrogenic differentiation. Transcriptomic analysis showed RSD-MSs induced chondrogenesis mainly through integrin-mediated adhesion pathways and glycosaminoglycan biosynthesis. Moreover, in vivo studies showed that seeding BMSCs onto RSD-MSs to create cartilage organoid precursors (COPs) significantly enhanced cartilage regeneration. In conclusion, RSD-MS was an ideal candidate for the construction and long-term cultivation of cartilage organoids, offering an innovative strategy and material choice for cartilage regeneration and tissue engineering.

A magnitude 7.3 earthquake occurred at 7:58 a.m. (Beijing time) on April 3, 2024, in the sea area of Hualien County, Taiwan Province, China (23.81°N，121.74°E), which had a large seismic hazard impact and attracted widespread attention at home and abroad. This paper introduces the geological and tectonic background of the earthquake and its disaster influence, as well as the volcanic activity on Kueishantao volcano that partially collapsed as a result of the seismic effect, and focuses on a comprehensive analysis of the possibility of whether the earthquake will trigger the volcanic activity. Through the analysis of seismic and hyperspectral gas data, it can be seen that the Kueishantao volcano has not yet shown obvious anomalous responses. Then the probability of triggering is quantitatively judged by introducing the non-dimensional index of earthquake triggering potential volcanoes，and the TRIGI value is 19.8 (> 10), which indicates that the probability of earthquake-triggered eruption of Kueishantao volcano is relatively low in the short term. At present, the volcano is still in the state of dormancy from the analysis of qualitative and quantitative aspects. In the future, we will continue to collect and improve macro and micro precursor anomaly data before volcanic eruption, track and judge the state of volcanic activity, and draw more accurate and reliable conclusions about the triggering possibility.

Abstract Background Osteoporosis is characterized by an imbalance in bone homeostasis, resulting in the excessive dissolution of bone minerals due to the acidified microenvironment mediated by overactive osteoclasts. Oroxylin A (ORO), a natural flavonoid, has shown potential in reversing osteoporosis by inhibiting osteoclast-mediated bone resorption. The limited water solubility and lack of targeting specificity hinder the effective accumulation of Oroxylin A within the pathological environment of osteoporosis. Results Osteoclasts’ microenvironment-responsive nanoparticles are prepared by incorporating Oroxylin A with amorphous calcium carbonate (ACC) and coated with glutamic acid hexapeptide-modified phospholipids, aiming at reinforcing the drug delivery efficiency as well as therapeutic effect. The obtained smart nanoparticles, coined as OAPLG, could instantly neutralize acid and release Oroxylin A in the extracellular microenvironment of osteoclasts. The combination of Oroxylin A and ACC synergistically inhibits osteoclast formation and activity, leading to a significant reversal of systemic bone loss in the ovariectomized mice model. Conclusion The work highlights an intelligent nanoplatform based on ACC for spatiotemporally controlled release of lipophilic drugs, and illustrates prominent therapeutic promise against osteoporosis.

Abstract In recent decades, there has been a significant increase in the application of single‐molecule electrical analysis platforms in studying proteins and peptides. These advanced analysis methods have the potential for deep investigation of enzymatic working mechanisms and accurate monitoring of dynamic changes in protein configurations, which are often challenging to achieve in ensemble measurements. In this work, the prominent research progress in peptide and protein‐related studies are surveyed using electronic devices with single‐molecule/single‐event sensitivity, including single‐molecule junctions, single‐molecule field‐effect transistors, and nanopores. In particular, the successful commercial application of nanopores in DNA sequencing has made it one of the most promising techniques in protein sequencing at the single‐molecule level. From single peptides to protein complexes, the correlation between their electrical characteristics, structures, and biological functions is gradually being established. This enables to distinguish different molecular configurations of these biomacromolecules through real‐time electrical monitoring of their life activities, significantly improving the understanding of the mechanisms underlying various life processes.

Abstract Additive manufacturing (AM) is widely recognized as a versatile tool for achieving complex geometries and customized functionalities in designed materials. However, the challenge lies in selecting an appropriate AM method that simultaneously realizes desired microstructures and macroscopic geometrical designs in a single sample. This study presents a direct ink writing method for 3D printing intricate, high‐fidelity macroscopic cellulose aerogel forms. The resulting aerogels exhibit tunable anisotropic mechanical and thermal characteristics by incorporating fibers of different length scales into the hydrogel inks. The alignment of nanofibers significantly enhances mechanical strength and thermal resistance, leading to higher thermal conductivities in the longitudinal direction (65 mW m−1 K−1) compared to the transverse direction (24 mW m−1 K−1). Moreover, the rehydration of printed cellulose aerogels for biomedical applications preserves their high surface area (≈300 m2 g−1) while significantly improving mechanical properties in the transverse direction. These printed cellulose aerogels demonstrate excellent cellular viability (>90% for NIH/3T3 fibroblasts) and exhibit robust antibacterial activity through in situ‐grown silver nanoparticles.

Perovskite light‐emitting diodes (LEDs) with advantages of high electroluminescence efficiency at high brightness, good color purity, and tunable bandgap, are believed to have potential applications in the next generation display and lighting technologies. Due to the complex degradation process, mathematic models to describe the degradation process of perovskite LEDs are absent. In this work, it is found that the mathematical fitting methods which have been widely used to describe the decay trend of organic LEDs and quantum‐dot LEDs, are unable to accurately predict the lifetime of perovskite LEDs. Then an ensemble machine learning model is developed, which utilizes data augmentation technique to predict T50 of perovskite LEDs based on features before T80, achieving an accuracy of 0.995. Furthermore, the model can also accurately predict the T90 lifetime of quantum‐dot LEDs (QLEDs) using features before T98, suggesting it is a useful tool to efficiently evaluate LED lifetimes.

