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Abstract Anxiety disorders are the most prevalent mental health conditions. Besides psycho-pharmacotherapy, cognitive behavioral therapy with an exposure-based approach is considered the gold standard. However, not all patients benefit from this approach. Here, we aimed to translate laboratory findings on enhanced fear extinction with repetitive transcranial magnetic stimulation (TMS) to the clinic. In this double-blind, randomized, placebo-controlled clinical trial, 76 participants with acrophobia received an activating intermittent theta burst stimulation (iTBS) targeting the left posterior prefrontal cortex immediately before two virtual reality exposure therapy sessions. Phobic symptoms were assessed at baseline, post-intervention, and a 6-month follow-up. Results revealed a significant reduction in phobic symptoms from baseline to post-assessment and follow-up and confirmed the efficacy of virtual reality exposure therapy as a treatment for specific phobias. Interestingly, no additional effect was observed for active iTBS compared to sham iTBS. Our post-hoc analyses argue for an individualized TMS application. Further research is needed to determine optimal TMS parameters and validate these results in clinical trials, accounting for methodological and inter- and intra-individual variability, as well as alternative therapeutic processes.

Abstract Recent results have evidenced that spontaneous brain activity signals are organized in bursts with scale free features and long-range spatio-temporal correlations. These observations have stimulated a theoretical interpretation of results inspired in critical phenomena. In particular, relying on maximum entropy arguments, certain aspects of time-averaged experimental neuronal data have been recently described using Ising-like models, allowing the study of neuronal networks under an analogous thermodynamical framework. This method has been so far applied to a variety of experimental datasets, but never to a biologically inspired neuronal network with short and long-term plasticity. Here, we apply for the first time the Maximum Entropy method to an Integrate-and-fire (IF) model that can be tuned at criticality, offering a controlled setting for a systematic study of criticality and finite-size effects in spontaneous neuronal activity, as opposed to experiments. We consider generalized Ising Hamiltonians whose local magnetic fields and interaction parameters are assigned according to the average activity of single neurons and correlation functions between neurons of the IF networks in the critical state. We show that these Hamiltonians exhibit a spin glass phase for low temperatures, having mostly negative intrinsic fields and a bimodal distribution of interaction constants that tends to become unimodal for larger networks. Results evidence that the magnetization and the response functions exhibit the expected singular behavior near the critical point. Furthermore, we also found that networks with higher percentage of inhibitory neurons lead to Ising-like systems with reduced thermal fluctuations. Finally, considering only neuronal pairs associated with the largest correlation functions allows the study of larger system sizes.

Abstract We analyze time-averaged experimental data from in vitro activities of neuronal networks. Through a Pairwise Maximum-Entropy method, we identify through an inverse binary Ising-like model the local fields and interaction couplings which best reproduce the average activities of each neuron as well as the statistical correlations between the activities of each pair of neurons in the system. The specific information about the type of neurons is mainly stored in the local fields, while a symmetric distribution of interaction constants seems generic. Our findings demonstrate that, despite not being directly incorporated into the inference approach, the experimentally observed correlations among groups of three neurons are accurately captured by the derived Ising-like model. Within the context of the thermodynamic analogy inherent to the Ising-like models developed in this study, our findings additionally indicate that these models demonstrate characteristics of second-order phase transitions between ferromagnetic and paramagnetic states at temperatures above, but close to, unity. Considering that the operating temperature utilized in the Maximum-Entropy method is $$T_{o}=1$$ T o = 1 , this observation further expands the thermodynamic conceptual parallelism postulated in this work for the manifestation of criticality in neuronal network behavior.

