Supervise-Assisted Self-Supervised Deep-Learning Method for Hyperspectral Image Restoration.

Hyperspectral image (HSI) restoration is a challenging research area, covering a variety of inverse problems. Previous works have shown the great success of deep learning in HSI restoration. However, facing the problem of distribution gaps between training HSIs and target HSI, those data-driven methods falter in delivering satisfactory outcomes for the target HSIs. In addition, the degradation process of HSIs is usually disturbed by noise, which is not well taken into account in existing restoration methods. The existence of noise further exacerbates the dissimilarities within the data, rendering it challenging to attain desirable results without an appropriate learning approach. To track these issues, in this article, we propose a supervise-assisted self-supervised deep-learning method to restore noisy degraded HSIs. Initially, we facilitate the restoration network to acquire a generalized prior through supervised learning from extensive training datasets. Then, the self-supervised learning stage is employed and utilizes the specific prior of the target HSI. Particularly, to restore clean HSIs during the self-supervised learning stage from noisy degraded HSIs, we introduce a noise-adaptive loss function that leverages inner statistics of noisy degraded HSIs for restoration. The proposed noise-adaptive loss consists of Stein's unbiased risk estimator (SURE) and total variation (TV) regularizer and fine-tunes the network with the presence of noise. We demonstrate through experiments on different HSI tasks, including denoising, compressive sensing, super-resolution, and inpainting, that our method outperforms state-of-the-art methods on benchmarks under quantitative metrics and visual quality. The code is available at https://github.com/ying-fu/SSDL-HSI.

Longitudinal ultrasound-based AI model predicts axillary lymph node response to neoadjuvant chemotherapy in breast cancer: a multicenter study.

OBJECTIVES: Developing a deep learning radiomics model from longitudinal breast ultrasound and sonographer's axillary ultrasound diagnosis for predicting axillary lymph node (ALN) response to neoadjuvant chemotherapy (NAC) in breast cancer. METHODS: Breast cancer patients undergoing NAC followed by surgery were recruited from three centers between November 2016 and December 2022. We collected ultrasound images for extracting tumor-derived radiomics and deep learning features, selecting quantitative features through various methods. Two machine learning models based on random forest were developed using pre-NAC and post-NAC features. A support vector machine integrated these data into a fusion model, evaluated via the area under the curve (AUC), decision curve analysis, and calibration curves. We compared the fusion model's performance against sonographer's diagnosis from pre-NAC and post-NAC axillary ultrasonography, referencing histological outcomes from sentinel lymph node biopsy or axillary lymph node dissection. RESULTS: In the validation cohort, the fusion model outperformed both pre-NAC (AUC: 0.899 vs. 0.786, p < 0.001) and post-NAC models (AUC: 0.899 vs. 0.853, p = 0.014), as well as the sonographer's diagnosis of ALN status on pre-NAC and post-NAC axillary ultrasonography (AUC: 0.899 vs. 0.719, p < 0.001). Decision curve analysis revealed patient benefits from the fusion model across threshold probabilities from 0.02 to 0.98. The model also enhanced sonographer's diagnostic ability, increasing accuracy from 71.9% to 79.2%. CONCLUSION: The deep learning radiomics model accurately predicted the ALN response to NAC in breast cancer. Furthermore, the model will assist sonographers to improve their diagnostic ability on ALN status before surgery. CLINICAL RELEVANCE STATEMENT: Our AI model based on pre- and post-neoadjuvant chemotherapy ultrasound can accurately predict axillary lymph node metastasis and assist sonographer's axillary diagnosis. KEY POINTS: Axillary lymph node metastasis status affects the choice of surgical treatment, and currently relies on subjective ultrasound. Our AI model outperformed sonographer's visual diagnosis on axillary ultrasound. Our deep learning radiomics model can improve sonographers' diagnosis and might assist in surgical decision-making.

Multi-stimuli-responsive cyanostilbene derivatives: Their fluorescent and mechanochromic properties, and potential application in water sensing and anti-counterfeiting.

