Identification Of Drivers Research Articles

Non-small cell lung cancer in China.

In China, lung cancer is a primary cancer type with high incidence and mortality. Risk factors for lung cancer include tobacco use, family history, radiation exposure, and the presence of chronic lung diseases. Most early‐stage non‐small cell lung cancer (NSCLC) patients miss the optimal timing for treatment due to the lack of clinical presentations. Population‐based nationwide screening programs are of significant help in increasing the early detection and survival rates of NSCLC in China. The understanding of molecular carcinogenesis and the identification of oncogenic drivers dramatically facilitate the development of targeted therapy for NSCLC, thus prolonging survival in patients with positive drivers. In the exploration of immune escape mechanisms, programmed cell death protein 1 (PD‐1)/programmed death‐ligand 1 (PD‐L1) inhibitor monotherapy and PD‐1/PD‐L1 inhibitor plus chemotherapy have become a standard of care for advanced NSCLC in China. In the Chinese Society of Clinical Oncology's guidelines for NSCLC, maintenance immunotherapy is recommended for locally advanced NSCLC after chemoradiotherapy. Adjuvant immunotherapy and neoadjuvant chemoimmunotherapy will be approved for resectable NSCLC. In this review, we summarized recent advances in NSCLC in China in terms of epidemiology, biology, molecular pathology, pathogenesis, screening, diagnosis, targeted therapy, and immunotherapy.

Identification of drivers of mycobacterial resistance to peptidoglycan synthesis inhibitors.

Beta-lactams have been excluded from tuberculosis therapy due to the intrinsic resistance of Mycobacterium tuberculosis (Mtb) to this antibiotic class, usually attributed to a potent beta-lactamase, BlaC, and to an unusually complex cell wall. In this pathogen, the peptidoglycan is cross-linked by penicillin-binding proteins (PBPs) and L,D-transpeptidases, the latter resistant to inhibition by most beta-lactams. However, recent studies have shown encouraging results of beta-lactam/beta-lactamase inhibitor combinations in clinical strains. Additional research on the mechanisms of action and resistance to these antibiotics and other inhibitors of peptidoglycan synthesis, such as the glycopeptides, is crucial to ascertain their place in alternative regimens against drug-resistant strains. Within this scope, we applied selective pressure to generate mutants resistant to amoxicillin, meropenem or vancomycin in Mtb H37Rv or Mycolicibacterium smegmatis (Msm) mc2-155. These were phenotypically characterized, and whole-genome sequencing was performed. Mutations in promising targets or orthologue genes were inspected in Mtb clinical strains to establish potential associations between altered susceptibility to beta-lactams and the presence of key genomic signatures. The obtained isolates had substantial increases in the minimum inhibitory concentration of the selection antibiotic, and beta-lactam cross-resistance was detected in Mtb. Mutations in L,D-transpeptidases and major PBPs, canonical targets, or BlaC were not found. The transcriptional regulator PhoP (Rv0757) emerged as a common denominator for Mtb resistance to both amoxicillin and meropenem, while Rv2864c, a lipoprotein with PBP activity, appears to be specifically involved in decreased susceptibility to the carbapenem. Nonetheless, the mutational pattern detected in meropenem-resistant mutants was different from the yielded by amoxicillin-or vancomycin-selected isolates, suggesting that distinct pathways may participate in increased resistance to peptidoglycan inhibitors, including at the level of beta-lactam subclasses. Cross-resistance between beta-lactams and antimycobacterials was mostly unnoticed, and Msm meropenem-resistant mutants from parental strains with previous resistance to isoniazid or ethambutol were isolated at a lower frequency. Although cell-associated nitrocefin hydrolysis was increased in some of the isolates, our findings suggest that traditional assumptions of Mtb resistance relying largely in beta-lactamase activity and impaired access of hydrophilic molecules through lipid-rich outer layers should be challenged. Moreover, the therapeutical potential of the identified Mtb targets should be explored.

