Molecular Network Analysis Research Articles

Cultivable epiphytic bacteria of the Chlorophyta Ulva sp.: diversity, antibacterial, and biofilm-modulating activities.

Macroalgae harbor a rich epiphytic microbiota that plays a crucial role in algal morphogenesis and defense mechanisms. This study aims to isolate epiphytic cultivable microbiota from Ulva sp. surfaces. Various culture media were employed to evaluate a wide range of cultivable microbiota. Our objective was to assess the antibacterial and biofilm-modulating activities of supernatants from isolated bacteria. Sixty-nine bacterial isolates from Ulva sp. were identified based on 16S rRNA gene sequencing. Their antibacterial activity and biofilm modulation potential were screened against three target marine bacteria: 45%, mostly affiliated with Gammaproteobacteria and mainly grown on diluted R2A medium (R2Ad), showed strong antibacterial activity, while 18% had a significant impact on biofilm modulation. Molecular network analysis was carried out on four bioactive bacterial supernatants, revealing new molecules potentially responsible for their activities. R2Ad offered the greatest diversity and proportion of active isolates. The molecular network approach holds promise for both identifying bacterial isolates based on their molecular production and characterizing antibacterial and biofilm-modulating activities.

Syntrophic Jiont of Sulfate-Reducing Bacteria and Hydrogen-Producing Acetogen Stimulated Methane Production from Waste Activated Sludge Digestion

Anaerobic digestion of waste-activated sludge (WAS) towards biogas recovery is constrained by the limited hydrolysis and inhibited acetogenesis steps that hinder subsequent energy recovery. This study employed Fe(VI)/S(IV) oxidation to enhance the WAS solubilization and coupled it with the syntrophic interaction of hydrogen-producing acetogen (HPA) and sulfate-reducing bacteria (SRB) to stimulate the successive procedure towards methane production. Results showed that the dosage ratio of HPA-SRB to WAS (H-S-W) with 1:1:50 outperformed with the highest methane production potential (11.63 ± 1.87 mL CH4/(g VSS·d). Meanwhile, the efficient and sequential process from acetogenesis to methanogenesis stimulated by HPA-SRB was evidenced by a significant decrease of 30.2% in the acetate concentration. The microbial community structure further manifested the crucial role of HPA-SRB with increased abundance of Desulfobulbus (2.07%), Syntrophomonas (1.24%) and Smithella (1.63%), which stimulated acetophilic methanogen boost with Methanobacterium dominating with 77.51% in H-S-W100. Furthermore, the positive syntrophic relationships among HPA-SRB and acetophilic methanogens towards methane production were confirmed via molecular ecological network and canonical correspondence analysis. This study highlighted the syntrophic cooperation of the mixed consortia of HPA and SRB on methane production based on Fe(VI)/S(IV) pretreatment and provided the theoretical and technical basis for the potential implementation of novel methanogenesis technology for WAS treatment.

AlphaFold2 Predictions of Conformational Ensembles and Atomistic Simulations of the SARS-CoV-2 Spike XBB Lineages Reveal Epistatic Couplings between Convergent Mutational Hotspots that Control ACE2 Affinity.

In this study, we combined AlphaFold-based atomistic structural modeling, microsecond molecular simulations, mutational profiling, and network analysis to characterize binding mechanisms of the SARS-CoV-2 spike protein with the host receptor ACE2 for a series of Omicron XBB variants including XBB.1.5, XBB.1.5+L455F, XBB.1.5+F456L, and XBB.1.5+L455F+F456L. AlphaFold-based structural and dynamic modeling of SARS-CoV-2 Spike XBB lineages can accurately predict the experimental structures and characterize conformational ensembles of the spike protein complexes with the ACE2. Microsecond molecular dynamics simulations identified important differences in the conformational landscapes and equilibrium ensembles of the XBB variants, suggesting that combining AlphaFold predictions of multiple conformations with molecular dynamics simulations can provide a complementary approach for the characterization of functional protein states and binding mechanisms. Using the ensemble-based mutational profiling of protein residues and physics-based rigorous calculations of binding affinities, we identified binding energy hotspots and characterized the molecular basis underlying epistatic couplings between convergent mutational hotspots. Consistent with the experiments, the results revealed the mediating role of the Q493 hotspot in the synchronization of epistatic couplings between L455F and F456L mutations, providing a quantitative insight into the energetic determinants underlying binding differences between XBB lineages. We also proposed a network-based perturbation approach for mutational profiling of allosteric communications and uncovered the important relationships between allosteric centers mediating long-range communication and binding hotspots of epistatic couplings. The results of this study support a mechanism in which the binding mechanisms of the XBB variants may be determined by epistatic effects between convergent evolutionary hotspots that control ACE2 binding.