In recent years, aggregation-induced emission luminogens (AIEgens) have witnessed numerous groundbreaking advances in fundamental theoretical research and functional applications. Notably, stimuli-responsive AIEgens have achieved remarkable results, demonstrating immense potential for application in various fields such as chemistry, materials science, biology, and medicine. Herein, two multi-stimuli-responsive cyanostilbene derivatives TPE-CNTPA and PH-CNTPA were synthesized by introducing tetraphenylethylene (TPE) and trifluoromethyl groups, respectively. Primarily, under the combined mechanism of aggregation-induced emission (AIE) and twisted intramolecular charge transfer (TICT), TPE-CNTPA and PH-CNTPA exhibit "on-off-on" fluorescent emission characteristics in solution. Secondly, under 365 nm ultraviolet light irradiation, the photo-induced isomerization of PH-CNTPA causes changes in photophysical property, demonstrating its responsiveness to ultraviolet light. In addition, TPE-CNTPA and PH-CNTPA exhibit high-contrast mechanochromic properties, providing broader possibilities for their potential applications in various fields. Moreover, owing to the unique fluorescence emission characteristics, TPE-CNTPA and PH-CNTP have enormous potential for application in the field of encryption anti-counterfeiting. Besides, PH-CNTPA can be utilized for the detection of trace water in single or mixed solvents, demonstrating outstanding sensitivity and anti-interference properties in different solvents. This research work reveals the potential in the fields of water sensing and anti-counterfeiting for these two multi-stimuli-responsive compounds.

Emerging anticancer potential and mechanisms of snake venom toxins: A review.

Animal-derived venom, like snake venom, has been proven to be valuable natural resources for the drug development. Previously, snake venom was mainly investigated in its pharmacological activities in regulating coagulation, vasodilation, and cardiovascular function, and several marketed cardiovascular drugs were successfully developed from snake venom. In recent years, snake venom fractions have been demonstrated with anticancer properties of inducing apoptotic and autophagic cell death, restraining proliferation, suppressing angiogenesis, inhibiting cell adhesion and migration, improving immunity, and so on. A number of active anticancer enzymes and peptides have been identified from snake venom toxins, such as L-amino acid oxidases (LAAOs), phospholipase A2 (PLA2), metalloproteinases (MPs), three-finger toxins (3FTxs), serine proteinases (SPs), disintegrins, C-type lectin-like proteins (CTLPs), cell-penetrating peptides, cysteine-rich secretory proteins (CRISPs). In this review, we focus on summarizing these snake venom-derived anticancer components on their anticancer activities and underlying mechanisms. We will also discuss their potential to be developed as anticancer drugs in the future.

Design, Synthesis, and Biological Activity of Novel Triketone-Containing Phenoxy Nicotinyl Inhibitors of HPPD.

4-Hydroxyphenylpyruvate dioxygenase (HPPD) is a crucial target enzyme in albino herbicides. The inhibition of HPPD activity interferes with the synthesis of carotenoids, blocking photosynthesis and resulting in bleaching and necrosis. To develop herbicides with excellent activity, a series of 3-hydroxy-2-(6-substituted phenoxynicotinoyl)-2-cyclohexen-1-one derivatives were designed via active substructure combination. The title compounds were characterized via infrared spectroscopy, 1H and 13C nuclear magnetic resonance spectroscopies, and high-resolution mass spectrometry. The structure of compound III-17 was confirmed via single-crystal X-ray diffraction. Preliminary tests demonstrated that some compounds had good herbicidal activity. Crop safety tests revealed that compound III-29 was safer than the commercial herbicide mesotrione in wheat and peanuts. Moreover, the compound exhibited the highest inhibitory activity against Arabidopsis thaliana HPPD (AtHPPD), with a half-maximal inhibitory concentration of 0.19 µM, demonstrating superior activity compared with mesotrione (0.28 µM) in vitro. A three-dimensional quantitative structure-activity relationship study revealed that the introduction of smaller groups to the 5-position of cyclohexanedione and negative charges to the 3-position of the benzene ring enhanced the herbicidal activity. A molecular structure comparison demonstrated that compound III-29 was beneficial to plant absorption and conduction. Molecular docking and molecular dynamics simulations further verified the stability of the complex formed by compound III-29 and AtHPPD. Thus, this study may provide insights into the development of green and efficient herbicides.