Beyond targeting amplified MDM2 and CDK4 in well differentiated and dedifferentiated liposarcomas: From promise and clinical applications towards identification of progression drivers.

Well differentiated and dedifferentiated liposarcomas (WDLPS and DDLPS) are tumors of the adipose tissue poorly responsive to conventional cytotoxic chemotherapy which currently remains the standard-of-care. The dismal prognosis of the DDLPS subtype indicates an urgent need to identify new therapeutic targets to improve the patient outcome. The amplification of the two driver genes MDM2 and CDK4, shared by WDLPD and DDLPS, has provided the rationale to explore targeting the encoded ubiquitin-protein ligase and cell cycle regulating kinase as a therapeutic approach. Investigation of the genomic landscape of WD/DDLPS and preclinical studies have revealed additional potential targets such as receptor tyrosine kinases, the cell cycle kinase Aurora A, and the nuclear exporter XPO1. While the therapeutic significance of these targets is being investigated in clinical trials, insights into the molecular characteristics associated with dedifferentiation and progression from WDLPS to DDLPS highlighted additional genetic alterations including fusion transcripts generated by chromosomal rearrangements potentially providing new druggable targets (e.g. NTRK, MAP2K6). Recent years have witnessed the increasing use of patient-derived cell and tumor xenograft models which offer valuable tools to accelerate drug repurposing and combination studies. Implementation of integrated “multi-omics” investigations applied to models recapitulating WD/DDLPS genetics, histologic differentiation and biology, will hopefully lead to a better understanding of molecular alterations driving liposarcomagenesis and DDLPS progression, as well as to the identification of new therapies tailored on tumor histology and molecular profile.

THE DRIVERS AND BARRIERS OF ONLINE SHOPPING BEHAVIOURS FOR OLDER ADULTS: A REVIEW

To date, digitalization is a necessity for all consumers regardless of the age groups to adapt to the online world. However, not all consumers have benefitted from the advantages of online shopping despite its increases importance over the years. One neglected group is the older adults; who is often overlooked by the online shopping industry due to preferences and focus on the youth market. There are also limited studies found in the literature on the topic of older adults’ behaviour as online shoppers. A gap in the literature is in lack of understanding on the role played by technology-enabled platforms on aging societies; this raises the needs for researchers and practitioners alike to study the challenges and concerns related to meeting older adults’ needs on technology as the group increases in numbers worldwide. In Malaysia, older adults are not active and engaged consumers in online shopping despite the group’s high market potential value. Taking note of the online shopping scenario in Malaysia as well as the gap identified in the literature, this study reviews the literature (secondary data) to identify the drivers and barriers of online shopping behaviours among older adults. It is expected that apart from enriching existing literature related to online shopping behaviour for older adults, this review would also benefit future scholars when deciding on possible drivers and/or barriers’ selection in the investigation of older adults’ online shopping behaviour. As for marketers, the identification of drivers and/or barriers would be useful to consider in planning for their future marketing strategies.

1683P Implementing next generation sequencing (NGS)/molecular tumor board (MTB)-based precision oncology practice: One-year experience at the Verona University Hospital