Abstract Hospital admissions due to acute cardiovascular events dropped during the COVID-19 pandemic in the general population; however, evidence for residents of long-term care facilities (LTCF) is sparse. We investigated rates of hospital admissions and deaths due to myocardial infarction (MI) and stroke in LTCF residents during the pandemic. Our nationwide cohort study used claims data. The sample comprised 1,140,139 AOK-ensured LTCF residents over 60 years of age (68.6% women; age 85.3 ± 8.5 years) from the largest statutory health insurance in Germany (AOK), which is not representative for all LTCF residents. We included MI and stroke admission and compared numbers of in-hospital deaths from January 2020 to end of April 2021 (i.e., during the first three waves of the pandemic) with the number of incidences in 2015–2019. To estimate incidence risk ratios (IRR), adjusted Poisson regression analyses were applied. During the observation period (2015–2021), there were 19,196 MI and 73,953 stroke admissions. MI admissions declined in the pandemic phase by 22.5% (IRR = 0.68 [CI 0.65–0.72]) compared to previous years. This decline was slightly more pronounced for NSTEMI than for STEMI. MI fatality risks remained comparable across years (IRR = 0.97 [CI95% 0.92–1.02]). Stroke admissions dropped by 15.1% (IRR = 0.75 [CI95% 0.72–0.78]) in the pandemic. There was an elevated case fatality risk for haemorrhagic stroke (IRR = 1.09 [CI95% 1.03–1.15]) but not for other stroke subtypes compared to previous years. This study provides first evidence of declines in MI and stroke admissions and in-hospital deaths among LTCF residents during the pandemic. The figures are alarming given the acute nature of the conditions and the vulnerability of the residents.

Abstract Spin-lock based functional magnetic resonance imaging (fMRI) has the potential for direct spatially-resolved detection of neuronal activity and thus may represent an important step for basic research in neuroscience. In this work, the corresponding fundamental effect of Rotary EXcitation (REX) is investigated both in simulations as well as in phantom and in vivo experiments. An empirical law for predicting optimal spin-lock pulse durations for maximum magnetic field sensitivity was found. Experimental conditions were established that allow robust detection of ultra-weak magnetic field oscillations with simultaneous compensation of static field inhomogeneities. Furthermore, this work presents a novel concept for the emulation of brain activity utilizing the built-in MRI gradient system, which allows REX sequences to be validated in vivo under controlled and reproducible conditions. Via transmission of Rotary EXcitation (tREX), we successfully detected magnetic field oscillations in the lower nano-Tesla range in brain tissue. Moreover, tREX paves the way for the quantification of biomagnetic fields.

Abstract Physical activity is a cornerstone in the treatment of obesity and metabolic syndrome (MetS). Given the leading physical activity barrier of time commitment and safety concerns about vigorous exercise in high-risk groups, this study aimed to investigate the effects of two extremely time-efficient training protocols (

Abstract Neurodegenerative diseases show an increase in prevalence and incidence, with the most prominent example being Alzheimer’s disease. DNA damage has been suggested to play a role in the pathogenesis, but the exact mechanisms remain elusive. We enrolled 425 participants with and without neurodegenerative diseases and analyzed DNA damage in the form of micronuclei in buccal mucosa samples. In addition, other parameters such as binucleated cells, karyolytic cells, and karyorrhectic cells were quantified. No relevant differences in DNA damage and cytotoxicity markers were observed in patients compared to healthy participants. Furthermore, other parameters such as lifestyle factors and diseases were also investigated. Overall, this study could not identify a direct link between changes in buccal cells and neurogenerative diseases, but highlights the influence of lifestyle factors and diseases on the human buccal cytome.

Abstract How big is the risk that a few initial failures of nodes in a network amplify to large cascades that span a substantial share of all nodes? Predicting the final cascade size is critical to ensure the functioning of a system as a whole. Yet, this task is hampered by uncertain and missing information. In infinitely large networks, the average cascade size can often be estimated by approaches building on local tree and mean field approximations. Yet, as we demonstrate, in finite networks, this average does not need to be a likely outcome. Instead, we find broad and even bimodal cascade size distributions. This phenomenon persists for system sizes up to 107 and different cascade models, i.e. it is relevant for most real systems. To show this, we derive explicit closed-form solutions for the full probability distribution of the final cascade size. We focus on two topological limit cases, the complete network representing a dense network with a very narrow degree distribution, and the star network representing a sparse network with a inhomogeneous degree distribution. Those topologies are of great interest, as they either minimize or maximize the average cascade size and are common motifs in many real world networks.

Abstract We propose a targeted intervention protocol where recovery is restricted to individuals that have the least number of infected neighbours. Our recovery strategy is highly efficient on any kind of network, since epidemic outbreaks are minimal when compared to the baseline scenario of spontaneous recovery. In the case of spatially embedded networks, we find that an epidemic stays strongly spatially confined with a characteristic length scale undergoing a random walk. We demonstrate numerically and analytically that this dynamics leads to an epidemic spot with a flat surface structure and a radius that grows linearly with the spreading rate.