Organic management pattern improves microbial community diversity and alters microbial network structure in karst tea plantation

Soil microbiomes play a crucial role in enhancing plant growth, health, and overall agricultural productivity. Nevertheless, the influence of distinct agricultural management practices on the microbial diversity and community structure within tea (Camellia sinensis) plantations has remained enigmatic. This study postulates that organic agricultural management models can enhance microbial diversity and optimise the microbial community structure within tea plantations, indirectly augmenting soil fertility and tea quality. We employed metagenome technology and conducted molecular ecological network analysis to explore the impact of organic management, pollution-free management, and conventional management on the microbial network structure of tea plantation soil in Weng'an County in the southwestern karst region. Soils subjected to organic management exhibited a higher relative abundance of soil microbial and carbohydrate-active enzyme functional genes than those subjected to other management regimes. Additionally, the relative abundance and diversity of dominant bacteria and keystone species were notably higher under organic management than under the other management regimes. Correlation analysis showed that soil microorganisms were closely related to soil fertility and tea quality, respectively. One-way analysis of variance and the structural equation modelling results showed significant variability in soil fertility under the three agricultural management modes and that soil fertility and soil microbial diversity had a direct impact on tea quality (P > 0.05). In conclusion, this study underscores the profound impact of management modes on microbial diversity and community structure within tea plantations. These management practices alter the soil microbial network structure and potential function, ultimately regulating the microecological dynamics of the soil community in tea plantations.

Rapid investigating of phase I metabolites of SR9009 in vitro horse liver microsomes via feature-based molecular networking approach: Potential applications in doping control

SR9009, a peroxisome proliferator-activated receptor δ (PPARδ) agonist, is known for its potential benefits in energy homeostasis. It failed to receive the United States Food and Drug Administration (USFDA) approval and its illegal distribution has raised concerns. As a result, it has been classified as a prohibited substance by the World Anti-Doping Agency and the International Federation of Horseracing Authorities (IFHA). This study emphasizes the application of the in-silico molecular networking technology to analyze phase I drug metabolites in horses, distinguishing it from conventional methodologies in forensic science. Feature-based molecular networking (FBMN) analysis identified 15 metabolites, with novel major N-dealkylated metabolite (-C8H7NO4S), indicative of diverse metabolic modifications in horse liver microsomes incubation assay. Additionally, a proposed metabolic pathway of SR9009 in the in vitro assay was outlined, including the previously known dehydroxylated metabolite. Finally, the metabolic pathways included in this study were as follows: hydroxylation, dehydrogenation, N-dealkylation dihydroxylation, and combinations. Molecular networking provided insights into MS spectra connectivity, facilitating rapid interpretation and accurate detection of previously undiscovered metabolites. In conclusion, this study contributes to the understanding of SR9009 metabolism in horses and underscores the importance of advanced analytical techniques, such as molecular networking, in enhancing the accuracy and efficiency of metabolite analysis for forensic and doping control purposes.

Hepatitis C virus subtype diversity and transmission clusters characteristics among drug users in Zhuhai, South China

