Energy Guided Diffusion for Generating Neurally Exciting Images.

In recent years, most exciting inputs (MEIs) synthesized from encoding models of neuronal activity have become an established method to study tuning properties of biological and artificial visual systems. However, as we move up the visual hierarchy, the complexity of neuronal computations increases. Consequently, it becomes more challenging to model neuronal activity, requiring more complex models. In this study, we introduce a new attention readout for a convolutional data-driven core for neurons in macaque V4 that outperforms the state-of-the-art task-driven ResNet model in predicting neuronal responses. However, as the predictive network becomes deeper and more complex, synthesizing MEIs via straightforward gradient ascent (GA) can struggle to produce qualitatively good results and overfit to idiosyncrasies of a more complex model, potentially decreasing the MEI's model-to-brain transferability. To solve this problem, we propose a diffusion-based method for generating MEIs via Energy Guidance (EGG). We show that for models of macaque V4, EGG generates single neuron MEIs that generalize better across architectures than the state-of-the-art GA while preserving the within-architectures activation and requiring 4.7x less compute time. Furthermore, EGG diffusion can be used to generate other neurally exciting images, like most exciting natural images that are on par with a selection of highly activating natural images, or image reconstructions that generalize better across architectures. Finally, EGG is simple to implement, requires no retraining of the diffusion model, and can easily be generalized to provide other characterizations of the visual system, such as invariances. Thus EGG provides a general and flexible framework to study coding properties of the visual system in the context of natural images.

Prenylated Isoflavanones with Antimicrobial Potential from the Root Bark of Dalbergia melanoxylon.

Dalbergia melanoxylon Guill. & Perr (Fabaceae) is widely utilized in the traditional medicine of East Africa, showing effects against a variety of ailments including microbial infections. Phytochemical investigation of the root bark led to the isolation of six previously undescribed prenylated isoflavanones together with eight known secondary metabolites comprising isoflavanoids, neoflavones and an alkyl hydroxylcinnamate. Structures were elucidated based on HR-ESI-MS, 1- and 2-D NMR and ECD spectra. The crude extract and the isolated compounds of D. melanoxylon were tested for their antibacterial, antifungal, anthelmintic and cytotoxic properties, applying established model organisms non-pathogenic to humans. The crude extract exhibited significant antibacterial activity against Gram-positive Bacillus subtilis (97% inhibition at 50 µg/mL) and antifungal activity against the phytopathogens Phytophthora infestans, Botrytis cinerea and Septoria tritici (96, 89 and 73% at 125 µg/mL, respectively). Among the pure compounds tested, kenusanone H and (3R)-tomentosanol B exhibited, in a panel of partially human pathogenic bacteria and fungi, promising antibacterial activity against Gram-positive bacteria including methicillin-resistant Staphylococcus aureus (MRSA) and Mycobacterium showing MIC values between 0.8 and 6.2 µg/mL. The observed biological effects support the traditional use of D. melanoxylon and warrant detailed investigations of its prenylated isoflavanones as antibacterial lead compounds.

Asymmetric distribution of color-opponent response types across mouse visual cortex supports superior color vision in the sky.

Color is an important visual feature that informs behavior, and the retinal basis for color vision has been studied across various vertebrate species. While we know how color information is processed in visual brain areas of primates, we have limited understanding of how it is organized beyond the retina in other species, including most dichromatic mammals. In this study, we systematically characterized how color is represented in the primary visual cortex (V1) of mice. Using large-scale neuronal recordings and a luminance and color noise stimulus, we found that more than a third of neurons in mouse V1 are color-opponent in their receptive field center, while the receptive field surround predominantly captures luminance contrast. Furthermore, we found that color-opponency is especially pronounced in posterior V1 that encodes the sky, matching the statistics of mouse natural scenes. Using unsupervised clustering, we demonstrate that the asymmetry in color representations across cortex can be explained by an uneven distribution of green-On/UV-Off color-opponent response types that are represented in the upper visual field. This type of color-opponency in the receptive field center was not present at the level of the retinal output and, therefore, is likely computed in the cortex by integrating upstream visual signals. Finally, a simple model with natural scene-inspired parametric stimuli shows that green-On/UV-Off color-opponent response types may enhance the detection of "predatory"-like dark UV-objects in noisy daylight scenes. The results from this study highlight the relevance of color processing in the mouse visual system and contribute to our understanding of how color information is organized in the visual hierarchy across species. More broadly, they support the hypothesis that visual cortex combines upstream information towards computing neuronal selectivity to behaviorally-relevant sensory features.

