Idiopathic nodular glomerulosclerosis: A case report and literature review.

This paper reports a 49-year-old male patient with a long-term smoking history who developed renal insufficiency and proteinuria in the range of nephropathy without diabetes. Renal biopsy showed nodular glomerulosclerosis with vitreous degeneration of arterioles and moderate and severe proliferation of glomerular mesangial cells and matrix. The patient was diagnosed with idiopathic nodular glomerulosclerosis. After treatment with angiotensin-converting enzyme inhibitor/angiotensin II receptor blocker (ACEI/ARB) drugs, the level of albuminuria decreased rapidly, and renal function remained stable. The clinical manifestations and pathological features of 122 cases of idiopathic nodular glomerulosclerosis reported from 1999 to August 2023 were analyzed, retrospectively.

Decision fatigue experience of front-line nurses in the context of public health emergency: an interpretative phenomenological analysis.

BACKGROUND: Decision fatigue is a new concept in the field of psychology and refers to a state of fatigue alongside impaired cognitive processing and emotional regulation ability. Previous studies have confirmed that nurses are prone to decision fatigue, and nurses who experience decision fatigue may implement nursing measures that are inconsistent with clinical evidence, thus affecting patients' benefits. COVID-19, as a large-scale global public health emergency, increased the workload and burden of nurses and aggravated decision fatigue. However, the factors leading to decision fatigue among nurses have not yet been identified. METHODS: This study is guided by interpretative phenomenology. During the epidemic period of COVID-19: From November 2022 to February 2023, a one-to-one, semi-structured in-depth interview was conducted among nurses with decision fatigue experience who were participating in front-line work in Jilin Province using homogenous sampling. The interview recordings and related data were transcribed into text within 24 h, and data analysis was assisted by NVivo 12.0 software. RESULTS: After a total of 14 front-line nurses were analyzed in this study, The thematic level reaches saturation, the findings present a persuasive and coherent narrative, and the study is terminated, and finally extracted and formed three core themes: "Cognition, influence and attitude of decision fatigue", "Approaching factors of decision fatigue" and "Avoidant factors of decision fatigue". CONCLUSION: This study confirmed that decision fatigue was widespread in the work of front-line nurses, affecting the physical and psychological health of nurses, the quality of nursing work, the degree of benefit of patients and the clinical outcome. However, nursing staff do not know enough about decision fatigue, so the popularization and research of decision fatigue should be strengthened. Improve the attention of medical institutions, nursing managers and nursing staff.Some suggestions are put forward for the intervention of decision fatigue through personnel, task, tool and technology, organization and environment.

Transcriptome sequencing data provides a solid base to understand the phylogenetic relationships, biogeography and reticulated evolution of the genus Zamia L. (Cycadales: Zamiaceae).

BACKGROUND AND AIMS: Cycad is a key lineage to understand the early evolution of seed plants and their response to past environmental changes. However, tracing the evolutionary trajectory of cycad species is challenging when the robust relationships at inter- or infrageneric level are not well resolved. METHODS: Here, using 2,901 single-copy nuclear genes, we explored the species relationships and gene flow within the second largest genus of cycads, i.e., Zamia, based on phylotranscriptomic analyses of 90% extant Zamia species. Based on a well-resolved phylogenetic framework, we performed gene flow analyses, molecular dating, and biogeographical reconstruction to examine the spatiotemporal evolution of Zamia. We also performed ancestral state reconstruction (ASR) of a total of 62 traits of the genus to comprehensively investigate its morphological evolution. KEY RESULTS: Zamia is comprised of seven major clades corresponding to seven distinct distribution areas in the Americas, with at least three reticulation nodes revealed in this genus. Extant lineages of Zamia initially diversified around 18.4-32.6 (29.14) million years ago (MA) in the Mega-Mexico, and then expanded eastward into the Caribbean and southward into Central and South America. ASR revealed homoplasy in most of the morphological characters. CONCLUSIONS: This study revealed congruent phylogenetic relationships from comparative methods/datasets, with some conflicts being the result of incomplete lineage sorting and ancient/recent hybridization events. The strong association between the clades and the biogeographic areas suggested that ancient dispersal events shaped the modern distribution pattern, and regional climatic factors may have resulted in the following in-situ diversification. Climate cooling starting during the mid Miocene is associated with the global expansion of Zamia to the tropical South America that have dramatically driven lineage diversification in the New World flora, as well as the extinction of cycad species in the nowadays cooler regions of both hemispheres as indicated by the fossil records.