Cancer is a multifactorial genetic disease: NGS-based broad genomic profiling allows the identification of potential molecular drivers. Evaluation of the clinical actionability of NGS results should be guided by the expert consensus of a MTB, providing management recommendations and translating molecular alterations into clinical indications. Here we describe the MTB experience at the Verona University Hospital. Between Feb 2021 and Mar 2022, 315 patients (pts) with advanced solid malignancies deemed orphan with respect to established molecular diagnostics and availability of standard molecularly targeted treatments, had access to somatic profiling using targeted NGS panels. NGS results were discussed at bi-weekly MTB meetings, encompassing oncologists, pathologists, geneticists, pharmacologists, and pharmacists. The three most represented primary tumors were pancreatic (30%), breast (16%) and head and neck (14%) cancers. Among 315 pts profiled (13% of the annual active oncological population at our Center), 42 were discussed at MTB meetings, so far: 15 patients (36%) received a treatment recommendation: 4 within an ongoing clinical trial, 11 through atypical drug access (authorized off label use, named patient programs and other access schemes). Six pts (14%) were referred for genetic counseling, based on evidence of potential germline alterations at somatic testing. Further molecular investigations were requested/proposed in 11 pts (26%): IHC in 5, germline testing in 5, and a second NGS test + IHC in 1 pt, respectively. NGS-based profiling is a comprehensive tool to identify potentially actionable targets in advanced solid tumors. Its systematic application may have a profound impact on individual pts clinical course and outcomes. MTB discussion successfully provided suitable management strategies in a significant fraction of pts. Based on the careful definition of the criteria for accessing NGS profiling and the consequent MTB discussion, such approach should become a constitutive part of the oncological care program in the era of precision medicine.

EP16.03-030 AKT Inhibition as a Therapeutic Strategy to Constrain Histological Transdifferentiation in EGFR-mutant Lung Adenocarcinoma.

In lung adenocarcinomas (LUADs), lineage plasticity drives neuroendocrine (NE) and squamous cell (LUSC) transdifferentiation in the context of acquired resistance to targeted inhibition of driver mutations, with up to 14% and 9% incidences in EGFR-mutant tumors relapsed on EGFR inhibitors, respectively. Notably, survival of patients with NE- or LUSC-transdifferentiated tumors is remarkably lower than those of LUAD or de novo LUSC patients. The paucity of transforming clinical specimens amenable for molecular analyses has hindered the identification of histological transformation drivers, and to date no specific therapies aimed to prevent or delay transdifferentiation-led therapy relapse are available for patients at high risk of transformation.

A Deep Learning Approach to Classify Sitting and Sleep History from Raw Accelerometry Data during Simulated Driving.

Prolonged sitting and inadequate sleep can impact driving performance. Therefore, objective knowledge of a driver’s recent sitting and sleep history could help reduce safety risks. This study aimed to apply deep learning to raw accelerometry data collected during a simulated driving task to classify recent sitting and sleep history. Participants (n = 84, Mean ± SD age = 23.5 ± 4.8, 49% Female) completed a seven-day laboratory study. Raw accelerometry data were collected from a thigh-worn accelerometer during a 20-min simulated drive (8:10 h and 17:30 h each day). Two convolutional neural networks (CNNs; ResNet-18 and DixonNet) were trained to classify accelerometry data into four classes (sitting or breaking up sitting and 9-h or 5-h sleep). Accuracy was determined using five-fold cross-validation. ResNet-18 produced higher accuracy scores: 88.6 ± 1.3% for activity (compared to 77.2 ± 2.6% from DixonNet) and 88.6 ± 1.1% for sleep history (compared to 75.2 ± 2.6% from DixonNet). Class activation mapping revealed distinct patterns of movement and postural changes between classes. Findings demonstrate the suitability of CNNs in classifying sitting and sleep history using thigh-worn accelerometer data collected during a simulated drive. This approach has implications for the identification of drivers at risk of fatigue-related impairment.

Genome-wide interrogation of structural variation reveals novel African-specific prostate cancer oncogenic drivers