Challenging Structure Elucidation of Lumnitzeralactone, an Ellagic Acid Derivative from the Mangrove Lumnitzera racemosa.

The previously undescribed natural product lumnitzeralactone (1), which represents a derivative of ellagic acid, was isolated from the anti-bacterial extract of the Indonesian mangrove species Lumnitzera racemosa Willd. The structure of lumnitzeralactone (1), a proton-deficient and highly challenging condensed aromatic ring system, was unambiguously elucidated by extensive spectroscopic analyses involving high-resolution mass spectrometry (HRMS), 1D 1H and 13C nuclear magnetic resonance spectroscopy (NMR), and 2D NMR (including 1,1-ADEQUATE and 1,n-ADEQUATE). Determination of the structure was supported by computer-assisted structure elucidation (CASE system applying ACD-SE), density functional theory (DFT) calculations, and a two-step chemical synthesis. Possible biosynthetic pathways involving mangrove-associated fungi have been suggested.

Bipartite invariance in mouse primary visual cortex.

A defining characteristic of intelligent systems, whether natural or artificial, is the ability to generalize and infer behaviorally relevant latent causes from high-dimensional sensory input, despite significant variations in the environment. To understand how brains achieve generalization, it is crucial to identify the features to which neurons respond selectively and invariantly. However, the high-dimensional nature of visual inputs, the non-linearity of information processing in the brain, and limited experimental time make it challenging to systematically characterize neuronal tuning and invariances, especially for natural stimuli. Here, we extended "inception loops" - a paradigm that iterates between large-scale recordings, neural predictive models, and in silico experiments followed by in vivo verification - to systematically characterize single neuron invariances in the mouse primary visual cortex. Using the predictive model we synthesized Diverse Exciting Inputs (DEIs), a set of inputs that differ substantially from each other while each driving a target neuron strongly, and verified these DEIs' efficacy in vivo. We discovered a novel bipartite invariance: one portion of the receptive field encoded phase-invariant texture-like patterns, while the other portion encoded a fixed spatial pattern. Our analysis revealed that the division between the fixed and invariant portions of the receptive fields aligns with object boundaries defined by spatial frequency differences present in highly activating natural images. These findings suggest that bipartite invariance might play a role in segmentation by detecting texture-defined object boundaries, independent of the phase of the texture. We also replicated these bipartite DEIs in the functional connectomics MICrONs data set, which opens the way towards a circuit-level mechanistic understanding of this novel type of invariance. Our study demonstrates the power of using a data-driven deep learning approach to systematically characterize neuronal invariances. By applying this method across the visual hierarchy, cell types, and sensory modalities, we can decipher how latent variables are robustly extracted from natural scenes, leading to a deeper understanding of generalization.

Pattern completion and disruption characterize contextual modulation in mouse visual cortex.