Abstract Background The pupillary response to tetanic electrical stimulation reflects the balance between nociceptive stimulation and analgesia. Although pupillary pain index (PPI) was utilized to predict postoperative pain, it depended on tetanic stimulation and was complex. We aim to describe the potential relationship between PD in the presence of surgical stimulation and pain levels after awakening. Methods According to the Verbal Rating Scale (VRS) score after extubation, the patients were divided into painless group (VRS = 0) and pain group (VRS ≥ 1). Pupillary diameter (PD) and pupillary light reflex velocity (PLRV) were compared between two groups when patients entered the operating room (T1), before incision (T2), 10 s after incision (T3), 30 s after incision (T4), 1 h after incision (T5), at the end of surgery (T6), shortly after extubation (T7), and when patients expressed pain clearly (T8). The magnitude of PD change (ΔPD) compared to the baseline value after anesthesia induction (T2) was calculated. The correlations between pupillary parameters and pain after awakening were calculated. Results Patients with VRS ≥ 1 had greater PD than painless patients at T3-7 (P = 0.04, 0.04, 0.003,

In this study, the effects of L-arginine or L-lysine on the quality of duck meat patties during repeated freeze-thaw cycles were studied to provide a theoretical basis for the application of L-arginine or L-lysine as cryoprotectant in meat products. L-arginine or L-lysine was added in the marinating process of duck meat patties, and the prepared duck meat patties was treated with freeze-thaw cycles. The texture, cooking loss, color, pH, total volatile base nitrogen (TVB-N), thiobarbituric reactive substances (TBARS), low-field nuclear magnetic resonance, and microstructure were measured to evaluate the quality of duck meat patties. The results showed that with the increase of freeze-thaw cycles, the hardness, springiness, cohesiveness, chewiness, a* value, pH and P21 of duck meat patties in the blank group decreased significantly (P

In this paper, a characteristic mode (CM)-based design methodology is developed for the reconfigurable microwave metasurface absorbers (MMA) with using commercially available substrates. Theoretical intrinsic connection between modal behaviors and absorption properties is first formulated for the design of the structures. As a proof of the method, a broadband MMA consisting of butterfly elements is step-by-step designed. The positions and values of the impedance loading are determined based on the modal significances and modal currents for broadband operation. The absorption performance is evaluated by the formulated theoretical model and verified by full-wave simulation. After that, a flexible implementation a employed for free-form surfaces conformal. Experimentally, the proposed MMA is fabricated and measured. The absorption fractional bandwidth with reflectivity less than –10 dB is achieved from 3.6 to 11.6 GHz (105%). Good agreements between the simulation and measurement results for both planar and cylindrical cases validate the developed CM-based design methodology. The mimicry of time-varying scattering cross section (SCS) is then further realized through real-time coding absorption states, which is a promising candidate for practical electromagnetic systems.

Abstract Fetal growth restriction (FGR), a leading cause of perinatal morbidity and mortality, is caused by fetal, maternal, and placental factors. Uniparental disomy (UPD) is a rare condition that leads to imprinting effects, low-level mosaic aneuploidies and homozygosity for pathogenic variants. In the present study, UPD events were detected in 5 women with FGR by trio exome sequencing (trio-WES) of a cohort of 150 FGR cases. Furthermore, noninvasive prenatal testing results of the 5 patients revealed a high risk of rare autosomal trisomy. Trio-WES showed no copy-number variations (CNVs) or nondisease-causing mutations associated with FGR. Among the 5 women with FGR, two showed gene imprinting, and two exhibited confined placental mosaicism (CPM) by copy number variant sequencing (CNV-seq). The present study showed that in FGR patients with UPD, the detection of imprinted genes and CPM could enhance the genetic diagnosis of FGR.

To investigate the effects of hydrolysis time (0, 20, 40, 60, 80 min) on the structure and functional properties of duck myofibrillar protein in low-salt solution, the duck myofibrillar protein was hydrolyzed by trypsin, the structure and functional properties of hydrolysate was assessed by analyzing the degree of hydrolysis, sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE), solubility, surface hydrophobicity, secondary structure, fluorescence spectrum, Zeta potential and emulsification after hydrolysis treatment. The results showed that in low-salt condition, with the prolongation of hydrolysis time, the solubility increased significantly (P

Current land use classification models based on very high-resolution (VHR) remote sensing images often suffer from high sample dependence and poor transferability. To address these challenges, we propose an unsupervised multisource domain adaptation framework for cross-domain land use classification that eliminates the need for repeatedly using source domain data. Our method uses the Swin Transformer as the backbone of the source domain model to extract features from multiple source domain samples. The model is trained on source domain samples, and unlabeled target domain samples are then used for target domain model training. To minimize the feature discrepancies between the source and target domains, we use a weighted information maximization loss and self-supervised pseudolabels to alleviate cross-domain classification noise. We conducted experiments on four public scene datasets and four new land use scene datasets created from different VHR images in four Chinese cities. Results show that our method outperformed three existing single-source cross-domain methods (i.e., DANN, DeepCORAL, and DSAN) and four multisource cross-domain methods (i.e., M3SDA, PTMDA, MFSAN, and SHOT), achieving the highest average classification accuracy and strong stability. We conclude that our method has high potential for practical applications in cross-domain land use classification using VHR images.

Mode-locked microcombs with flat spectral profiles provide the high signal-to-noise ratio and are in high demand for wavelength division multiplexing (WDM)-based applications, particularly in future high-capacity communication and parallel optical computing. Here, we present two solutions to generate local relatively flat spectral profiles. One microcavity with ultra-flat integrated dispersion is pumped to generate one relatively flat single soliton source spanning over 150 nm. Besides, one extraordinary soliton crystal with single vacancy demonstrates the local relatively flat microcomb lines when the inner soliton spacings are slightly irregular. Our work paves a new way for soliton-based applications owing to the relatively flat spectral characteristics.

