Mechanistic insight into allosteric activation of human pyruvate carboxylase by acetyl-CoA.

Pyruvate carboxylase (PC) catalyzes the two-step carboxylation of pyruvate to produce oxaloacetate, playing a key role in the maintenance of metabolic homeostasis in cells. Given its involvement in multiple diseases, PC has been regarded as a potential therapeutic target for obesity, diabetes, and cancer. Albeit acetyl-CoA has been recognized as the allosteric regulator of PC for over 60 years, the underlying mechanism of how acetyl-CoA induces PC activation remains enigmatic. Herein, by using time-resolved cryo-electron microscopy, we have captured the snapshots of PC transitional states during its catalytic cycle. These structures and the biochemical studies reveal that acetyl-CoA stabilizes PC in a catalytically competent conformation, which triggers a cascade of events, including ATP hydrolysis and the long-distance communication between the two reactive centers. These findings provide an integrated picture for PC catalysis and unveil the unique allosteric mechanism of acetyl-CoA in an essential biochemical reaction in all kingdoms of life.

Structural basis of ligand recognition and self-activation of orphan GPR52.

GPR52 is a class-A orphan G-protein-coupled receptor that is highly expressed in the brain and represents a promising therapeutic target for the treatment of Huntington's disease and several psychiatric disorders1,2. Pathological malfunction of GPR52 signalling occurs primarily through the heterotrimeric Gs protein2, but it is unclear how GPR52 and Gs couple for signal transduction and whether a native ligand or other activating input is required. Here we present the high-resolution structures of human GPR52 in three states: a ligand-free state, a Gs-coupled self-activation state and a potential allosteric ligand-bound state. Together, our structures reveal that extracellular loop 2 occupies the orthosteric binding pocket and operates as a built-in agonist, conferring an intrinsically high level of basal activity to GPR523. A fully active state is achieved when Gs is coupled to GPR52 in the absence of an external agonist. The receptor also features a side pocket for ligand binding. These insights into the structure and function of GPR52 could improve our understanding of other self-activated GPCRs, enable the identification of endogenous and tool ligands, and guide drug discovery efforts that target GPR52.

Stoichiometry and architecture of the platelet membrane complex glycoprotein Ib-IX-V.

Glycoprotein (GP) Ib-IX-V is the second most abundant platelet receptor for thrombin and other ligands crucial for hemostasis and thrombosis. Its activity is involved in platelet adhesion to vascular injury sites and thrombin-induced platelet aggregation. GPIb-IX-V is a heteromeric complex composed of four subunits, GPIbα, GPIbß, GPV and GPIX, in a stoichiometric ratio that has been wildly debated. Despite its important physiological roles, the overall structure and molecular arrangement of GPIb-IX-V are not yet fully understood. Here, we purify stable and functional human GPIb-IX-V complex from reconstituted EXPi293F cells in high homogeneity, and perform biochemical and structural characterization of this complex. Single-particle cryo-electron microscopy structure of GPIb-IX-V is determined at ∼11 Å resolution, which unveils the architecture of GPIb-IX-V and its subunit organization. Size-exclusion chromatography-multi-angle static light scattering analysis reveals that GPIb-IX-V contains GPIb-IX and GPV at a 1:1 stoichiometric ratio and surface plasmon resonance assays show that association of GPV leads to slow kinetics of thrombin binding to GPIb-IX-V. Taken together, our results provide the first three-dimensional architecture of the intact GPIb-IX-V complex, which extends our understanding of the structure and functional mechanism of this complex in hemostasis and thrombosis.

Inter-observer agreement among specialists in the diagnosis of oral potentially malignant disorders and oral cancer using store-and-forward technology.

