Characterizing third-order intermodulation distortion of photodetectors based on de-coupling and de-embedding modulation distortion of modulators.

A novel, to the best of our knowledge, electro-optical modulation method is proposed for measuring third-order intermodulation distortion of photodetectors (PDs) based on de-coupling and de-embedding modulation distortion of modulators. The method utilizes dual parallel intensity modulation to generate electro-optical stimulus signals with fast and fine sweeping capability, and it eliminates the nonlinear impact of modulators by using low-frequency bias swing, allowing a direct extraction of the third-order output intercept point (OIP3) of PD from the combined nonlinear response contributed by both the modulators and the PD. The OIP3 of PD is frequency-swept measured with our method and compared to those with the conventional method to check for consistency. The proposed method enables a modulator-distortion-free, fast, and fine sweeping measurement of PDs using a simple system.

Source-risk and uncertainty assessment of trace metals in surface sediments of a human-dominated seaward catchment in eastern China.

Current total concentration-based methods for source attribution and risk assessment often overestimate metal risks, thereby impeding the formulation of effective risk management strategies. This study aims to develop a framework for source-specific risk assessment based on metal bioavailability in surface river sediments from a human-dominated seaward catchment in eastern China. Metal bioavailability was quantified using chemical fractionation results, and source apportionment was conducted using the positive matrix factorization (PMF) model. Risk assessment integrated these findings using two indices: the Potential Ecological Risk Index (PERI) and the Mean Probable Effect Concentration Quotient (mPEC-Q), with uncertainty addressed via Monte Carlo simulations. Results indicated that average total concentrations of Cu, Pb, Zn, Cr, Hg, Cd, and As exceeded their respective background levels by 1.63 to 15.00 times. The residual fraction constituted the majority, accounting for 53.84 % to 77.79 % of total concentrations, suggesting significant natural origins. However, source apportionment revealed a predominant contribution from anthropogenic activities, including industrial smelting, agricultural practices, and atmospheric deposition. The contributions were found to vary between 5.35 % and 40.03 % when the total concentration was adjusted to bioavailable content. Total concentration-based PERI/mPEC-Q assessments indicated high/moderate risk levels, decreasing to considerable/low risk levels with bioavailability adjustment. Hg and Cd were identified as priority metals. Further incorporating source appointment parameters into the risk assessment, industrial smelting was identified as the primary contributor, accounting for 66.06 % of total risk by total concentration and 65.63 % by bioavailability. This underscores the role of bioavailability in mitigating risk overestimation. Monte Carlo simulations validated industrial smelting as a major risk contributor. This study emphasizes the importance of considering bioavailability in the source-risk assessment of sediment-metals, crucial for targeted risk management in urbanized catchment areas.

Association of Short-term Pain and Chronic Pain Intensity With Cardiometabolic Multimorbidity Progression: A Multistate Markov Model Analysis.

BACKGROUND: The impact of pain intensity on the progression trajectories of cardiometabolic multimorbidity (CMM) is not well understood. We attempted to dissect the relationship of short-term pain (STP) and chronic pain intensity with the temporal progression of CMM. METHODS: We conducted a prospective cohort study based on the UK Biobank participants. Incident cases of cardiometabolic diseases (CMDs) were identified based on self-reported information and multiple health-related records in the UK Biobank. CMM was defined as the occurrence of at least 2 CMDs, including heart failure (HF), ischemic heart disease (IHD), stroke, and type 2 diabetes (T2D). The pain intensity was categorized into 5 levels based on pain duration and the number of sites involved, including chronic widespread pain (CWSP), chronic multilocation pain (CMLP), chronic single-location pain (CSLP), STP, and free-of-pain (FOP). Multistate models were used to assess the impact of pain intensity on the CMM trajectories from enrollment to initial cardiometabolic disease (ICMD), subsequently to CMM, and ultimately to death. RESULTS: A total of 429,145 participants were included. Over the course of a 12.8-year median follow-up, 13.1% (56,137/429,145) developed ICMD, 19.6% (10,979/56,137) further progressed to CMM, and a total of 5.3% (22,775/429,145) died. Compared with FOP, CMLP (hazard ratio [HR], 1.11; 95% confidence interval [CI], 1.06-1.17) and CWSP (HR, 1.26; 95% CI, 1.13-1.42) elevated the risk of transitioning from ICMD to CMM. STP (HR, 0.89; 95% CI, 0.82-0.96), CSLP (HR, 0.88; 95% CI, 0.82-0.95), and CMLP (HR, 0.87; 95% CI, 0.81-0.93) lowered the risk of transition from ICMD to mortality, and STP also reduced the risk of transition from enrollment to mortality (HR, 0.94; 95% CI, 0.89-0.98). The results of disease-specific transitions revealed that the influence of pain intensity varied across transitional stages. Specifically, CMLP and CWSP heightened the risk of conversion from T2D or IHD to CMM, whereas only CWSP substantially elevated the transition risk from HF to CMM. CONCLUSIONS: Our results highlighted reductions in chronic pain may mitigate both the onset and progression of CMM, potentially having an important impact on future revisions of cardiometabolic and pain-related guidelines.

