The Role of Astrocytes in Migraine with Cortical Spreading Depression: Protagonists or Bystanders? A Narrative Review.

Cortical spreading depression (CSD) is a slow wave of cortical depolarization closely associated with migraines with an aura. Previously, it was thought that CSD depolarization was mainly driven by neurons, with characteristic changes in neuronal swelling and increased extracellular potassium (K+) and glutamate. However, the role of astrocytes, a member of the neurovascular unit, in migraine with CSD has recently received increasing attention. In the early stages of CSD, astrocytes provide neurons with energy support and clear K+ and glutamate from synaptic gaps. However, in the late stages of CSD, astrocytes release large amounts of lactic acid to exacerbate hypoxia when the energy demand exceeds the astrocytes' compensatory capacity. Astrocyte endfoot swelling is a characteristic of CSD, and neurons are not similarly altered. It is primarily due to K+ influx and abnormally active calcium (Ca2+) signaling. Aquaporin 4 (AQP-4) only mediates K+ influx and has little role as an aquaporin. Astrocytes endfoot swelling causes perivascular space closure, slowing the glymphatic system flow and exacerbating neuroinflammation, leading to persistent CSD. Astrocytes are double-edged swords in migraine with CSD and may be potential targets for CSD interventions.

GNNGL-PPI: multi-category prediction of protein-protein interactions using graph neural networks based on global graphs and local subgraphs.

Most proteins exert their functions by interacting with other proteins, making the identification of protein-protein interactions (PPI) crucial for understanding biological activities, pathological mechanisms, and clinical therapies. Developing effective and reliable computational methods for predicting PPI can significantly reduce the time-consuming and labor-intensive associated traditional biological experiments. However, accurately identifying the specific categories of protein-protein interactions and improving the prediction accuracy of the computational methods remain dual challenges. To tackle these challenges, we proposed a novel graph neural network method called GNNGL-PPI for multi-category prediction of PPI based on global graphs and local subgraphs. GNNGL-PPI consisted of two main components: using Graph Isomorphism Network (GIN) to extract global graph features from PPI network graph, and employing GIN As Kernel (GIN-AK) to extract local subgraph features from the subgraphs of protein vertices. Additionally, considering the imbalanced distribution of samples in each category within the benchmark datasets, we introduced an Asymmetric Loss (ASL) function to further enhance the predictive performance of the method. Through evaluations on six benchmark test sets formed by three different dataset partitioning algorithms (Random, BFS, DFS), GNNGL-PPI outperformed the state-of-the-art multi-category prediction methods of PPI, as measured by the comprehensive performance evaluation metric F1-measure. Furthermore, interpretability analysis confirmed the effectiveness of GNNGL-PPI as a reliable multi-category prediction method for predicting protein-protein interactions.

Effects of probiotic supplementation on 12 min run performance, mood management, body composition and gut microbiota in amateur marathon runners: A double-blind controlled trial.

Background: Probiotic supplementation has a positive effect on endurance exercise performance and body composition in athletes, but the underlying mechanisms remain unclear. Gut microbiota can provide measurable markers of immune function in athletes, and microbial composition analysis may be sensitive enough to detect stress and metabolic disorders caused by exercise. Methods: Nineteen healthy active amateur marathon runners (15 male and 4 female) with a mean age of 29.11 years volunteered to participate in this double-blind controlled study. Based on the performance of the Cooper 12-min running test (CRT), the participants were allocated into two groups to receive either a probiotic formulation comprising lactobacillus acidophilus and bifidobacterium longum (n = 10) or placebo containing maltodextrin (n = 9) for five weeks. Consistency of diet and exercise was ensured throughout the experimental period. Before and after the intervention, all participants were assessed for CRT, emotional stability and gastrointestinal symptoms, gut microbiota composition, body composition and magnetic resonance imaging (MRI) indicators of skeletal muscle microcirculation. Results: Compared to before the intervention, the probiotics group showed an increase in CRT score (2.88 ± 0.57 vs 3.01 ± 0.60 km, P＜0.05), significant improvement in GSRS and GIQLI (9.20 ± 4.64 vs 7.40 ± 3.24, 118.90 ± 12.30 vs 127.50 ± 9.85, P＜0.05), while these indicators remained unchanged in the control group, with a significant time-group interaction effect on gastrointestinal symptoms. Additionally, some MRI metabolic cycling indicators of the thigh skeletal muscle also changed in the probiotics group (P＜0.05). Regarding microbiota abundance, the probiotics group exhibited a significant increase in the abundance of beneficial bacteria and a significant decrease in the abundance of harmful bacteria post-intervention (P＜0.05). Conclusion: As a sports nutritional supplement, probiotics have the potential to improve athletic performance by optimizing the balance of gut microbiota, alleviating gastrointestinal symptoms.