OBJECTIVES: Oral cancer is a leading cause of morbidity and mortality. Screening and mobile Health (mHealth)-based approach facilitates early detection remotely in a resource-limited settings. Recent advances in eHealth technology have enabled remote monitoring and triage to detect oral cancer in its early stages. Although studies have been conducted to evaluate the diagnostic efficacy of remote specialists, to our knowledge, no studies have been conducted to evaluate the consistency of remote specialists. The aim of this study was to evaluate interobserver agreement between specialists through telemedicine systems in real-world settings using store-and-forward technology. MATERIALS AND METHODS: The two remote specialists independently diagnosed clinical images (n=822) from image archives. The onsite specialist diagnosed the same participants using conventional visual examination, which was tabulated. The diagnostic accuracy of two remote specialists was compared with that of the onsite specialist. Images that were confirmed histopathologically were compared with the onsite diagnoses and the two remote specialists. RESULTS: There was moderate agreement (k= 0.682) between two remote specialists and (k= 0.629) between the onsite specialist and two remote specialists in the diagnosis of oral lesions. The sensitivity and specificity of remote specialist 1 were 92.7% and 83.3%, respectively, and those of remote specialist 2 were 95.8% and 60%, respectively, each compared with histopathology. CONCLUSION: The diagnostic accuracy of the two remote specialists was optimal, suggesting that "store and forward" technology and telehealth can be an effective tool for triage and monitoring of patients. CLINICAL RELEVANCE: Telemedicine is a good tool for triage and enables faster patient care in real-world settings.

MicroLED chromatic confocal microscope.

In this Letter, a microLED-based chromatic confocal microscope with a virtual confocal slit is proposed and demonstrated for three-dimensional (3D) profiling without any mechanical scanning or external light source. In the proposed method, a micro-scale light-emitting diode (microLED) panel works as a point source array to achieve lateral scanning. Axial scanning is realized through the chromatic aberration of an aspherical objective. A virtual pinhole technique is utilized to improve the contrast and precision of depth reconstruction. The system performance has been demonstrated with a diamond-turned copper sample and onion epidermis. The experimental results show that the microLED panel could be a potential solution for portable 3D confocal microscopy. Several considerations and prospects are proposed for future microLED requirements in confocal imaging.

DMD-based three-dimensional chromatic confocal microscopy.

In this paper, a digital mirror device (DMD)-based chromatic confocal microscopy is proposed and demonstrated for three-dimensional (3D) surface profiling without any mechanical scanning. In this method, the DMD works as the multipoint source and multi-pinhole at the same time to achieve the lateral scanning. Moreover, axial scanning is realized through the chromatic aberration of the confocal optics. Since the micromirror array of the DMD is not perpendicular to the confocal imaging axis, a corresponding calibration is needed to eliminate the tilt effects and perform accurate 3D imaging. The measurement range with the current optical system is 45 µm over 505-650 nm working spectrum and can be increased by using a custom objective with large chromatic aberration. The system performance has been demonstrated with a multistep sample.

Rapid measurement and compensation method of eccentricity in automatic profile measurement of the ICF capsule.

In this paper, we propose a new measurement and compensation method for the eccentricity of the inertial confinement fusion (ICF) capsule, which combines computer vision and the laser differential confocal method to align the capsule in rotation measurement. This technique measures the eccentricity of the capsule by obtaining the sub-pixel profile with a moment-based algorithm, then performs the preliminary alignment by the two-dimensional adjustment. Next, we use the laser differential confocal sensor to measure the height data of the equatorial surface of the capsule by turning it around, then obtain and compensate the remaining eccentricity ultimately. This method is a non-contact, automatic, rapid, high-precision measurement and compensation technique of eccentricity for the capsule. Theoretical analyses and preliminary experiments indicate that the maximum measurement range of eccentricity of this proposed method is 1.8 mm for the capsule with a diameter of 1 mm, and it could eliminate the eccentricity to less than 0.5 µm in 30 s.

Immobilization of trace elements in municipal solid waste incinerator (MSWI) fly ash by producing calcium sulphoaluminate cement after carbonation and washing.