Revealing brain cell-stratified causality through dissecting causal variants according to their cell-type-specific effects on gene expression.

The human brain has been implicated in the pathogenesis of several complex diseases. Taking advantage of single-cell techniques, genome-wide association studies (GWAS) have taken it a step further and revealed brain cell-type-specific functions for disease loci. However, genetic causal associations inferred by Mendelian randomization (MR) studies usually include all instrumental variables from GWAS, which hampers the understanding of cell-specific causality. Here, we developed an analytical framework, Cell-Stratified MR (csMR), to investigate cell-stratified causality through colocalizing GWAS signals with single-cell eQTL from different brain cells. By applying to obesity-related traits, our results demonstrate the cell-type-specific effects of GWAS variants on gene expression, and indicate the benefits of csMR to identify cell-type-specific causal effect that is often hidden from bulk analyses. We also found csMR valuable to reveal distinct causal pathways between different obesity indicators. These findings suggest the value of our approach to prioritize target cells for extending genetic causation studies.

Proto-oncogene c-Myb potentiates cisplatin resistance of ovarian cancer cells by downregulating lncRNA NKILA and modulating cancer stemness and LIN28A-let7 axis.

Ovarian cancer is a major gynecological cancer that has poor prognosis associated mainly to its late diagnosis. Cisplatin is an FDA approved ovarian cancer therapy and even though the therapy is initially promising, the patients mostly progress to resistance against cisplatin. The underlying mechanisms are complex and not very clearly understood. Using two different paired cell lines representing cisplatin-sensitive and the cisplatin-resistant ovarian cancer cells, the ES2 and the A2780 parental and cisplatin-resistant cells, we show an elevated proto-oncogene c-Myb in resistant cells. We further show down-regulated lncRNA NKILA in resistant cells with its de-repression in resistant cells when c-Myb is silenced. NKILA negatively correlates with cancer cell and invasion but has no effect on cellular proliferation or cell cycle. C-Myb activates NF-κB signaling which is inhibited by NKILA. The cisplatin resistant cells are also marked by upregulated stem cell markers, particularly LIN28A and OCT4, and downregulated LIN28A-targeted let-7 family miRNAs. Whereas LIN28A and downregulated let-7s individually de-repress c-Myb-mediated cisplatin resistance, the ectopic expression of let-7s attenuates LIN28A effects, thus underlying a c-Myb-NKILA-LIN28A-let-7 axis in cisplatin resistance of ovarian cancer cells that needs to be further explored for therapeutic intervention.

Unveiling Promising Neuroimaging Biomarkers for Schizophrenia Through Clinical and Genetic Perspectives.

Schizophrenia is a complex and serious brain disorder. Neuroscientists have become increasingly interested in using magnetic resonance-based brain imaging-derived phenotypes (IDPs) to investigate the etiology of psychiatric disorders. IDPs capture valuable clinical advantages and hold biological significance in identifying brain abnormalities. In this review, we aim to discuss current and prospective approaches to identify potential biomarkers for schizophrenia using clinical multimodal neuroimaging and imaging genetics. We first described IDPs through their phenotypic classification and neuroimaging genomics. Secondly, we discussed the applications of multimodal neuroimaging by clinical evidence in observational studies and randomized controlled trials. Thirdly, considering the genetic evidence of IDPs, we discussed how can utilize neuroimaging data as an intermediate phenotype to make association inferences by polygenic risk scores and Mendelian randomization. Finally, we discussed machine learning as an optimum approach for validating biomarkers. Together, future research efforts focused on neuroimaging biomarkers aim to enhance our understanding of schizophrenia.

Development and validation of machine learning models to predict frailty risk for elderly.

