Rapid construction of tricyclic tetrahydrocyclopenta[4,5]pyrrolo[2,3-b]pyridine via isocyanide-based multicomponent reaction.

An efficient protocol for the synthesis of polyfunctionalized tetrahydrocyclopenta[4,5]pyrrolo[2,3-b]pyridine-3,4b,5,6,7(1H)-pentacarboxylates was developed by a three-component reaction. In the absence of any catalyst, the three-component reaction of alkyl isocyanides, dialkyl but-2-ynedioates and 5,6-unsubstituted 1,4-dihydropyridines in refluxing acetonitrile afforded polyfunctionalized tetrahydrocyclopenta[4,5]pyrrolo[2,3-b]pyridine-3,4b,5,6,7(1H)-pentacarboxylates in high yields and with high diastereoselectivity. The reaction was finished by in situ generation of activated 5-(alkylimino)cyclopenta-1,3-dienes from addition of alkyl isocyanide to two molecules of but-2-ynedioates and sequential formal [3 + 2] cycloaddition reaction with 5,6-unsubstituted 1,4-dihydropyridine.

Multiple factors trigger the formation and resuscitation of the VBNC state in alcohol-producing Klebsiella pneumoniae.

Klebsiella pneumoniae can enter a viable but nonculturable (VBNC) state to survive in unfavorable environments. Our research found that high-, medium-, and low-alcohol-producing K. pneumoniae strains are associated with nonalcoholic fatty liver disease. However, the presence of the three Kpn strains has not been reported in the VBNC state or during resuscitation. In this study, the effects of different strains, salt concentrations, oxygen concentrations, temperatures, and nutrients in K. pneumoniae VBNC state were evaluated. The results showed that high-alcohol-producing K. pneumoniae induced a slower VBNC state than medium-alcohol-producing K. pneumoniae, and low-alcohol-producing K. pneumoniae. A high-salt concentration and micro-oxygen environment accelerated the loss of culturability. Simultaneously, both real-time quantitative PCR and droplet digital PCR were developed to compare the quantitative comparison of three Kpn strain VBNC states by counting single-copy gene numbers. At 22°C or 37°C, the number of culturable cells decreased significantly from about 108 to 105-106 CFU/mL. In addition, imipenem, ciprofloxacin, polymyxin, and phiW14 inhibited cell resuscitation but could not kill VBNC-state cells. These results revealed that the different environments evaluated play different roles in the VBNC induction process, and new effective strategies for eliminating VBNC-state cells need to be further studied. These findings provide a better understanding of VBNC-state occurrence, maintenance, detection, and absolute quantification, as well as metabolic studies of resuscitation resistance and ethanol production.IMPORTANCEBacteria may enter VBNC state under different harsh environments. Pathogenic VBNC bacteria cells in clinical and environmental samples pose a potential threat to public health because cells cannot be found by routine culture. The alcohol-producing Kpn VBNC state was not reported, and the influencing factors were unknown. The formation and recovery of VBNC state is a complete bacterial escape process. We evaluated the influence of multiple induction conditions on the formation of VBNC state and recovery from antibiotic and bacteriophage inhibition, and established a sensitive molecular method to enumerate the VBNC cells single-copy gene. The method can improve the sensitivity of pathogen detection in clinical, food, and environmental contamination monitoring, and outbreak warning. The study of the formation and recovery of VBNC-state cells under different stress environments will also promote the microbiological research on the development, adaptation, and resuscitation in VBNC-state ecology.

Chromosome-scale genome assembly for soft-stem bulrush (Schoenoplectus tabernaemontani) confirms a clade-specific whole genome duplication in Cyperaceae.