Anti-neurofascin-155 antibody mediated a distinct phenotype of chronic inflammatory demyelinating polyradiculoneuropathy.

BACKGROUND: To investigate Ranvier's autoantibodies prevalence and isotypes in various peripheral neuropathy variants, compare clinical features between seronegative and seropositive patients, and elucidate immune mechanisms underlying antibody generation. METHODS: Antibodies against anti-neurofascin-155 (NF155), NF186, contactin-1 (CNTN1), CNTN2, contactin-associated protein 1 (CASPR1), and CASPR2 were identified through cell-based assays. Plasma cytokines were analyzed in anti-NF155 antibody-positive chronic inflammatory demyelinating polyneuropathy (NF155+ CIDP) and Ranvier's antibodies-negative CIDP (Ab- CIDP) patients using a multiplexed fluorescent immunoassay, validated in vitro in a cell culture model. RESULTS: In 368 plasma samples, 50 Ranvier's autoantibodies were found in 45 individuals, primarily in CIDP cases (25 out of 69 patients) and in 10 out of 122 Guillain-Barré syndrome patients. Anti-NF155 and CNTN1-IgG were exclusive to CIDP. Fourteen samples were NF155-IgG, primarily IgG4 subclass, linked to CIDP features including early onset, tremor, sensory disturbance, elevated CSF protein, prolonged motor latency, conduction block, and poor treatment response. NF155-IgG had low sensitivity (20.28%) but high specificity (100%) for CIDP, rising to 88.88% with tremor and prolonged motor latency. Cytokine profiling in NF155+ CIDP revealed distinct immune responses involving helper T cells, toll-like receptor pathways. Some NF155+ CIDP patients had circulating NF155-specific B cells producing NF155-IgG without antigen presence, suggesting therapeutic potential. CONCLUSION: The study emphasizes the high specificity and sensitivity of NF155-IgG for diagnosing CIDP characterized by distinctive features. Further investigation into circulating NF155-specific B cell phenotypes may pave the way for B cell directed therapy.

Antibiotic susceptibility patterns and trends of the gram-negative bacteria isolated from the patients in the emergency departments in China: results of SMART 2016-2019.

BACKGROUND: The study aims were to evaluate the species distribution and antimicrobial resistance profile of Gram-negative pathogens isolated from specimens of intra-abdominal infections (IAI), urinary tract infections (UTI), respiratory tract infections (RTI), and blood stream infections (BSI) in emergency departments (EDs) in China. METHODS: From 2016 to 2019, 656 isolates were collected from 18 hospitals across China. Minimum inhibitory concentrations were determined by CLSI broth microdilution and interpreted according to CLSI M100 (2021) guidelines. In addition, organ-specific weighted incidence antibiograms (OSWIAs) were constructed. RESULTS: Escherichia coli (E. coli) and Klebsiella pneumoniae (K. pneumoniae) were the most common pathogens isolated from BSI, IAI and UTI, accounting for 80% of the Gram-negative clinical isolates, while Pseudomonas aeruginosa (P. aeruginosa) was mainly isolated from RTI. E. coli showed < 10% resistance rates to amikacin, colistin, ertapenem, imipenem, meropenem and piperacillin/tazobactam. K. pneumoniae exhibited low resistance rates only to colistin (6.4%) and amikacin (17.5%) with resistance rates of 25-29% to carbapenems. P. aeruginosa exhibited low resistance rates only to amikacin (13.4%), colistin (11.6%), and tobramycin (10.8%) with over 30% resistance to all traditional antipseudomonal antimicrobials including ceftazidime, cefepime, carbapenems and levofloxacin. OSWIAs were different at different infection sites. Among them, the susceptibility of RTI to conventional antibiotics was lower than for IAI, UTI or BSI. CONCLUSIONS: Gram-negative bacteria collected from Chinese EDs exhibited high resistance to commonly used antibiotics. Susceptibilities were organ specific for different infection sites, knowledge which will be useful for guiding empirical therapies in the clinic.