Abstract Recent studies have proposed that the diffusion of messenger molecules, such as monoamines, can mediate the plastic adaptation of synapses in supervised learning of neural networks. Based on these findings we developed a model for neural learning, where the signal for plastic adaptation is assumed to propagate through the extracellular space. We investigate the conditions allowing learning of Boolean rules in a neural network. Even fully excitatory networks show very good learning performances. Moreover, the investigation of the plastic adaptation features optimizing the performance suggests that learning is very sensitive to the extent of the plastic adaptation and the spatial range of synaptic connections.

Abstract Many examples of natural systems can be described by random Gaussian surfaces. Much can be learned by analyzing the Fourier expansion of the surfaces, from which it is possible to determine the corresponding Hurst exponent and consequently establish the presence of scale invariance. We show that this symmetry is not affected by the distribution of the modulus of the Fourier coefficients. Furthermore, we investigate the role of the Fourier phases of random surfaces. In particular, we show how the surface is affected by a non-uniform distribution of phases.

Collagen fibers, one of the key load-bearing components of the extracellular matrix, contribute significantly to tissue integrity through their mechanical properties of strain-dependent stiffening. This study investigated the effects of bacterial collagenase on the mechanical behavior of individual bovine lung collagen fibers in the presence or absence of mechanical forces, with a focus on potential implications for emphysema, a condition associated with collagen degradation and alveolar wall rupture. Tensile tests were conducted on individual collagen fibers isolated from bovine lung tissue. The rate of degradation was characterized by the change in fiber Young's modulus during 60 min of digestion under various mechanical conditions mimicking the mechanical stresses on the fibers during breathing. Compared to digestion without mechanical forces, a significantly larger drop of fiber modulus was observed in the presence of static or intermittent mechanical forces. Fiber yield stress was also reduced after digestion indicating compromised fiber failure. By incorporating fibril waviness obtained by scanning electron microscopic images, an analytic model allowed estimation of fibril modulus. A computational model that incorporated waviness and the results of tensile tests was also developed to simulate and interpret the data. The simulation results provided insights into the mechanical consequences of bacterial collagenase and mechanical forces on collagen fibers, revealing both fibril softening and rupture during digestion. These findings shed light on the microscale changes in collagen fiber structure and mechanics under enzymatic digestion and breathing-like mechanical stresses with implications for diseases that are impacted by collagen degradation such as emphysema., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Sample preparation in untargeted metabolomics should allow reproducible extractions of as many molecules as possible. Thus, optimizing sample preparation is crucial. This study compared six different extraction procedures to find the most suitable for extracting zebrafish larvae in the context of an infection model. Two one-phase extractions employing methanol (I) and a single miscible phase of methanol/acetonitrile/water (II) and two two-phase methods using phase separation between chloroform and methanol/water combinations (III and IV) were tested. Additional bead homogenization was used for methods III and IV (III_B and IV_B). Nine internal standards and 59 molecules of interest (MoInt) related to mycobacterial infection were used for method evaluation. Two-phase methods (III and IV) led to a lower feature count, higher peak areas of MoInt, especially amino acids, and higher coefficients of variation in comparison to one-phase extractions. Adding bead homogenization increased feature count, peak areas, and CVs. Extraction I showed higher peak areas and lower CVs than extraction II, thus being the most suited one-phase method. Extraction III and IV showed similar results, with III being easier to execute and less prone to imprecisions. Thus, for future applications in zebrafish larvae metabolomics and infection models, extractions I and III might be chosen., (© 2023. The Author(s).)

Long-term sequelae in hospitalized Coronavirus Disease 2019 (COVID-19) patients may result in limited quality of life. The current study aimed to determine health-related quality of life (HRQoL) after COVID-19 hospitalization in non-intensive care unit (ICU) and ICU patients. This is a single-center study at the University Hospital of Wuerzburg, Germany. Patients eligible were hospitalized with COVID-19 between March 2020 and December 2020. Patients were interviewed 3 and 12 months after hospital discharge. Questionnaires included the European Quality of Life 5 Dimensions 5 Level (EQ-5D-5L), patient health questionnaire-9 (PHQ-9), the generalized anxiety disorder 7 scale (GAD-7), FACIT fatigue scale, perceived stress scale (PSS-10) and posttraumatic symptom scale 10 (PTSS-10). 85 patients were included in the study. The EQ5D-5L-Index significantly differed between non-ICU (0.78 ± 0.33 and 0.84 ± 0.23) and ICU (0.71 ± 0.27; 0.74 ± 0.2) patients after 3- and 12-months. Of non-ICU 87% and 80% of ICU survivors lived at home without support after 12 months. One-third of ICU and half of the non-ICU patients returned to work. A higher percentage of ICU patients was limited in their activities of daily living compared to non-ICU patients. Depression and fatigue were present in one fifth of the ICU patients. Stress levels remained high with only 24% of non-ICU and 3% of ICU patients (p = 0.0186) having low perceived stress. Posttraumatic symptoms were present in 5% of non-ICU and 10% of ICU patients. HRQoL is limited in COVID-19 ICU patients 3- and 12-months post COVID-19 hospitalization, with significantly less improvement at 12-months compared to non-ICU patients. Mental disorders were common highlighting the complexity of post-COVID-19 symptoms as well as the necessity to educate patients and primary care providers about monitoring mental well-being post COVID-19., (© 2023. The Author(s).)