Height map estimation from a single aerial image plays a crucial role in localization, mapping, and 3D object detection. Deep convolutional neural networks have been used to predict height information from single-view remote sensing images, but these methods rely on large volumes of training data and often overlook geometric features present in orthographic images. To address these issues, this study proposes a gradient-based self-supervised learning network with momentum contrastive loss to extract geometric information from non-labeled images in the pretraining stage. Additionally, novel local implicit constraint layers are used at multiple decoding stages in the proposed supervised network to refine high-resolution features in height estimation. The structural-aware loss is also applied to improve the robustness of the network to positional shift and minor structural changes along the boundary area. Experimental evaluation on the ISPRS benchmark datasets shows that the proposed method outperforms other baseline networks, with minimum MAE and RMSE of 0.116 and 0.289 for the Vaihingen dataset and 0.077 and 0.481 for the Potsdam dataset, respectively. The proposed method also shows around threefold data efficiency improvements on the Potsdam dataset and domain generalization on the Enschede datasets. These results demonstrate the effectiveness of the proposed method in height map estimation from single-view remote sensing images.

Digital information on sea ice extent, thickness, volume, and distribution is crucial for understanding Earth's climate system. The Snow and Ice Mass Balance Apparatus (SIMBA) is used to determine snow and ice temperatures in Arctic, Antarctic, ice-covered seas, and boreal lakes. Snow depth and ice thickness are derived from SIMBA temperature regimes (SIMBA_ET and SIMBA_HT). In warm conditions, SIMBA_ET temperature-based ice thickness may have errors due to the isothermal vertical profile. SIMBA_HT provides a visible ice-bottom interface for manual quantification. We propose an unmanned approach, combining neural networks, wavelet analysis, and Kalman filtering (NWK), to mathematically establish NWK and retrieve ice bottoms from various SIMBA_HT datasets. In the Arctic, NWK-derived total thickness showed a bias range of −5.64 cm to 4.01 cm and a correlation coefficient of 95%−99%. For Baltic Sea ice, values ranged from 1.31 cm to 2.41 cm (88%−98% correlation), and for boreal lake ice, −0.7 cm to 2.6 cm (75%−83% correlation). During ice growth, thermal equilibrium, and melting, the bias varied from −3.93 cm to 2.37 cm, −1.92 cm to 0.04 cm, and −4.90 cm to 3.96 cm, with correlation coefficients of 76%−99%. These results demonstrate NWK's robustness in retrieving ice bottom evolution in different water environments.

The lipid and flavor in milk are key factors that affect its quality, which profiles during donkey lactation are not yet clear. In this study, the lipids and volatile compounds (VOCs) in donkey milk from stages of lactation were analyzed by using LC-MS and GC-IMS. A total of 1774 lipids were identified in donkey milk, spanning over 6 major categories and attributed to 30 subclasses. The 233 differentially expressed lipids were identified between donkey colostrum and mature milk, which participate in 20 metabolic pathways, including glycerophospholipid, linoleic acid, and sphingolipid. Additionally, 35 VOCs in donkey milk were identified, including 28.57% aldehydes, 28.57% ketones, 25.71% esters, and 8.57% alcohols. Of these VOCs, 15 were determined to be characteristic flavors in donkey milk, mainly including methyl 2-methylbutanoate, 2-pentanone, and butyl acetate. 11 significantly different VOCs were found between the groups. Acetone, 2-heptanone, and ethyl acetate-m were considered potential discriminatory markers.

Background: The utilization of Tuina as a therapeutic intervention for the management of chronic pain has experienced a gradually increase in its popularity, and the purpose of this bibliometric analysis is to offer a comprehensive understanding of the current state and frontier trends, as well as to provide recommendations for future research directions. Methods: Publications on Tuina for chronic pain published between 2004 and 2023 were retrieved from the Web of Science Core Collection (WoSCC). Microsoft Excel, CiteSpace, VOSViewer, and the R package “bibliometrix” were used to quantitatively analyse the annual publication volume, countries/regions, journals, institutions, cited references, authors, and keywords. Results: A total of 287 publications were retrieved. The number of annual publications on the use of Tuina for treating chronic pain has gradually increased. Most publications were published in China and the United States. Notably, the most productive institution and author were identified as Shanghai University of Traditional Chinese Medicine and Min Fang, respectively. Medicine ranked first as the most influential affiliate and most productive journal. These publications came from 1650 authors, among whom Edzard Ernst had the most co-citations. Keyword analysis revealed that the new research frontier was low back pain. Conclusion: The utilization of Tuina for the treatment of chronic pain has been gaining increasing recognition. Acupuncture, randomised controlled trials, systematic reviews, etc. were the main research subjects. Furthermore, low back pain is the new research frontier. This study provides an in-depth perspective on Tuina for chronic pain, which provides valuable reference material for clinicians with insights of therapeutic strategy, educators with valuable topics, and researchers with new research directions.