AIMS: Early identification and intervention of the frailty of the elderly will help lighten the burden of social medical care and improve the quality of life of the elderly. Therefore, we used machine learning (ML) algorithm to develop models to predict frailty risk in the elderly. DESIGN: A prospective cohort study. METHODS: We collected data on 6997 elderly people from Chinese Longitudinal Healthy Longevity Study wave 6-7 surveys (2011-2012, 2014). After the baseline survey in 1998 (wave 1), the project conducted follow-up surveys (wave 2-8) in 2000-2018. The osteoporotic fractures index was used to assess frailty. Four ML algorithms (random forest [RF], support vector machine, XGBoost and logistic regression [LR]) were used to develop models to identify the risk factors of frailty and predict the risk of frailty. Different ML models were used for the prediction of frailty risk in the elderly and frailty risk was trained on a cohort of 4385 elderly people with frailty (split into a training cohort [75%] and internal validation cohort [25%]). The best-performing model for each study outcome was tested in an external validation cohort of 6997 elderly people with frailty pooled from the surveys (wave 6-7). Model performance was assessed by receiver operating curve and F2-score. RESULTS: Among the four ML models, the F2-score values were similar (0.91 vs. 0.91 vs. 0.88 vs. 0.90), and the area under the curve (AUC) values of RF model was the highest (0.75), followed by LR model (0.74). In the final two models, the AUC values of RF and LR model were similar (0.77 vs. 0.76) and their accuracy was identical (87.4% vs. 87.4%). CONCLUSION: Our study developed a preliminary prediction model based on two different ML approaches to help predict frailty risk in the elderly. IMPACT: The presented models from this study can be used to inform healthcare providers to predict the frailty probability among older adults and maybe help guide the development of effective frailty risk management interventions. IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE: Detecting frailty at an early stage and implementing timely targeted interventions may help to improve the allocation of health care resources and to reduce frailty-related burden. Identifying risk factors for frailty could be beneficial to provide tailored and personalized care intervention for older adults to more accurately prevent or improve their frail conditions so as to improve their quality of life. REPORTING METHOD: The study has adhered to STROBE guidelines. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution.

Berberine alleviates Alzheimer's disease by regulating the gut microenvironment, restoring the gut barrier and brain-gut axis balance.

BACKGROUND: Alzheimer's disease (AD) is the most common neurodegenerative disease. Intestinal flora and its metabolism play a significant role in ameliorating central nervous system disorders, including AD, through bidirectional interactions between the gut-brain axis. A naturally occurring alkaloid compound called berberine (BBR) has neuroprotective properties and prevents Aß-induced microglial activation. Additionally, BBR can suppress the synthesis of Aß and decrease BACE1 expression. However, it is still unclear if BBR therapy can alleviate AD by changing the gut flora. PURPOSE: In this study, we examined whether a partial alleviation of AD could be achieved with BBR treatment and the molecular mechanisms involved. METHODS: We did this by analyzing alterations in Aß plaques, neurons, and related neuroinflammation-related markers in the brain and the transcriptome of the mouse brain. The relationship between the intestinal flora of 5xFAD model mice and BBR treatment was investigated using high-throughput sequencing analysis of 16S rRNA from mouse feces. RESULTS: The findings demonstrated that treatment with BBR cleared Aß plaques, alleviated neuroinflammation, and ameliorated spatial memory dysfunction in AD. BBR significantly alleviated intestinal inflammation, decreased intestinal permeability, and could improve intestinal microbiota composition in 5xFAD mice.

The Causal Relationships Between Gut Microbiota, Brain Volume, and Intelligence: A Two-Step Mendelian Randomization Analysis.

BACKGROUND: Growing evidence indicates that dynamic changes in gut microbiome can affect intelligence; however, whether these relationships are causal remains elusive. We aimed to disentangle the poorly understood causal relationship between gut microbiota and intelligence. METHODS: We performed a 2-sample Mendelian randomization (MR) analysis using genetic variants from the largest available genome-wide association studies of gut microbiota (N = 18,340) and intelligence (N = 269,867). The inverse-variance weighted method was used to conduct the MR analyses complemented by a range of sensitivity analyses to validate the robustness of the results. Considering the close relationship between brain volume and intelligence, we applied 2-step MR to evaluate whether the identified effect was mediated by regulating brain volume (N = 47,316). RESULTS: We found a risk effect of the genus Oxalobacter on intelligence (odds ratio = 0.968 change in intelligence per standard deviation increase in taxa; 95% CI, 0.952-0.985; p = 1.88 × 10-4) and a protective effect of the genus Fusicatenibacter on intelligence (odds ratio = 1.053; 95% CI, 1.024-1.082; p = 3.03 × 10-4). The 2-step MR analysis further showed that the effect of genus Fusicatenibacter on intelligence was partially mediated by regulating brain volume, with a mediated proportion of 33.6% (95% CI, 6.8%-60.4%; p = .014). CONCLUSIONS: Our results provide causal evidence indicating the role of the microbiome in intelligence. Our findings may help reshape our understanding of the microbiota-gut-brain axis and development of novel intervention approaches for preventing cognitive impairment.

Dl-3-n-butylphthalide attenuates cerebral ischemia/reperfusion injury in mice through AMPK-mediated mitochondrial fusion.