Oncogenic functions and therapeutic potentials of targeted inhibition of SMARCAL1 in small cell lung cancer.

Small cell lung cancer (SCLC) is a recalcitrant cancer characterized by high frequency loss-of-function mutations in tumor suppressors with a lack of targeted therapy due to absence of high frequency gain-of-function abnormalities in oncogenes. SMARCAL1 is a member of the ATP-dependent chromatin remodeling protein SNF2 family that plays critical roles in DNA damage repair and genome stability maintenance. Here, we showed that SMARCAL1 was overexpressed in SCLC patient samples and was inversely associated with overall survival of the patients. SMARCAL1 was required for SCLC cell proliferation and genome integrity. Mass spectrometry revealed that PAR6B was a downstream SMARCAL1 signal molecule which rescued inhibitory effects caused by silencing of SMARCAL1. By screening of 36 FDA-approved clinically available agents related to DNA damage repair, we found that an aza-anthracenedione, pixantrone, was a potent SMARCAL1 inhibitor which suppressed the expression of SMARCAL1 and PAR6B at protein level. Pixantrone caused DNA damage and exhibited inhibitory effects on SCLC cells in vitro and in a patient-derived xenograft mouse model. These results indicated that SMARCAL1 functions as an oncogene in SCLC, and pixantrone as a SMARCAL1 inhibitor bears therapeutic potentials in this deadly disease.

Lactate metabolism promotes in vivo fitness during Acinetobacter baumannii infection.

Acinetobacter baumannii is one of the most prevalent causes of nosocomial infections worldwide. However, a paucity of information exists regarding the connection between metabolic capacity and in vivo bacterial fitness. Elevated lactate is a key marker of severe sepsis. We have previously shown that the putative A. baumannii lactate permease gene, lldP, is upregulated during in vivo infection. Here, we confirm that lldP expression is upregulated in three A. baumannii strains during a mammalian systemic infection. Utilising a transposon mutant disrupted for lldP in the contemporary clinical strain AB5075-UW, and a complemented strain, we confirmed its role in the in vitro utilisation of l-(+)-lactate. Furthermore, disruption of the lactate metabolism pathway resulted in reduced bacterial fitness during an in vivo systemic murine competition assay. The disruption of lldP had no impact on the susceptibility of this strain to complement mediated killing by healthy human serum. However, growth in biologically relevant concentrations of lactate observed during severe sepsis, led to bacterial tolerance to killing by healthy human blood, a phenotype that was abolished in the lldP mutant. This study highlights the importance of the lactate metabolism pathway for survival and growth of A. baumannii during infection.

Direct electrospinning for producing multiple activity nanofibers consisting of aggregated luteolin/hydroxypropyl-gamma-cyclodextrin inclusion complex.

Hydroxypropyl-gamma-cyclodextrin (HPγCD) inclusion complex nanofibers (Lut/HPγCD-IC-NF) containing Luteolin (Lut) were prepared by electrospinning technology. Fourier transform infrared (FTIR) spectroscopy and X-ray diffraction (XRD) spectra confirmed the formation of Lut/HPγCD-IC-NF. Scanning electron microscopy (SEM) images showed that the morphology of Lut/HPγCD-IC-NF was uniform and bead-free, suggesting that self-assembled aggregates, macromolecules with higher molecular weights, were formed by strong hydrogen bonding interactions between the cyclodextrin inclusion complexes. Confocal laser scanning microscopy (CLSM) images showed that Lut was distributed in Lut/HPγCD-IC-NF. Proton nuclear magnetic resonance (1H NMR) spectroscopy revealed the change in chemical shift of the proton peak between Lut and HPγCD, confirming the formation of inclusion complex. Thermogravimetric analysis (TGA) proved that Lut/HPγCD-IC-NF had good thermal stability. The phase solubility test confirmed that HPγCD had a solubilizing effect on Lut. When the solubility of HPγCD reached 10 mM, the solubility of Lut increased by 15-fold. The drug loading test showed that the content of Lut in fibers reached 8.57 ± 0.02 %. The rapid dissolution experiment showed that Lut/HPγCD-IC-NF dissolved within 3 s. The molecular simulation provides three-dimensional evidence for the formation of inclusion complexes between Lut and HPγCD. Antibacterial experiments showed that Lut/HPγCD-IC-NF had enhanced antibacterial activity against S. aureus. Lut/HPγCD-IC-NF exhibited excellent antioxidant properties with a free radical scavenging ability of 89.5 ± 1.1 %. In vitro release experiments showed Lut/HPγCD-IC-NF had a higher release amount of Lut. In conclusion, Lut/HPγCD-IC-NF improved the physicochemical properties and bioavailability of Lut, providing potential applications of Lut in the pharmaceutical field.