Cognitive-behavioral therapy for patients with somatoform disorders: A pilot preliminary randomized controlled trial.

Background and objective: Cognitive-behavioral therapy (CBT) for somatoform disorders (SFDs) is understudied in China. Western findings may not be applicable to Chinese culture. This preliminary study evaluated the efficacy of CBT for patients in China, relative to treatment-as-usual (TAU). Methods: Seventy patients with SFDs randomly received either combined CBT and TAU (CBT + TAU), or TAU alone between January 2018 to May 2019. The CBT + TAU group received 12 weekly individual 50-minute CBT sessions. Participants were blindly assessed at 4 timepoints (baseline, week 6, end of treatment: week 12; 12 weeks post-treatment: week 24) using the following outcome measures: SQSS (Self-screening Questionnaire for Somatic Symptoms); PHQ-15 (Patient-Health-Questionnaire-15) and the WI (Whiteley Index); GAD-7 (General Anxiety Disorder-7); HAMD-17 (Hamilton Depression Rating Scale-17); Family Burden Interview Schedule (FBIS); Sheehan Disability Scale (SDS); and the Short Form of Quality-of-Life Enjoyment and Satisfaction Questionnaire (Q-LES-Q-SF). The primary endpoint was the difference between the SQSS total score at week 24 and the baseline. A mixed model for repeated measures was used to analyze inter- and intra-group changes from the baseline. Results: At week 24, The least-squares mean (LSM) change of the total score on the SQSS was -18.87 points and -9.69 points, respectively in the CBT + TAU group and in the TAU group (LSM difference, -9.18 points; 95% confidence interval, -15.72 to -2.64; P = 0.0068). At week 24, the LSM changes from baseline in the WI, HAMD, PHQ15, FBIS and SDS total scores were significantly different between the two groups, however, there was no significant difference in the Q-LES-Q-SF. The SQSS of group effect sizes were 0.63 at 24 weeks. The dropout rates of the CBT + TAU and TAU groups were comparable (22.9% and 19.3%). Conclusions: These preliminary findings suggest that CBT may be helpful for improving the symptoms of patients with SFDs in China.

Machine learning reveals the selection pressure exerted by nonantibiotic pharmaceuticals at environmentally relevant concentrations on antibiotic resistance genotypes.