A key role of sensory processing is integrating information across space. Neuronal responses in the visual system are influenced by both local features in the receptive field center and contextual information from the surround. While center-surround interactions have been extensively studied using simple stimuli like gratings, investigating these interactions with more complex, ecologically-relevant stimuli is challenging due to the high dimensionality of the stimulus space. We used large-scale neuronal recordings in mouse primary visual cortex to train convolutional neural network (CNN) models that accurately predicted center-surround interactions for natural stimuli. These models enabled us to synthesize surround stimuli that strongly suppressed or enhanced neuronal responses to the optimal center stimulus, as confirmed by in vivo experiments. In contrast to the common notion that congruent center and surround stimuli are suppressive, we found that excitatory surrounds appeared to complete spatial patterns in the center, while inhibitory surrounds disrupted them. We quantified this effect by demonstrating that CNN-optimized excitatory surround images have strong similarity in neuronal response space with surround images generated by extrapolating the statistical properties of the center, and with patches of natural scenes, which are known to exhibit high spatial correlations. Our findings cannot be explained by theories like redundancy reduction or predictive coding previously linked to contextual modulation in visual cortex. Instead, we demonstrated that a hierarchical probabilistic model incorporating Bayesian inference, and modulating neuronal responses based on prior knowledge of natural scene statistics, can explain our empirical results. We replicated these center-surround effects in the multi-area functional connectomics MICrONS dataset using natural movies as visual stimuli, which opens the way towards understanding circuit level mechanism, such as the contributions of lateral and feedback recurrent connections. Our data-driven modeling approach provides a new understanding of the role of contextual interactions in sensory processing and can be adapted across brain areas, sensory modalities, and species.

Towards a Foundation Model of the Mouse Visual Cortex.

Understanding the brain's perception algorithm is a highly intricate problem, as the inherent complexity of sensory inputs and the brain's nonlinear processing make characterizing sensory representations difficult. Recent studies have shown that functional models-capable of predicting large-scale neuronal activity in response to arbitrary sensory input-can be powerful tools for characterizing neuronal representations by enabling high-throughput in silico experiments. However, accurately modeling responses to dynamic and ecologically relevant inputs like videos remains challenging, particularly when generalizing to new stimulus domains outside the training distribution. Inspired by recent breakthroughs in artificial intelligence, where foundation models-trained on vast quantities of data-have demonstrated remarkable capabilities and generalization, we developed a "foundation model" of the mouse visual cortex: a deep neural network trained on large amounts of neuronal responses to ecological videos from multiple visual cortical areas and mice. The model accurately predicted neuronal responses not only to natural videos but also to various new stimulus domains, such as coherent moving dots and noise patterns, underscoring its generalization abilities. The foundation model could also be adapted to new mice with minimal natural movie training data. We applied the foundation model to the MICrONS dataset: a study of the brain that integrates structure with function at unprecedented scale, containing nanometer-scale morphology, connectivity with >500,000,000 synapses, and function of >70,000 neurons within a ~1mm3 volume spanning multiple areas of the mouse visual cortex. This accurate functional model of the MICrONS data opens the possibility for a systematic characterization of the relationship between circuit structure and function. By precisely capturing the response properties of the visual cortex and generalizing to new stimulus domains and mice, foundation models can pave the way for a deeper understanding of visual computation.

Molecular Modes of Action of an Aqueous Nerium oleander Extract in Cancer Cells In Vitro and In Vivo.