A novel fluorescence platform for specific detection of tetracycline antibiotics based on [MQDA-Eu3+] system.

Tetracycline antibiotics (TCs) are extensively used in clinical medicine, animal husbandry, and aquaculture because of their cost-effectiveness and high antibacterial efficacy. However, the presence of TCs residues in the environment poses risks to humans. In this study, an inner filter effect (IFE) fluorescent probe, 2,2'-(ethane-1,2-diylbis((2-((2-methylquinolin-8-yl)amino)-2-oxoethyl)azanediyl))diacetic acid (MQDA), was developed for the rapid detection of Eu3+ within 30 s. And its complex [MQDA-Eu3+] was successfully used for the detection of TCs. Upon coordination of a carboxyl of MQDA with Eu3+ to form a [MQDA-Eu3+] complex, the carboxyl served as an antenna ligand for the effective detection of Eu3+ to intensify the emission intensity of MQDA via "antenna effect", the process was the energy absorbed by TCs via UV excitation was effectively transferred to Eu3+. Fluorescence quenching of the [MQDA-Eu3+] complex was caused by the IFE in multicolor fluorescence systems. The limits of detection of [MQDA-Eu3+] for oxytetracycline, chlorotetracycline hydrochloride, and tetracycline were 0.80, 0.93, and 1.7 µM in DMSO/HEPES (7:3, v/v, pH = 7.0), respectively. [MQDA-Eu3+] demonstrated sensitive detection of TCs in environmental and food samples with satisfactory recoveries and exhibited excellent imaging capabilities for TCs in living cells and zebrafish with low cytotoxicity. The proposed approach demonstrated considerable potential for the quantitative detection of TCs.

Transformer based Pluralistic Image Completion with Reduced Information Loss.

Transformer based methods have achieved great success in image inpainting recently. However, we find that these solutions regard each pixel as a token, thus suffering from an information loss issue from two aspects: 1) They downsample the input image into much lower resolutions for efficiency consideration. 2) They quantize 2563 RGB values to a small number (such as 512) of quantized color values. The indices of quantized pixels are used as tokens for the inputs and prediction targets of the transformer. To mitigate these issues, we propose a new transformer based framework called "PUT". Specifically, to avoid input downsampling while maintaining computation efficiency, we design a patch-based auto-encoder P-VQVAE. The encoder converts the masked image into non-overlapped patch tokens and the decoder recovers the masked regions from the inpainted tokens while keeping the unmasked regions unchanged. To eliminate the information loss caused by input quantization, an Un-quantized Transformer is applied. It directly takes features from the P-VQVAE encoder as input without any quantization and only regards the quantized tokens as prediction targets.Furthermore, to make the inpainting process more controllable, we introduce semantic and structural conditions as extra guidance. Extensive experiments show that our method greatly outperforms existing transformer based methods on image fidelity and achieves much higher diversity and better fidelity than state-of-the-art pluralistic inpainting methods on complex large-scale datasets (e.g., ImageNet). Codes are available at https://github.com/liuqk3/PUT.

A metabolic perspective to sleep genetics.