Schoenoplectus tabernaemontani (C. C. Gmelin) Palla is a typical macrophyte in diverse wetland ecosystems. This species holds great potential in decontamination applications and carbon sequestration. Previous studies have shown that this species may have experienced recent polyploidization. This would make S. tabernaemontani a unique model to study the processes and consequences of whole genome duplications in the context of the well-documented holocentric chromosomes and dysploidy events in Cyperaceae. However, the inference was not completely solid because it lacked homology information which is essential to ascertain polyploidy. We present here the first chromosome-level genome assembly for S.tabernaemontani. By combining ONT long-reads and Illumina short-reads, plus chromatin conformation via the Hi-C method, we assembled a genome spanning 507.96 Mb, with 99.43% of Hi-C data accurately mapped to the assembly. The assembly contig N50 value was 3.62 Mb. The overall BUSCO score was 94.40%. About 68.94% of the genome was comprised of repetitive elements. 36994 protein-coding genes were predicted and annotated. Long terminal repeat retrotransposons (LTR-rts) accounted for approximate 26.99% of the genome, surpassing the content observed in most sequenced Cyperid genomes. Our well-supported haploid assembly comprised 21 pseudochromosomes, each harboring putative holocentric centromeres. Our findings corroborated a karyotype of 2n=2X=42. We also confirmed a recent whole genome duplication (WGD) occurring after the divergence between Schoenoplecteae and Bolboschoeneae. Our genome assembly expands the scope of sequenced genomes within the Cyperaceae family, encompassing the fifth genus. It also provides research resources on Cyperid evolution and wetland conservation.

Fecal microbiota transplantation provides insights into the consequences of transcriptome profiles and cell energy in response to circadian misalignment of chickens.

The circadian misalignment (CM) disordered circadian rhythms exert adverse effects on animals. Poultry as one of animals suffers health and welfare problems due to long-term lighting photoperiods caused by CM. However, the roles of CM on organ development, cell growth, metabolism and immune are still unclear in chickens. In this study, a Chinese dual-purpose native breed, was used to explore the effects of CM on transcriptomic pattern of brain and cell energy biogenesis, and further fecal microbiota transplantation (FMT) was applied to investigate its "therapy" effect from CM suffering. Our results showed that the CM led to stunting in brain and small intestine of chicken. CM decreased of cell proliferation, and energy production, mtDNA copies and expression of genes related to cell cycle or mitochondrial biogenetics, while it upregulated the reactive oxygen species (ROS) level and the sensitivity to inflammation. Interestingly, FMT rescued the organ developmental defects and cell dysfunctions induced by CM. Circadian misalignment brought about abnormal tissue and cell developments, energy biogenesis, and immune response in birds. This study provided a comprehensive perspective on understanding the regulation of CM and FMT on bird development and welfare.

Neuroanatomical dimensions in medication-free individuals with major depressive disorder and treatment response to SSRI antidepressant medications or placebo.

Major depressive disorder (MDD) is a heterogeneous clinical syndrome with widespread subtle neuroanatomical correlates. Our objective was to identify the neuroanatomical dimensions that characterize MDD and predict treatment response to selective serotonin reuptake inhibitor (SSRI) antidepressants or placebo. In the COORDINATE-MDD consortium, raw MRI data were shared from international samples (N = 1,384) of medication-free individuals with first-episode and recurrent MDD (N = 685) in a current depressive episode of at least moderate severity, but not treatment-resistant depression, as well as healthy controls (N = 699). Prospective longitudinal data on treatment response were available for a subset of MDD individuals (N = 359). Treatments were either SSRI antidepressant medication (escitalopram, citalopram, sertraline) or placebo. Multi-center MRI data were harmonized, and HYDRA, a semi-supervised machine-learning clustering algorithm, was utilized to identify patterns in regional brain volumes that are associated with disease. MDD was optimally characterized by two neuroanatomical dimensions that exhibited distinct treatment responses to placebo and SSRI antidepressant medications. Dimension 1 was characterized by preserved gray and white matter (N = 290 MDD), whereas Dimension 2 was characterized by widespread subtle reductions in gray and white matter (N = 395 MDD) relative to healthy controls. Although there were no significant differences in age of onset, years of illness, number of episodes, or duration of current episode between dimensions, there was a significant interaction effect between dimensions and treatment response. Dimension 1 showed a significant improvement in depressive symptoms following treatment with SSRI medication (51.1%) but limited changes following placebo (28.6%). By contrast, Dimension 2 showed comparable improvements to either SSRI (46.9%) or placebo (42.2%) (ß = -18.3, 95% CI (-34.3 to -2.3), P = 0.03). Findings from this case-control study indicate that neuroimaging-based markers can help identify the disease-based dimensions that constitute MDD and predict treatment response.

"Coir Raincoat"-Boosted Biomimetic Hydrogel for Efficient Solar Desalination and Wastewater Purification.

