Collective magnetotaxis of microbial holobionts is optimized by the three-dimensional organization and magnetic properties of ectosymbionts.

Over the last few decades, symbiosis and the concept of holobiont-a host entity with a population of symbionts-have gained a central role in our understanding of life functioning and diversification. Regardless of the type of partner interactions, understanding how the biophysical properties of each individual symbiont and their assembly may generate collective behaviors at the holobiont scale remains a fundamental challenge. This is particularly intriguing in the case of the newly discovered magnetotactic holobionts (MHB) whose motility relies on a collective magnetotaxis (i.e., a magnetic field-assisted motility guided by a chemoaerotaxis system). This complex behavior raises many questions regarding how magnetic properties of symbionts determine holobiont magnetism and motility. Here, a suite of light-, electron- and X-ray-based microscopy techniques [including X-ray magnetic circular dichroism (XMCD)] reveals that symbionts optimize the motility, the ultrastructure, and the magnetic properties of MHBs from the microscale to the nanoscale. In the case of these magnetic symbionts, the magnetic moment transferred to the host cell is in excess (102 to 103 times stronger than free-living magnetotactic bacteria), well above the threshold for the host cell to gain a magnetotactic advantage. The surface organization of symbionts is explicitly presented herein, depicting bacterial membrane structures that ensure longitudinal alignment of cells. Magnetic dipole and nanocrystalline orientations of magnetosomes were also shown to be consistently oriented in the longitudinal direction, maximizing the magnetic moment of each symbiont. With an excessive magnetic moment given to the host cell, the benefit provided by magnetosome biomineralization beyond magnetotaxis can be questioned.

Vitamin C alleviates hyperglycemic stress in retinal pigment epithelial cells.

BACKGROUND: Retinal pigment epithelial cells (RPECs) are a type of retinal cells that structurally and physiologically support photoreceptors. However, hyperglycemia has been shown to play a critical role in the progression of diabetic retinopathy (DR), which is one of the leading causes of vision impairment. In the diabetic eye, the high glucose environment damages RPECs via the induction of oxidative stress, leading to the release of excess reactive oxygen species (ROS) and triggering apoptosis. In this study, we aim to investigate the antioxidant mechanism of Vitamin C in reducing hyperglycemia-induced stress and whether this mechanism can preserve the function of RPECs. METHODS AND RESULTS: ARPE-19 cells were treated with high glucose in the presence or absence of Vitamin C. Cell viability was measured by MTT assay. Cleaved poly ADP-ribose polymerase (PARP) was used to identify apoptosis in the cells. ROS were detected by the DCFH-DA reaction. The accumulation of sorbitol in the aldose reductase (AR) polyol pathway was determined using the sorbitol detection assay. Primary mouse RPECs were isolated from adult mice and identified by Rpe65 expression. The mitochondrial damage was measured by mitochondrial membrane depolarization. Our results showed that high glucose conditions reduce cell viability in RPECs while Vitamin C can restore cell viability, compared to the vehicle treatment. We also demonstrated that Vitamin C reduces hyperglycemia-induced ROS production and prevents cell apoptosis in RPECs in an AR-independent pathway. CONCLUSIONS: These results suggest that Vitamin C is not only a nutritional necessity but also an adjuvant that can be combined with AR inhibitors for alleviating hyperglycemic stress in RPECs.

Complete Pathologic Response to Neoadjuvant Chemoimmunotherapy and Oxaliplatin-Induced Fever Associated With IL-6 Release in a Patient With Locally Advanced Colon Cancer