In cities, green infrastructure (GI) is a vital natural life support system that is intimately linked to the daily lives of citizens. High levels of Urban Green Infrastructure (UGI) can help mitigate a series of ecological problems faced by cities, which is extremely important for preserving the stability of urban ecosystems and promoting sustainable urban development. However, current research has not fully explored the influencing factors of UGI and the interaction effect between them. Therefore, in order to better explore the results of China’s proposed policy to promote GI development, data from 110 cities in China’s Yangtze River Economic Belt (YREB) region during the 12th Five-Year Plan and 13th Five-Year Plan periods were measured separately, and natural and geographic environmental conditions, quality of urban construction, level of economic development, socio-cultural development, and eco-environmental quality were selected as the influencing factors. The entropy TOPSIS was used to evaluate the development trend of UGI in the two periods of the region, and the relationship between influencing factors and UGI development was investigated through the use of fs/QCA, and the high-level development path of each city to achieve GI was explained. The results show that (1) Cities with high UGI development are mostly concentrated in economically developed areas, while cities in the YREB’s central and western regions have relatively low levels of UGI development. (2) According to the spatial and temporal differences, the factors driving the high level and non-high level of UGI development in prefecture-level cities in the YREB showed several different configurations, confirming that the development level of UGI was affected by a variety of conditions. (3) During the 12th Five-Year Plan to 13th Five-Year Plan periods, the configuration of urban high-level UGI was found to be more consistent, while the development path of non-high-level UGI is more diversified. The study explores the overall development level and trend of green infrastructure in different cities, and the citation of fs/QCA provides a better understanding of the complex mechanisms of the interactions between these variables, with a view to providing some guidance and enlightenment for enhancing the future urban UGI development and urban high-quality development in the Yangtze River Economic Belt.

Phenological information on crop growth aids in identifying crop types from remote sensing images, but its incorporation into classification models is insufficiently exploited, especially in deep learning frameworks. This study presents a new model, Phenological-Temporal-Spatial LSTM (PST-LSTM), for mapping tobacco planting areas in smallholder farmlands using time-series Sentinel-1 Synthetic Aperture Radar (SAR) images. The PST-LSTM model is built on a multi-modal learning framework that fuses phenological information with deep spatial–temporal features. We applied the model to extract tobacco planting areas in Ninghua, Pucheng, and Shanghang Counties, in Fujian Province, and Luoping County in Yunnan Province, China. We compared PST-LSTM with existing methods based on phenological rules and Dynamic Time Warping (DTW) methods, and analyzed its strength in feature fusion. Results showed that our model outperformed these methods, achieving an overall accuracy (OA) of 93.16% compared to 86.69% and 85.93% for the phenological rules and DTW methods, respectively, in the Ninghua area. PST-LSTM effectively integrated time-series data with phenological information derived from different strategies at the feature level and performed better than existing feature fusion methods (based upon fuzzy sets) at the decision level. It also demonstrated a better spatial transferability than other methods when applied to different study areas, achieving an OA of 90.95%, 91.41%, and 80.75% for the Pucheng, Shanghang, and Luoping areas, respectively, using training samples from Ninghua. We conclude that PST-LSTM can effectively extract tobacco planting areas in smallholder farming from time-series SAR images and has the potential for mapping other crop types.

The rising incidence of defects in oral and maxillofacial tissues, linked to factors such as trauma, tumors, periodontal disease, and aging, poses significant challenges. Current treatments, involving autografts, allografts, and synthetic graft materials, face obstacles like secondary trauma, inflammation, and inadequate biocompatibility. Tissue engineering, integrating cell biology and material science since the 1990s, relies heavily on biomaterial scaffolds to promote cell adhesion, proliferation, and differentiation. Traditional scaffold fabrication, including 3D printing, methods lack precision, hindering effective tissue repair by controlling cell distribution and the extracellular matrix. Biomedical engineering advancements have introduced 3D bioprinting as an innovative solution, overcoming constraints of conventional scaffolds. 3D bioprinting technology enables rapid and precise reconstruction of damaged tissues with loaded cells, mimicking in vivo environments. This paper explores key 3D bioprinting technologies such as inkjet-based, extrusion-based, fused deposition modeling, laser-assisted, VAT photopolymerization, freeform reversible embedding of suspended hydrogels, and sacrificial template printing. The selection of materials with suitable mechanical and biological properties is crucial, considering the distinct requirements of each technique. This review provides a comprehensive survey of research progress on 3D printing biomaterial applications in craniofacial and dental tissue engineering, serving as a valuable reference for future medical research.

Drug Reaction with Eosinophilia and Systemic Symptoms (DRESS) is characterized by a widespread maculopapular rash, lymphadenopathy, fever, and multisystem involvement. Conversely, hemophagocytic lymphohistiocytosis (HLH) is an infrequent yet critical condition presenting with fever, hepatosplenomegaly, cytopenias, coagulation abnormalities, and elevated inflammatory markers. The overlapping clinical and laboratory features between DRESS and HLH poses a significant diagnostic challenge. Secondary HLH (sHLH) typically occurs in adults triggered by viral infections, malignancies, rheumatologic diseases, or immune deficiencies. Recently, COVID-19 has also been identified as one of the triggers for sHLH. Herein, we present a case of Sulfasalazine-induced DRESS coinfected with COVID-19 that subsequently progressed into HLH. Our patient exhibited common hepatorenal and splenic involvement along with rare cholecystitis and appendicitis. However, a significant improvement was observed upon the addition of etoposide and azathioprine. We hypothesize that excessive activation of the immune system and cytokine storm due to DRESS combined with COVID-19 infection led to more extensive systemic damage resulting in HLH development. This highlights the potential for severe consequences when DRESS coincides with HLH during a COVID-19 infection.

The ongoing coronavirus infectious disease (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) still urgently requires effective treatments. The 3C-like (3CL) protease of SARS-CoV-2 is a highly conserved cysteine protease that plays an important role in the viral life cycle and host inflammation, providing an ideal target for developing broad-spectrum antiviral drugs. Herein, we describe the discovery of a large number of herbs mainly produced in Heilongjiang Province, China, that exhibited different inhibitory activities against SARS-CoV-2 3CL protease. We confirmed that Syringa reticulata, which is used for clinical treatment of chronic bronchitis and asthma, is a specific and potent inhibitor of 3CL protease. A 70 % ethanol extract of S. reticulata dose-dependently inhibited the cleavage activity of 3CL protease in a fluorescence resonance energy transfer assay with an IC50 value of 0.0018 mg/mL, but had minimal effect in pseudovirus-based cell entry and luciferase-based RNA-dependent RNA polymerase assays. These results suggest that S. reticulata will be a potential leading candidate for COVID-19 treatment.