Introduction: NBP is a compound isolated from celery seeds, which was approved by the National Medical Products Administration in 2002 for clinical treatment of ischemic stroke. However, in brain ischemia/reperfusion (I/R) injury, the related research on mitochondrial dynamics and its mechanism of action of NBP still need to be further studied. The aim of this study was to assess NBP on cerebral pathology in ischemic stroke in vivo, with a specific focus on the molecular mechanisms of how NBP promotes mitochondrial fusion. Methods: Male C57BL/6 mice were utilized in this study and were subjected to middle cerebral artery occlusion/reperfusion (MCAO/R). Pre-ischemia, NBP was administered through intraperitoneal (i.p.) injection for 7 days. Results: Our findings demonstrated that NBP effectively reduced infarct volume, improved neurological dysfunction, enhanced cerebral blood flow, and promoted mitochondrial fusion in mice subjected to MCAO/R. More importantly, the pro-fusion effects of NBP were found to be linked to the activation of AMPK/Mfn1 pathway, and with the activation of neurological function, which was partially eliminated by inhibitors of AMPK. Discussion: Our results revealed that NBP is a novel mitochondrial fusion promoter in protecting against ischemic stroke through the AMPK-mediated Mfn1. These findings contribute to the understanding of novel mechanisms involved in the protection of neurological function following NBP treatment for ischemic stroke.

Eco-evolutionary evidence for the global diversity pattern of Cycas (Cycadaceae).

The evolution of the latitudinal diversity gradient (LDG), characterized by a peak in diversity toward the tropics, has captured significant attention in evolutionary biology and ecology. However, the inverse LDG (i-LDG) mechanism, wherein species richness increases toward the poles, remains inadequately explored. Cycads are among one of the oldest lineages of extant seed plants and have undergone extensive diversification in the tropics. Intriguingly, the extant cycad abundance exhibits an i-LDG pattern, and the underlying causes for this phenomenon remain largely elusive. Here, using 1,843 nuclear genes from a nearly complete sampling, we conducted comprehensive phylogenomic analyses to establish a robust species-level phylogeny for Cycas, the largest genus within cycads. We then reconstructed the spatial-temporal dynamics and integrated global environmental data to evaluate the roles of species ages, diversification rates, contemporary environment, and conservatism to ancestral niches in shaping the i-LDG pattern. We found Cycas experienced decreased diversification rates, coupled with the cooling temperature since its origin in the Eocene from continental Asia. Different regions have distinctively contributed to the formation of i-LDG for Cycas, with the northern hemisphere acting as evolutionary museums and the southern hemisphere serving as cradles. Moreover, water-related climate variables, specifically precipitation seasonality and potential evapotranspiration, were identified as paramount factors constraining Cycas species richness in the rainforest biome near the equator. Notably, the adherence to ancestral monsoonal climates emerges as a critical factor in sustaining the diversity pattern. This study underscores the imperative of integrating both evolutionary and ecological approaches to comprehensively unravel the mechanisms underpinning global biodiversity patterns.

The Therapeutic Effect of Buyang Huanwu Decoction on Mild Cognitive Impairment (MCI) in Patients with Diabetes.

OBJECTIVE: This study aims to comprehensively verify the efficacy of Buyang Huanwu Decoction in improving cognitive function in patients with diabetes. METHODS: Patients clinically diagnosed with mild cognitive impairment (MCI) assigned to either the placebo group or the Buyang Huanwu Decoction group. After strict screening and exclusions, a total of 156 participants completed the clinical trial, with 76 in the placebo group and 80 in the Buyang Huanwu Decoction group. RESULTS: After treatment, Buyang Huanwu Decoction group showed higher Mini-Mental State Examination and Montreal Cognitive Assessment scores compared to placebo (p < 0.05). Memory and Executive Screening, Boston Naming Test, and Animal Fluency Test scores were also higher in the treatment group (p < 0.05). No significant differences were found in DST and CDT scores (p > 0.05). Trail Making Test scores were lower in the treatment group (p < 0.05). No significant difference was observed between the two groups in terms of complications (p > 0.05). CONCLUSION: Patients receiving Buyang Huanwu Decoction treatment demonstrated improvement in cognitive function, showing positive effects and providing preliminary evidence for the role of Buyang Huanwu Decoction in improving cognitive function in patients with diabetes. This suggests its potential for clinical application and further promotion.

Integrative high-throughput enhancer surveying and functional verification divulges a YY2-condensed regulatory axis conferring risk for osteoporosis.