The possibility of producing calcium sulphoaluminate cement (CSA) by adding municipal solid waste incinerator (MSWI) fly ash to raw meal was investigated. After subjecting MSWI fly ash to accelerated carbonation and washing with water (ACW), various amounts (i.e., 5, 10 and 15 wt%) of the treated ash were added to raw meal composed of a mixture of bauxite, limestone and gypsum. The mixtures were sintered in a laboratory-scale muffle furnace at temperatures of 1250°, 1300°, 1325° and 1350 °C for various durations. The influence of different quantities of MSWI fly ash on the mineralogy, major phase composition and strength development of the resulting clinker was studied, as was the effect of ash treatments on leaching and volatilization of trace elements. The ACW treatment reduced the volatilization ratio of trace elements during the clinkerization process. Volatilization ratios for lead, cadmium and zinc were 21.5%, 33.6% and 16.3%, respectively, from the ACW fly ash treatment, compared with ratios of 97.5%, 93.1% and 85.2% from untreated fly ash. The volatilization ratios of trace elements were ordered as follows: untreated fly ash > carbonated fly ash > carbonated and water-washed fly ash. The ACW process also reduced the chloride content in the MSWI fly ash by 90 wt% and prevented high concentrations of trace elements in the effluents.

Classification of Mobile-Based Oral Cancer Images Using the Vision Transformer and the Swin Transformer.

Oral cancer, a pervasive and rapidly growing malignant disease, poses a significant global health concern. Early and accurate diagnosis is pivotal for improving patient outcomes. Automatic diagnosis methods based on artificial intelligence have shown promising results in the oral cancer field, but the accuracy still needs to be improved for realistic diagnostic scenarios. Vision Transformers (ViT) have outperformed learning CNN models recently in many computer vision benchmark tasks. This study explores the effectiveness of the Vision Transformer and the Swin Transformer, two cutting-edge variants of the transformer architecture, for the mobile-based oral cancer image classification application. The pre-trained Swin transformer model achieved 88.7% accuracy in the binary classification task, outperforming the ViT model by 2.3%, while the conventional convolutional network model VGG19 and ResNet50 achieved 85.2% and 84.5% accuracy. Our experiments demonstrate that these transformer-based architectures outperform traditional convolutional neural networks in terms of oral cancer image classification, and underscore the potential of the ViT and the Swin Transformer in advancing the state of the art in oral cancer image analysis.

Structural insights into human EMC and its interaction with VDAC.

The endoplasmic reticulum (ER) membrane protein complex (EMC) is a conserved, multi-subunit complex acting as an insertase at the ER membrane. Growing evidence shows that the EMC is also involved in stabilizing and trafficking membrane proteins. However, the structural basis and regulation of its multifunctionality remain elusive. Here, we report cryo-electron microscopy structures of human EMC in apo- and voltage-dependent anion channel (VDAC)-bound states at resolutions of 3.47 Å and 3.32 Å, respectively. We discovered a specific interaction between VDAC proteins and the EMC at mitochondria-ER contact sites, which is conserved from yeast to humans. Moreover, we identified a gating plug located inside the EMC hydrophilic vestibule, the substrate-binding pocket for client insertion. Conformation changes of this gating plug during the apo-to-VDAC-bound transition reveal that the EMC unlikely acts as an insertase in the VDAC1-bound state. Based on the data analysis, the gating plug may regulate EMC functions by modifying the hydrophilic vestibule in different states. Our discovery offers valuable insights into the structural basis of EMC's multifunctionality.

Cryo-EM structure of human sphingomyelin synthase and its mechanistic implications for sphingomyelin synthesis.

Sphingomyelin (SM) has key roles in modulating mammalian membrane properties and serves as an important pool for bioactive molecules. SM biosynthesis is mediated by the sphingomyelin synthase (SMS) family, comprising SMS1, SMS2 and SMS-related (SMSr) members. Although SMS1 and SMS2 exhibit SMS activity, SMSr possesses ceramide phosphoethanolamine synthase activity. Here we determined the cryo-electron microscopic structures of human SMSr in complexes with ceramide, diacylglycerol/phosphoethanolamine and ceramide/phosphoethanolamine (CPE). The structures revealed a hexameric arrangement with a reaction chamber located between the transmembrane helices. Within this structure, a catalytic pentad E-H/D-H-D was identified, situated at the interface between the lipophilic and hydrophilic segments of the reaction chamber. Additionally, the study unveiled the two-step synthesis process catalyzed by SMSr, involving PE-PLC (phosphatidylethanolamine-phospholipase C) hydrolysis and the subsequent transfer of the phosphoethanolamine moiety to ceramide. This research provides insights into the catalytic mechanism of SMSr and expands our understanding of sphingolipid metabolism.