Cancer drug resistance remains a major obstacle in clinical oncology. As most anticancer drugs are of natural origin, we investigated the anticancer potential of a standardized cold-water leaf extract from Nerium oleander L., termed Breastin. The phytochemical characterization by nuclear magnetic resonance spectroscopy (NMR) and low- and high-resolution mass spectrometry revealed several monoglycosidic cardenolides as major constituents (adynerin, neritaloside, odoroside A, odoroside H, oleandrin, and vanderoside). Breastin inhibited the growth of 14 cell lines from hematopoietic tumors and 5 of 6 carcinomas. Remarkably, the cellular responsiveness of odoroside H and neritaloside was not correlated with all other classical drug resistance mechanisms, i.e., ATP-binding cassette transporters (ABCB1, ABCB5, ABCC1, ABCG2), oncogenes (EGFR, RAS), tumor suppressors (TP53, WT1), and others (GSTP1, HSP90, proliferation rate), in 59 tumor cell lines of the National Cancer Institute (NCI, USA), indicating that Breastin may indeed bypass drug resistance. COMPARE analyses with 153 anticancer agents in 74 tumor cell lines of the Oncotest panel revealed frequent correlations of Breastin with mitosis-inhibiting drugs. Using tubulin-GFP-transfected U2OS cells and confocal microscopy, it was found that the microtubule-disturbing effect of Breastin was comparable to that of the tubulin-depolymerizing drug paclitaxel. This result was verified by a tubulin polymerization assay in vitro and molecular docking in silico. Proteome profiling of 3171 proteins in the NCI panel revealed protein subsets whose expression significantly correlated with cellular responsiveness to odoroside H and neritaloside, indicating that protein expression profiles can be identified to predict the sensitivity or resistance of tumor cells to Breastin constituents. Breastin moderately inhibited breast cancer xenograft tumors in vivo. Remarkably, in contrast to what was observed with paclitaxel monotherapy, the combination of paclitaxel and Breastin prevented tumor relapse, indicating Breastin's potential for drug combination regimens.

Characterization and Bioactive Potential of Secondary Metabolites Isolated from Piper sarmentosum Roxb.

Piper sarmentosum Roxb. (Piperaceae) is a traditional medicinal plant in South-East Asian countries. The chemical investigation of leaves from this species resulted in the isolation of three previously not described compounds, namely 4″-(3-hydroxy-3-methylglutaroyl)-2″-ß-D-glucopyranosyl vitexin (1), kadukoside (2), and 6-O-trans-p-coumaroyl-D-glucono-1,4-lactone (3), together with 31 known compounds. Of these known compounds, 21 compounds were isolated for the first time from P. sarmentosum. The structures were established by 1D and 2D NMR techniques and HR-ESI-MS analyses. The compounds were evaluated for their anthelmintic (Caenorhabditis elegans), antifungal (Botrytis cinerea, Septoria tritici and Phytophthora infestans), antibacterial (Aliivibrio fischeri) and cytotoxic (PC-3 and HT-29 human cancer cells lines) activities. Methyl-3-(4-methoxyphenyl)propionate (8), isoasarone (12), and trans-asarone (15) demonstrated anthelmintic activity with IC50 values between 0.9 and 2.04 mM. Kadukoside (2) was most active against S. tritici with IC50 at 5.0 µM and also induced 94% inhibition of P. infestans growth at 125 µM. Trans-asarone (15), piperolactam A (23), and dehydroformouregine (24) displayed a dose-dependent effect against B. cinerea from 1.5 to 125 µM up to more than 80% inhibition. Paprazine (19), cepharadione A (21) and piperolactam A (23) inhibited bacterial growth by more than 85% at 100 µM. Only mild cytotoxic effects were observed.

Lehmanniaside, a new cycloartane triterpene glycoside from Astragalus lehmannianus.

Chemical investigation of the aerial parts of Astragalus lehmannianus Bunge (Leguminosae) led to the isolation and identification of a new cycloartane triterpene glycoside - lehmanniaside (2'-O-acetyl-3-ß-O-D-xylopyranosyl-3ß,6α,16ß,24α-tetrahydroxy-20,25-epoxycycloartane). Its structure was elucidated by means of spectroscopic analysis (HR-MS, 1D and 2D NMR). Bioassays showed that lehmanniaside exhibits weak anthelmintic, antifungal, and cytotoxic activities.

Bichromonol, a dimeric coumarin with anti-HIV activity from the stem bark of Hypericum roeperianum.