BackgroundAfrican ancestry is a significant risk factor for advanced prostate cancer (PCa). Mortality rates in sub-Saharan Africa are 2.5-fold greater than global averages. However, the region has largely been excluded from the benefits of whole genome interrogation studies. Additionally, while structural variation (SV) is highly prevalent, PCa genomic studies are still biased towards small variant interrogation.MethodsUsing whole genome sequencing and best practice workflows, we performed a comprehensive analysis of SVs for 180 (predominantly Gleason score ≥ 8) prostate tumours derived from 115 African, 61 European and four ancestrally admixed patients. We investigated the landscape and relationship of somatic SVs in driving ethnic disparity (African versus European), with a focus on African men from southern Africa.ResultsDuplication events showed the greatest ethnic disparity, with a 1.6- (relative frequency) to 2.5-fold (count) increase in African-derived tumours. Furthermore, we found duplication events to be associated with CDK12 inactivation and MYC copy number gain, and deletion events associated with SPOP mutation. Overall, African-derived tumours were 2-fold more likely to present with a hyper-SV subtype. In addition to hyper-duplication and deletion subtypes, we describe a new hyper-translocation subtype. While we confirm a lower TMPRSS2-ERG fusion-positive rate in tumours from African cases (10% versus 33%), novel African-specific PCa ETS family member and TMPRSS2 fusion partners were identified, including LINC01525, FBXO7, GTF3C2, NTNG1 and YPEL5. Notably, we found 74 somatic SV hotspots impacting 18 new candidate driver genes, with CADM2, LSAMP, PTPRD, PDE4D and PACRG having therapeutic implications for African patients.ConclusionsIn this first African-inclusive SV study for high-risk PCa, we demonstrate the power of SV interrogation for the identification of novel subtypes, oncogenic drivers and therapeutic targets. Identifying a novel spectrum of SVs in tumours derived from African patients provides a mechanism that may contribute, at least in part, to the observed ethnic disparity in advanced PCa presentation in men of African ancestry.

Statistics in marketing research: A brief review on special methods and applications

The work considers statistical techniques developed for solving various special marketing research problems. These approaches include items comparisons in Thurstone and Bradley-Terry scaling, total unduplicated reach and frequency and Shapley value, sample balancing and price sensitivity analysis, customer satisfaction and identification of key drivers, best-worst and max-diff priority estimation, items cannibalization and synergy, and different other methods. The described techniques have been developed and employed in multiple marketing research projects, and they are helpful for successful solving various practical problems.

Identification of atrial fibrillation drivers by means of concentric ring electrodes

Background and objectiveThe prevalence of atrial fibrillation (AF) has tripled in the last 50 years due to population aging. High-frequency (DFdriver) activated atrial regions lead the activation of the rest of the atria, disrupting the propagation wavefront. Fourier based spectral analysis of body surface potential maps have been proposed for DFdriver identification, although these approaches present serious drawbacks due to their limited spectral resolution for short AF epochs and the blurring effect of the volume conductor. Laplacian signals (BC-ECG) from bipolar concentric ring electrodes (CRE) have been shown to outperform the spatial resolution achieved with conventional unipolar recordings. Our aimed was to determine the best DFdriver estimator in endocardial electrograms and to assess the BC-ECG capacity of CRE to quantify AF activity non-invasively. Methods31 AF episodes were simulated using realistic tridimensional models of the atria electrical activity and torso. Periodogram and autoregressive (AR) spectral estimators were computed and the percentile (P90th, P95th and P98th) to impose on the dominant frequencies (DFs) across whole atria to define the best DFdriver estimator evaluated. The identification of DFdriver on DFs from BC-ECG and unipolar surface signals with conventional disc electrodes was compared. ResultsThe best DFdriver estimator was P95th and AR order 100. BC-ECG signals allowed better detection of AF activity than unipolar signals, with a significantly greater percentage of electrode locations in which DFdriver was identified (p-value 0.0095). ConclusionsThe use of BC-ECG signals for body surface Laplacian potential mapping with CRE could be helpful for better AF diagnosis, prognosis and ablation procedures than those with conventional disk electrodes.