Structural insight into the intraflagellar transport complex IFT-A and its assembly in the anterograde IFT train.

Intraflagellar transport (IFT) trains, the polymers composed of two multi-subunit complexes, IFT-A and IFT-B, carry out bidirectional intracellular transport in cilia, vital for cilia biogenesis and signaling. IFT-A plays crucial roles in the ciliary import of membrane proteins and the retrograde cargo trafficking. However, the molecular architecture of IFT-A and the assembly mechanism of the IFT-A into the IFT trains in vivo remains elusive. Here, we report the cryo-electron microscopic structures of the IFT-A complex from protozoa Tetrahymena thermophila. We find that IFT-A complexes present two distinct, elongated and folded states. Remarkably, comparison with the in situ cryo-electron tomography structure of the anterograde IFT train unveils a series of adjustments of the flexible arms in apo IFT-A when incorporated into the anterograde train. Our results provide an atomic-resolution model for the IFT-A complex and valuable insights into the assembly mechanism of anterograde IFT trains.

The structural basis of the pH-homeostasis mediated by the Cl-/HCO3- exchanger, AE2.

The cell maintains its intracellular pH in a narrow physiological range and disrupting the pH-homeostasis could cause dysfunctional metabolic states. Anion exchanger 2 (AE2) works at high cellular pH to catalyze the exchange between the intracellular HCO3- and extracellular Cl-, thereby maintaining the pH-homeostasis. Here, we determine the cryo-EM structures of human AE2 in five major operating states and one transitional hybrid state. Among those states, the AE2 shows the inward-facing, outward-facing, and intermediate conformations, as well as the substrate-binding pockets at two sides of the cell membrane. Furthermore, critical structural features were identified showing an interlock mechanism for interactions among the cytoplasmic N-terminal domain and the transmembrane domain and the self-inhibitory effect of the C-terminal loop. The structural and cell-based functional assay collectively demonstrate the dynamic process of the anion exchange across membranes and provide the structural basis for the pH-sensitive pH-rebalancing activity of AE2.

The cryo-EM structure of the human ERAD retrotranslocation complex.

Endoplasmic reticulum-associated degradation (ERAD) maintains protein homeostasis by retrieving misfolded proteins from the endoplasmic reticulum (ER) lumen into the cytosol for degradation. The retrotranslocation of misfolded proteins across the ER membrane is an energy-consuming process, with the detailed transportation mechanism still needing clarification. We determined the cryo-EM structures of the hetero-decameric complex formed by the Derlin-1 tetramer and the p97 hexamer. It showed an intriguing asymmetric complex and a putative coordinated squeezing movement in Derlin-1 and p97 parts. With the conformational changes of p97 induced by its ATP hydrolysis activities, the Derlin-1 channel could be torn into a "U" shape with a large opening to the lipidic environment, thereby forming an entry for the substrates in the ER membrane. The EM analysis showed that p97 formed a functional protein complex with Derlin-1, revealing the coupling mechanism between the ERAD retrotranslocation and the ATP hydrolysis activities.

An updated review of feline coronavirus: mind the two biotypes.

Feline coronavirus (FCoV) includes two biotypes: feline infectious peritonitis virus (FIPV) and feline enteric coronavirus (FECV). Although both biotypes can infect cats, their pathogenicities differ. The FIPV biotype is more virulent than the FECV biotype and can cause peritonitis or even death in cats, while most FECV biotypes do not cause lesions. Even pathogenic strains of the FECV biotype can cause only mild enteritis because of their very low virulence. This article reviews recent progress in FCoV research with regard to FCoV etiological characteristics; epidemiology; clinical symptoms and pathological changes; pathogenesis; and current diagnosis, prevention and treatment methods. It is hoped that this review will provide a reference for further research on FCoV and other coronaviruses.