Neoadjuvant systemic therapy is a preferred treatment approach for a number of tumor types due to many potential advantages over upfront surgery, including tumor downstaging, early treatment of micrometastatic disease, and providing an in vivo test of tumor biology. For colon cancer, current standard of care is upfront surgery followed by adjuvant systemic therapy in high-risk patients. Concerns about inaccurate radiological staging and tumor progression during preoperative treatment, as well the lack of randomized data demonstrating benefit, are among the reasons for the limited use of neoadjuvant therapy in this disease. Locally advanced colon cancer, defined as primary colon cancer with direct invasion into the adjacent structures or extensive regional lymph node involvement, is not always amenable to pathological complete resection, and when attempted it comes with high incidence of postoperative morbidity and mortality because of the required multivisceral resection. Clinical trials of neoadjuvant chemotherapy for colon cancer to date have been promising with downstaging of disease and higher rates of R0 resection. Here, we report a case of a patient with locally advanced, unresectable, mismatch repair deficient sigmoid colon cancer who was treated with neoadjuvant chemoimmunotherapy followed by surgical resection leading to a complete pathologic response after preoperative systemic chemoimmunotherapy.

A 65-Year-Old Man With Back Pain and Imaging Findings of Spinal Cord Compression.

Spinal cord compression is a potentially devastating consequence of cancer. Early recognition of the signs and symptoms permit diagnosis prior to the development of irreversible neurological damage. This complication occurs in 5% to 10% of patients with malignancy, often at the end stages of the patient's illness; however, it can be the presenting manifestation of malignancy in up to 23% of patients. With the advances in surgical, radiation, and medical oncology approaches, the outcomes of patients with malignant spinal cord compression continue to improve. We discuss the case of a previously healthy man, aged 65 years, who presented with back pain and large T8 spinal mass, leading to a diagnosis of multiple myeloma with spinal cord compromise.

Recurrent EGFR-Mutated Non-Small Cell Lung Cancer Discovered by Abnormal Mammogram: Adjuvant/Frontline Metastatic Management Options.

Breast metastasis from extramammary malignancy is rare, with a reported incidence rate of 0.4% to 1.3% in the published literature. The primary malignancies that most commonly metastasize to the breast are leukemia, lymphoma, and malignant melanoma. Here, we report a very rare case of metastatic EGFR-mutated non-small cell lung cancer (NSCLC) in the breast detected by screening mammography. The patient had initially been diagnosed with a clinical stage IIIA NSCLC and had been treated with neoadjuvant chemoradiation followed by curative-intent surgery. Several interesting aspects of the case, along with a discussion of evolving adjuvant and frontline metastatic management options in EGFR-mutated NSCLC, will be presented.

Enzyme Conformation Influences the Performance of Lipase-powered Nanomotors.

Enzyme-powered micro/nanomotors have myriads of potential applications in various areas. To efficiently reach those applications, it is necessary and critical to understand the fundamental aspects affecting the motion dynamics. Herein, we explored the impact of enzyme orientation on the performance of lipase-powered nanomotors by tuning the lipase immobilization strategies. The influence of the lipase orientation and lid conformation on substrate binding and catalysis was analyzed using molecular dynamics simulations. Besides, the motion performance indicates that the hydrophobic binding (via OTES) represents the best orienting strategy, providing 48.4 % and 95.4 % increase in diffusion coefficient compared to hydrophilic binding (via APTES) and Brownian motion (no fuel), respectively (with C[triacetin] of 100 mm). This work provides vital evidence for the importance of immobilization strategy and corresponding enzyme orientation for the catalytic activity and in turn, the motion performance of nanomotors, and is thus helpful to future applications.

Disposable amperometric immunosensor for Saccharomyces cerevisiae based on carboxylated graphene oxide-modified electrodes.

A sensitive and disposable amperometric immunosensor for Saccharomyces cerevisiae was constructed by using carbon screen-printed electrodes modified with propionic acid-functionalized graphene oxide as transduction element. The affinity-based biosensing interface was assembled by covalent immobilization of a specific polyclonal antibody on the carboxylate-enriched electrode surface via a water-soluble carbodiimide/N-hydroxysuccinimide coupling approach. A concanavalin A-peroxidase conjugate was further used as signaling element. The immunosensor allowed the amperometric detection of the yeast in buffer solution and white wine samples in the range of 10-107 CFU/mL. This electroanalytical device also exhibited low detection limit and high selectivity, reproducibility, and storage stability. The immunosensor was successfully validated in spiked white wine samples.

