Affinity For Channels Research Articles

Amphetamine Derivatives as Potent Central Nervous System Multitarget SERT/NET/H3 Agents: Synthesis and Biological Evaluation

In this research, a variety of novel amphetamine derivatives were synthesized and assessed for their potential as multifaceted antidepressant agents. Among these compounds, compound 11b demonstrated potent inhibitory effects on both serotonin and noradrenaline transporters (SERT/NET) and high affinity for histamine H3 receptor (H3R), and displayed low affinity for off-target receptors (H1, α1) and hERG channels, which can reduce the prolongation of the QT interval. Molecular docking studies offered a rational binding model of compound 11b when it forms a complex with SERT, NET, and the histamine H3 receptor. In vivo behavioral studies, compound 11b dose-dependently reduced the immobility duration in the mouse FST and TST assays without a stimulatory effect on the locomotor activity. Furthermore, compound 11b had a favorable pharmacokinetic profile in rats. Thus, compound 11b has the potential to develop a novel class of drugs for the treatment of depression.

Scorpion Neurotoxin: An Analgesic Antitumor Peptide Down-Regulates VGSCs and Exhibits Local Anesthetic Potency during Sciatic Nerve Block

Background: Some neurotoxins inhibit nerves strongly. Saxitoxins and tetrodotoxin exhibit strong affinity for various voltage-gated sodium channels (VGSCs), including Nav 1.7, but low affinity for Nav 1.8. Emerging data suggests AGAP mediate analgesia by binding voltage-independently to sodium channel site-3. Objective: This study examined AGAP's mechanism and analgesic efficacy during sciatic nerve block. Methods: In rats, partial sciatic nerve ligation caused rapid and persistent mechanical hyperalgesia. Mechanical hyperalgesia after medication delivery was assessed with von Frey filaments. Western blot and immunohistochemical staining assessed VGSC expression following drug treatment. Results: The data showed that lidocaine and AGAP increased paw withdrawal threshold compared to control rats. Compared to the control group, lidocaine or AGAP inhibited VGSCs. Conclusion: This study suggested that AGAP inhibits VGSCs to elicit lidocaine-like analgesia.

Inactivation induced by pathogenic Cav1.3 L-type Ca2+-channel variants enhances sensitivity for dihydropyridine Ca2+ channel blockers.

Pathogenic gain-of-function mutations in Cav1.3 L-type voltage-gated Ca2+-channels (CACNA1D) cause neurodevelopmental disorders with or without endocrine symptoms. We aimed to confirm a pathogenic gain-of function phenotype of CACNA1D de novo missense mutations A749T and L271H, and investigated the molecular mechanism causing their enhanced sensitivity for the Ca2+-channel blocker isradipine, a potential therapeutic for affected patients. Wildtype and mutant channels were expressed in tsA-201 cells and their gating analysed using whole-cell and single-channel patch-clamp recordings. The voltage-dependence of isradipine action was quantified using protocols inducing variable fractions of inactivated channels. The molecular basis for altered channel gating in the mutants was investigated using in silico modelling and molecular dynamics simulations. Both mutations were confirmed pathogenic due to characteristic shifts of voltage-dependent activation and inactivation towards negative potentials (~20 mV). At negative holding potentials both mutations showed significantly higher isradipine sensitivity compared to wildtype. The affinity for wildtype and mutant channels increased with channel inactivation as predicted by the modulated receptor hypothesis (30- to 40-fold). The IC50 was indistinguishable for wildtype and mutants when >50% of channels were inactivated. Mutations A749T and L271H induce pathogenic gating changes. Like wildtype, isradipine inhibition is strongly voltage-dependent. Our data explains their apparent higher drug sensitivity at a given negative voltage by the availability of more inactivated channels due to their more negative inactivation voltage range. Low nanomolar isradipine concentrations will only inhibit Cav1.3 channels in neurons during prolonged depolarized states without selectivity for mutant channels.

Review of Emamectin Benzoate Poisoning.