Solar-driven interfacial evaporation is an efficient method for purifying contaminated or saline water. Nonetheless, the suboptimal design of the structure and composition still necessitates a compromise between evaporation rate and service life. Therefore, achieving efficient production of clean water remains a key challenge. Here, a biomimetic dictyophora hydrogel based on loofah/carbonized sucrose@ZIF-8/polyvinyl alcohol is demonstrated, which can serve as an independent solar evaporator for clean water recovery. This special structural design achieves effective thermal positioning and minimal heat loss, while reducing the actual enthalpy of water evaporation. The evaporator achieves a pure water evaporation rate of 3.88 kg m-2 h-1 and a solar-vapor conversion efficiency of 97.16% under 1 sun irradiation. In comparison, the wastewater evaporation rate of the evaporator with ZIF-8 remains at 3.85 kg m-2 h-1 for 30 days, which is 16.3% higher than the light irradiation without ZIF-8. Equally important, the evaporator also showcases the capability to cleanse water from diverse sources of contaminants, including those with small molecules, oil, heavy metal ions, and bacteria, greatly improving the lifespan of the evaporator.

Psychometric evaluation of the Social Touch Questionnaire in Chinese adolescents.

Social touch promotes psychological well-being through inducing positive effects on social affiliation and stress alleviation, especially in adolescence. However, there is a scarcity of instruments available for evaluating adolescents' attitude toward social touch in China. The present study aimed to investigate the validity and reliability of the Social Touch Questionnaire (STQ) in Chinese adolescents. A total of 2839 high school students were enrolled, ranging in age from 11 to 19 years. The dimensions of the scale were conducted by exploratory factor analysis, and validated by confirmatory factor analysis. A three-factor model showed the best fit and consisted of the following subgroups: liking of informal social touch, liking of general social touch, and dislike of social touch. Furthermore, positive associations were found between social touch and interaction anxiety, fear of negative evaluation, depressive and anxiety symptoms, and sleep quality. Short-term prediction of dislike of social touch in anxiety symptoms was determined, while no significant predictor of depressive symptoms was found. The STQ demonstrates reliability and validity as a self-report questionnaire designed to assess behaviors and attitudes toward social touch. It effectively adapts to the nuances of the Chinese context among adolescents.

Deep learning framework for comprehensive molecular and prognostic stratifications of triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is the most challenging breast cancer subtype. Molecular stratification and target therapy bring clinical benefit for TNBC patients, but it is difficult to implement comprehensive molecular testing in clinical practice. Here, using our multi-omics TNBC cohort (N = 425), a deep learning-based framework was devised and validated for comprehensive predictions of molecular features, subtypes and prognosis from pathological whole slide images. The framework first incorporated a neural network to decompose the tissue on WSIs, followed by a second one which was trained based on certain tissue types for predicting different targets. Multi-omics molecular features were analyzed including somatic mutations, copy number alterations, germline mutations, biological pathway activities, metabolomics features and immunotherapy biomarkers. It was shown that the molecular features with therapeutic implications can be predicted including the somatic PIK3CA mutation, germline BRCA2 mutation and PD-L1 protein expression (area under the curve [AUC]: 0.78, 0.79 and 0.74 respectively). The molecular subtypes of TNBC can be identified (AUC: 0.84, 0.85, 0.93 and 0.73 for the basal-like immune-suppressed, immunomodulatory, luminal androgen receptor, and mesenchymal-like subtypes respectively) and their distinctive morphological patterns were revealed, which provided novel insights into the heterogeneity of TNBC. A neural network integrating image features and clinical covariates stratified patients into groups with different survival outcomes (log-rank P < 0.001). Our prediction framework and neural network models were externally validated on the TNBC cases from TCGA (N = 143) and appeared robust to the changes in patient population. For potential clinical translation, we built a novel online platform, where we modularized and deployed our framework along with the validated models. It can realize real-time one-stop prediction for new cases. In summary, using only pathological WSIs, our proposed framework can enable comprehensive stratifications of TNBC patients and provide valuable information for therapeutic decision-making. It had the potential to be clinically implemented and promote the personalized management of TNBC.

Revolutionizing cancer treatment: Harnessing the power of terrestrial microbial polysaccharides.