Clinical assessment of a low-cost, hand-held, smartphone-attached intraoral imaging probe for 5-aminolevulinic acid photodynamic therapy monitoring and guidance.

Significance: India has one of the highest rates of oral squamous cell carcinoma (OSCC) in the world, with an incidence of 15 per 100,000 and more than 70,000 deaths per year. The problem is exacerbated by a lack of medical infrastructure and routine screening, especially in rural areas. New technologies for oral cancer detection and timely treatment at the point of care are urgently needed. Aim: Our study aimed to use a hand-held smartphone-coupled intraoral imaging device, previously investigated for autofluorescence (auto-FL) diagnostics adapted here for treatment guidance and monitoring photodynamic therapy (PDT) using 5-aminolevulinic acid (ALA)-induced protoporphyrin IX (PpIX) fluorescence (FL). Approach: A total of 12 patients with 14 buccal mucosal lesions having moderately/well-differentiated micro-invasive OSCC lesions (<2 cm diameter and <5 mm depth) were systemically (in oral solution) administered three doses of 20 mg/kg ALA (total 60 mg/kg). Lesion site PpIX and auto-FL were imaged using the multichannel FL and polarized white-light oral cancer imaging probe before/after ALA administration and after light delivery (fractionated, total 100 J/cm2 of 635 nm red LED light). Results: The handheld device was conducive for access to lesion site images in the oral cavity. Segmentation of ratiometric images in which PpIX FL is mapped relative to auto-FL enabled improved demarcation of lesion boundaries relative to PpIX alone. A relative FL (R-value) threshold of 1.4 was found to segment lesion site PpIX production among the patients with mild to severe dysplasia malignancy. The segmented lesion size is well correlated with ultrasound findings. Lesions for which R-value was >1.65 at the time of treatment were associated with successful outcomes. Conclusion: These results indicate the utility of a low-cost, handheld intraoral imaging probe for image-guided PDT and treatment monitoring while also laying the groundwork for an integrated approach, combining cancer screening and treatment with the same hardware.

Inter-observer agreement among specialists in the diagnosis of Oral Potentially Malignant Disorders and Oral Cancer using Store-and-Forward technology.

Oral Cancer is one of the most common causes of morbidity and mortality. Screening and mobile Health (mHealth) based approach facilitates remote early detection of Oral cancer in a resource-constrained settings. The emerging eHealth technology has aided specialist reach to rural areas enabling remote monitoring and triaging to downstage Oral cancer. Though the diagnostic accuracy of the remote specialist has been evaluated, there are no studies evaluating the consistency among the remote specialists, to the best of our knowledge. The purpose of the study was to evaluate the interobserver agreement between the specialists through telemedicine systems in real-world settings using store and forward technology. Two remote specialists independently diagnosed the clinical images from image repositories, and the diagnostic accuracy was compared with onsite specialist and histopathological diagnosis when available. Moderate agreement (k = 0.682) between two remote specialists and (k = 0.629) between the onsite specialist and two remote specialists in diagnosing oral lesions. The sensitivity and specificity of remote specialist 1 were 92.7% and 83.3%, whereas remote specialist 2 was 95.8% and 60%, respectively, compared to histopathology. The store and forward technology and telecare can be effective tools in triaging and surveillance of patients.

Interpretable and Reliable Oral Cancer Classifier with Attention Mechanism and Expert Knowledge Embedding via Attention Map.