Abstract Background Postoperative delirium (POD) is a common complication in elderly patients after hip fracture surgery. Our study was to investigate whether intraoperative mean arterial pressure variability (MAPV) was associated with POD in elderly patients after hip fracture surgery. Methods In this retrospective cohort study, patients aged 65 years and older undergoing hip fracture surgery were included. The correlation between MAPV and POD was investigated using univariate and multivariate logistic regression. Covariate-related confounding effects were eliminated with propensity score matching (PSM) analysis. Then, a subgroup analysis was conducted to further examine the associations between MAPV and POD. Results Nine hundred sixty-three patients with a median age of 80 years (IQR: 73–84) were enrolled. POD occurred in 115/963 (11.9%) patients within 7 days after surgery. According to multivariate regression analysis, MAPV > 2.17 was associated with an increased risk of POD (OR: 2.379, 95% CI: 1.496–3.771, P

Background: Incidence rates of papillary thyroid cancer (PTC) have increased rapidly, with incidentally detected cancers contributing a large proportion. We aimed to explore the impact of incidental detection on thyroid cancer-specific and competing mortality among PTC patients. Methods: We conducted a retrospective cohort study of PTC patients at a cancer center in Guangzhou. Baseline information on detection route and other covariates were collected between 2010 and 2018, and death outcome was followed up for each patient. Cumulative incidence functions were used to estimate the mortality risk of thyroid cancer and competing risk. Cause-specific hazard models were the n utilized to explore the association between detection routes and PTC-specific and competing mortality. Results: Of the 2874 patients included, 2011 (70.0%) were detected incidentally, and the proportion increased from 36.9% in 2011 to 82.3% in 2018. During a median follow-up of 5.6 years, 42 deaths occurred, with 60% of them due to competing causes. The probability of competing mortality at 5 years in the non-incidental group and incidental group was 1.4% and 0.4%, respectively, and PTC-specific mortality in the non-incidental group and incidental group was 1.0% and 0.1%, respectively. After adjusting for covariates, the HRs of incidental detection were 0.13 (95% CI: 0.04–0.46; P = 0.01) and 0.47 (95% CI: 0.20–1.10; P = 0.10) on PTC-specific mortality and competing mortality, respectively. Conclusions: Incidental detection is associated with a lower risk of PTC-specific and competing mortality. Under the context of increasing magnitude of overdiagnosis, incorporation of detection route in clinical decision-making might be helpful to identify patients who might benefit from more extensive or conservative therapeutic strategies.

Numerical simulation is an effective research approach to assess the condition and predict the remaining service life of process pipelines suffering corrosion hazards. This work comprises a critical review of 182 academic articles to analyze environmental factors affecting the pipeline corrosion process, basic numerical methods for corrosion simulation, and single- and coupled-factor numerical investigations. Numerical simulation of corroded pipelines could combine the electrochemical corrosion processes and structural characteristics of pipelines to obtain more accurate results. Multiphysics-based techniques have been successfully applied to simulate the evolution process of corroded pipelines affected by two or more coupled factors under stray current interference. Through integration with learning-based algorithms, predictive studies are conducted to assess the development of corrosion. The challenge for current research is that the remaining types of corrosion are difficult to describe by numerical methods. Opportunities are proposed to improve the pipeline corrosion simulation model to describe more corrosion types and realistic corrosion morphologies, including time-varying corrosion simulation, random field in the simulation, and microelectrochemical corrosion simulation.

Abstract Laryngeal squamous cell carcinoma (LSCC) is one of the most commonly seen cancers in the head and neck region with increasing morbidity and mortality globally. N6-methyladenosine (m6A) modification plays a critical role in the carcinogenesis of LSCC. In this study, two datasets from online database were analyzed for differentially expressed genes (DEGs) between LSCC and normal samples. Furthermore, we carried out a series of experiments, including hematoxylin & eosin staining, immunohistochemical (IHC) staining, CCK-8, colony formation, transwell, flow cytometry, xenograft tumor model assays, actinomycin D assay, cycloheximide (CHX) assay, methylated m6A RNA immunoprecipitation (Me-RIP), RNA immunoprecipitation (RIP) assay, to verify the relevant findings in vivo and in vitro. Insulin like growth factor 2 mRNA binding protein 2 (IGF2BP2) was identified as an up-regulated m6A regulator in LSCC samples. Lower IGF2BP2 expression was linked to higher survival probability in LSCC and other head and neck squamous cell carcinoma patients. In LSCC cells, IGF2BP2 knockdown attenuated cancer cell aggressiveness, possibly through modulating cell cycle arrest. In the xenograft tumor model derived from IGF2BP2 knocked-down LSCC cells, IGF2BP2 knockdown inhibited tumor growth. IGF2BP2 up-regulated CDK6 expression through facilitating the stability of CDK6 mRNA and protein. CDK6 knockdown caused no changes in IGF2BP2 expression, but partially eliminated the promotive effects of IGF2BP2 overexpression on LSCC cells’ aggressiveness. Overexpressed IGF2BP2 in LSCC serves as an oncogenic factor, promoting LSCC cell proliferation and invasion in vitro and tumor growth in a xenograft tumor model in vivo through facilitating CDK6 mRNA stabilization.