Infectious diseases caused by viruses like HIV and SARS-COV-2 (COVID-19) pose serious public health threats. In search for new antiviral small molecules from chemically underexplored Hypericum species, a previously undescribed atropisomeric C8-C8' linked dimeric coumarin named bichromonol (1) was isolated from the stem bark of Hypericum roeperianum. The structure was elucidated by MS data and NMR spectroscopy. The absolute configuration at the biaryl axis was determined by comparing the experimental ECD spectrum with those calculated for the respective atropisomers. Bichromonol was tested in cell-based assays for cytotoxicity against MT-4 (CC50 = 54 µM) cells and anti-HIV activity in infected MT-4 cells. It exhibits significant activity at EC50 = 6.6-12.0 µM against HIV-1 wild type and its clinically relevant mutant strains. Especially, against the resistant variants A17 and EFVR, bichromonol is more effective than the commercial drug nevirapine and might thus have potential to serve as a new anti-HIV lead.

Center-surround interactions underlie bipolar cell motion sensitivity in the mouse retina.

Motion sensing is a critical aspect of vision. We studied the representation of motion in mouse retinal bipolar cells and found that some bipolar cells are radially direction selective, preferring the origin of small object motion trajectories. Using a glutamate sensor, we directly observed bipolar cells synaptic output and found that there are radial direction selective and non-selective bipolar cell types, the majority being selective, and that radial direction selectivity relies on properties of the center-surround receptive field. We used these bipolar cell receptive fields along with connectomics to design biophysical models of downstream cells. The models and additional experiments demonstrated that bipolar cells pass radial direction selective excitation to starburst amacrine cells, which contributes to their directional tuning. As bipolar cells provide excitation to most amacrine and ganglion cells, their radial direction selectivity may contribute to motion processing throughout the visual system.

State-dependent pupil dilation rapidly shifts visual feature selectivity.

To increase computational flexibility, the processing of sensory inputs changes with behavioural context. In the visual system, active behavioural states characterized by motor activity and pupil dilation1,2 enhance sensory responses, but typically leave the preferred stimuli of neurons unchanged2-9. Here we find that behavioural state also modulates stimulus selectivity in the mouse visual cortex in the context of coloured natural scenes. Using population imaging in behaving mice, pharmacology and deep neural network modelling, we identified a rapid shift in colour selectivity towards ultraviolet stimuli during an active behavioural state. This was exclusively caused by state-dependent pupil dilation, which resulted in a dynamic switch from rod to cone photoreceptors, thereby extending their role beyond night and day vision. The change in tuning facilitated the decoding of ethological stimuli, such as aerial predators against the twilight sky10. For decades, studies in neuroscience and cognitive science have used pupil dilation as an indirect measure of brain state. Our data suggest that, in addition, state-dependent pupil dilation itself tunes visual representations to behavioural demands by differentially recruiting rods and cones on fast timescales.

Sustained deep-tissue voltage recording using a fast indicator evolved for two-photon microscopy.

Genetically encoded voltage indicators are emerging tools for monitoring voltage dynamics with cell-type specificity. However, current indicators enable a narrow range of applications due to poor performance under two-photon microscopy, a method of choice for deep-tissue recording. To improve indicators, we developed a multiparameter high-throughput platform to optimize voltage indicators for two-photon microscopy. Using this system, we identified JEDI-2P, an indicator that is faster, brighter, and more sensitive and photostable than its predecessors. We demonstrate that JEDI-2P can report light-evoked responses in axonal termini of Drosophila interneurons and the dendrites and somata of amacrine cells of isolated mouse retina. JEDI-2P can also optically record the voltage dynamics of individual cortical neurons in awake behaving mice for more than 30 min using both resonant-scanning and ULoVE random-access microscopy. Finally, ULoVE recording of JEDI-2P can robustly detect spikes at depths exceeding 400 µm and report voltage correlations in pairs of neurons.

Bioactive Phenolic Compounds from Peperomia obtusifolia.