Development of selective heterocyclic PDE4 inhibitors for treatment of psoriasis.

Psoriasis is a chronic autoimmune disease that badly affects the life quality of patients and their families. Inadequate efficacy, safety risks, high cost and low compliance of current psoriasis drugs urge development of novel small molecular drugs. In this study, two series of 37 novel compounds were designed and synthesized as inhibitors of phosphodiesterase 4 (PDE4) that specifically hydrolyzes second messenger cAMP and is an effective target for treatment of inflammatory diseases. Comprehensive structural-activity optimization led to finding of inhibitor 2e with IC50 = 2.4 nM for PDE4D and >4100-fold selectivity over other PDE families. Compound 2e inhibited the release of TNF-α (IC50 = 21.36 µM) and IL-6 (IC50 = 29.22 µM) in the LPS-stimulated Raw264.7 cells. Topical application of 2e exhibited remarkable therapeutic efficacy in imiquimod-induced psoriasis mice model, suggesting that 2e is a strong drug candidate for treatment of psoriasis.

Bio-organic substitution in tobacco (Nicotiana tabacum L) cultivation: Optimum strategy to lower carbon footprint and boost net ecosystem economic benefit.

The partial substitution of organic manure for chemical nitrogen fertilizers, known as organic substitution, is widely regarded as a cleaner and more sustainable production strategy. However, few studies have quantified greenhouse gas emissions, product income and net ecosystem economic benefit (NEEB) using a life cycle assessment (LCA) approach, particularly for typical tobacco (Nicotiana tabacum L.) production. Here, we quantified the yield and quality of a typical tobacco production in Qujing, Yunnan, China, through field experiments and calculated its carbon footprint and NEEB using the LCA approach. Four organic substitution strategies were established with equal nitrogen inputs, including synthesized chemical fertilizer (SN), farmyard organic manure (NF), commercial organic manure (NC), and bio-organic (Trichoderma viride Pers.) manure (NT), each substituting 15% of synthesized nitrogen fertilizer. Compared to the SN strategy, the NT strategy significantly increased yield and income by 10.3% and 9.6%, respectively. In contrast, the NF strategy significantly reduced income, while the NC strategy showed no significant difference. Both the NC and NT strategies significantly reduced N2O cumulative emissions (by 15.9% and 8.0%, respectively), increased δSOC (by 38.4% and 15.0%, respectively), and decreased carbon footprint compared to the SN strategy. However, the NF strategy significantly increased the income-scaled carbon footprint, even though it also notably reduced N2O cumulative emissions (by 22.6%) and increased δSOC (by 7.9%). The NT strategy achieved a win-win scenario of low environmental risk and high economic returns of tobacco production with significantly increased NEEB (by 10.6%) compared to the SN strategy (37.60 × 103 CNY yr-1). This suggests that the bio-organic Trichoderma manure substituting 15% synthesized nitrogen fertilizer is the best organic substitution strategy for sustainable tobacco production.

Excellent Low-Frequency Microwave Absorption and High Thermal Conductivity in Polydimethylsiloxane Composites Endowed by Hydrangea-Like CoNi@BN Heterostructure Fillers.