The precise roles of chromatin organization at osteoporosis risk loci remain largely elusive. Here, we combined chromatin interaction conformation (Hi-C) profiling and self-transcribing active regulatory region sequencing (STARR-seq) to qualify enhancer activities of prioritized osteoporosis-associated single-nucleotide polymorphisms (SNPs). We identified 319 SNPs with biased allelic enhancer activity effect (baaSNPs) that linked to hundreds of candidate target genes through chromatin interactions across 146 loci. Functional characterizations revealed active epigenetic enrichment for baaSNPs and prevailing osteoporosis-relevant regulatory roles for their chromatin interaction genes. Further motif enrichment and network mapping prioritized several putative, key transcription factors (TFs) controlling osteoporosis binding to baaSNPs. Specifically, we selected one top-ranked TF and deciphered that an intronic baaSNP (rs11202530) could allele-preferentially bind to YY2 to augment PAPSS2 expression through chromatin interactions and promote osteoblast differentiation. Our results underline the roles of TF-mediated enhancer-promoter contacts for osteoporosis, which may help to better understand the intricate molecular regulatory mechanisms underlying osteoporosis risk loci.

Experimental models for cancer brain metastasis.

Brain metastases are a leading cause of cancer-related mortality. However, progress in their treatment has been limited over the past decade, due to an incomplete understanding of the underlying biological mechanisms. Employing accurate in vitro and in vivo models to recapitulate the complexities of brain metastasis offers the most promising approach to unravel the intricate cellular and physiological processes involved. Here, we present a comprehensive review of the currently accessible models for studying brain metastasis. We introduce a diverse array of in vitro and in vivo models, including cultured cells using the Transwell system, organoids, microfluidic models, syngeneic models, xenograft models, and genetically engineered models. We have also provided a concise summary of the merits and limitations inherent to each model while identifying the optimal contexts for their effective utilization. This review serves as a comprehensive resource, aiding researchers in making well-informed decisions regarding model selection that align with specific research questions.

Mechanism of Efferocytosis in Determining Ischaemic Stroke Resolution-Diving into Microglia/Macrophage Functions and Therapeutic Modality.

After ischaemic cerebral vascular injury, efferocytosis-a process known as the efficient clearance of apoptotic cells (ACs) by various phagocytes in both physiological and pathological states-is crucial for maintaining central nervous system (CNS) homeostasis and regaining prognosis. The mechanisms of efferocytosis in ischaemic stroke and its influence on preventing inflammation progression from secondary injury were still not fully understood, despite the fact that the fundamental process of efferocytosis has been described in a series of phases, including AC recognition, phagocyte engulfment, and subsequent degradation. The genetic reprogramming of macrophages and brain-resident microglia after an ischaemic stroke has been equated by some researchers to that of the peripheral blood and brain. Based on previous studies, some molecules, such as signal transducer and activator of transcription 6 (STAT6), peroxisome proliferator-activated receptor γ (PPARG), CD300A, and sigma non-opioid intracellular receptor 1 (SIGMAR1), were discovered to be largely associated with aspects of apoptotic cell elimination and accompanying neuroinflammation, such as inflammatory cytokine release, phenotype transformation, and suppressing of antigen presentation. Exacerbated stroke outcomes are brought on by defective efferocytosis and improper modulation of pertinent signalling pathways in blood-borne macrophages and brain microglia, which also results in subsequent tissue inflammatory damage. This review focuses on recent researches which contain a number of recently discovered mechanisms, such as studies on the relationship between benign efferocytosis and the regulation of inflammation in ischaemic stroke, the roles of some risk factors in disease progression, and current immune approaches that aim to promote efferocytosis to treat some autoimmune diseases. Understanding these pathways provides insight into novel pathophysiological processes and fresh characteristics, which can be used to build cerebral ischaemia targeting techniques.

A landscape of gene expression regulation for synovium in arthritis.

The synovium is an important component of any synovial joint and is the major target tissue of inflammatory arthritis. However, the multi-omics landscape of synovium required for functional inference is absent from large-scale resources. Here we integrate genomics with transcriptomics and chromatin accessibility features of human synovium in up to 245 arthritic patients, to characterize the landscape of genetic regulation on gene expression and the regulatory mechanisms mediating arthritic diseases predisposition. We identify 4765 independent primary and 616 secondary cis-expression quantitative trait loci (cis-eQTLs) in the synovium and find that the eQTLs with multiple independent signals have stronger effects and heritability than single independent eQTLs. Integration of genome-wide association studies (GWASs) and eQTLs identifies 84 arthritis related genes, revealing 38 novel genes which have not been reported by previous studies using eQTL data from the GTEx project or immune cells. We further develop a method called eQTac to identify variants that could affect gene expression by affecting chromatin accessibility and identify 1517 regions with potential regulatory function of chromatin accessibility. Altogether, our study provides a comprehensive synovium multi-omics resource for arthritic diseases and gains new insights into the regulation of gene expression.