Emamectin Benzoate, a potent pesticide extensively used in agriculture, has raised concerns due to its potential for severe poisoning. While its safety in mammals is attributed to limited blood-brain barrier penetration and reduced affinity for specific channels, Emamectin Benzoate Poisoning can unexpectedly manifest with severe symptoms. Predominantly resulting from intentional ingestion, clinical presentations involve central nervous system depression, respiratory distress, gastrointestinal symptoms, and sore throat. Formulation solvents enhance toxicity, leading to corrosive injuries and metabolic imbalances. Skin contact induces irritation. Diagnosis relies on clinical evaluation, lacking specific laboratory data. Treatment lacks a designated antidote; hence, decontamination and cautious symptomatic management play pivotal roles. Severe cases require vigilant monitoring, with intensive care unit admission calling for altered consciousness and respiratory distress.

Technology Affinity, Interaction, Accessibility, Attitude to Learning, and Learning Performance: Examining the Interrelationships

There is unanimity among educational researchers regarding the causal effects of the use of technologies in education. However, issues concerning how human-technology attributes such as technology affinity, interaction, channel affinity and accessibility are related to learning remain unclear. This study examined how the levels of students’ technology affinity, interaction, and accessibility are related to the students’ attitudes to learning and learning performance. The study deployed the basic descriptive survey design. Five hundred and thirty-four students drawn from six Open and Distance Learning (ODL) universities located in three of the six States in South West, Nigeria participated. Data sources included four questionnaires and a 15-item Technology-mediated Scientific Cognitive Abilities Test. Data were analysed using descriptive statistics, correlation analysis and regression analysis. The study found that technology affinity levels exhibited a statistically significant but negative relationship with attitude to learning (β = -0.21, t = -3.69, p = 0.0000), while the relationship with learning performance was statistically non-significant but positive (β = -0.21, t = -3.69, p = 0.692). Interaction levels exhibited a non-significant and positive relationship with attitude to learning (β = 0.05, t = 0.99, p = 0.322), and a statistically non-significant but negative relationship with learning performance (β = -0.10, t = -1.40, p = 0.161). Accessibility was significantly but negatively related to attitude to learning (β = -0.13, t = -2.242, p = 0.025, intercept = -0.88) while exhibiting a non-significant but positive relationship with learning performance (β = 0.05, t = 0.68, p = 0.499, intercept = 0.25). The study concluded that significant relationships existed among and between the ODL students’ technology attributes, attitude to learning and learning performance. It was recommended, among other things, that in adopting digital technologies for educational purposes, higher education institutions (HEIs) should sufficiently factor in the impact of the students’ technology attributes.

Network pharmacology of xylazine to understand its health consequences and develop mechanistic-based remediations

The recent rise in xylazine use disorders (XUD) in humans is a significant cause for concern as a comprehensive understanding of its molecular pathology is limited, and hence, the ability to reverse the potential adverse effects is lacking. To address this gap, this study evaluates the dose-dependent impact of xylazine and its interactions with various potential targets to identify an optimal reversal strategy. A trichotomized (Low, medium, and high) dose, volume of distribution, and predicted plasma concentration of xylazine were defined. A detailed analysis of xylazine's network protein targets and their tissue-specific expression was performed using classical pharmacoinformatic tools. Molecular docking was used to assess the drug-target affinities and identify potential reversal agents. The study categorized xylazine plasma concentrations ranging from 5-8 µM, 14-20 µM, and 28-40 µM as low, medium, and high concentrations, respectively. Xylazine displayed a preferential affinity for hydrolases, kinases, transporters, and ion channels. Xylazine's network analysis revealed the following proteins: ABCC9, RET, RAPGEF4, ACHE, TGFBR1, PGR, KCNH2, KCNN2, and TRPM8 as its high-affinity targets. The tissue-specific expression of these high-affinity targets suggested potential adverse effects on various organs, particularly skeletal and smooth muscles and the adrenal gland. The study further explored the potential reversal of xylazine pharmacology using alpha2ARantagonists and CNS stimulants. Prazosin emerged as the most promising candidate, exhibiting a 200 to 2000-fold superior affinity against all high-affinity targets of xylazine. This study contributes to our understanding of xylazine's molecular mechanisms, which could be relevant to its pharmacological effects in all species, and suggests that prazosin can serve as an effective therapeutic option for mitigating xylazine-induced adverse effects in XUD patients, which warrants clinical investigation.