Photochemical CVD of Ru on functionalized self-assembled monolayers from organometallic precursors.

Chemical vapor deposition (CVD) is an attractive technique for the metallization of organic thin films because it is selective and the thickness of the deposited film can easily be controlled. However, thermal CVD processes often require high temperatures which are generally incompatible with organic films. In this paper, we perform proof-of-concept studies of photochemical CVD to metallize organic thin films. In this method, a precursor undergoes photolytic decomposition to generate thermally labile intermediates prior to adsorption on the sample. Three readily available Ru precursors, CpRu(CO)2Me, (η3-allyl)Ru(CO)3Br, and (COT)Ru(CO)3, were employed to investigate the role of precursor quantum yield, ligand chemistry, and the Ru oxidation state on the deposition. To investigate the role of the substrate chemistry on deposition, carboxylic acid-, hydroxyl-, and methyl-terminated self-assembled monolayers were used. The data indicate that moderate quantum yields for ligand loss (φ ≥ 0.4) are required for ruthenium deposition, and the deposition is wavelength dependent. Second, anionic polyhapto ligands such as cyclopentadienyl and allyl are more difficult to remove than carbonyls, halides, and alkyls. Third, in contrast to the atomic layer deposition, acid-base reactions between the precursor and the substrate are more effective for deposition than nucleophilic reactions. Finally, the data suggest that selective deposition can be achieved on organic thin films by judicious choice of precursor and functional groups present on the substrate. These studies thus provide guidelines for the rational design of new precursors specifically for selective photochemical CVD on organic substrates.

Molecular Properties of Drugs Interacting with SLC22 Transporters OAT1, OAT3, OCT1, and OCT2: A Machine-Learning Approach.

Statistical analysis was performed on physicochemical descriptors of ∼250 drugs known to interact with one or more SLC22 "drug" transporters (i.e., SLC22A6 or OAT1, SLC22A8 or OAT3, SLC22A1 or OCT1, and SLC22A2 or OCT2), followed by application of machine-learning methods and wet laboratory testing of novel predictions. In addition to molecular charge, organic anion transporters (OATs) were found to prefer interacting with planar structures, whereas organic cation transporters (OCTs) interact with more three-dimensional structures (i.e., greater SP3 character). Moreover, compared with OAT1 ligands, OAT3 ligands possess more acyclic tetravalent bonds and have a more zwitterionic/cationic character. In contrast, OCT1 and OCT2 ligands were not clearly distinquishable form one another by the methods employed. Multiple pharmacophore models were generated on the basis of the drugs and, consistent with the machine-learning analyses, one unique pharmacophore created from ligands of OAT3 possessed cationic properties similar to OCT ligands; this was confirmed by quantitative atomic property field analysis. Virtual screening with this pharmacophore, followed by transport assays, identified several cationic drugs that selectively interact with OAT3 but not OAT1. Although the present analysis may be somewhat limited by the need to rely largely on inhibition data for modeling, wet laboratory/in vitro transport studies, as well as analysis of drug/metabolite handling in Oat and Oct knockout animals, support the general validity of the approach-which can also be applied to other SLC and ATP binding cassette drug transporters. This may make it possible to predict the molecular properties of a drug or metabolite necessary for interaction with the transporter(s), thereby enabling better prediction of drug-drug interactions and drug-metabolite interactions. Furthermore, understanding the overlapping specificities of OATs and OCTs in the context of dynamic transporter tissue expression patterns should help predict net flux in a particular tissue of anionic, cationic, and zwitterionic molecules in normal and pathophysiological states.

Crawling Waves Speed Estimation Based on the Dominant Component Analysis Paradigm.