The emergence and increasing prevalence of antibiotic resistance pose a global public risk for human health, and nonantimicrobial pharmaceuticals play an important role in this process. Herein, five nonantimicrobial pharmaceuticals, including acetaminophen (ACT), clofibric acid (CA), carbamazepine (CBZ), caffeine (CF) and nicotine (NCT), tetracycline-resistant strains, five ARGs (sul1, sul2, tetG, tetM and tetW) and one integrase gene (intI1), were detected in 101 wastewater samples during two typical sewage treatment processes including anaerobic-oxic (A/O) and biological aerated filter (BAF) in Harbin, China. The impact of nonantibiotic pharmaceuticals at environmentally relevant concentrations on both the resistance genotypes and resistance phenotypes were explored. The results showed that a significant impact of nonantibiotic pharmaceuticals at environmentally relevant concentrations on tetracycline resistance genes encoding ribosomal protection proteins (RPPs) was found, while no changes in antibiotic phenotypes, such as minimal inhibitory concentrations (MICs), were observed. Machine learning was applied to further sort out the contribution of nonantibiotic pharmaceuticals at environmentally relevant concentrations to different ARG subtypes. The highest contribution and correlation were found at concentrations of 1400-1800 ng/L for NCT, 900-1500 ng/L for ACT and 7000-10,000 ng/L for CF for tetracycline resistance genes encoding RPPs, while no significant correlation was found between the target compounds and ARGs when their concentrations were lower than 500 ng/L for NCT, 100 ng/L for ACT and 1000 ng/L for CF, which were higher than the concentrations detected in effluent samples. Therefore, the removal of nonantibiotic pharmaceuticals in WWTPs can reduce their selection pressure for resistance genes in wastewater.

The combination of deep learning and pseudo-MS image improves the applicability of metabolomics to congenital heart defect prenatal screening.

To investigate the metabolic alterations in maternal individuals with fetal congenital heart disease (FCHD), establish the FCHD diagnostic models, and assess the performance of these models, we recruited two batches of pregnant women. By metabolomics analysis using Ultra High-performance Liquid Chromatography-Mass/Mass (UPLC-MS/MS), a total of 36 significantly altered metabolites (VIP >1.0) were identified between FCHD and non-FCHD groups. Two logistic regression models and four support vector machine (SVM) models exhibited strong performance and clinical utility in the training set (area under the curve (AUC) = 1.00). The convolutional neural network (CNN) model also demonstrated commendable performance and clinical utility (AUC = 0.89 in the training set). Notably, in the validation set, the performance of the CNN model (AUC = 0.66, precision = 0.714) exhibited better robustness than the six models above (AUC≤0.50). In conclusion, the CNN model based on pseudo-MS images holds promise for real-world and clinical applications due to its better repeatability.

Full-Endoscopic Transforaminal Debridement and Decompression for Brucellar Thoracic Spinal Epidural Abscess: A Minimally Invasive Alternative to Open Surgery.

OBJECTIVE: Thoracic spinal epidural abscess (SEA) is a rare but dangerous condition, and traditional surgical methods are accompanied by extensive trauma and approach-related complications. Here we introduce the technique of full-endoscopic transforaminal debridement and decompression and evaluate its feasibility for treating brucellar thoracic SEA. METHODS: We performed thoracic full-endoscopic transforaminal decompression and debridement on two patients with neurological deficits caused by brucellar SEA, which is mainly composed of granulation tissue rather than pus. Postoperative MRI was conducted to confirm the presence of any residual abscess compressing the nerves. Frankel grading was employed to assess the recovery of neurological function, and complications were documented. RESULTS: There were no occurrences of dural tear, postoperative hematoma, or pulmonary complications. Their neurological function had significantly improved after surgery, and postoperative MRI confirmed no residual abscess compressing the spinal cord. During the 2-year follow-up, one patient achieved complete recovery (from Frankel-C to Frankel-E), while another patient improved from Frankel-A to Frankel-D. Neither patient experienced infection recurrence, instability, nor kyphotic deformity. CONCLUSION: We described the novel application of transforaminal endoscopic surgery in brucellar thoracic granulomatous SEA and preliminarily indicated the feasibility of this technique as a minimally invasive alternative to open surgery.

Bithiophene-Functionalized Infrared Two-Photon Absorption Metal Complexes as Single-Molecule Platforms for Synergistic Photodynamic, Photothermal, and Chemotherapy.