The metabolic signals that regulate sleep and the metabolic functions that occur during sleep are active areas of research. Prior studies have focused on sugars and nucleotides but new genetic evidence suggests novel functions of lipid and amino acid metabolites in sleep. Additional genetic studies of energetic signaling pathways and the circadian clock transcription factor network have increased our understanding of how sleep responds to changes in the metabolic state. This review focuses on key recent insights from genetic experiments in humans and model organisms to improve our understanding of the interrelationship between metabolism and sleep.

SASAN: Spectrum-Axial Spatial Approach Networks for Medical Image Segmentation.

Ophthalmic diseases such as central serous chorioretinopathy (CSC) significantly impair the vision of millions of people globally. Precise segmentation of choroid and macular edema is critical for diagnosing and treating these conditions. However, existing 3D medical image segmentation methods often fall short due to the heterogeneous nature and blurry features of these conditions, compounded by medical image clarity issues and noise interference arising from equipment and environmental limitations. To address these challenges, we propose the Spectrum Analysis Synergy Axial-Spatial Network (SASAN), an approach that innovatively integrates spectrum features using the Fast Fourier Transform (FFT). SASAN incorporates two key modules: the Frequency Integrated Neural Enhancer (FINE), which mitigates noise interference, and the Axial-Spatial Elementum Multiplier (ASEM), which enhances feature extraction. Additionally, we introduce the Self-Adaptive Multi-Aspect Loss (LSM), which balances image regions, distribution, and boundaries, adaptively updating weights during training. We compiled and meticulously annotated the Choroid and Macular Edema OCT Mega Dataset (CMED-18k), currently the world's largest dataset of its kind. Comparative analysis against 13 baselines shows our method surpasses these benchmarks, achieving the highest Dice scores and lowest HD95 in the CMED and OIMHS datasets. Our code is publicly available at https://github.com/IMOP-lab/SASAN-Pytorch.

Efficacy and survival outcomes of alectinib vs. crizotinib in ALK­positive NSCLC patients with CNS metastases: A retrospective study.

Anaplastic lymphoma kinase (ALK) tyrosine kinase inhibitors (TKIs) have transformed the treatment paradigm for patients with ALK-positive non-small cell lung cancer (NSCLC). Yet the differential efficacy between alectinib and crizotinib in treating patients with NSCLC and central nervous system (CNS) metastases has been insufficiently studied. A retrospective analysis was conducted of clinical outcomes of patients with ALK-positive NSCLC and CNS metastases treated at the Shandong Cancer Centre. Based on their initial ALK-TKI treatment, patients were categorised into either the crizotinib group or the alectinib group. Efficacy, progression-free survival (PFS), intracranial PFS and overall survival (OS) were evaluated. A total of 46 eligible patients were enrolled in the present study: 33 patients received crizotinib and 13 patients received alectinib. The median OS of the entire group was 66.8 months (95% CI: 48.5-85.1). Compared with the patients in the crizotinib group, the patients in the alectinib group showed a significant improvement in both median (m)PFS (27.5 vs. 9.5 months; P=0.003) and intracranial mPFS (36.0 vs. 10.8 months; P<0.001). However, there was no significant difference in OS between the alectinib and crizotinib groups (not reached vs. 58.7 months; P=0.149). Furthermore, there were no significant differences between patients receiving TKI combined with radiotherapy (RT) vs. TKI alone with respect to mPFS (11.0 vs. 11.7 months, P=0.863) as well as intracranial mPFS (12.5 vs. 16.9 months, P=0.721). In the present study, alectinib exhibited superior efficacy to crizotinib for treating patients with ALK-positive NSCLC and CNS metastases, especially in terms of delaying disease progression and preventing CNS recurrence. Moreover, the results demonstrated that it might be beneficial to delay local RT for patients with ALK-positive NSCL and CNS metastases.

Relationship between brain white matter damage and grey matter atrophy in hereditary spastic paraplegia types 4 and 5.