The advancement of thin, lightweight, and high-power electronic devices has increasingly exacerbated issues related to electromagnetic interference and heat accumulation. To address these challenges, a spray-drying-sintering process is employed to assemble chain-like CoNi and flake boron nitride (BN) into hydrangea-like CoNi@BN heterostructure fillers. These fillers are then composited with polydimethylsiloxane (PDMS) to develop CoNi@BN/PDMS composites, which integrate low-frequency microwave absorption and thermal conductivity. When the volume fraction of CoNi@BN is 44 vol% and the mass ratio of CoNi to BN is 3:1, the CoNi@BN/PDMS composites exhibit optimal performance in both low-frequency microwave absorption and thermal conductivity. These composites achieve a minimum reflection loss of -49.9 dB and a low-frequency effective absorption bandwidth of 2.40 GHz (3.92-6.32 GHz) at a thickness of 4.4 mm, fully covering the n79 band (4.4-5.0 GHz) for 5G communications. Meanwhile, the in-plane thermal conductivity (λ∥) of the CoNi@BN/PDMS composites is 7.31 W m-1 K-1, which is ≈11.4 times of the λ∥ (0.64 W m-1 K-1) for pure PDMS, and 32% higher than that of the (CoNi/BN)/PDMS composites (5.52 W m-1 K-1) with the same volume fraction of CoNi and BN obtained through direct mixing.

Microbiome Geographic Population Structure (mGPS) Detects Fine-Scale Geography.

Over the past decade, sequencing data generated by large microbiome projects showed that taxa exhibit patchy geographical distribution, raising questions about the geospatial dynamics that shape natural microbiomes and the spread of antimicrobial resistance (AMR) genes. Answering these questions requires distinguishing between local and non-local microorganisms and identifying the source sites for the latter. Predicting the source sites and migration routes of microbiota has been envisioned for decades but was hampered by the lack of data, tools, and understanding of the processes governing biodiversity. State-of-the-art biogeographical tools suffer from low resolution and cannot predict biogeographical patterns at a scale relevant to ecological, medical, or epidemiological applications. Analyzing urban, soil, and marine microorganisms, we found that some taxa exhibit regional-specific composition and abundance, suggesting they can be used as biogeographical biomarkers. We developed the Microbiome Geographic Population Structure (mGPS), a machine-learning-based tool that utilizes microbial relative sequence abundances to yield a fine-scale source site for microorganisms. mGPS predicted the source city for 92% of the samples and the within-city source for 82% of the samples, though they were often only a few hundred meters apart. mGPS also predicted soil and marine sampling sites for 86% and 74% of the samples, respectively. We demonstrated that mGPS differentiated local from non-local microorganisms and used it to trace the global spread of AMR genes. mGPS's ability to localize samples to their waterbody, country, city, and transit stations opens new possibilities in tracing microbiomes and has applications in forensics, medicine, and epidemiology.

Immune Cell Molecular Pharmacodynamics of Lanreotide in Relation to Treatment Response in Patients with Gastroenteropancreatic Neuroendocrine Tumors.

The CLARINET trial led to the approval of lanreotide for the treatment of patients with gastroenteropancreatic neuroendocrine tumors (NETs). It is hypothesized that lanreotide regulates proliferation, hormone synthesis, and other cellular functions via binding to somatostatin receptors (SSTR1-5) present in NETs. However, our knowledge of how lanreotide affects the immune system is limited. In vitro studies have investigated functional immune response parameters with lanreotide treatment in healthy donor T cell subsets, encompassing the breadth of SSTR expression, apoptosis induction, cytokine production, and activity of transcription factor signaling pathways. In our study, we characterized in vitro immune mechanisms in healthy donor T cells in response to lanreotide. We also studied the in vivo effects by looking at differential gene expression pre- and post-lanreotide therapy in patients with NET. Immune-focused gene and protein expression profiling was performed on peripheral blood samples from 17 NET patients and correlated with clinical response. In vivo, lanreotide therapy showed reduced effects on wnt, T cell receptor (TCR), and nuclear factor kappa-light-chain-enhancer of activated B cells (NF-kB) signaling in CD8+ T cells in responders compared to non-responders. Compared to non-responders, responders showed reduced effects on cytokine and chemokine signaling but greater effects on ubiquitination and proteasome degradation genes. Our results suggest significant lanreotide pharmacodynamic effects on immune function in vivo, which correlate with responses in NET patients. This is not evident from experimental in vitro settings.

Strategy of constructing D-A structure and accurate active sites over graphitic carbon nitride nanowires for high efficient photocatalytic nitrogen fixation.