Convolutional neural networks have demonstrated excellent performance in oral cancer detection and classification. However, the end-to-end learning strategy makes CNNs hard to interpret, and it can be challenging to fully understand the decision-making procedure. Additionally, reliability is also a significant challenge for CNN based approaches. In this study, we proposed a neural network called the attention branch network (ABN), which combines the visual explanation and attention mechanisms to improve the recognition performance and interpret the decision-making simultaneously. We also embedded expert knowledge into the network by having human experts manually edit the attention maps for the attention mechanism. Our experiments have shown that ABN performs better than the original baseline network. By introducing the Squeeze-and-Excitation (SE) blocks to the network, the cross-validation accuracy increased further. Furthermore, we observed that some previously misclassified cases were correctly recognized after updating by manually editing the attention maps. The cross-validation accuracy increased from 0.846 to 0.875 with the ABN (Resnet18 as baseline), 0.877 with SE-ABN, and 0.903 after embedding expert knowledge. The proposed method provides an accurate, interpretable, and reliable oral cancer computer-aided diagnosis system through visual explanation, attention mechanisms, and expert knowledge embedding.

Exploring uncertainty measures in convolutional neural network for semantic segmentation of oral cancer images.

Significance: Oral cancer is one of the most prevalent cancers, especially in middle- and low-income countries such as India. Automatic segmentation of oral cancer images can improve the diagnostic workflow, which is a significant task in oral cancer image analysis. Despite the remarkable success of deep-learning networks in medical segmentation, they rarely provide uncertainty quantification for their output. Aim: We aim to estimate uncertainty in a deep-learning approach to semantic segmentation of oral cancer images and to improve the accuracy and reliability of predictions. Approach: This work introduced a UNet-based Bayesian deep-learning (BDL) model to segment potentially malignant and malignant lesion areas in the oral cavity. The model can quantify uncertainty in predictions. We also developed an efficient model that increased the inference speed, which is almost six times smaller and two times faster (inference speed) than the original UNet. The dataset in this study was collected using our customized screening platform and was annotated by oral oncology specialists. Results: The proposed approach achieved good segmentation performance as well as good uncertainty estimation performance. In the experiments, we observed an improvement in pixel accuracy and mean intersection over union by removing uncertain pixels. This result reflects that the model provided less accurate predictions in uncertain areas that may need more attention and further inspection. The experiments also showed that with some performance compromises, the efficient model reduced computation time and model size, which expands the potential for implementation on portable devices used in resource-limited settings. Conclusions: Our study demonstrates the UNet-based BDL model not only can perform potentially malignant and malignant oral lesion segmentation, but also can provide informative pixel-level uncertainty estimation. With this extra uncertainty information, the accuracy and reliability of the model's prediction can be improved.

Interpretable deep learning approach for oral cancer classification using guided attention inference network.

SIGNIFICANCE: Convolutional neural networks (CNNs) show the potential for automated classification of different cancer lesions. However, their lack of interpretability and explainability makes CNNs less than understandable. Furthermore, CNNs may incorrectly concentrate on other areas surrounding the salient object, rather than the network's attention focusing directly on the object to be recognized, as the network has no incentive to focus solely on the correct subjects to be detected. This inhibits the reliability of CNNs, especially for biomedical applications. AIM: Develop a deep learning training approach that could provide understandability to its predictions and directly guide the network to concentrate its attention and accurately delineate cancerous regions of the image. APPROACH: We utilized Selvaraju et al.'s gradient-weighted class activation mapping to inject interpretability and explainability into CNNs. We adopted a two-stage training process with data augmentation techniques and Li et al.'s guided attention inference network (GAIN) to train images captured using our customized mobile oral screening devices. The GAIN architecture consists of three streams of network training: classification stream, attention mining stream, and bounding box stream. By adopting the GAIN training architecture, we jointly optimized the classification and segmentation accuracy of our CNN by treating these attention maps as reliable priors to develop attention maps with more complete and accurate segmentation. RESULTS: The network's attention map will help us to actively understand what the network is focusing on and looking at during its decision-making process. The results also show that the proposed method could guide the trained neural network to highlight and focus its attention on the correct lesion areas in the images when making a decision, rather than focusing its attention on relevant yet incorrect regions. CONCLUSIONS: We demonstrate the effectiveness of our approach for more interpretable and reliable oral potentially malignant lesion and malignant lesion classification.