BackgroundHepatitis C virus (HCV) infection poses a major public health challenge globally, especially among injecting drug users. China has the world’s largest burden of HCV infections. However, little is known about the characteristics of transmission networks among drug user populations. This study aims to investigate the molecular epidemiology and transmission characteristics of HCV infections among drug users in Zhuhai, a bustling port city connecting Mainland China and its Special Administrative Regions.MethodsParticipants enrolled in this study were drug users incarcerated at Zhuhai’s drug rehabilitation center in 2015. Their sociodemographic and behavioral information, including gender, promiscuity, drug use method, and so forth, was collected using a standardized questionnaire. Plasmas separated from venous blood were analyzed for HCV infection through ELISA and RT-PCR methods to detect anti-HCV antibodies and HCV RNA. The 5’UTR fragment of the HCV genome was amplified and further sequenced for subtype identifications and phylogenetic analysis. The phylogenetic tree was inferred using the Maximum Likelihood method based on the Tamura-Nei model, and the transmission cluster network was constructed using Cytoscape3.8.0 software with a threshold of 0.015. Binary logistic regression models were employed to assess the factors associated with HCV infection.ResultsThe overall prevalence of HCV infection among drug users was 44.37%, with approximately 19.69% appearing to clear the HCV virus successfully. Binary logistic regression analysis revealed that those aged over 40, engaging in injecting drug use, and being native residents were at heightened risk for HCV infection among drug user cohorts. The predominant HCV subtypes circulating among those drug users were 6a (60.26%), followed by 3b (16.7%), 3a (12.8%), 1b (6.41%) and 1a (3.85%), respectively. Molecular transmission network analysis unveiled the presence of six transmission clusters, with the largest propagation cluster consisting of 41 individuals infected with HCV subtype 6a. Furthermore, distinct transmission clusters involved eight individuals infected with subtype 3b and seven with subtype 3a were also observed.ConclusionThe genetic transmission networks revealed a complex transmission pattern among drug users in Zhuhai, emphasizing the imperative for a targeted and effective intervention strategy to mitigate HCV dissemination. These insights are pivotal for shaping future national policies on HCV screening, treatment, and prevention in port cities.

Chemical Investigation of the Calcareous Marine Sponge Pericharax heteroraphis, Clathridine-A Related Derivatives Isolation, Synthesis and Osteogenic Activity.

As a result of screening a panel of marine organisms to identify lead molecules for the stimulation of endochondral bone formation, the calcareous sponge Pericharax heteroraphis was identified to exhibit significant activity during endochondral differentiation. On further molecular networking analysis, dereplication and chemical fractionation yielded the known clathridine A-related metabolites 3-6 and the homodimeric complex (clathridine A)2 Zn2+ (9), together with the new unstable heterodimeric complex (clathridine A-clathridimine)Zn2+ (10). With the presence of the zinc complexes annotated through the LC-MS analysis of the crude extract changing due to the instability of some metabolites and complexes constituting the mixture, we combined the isolation of the predicted molecules with their synthesis in order to confirm their structure and to understand their reactivity. Interestingly, we also found a large quantity of the contaminant benzotriazoles BTZ (7) and its semi-dimer (BTZ)2CH2 (8), which are known to form complexes with transition metals and are used for preventing corrosion in water. All isolated 2-aminoimidazole derivatives and complexes were synthesized not only for structural confirmation and chemical understanding but to further study their bioactivity during endochondral differentiation, particularly the positively screened imidazolone derivatives. Compounds leucettamine B, clathridine A and clathridimine were found to increase type X collagen transcription and stimulate endochondral ossification in the ATDC5 micromass model.

Effect of Poria cocos Terpenes: Verifying Modes of Action Using Molecular Docking, Drug-Induced Transcriptomes, and Diffusion Network Analyses.

We characterized the therapeutic biological modes of action of several terpenes in Poria cocos F.A Wolf (PC) and proposed a broad therapeutic mode of action for PC. Molecular docking and drug-induced transcriptome analysis were performed to confirm the pharmacological mechanism of PC terpene, and a new analysis method, namely diffusion network analysis, was proposed to verify the mechanism of action against Alzheimer's disease. We confirmed that the compound that exists only in PC has a unique mechanism through statistical-based docking analysis. Also, docking and transcriptomic analysis results could reflect results in clinical practice when used complementarily. The detailed pharmacological mechanism of PC was confirmed by constructing and analyzing the Alzheimer's disease diffusion network, and the antioxidant activity based on microglial cells was verified. In this study, we used two bioinformatics approaches to reveal PC's broad mode of action while also using diffusion networks to identify its detailed pharmacological mechanisms of action. The results of this study provide evidence that future pharmacological mechanism analysis should simultaneously consider complementary docking and transcriptomics and suggest diffusion network analysis, a new method to derive pharmacological mechanisms based on natural complex compounds.

Characterization and Discrimination of Marigold Oleoresin from Different Origins Based on UPLC-QTOF-MS Combined Molecular Networking and Multivariate Statistical Analysis.