A novel method for estimating the shear wave speed from crawling waves based on the amplitude modulation-frequency modulation model is proposed. Our method consists of a two-step approach for estimating the stiffness parameter at the central region of the material of interest. First, narrowband signals are isolated in the time dimension to recover the locally strongest component and to reject distortions from the ultrasound data. Then, the shear wave speed is computed by the dominant component analysis approach and its spatial instantaneous frequency is estimated by the discrete quasi-eigenfunction approximations method. Experimental results on phantoms with different compositions and operating frequencies show coherent speed estimations and accurate inclusion locations.

An InN/InGaN quantum dot electrochemical biosensor for clinical diagnosis.

Low-dimensional InN/InGaN quantum dots (QDs) are demonstrated for realizing highly sensitive and efficient potentiometric biosensors owing to their unique electronic properties. The InN QDs are biochemically functionalized. The fabricated biosensor exhibits high sensitivity of 97 mV/decade with fast output response within two seconds for the detection of cholesterol in the logarithmic concentration range of 1 × 10⁻6 M to 1 × 10⁻³ M. The selectivity and reusability of the biosensor are excellent and it shows negligible response to common interferents such as uric acid and ascorbic acid. We also compare the biosensing properties of the InN QDs with those of an InN thin film having the same surface properties, i.e., high density of surface donor states, but different morphology and electronic properties. The sensitivity of the InN QDs-based biosensor is twice that of the InN thin film-based biosensor, the EMF is three times larger, and the response time is five times shorter. A bare InGaN layer does not produce a stable response. Hence, the superior biosensing properties of the InN QDs are governed by their unique surface properties together with the zero-dimensional electronic properties. Altogether, the InN QDs-based biosensor reveals great potential for clinical diagnosis applications.

Azide click chemistry on magnetotactic bacteria: A versatile technique to attach a cargo.

Adding biomolecules to living organisms and cells is the basis for creating living materials or biohybrids for robotic systems. Bioorthogonal chemistry allows covalently modifying biomolecules with functional groups not natively present under biological conditions and is therefore applicable to microorganisms and cells. Click chemistry is a biorthogonal chemistry approach that allows the study and manipulation of living entities. Incorporating the bioorthogonal click-chemistry handle, azide groups, into living microorganisms has been achieved by metabolic labeling, i.e., by culturing cells or organisms in a modified culture media having a specific natural molecular building block (e.g., amino acid, nucleotide, carbohydrate) modified with a tagged chemical analog. Here we explore the effect of the azide group incorporation into the magnetotactic bacteria Magnetospirillum gryphiswaldense (MSR-1) by adding a modified amino acid, 3-Azido-d-Alanine, during their cultivation. We show the existence of a concentration limit to effectively incorporate the azide group while maintaining the magnetic properties of the cells. We explore the use of this modification to explore the combination with versatile single-cell tagging methods.

The Neuroimmune Regulation and Potential Therapeutic Strategies of Optic Pathway Glioma.

Optic pathway glioma (OPG) is one of the causes of pediatric visual impairment. Unfortunately, there is as yet no cure for such a disease. Understanding the underlying mechanisms and the potential therapeutic strategies may help to delay the progression of OPG and rescue the visual morbidities. Here, we provide an overview of preclinical OPG studies and the regulatory pathways controlling OPG pathophysiology. We next discuss the role of microenvironmental cells (neurons, T cells, and tumor-associated microglia and macrophages) in OPG development. Last, we provide insight into potential therapeutic strategies for treating OPG and promoting axon regeneration.

Real-Time Optical Tracking of Protein Corona Formation on Single Nanoparticles in Serum.