Cancer treatment faces numerous challenges, such as inadequate drug targeting, steep price tags, grave toxic side effects, and limited therapeutic efficacy. Therefore, there is an urgent need for a safe and effective new drug to combat cancer. Microbial polysaccharides, complex and diverse biological macromolecules, exhibit significant microbial variability and uniqueness. Studies have shown that terrestrial microbial polysaccharides possess a wide range of biological activities, including immune enhancement, antioxidant properties, antiviral effects, anti-tumour potential, and hypoglycemic functions. To delve deeper into the structure-activity relationship of these land-based microbial polysaccharides against cancer, we conducted a comprehensive review and analysis of anti-cancer literature published between 2020 and 2024. The anticancer efficacy of terrestrial microbial polysaccharides is influenced by multiple factors, including the microbial species, existing form, chemical structure, and polysaccharide purity. According to the literature, an optimal molecular weight and good water solubility are essential for demonstrating anticancer activity. Furthermore, the addition of mannose and galactose has been found to significantly enhance the anticancer properties of these polysaccharides. These insights will serve as a valuable reference for future research and progress in the field of cancer drug therapy, particularly with regards to terrestrial microbial polysaccharides.

Deep learning image reconstruction generates thinner slice iodine maps with improved image quality to increase diagnostic acceptance and lesion conspicuity: a prospective study on abdominal dual-energy CT.

BACKGROUND: To assess the improvement of image quality and diagnostic acceptance of thinner slice iodine maps enabled by deep learning image reconstruction (DLIR) in abdominal dual-energy CT (DECT). METHODS: This study prospectively included 104 participants with 136 lesions. Four series of iodine maps were generated based on portal-venous scans of contrast-enhanced abdominal DECT: 5-mm and 1.25-mm using adaptive statistical iterative reconstruction-V (Asir-V) with 50% blending (AV-50), and 1.25-mm using DLIR with medium (DLIR-M), and high strength (DLIR-H). The iodine concentrations (IC) and their standard deviations of nine anatomical sites were measured, and the corresponding coefficient of variations (CV) were calculated. Noise-power-spectrum (NPS) and edge-rise-slope (ERS) were measured. Five radiologists rated image quality in terms of image noise, contrast, sharpness, texture, and small structure visibility, and evaluated overall diagnostic acceptability of images and lesion conspicuity. RESULTS: The four reconstructions maintained the IC values unchanged in nine anatomical sites (all p > 0.999). Compared to 1.25-mm AV-50, 1.25-mm DLIR-M and DLIR-H significantly reduced CV values (all p < 0.001) and presented lower noise and noise peak (both p < 0.001). Compared to 5-mm AV-50, 1.25-mm images had higher ERS (all p < 0.001). The difference of the peak and average spatial frequency among the four reconstructions was relatively small but statistically significant (both p < 0.001). The 1.25-mm DLIR-M images were rated higher than the 5-mm and 1.25-mm AV-50 images for diagnostic acceptability and lesion conspicuity (all P < 0.001). CONCLUSIONS: DLIR may facilitate the thinner slice thickness iodine maps in abdominal DECT for improvement of image quality, diagnostic acceptability, and lesion conspicuity.

Development of a Recombinase-Aided Amplification Assay for the Rapid Detection of Candida auris.

Candida auris (C. auris) was first discovered in Japan in 2009 and has since spread worldwide. It exhibits strong transmission ability, high multidrug resistance, blood infectivity, and mortality rates. Traditional diagnostic techniques for C. auris have shortcomings, leading to difficulty in its timely diagnosis and identification. Therefore, timely and accurate diagnostic assays for clinical samples are crucial. We developed a novel, rapid recombinase-aided amplification (RAA) assay targeting the 18S rRNA, ITS1, 5.8S rRNA, ITS2, and 28S rRNA genes for C. auris identification. This assay can rapidly amplify DNA at 39 °C in 20 min. The analytical sensitivity and specificity were evaluated. From 241 clinical samples collected from pediatric inpatients, none were detected as C. auris-positive. We then prepared simulated clinical samples by adding 10-fold serial dilutions of C. auris into the samples to test the RAA assay's efficacy and compared it with that of real-time PCR. The assay demonstrated an analytical sensitivity of 10 copies/µL and an analytical specificity of 100%. The lower detection limit of the RAA assay for simulated clinical samples was 101 CFU/mL, which was better than that of real-time PCR (102-103 CFU/mL), demonstrating that the RAA assay may have a better detection efficacy for clinical samples. In summary, the RAA assay has high sensitivity, specificity, and detection efficacy. This assay is a potential new method for detecting C. auris, with simple reaction condition requirements, thus helping to manage C. auris epidemics.

Generating Synthetic Electronic Health Record Data Using Generative Adversarial Networks: Tutorial.