Marigold oleoresin is an oil-soluble natural colorant mainly extracted from marigold flowers. Xinjiang of China, India, and Zambia of Africa are the three main production areas of marigold flowers. Therefore, this study utilized ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS/MS) technology, combined with Global Natural Products Social Molecular Networking (GNPS) and multivariate statistical analysis, for the qualitative and discriminant analysis of marigold oleoresin obtained from three different regions. Firstly, 83 compounds were identified in these marigold oleoresin samples. Furthermore, the results of a principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) indicated significant differences in the chemical compositions of the marigold oleoresin samples from different regions. Finally, 12, 23, and 38 differential metabolites were, respectively, identified by comparing the marigold oleoresin from Africa with Xinjiang, Africa with India, and Xinjiang with India. In summary, these results can be used to distinguish marigold oleoresin samples from different regions, laying a solid foundation for further quality control and providing a theoretical basis for assessing its safety and nutritional aspects.

Secondary metabolite profiling of Pseudomonas aeruginosa isolates reveals rare genomic traits.

Pseudomonas aeruginosa is a ubiquitous Gram-negative opportunistic pathogen with remarkable phylogenetic and phenotypic variabilities. In this work, we applied classical molecular networking analysis to secondary metabolite profiling data from seven Pseudomonas aeruginosa strains, including five clinical isolates from the lung secretions of people with cystic fibrosis (CF). We provide three vignettes illustrating how secondary metabolite profiling aids in the identification of rare genomics traits in P. aeruginosa. First, we describe the identification of a previously unreported class of acyl putrescines produced by isolate mFLRO1. Secondary analysis of publicly available metabolomics data revealed that acyl putrescines are produced by <5% of P. aeruginosa strains. Second, we show that isolate SH3A does not produce di-rhamnolipids. Whole-genome sequencing and comparative genomics revealed that SH3A cannot produce di-rhamnolipids because its genome belongs to clade 5 of the P. aeruginosa phylogenetic tree. Previous phylogenetic analysis of thousands of P. aeruginosa strains concluded that <1% of publicly available genome sequences contribute to this clade. Last, we show that isolate SH1B does not produce the phenazine pyocyanin or rhamnolipids because it has a one-base insertion frameshift mutation (678insC) in the gene rhlR, which disrupts rhl-driven quorum sensing. Secondary analysis of the tens of thousands of publicly available genomes in the National Center for Biotechnology Information (NCBI) and the Pseudomonas Genome Database revealed that this mutation was present in only four P. aeruginosa genomes. Taken together, this study highlights that secondary metabolite profiling combined with genomic analysis can identify rare genetic traits of P. aeruginosa isolates.IMPORTANCESecondary metabolite profiling of five Pseudomonas aeruginosa isolates from cystic fibrosis sputum captured three traits present in <1%-5% of publicly available data, pointing to how our current library of P. aeruginosa strains may not represent the diversity within this species or the genetic variance that occurs in the CF lung.

Nitrogen addition changed soil fungal community structure and increased the biomass of functional fungi in Korean pine plantations in temperate northeast China

Nitrogen (N) deposition is a global environmental issue that can have significant impacts on the community structure and function in ecosystems. Fungi play a key role in soil biogeochemical cycles and their community structures are tightly linked to the health and productivity of forest ecosystems. Based on high-throughput sequencing and ergosterol extraction, we examined the changes in community structure, composition, and biomass of soil ectomycorrhizal (ECM) and saprophytic (SAP) fungi in 0–10 cm soil layer after 8 years of continuous N addition and their driving factors in a temperate Korean pine plantation in northeast China. Our results showed that N addition increased fungal community richness, with the highest richness and Chao1 index under the low N treatment (LN: 20 kg N ha−1 yr−1). Based on the FUN Guild database, we found that the relative abundance of ECM and SAP fungi increased first and then decreased with increasing N deposition concentration. The molecular ecological network analysis showed that the interaction between ECM and SAP fungi was enhanced by N addition, and the interaction was mainly positive in the ECM fungal network. N addition increased fungal biomass, and the total fungal biomass (TFB) was the highest under the MN treatment (6.05 ± 0.3 mg g−1).Overall, we concluded that N addition changed soil biochemical parameters, increased fungal activity, and enhanced functional fungal interactions in the Korean pine plantation over an 8-year simulated N addition. We need to consider the effects of complex soil conditions on soil fungi and emphasize the importance of regulating soil fungal community structure and biomass for managing forest ecosystems. These findings could deepen our understanding of the effects of increased N deposition on soil fungi in temperate forests in northern China, which can provide the theoretical basis for reducing the effects of increased N deposition on forest soil.