Constructing photocatalysts for the stable and efficient production of NH3 is of excellent research significance and challenging. In this paper, the electron acceptor 5-amino-1,10-phenanthroline (AP) is introduced into the electron-donor graphitic carbon nitride (CN) framework by a simple heated copolymerization method to construct a donor-acceptor (D-A) structure. Subsequently, the phenanthroline unit is coordinated with transition metal Fe3+ ions to obtain the photocatalyst Fe(III)-0.5-AP-CN with better nitrogen fixation performance, and the average NH3 yield can reach 825.3 µmol g-1 h-1. Comprehensive experimental results and theoretical calculations show that the presence of the D-A structure can induce intramolecular charge transfer, effectively separating photogenerated electrons and holes. The Fe active sites can improve the chemisorption energy for N2, enhance the N-Fe bonding, and better activate the N2 molecule. Therefore, the synergistic effect between the construction of the D-A structure and the stably dispersed Fe active sites can enable CN to achieve high-performance N2 reduction to produce NH3.

High-risk screening for late-onset Pompe disease in China: An expanded multicenter study.

Late-onset Pompe disease (LOPD) is caused by a genetic deficiency of the lysosomal enzyme acid alpha-glucosidase (GAA), leading to progressive limb-girdle weakness and respiratory impairment. The insidious onset of non-specific early symptoms often prohibits timely diagnosis. This study aimed to validate the high-risk screening criteria for LOPD in the Chinese population. A total of 726 patients were included, including 96 patients under 14 years of age. Dried blood spots (DBS) and tandem mass spectrometry (MS/MS) were employed to evaluate serum GAA activity. Forty-four patients exhibited a decreased GAA activity, 16 (2.2%) of which were confirmed as LOPD by genetic testing. Three previously unreported GAA mutations were also identified. The median diagnostic delay was shortened to 3 years, which excelled the previous retrospective studies. At diagnosis, most patients exhibited impaired respiratory function and/or limb-girdle weakness. Elevated serum creatine kinase (CK) levels were more frequently observed in patients who manifested before age 16. Overall, high-risk screening is a feasible and efficient method to identify LOPD patients at an early stage. Patients over 1 year of age with either weakness in axial and/or proximal limb muscles, or unexplained respiratory distress shall be subject to GAA enzymatic test, while CK levels above 2 times the upper normal limit shall be an additional criterion for patients under 16. This modified high-risk screening criteria for LOPD requires further validation in larger Chinese cohorts.

Multifunctional microwave absorption materials: construction strategies and functional applications.

The widespread adoption of wireless communication technology, especially with the introduction of artificial intelligence and the Internet of Things, has greatly improved our quality of life. However, this progress has led to increased electromagnetic (EM) interference and pollution issues. The development of advanced microwave absorbing materials (MAMs) is one of the most feasible solutions to solve these problems, and has therefore received widespread attention. However, MAMs still face many limitations in practical applications and are not yet widely used. This paper presents a comprehensive review of the current status and future prospects of MAMs, and identifies the various challenges from practical application scenarios. Furthermore, strategies and principles for the construction of multifunctional MAMs are discussed in order to address the possible problems that are faced. This article also presents the potential applications of MAMs in other fields including environmental science, energy conversion, and medicine. Finally, an analysis of the potential outcomes and future challenges of multifunctional MAMs are presented.

Downregulation of autophagy is associated with poor clinical outcome after immunochemotherapy in patients with diffuse large B-cell lymphoma.

This study aimed to determine the expression levels of the autophagy markers Beclin-1 and p62 in patients with diffuse large B-cell lymphoma (DLBCL) and explore the association between autophagy and disease prognosis. The expression of Beclin-1 and p62 was investigated in patients with DLBCL and patients with reactive lymphoproliferative disease (RLD) using immunohistochemistry. The association between the clinical characteristics of patients with DLBCL and autophagy status was further analyzed. Beclin-1 levels were increased in RLD patients compared with those with DLBCL, but the difference was not statistically significant (p > 0.05). p62 levels in DLBCL patients were significantly higher than those in RLD patients (p < 0.05). Beclin-1 expression was associated only with the Ann Arbor stage (p < 0.05), whereas p62 expression was associated with the Ann Arbor stage, IPI score, extranodal involvement, and Ki-67 index (p < 0.05). Beclin-1 and p62 levels were not associated with short-term treatment efficacy in DLBCL patients. Survival analysis showed that Beclin-1 expression had no significant effect on 2-year progression-free survival (PFS) or overall survival (OS) (p > 0.05). However, high p62 expression in DLBCL patients was associated with reduced 2-year PFS compared with that of patients with low p62 expression (p < 0.05); the 2-year OS was not affected (p > 0.05). Our results demonstrate that autophagic activity affects the prognosis of DLBCL patients; the lower the autophagic activity, the shorter the PFS. Targeted p62 knockout may be a novel therapeutic strategy for the treatment of DLBCL patients.