Identification of Key Drivers of Cost and Environmental Impact for Biomass-Derived Fuel for Advanced Multimode Engines Based on Techno-Economic and Life Cycle Analysis

Early stage research and development are needed to accelerate the introduction of advanced biofuel and engine technologies. Under the Co-Optima initiative, the U.S. Department of Energy is leveraging capabilities from its nine national laboratories and more than 35 university and industry partners including advanced computational tools, process design, data analysis, and economic and sustainability modeling tools to simultaneously design fuels and engines capable of running efficiently in an affordable, scalable, and sustainable way. In this work, we conducted techno-economic analysis (TEA) and life cycle assessment (LCA) to understand the cost, technology development, and environmental impacts of producing selected bioblendstocks for advanced engines such as multimode (MM) type engines at the commercial scale. We assessed 12 biofuel production pathways from renewable lignocellulosic biomass feedstocks using different conversion technologies (biochemical, thermochemical, or hybrid) to produce target co-optimized biofuels. TEA and LCA were used to evaluate 19 metrics across technology readiness, economic viability, and environmental impact and for each ranked on a set of criteria as favorable, neutral, unfavorable, or unknown. We found that most bioblendstocks presented in this study showed favorable economic metrics, while the technology readiness metrics were mostly neutral. The economic viability results showed potentially competitive target costs of less than $4 per gasoline gallon equivalent (GGE) for six candidates and less than $2.5/GGE for methanol. We identified 10 MM bioblendstock candidates with synergistic blending performance and with the potential to reduce greenhouse gas (GHG) emissions by 60% or more compared to petroleum-derived gasoline. The analysis presented here also provides insights into major economic and sustainability drivers of the production process and potential availability of the feedstocks for producing each MM bioblendstock.

Paving the Way for Circular Economy Innovation: Evidence on Barriers and Drivers

Eco-innovation (EI) has been proposed by scholars, policymakers, and practitioners to be instrumental in achieving the Circular Economy (CE) vision. While the available body of knowledge on EI has largely focused on ‘eco-efficient’ incremental technological innovation, a successful CE transition, however, requires systemic ‘eco-effective’ CE-innovation. Yet, little is known about what barriers and drivers are stimulating systemic CE-innovation in sector specific contexts and geographies. This research aims to mitigate this existing gap in knowledge by delivering an identification of major CE barriers and drivers that hinder or facilitate systemic ‘eco-effective’ CE-innovation—identified in the European polyurethane (PUR) plastics industry. By applying a hybrid research approach using an original combination of the inductive GABEK method (“GAnzheitliche BEwältigung von Komplexität”—holistic processing of complexity) with deductive consideration of existing theories, this article provides novel findings indicating that barriers to CE-innovation largely materialize on individual firm and intra-industrial levels, while drivers to CE-innovation primarily appear beyond immediate industrial boundaries (inter-/cross-industrial). Our key contribution lies on revealing the necessity to reframe the focus from mere individual ‘optimization’—primarily discussed in EI literature—to a collective (horizontal) ‘coordination’ challenge across industries to enable functional CE-innovation. In addition, we deliver five strategic deliberations for managers to facilitate and further advance towards systemic CE-innovation activities.

Implementing Digital, Intelligent and Sustainable Logistics (DISL) to SMEs and Large Companies - Identification and Significance of Drivers and Barriers

Implementing Digital, Intelligent and Sustainable Logistics (DISL) to SMEs and Large Companies - Identification and Significance of Drivers and Barriers

Facilitating systemic eco‐innovation to pave the way for a circular economy: A qualitative‐empirical study on barriers and drivers in the European polyurethane industry

AbstractScholars, politicians, and practitioners have recently advocated that eco‐innovation (EI) is critical to achieve the circular economy (CE) vision. While much of the available body of knowledge on EI has predominantly focused on “eco‐efficient” incremental technological innovation, a successful CE transition requires systemic “eco‐effective” CE innovation. Yet, little is known about what barriers and drivers are stimulating systemic CE innovation in different sectors and regions. This research aims to deliver an identification of major CE barriers and drivers that impede or facilitate systemic “eco‐effective” CE innovation in the European polyurethane plastics industry. A hybrid research approach is applied using an original combination of the inductive GABEK method (“GAnzheitliche BEwältigung von Komplexität”—holistic processing of complexity) with deductive consideration of existing theories. Novel findings indicate that barriers to CE innovation largely materialize on individual firm and intra‐industrial levels, while drivers to CE innovation primarily manifest beyond immediate industrial boundaries (inter‐/cross‐industrial). The key contribution lies on revealing the necessity to reframe the focus from mere individual “optimization”, which has been primarily discussed in the contemporary EI literature, to a collective (horizontal) “coordination” challenge across industries to enable a functional CE innovation. In addition, five strategic deliberations are proposed to facilitate and further advance the management of systemic CE innovation activities.