Molecular Networking‐Guided Discovery of Kyonggic Acids in Massilia spp.

AbstractIn recent years, bacteria of the genus Massilia have been identified as promising sources of bioactive natural products. In this study, we used mass spectrometry (MS)‐based molecular networking for the first comprehensive analysis of the secondary metabolome of these microorganisms. Annotation of the detected metabolite clusters with a mass fragmentation database revealed several compounds not previously known to be produced by Massilia species. To secure sufficient material for further structural analyses as well as biological testing, we selected the most promising producer strains from our molecular networking analysis and subjected them to larger‐scale cultivation. Following extraction and UV‐directed isolation, we obtained five metabolites in milligram quantities. In addition to a cyclic dipeptide, we elucidated the structures of four acyl amino acids that are related to thalassotalic acid C from the marine bacterium Thalassotalea sp. The Massilia‐derived kyonggic acids were found to inhibit the enzyme tyrosinase, which is involved in melanin biosynthesis influencing skin and hair pigmentation. This study illustrates the value of combining spectroscopic and computational tools in natural product discovery in order to detect and guide the isolation of previously overlooked bioactive compounds.

Discovery of components in honeysuckle for treating COVID-19 and diabetes based on molecular docking, network analysis and experimental validation.

Molecular docking screening identified ochnaflavone, madreselvin B and hydnocarpin as key components for treating COVID-19 with diabetes in honeysuckle using 3 C-like protease (Mpro), angiotensin-converting enzyme 2 (ACE2), and dipeptidyl peptidase 4 (DPP4) as molecular docking targets, ACE2, DPP4, IL2, NFKB1, PLG, TBK1, TLR4 and TNF were the core targets, and multiple antiviral and anti-inflammatory signalling pathways were involved. Further, the levels of IL-1β and DPP4 in cell supernatant that had been activated by LPS was decreased by hypnocarpin, and ACE2 protein and DPP4 mRNA in cells were down-regulated. Overall, we have identified three components from honeysuckle that have potency to treat COVID-19 combined with diabetes. SARS-CoV-2 transcription may be inhibited by these components in honeysuckle, reducing virus invasion, inhibiting inflammatory factors, and improving immune response. Our findings could provide a basis for the clinical application and further development of honeysuckle.

Dynamic molecular network analysis of iPSC-Purkinje cells differentiation delineates roles of ISG15 in SCA1 at the earliest stage

Better understanding of the earliest molecular pathologies of all neurodegenerative diseases is expected to improve human therapeutics. We investigated the earliest molecular pathology of spinocerebellar ataxia type 1 (SCA1), a rare familial neurodegenerative disease that primarily induces death and dysfunction of cerebellum Purkinje cells. Extensive prior studies have identified involvement of transcription or RNA-splicing factors in the molecular pathology of SCA1. However, the regulatory network of SCA1 pathology, especially central regulators of the earliest developmental stages and inflammatory events, remains incompletely understood. Here, we elucidated the earliest developmental pathology of SCA1 using originally developed dynamic molecular network analyses of sequentially acquired RNA-seq data during differentiation of SCA1 patient-derived induced pluripotent stem cells (iPSCs) to Purkinje cells. Dynamic molecular network analysis implicated histone genes and cytokine-relevant immune response genes at the earliest stages of development, and revealed relevance of ISG15 to the following degradation and accumulation of mutant ataxin-1 in Purkinje cells of SCA1 model mice and human patients.

Analysis of shear shock waves in soft materials: From periodic elastic laminates and fibre-reinforced composites to molecular chain networks

We investigate the effect of microstructure and molecular length-scale structures on the formation of shear shock waves in soft materials. We consider (i) soft materials with layered microstructures, (ii) transversely isotropic fibre-reinforced composites (FC), as well as (iii) molecular chain networks, using homogenised energy density functions at the continuum scale. Critical conditions for the formation of shear shocks are found analytically for laminates and FCs, and are shown to depend only on the angle between the initial orientation direction and the applied load. We elucidate the effects of the microstructural material parameters on the shock formation distance. Our results show that increased stiffness ratio and volume fraction of fibres decreases the shock formation distance. The analysis of molecular chain networks indicates that an increase in the entanglement increases the critical shock formation distance. We also highlight that by an appropriate choice of loading and material parameters, shock formation can be avoided, providing guidance for design of protective materials and structures.