A quadri-fluorescence SARS-CoV-2 pseudovirus system for efficient antigenic characterization of multiple circulating variants.

The ongoing co-circulation of multiple severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) strains necessitates advanced methods such as high-throughput multiplex pseudovirus systems for evaluating immune responses to different variants, crucial for developing updated vaccines and neutralizing antibodies (nAbs). We have developed a quadri-fluorescence (qFluo) pseudovirus platform by four fluorescent reporters with different spectra, allowing simultaneous measurement of the nAbs against four variants in a single test. qFluo shows high concordance with the classical single-reporter assay when testing monoclonal antibodies and human plasma. Utilizing qFluo, we assessed the immunogenicities of the spike of BA.5, BQ.1.1, XBB.1.5, and CH.1.1 in hamsters. An analysis of cross-neutralization against 51 variants demonstrated superior protective immunity from XBB.1.5, especially against prevalent strains such as "FLip" and JN.1, compared to BA.5. Our finding partially fills the knowledge gap concerning the immunogenic efficacy of the XBB.1.5 vaccine against current dominant variants, being instrumental in vaccine-strain decisions and insight into the evolutionary path of SARS-CoV-2.

Enrichment of novel entomopathogenic Pseudomonas species enhances willow resistance to leaf beetles.

BACKGROUND: Plants have evolved various defense mechanisms against insect herbivores, including the formation of physical barriers, the synthesis of toxic metabolites, and the activation of phytohormone responses. Although plant-associated microbiota influence plant growth and health, whether they play a role in plant defense against insect pests in natural ecosystems is unknown. RESULTS: Here, we show that leaves of beetle-damaged weeping willow (Salix babylonica) trees are more resistant to the leaf beetle Plagiodera versicolora (Coleoptera) than those of undamaged leaves. Bacterial community transplantation experiments demonstrated that plant-associated microbiota from the beetle-damaged willow contribute to the resistance of the beetle-damaged willow to P. versicolora. Analysis of the composition and abundance of the microbiome revealed that Pseudomonas spp. is significantly enriched in the phyllosphere, roots, and rhizosphere soil of beetle-damaged willows relative to undamaged willows. From a total of 49 Pseudomonas strains isolated from willows and rhizosphere soil, we identified seven novel Pseudomonas strains that are toxic to P. versicolora. Moreover, re-inoculation of a synthetic microbial community (SynCom) with these Pseudomonas strains enhances willow resistance to P. versicolora. CONCLUSIONS: Collectively, our data reveal that willows can exploit specific entomopathogenic bacteria to enhance defense against P. versicolora, suggesting that there is a complex interplay among plants, insects, and plant-associated microbiota in natural ecosystems.

[Etiology, Clinical Characteristics and Prognosis of Secondary Hemophagocytic Syndrome].

OBJECTIVE: To understand the etiology, clinical characteristics and prognosis of secondary hemophagocytic syndrome (HLH), so as to improve the understanding of HLH and reduce the rates of misdiagnosis and missed diagnosis of HLH. METHODS: A retrospective study was conducted to analyze the cause, clinical characteristics, laboratory findings, therapy and outcomes of 75 adult patients with secondary HLH admitted to our hospital from January 2015 to December 2021. Follow-up continued until the last discharge time. RESULTS: Among 75 patients, infection-related HLH was the most common (45.33%), followed by lymphoma-related HLH (17.33%). Fever was the most common clinical manifestation (97.67%). Laboratory indicators such as NK cell activity (98.31% low or absent), sCD25 (93.22% increased), and serum ferritin (94.44% elevated) had higher sensitivity in diagnosis. By comparing the clinical manifestations and laboratory indicators of HLH patients with different causes, sex, lymph node enlargement and bone marrow morphology were more valuable for the diagnosis of primary disease (all P <0.05). By comparing the treatment and clinical outcomes of HLH patients with different causes, the highest clinical remission rate (83.3%) was achieved in patients with autoimmune disease-related HLH treated with hormone+cyclosporine (P <0.05). The overall 12-month survival rate of all patients was 26.7%, in which the infection-related HLH was the lowest (14.7%) while autoimmune disease-related HLH was the highest (63.6%). CONCLUSION: The causes and clinical characteristics of adult secondary HLH are varied, with poor prognosis and heterogeneity in disease severity. It is important to identify HLH cause early for diagnosis and needed to further understand HLH.