Abstract Endonuclease G (ENDOG), a nuclear-encoded mitochondrial intermembrane space protein, is well known to be translocated into the nucleus during apoptosis. Recent studies have shown that ENDOG might enter the mitochondrial matrix to regulate mitochondrial genome cleavage and replication. However, little is known about the role of ENDOG in the cytosol. Our previous work showed that cytoplasmic ENDOG competitively binds with 14-3-3γ, which released TSC2 to repress mTORC1 signaling and induce autophagy. Here, we demonstrate that cytoplasmic ENDOG could also release Rictor from 14-3-3γ to activate the mTORC2-AKT-ACLY axis, resulting in acetyl-CoA production. Importantly, we observe that ENDOG could translocate to the ER, bind with Bip, and release IRE1a/PERK to activate the endoplasmic reticulum stress response, promoting lipid synthesis. Taken together, we demonstrate that loss of ENDOG suppresses acetyl-CoA production and lipid synthesis, along with reducing endoplasmic reticulum stress, which eventually alleviates high-fat diet-induced nonalcoholic fatty liver disease in female mice.

Diabetes mellitus is a chronically inflamed disease that predisposes to delayed fracture healing. Macrophages play a key role in the process of fracture healing by undergoing polarization into either M1 or M2 subtypes, which respectively exhibit pro-inflammatory or anti-inflammatory functions. Therefore, modulation of macrophage polarization to the M2 subtype is beneficial for fracture healing. Exosomes perform an important role in improving the osteoimmune microenvironment due to their extremely low immunogenicity and high bioactivity. In this study, we extracted the M2-exosomes and used them to intervene the bone repair in diabetic fractures. The results showed that M2-exosomes significantly modulate the osteoimmune microenvironment by decreasing the proportion of M1 macrophages, thereby accelerating diabetic fracture healing. We further confirmed that M2-exosomes induced the conversion of M1 macrophages into M2 macrophages by stimulating the PI3K/AKT pathway. Our study offers a fresh perspective and a potential therapeutic approach for M2-exosomes to improve diabetic fracture healing.

A miniaturized and wideband four-port multiple-input multiple-output (MIMO) antenna pair for Wi-Fi mobile terminals application is proposed. The proposed antenna pair consists of four multi-branch antenna elements arranged orthogonally, with an overall size of 40 × 40 × 3.5 mm3 and each antenna element size of 15.2 × 3.5 mm × 0.8 mm3. The performance of the proposed antenna shows the advantages of a wide frequency band, low mutual coupling, high efficiency, and a compact structure. The wideband characteristics of the antenna elements are achieved through multi-mode resonance. The suppression of coupling is accomplished by strategically positioning the four compact antenna elements to ensure their maximum radiation directions are orthogonal, thus eliminating the need for an additional decoupling structure. In this paper, the proposed antenna is optimized in terms of the parameters then simulated and measured. The simulated results illustrate that an impedance bandwidth of the antenna is about 15% (5.06~5.88 GHz) with S11 < −10 dB, excellent port isolation exceeds 20 dB between all ports, a high radiation efficiency ranges from 51.2% to 89.9%, the maximum gain is 4.5 dBi, and the ECCs are less than 0.04. The measured results show that the −10 dB impedance bandwidth of the antenna is about 13% (5.13~5.80 GHz), the isolation between the antenna elements is better than 21 dB, the radiation efficiency ranges from 51.8% to 92.3%, the maximum gain is 5.3 dBi, and the ECCs are less than 0.05. The proposed four-port MIMO antenna works on the 5G LTE band 46 and Wi-Fi 6E operating bands. As a mobile terminal antenna, the proposed design scheme demonstrates excellent performance and applicability, fulfilling the requirements for 5G mobile terminal applications.

Groupitizing is a well-established strategy in numerosity perception that enhances speed and sensory precision. Building on the ATOM theory, Anobile proposed the sensorimotor numerosity system, which posits a strong link between number and action. Previous studies using motor adaptation technology have shown that high-frequency motor adaptation leads to underestimation of numerosity perception, while low-frequency adaptation leads to overestimation. However, the impact of motor adaptation on groupitizing, and whether visual motion adaptation produces similar effects, remain unclear. In this study, we investigate the persistence of the advantage of groupitizing after motor adaptation and explore the effects of visual motion adaptation. Surprisingly, our findings reveal that proprioceptive motor adaptation weakens the advantage of groupitizing, indicating a robust effect of motor adaptation even when groupitizing is employed. Moreover, we observe a bidirectional relationship, as groupitizing also weakens the adaptation effect. These results highlight the complex interplay between motor adaptation and groupitizing in numerosity perception. Furthermore, our study provides evidence that visual motion adaptation also has an adaptation effect, but does not fully replicate the effects of proprioceptive motor adaptation on groupitizing. In conclusion, our research underscores the importance of groupitizing as a valuable strategy in numerosity perception, and sheds light on the influence of motion adaptation on this strategy.

In rice cultivation, the traits of semi-dwarfism and glutinous texture are pivotal for optimizing yield potential and grain quality, respectively. Xiangdaowan (XDW) rice, renowned for its exceptional aromatic properties, has faced challenges due to its tall stature and high amylose content, resulting in poor lodging resistance and suboptimal culinary attributes. To address these issues, we employed CRISPR/Cas9 technology to precisely edit the SD1 and Wx genes in XDW rice, leading to the development of stable genetically homozygous lines with desired semi-dwarf and glutinous characteristics. The sd1-wx mutant lines exhibited reduced gibberellin content, plant height, and amylose content, while maintaining hardly changed germination rate and other key agronomic traits. Importantly, our study demonstrated that exogenous GA3 application effectively promoted growth by compensating for the deficiency of endogenous gibberellin. Based on this, a semi-dwarf glutinous elite rice (Oryza sativa L.) Lines was developed without too much effect on most agronomic traits. Furthermore, a comparative transcriptome analysis unveiled that differentially expressed genes (DEGs) were primarily associated with the anchored component of the membrane, hydrogen peroxide catabolic process, peroxidase activity, terpene synthase activity, and apoplast. Additionally, terpene synthase genes involved in catalyzing the biosynthesis of diterpenoids to gibberellins were enriched and significantly down-regulated. This comprehensive study provides an efficient method for simultaneously enhancing rice plant height and quality, paving the way for the development of lodging-resistant and high-quality rice varieties.