A planar conjugated ligand functionalized with bithiophene and its Ru(II), Os(II), and Ir(III) complexes have been constructed as single-molecule platform for synergistic photodynamic, photothermal, and chemotherapy. The complexes have significant two-photon absorption at 808 nm and remarkable singlet oxygen and superoxide anion production in aqueous solution and cells when exposed to 808 nm infrared irradiation. The most potent Ru(II) complex Ru7 enters tumor cells via the rare macropinocytosis, locates in both nuclei and mitochondria, and regulates DNA-related chemotherapeutic mechanisms intranuclearly including DNA topoisomerase and RNA polymerase inhibition and their synergistic effects with photoactivated apoptosis, ferroptosis and DNA cleavage. Ru7 exhibits high efficacy in vivo for malignant melanoma and cisplatin-resistant non-small cell lung cancer tumors, with a 100% survival rate of mice, low toxicity to normal cells and low residual rate. Such an infrared two-photon activatable metal complex may contribute to a new generation of single-molecule-based integrated diagnosis and treatment platform to address drug resistance in clinical practice and phototherapy for large, deeply located solid tumors.

Fusion of memristor and digital compute-in-memory processing for energy-efficient edge computing.

Artificial intelligence (AI) edge devices prefer employing high-capacity nonvolatile compute-in-memory (CIM) to achieve high energy efficiency and rapid wakeup-to-response with sufficient accuracy. Most previous works are based on either memristor-based CIMs, which suffer from accuracy loss and do not support training as a result of limited endurance, or digital static random-access memory (SRAM)-based CIMs, which suffer from large area requirements and volatile storage. We report an AI edge processor that uses a memristor-SRAM CIM-fusion scheme to simultaneously exploit the high accuracy of the digital SRAM CIM and the high energy-efficiency and storage density of the resistive random-access memory memristor CIM. This also enables adaptive local training to accommodate personalized characterization and user environment. The fusion processor achieved high CIM capacity, short wakeup-to-response latency (392 microseconds), high peak energy efficiency (77.64 teraoperations per second per watt), and robust accuracy (<0.5% accuracy loss). This work demonstrates that memristor technology has moved beyond in-lab development stages and now has manufacturability for AI edge processors.

PIII/PV-Catalyzed Beckmann Reaction and Sequential [2,3]-Sigmatropic Rearrangement to Construct 2-Amidopyridines.

An organophosphorus catalytic method for the synthesis of substituted 2-amidopyridines is reported. The method employs a small-ring organophosphorus-based catalyst and a hydrosilane reductant to drive the conversion of ketoximes and pyridine-N-oxides into 2-amidopyridines through sequential Beckmann rearrangement followed by [2,3]-sigmatropic rearrangement. The readily available ketoximes could be activated to nitrilium ions in PIII/PV redox catalysis and could efficiently participate in the domino reaction of pyridine-N-oxides, thus providing various substituted 2-amidopyridines in moderate to excellent yields. This presented strategy features excellent functional group tolerance and a broad substrate scope.

Improving photochemical indicators for attributing ozone sensitivities in source apportionment analysis.

Comprehensive Air Quality Model with extensions (CAMx)-Decoupled Direct Method (DDM) simulations of first-order ozone (O3) sensitivity to nitrogen oxides (NOx) and volatile organic compounds (VOCs) emissions were performed and combined with modelled [Formula: see text] ratios to obtain a range of thresholds for determining O3-sensitivity regimes for different areas of China. Utilising the new threshold ranges for photochemical indicators, the method for determining O3 formation in the Ozone Source Apportionment Technology (OSAT) module within CAMx was improved by a dynamically varied threshold of [Formula: see text] ratio. The O3 concentration contributions in the newly added transition regime were apportioned to NOx and VOCs emissions in proportion to the relationship between the [Formula: see text] ratio and first-order O3 sensitivity. The source contributions of O3 concentrations from different emission sectors from June to September 2019 were compared using the original and improved CAMx-OSAT. The results showed that the O3 concentration contributions changed significantly in the NOx-limited regime, with a maximum decrease of 21.89%, while the contributions increased by up to 7.57% in the VOC-limited regime, and were within 15 µg/m3 in the transition regime. The modified OSAT module enabled a more sophisticated attribution of O3 to precursor emissions and may have far-reaching implications for informing O3 pollution control policy.