Synthesis and Chemoinformatic Analysis of Fluorinated Piperidines as 3D Fragments for Fragment-Based Drug Discovery.

The concise synthesis of a small library of fluorinated piperidines from readily available dihydropyridinone derivatives has been described. The effect of the fluorination on different positions has then been evaluated by chemoinformatic tools. In particular, the compounds' pKa's have been calculated, revealing that the fluorine atoms notably lowered their basicity, which is correlated to the affinity for hERG channels resulting in cardiac toxicity. The "lead-likeness" and three-dimensionality have also been evaluated to assess their ability as useful fragments for drug design. A random screening on a panel of representative proteolytic enzymes was then carried out and revealed that one scaffold is recognized by the catalytic pocket of 3CLPro (main protease of SARS-CoV-2 coronavirus).

Ion Channels in Critical Membranes: Clustering, Cooperativity, and Memory Effects

Much progress has been made in elucidating the inner workings of voltage-gated ion channels, but less understood is the influence of lipid rafts on gating kinetics. Here we propose that state-dependent channel affinity for different lipid species provides a unified explanation for the experimentally observed behaviors of clustering, cooperativity, and hysteresis. We develop models of diffusing lipids and channels engaged in Ising-like interactions to investigate the collective behaviors driven by raft formation in critical membranes close to the demixing transition. The model channels demonstrate lipid-mediated long-range interactions, activation curve steepening, and long-term memory in ionic currents. These behaviors likely play a role in channel-mediated cellular signaling and suggest a universal mechanism for self-organization of biomolecular assemblies. Published by the American Physical Society 2024

Progressive Spatial Information-Guided Deep Aggregation Convolutional Network for Hyperspectral Spectral Super-Resolution.

Fusion-based spectral super-resolution aims to yield a high-resolution hyperspectral image (HR-HSI) by integrating the available high-resolution multispectral image (HR-MSI) with the corresponding low-resolution hyperspectral image (LR-HSI). With the prosperity of deep convolutional neural networks, plentiful fusion methods have made breakthroughs in reconstruction performance promotions. Nevertheless, due to inadequate and improper utilization of cross-modality information, the most current state-of-the-art (SOTA) fusion-based methods cannot produce very satisfactory recovery quality and only yield desired results with a small upsampling scale, thus affecting the practical applications. In this article, we propose a novel progressive spatial information-guided deep aggregation convolutional neural network (SIGnet) for enhancing the performance of hyperspectral image (HSI) spectral super-resolution (SSR), which is decorated through several dense residual channel affinity learning (DRCA) blocks cooperating with a spatial-guided propagation (SGP) module as the backbone. Specifically, the DRCA block consists of an encoding part and a decoding part connected by a channel affinity propagation (CAP) module and several cross-layer skip connections. In detail, the CAP module is customized by exploiting the channel affinity matrix to model correlations among channels of the feature maps for aggregating the channel-wise interdependencies of the middle layers, thereby further boosting the reconstruction accuracy. Additionally, to efficiently utilize the two cross-modality information, we developed an innovative SGP module equipped with a simulation of the degradation part and a deformable adaptive fusion part, which is capable of refining the coarse HSI feature maps at pixel-level progressively. Extensive experimental results demonstrate the superiority of our proposed SIGnet over several SOTA fusion-based algorithms.

Multi-modal fusion network with intra- and inter-modality attention for prognosis prediction in breast cancer