Insect-provided pollination services are increasingly threatened due to alarming declines in insect pollinator populations. One of the main threats to insect pollinators and consequently pollination is urbanisation. Here, we investigate the effects of local habitat quality (patch size, flowering plant richness, bare soil cover, vegetation structure), degree of urbanisation (impervious surfaces) and 3D connectivity on bee, hoverfly and butterfly flower visitors and plant-flower visitor networks in flower-rich urban dry grasslands. Overall, the degree of urbanisation and the quality of the local habitat influenced the flowering plant and pollinator communities. Although flowering plant abundance increased with urbanisation, bee species richness and butterfly species richness decreased with increasing impervious surfaces. Flowering plant richness and ground nesting resource availability were positively related to bee richness and local vegetation structure boosted hoverfly and butterfly visitation rates. In terms of plant-pollinator interactions, insect pollinators visited a lower proportion of the available flowering plants in more urbanised areas and network modularity and specialisation increased with patch size. Our findings show that urban dry grasslands are valuable habitats for species-rich pollinator communities and further highlight the importance of minimizing the intensity of urbanisation and the potential of local management practices to support insect biodiversity in cities., (© 2023. The Author(s).)

Previous studies have indicated that glabellar botulinum toxin (BTX) injections may lead to a sustained alleviation of depression. This may be accomplished by the disruption of a facial feedback loop, which potentially mitigates the experience of negative emotions. Accordingly, glabellar BTX injection can attenuate amygdala activity in response to emotional stimuli. A prototypic condition with an excess of negative emotionality and impulsivity accompanied by elevated amygdala reactivity to emotional stimuli is borderline personality disorder (BPD). In order to improve the understanding of how glabellar BTX may affect the processing of emotional stimuli and impulsivity, we conducted a functional magnetic resonance imaging (fMRI) study. Our hypotheses were (1) glabellar BTX leads to increased activation in prefrontal areas during inhibition performance and (2) BTX decreases amygdala activity during the processing of emotional stimuli in general. Using an emotional go-/no-go paradigm during fMRI, the interference of emotion processing and impulsivity in a sample of n = 45 women with BPD was assessed. Subjects were randomly assigned to BTX treatment or serial acupuncture (ACU) of the head. After 4 weeks, both treatments led to a reduction in the symptoms of BPD. However, BTX treatment was specifically associated with improved inhibition performance and increased activity in the motor cortex. In addition, the processing of negative emotional faces was accompanied by a reduction in right amygdala activity. This study provides the first evidence that glabellar BTX injections may modify central neurobiological and behavioural aspects of BPD. Since the control treatment produced similar clinical effects, these neurobiological findings may be specific to BTX and not a general correlate of symptomatic improvement., (© 2022. The Author(s).)

The relationship between pressure (P) and volume (V) in the human lung has been extensively studied. However, the combined effects of gravity and the mechanical properties of elastin and collagen on alveolar and lung P-V curves during breathing are not well understood. Here, we extended a previously established thick-walled spherical model of a single alveolus with wavy collagen fibers during positive pressure inflation. First, we updated the model for negative pressure-driven inflation that allowed incorporation of a gravity-induced pleural pressure gradient to predict how the static alveolar P-V relations vary spatially throughout an upright human lung. Second, by introducing dynamic surface tension and collagen viscoelasticity, we computed the hysteresis loop of the lung P-V curve. The model was tested by comparing its predicted regional ventilation to literature data, which offered insight into the effects of microgravity on ventilation. The model has also produced novel testable predictions for future experiments about the variation of mechanical stresses in the septal walls and the contribution of collagen and elastin fibers to the P-V curve and throughout the lung. The model may help us better understand how mechanical stresses arising from breathing and pleural pressure variations affect regional cellular mechanotransduction in the lung., (© 2022. The Author(s).)