The formation of a protein corona, where proteins spontaneously adhere to the surface of nanomaterials in biological environments, leads to changes in their physicochemical properties and subsequently affects their intended biomedical functionalities. Most current methods to study protein corona formation are ensemble-averaging and either require fluorescent labeling, washing steps, or are only applicable to specific types of particles. Here we introduce real-time all-optical nanoparticle analysis by scattering microscopy (RONAS) to track the formation of protein corona in full serum, at the single-particle level, without any labeling. RONAS uses optical scattering microscopy and enables real-time and in situ tracking of protein adsorption on metallic and dielectric nanoparticles with different geometries directly in blood serum. We analyzed the adsorbed protein mass, the affinity, and the kinetics of the protein adsorption at the single particle level. While there is a high degree of heterogeneity from particle to particle, the predominant factor in protein adsorption is surface chemistry rather than the underlying nanoparticle material or size. RONAS offers an in-depth understanding of the mechanisms related to protein coronas and, thus, enables the development of strategies to engineer efficient bionanomaterials.

Multicolor Super-Resolution Microscopy of Protein Corona on Single Nanoparticles.

Nanoparticles represent a promising class of material for nanomedicine and molecular biosensing. The formation of a protein corona due to nonspecific particle-protein interactions is a determining factor for the biological fate of nanoparticles in vivo and strongly impacts the performance of nanoparticles when used as biosensors. Nonspecific interactions are usually highly heterogeneous, yet little is known about the heterogeneity of the protein corona that may lead to inter- and intraparticle differences in composition and protein distribution. Here, we present a super-resolution microscopic approach to study the protein corona on single silica nanoparticles and subsequent cellular interactions using multicolor stimulated emission depletion (STED) microscopy. We demonstrate that STED resolves structural features of protein corona on single particles including the distribution on the particle surface and the degree of protein internalization in porous particles. Using multicolor measurements of multiple labeled protein species, we determine the composition of the protein corona at the single-particle level. We quantify particle-to-particle differences in the composition and find that the composition is considerably influenced by the particle geometry. In a subsequent cellular uptake measurement, we demonstrate multicolor STED of protein corona on single particles internalized by cells. Our study shows that STED microscopy opens the window toward mechanistic understanding of protein coronas and aids in the rational design of nanoparticles as nanomedicines and biosensors.

BDNF val66met polymorphism influences motor system function in the human brain.

Brain-derived neurotrophic factor (BDNF) is important to brain functions such as plasticity and repair. A single nucleotide polymorphism for this growth factor, val(66)met, is common and associated with decreased activity-dependent BDNF release. The current study evaluated the effects of this polymorphism in relation to human brain motor system function, short-term plasticity, and learning. Functional magnetic resonance imaging (fMRI) scanning during right index finger movement (n = 24) identified activation in a broad sensorimotor network. However, subjects with the polymorphism showed smaller activation volume within several brain regions as compared with subjects without the polymorphism. Repeat fMRI after 25 min of right index finger training found that the 2 genotype groups modulated brain activation differently. In several brain regions, subjects with the polymorphism showed greater activation volume reduction, whereas subjects without the polymorphism showed greater activation volume expansion. On a driving-based motor learning task (independent cohort, n = 29), subjects with the polymorphism showed greater error during short-term learning and poorer retention over 4 days, relative to subjects without the polymorphism. The presence of this BDNF polymorphism is associated with differences in brain motor system function, altered short-term plasticity, and greater error in short-term motor learning. The broader implications of these findings are considered.

Using conditional maximization to determine hyperparameters in model-based fMRI.

In model-based analysis of fMRI data, a neural or cognitive mathematical model of behavior is used to predict changes in fMRI activity. The model predictions are often applied as a parametric modulation of the main stimulus effect within the context of the general linear model (GLM). Using a mathematical model has become an important method for connecting fMRI signals to behavior because the model represents how stimulus processing leads to behavior, and the parametric modulation represents a specific test about the profile of stimulus-related fMRI activity (for review and discussion, see O'Doherty et al., 2007). However, in some cases the parameters of the mathematical model may be under-determined because there is a range of values that equally well account for behavior, or perhaps an exploratory analysis is desired. Thus, in order to fully gauge the applicability of some mathematical model it would be useful to understand how fMRI analysis depends on those parameters. Here, a conditional maximization procedure is developed to search for parameter values in the mathematical model as hyperparameters in the GLM. Simulations and analysis with real fMRI data show that conditional maximization is an effective and simple procedure for estimating hyperparameters. General recommendations and caveats for using hyperparameters in model-based fMRI analysis are also presented.