Of Fears and Budgets: Strategies of Control in Vespa velutina Invasion and Lessons for Best Management Practices

Implementing management practices for the control of invasive species can be a complex task with multiple dimensions, where the identification of stakeholders and drivers of those practices is of paramount importance. The invasive hornet Vespa velutina has spread across Europe and Asia from its native range in SE Asia in recent years. A common control method is the removal and destruction of its nests on citizens’ request to call centers. In this paper we have explored the knowledge and main factors that influence the perceptions of the citizens on the species in an invaded municipality in NW Spain, as well as the management practices of the municipal emergency unit responsible for nest removal activities. Our analysis brings out multiple drivers of management practices that derive both from the citizens’ and practitioners’ knowledge, and highlights several points of conflict between both stakeholder groups connected to (1) the degree of service provided to the local population, (2) the risk of allergic reactions as a motive to urge removals, or (3) the quality of information provided by mass media. Our results support the crucial importance of environmental education programs that seek to increase the knowledge of the general public about the threats of invasive species. Such programs might be incorporated to implement and optimize management plans of V. velutina by enhancing communication between experts and local population.

THE INFLUENCE OF IMPLEMENTATION OF ELECTRONIC TICKETS, POLICY ISSUING PERMISSIONS DRIVING AND DISCIPLINE AGAINST TRAFFIC VIOLATIONS

Traffic Unit (Satlantas) is an implementing element whose duties are responsible for carrying out police duties including in the field of traffic, which is the elaboration of professional technical capabilities which include regulation, guarding, escort, patrolling, public education, and traffic engineering, registration and identification of drivers or motorized vehicles, investigation of traffic accidents and law enforcement in the field of traffic, to maintain security, order, and smooth traffic. This study examined and analyzed the effect of ETLE, SIM issuance policies, and discipline on reducing traffic violations in 5 areas of DKI Jakarta province. This research was conducted on 100 vehicle users using the partial least squares data analysis technique. The results showed that the implementation of ETLE implementation reduced traffic violations; SIM issuance policy reduced traffic violations, and discipline reduced traffic violations

RNA profiling of human dorsal root ganglia reveals sex differences in mechanisms promoting neuropathic pain.

Neuropathic pain is a leading cause of high-impact pain, is often disabling and is poorly managed by current therapeutics. Here we focused on a unique group of neuropathic pain patients undergoing thoracic vertebrectomy where the dorsal root ganglia is removed as part of the surgery allowing for molecular characterization and identification of mechanistic drivers of neuropathic pain independently of preclinical models. Our goal was to quantify whole transcriptome RNA abundances using RNA-seq in pain-associated human dorsal root ganglia from these patients, allowing comprehensive identification of molecular changes in these samples by contrasting them with non-pain-associated dorsal root ganglia. We sequenced 70 human dorsal root ganglia, and among these 50 met inclusion criteria for sufficient neuronal mRNA signal for downstream analysis. Our expression analysis revealed profound sex differences in differentially expressed genes including increase of IL1B, TNF, CXCL14 and OSM in male and CCL1, CCL21, PENK and TLR3 in female dorsal root ganglia associated with neuropathic pain. Coexpression modules revealed enrichment in members of JUN-FOS signalling in males and centromere protein coding genes in females. Neuro-immune signalling pathways revealed distinct cytokine signalling pathways associated with neuropathic pain in males (OSM, LIF, SOCS1) and females (CCL1, CCL19, CCL21). We validated cellular expression profiles of a subset of these findings using RNAscope in situ hybridization. Our findings give direct support for sex differences in underlying mechanisms of neuropathic pain in patient populations.