Peperomia obtusifolia (L.) A. Dietr., native to Middle America, is an ornamental plant also traditionally used for its mild antimicrobial properties. Chemical investigation on the leaves of P. obtusifolia resulted in the isolation of two previously undescribed compounds, named peperomic ester (1) and peperoside (2), together with five known compounds, viz. N-[2-(3,4-dihydroxyphenyl)ethyl]-3,4-dihydroxybenzamide (3), becatamide (4), peperobtusin A (5), peperomin B (6), and arabinothalictoside (7). The structures of these compounds were elucidated by 1D and 2D NMR techniques and HREIMS analyses. Compounds 1-7 were evaluated for their anthelmintic (against Caenorhabditis elegans), antifungal (against Botrytis cinerea, Septoria tritici and Phytophthora infestans), antibacterial (against Bacillus subtilis and Aliivibrio fischeri), and antiproliferative (against PC-3 and HT-29 human cancer cell lines) activities. The known peperobtusin A (5) was the most active compound against the PC-3 cancer cell line with IC50 values of 25.6 µM and 36.0 µM in MTT and CV assays, respectively. This compound also induced 90% inhibition of bacterial growth of the Gram-positive B. subtilis at a concentration of 100 µM. In addition, compound 3 showed anti-oomycotic activity against P. infestans with an inhibition value of 56% by using a concentration of 125 µM. However, no anthelmintic activity was observed.

Suppression without inhibition: how retinal computation contributes to saccadic suppression.

Visual perception remains stable across saccadic eye movements, despite the concurrent strongly disruptive visual flow. This stability is partially associated with a reduction in visual sensitivity, known as saccadic suppression, which already starts in the retina with reduced ganglion cell sensitivity. However, the retinal circuit mechanisms giving rise to such suppression remain unknown. Here, we describe these mechanisms using electrophysiology in mouse, pig, and macaque retina, 2-photon calcium imaging, computational modeling, and human psychophysics. We find that sequential stimuli, like those that naturally occur during saccades, trigger three independent suppressive mechanisms in the retina. The main mechanism is triggered by contrast-reversing sequential stimuli and originates within the receptive field center of ganglion cells. It does not involve inhibition or other known suppressive mechanisms like saturation or adaptation. Instead, it relies on temporal filtering of the inherently slow response of cone photoreceptors coupled with downstream nonlinearities. Two further mechanisms of suppression are present predominantly in ON ganglion cells and originate in the receptive field surround, highlighting another disparity between ON and OFF ganglion cells. The mechanisms uncovered here likely play a role in shaping the retinal output following eye movements and other natural viewing conditions where sequential stimulation is ubiquitous.

Retinal horizontal cells use different synaptic sites for global feedforward and local feedback signaling.

In the outer plexiform layer (OPL) of the mammalian retina, cone photoreceptors (cones) provide input to more than a dozen types of cone bipolar cells (CBCs). In the mouse, this transmission is modulated by a single horizontal cell (HC) type. HCs perform global signaling within their laterally coupled network but also provide local, cone-specific feedback. However, it is unknown how HCs provide local feedback to cones at the same time as global forward signaling to CBCs and where the underlying synapses are located. To assess how HCs simultaneously perform different modes of signaling, we reconstructed the dendritic trees of five HCs as well as cone axon terminals and CBC dendrites in a serial block-face electron microscopy volume and analyzed their connectivity. In addition to the fine HC dendritic tips invaginating cone axon terminals, we also identified "bulbs," short segments of increased dendritic diameter on the primary dendrites of HCs. These bulbs are in an OPL stratum well below the cone axon terminal base and make contacts with other HCs and CBCs. Our results from immunolabeling, electron microscopy, and glutamate imaging suggest that HC bulbs represent GABAergic synapses that do not receive any direct photoreceptor input. Together, our data suggest the existence of two synaptic strata in the mouse OPL, spatially separating cone-specific feedback and feedforward signaling to CBCs. A biophysical model of a HC dendritic branch and voltage imaging support the hypothesis that this spatial arrangement of synaptic contacts allows for simultaneous local feedback and global feedforward signaling by HCs.