Accurate breast cancer prognosis prediction can help clinicians to develop appropriate treatment plans and improve life quality for patients. Recent prognostic prediction studies suggest that fusing multi-modal data, e.g., genomic data and pathological images, plays a crucial role in improving predictive performance. Despite promising results of existing approaches, there remain challenges in effective multi-modal fusion. First, albeit a powerful fusion technique, Kronecker product produces high-dimensional quadratic expansion of features that may result in high computational cost and overfitting risk, thereby limiting its performance and applicability in cancer prognosis prediction. Second, most existing methods put more attention on learning cross-modality relations between different modalities, ignoring modality-specific relations that are complementary to cross-modality relations and beneficial for cancer prognosis prediction. To address these challenges, in this study we propose a novel attention-based multi-modal network to accurately predict breast cancer prognosis, which efficiently models both modality-specific and cross-modality relations without bringing in high-dimensional features. Specifically, two intra-modality self-attentional modules and an inter-modality cross-attentional module, accompanied by latent space transformation of channel affinity matrix, are developed to successfully capture modality-specific and cross-modality relations for efficient integration of genomic data and pathological images, respectively. Moreover, we design an adaptive fusion block to take full advantage of both modality-specific and cross-modality relations. Comprehensive experiment demonstrates that our method can effectively boost prognosis prediction performance of breast cancer and compare favorably with the state-of-the-art methods.

Transcriptomic Profiling of Tetrodotoxin-Induced Neurotoxicity in Human Cerebral Organoids.

Tetrodotoxin (TTX) is an exceedingly toxic non-protein biotoxin that demonstrates remarkable selectivity and affinity for sodium channels on the excitation membrane of nerves. This property allows TTX to effectively obstruct nerve conduction, resulting in nerve paralysis and fatality. Although the mechanistic aspects of its toxicity are well understood, there is a dearth of literature addressing alterations in the neural microenvironment subsequent to TTX poisoning. In this research endeavor, we harnessed human pluripotent induced stem cells to generate cerebral organoids-an innovative model closely mirroring the structural and functional intricacies of the human brain. This model was employed to scrutinize the comprehensive transcriptomic shifts induced by TTX exposure, thereby delving into the neurotoxic properties of TTX and its potential underlying mechanisms. Our findings revealed 455 differentially expressed mRNAs (DEmRNAs), 212 differentially expressed lncRNAs (DElncRNAs), and 18 differentially expressed miRNAs (DEmiRNAs) in the TTX-exposed group when juxtaposed with the control cohort. Through meticulous Gene Ontology (GO) annotation, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, and protein-protein interaction (PPI) analysis, we ascertained that these differential genes predominantly participate in the regulation of voltage-gated channels and synaptic homeostasis. A comprehensive ceRNA network analysis unveiled that DEmRNAs exert control over the expression of ion channels and neurocytokines, suggesting their potential role in mediating apoptosis.

Polyimide/Ionic Liquids Hybrid Membranes with NH3-Philic Channels for Ammonia-Based CO2 Separation Processes.

An efficient separation technology involving ammonia (NH3) and carbon dioxide (CO2) is of great importance for achieving low-carbon economy, environmental protection, and resource utilization. However, directly separating NH3 and CO2 for ammonia-based CO2 capture processes is still a great challenge. Herein, we propose a new strategy for selective separation of NH3 and CO2 by functional hybrid membranes that integrate polyimide (PI) and ionic liquids (ILs). The incorporated protic IL [Bim][NTf2] is confined in the interchain segment of PI, which decreases the fractional free volume and narrows the gas transport channel, benefiting the high separation selectivity of hybrid membranes. At the same time, the confined IL also provides high NH3 affinity for transport channels, promoting NH3 selective and fast transport owing to strong hydrogen bonding interaction between [Bim][NTf2] and NH3 molecules. Thus, the optimal hybrid membrane exhibits an ultrahigh NH3/CO2 ideal selectivity of up to 159 at 30 °C without sacrificing permeability, which is 60 times higher than that of the neat PI membrane and superior to the state-of-the art reported values. Moreover, the introduction of [Bim][NTf2] also reduces the permeation active energy of NH3 and reverses the hybrid membrane toward "NH3 affinity", as understood by studying the effect of temperature. Also, NH3 molecules are much easier to transport at high temperature, showing great application potential in direct NH3/CO2 separation. Overall, this work provides a promising ultraselective membrane material for ammonia-based CO2 capture processes.