[Interaction between central nervous system and immune system after ischemic stroke and its therapeutic significance of traditional Chinese medicine].

Ischemic stroke is divided into acute phase, subacute phase, and recovery phase, with different pathological and physiological characteristics manifested at each stage. Among them, immune and inflammatory reactions persist for several days and weeks after ischemia. Ischemic stroke not only triggers local inflammation in damaged brain regions but also induces a disorder in the immune system, thereby promoting neuroinflammation and exacerbating brain damage. Therefore, conducting an in-depth analysis of the interaction between the central nervous system and the immune system after ischemic stroke, intervening in the main factors of the interaction between them, blocking pathological cascades, and thereby reducing brain inflammation have become the treatment strategies for ischemic stroke. This study summarizes and sorts out the interaction pathways between the central nervous system and the immune system. The impact of the central nervous system on the immune system can be analyzed from the perspective of the autonomic nervous system, the hypothalamic-pituitary-adrenal axis(HPA), and local inflammatory stimulation. The impact of the immune system on the central nervous system can be analyzed from the dynamic changes of immune cells. At the same time, the relevant progress in the prevention and treatment of traditional Chinese medicine(TCM) is summarized, so as to provide new insights for the analysis of complex mechanisms of TCM in preventing and treating ischemic stroke.

Mechanistic study of Huangqi Guizhi Wuwu decoction amelioration of doxorubicin-induced cardiotoxicity by reducing oxidative stress and inhibiting cellular pyroptosis.

Huangqi Guizhi Wuwu Decoction (HQGZWWD) has shown promising potential in treating various cardiovascular diseases. This study aimed to elucidate the molecular basis and therapeutic role of HQGZWWD in the treatment of doxorubicin (DOX)-induced myocardial injury. The HPLC fingerprint of HQGZWWD was used to analyze the active components. A DOX-induced myocardial damage rat model was developed, and the therapeutic effects of HQGZWWD were evaluated using echocardiography, myocardial enzyme levels, and hematoxylin and eosin staining. Network pharmacology was used to screen treatment targets, and western blotting and immunohistochemistry were performed to assess cellular pyroptosis levels. Oxidative stress levels were measured using assay kits, and mitochondrial damage was examined using transmission electron microscopy. An in vitro model of DOX-induced cell damage was established, and treatment was administered using serum containing HQGZWWD and N-acetylcysteine (NAC). Oxidative stress levels were detected using assay kits and DCFH-DA, whereas cellular pyroptosis levels were assessed through WB, immunofluorescence, and ELISA assays. HQGZWWD ameliorated DOX-induced myocardial injury. Network pharmacology identified IL-1ß and IL-18 as crucial targets. HQGZWWD downregulated the protein levels of the inflammatory factors IL-1ß and IL-18, inhibited the expression of GSDMD-NT, and simultaneously suppressed the synthesis of Caspase-1, ASC, NLRP3, and Caspase-11. Additionally, HQGZWWD inhibited oxidative stress, and the use of NAC as an oxidative stress inhibitor resulted in significant inhibition of the GSDMD-NT protein in H9C2 cells. These findings highlight the myocardial protective effects of HQGZWWD by inhibiting oxidative stress and suppressing both canonical and non-canonical pyroptotic pathways.

Dendrobium officinale phenolic extract maintains proteostasis by regulating autophagy in a Caenorhabditis elegans model of Alzheimer's disease.