Neural decoding of goal locations in spatial navigation in humans with fMRI.

We demonstrate that multivoxel pattern analysis can be used to decode place-related information in fMRI. Subjects performed a working memory version of the Morris water maze task in a virtual environment with a single wall cue. The voxel data that corresponds to when subjects were located at the goal was extracted for seven regions implicated in spatial navigation, and then used to train a pattern classifier based on partial least squares. Using a leave-one-out (LOO) test procedure, goal locations at E, W, N positions (relative to the cue as S) were predicted significantly better than a naïve classifier for voxels in medial prefrontal cortex, hippocampus, and inferior parietal cortex. Prediction with voxels from other regions involved in navigation was also better than a naïve classifier, which raises the possibility that goal-location information is widely disseminated among the navigation network. It turns out that predictive capability of all regions combined significantly decreases, relative to no change, only when voxel data from the hippocampus is left out. This implies that the hippocampus contains some unique information that identifies goal locations, whereas other regions contain information that also identifies goal locations but is more redundant. Classification of goal locations is an important step toward decoding a variety of place-related information in spatial navigation with fMRI.

Design and evaluation of a dopant-delivery system for an orthogonal atmospheric-pressure photoionization source and its performance in the analysis of polycyclic aromatic hydrocarbons.

Atmospheric-pressure photoionization (APPI) mass spectrometry benefits from the addition of an ionization-enhancing dopant such as benzene. A passive dopant-delivery system has therefore been designed for use with the orthogonal APPI source within a commercial liquid chromatographic instrument with mass spectrometric detector. By providing the dopant in the gas phase, the newly designed equipment avoids mixing problems and other difficulties associated with liquid dopant addition. The system is a simple and durable design that can reliably deliver virtually any dopant with sufficient vapor pressure in the temperature range of 20 to 120 degrees C. At the optimum dopant flow rate (10% of the mobile phase flow rate) for high-performance liquid chromatography with narrow-bore (2.1 mm) columns, the system allows for uninterrupted routine analysis for up to two weeks. The performance of the device has been evaluated with benzene as dopant and with a test mixture consisting of four polycyclic aromatic hydrocarbons (PAH): naphthalene, 9H-fluorene, anthracene, and phenanthrene. All four PAH can be detected with an excellent signal-to-noise ratio in the scanning mode and a limit of detection down to 0.42 ng on column (51 pg in single-ion monitoring mode). The concentration calibration curves are linear over a range of three orders of magnitude, with correlation coefficients greater than 0.99. The utilization of benzene as dopant not only increases the sensitivity significantly - 20-fold, compared with dopant-free operation - but the low m/z values of the background ions observed also allow for the effective quantitative and qualitative analysis of PAH.

Stimulus-outcome learnability differentially activates anterior cingulate and hippocampus at feedback processing.

Memory systems are known to be influenced by feedback and error processing, but it is not well known what aspects of outcome contingencies are related to different memory systems. Here we use the Rescorla-Wagner model to estimate prediction errors in an fMRI study of stimulus-outcome association learning. The conditional probabilities of outcomes for a given stimulus are manipulated so that associations are either learnable or unlearnable (pseudorandom). The delay between stimulus and outcome is jittered so that we can separately compare activity for either stimulus processing or feedback processing. We find that hippocampus and anterior cingulate are differentially active primarily at feedback processing: Learnable associations are correlated with significantly more hippocampal activity and significantly less anterior cingulate activity than unlearnable associations. We also find that positive prediction errors modulate feedback processing in the midbrain for both types of associations. We suggest that learnable associations use more declarative memory, unlearnable associations involve more uncertainty monitoring, and, in both kinds of associations, positive prediction errors provide a reinforcement signal.