Natural environment statistics in the upper and lower visual field are reflected in mouse retinal specializations.

Pressures for survival make sensory circuits adapted to a species' natural habitat and its behavioral challenges. Thus, to advance our understanding of the visual system, it is essential to consider an animal's specific visual environment by capturing natural scenes, characterizing their statistical regularities, and using them to probe visual computations. Mice, a prominent visual system model, have salient visual specializations, being dichromatic with enhanced sensitivity to green and UV in the dorsal and ventral retina, respectively. However, the characteristics of their visual environment that likely have driven these adaptations are rarely considered. Here, we built a UV-green-sensitive camera to record footage from mouse habitats. This footage is publicly available as a resource for mouse vision research. We found chromatic contrast to greatly diverge in the upper, but not the lower, visual field. Moreover, training a convolutional autoencoder on upper, but not lower, visual field scenes was sufficient for the emergence of color-opponent filters, suggesting that this environmental difference might have driven superior chromatic opponency in the ventral mouse retina, supporting color discrimination in the upper visual field. Furthermore, the upper visual field was biased toward dark UV contrasts, paralleled by more light-offset-sensitive ganglion cells in the ventral retina. Finally, footage recorded at twilight suggests that UV promotes aerial predator detection. Our findings support that natural scene statistics shaped early visual processing in evolution.

Anthelmintic and antimicrobial activities of three new depsides and ten known depsides and phenols from Indonesian lichen: Parmelia cetrata Ach.

An extensive phytochemical study of a foliose lichen from Indonesia, Parmelia cetrata, resulted in the successful isolation of 13 phenol and depside derivatives (1-13) including the previously unreported depsides 3'-hydroxyl-5'-pentylphenyl 2,4-dihydroxyl-6-methylbenzoate (7), 3'-hydroxyl-5'-propylphenyl 2,4-dihydroxyl-6-methylbenzoate (8) and 3'-hydroxyl-5'-methylphenyl 2-hydroxyl-4-methoxyl-6-propylbenzoate (9). The anti-infective activity of isolated compounds was evaluated against the gram-negative bacterium Aliivibrio fischeri and the nematode Caenorhabditis elegans. 2,4-Dihydroxyl-6-pentylbenzoate (5) and lecanoric acid (6) induced growth inhibition of A. fischeri with inhibition values of 49% and 100% at a concentration of 100 µM, respectively. The antibacterial activity might be due to their free carboxyl group. A phenolic group at C4 also contributed to the antimicrobial activity of the depsides as shown for compounds 7 and 8, which caused 89% and 96% growth inhibition at 100 µM, respectively. Lecanoric acid (6) in addition possesses significant anthelmintic effects causing 80% mortality of C. elegans at 100 µg/mL.

PSYCHE-A Valuable Experiment in Plant NMR-Metabolomics.

1H-NMR is a very reproducible spectroscopic method and, therefore, a powerful tool for the metabolomic analysis of biological samples. However, due to the high complexity of natural samples, such as plant extracts, the evaluation of spectra is difficult because of signal overlap. The new NMR "Pure Shift" methods improve spectral resolution by suppressing homonuclear coupling and turning multiplets into singlets. The PSYCHE (Pure Shift yielded by Chirp excitation) and the Zangger-Sterk pulse sequence were tested. The parameters of the more suitable PSYCHE experiment were optimized, and the extracts of 21 Hypericum species were measured. Different evaluation criteria were used to compare the suitability of the PSYCHE experiment with conventional 1H-NMR. The relationship between the integral of a signal and the related bin value established by linear regression demonstrates an equal representation of the integrals in binned PSYCHE spectra compared to conventional 1H-NMR. Using multivariate data analysis based on both techniques reveals comparable results. The obtained data demonstrate that Pure Shift spectra can support the evaluation of conventional 1H-NMR experiments.