Fibrotic diseases are characterized by progressive and often irreversible scarring of connective tissue in various organs, leading to substantial changes in tissue mechanics largely as a result of alterations in collagen structure. This is particularly important in the lung because its bulk modulus is so critical to the volume changes that take place during breathing. Nevertheless, it remains unclear how fibrotic abnormalities in the mechanical properties of pulmonary connective tissue can be linked to the stiffening of its individual collagen fibers. To address this question, we developed a network model of randomly oriented collagen and elastin fibers to represent pulmonary alveolar wall tissue. We show that the stress-strain behavior of this model arises via the interactions of collagen and elastin fiber networks and is critically dependent on the relative fiber stiffnesses of the individual collagen and elastin fibers themselves. We also show that the progression from linear to nonlinear stress-strain behavior of the model is associated with the percolation of stress across the collagen fiber network, but that the location of the percolation threshold is influenced by the waviness of collagen fibers., (© 2021. The Author(s).)

The purpose of this study was to develop a fully-automated segmentation algorithm, robust to various density enhancing lung abnormalities, to facilitate rapid quantitative analysis of computed tomography images. A polymorphic training approach is proposed, in which both specifically labeled left and right lungs of humans with COPD, and nonspecifically labeled lungs of animals with acute lung injury, were incorporated into training a single neural network. The resulting network is intended for predicting left and right lung regions in humans with or without diffuse opacification and consolidation. Performance of the proposed lung segmentation algorithm was extensively evaluated on CT scans of subjects with COPD, confirmed COVID-19, lung cancer, and IPF, despite no labeled training data of the latter three diseases. Lobar segmentations were obtained using the left and right lung segmentation as input to the LobeNet algorithm. Regional lobar analysis was performed using hierarchical clustering to identify radiographic subtypes of COVID-19. The proposed lung segmentation algorithm was quantitatively evaluated using semi-automated and manually-corrected segmentations in 87 COVID-19 CT images, achieving an average symmetric surface distance of [Formula: see text] mm and Dice coefficient of [Formula: see text]. Hierarchical clustering identified four radiographical phenotypes of COVID-19 based on lobar fractions of consolidated and poorly aerated tissue. Lower left and lower right lobes were consistently more afflicted with poor aeration and consolidation. However, the most severe cases demonstrated involvement of all lobes. The polymorphic training approach was able to accurately segment COVID-19 cases with diffuse consolidation without requiring COVID-19 cases for training.

Particle deposition in the lung during inhalation is of interest to a wide range of biomedical sciences due to the noninvasive therapeutic route to deliver drugs to the lung and other organs via the blood stream. Before reaching the alveoli, particles must transverse the bifurcating network of airways. Computational fluid mechanical studies are often used to estimate high-fidelity flow patterns through the large conducting airways, but there is a need for reduced-dimensional modeling that enables rapid parameter optimization while accommodating the complete airway network. Here, we introduce a Markov chain model with each state corresponding to an airway segment in which a particle may be located. The local flows and transition probabilities of the Markov chain, verified against computational fluid dynamics simulations, indicate that the independent effects of three fundamental forces (gravity, fluid drag, diffusion) provide a sufficient approximation of overall particle behavior. The model enables fast computation of how different inhalation strategies, called flow policies, determine total particle escape rates and local particle deposition. In a 3-dimensional airway tree model, the optimal flow policy minimizing the risk of deposition at each generation, compared to other inlet flow waveforms, predicted significantly higher probability of escape defined as the fraction of particles exiting the tree. The model also predicts a small influence of body orientation with respect to a gravitational field on total escape probability, but a significant effect of airway narrowing on regional deposition. In summary, this model provides insight into inhalation strategies for targeted drug delivery.