Synthetic electronic health record (EHR) data generation has been increasingly recognized as an important solution to expand the accessibility and maximize the value of private health data on a large scale. Recent advances in machine learning have facilitated more accurate modeling for complex and high-dimensional data, thereby greatly enhancing the data quality of synthetic EHR data. Among various approaches, generative adversarial networks (GANs) have become the main technical path in the literature due to their ability to capture the statistical characteristics of real data. However, there is a scarcity of detailed guidance within the domain regarding the development procedures of synthetic EHR data. The objective of this tutorial is to present a transparent and reproducible process for generating structured synthetic EHR data using a publicly accessible EHR data set as an example. We cover the topics of GAN architecture, EHR data types and representation, data preprocessing, GAN training, synthetic data generation and postprocessing, and data quality evaluation. We conclude this tutorial by discussing multiple important issues and future opportunities in this domain. The source code of the entire process has been made publicly available.

Uncovering the power of neurofeedback: a meta-analysis of its effectiveness in treating major depressive disorders.

Neurofeedback, a non-invasive intervention, has been increasingly used as a potential treatment for major depressive disorders. However, the effectiveness of neurofeedback in alleviating depressive symptoms remains uncertain. To address this gap, we conducted a comprehensive meta-analysis to evaluate the efficacy of neurofeedback as a treatment for major depressive disorders. We conducted a comprehensive meta-analysis of 22 studies investigating the effects of neurofeedback interventions on depression symptoms, neurophysiological outcomes, and neuropsychological function. Our analysis included the calculation of Hedges' g effect sizes and explored various moderators like intervention settings, study designs, and demographics. Our findings revealed that neurofeedback intervention had a significant impact on depression symptoms (Hedges' g = -0.600) and neurophysiological outcomes (Hedges' g = -0.726). We also observed a moderate effect size for neurofeedback intervention on neuropsychological function (Hedges' g = -0.418). As expected, we observed that longer intervention length was associated with better outcomes for depressive symptoms (ß = -4.36, P < 0.001) and neuropsychological function (ß = -2.89, P = 0.003). Surprisingly, we found that shorter neurofeedback sessions were associated with improvements in neurophysiological outcomes (ß = 3.34, P < 0.001). Our meta-analysis provides compelling evidence that neurofeedback holds promising potential as a non-pharmacological intervention option for effectively improving depressive symptoms, neurophysiological outcomes, and neuropsychological function in individuals with major depressive disorders.

The effects of alfacalcidol combined with calcitonin in the treatment of osteoporosis and its influence on levels of inflammation.

OBJECTIVE: To investigate the effectiveness of Alfacalcidol combined with Calcitonin in the treatment of osteoporosis and its influence on the degree of pain, bone metabolism indexes, bone mineral density and inflammatory factor levels. METHODS: In this retrospective study, 110 patients with osteoporosis treated in The Second Affiliated Hospital of Shandong First Medical University from January 2019 to June 2021 were selected as the study subjects. According to different treatment methods, these patients were divided into an observation group and a control group with 55 cases in each group. Patients from the control group were treated with the alfacalcidol capsules alone, while those from the observation group were treated with the alfacalcidol capsules combined with intramuscular calcitonin injection. Patients in both groups were treated for 6 months continuously. The treatment effect, visual analogue scale (VAS) score and Oswestry disability index (ODI), bone mineral density (BMD), serum markers levels such as calcium (Ca), phosphorus (P), alkaline phosphatase (ALP), tartrate-resistant acid phosphatase-5b (TRACP-5b), insulin-like growth factor (IGF-1), type I procollagen amino terminal propeptide (PINP) and ß-collagen special sequence (ß-Crosslaps), the levels of inflammatory factor including interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α), quality Life Questionnaire Core 30 (QLQ-C30) scores and incidences of adverse reactions were evaluated and compared between the two groups. RESULTS: The effective rate of patients in the observation group was 90.91%, which was significantly higher than 74.54% in the control group (P<0.05). There was no significant difference in the term of VAS score, ODI score, serum markers levels, bone mineral density, inflammatory levels, QLQ-C30 before treatment between the two groups. Compared with the control group, the post-treatment VAS score, ODI score, the levels of IL-6, TNF-α, TRACP-5b, PINP and ß-Crosslaps in the observation group were obviously lower, while the post-treatment QLQ-C30, bone mineral density, Ca, P, ALP, IGF-1 levels were significantly higher (all P<0.05). No statistical differences were found in the incidences of adverse reactions between the two groups (P>0.05). CONCLUSION: The combination of Alfacalcidol combined with Calcitonin is effective in the treatment of osteoporosis patients, which can effectively improve the levels of bone metabolism indexes and bone mineral density, alleviate the symptoms, enhance the life quality and reduce the levels of inflammation. Therefore, it is worth promoting.