RRM2 enhances MYCN-driven neuroblastoma formation and acts as a synergistic target with CHK1 inhibition.

High-risk neuroblastoma, a pediatric tumor originating from the sympathetic nervous system, has a low mutation load but highly recurrent somatic DNA copy number variants. Previously, segmental gains and/or amplifications allowed identification of drivers for neuroblastoma development. Using this approach, combined with gene dosage impact on expression and survival, we identified ribonucleotide reductase subunit M2 (RRM2) as a candidate dependency factor further supported by growth inhibition upon in vitro knockdown and accelerated tumor formation in a neuroblastoma zebrafish model coexpressing human RRM2 with MYCN. Forced RRM2 induction alleviates excessive replicative stress induced by CHK1 inhibition, while high RRM2 expression in human neuroblastomas correlates with high CHK1 activity. MYCN-driven zebrafish tumors with RRM2 co-overexpression exhibit differentially expressed DNA repair genes in keeping with enhanced ATR-CHK1 signaling activity. In vitro, RRM2 inhibition enhances intrinsic replication stress checkpoint addiction. Last, combinatorial RRM2-CHK1 inhibition acts synergistic in high-risk neuroblastoma cell lines and patient-derived xenograft models, illustrating the therapeutic potential.

Exploring the main factors influencing habitat preference of Popillia japonica in an area of recent introduction

The possibility of establishment of an invasive species in an area of new introduction is influenced by several factors, including weather conditions, soil characteristics, and species spread dynamics. Disentangling the role of multiple variables on habitat preference can provide important elements supporting the management of invasive species. In this work, we present a modelling framework that allows i) the identification of the main drivers influencing the probability of the presence of the invasive pest Japanese beetle Popillia japonica, in an area of recent introduction in Northern Italy, and ii) the evaluation of bi-dimensional niches to investigate the non-linear combined effects of couples of variables on the potential distribution of this species. Occurrence records of larval populations sampled between 2017 and 2019 in 8488 sites in Northern Italy were used in the present study. The sample sites were characterised based on a set of explanatory variables related to land use, soil characteristics, meteorological conditions, and infestation history. We performed a stepwise logistic regression analysis for testing the statistical significance of explanatory variables on the occurrence of local larval populations. Then, we implemented a Generalized Additive Model to investigate the bi-dimensional ecological niche determined by the interaction of two variables on the probability of the presence of P. japonica. The results highlight the prominent role of soil and weather variables and the infestation history of the species in driving the presence of P. japonica larvae. Less acidic soils, especially with sandy-skeletal particles, are preferred. A high density of P. japonica larvae is associated with medium content of soil organic carbon in the soil. Long drought periods or high precipitation levels reduce the probability of the presence of the species. Non-linear effects are observed between soil temperature variables and habitat preferences of P. japonica. The probability of the presence of P. japonica is also related to the number of years since the first occurrence of the species at the site. The results of the present work provide fundamental elements for guiding the assessment of the risk and the management of P. japonica.

Identification of key drivers of the microbial shikimic acid pathway during different materials composting

Metabolites of shikimic acid (SA) pathway can be used as humic substance (HS) precursors. Due to the complexity of SA anabolism, there were few studies on SA pathway during composting. The aim of this study was to identify the key drivers of SA pathway during different materials composting. During composting, the SA, protocatechuic acid (PA) and gallic acid (GA) decreased by 57.09%, 72.27% and 54.04% on average, respectively. The structural equation model showed that SA had key driving factors (organic matter and pH) during lawn waste composting. In addition, the complexity of material structure was the main factor affecting PA driving factors. The factors and degree of influence on GA varied with different materials. Accordingly, this study provided theoretical support for the improvement of SA metabolic intensity by single material and mixed material composting, and further provided a new direction for future HS research.