Metabolomics Approach to Explore Bioactive Natural Products Derived From Plant-Root-Associated Streptomyces.

Streptomyces, a prominent genus within the Actinomycetota phylum, is responsible for over 60% of clinically relevant antibiotics. Streptomyces strains inhabiting plant roots possess the potential to synthesize bioactive natural products, conferring defense and resilience to plants against pathogenic microorganisms. However, this potential remains largely unexplored. This study aims to screen for bioactive metabolites produced by Streptomyces strains in the plant rhizosphere.Six Streptomyces isolates were cultivated using three modified media to induce the production of diverse metabolites, employing the One Strain Many Compounds (OSMAC) approach. The metabolites present in extracts from fermentation broths were examined through a non-targeted Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS) approach coupled with Global Natural Products Social Molecular Networking (GNPS MN). The antimicrobial activity of the extracts was assessed using the disc diffusion method.The strains demonstrated a wide-ranging antimicrobial efficacy against all examined organisms. The GNPS molecular network analyses reveal that metabolite profiles in extracts can exhibit variations based on the medium and solvent system employed. Notably, the ethyl acetate and dichloromethane extracts from Streptomyces sp. CAH29, cultivated in Glucose-Yeast Extract Medium (GYM), exhibited inhibition diameters of up to 30mm against both Staphylococcus aureus and Candida albicans. Within the metabolomes of these strains, the antibiotics spiramycin and actinomycin were detected. Additionally, lyngbatoxin, a tumor promoter, and potential new analogs were identified. Significantly, a considerable portion of the produced metabolites did not align with any known compounds, indicating the existence of unidentified metabolites generated by these strains. This suggests the possibility of introducing novel chemical entities.Our study illustrated that Streptomyces strains associated with plant roots could be considered a valuable source of bioactive secondary metabolites. Furthermore, the metabolomics approach utilized in this study serves as a rapid and valuable tool for the screening of microorganisms capable of producing bioactive metabolites.

Exploring HIV-1 Transmission Features Among Older Individuals in Developed Eastern China.

The number of newly reported HIV-1 infections among older individuals (≥50 years of age) has increased rapidly in Hangzhou, a central city in the Yangtze River Delta region of China. To provide a scientific basis for prevention and intervention strategies targeted at older individuals in Hangzhou, an epidemiological survey combined with molecular transmission network analysis was conducted. A total of 2,899 individuals with newly confirmed HIV-1 infections, including 635 older individuals and 2,264 younger individuals (<50 years of age), were enrolled in this study. Among older individuals, heterosexual contact was the predominant mode of HIV-1 transmission. In addition, it was observed that older individuals with lower levels of education exhibited a higher susceptibility to HIV-1 infection. The analysis of transmission network, which was inferred using HIV-TRACE algorithm, revealed that the newly diagnosed HIV-1 infections among older individuals in Hangzhou exhibited a pattern of scattered transmission, with key clusters primarily located in non-main urban areas. The predominant mode of transmission in these areas was nonmarital and noncommercial or nonmarital and commercial heterosexual transmission. Notably, the study highlighted a significant proportion of older individuals (73.3%, 11/15) within B subtype. Multivariate logistic regression analysis further revealed that the subtype B was a significant factor associated with older individuals having ≥3 node degrees in the network, occurring 5.55 times more frequent than subtype CRF07_BC (95% confidence intervals = 1.17-26.22, p = .031). Furthermore, the lower CD4 levels observed among older individuals underscored the challenge of late diagnosis in Hangzhou. Taken together, it is imperative to test and intervene for high-risk older individuals. To tackle this issue effectively, it is essential to enhance the detection of the B subtype and implement targeted interventions in key clusters within non-main urban areas. In addition, proactive measures should be implemented to address the challenge of late diagnosis in Hangzhou by promoting widespread testing among the older individuals, particularly in priority areas.