The capsaicin binding affinity of wildtype and mutant TRPV1 ion channels

Vanilloids such as capsaicin and resiniferatoxin are highly selective and potent activators for transient receptor potential vanilloid subfamily, member 1, a nociceptor for heat and pain perception. However, the intrinsic vanilloid binding affinity, key for understanding transient receptor potential vanilloid subfamily, member 1 function, remains unknown despite intensive investigations by electrophysiological, structural, and computational methods. In this study, we determined capsaicin binding affinity under physiological conditions by isolating individual binding steps to each subunit with concatemers. We estimated the capsaicin association constant of a wildtype subunit to be in the order of 106M-1 and that of the Y511A mutant subunit to be a hundred times lower, in the order of 104M-1. The Y511A mutation, located at the entrance of the vanilloid binding pocket, reduces binding affinity without a noticeable effect on activation gating. We further affirmed that there is little cooperativity between vanilloid binding steps. Models based on independent binding and equally cooperative subunit gating can accurately describe capsaicin activation.

The Effect of the Pyrethroid Pesticide Fenpropathrin on the Cardiac Performance of Zebrafish and the Potential Mechanism of Toxicity.

Fenpropathrin, a pyrethroid insecticide, has been widely used for many years in agricultural fields. It works by disturbing the voltage-gated sodium channel, leading to paralysis and the death of the target animal. While past studies have focused on neurodegeneration following fenpropathrin poisoning in humans, relatively few pieces of research have examined its effect on other peripheral organs. This study successfully investigated the potential toxicity of fenpropathrin on the cardiovascular system using zebrafish as an animal model. Zebrafish larvae exposed to varying doses of fenpropathrin underwent an evaluation of cardiac physiology by measuring the heart rate, stroke volume, cardiac output, and shortening fraction. The blood flow velocity and the dorsal aorta diameter were also measured to assess the impact of fenpropathrin exposure on the vascular system. Furthermore, molecular docking was performed to evaluate the pesticide binding affinity to various proteins associated with the cardiovascular system, revealing the potential mechanism of the fenpropathrin cardiotoxic effect. The findings demonstrated a significant dose-dependent increase in the heart rate stroke volume, cardiac output, shortening fraction, and ejection fraction of zebrafish larvae after 24 h of acute treatment with fenpropathrin. Additionally, zebrafish treated at a concentration of 1 ppm exhibited significantly larger blood vessels in diameter and an increased blood flow velocity compared to the control group. According to molecular docking, fenpropathrin showed a high affinity for various voltage-gated sodium channels like scn1lab, cacna1sb, and clcn3. Finally, from the results, we found that fenpropathrin caused cardiomegaly, which may have been induced by the voltage-gated sodium channel disruption. This study highlights the significant disruption of fenpropathrin in the cardiovascular system and emphasizes the need for further research on the health implications of this pesticide.

Adaptation memory in photoreceptors: different mechanisms in rods and cones.

Vertebrate rods and cones operate over a wide range of ambient illumination, which is provided by light adaptation mechanisms regulating the sensitivity and speed of the phototransduction cascade. Three calcium-sensitive feedback loops are well established in both rods and cones: acceleration of the quenching of a light-activated visual pigment and cGMP synthesis by guanylate cyclase, and increased affinity of ion channels for cGMP. Accumulating evidence suggests that the molecular mechanisms of light adaptation are more complex. While investigating these putative mechanisms, we discovered a novel phenomenon, observing that the recovery of light sensitivity in rods after turning off non-saturating adaptive light can take tens of seconds. Moreover, after a formal return of the membrane current to the dark level, cell sensitivity to the stimuli remains decreased for a further 1-2 min. We termed this phenomenon of prolonged photoreceptor desensitization 'adaptation memory' (of previous illumination) and the current study is focused on its detailed investigation in rods and an attempt to find the same phenomenon in cones. In rods, we have explored the dependencies of this phenomenon on adapting conditions, specifically, the intensity and duration of adapting illumination. Additionally, we report that fish and frog red-sensitive cones possess similar features of adaptation memory, such as a drop in sensitivity just after the steps of bright light and slow sensitivity recovery. However, we have found that the rate of this process and its nature are not the same as in rods. Our results indicate that the nature of the temporary drop in the sensitivity in rods and cones after adapting steps of light is different. In the rods, adaptation memory could be attributed to the existence of long-lasting modifications of the components of the phototransduction cascade after adapting illumination. In cones, the observed form of the adaptation memory seems to be due to the sensitivity drop caused by a decrease in the availability of the visual pigment, that is, by bleaching.