BackgroundNitrogen dioxide (NO2) has been frequently linked to a range of diseases and associated with high rates of mortality and morbidity worldwide. However, there is limited evidence regarding the risk of NO2 on a spectrum of causes of mortality. Moreover, adjustment for potential confounders in NO2 analysis has been insufficient, and the spatial resolution of exposure assessment has been limited. ObjectiveThis study aimed to quantitatively assess the relationship between short-term NO2 exposure and death from a range of causes by adjusting for potential confounders in Guangzhou, China, and determine the modifying effect of gender and age. MethodsA time series study was conducted on 413,703 deaths that occurred in Guangzhou during the period of 2010 to 2018. The causes of death were classified into 10 categories and 26 subcategories. We utilized a generalized additive model with quasi-Poisson regression analysis using a natural cubic splines function with lag structure of 0 to 4 days to estimate the potential lag effect of NO2 on cause-specific mortality. We estimated the percentage change in cause-specific mortality rates per 10 μg/m3 increase in NO2 levels. We stratified meteorological factors such as temperature, humidity, wind speed, and air pressure into high and low levels with the median as the critical value and analyzed the effects of NO2 on various death-causing diseases at those high and low levels. To further identify potentially vulnerable subpopulations, we analyzed groups stratified by gender and age. ResultsA significant association existed between NO2 exposure and deaths from multiple causes. Each 10 μg/m3 increment in NO2 density at a lag of 0 to 4 days increased the risks of all-cause mortality by 1.73% (95% CI 1.36%-2.09%) and mortality due to nonaccidental causes, cardiovascular disease, respiratory disease, endocrine disease, and neoplasms by 1.75% (95% CI 1.38%-2.12%), 2.06% (95% CI 1.54%-2.59%), 2.32% (95% CI 1.51%-3.13%), 2.40% (95% CI 0.84%-3.98%), and 1.18% (95% CI 0.59%-1.78%), respectively. Among the 26 subcategories, mortality risk was associated with 16, including intentional self-harm, hypertensive disease, and ischemic stroke disease. Relatively higher effect estimates of NO2 on mortality existed for low levels of temperature, relative humidity, wind speed, and air pressure than with high levels, except a relatively higher effect estimate was present for endocrine disease at a high air pressure level. Most of the differences between subgroups were not statistically significant. The effect estimates for NO2 were similar by gender. There were significant differences between the age groups for mortality due to all causes, nonaccidental causes, and cardiovascular disease. ConclusionsShort-term NO2 exposure may increase the risk of mortality due to a spectrum of causes, especially in potentially vulnerable populations. These findings may be important for predicting and modifying guidelines for NO2 exposure in China.

With the development of conformable photonic platforms, particularly those that could be interfaced with the human body or integrated into wearable technology, there is an ever-increasing need for mechanically flexible optical photonic elements in soft materials. Here, we realize mechanically flexible liquid crystal (LC) waveguides using a combination of ultrafast direct laser writing and ultraviolet (UV) photo-polymerization. Results are presented that demonstrate that these laser-written waveguides can be either electrically switchable (by omitting the bulk UV polymerization step) or mechanically flexible. Characteristics of the waveguide are investigated for different fabrication conditions and geometrical configurations, including the dimensions of the waveguide and laser writing power. Our findings reveal that smaller waveguide geometries result in reduced intensity attenuation. Specifically, for a 10-μm-wide laser-written channel in a 14-μm-thick LC layer, a loss factor of −1.8 dB/mm at λ = 650 nm was observed. Following the UV polymerization step and subsequent delamination of the glass substrates, we demonstrate a free-standing flexible LC waveguide, which retains waveguide functionality even when bent, making it potentially suitable for on-skin sensors and other photonic devices that could interface with the human body. For the flexible LC waveguides fabricated in this study, the loss in a straight waveguide with a cross-sectional area of 20 μm × 20 μm was recorded to be −0.2 dB/mm. These results highlight the promising potential of electrically responsive and mechanically moldable optical waveguides using laser writing and UV-assisted polymer network formation.

ObjectiveThe purpose of this study was to investigate whether the combination of abnormal systemic immune-inflammation index (SII) levels and hyperglycemia increased the risk of cognitive function decline and reduced survival rate in the United States.MethodsThis cross-sectional study used data from the National Health and Nutrition Examination Survey (NHANES) database from 2011-2014 and enrolled 1,447 participants aged 60 years or older. Restricted cubic splines (RCS), linear regression and kaplan-meier(KM) curve were employed to explore the combined effects of abnormal SII and hyperglycemia on cognitive function and survival rate, and subgroup analysis was also conducted.ResultsThe RCS analysis revealed an inverted U-shaped relationship between lgSII levels and cognitive function. Linear regression analysis indicated that neither abnormal SII nor diabetes alone significantly contributed to the decline in cognitive function compared to participants with normal SII levels and blood glucose. However, when abnormal SII coexisted with diabetes (but not prediabetes), it resulted to a significant decline in cognitive function. After adjusting for various confounding factors, these results remained significant in Delayed Word Recall (β:-0.76, PConclusionThe findings suggest that the impact of diabetes on cognitive function/survival rate is correlated with SII levels, indicating that their combination enhances predictive power.