MXene-based fibers: Preparation, applications, and prospects.

With the vigorous development and huge demand for portable wearable devices, wearable electronics based on functional fibers continue to emerge in a wide range of energy storage, motion monitoring, disease prevention, electromagnetic interference (EMI) shielding, etc. MXene, as an emerging two-dimensional inorganic compound, has shown great potential in functional fiber manufacturing and has attracted much research attention due to its own good mechanical properties, high electrical conductivity, excellent electrochemical properties and favorable processability. Herein, this paper reviews recent advances of MXene-based fibers. Speaking to MXene dispersions, the properties of MXene dispersions including dispersion stability, rheological properties and liquid crystalline properties are highlighted. The preparation techniques used to produce MXene-based fibers and application progress regarding MXene-based fibers into supercapacitors, sensors, EMI shielding and Joule heaters are summarized. Challenges and prospects surrounding the development of MXene-based fibers are proposed in future. This review aims to provide processing guidelines for MXene-based fiber manufacturing, thereby achieving more possibilities of MXene-based fibers in advanced applications with a view to injecting more vitality into the field of smart wearables.

Cytokinin catabolism and transport are involved in strigolactone-modulated rice tiller bud elongation fueled by phosphate and nitrogen supply.

Phosphate (P) and nitrogen (N) fertilization affect rice tillering, indicating that P- and N-regulated tiller growth has a crucial effect on grain yield. Cytokinins and strigolactones (SLs) promote and inhibit tiller bud outgrowth, respectively; however, the underlying mechanisms are unclear. In this study, tiller bud outgrowth and cytokinin fractions were evaluated in rice plants fertilized at different levels of P and N. Low phosphate or nitrogen (LP or LN) reduced rice tiller numbers and bud elongation, in line with low cytokinin levels in tiller buds and xylem sap as well as low TCSn:GUS expression, a sensitive cytokinin signal reporter, in the stem base. Furthermore, exogenous cytokinin (6-benzylaminopurin, 6-BA) administration restored bud length and TCSn:GUS activity in LP- and LN-treated plants to similar levels as control plants. The TCSn:GUS activity and tiller bud outgrowth were less affected by LP and LN supplies in SL-synthetic and SL-signaling mutants (d17 and d53) compared to LP- and LN-treated wild-type (WT) plants, indicating that SL modulate tiller bud elongation under LP and LN supplies by reducing the cytokinin levels in tiller buds. OsCKX9 (a cytokinin catabolism gene) transcription in buds and roots was induced by LP, LN supplies and by adding the SL analog GR24. A reduced response of cytokinin fractions to LP and LN supplies was observed in tiller buds and xylem sap of the d53 mutant compared to WT plants. These results suggest that cytokinin catabolism and transport are involved in SL-modulated rice tillering fueled by P and N fertilization.

Efficient control of root-knot nematodes by expressing Bt nematicidal proteins in root leucoplasts.

Root-knot nematodes (RKNs) are plant pests that infect the roots of host plants. Bacillus thuringiensis (Bt) nematicidal proteins exhibited toxicity to nematodes. However, the application of nematicidal proteins for plant protection is hampered by the lack of effective delivery systems in transgenic plants. In this study, we discovered the accumulation of leucoplasts (root plastids) in galls and RKN-induced giant cells. RKN infection causes the degradation of leucoplasts into small vesicle-like structures, which are responsible for delivering proteins to RKNs, as observed through confocal microscopy and immunoelectron microscopy. We showed that different-sized proteins from leucoplasts could be taken up by Meloidogyne incognita female. To further explore the potential applications of leucoplasts, we introduced the Bt crystal protein Cry5Ba2 into tobacco and tomato leucoplasts by fusing it with a transit peptide. The transgenic plants showed significant resistance to RKNs. Intriguingly, RKN females preferentially took up Cry5Ba2 protein when delivered through plastids rather than the cytosol. The decrease in progeny was positively correlated with the delivery efficiency of the nematicidal protein. In conclusion, this study offers new insights into the feeding behavior of RKNs and their ability to ingest leucoplast proteins, and demonstrates that root leucoplasts can be used for delivering nematicidal proteins, thereby offering a promising approach for nematode control.