Serum amyloid A (SAA) is an uremic toxin and acute phase protein. It accumulates under inflammatory conditions associated with high cardiovascular morbidity and mortality in patients with sepsis or end-stage renal disease (ESRD). SAA is an apolipoprotein of the high-density lipoprotein (HDL). SAA accumulation turns HDL from an anti-inflammatory to a pro-inflammatory particle. SAA activates monocyte chemoattractant protein-1 (MCP-1) in vascular smooth muscle cells. However, the SAA receptor-mediated signaling pathway in vascular cells is poorly understood. Therefore, the SAA-mediated signaling pathway for MCP-1 production was investigated in this study. The SAA-induced MCP-1 production is dependent on the activation of TLR2 and TLR4 as determined by studies with specific receptor antagonists and agonists or siRNA approach. Experiments were confirmed in tissues from TLR2 knockout, TLR4 deficient and TLR2 knock-out/TLR4 deficient mice. The intracellular signaling pathway is IκBα and subsequently NFκB dependent. The MCP-1 production induced by SAA-enriched HDL and HDL isolated from septic patients with high SAA content is also TLR2 and TLR4 dependent. Taken together, the TLR2 and TLR4 receptors are functional SAA receptors mediating MCP-1 release. Furthermore, the TLR2 and TLR4 are receptors for dysfunctional HDL. These results give a further inside in SAA as uremic toxin involved in uremia-related pro-inflammatory response in the vascular wall.

We analytically and numerically investigate magneto-plasmons in metal films surrounded by a ferromagnetic dielectric. In such waveguide using a metal film with a thickness exceeding the Skin depth, an external magnetic field in the transverse direction can induce a significant spatial asymmetry of mode distribution. Superposition of the odd and the even asymmetric modes over a distance leads to a concentration of the energy on one interface which is switched to the other interface by the magnetic field reversal. The requested magnitude of magnetization is exponentially reduced with the increase of the metal film thickness. Based on this phenomenon, we propose a waveguide-integrated magnetically controlled switchable plasmonic routers with 99-%-high contrast within the optical bandwidth of tens of THz. This configuration can also operate as a magneto-plasmonic modulator.

Three-dimensional models of kidney tissue that recapitulate human responses are needed for drug screening, disease modeling, and, ultimately, kidney organ engineering. Here, we report a bioprinting method for creating 3D human renal proximal tubules in vitro that are fully embedded within an extracellular matrix and housed in perfusable tissue chips, allowing them to be maintained for greater than two months. Their convoluted tubular architecture is circumscribed by proximal tubule epithelial cells and actively perfused through the open lumen. These engineered 3D proximal tubules on chip exhibit significantly enhanced epithelial morphology and functional properties relative to the same cells grown on 2D controls with or without perfusion. Upon introducing the nephrotoxin, Cyclosporine A, the epithelial barrier is disrupted in a dose-dependent manner. Our bioprinting method provides a new route for programmably fabricating advanced human kidney tissue models on demand., Competing Interests: K.A.H., D.B.K., M.S.S. and J.A.L. are named as co-inventors on patent applications WO2015069619 and 62157239, which are based, in part, on the research reported herein. A.M. works for Roche Pharmaceutical Sciences, who provided partial funding for this work. The other authors declare that they have no competing interests.

Bacterial competent cells are essential for cloning, construction of DNA libraries, and mutagenesis in every molecular biology laboratory. Among various transformation methods, electroporation is found to own the best transformation efficiency. Previous electroporation methods are based on washing and electroporating the bacterial cells in ice-cold condition that make them fragile and prone to death. Here we present simple temperature shift based methods that improve DNA transformation and recombineering efficiency in E. coli and several other gram-negative bacteria thereby economizing time and cost. Increased transformation efficiency of large DNA molecules is a significant advantage that might facilitate the cloning of large fragments from genomic DNA preparations and metagenomics samples.

Disorazol, a macrocyclic polykitide produced by the myxobacterium Sorangium cellulosum So ce12 and it is reported to have potential cytotoxic activity towards several cancer cell lines, including multi-drug resistant cells. The disorazol biosynthetic gene cluster (dis) from Sorangium cellulosum (So ce12) was identified by transposon mutagenesis and cloned in a bacterial artificial chromosome (BAC) library. The 58-kb dis core gene cluster was reconstituted from BACs via Red/ET recombineering and expressed in Myxococcus xanthus DK1622. For the first time ever, a myxobacterial trans-AT polyketide synthase has been expressed heterologously in this study. Expression in M. xanthus allowed us to optimize the yield of several biosynthetic products using promoter engineering. The insertion of an artificial synthetic promoter upstream of the disD gene encoding a discrete acyl transferase (AT), together with an oxidoreductase (Or), resulted in 7-fold increase in disorazol production. The successful reconstitution and expression of the genetic sequences encoding for these promising cytotoxic compounds will allow combinatorial biosynthesis to generate novel disorazol derivatives for further bioactivity evaluation.