BACKGROUND AND PURPOSE: White matter (WM) damage is the main target of hereditary spastic paraplegia (HSP), but mounting evidence indicates that genotype-specific grey matter (GM) damage is not uncommon. Our aim was to identify and compare brain GM and WM damage patterns in HSP subtypes and investigate how gene expression contributes to these patterns, and explore the relationship between GM and WM damage. METHODS: In this prospective single-centre cohort study from 2019 to 2022, HSP patients and controls underwent magnetic resonance imaging evaluations. The alterations of GM and WM patterns were compared between groups by applying a source-based morphometry approach. Spearman rank correlation was used to explore the associations between gene expression and GM atrophy patterns in HSP subtypes. Mediation analysis was conducted to investigate the interplay between GM and WM damage. RESULTS: Twenty-one spastic paraplegia type 4 (SPG4) patients (mean age 50.7 years ± 12.0 SD, 15 men), 21 spastic paraplegia type 5 (SPG5) patients (mean age 29.1 years ± 12.8 SD, 14 men) and 42 controls (sex- and age-matched) were evaluated. Compared to controls, SPG4 and SPG5 showed similar WM damage but different GM atrophy patterns. GM atrophy patterns in SPG4 and SPG5 were correlated with corresponding gene expression (ρ = 0.30, p = 0.008, ρ = 0.40, p < 0.001, respectively). Mediation analysis indicated that GM atrophy patterns were mediated by WM damage in HSP. CONCLUSIONS: Grey matter atrophy patterns were distinct between SPG4 and SPG5 and were not only secondary to WM damage but also associated with disease-related gene expression. CLINICAL TRIAL REGISTRATION NO: NCT04006418.

Cryo-EM structure of human HCN3 channel and its regulation by cAMP.

HCN channels are important for regulating heart rhythm and nerve activity and have been studied as potential drug targets for treating depression, arrhythmia, nerve pain, and epilepsy. Despite possessing unique pharmacological properties, HCN channels share common characteristics in that they are activated by hyperpolarization and modulated by cAMP and other membrane lipids. However, the mechanisms of how these ligands bind and modulate HCN channels are unclear. In this study, we solved structures of full-length human HCN3 using cryo-EM and captured two different states, including a state without any ligand bound and a state with cAMP bound. Our structures reveal the novel binding sites for cholesteryl hemisuccinate in apo state and show how cholesteryl hemisuccinate and cAMP binding cause conformational changes in different states. These findings explain how these small modulators are sensed in mammals at the molecular level. The results of our study could help to design more potent and specific compounds to influence HCN channel activity and offer new therapeutic possibilities for diseases that lack effective treatment.

Cortical Microhemorrhage Presentation of Small Vessel Primary Angiitis of the Central Nervous System.

OBJECTIVE: Primary angiitis of the central nervous system (PACNS) is a rare vasculitis restricted to the brain, spinal cord, and leptomeninges. This study aimed to describe the imaging characteristics of patients with small vessel PACNS (SV-PACNS) using 7 T magnetic resonance imaging (MRI). METHODS: This ongoing prospective observational cohort study included patients who met the Calabrese and Mallek criteria and underwent 7 T MRI scan. The MRI protocol includes T1-weighted magnetization-prepared rapid gradient echo imaging, T2 star weighted imaging, and susceptibility-weighted imaging. Two experienced readers independently reviewed the neuroimages. Clinical data were extracted from the electronic patient records. The findings were then applied to a cohort of patients with large vessel central nervous system (CNS) vasculitis. RESULTS: We included 21 patients with SV-PACNS from December 2021 to November 2023. Of these, 12 (57.14%) had cerebral cortical microhemorrhages with atrophy. The pattern with microhemorrhages was described in detail based on the gradient echo sequence, leading to the identification of what we have termed the "coral-like sign." The onset age of patients with coral-like sign (33.83 ± 9.93 years) appeared younger than that of patients without coral-like sign (42.11 ± 14.18 years) (P = 0.131). Furthermore, the cerebral lesions in patients with cortical microhemorrhagic SV-PACNS showed greater propensity toward bilateral lesions (P = 0.03). The coral-like sign was not observed in patients with large vessel CNS vasculitis. INTERPRETATION: The key characteristics of the coral-like sign represent cerebral cortical diffuse microhemorrhages with atrophy, which may be an important MRI pattern of SV-PACNS. ANN NEUROL 2024.