The use of multielectron Mn2+/MnO2 cathode reaction achieves high‐energy aqueous acid–base asymmetric hybrid batteries. However, the ion crossover through the membrane and the accumulation of unreacted MnO2 lead to serve potential and capacity decay of the cathode during cycling. Herein, the catholyte modulation using the KCl additive and the design of a Prussian blue/Berlin green (PB/BG) redox mediator on the cathode current collector are developed to promote high‐potential Mn2+/MnO2 reaction. The addition of saturated KCl greatly suppresses the ion crossover to maintain the catholyte acidity, thus enabling high‐potential Mn2+/MnO2 reaction and stable high‐voltage discharge plateau of ≈2.2 V for the hybrid battery at a prolonged cycling. The reversible MnO2 deposition is effectively improved by the PB/BG redox mediator, which contributes to significant enhancements in the reversible capacity, rate capability, and cycling stability of the cathode. Importantly, the as‐assembled hybrid battery exhibits the highest energy density of ≈260 Wh kg−1 (based on the mass of the aqueous MnCl2 catholyte and a hydrogen storage anode material) among the previously reported Mn‐based acid–base asymmetric batteries.

Abstract Data missing is a prevalent issue in various real‐world systems. It may deteriorate the performance of classification algorithms running on these platforms. Numerous effective imputation methods exist to address this problem. However, traditional data imputation approaches mainly focus on low‐dimensional missing data, and in addition, they do not make use of the randomness of the missing values and the information of labels simultaneously. To solve these problems, the authors propose a novel data imputation algorithm, named Particle Swarm Optimization for High‐dimensional mixed Missing variables data (PSOHM). PSOHM introduces a feature filtering algorithm for feature selection on missing data, followed by a feature discrimination method to categorize chosen features. PSOHM then employs particle swarm optimization to optimize imputation functions for both continuous and discrete features. Continuous features are modelled as Gaussian distributions, with the mean and standard deviation encoded into particles. Additionally, the probabilities of values for discrete features are also encoded. Moreover, accuracy serves as the optimization objective, utilizing both the randomness of missing values and the label information to improve the algorithm's performance. Six typical algorithms are employed to make a comparison. The results demonstrate that the authors’ method is superior to the compared approaches on the six different kinds of classical datasets.

Urban trees mitigate urban heat by altering evapotranspiration processes and providing shade to their surrounding environment. Nevertheless, the impact through which three-dimensional tree characteristics alleviate Land Surface Temperature (LST) remain uncertain, especially for climatic zone differences. In this study, we investigated the potential of trees to mitigate LST in 35 Chinese major cities and quantified the importance of diverse factors influencing the magnitude of cooling effects. Results showed that LST in tree-covered areas was about 2.23 °C lower than their surrounding built-up areas during summer, but an opposite temperature pattern was observed in winter and these cities are mostly distributed in Bs (arid-steppe) and Dw (cold-dry winter) climate zones. Moreover, we found that for every 1 m increase in tree height, LST decreased by ∼ 0.19 °C and ∼ 0.10 °C during summer and winter, respectively. Notably, we also found seasonal and climatic zone differences in the drivers of tree cooling intensity, with the digital elevation model (DEM = ∼13.21 %) as the key factor. These findings can help planners and architects better understand the effects of tree cooling, which can be a significant guide to reducing urban heat.

In the context of global warming and rapid urbanization, urban wind-heat environment has become increasingly prominent. Although the identification of ventilation corridors has been well investigated, the impact of ventilation corridors on thermal environment remains unclear. Here, we use the single-window algorithm and circuit theory method to analyze the characteristics of land surface temperature (LST) and ventilation corridors in four megacities of China, so as to quantify the effect of ventilation corridors on thermal environment. Results show that circuit theory works well for identifying ventilation corridors. Moreover, we find that spatial distribution of ventilation corridors in one city is remarkably different from another. Interestingly, ventilation corridors, which consist of green spaces, waters, and roads, have a remarkable mitigation effect on thermal environment. LST of each city is mitigated by 2.39 ℃, 3.22 ℃, 2.11 ℃ and 2.60 ℃, respectively, and the cooling intensity in summer is better than that in winter. Thus, it is of great significance to arrange urban form and ventilation corridors to alleviate the impact of high temperature on urban residents.

AbstractCOVID-19 has caused profound health, social, educational and economic devastation around the world, especially among the lives of adolescents in low- and middle-income countries. This paper looks at a wide array of outcomes impacting adolescents’ daily lives including health (mental, physical, sexual and reproductive health, vaccine perceptions and overlap between these topics), social relationships (family and peer), education and socio-economic disparities. Both scientific and grey literature between December 2019 and February 2022 were sought from PubMed, Google Scholar and organisations conducting research among adolescents, and coded. A total of 89 articles were included, 73% of which were peer-reviewed; 37% of the articles were from WHO’s Western Pacific region; 62% of the articles were cross-sectional; 75% were quantitative. Three major topics emerged in more than half the articles: mental health (72%), education (61%) and socio-economic ramifications (55%). However, there were regional differences in topics and many of them overlapped. The results indicate that, where there has been research, almost all findings have been linked to worse mental health during the pandemic. Overall, remote education was seen as a negative experience. The ramification of school closures on future aspirations, in particular early school leaving, highlights the importance of prioritising education during future pandemics based on the situation within the country. Gender and other disparities have made marginalised adolescents vulnerable to the economic ramifications of containment measures. Given the risks identified, there is a pressing need to put adolescents at the centre of establishing priorities for their health agenda for post-pandemic recovery.