A combined toxicokinetic and metabolic approach to investigate deschloro-N-ethylketamine exposure in a multidrug user

The use of new psychoactive substances derived from ketamine is rarely reported in France. A chronic GHB, 3-MMC, and methoxetamine consumer presented a loss of consciousness in a chemsex context and was referred to the intensive care unit with a rapid and favorable outcome. To investigate the chemicals responsible for the intoxication, a comprehensive analysis was conducted on the ten plasma samples collected over a 29.5-hour period, urine obtained upon admission, a 2-cm hair strand sample, and a seized crystal. These analyses were performed using liquid chromatography hyphenated to high resolution tandem mass spectrometry operating in targeted and untargeted modes. Additionally, analyses using gas chromatography coupled to mass spectrometry and nuclear magnetic resonance were conducted to probe the composition of the seized crystal. The molecular network-based approach was employed for data processing in non-targeted analyses. It allowed to confirm a multidrug exposure encompassing GHB, methyl-(aminopropyl)benzofuran (MAPB), (aminopropyl)benzofuran (APB), methylmethcathinone, chloromethcathinone, and a new psychoactive substance belonging to the arylcyclohexylamine family namely deschloro-N-ethyl-ketamine (O-PCE). Molecular network analysis facilitated the annotation of 27 O-PCE metabolites, including phase II compounds not previously reported. Plasma kinetics of O-PCE allowed the estimation of the elimination half-life of ∼5 hours. Kinetics of O-PCE metabolites was additionally characterized, possibly useful as surrogate biomarkers of consumption. We also observed marked alterations in lipid metabolism related to poly consumption of drugs. In conclusion, this case report provides a comprehensive analysis of exposure to O-PCE in a multidrug user including kinetic and metabolism data in human.

Targeted isolation, identification, and antioxidant evaluation of aromatic polyketides from a plant-derived fungus Ophiobolus cirsii LZU-1509

There are >350 species of the Ophiobolus genus, which is not yet very well-known and lacks research reports on secondary metabolites. Three new 3,4-benzofuran polyketides 1–3, a new 3,4-benzofuran polyketide racemate 4, two new pairs of polyketide enantiomers (±)-5 and (±)-7, two new acetophenone derivatives 6 and 8, and three novel 1,4-dioxane aromatic polyketides 9–11, were isolated from a fungus Ophiobolus cirsii LZU-1509 derived from an important medicinal and economic crop Anaphalis lactea. The isolation was guided by LC-MS/MS-based GNPS molecular networking analysis. The planar structures and relative configurations were mainly elucidated by NMR and HR-ESI-MS data. Their absolute configurations were determined by using X-ray diffraction analysis and via comparing computational and experimental ECD, NMR, and specific optical rotation data. 9 possesses an unreported 5/6/6/6/5 five-ring framework with a 1,4-dioxane, and 10 and 11 feature unprecedented 6/6/6/5 and 6/6/5/6 four-ring frames containing a 1,4-dioxane. The biosynthetic pathways of 9–11 were proposed. 1–11 were nontoxic in HT-1080 and HepG2 tumor cells at a concentration of 20 μM, whereas 3 and 5 exerted higher antioxidant properties in the hydrogen peroxide-stimulated model in the neuron-like PC12 cells. They could be potential antioxidant agents for neuroprotection.

Thiosulfate/FeCl3 pre-treatment enhances short-chain fatty acid production and mitigates H2S generation during anaerobic fermentation of waste activated sludge: Performance, microbial community and ecological analyses

Anaerobic fermentation (AF) has been identified as a promising method of transforming waste activated sludge (WAS) into high-value products (e.g., short-chain fatty acids (SCFAs)). This study developed thiosulfate/FeCl3 pre-treatment and investigated the effects of different thiosulfate/FeCl3 ratios (S:Fe = 3:1, 3:2, 1:1, 3:4 and 3:5) on SCFA production and sulfur transformation during the AF of WAS. At a S:Fe ratio of 1:1, the maximal SCFA yield (933.3 mg COD/L) and efficient H2S removal (96.5 %) were obtained. S:Fe ratios ≤ 1:1 not only benefited hydrolysis and acidification but largely mitigated H2S generation. These results were supported by the enriched acidogens and reduced sulfur-reducing bacteria (SRB). Molecular ecological network analysis further revealed that the keystone taxon (g_Saccharimonadales) was found in S:Fe = 1:1, together with reductions in associations among methanogens, acidogens and SRB. This work provides a strategy for enhancing high-value product recovery from WAS and minimising H2S emissions.