Controllable Pseudospin Topological Add-Drop Filter Based on Magnetic-Optical Photonic Crystals.

We propose a controllable topological add-drop filter based on magnetic-optical photonic crystals. This add-drop filter is composed of two straight waveguides and a hexagonal photonic crystal ring resonator. The waveguide and ring resonator are constructed by three different honeycomb magnetic-optical photonic crystals. The expanded lattice is applied with an external magnetic field so that it breaks time-reversal symmetry and the analogous quantum spin Hall effect simultaneously. While the standard one and the compressed one are not magnetized and trivial, the straight waveguide supports pseudospin-down (or pseudospin-up) one-way states when the expanded lattice is applied with an external magnetic field of +H (or -H). The ring resonator possesses multiple resonant modes which can be divided into travelling modes and standing modes. By using the travelling modes, we have demonstrated the function of the add-drop filter and realized the output port control by changing the direction of the magnetic field. Moreover, a large tunable power ratio from near 0 to 52.6 is achieved by adjusting the strength of the external magnetic field. The structure has strong robustness against defects due to the topological protection property. These results have potential in wavelength division multiplexing systems and integrated topological optical devices.

Kinetics and Mechanism of the Singlet Oxygen Atom Reaction with Dimethyl Ether.

We combine in situ laser spectroscopy, quantum chemistry, and kinetic calculations to study the reaction of a singlet oxygen atom with dimethyl ether. Infrared laser absorption spectroscopy and Faraday rotation spectroscopy are used for the detection and quantification of the reaction products OH, H2O, HO2, and CH2O on submillisecond time scales. Fitting temporal profiles of products with simulations using an in-house reaction mechanism allows product branching to be quantified at 30, 60, and 150 Torr. The experimentally determined product branching agrees well with master equation calculations based on electronic structure data and transition state theory. The calculations demonstrate that the dimethyl peroxide (CH3OOCH3) generated via O-insertion into the C-O bond undergoes subsequent dissociation to CH3O + CH3O through energetically favored reactions without an intrinsic barrier. This O-insertion mechanism can be important for understanding the fate of biofuels leaking into the atmosphere and for plasma-based biofuel processing technologies.

What Is the Impact of Baseline Inflammatory and Hemostatic Indicators with the Risk of Mortality in Severe Inpatients with COVID-19: A Retrospective Study.

The purpose of the study was to investigate baseline inflammatory, hemostatic indicators and new-onset deep vein thrombosis (DVT) with the risk of mortality in COVID-19 inpatients. In this single-center study, a total of 401 COVID-19 patients hospitalized in Sir Run Run Shaw Hospital, Zhejiang University School of Medicine were enrolled from December 1, 2022 to January 31, 2023. The basic information, first laboratory examination results, imaging examination, and outcome-related indicators were compared between patients in the moderate and severe subgroups. We found that baseline D-dimer and baseline absolute neutrophil count (ANC) levels were associated with new-onset DVT and death in severe hospitalized patients with COVID-19. The odds ratio (OR) of baseline D-dimer and baseline ANC with mortality was 1.18 (95% confidence interval [CI], 1.08-1.28; P < .001) and 1.13 (95% CI, 1.06-1.21; P < .001). Baseline ANC was associated with the risk of death in severe hospitalized COVID-19 patients, irrespective of the DVT status. In addition, a significantly higher serum neutrophil activity was observed in severe COVID-19 inpatients with DVT or those deceased during hospital stay. New-onset DVT partially mediated the association between baseline D-dimer (indirect effect: 0.011, estimated mediating proportion: 67.0%), baseline ANC (indirect effect: 0.006, estimated mediating proportion: 48.7%), and mortality in severe hospitalized patients with COVID-19. In summary, baseline D-dimer and baseline absolute neutrophil count (ANC) levels were associated with the mortality in severe hospitalized patients with COVID-19, especially DVT inpatients. New-onset DVT partially mediated the association between baseline D-dimer, baseline ANC, and mortality in severe hospitalized patients with COVID-19.

Global variability in atmospheric new particle formation mechanisms.