Wykorzystanie sekwencyjnego wirtualnego skriningu opartego na uczeniu maszynowym w poszukiwaniu nowych ligandów receptora 5-HT6

5-HT6 receptor takes part in learning and memory processes. For this reason, the use of ligands of this receptor in the treatment of neurodegenerative diseases such as Alzheimer's disease, depression or autism is being investigated. The development of machine learning (ML) and access to large compound databases allow for the increasing use of these methods in search of new drugs. The use of ML in pre-clinical tests allows for a reduction in time and costs of drug discovery. In this study, we used a sequential virtual screening approach in search of new structures with potential high affinity for the 5-HT6 receptor. Data from the ChEMBL database containing ligand binding affinities, measured as an inhibition constant (Ki), was used as the training dataset. Each step of the screening was based on machine learning models, the task of which was to classify compounds as potentially active and inactive. The first step included a ligand-based drug discovery (LBDD) approach, in which, using Klekota-Roth fingerprints and descriptors describing the chemical structure of the ligands, a classification model was developed to select a preliminary group of candidates from the Otava chemical compound database. In the second step, a structure-based drug discovery (SBDD) approach was used. For this purpose, compounds were docked to the homology model of the 5-HT6 receptor, developed using the AlphaFold algorithm and optimized by Induced-Fit Docking tool and molecular dynamics. Docking poses were scored by a trained Extra Trees classifier. Interactions of a reference ligand with 14 binding site residues were used as features for the trained model. The use of machine learning as a scoring function allowed to improve the virtual screening parameters compared to the Glide GScore scoring function. Based on the obtained model, it was also confirmed that the location of a ligand near the Ser5.43 and Phe5.38 residues is important for binding the compound to the receptor. The procedure has allowed to select 20 candidates with new chemical structures compared to known ligands. In addition, the obtained compounds had a relatively low basic pKa compared to known ligands and thus may be suspected to have a low affinity for hERG channels and good brain penetration.

Identification of a new family of inhibitors of the human Hv1 proton channel.

The human voltage-gated proton channel (hHv1) plays an important role in immune and cancer cells being involved in functions such as proliferation, migration, and oxidative burst. The structure of this protein differs from that of other voltage-gated ion channels in that it has no conventional ion-conducting pore, conduction occurs through the voltage-sensing domain itself. This dissemblance may be the reason for the lack of selective hHv1 inhibitors. Our aim was to find potent and selective inhibitors for hHv1, which could be useful research tools and serve as lead molecules for the development of drug molecules targeting Hv1 for therapeutic goals. We used manual patch-clamp to test the Hv1-affinity and selectivity of potential inhibitors on CHO (Chinese hamster ovary) and HEK (human embryonic kidney) cells expressing hHv1 and other channels. Proliferation assays were performed to test possible off-target effects of the molecules. Over 30 small molecules were tested, of which seven turned out to be effective on hHv1 (i.e. blocked more than 50% of the current in 50 µM). Six of them had the same scaffold in their structure. The scaffold itself, named NZ-13, was also one of the hit molecules, and had an IC50 value of 26 µM for hHv1. Most of the hit molecules turned out to have low selectivity: they had comparable or even higher affinity for the other tested Kv and NaV ion channels than for Hv1. However, NZ-13 had lower affinity for the other channels than for Hv1 and also proved to have the smallest effect on T-cell proliferation. Based on our results, we have successfully identified a scaffold, which can be a starting point for creating new, potent and selective hHv1 inhibitors.