Role of gut microbiota and metabolomics in the lipid-lowering efficacy of statins among Chinese patients with coronary heart disease and hypercholesterolemia.

Background: Statins, being the primary pharmacological intervention for hypercholesterolemia, exhibit a notable degree of interpatient variability in their effectiveness, which may be associated with gut microbiota. This study sought to identify the biomarkers for evaluating differences in statin efficacy. Methods: A quasi case-control study was conducted among participants with hypercholesterolemia and coronary heart disease taking rosuvastatin essential. According to the level of low density lipoprotein cholesterol (LDL-C), participants was divided into the "Up to standard" (US) group and the "Below standard" (BS) group. 16S rDNA sequencing and untargeted metabolomics were applied to detected the information of gut microbiota and related metabolites. Results: A total of 8 US and 8 BS group matched by age and sex were included in the final analysis. 16S rDNA sequencing results indicated that the characteristic strains of the US group were f-Eubacterium_coprostanoligenes and g-Papillibacter, while the characteristic flora of the BS group were o-C0119, g-Pseudolabrys, s-Dyella-Marensis and f-Xanthobacaceae. Metabolomic results suggested that the levels of chenodeoxycholic acid-3-ß-D-glucuronide, 1-methylnicotinamide and acetoacetate in stool samples of the US group were significantly higher than those of the BS group. By identifying the differentially abundant bacterial taxa, the gut microbiota could modulate the efficacy of statins through producing enzymes involved in cholesterol metabolism. Conclusions: The findings suggest that the difference in statin efficacy may be related to gut microbiota strains that can produce short-chain fatty acids and secondary bile acids and affect the efficacy of statins by regulating the activities of cholesterol metabolite-related proteins. Metabolites related to short-chain fatty acids and secondary bile acids in the gut are expected to be biomarkers indicating the efficacy of statins.

Machine Learning Prediction of Autism Spectrum Disorder From a Minimal Set of Medical and Background Information.

Importance: Early identification of the likelihood of autism spectrum disorder (ASD) using minimal information is crucial for early diagnosis and intervention, which can affect developmental outcomes. Objective: To develop and validate a machine learning (ML) model for predicting ASD using a minimal set of features from background and medical information and to evaluate the predictors and the utility of the ML model. Design, Setting, and Participants: For this diagnostic study, a retrospective analysis of the Simons Foundation Powering Autism Research for Knowledge (SPARK) database, version 8 (released June 6, 2022), was conducted, including data from 30 660 participants after adjustments for missing values and class imbalances (15 330 with ASD and 15 330 without ASD). The SPARK database contains participants recruited from 31 university-affiliated research clinicals and online in 26 states in the US. All individuals with a professional ASD diagnosis and their families were eligible to participate. The model performance was validated on independent datasets from SPARK, version 10 (released July 21, 2023), and the Simons Simplex Collection (SSC), consisting of 14 790 participants, followed by phenotypic associations. Exposures: Twenty-eight basic medical screening and background history items present before 24 months of age. Main Outcomes and Measures: Generalizable ML prediction models were developed for detecting ASD using 4 algorithms (logistic regression, decision tree, random forest, and eXtreme Gradient Boosting [XGBoost]). Performance metrics included accuracy, area under the receiver operating characteristics curve (AUROC), sensitivity, specificity, positive predictive value (PPV), and F1 score, offering a comprehensive assessment of the predictive accuracy of the model. Explainable AI methods were applied to determine the effect of individual features in predicting ASD as secondary outcomes, enhancing the interpretability of the best-performing model. The secondary outcome analyses were further complemented by examining differences in various phenotypic measures using nonparametric statistical methods, providing insights into the ability of the model to differentiate between different presentations of ASD. Results: The study included 19 477 (63.5%) male and 11 183 (36.5%) female participants (mean [SD] age, 106 [62] months). The mean (SD) age was 113 (68) months for the ASD group and 100 (55) months for the non-ASD group. The XGBoost (termed AutMedAI) model demonstrated strong performance with an AUROC score of 0.895, sensitivity of 0.805, specificity of 0.829, and PPV of 0.897. Developmental milestones and eating behavior were the most important predictors. Validation on independent cohorts showed an AUROC of 0.790, indicating good generalizability. Conclusions and Relevance: In this diagnostic study of ML prediction of ASD, robust model performance was observed to identify autistic individuals with more symptoms and lower cognitive levels. The robustness and ML model generalizability results are promising for further validation and use in clinical and population settings.