A key challenge in aerosol pollution studies and climate change assessment is to understand how atmospheric aerosol particles are initially formed1,2. Although new particle formation (NPF) mechanisms have been described at specific sites3-6, in most regions, such mechanisms remain uncertain to a large extent because of the limited ability of atmospheric models to simulate critical NPF processes1,7. Here we synthesize molecular-level experiments to develop comprehensive representations of 11 NPF mechanisms and the complex chemical transformation of precursor gases in a fully coupled global climate model. Combined simulations and observations show that the dominant NPF mechanisms are distinct worldwide and vary with region and altitude. Previously neglected or underrepresented mechanisms involving organics, amines, iodine oxoacids and HNO3 probably dominate NPF in most regions with high concentrations of aerosols or large aerosol radiative forcing; such regions include oceanic and human-polluted continental boundary layers, as well as the upper troposphere over rainforests and Asian monsoon regions. These underrepresented mechanisms also play notable roles in other areas, such as the upper troposphere of the Pacific and Atlantic oceans. Accordingly, NPF accounts for different fractions (10-80%) of the nuclei on which cloud forms at 0.5% supersaturation over various regions in the lower troposphere. The comprehensive simulation of global NPF mechanisms can help improve estimation and source attribution of the climate effects of aerosols.

The G932C mutation of chitin synthase 1 gene (CHS1) mediates buprofezin resistance as confirmed by CRISPR/Cas9-mediated knock-in approach in the brown planthopper, Nilaparvata lugens.

The brown planthopper (Nilaparvata lugens) is a major destructive rice pest in Asia. High levels of insecticide resistance have been frequently reported, and the G932C mutation in the chitin synthase 1 (CHS1) gene has been found to mediate buprofezin resistance. However, there has been no direct evidence to confirm the functional significance of the single G932C substitution mutation leading to buprofezin resistance in N. lugens. Here, we successfully constructed a knock-in homozygous strain (Nl-G932C) of N. lugens using CRISPR/Cas9 coupled with homology-directed repair (HDR). Compared with the background strain susceptible to buprofezin (Nl-SS), the knock-in strain (Nl-G932C) showed a 94.9-fold resistance to buprofezin. Furthermore, resistant strains (Nl-932C) isolated from the field exhibited a 2078.8-fold resistance to buprofezin, indicating that there are other mechanisms contributing to buprofezin resistance in the field. Inheritance analysis showed that the resistance trait is incomplete dominance. In addition, the Nl-G932C strain had a relative fitness of 0.33 with a substantially decreased survival rate, emergence rate, and fecundity. This study provided in vivo functional evidence for the causality of G932C substitution mutation of CHS1 with buprofezin resistance and valuable information for facilitating the development of resistance management strategies in N. lugens. This is the first example of using CRISPR/Cas9 gene-editing technology in a hemipteran insect to directly confirm the role of a candidate target site mutation in insecticide resistance.

Identifying Driving Factors of Atmospheric N2O5 with Machine Learning.

Dinitrogen pentoxide (N2O5) plays an essential role in tropospheric chemistry, serving as a nocturnal reservoir of reactive nitrogen and significantly promoting nitrate formations. However, identifying key environmental drivers of N2O5 formation remains challenging using traditional statistical methods, impeding effective emission control measures to mitigate NOx-induced air pollution. Here, we adopted machine learning assisted by steady-state analysis to elucidate the driving factors of N2O5 before and during the 2022 Winter Olympics (WO) in Beijing. Higher N2O5 concentrations were observed during the WO period compared to the Pre-Winter-Olympics (Pre-WO) period. The machine learning model accurately reproduced ambient N2O5 concentrations and showed that ozone (O3), nitrogen dioxide (NO2), and relative humidity (RH) were the most important driving factors of N2O5. Compared to the Pre-WO period, the variation in trace gases (i.e., NO2 and O3) along with the reduced N2O5 uptake coefficient was the main reason for higher N2O5 levels during the WO period. By predicting N2O5 under various control scenarios of NOx and calculating the nitrate formation potential from N2O5 uptake, we found that the progressive reduction of nitrogen oxides initially increases the nitrate formation potential before further decreasing it. The threshold of NOx was approximately 13 ppbv, below which NOx reduction effectively reduced the level of night-time nitrate formations. These results demonstrate the capacity of machine learning to provide insights into understanding atmospheric nitrogen chemistry and highlight the necessity of more stringent emission control of NOx to mitigate haze pollution.