Common and Rare Variants in TMEM175 Gene Concur to the Pathogenesis of Parkinson’s Disease in Italian Patients

Parkinson’s disease (PD) represents the most common neurodegenerative movement disorder. We recently identified 16 novel genes associated with PD. In this study, we focused the attention on the common and rare variants identified in the lysosomal K+ channel TMEM175. The study includes a detailed clinical and genetic analysis of 400 cases and 300 controls. Molecular studies were performed on patient-derived fibroblasts. The functional properties of the mutant channels were assessed by patch-clamp technique and co-immunoprecipitation. We have found that TMEM175 was highly expressed in dopaminergic neurons of the substantia nigra pars compacta and in microglia of the cerebral cortex of the human brain. Four common variants were associated with PD, including two novel variants rs2290402 (c.-10C > T) and rs80114247 (c.T1022C, p.M341T), located in the Kozak consensus sequence and TM3II domain, respectively. We also disclosed 13 novel highly penetrant detrimental mutations in the TMEM175 gene associated with PD. At least nine of these mutations (p.R35C, p. R183X, p.A270T, p.P308L, p.S348L, p. L405V, p.R414W, p.P427fs, p.R481W) may be sufficient to cause the disease, and the presence of mutations of other genes correlated with an earlier disease onset. In vitro functional analysis of the ion channel encoded by the mutated TMEM175 gene revealed a loss of the K+ conductance and a reduced channel affinity for Akt. Moreover, we observed an impaired autophagic/lysosomal proteolytic flux and an increase expression of unfolded protein response markers in patient-derived fibroblasts. These data suggest that mutations in TMEM175 gene may contribute to the pathophysiology of PD.

A Synergistical Attention Model for Semantic Segmentation of Remote Sensing Images

In remotely sensed images, high intra-class variance and inter-class similarity are ubiquitous due to complex scenes and objects with multivariate features, making semantic segmentation a challenging task. Deep convolutional neural networks can solve this problem by modelling the context of features and improving their discriminability. However, current learning paradigms model the feature affinity in spatial dimension and channel dimension separately and then fuse them in a sequential or parallel manner, leading to suboptimal performance. In this study, we first analyze this problem practically and summarize it as attention bias that reduces the capability of network in distinguishing weak and discretely distributed objects from wide-range objects with internal connectivity, when modeled only in spatial or channel domain. To jointly model both spatial and channel affinity, we design a synergistic attention module (SAM), which allows for channel-wise affinity extraction while preserving spatial details. In addition, we propose a synergistic attention perception neural network (SAPNet) for the semantic segmentation of remote sensing images. The hierarchical-embedded synergistic attention perception module aggregates SAM-refined features and decoded features. As a result, SAPNet enriches inference clues with desired spatial and channel details. Experiments on three benchmark datasets show that SAPNet is competitive in accuracy and adaptability compared with state-of-the-art methods. The experiments also validate the hypothesis of attention bias and the efficiency of SAM.

O1-conotoxin Tx6.7 cloned from the genomic DNA of Conus textile that inhibits calcium currents.

Conotoxins exhibit great potential as neuropharmacology tools and therapeutic candidates due to their high affinity and specificity for ion channels, neurotransmitter receptors or transporters. The traditional methods to discover new conotoxins are peptide purification from the crude venom or gene amplification from the venom duct. In this study, a novel O1 superfamily conotoxin Tx6.7 was directly cloned from the genomic DNA of Conus textile using primers corresponding to the conserved intronic sequence and 3' UTR elements. The mature peptide of Tx6.7 (DCHERWDWCPASLLGVIYCCEGLICFIAFCI) was synthesized by solid-phase chemical synthesis and confirmed by mass spectrometry. Patch clamp experiments on rat DRG neurons showed that Tx6.7 inhibited peak calcium currents by 59.29 ± 2.34% and peak potassium currents by 22.33 ± 7.81%. In addition, patch clamp on the ion channel subtypes showed that 10 μM Tx6.7 inhibited 56.61 ± 3.20% of the hCaV1.2 currents, 24.67 ± 0.91% of the hCaV2.2 currents and 7.30 ± 3.38% of the hNaV1.8 currents. Tx6.7 had no significant toxicity to ND7/23 cells and increased the pain threshold from 0.5 to 4 hours in the mouse hot plate assay. Our results suggested that direct cloning of conotoxin sequences from the genomic DNA of cone snails would be an alternative approach to obtaining novel conotoxins. Tx6.7 could be used as a probe tool for ion channel research or a therapeutic candidate for novel drug development.