Optical fiber surface plasmon resonance sensor using electroless-plated gold film for thrombin detection.

This paper describes the simple and label-free detection of thrombin using optical fiber surface plasmon resonance (SPR) sensors based on gold films prepared by the cost-effective method of electroless plating. The plating conditions for simultaneously obtaining gold film on cylindrical core and end surfaces of an optical fiber suitable for measurement were optimized. The fabricated sensor exhibited a linear refractive index sensitivity of 2150 nm/RIU and 7.136 (a.u.)/RIU in the refractive index of 1.3329-1.3605 interrogated by resonance wavelength and amplitude methods respectively and a single wavelength monitoring method was proposed to investigate the sensing performance of this sensor. Polyadenine diblock and thiolated thrombin aptamers were immobilized on gold nanoparticles and gold films respectively to implement a sandwich optical fiber assay for thrombin. The developed optical fiber SPR sensors were successfully used in the determination of thrombin down to 0.56 nM over a wide range from 2 to 100 nM and showed good selectivity for thrombin, which indicated their potential clinical applications for biomedical samples.

Chromosome-level genome assembly of Niphotrichum japonicum provides new insights into heat stress responses in mosses.

With a diversity of approximately 22,000 species, bryophytes (hornworts, liverworts, and mosses) represent a major and diverse lineage of land plants. Bryophytes can thrive in many extreme environments as they can endure the stresses of drought, heat, and cold. The moss Niphotrichum japonicum (Grimmiaceae, Grimmiales) can subsist for extended periods under heat and drought conditions, providing a good candidate for studying the genetic basis underlying such high resilience. Here, we de novo assembled the genome of N. japonicum using Nanopore long reads combined with Hi-C scaffolding technology to anchor the 191.61 Mb assembly into 14 pseudochromosomes. The genome structure of N. japonicum's autosomes is mostly conserved and highly syntenic, in contrast to the sparse and disordered genes present in its sex chromosome. Comparative genomic analysis revealed the presence of 10,019 genes exclusively in N. japonicum. These genes may contribute to the species-specific resilience, as demonstrated by the gene ontology (GO) enrichment. Transcriptome analysis showed that 37.44% (including 3,107 unique genes) of the total annotated genes (26,898) exhibited differential expression as a result of heat-induced stress, and the mechanisms that respond to heat stress are generally conserved across plants. These include the upregulation of HSPs, LEAs, and reactive oxygen species (ROS) scavenging genes, and the downregulation of PPR genes. N. japonicum also appears to have distinctive thermal mechanisms, including species-specific expansion and upregulation of the Self-incomp_S1 gene family, functional divergence of duplicated genes, structural clusters of upregulated genes, and expression piggybacking of hub genes. Overall, our study highlights both shared and species-specific heat tolerance strategies in N. japonicum, providing valuable insights into the heat tolerance mechanism and the evolution of resilient plants.

Rapid detection of residual chlorpyrifos and pyrimethanil on fruit surface by surface-enhanced Raman spectroscopy integrated with deep learning approach.

Chlorpyrifos and pyrimethanil are widely used insecticides/fungicides in agriculture. The residual pesticides/fungicides remaining in fruits and vegetables may do harm to human health if they are taken without notice by the customers. Therefore, it is important to develop methods and tools for the rapid detection of pesticides/fungicides in fruits and vegetables, which are highly demanded in the current markets. Surface-enhanced Raman spectroscopy (SERS) can achieve trace chemical detection, while it is still a challenge to apply SERS for the detection and identification of mixed pesticides/fungicides. In this work, we tried to combine SERS technique and deep learning spectral analysis for the determination of mixed chlorpyrifos and pyrimethanil on the surface of fruits including apples and strawberries. Especially, the multi-channel convolutional neural networks-gate recurrent unit (MC-CNN-GRU) classification model was used to extract sequence and spatial information in the spectra, so that the accuracy of the optimized classification model could reach 99% even when the mixture ratio of pesticide/fungicide varied considerably. This work therefore demonstrates an effective application of using SERS combined deep learning approach in the rapid detection and identification of different mixed pesticides in agricultural products.