Alzheimer's disease (AD) is a progressive neurodegenerative disease, and accumulating evidence suggested that proteostatic imbalance is a key feature of the disease. Traditional Chinese medicine exhibits a multi-target therapeutic effect, making it highly suitable for addressing protein homeostasis imbalance in AD. Dendrobium officinale is a traditional Chinese herbs commonly used as tonic agent in China. In this study, we investigated protection effects of D. officinale phenolic extract (SH-F) and examined its underlying mechanisms by using transgenic Caenorhabditis elegans models. We found that treatment with SH-F (50 µg/mL) alleviated Aß and tau protein toxicity in worms, and also reduced aggregation of polyglutamine proteins to help maintain proteostasis. RNA sequencing results showed that SH-F treatment significantly affected the proteolytic process and autophagy-lysosomal pathway. Furthermore, we confirmed that SH-F showing maintainance of proteostasis was dependent on bec-1 by qRT-PCR analysis and RNAi methods. Finally, we identified active components of SH-F by LC-MS method, and found the five major compounds including koaburaside, tyramine dihydroferulate, N-p-trans-coumaroyltyramine, naringenin and isolariciresinol are the main bioactive components responsible for the anti-AD activity of SH-F. Our findings provide new insights to develop a treatment strategy for AD by targeting proteostasis, and SH-F could be an alternative drug for the treatment of AD.

Complex-Amplitude Programmable Versatile Metasurface Platform Driven by Guided Wave.

Metasurfaces have shown unparalleled controllability of electromagnetic (EM) waves. However, most of the metasurfaces need external spatial feeding sources, which renders practical implementation quite challenging. Here, a low-profile programmable metasurface with 0.05λ0 thickness driven by guided waves is proposed to achieve dynamic control of both amplitude and phase simultaneously. The metasurface is fed by a guided wave traveling in a substrate-integrated waveguide, avoiding external spatial sources and complex power divider networks. By manipulating the state of the p-i-n diodes embedded in each meta-atom, the proposed metasurface enables 1-bit amplitude switching between radiating and nonradiating states, as well as a 1-bit phase switching between 0° and 180°. As a proof of concept, two advanced functionalities, namely, low sidelobe-level beam scanning and Airy beam generation, are experimentally demonstrated with a single platform operating in the far- and near-field respectively. Such complex-amplitude, programmable, and low-profile metasurfaces can overcome integration limitations of traditional metasurfaces, and open up new avenues for more accurate and advanced EM wave control within an unprecedented degree of freedom.

Hardware implementation of memristor-based artificial neural networks.

Artificial Intelligence (AI) is currently experiencing a bloom driven by deep learning (DL) techniques, which rely on networks of connected simple computing units operating in parallel. The low communication bandwidth between memory and processing units in conventional von Neumann machines does not support the requirements of emerging applications that rely extensively on large sets of data. More recent computing paradigms, such as high parallelization and near-memory computing, help alleviate the data communication bottleneck to some extent, but paradigm- shifting concepts are required. Memristors, a novel beyond-complementary metal-oxide-semiconductor (CMOS) technology, are a promising choice for memory devices due to their unique intrinsic device-level properties, enabling both storing and computing with a small, massively-parallel footprint at low power. Theoretically, this directly translates to a major boost in energy efficiency and computational throughput, but various practical challenges remain. In this work we review the latest efforts for achieving hardware-based memristive artificial neural networks (ANNs), describing with detail the working principia of each block and the different design alternatives with their own advantages and disadvantages, as well as the tools required for accurate estimation of performance metrics. Ultimately, we aim to provide a comprehensive protocol of the materials and methods involved in memristive neural networks to those aiming to start working in this field and the experts looking for a holistic approach.

Transcriptomic Analysis of Type 2 Diabetes Mellitus Combined with Lower Extremity Atherosclerotic Occlusive Disease.

Background: The pathological damage mechanism of type 2 diabetes (T2D) and macroangiopathy is extremely complex, and T2D and arteriosclerosis obliterans have different biological behaviors and clinical features. To explore the mechanism of lower extremity arteriosclerosis occlusion (LEAOD) in T2D patients, we utilized RNA-seq to identify unique gene expression signatures of T2D and LEAOD through transcriptomic analysis. Methods: We obtained blood samples and performed RNA sequencing from four patients with T2D, five of whom had LEAOD. Another six age- and gender-matched blood samples from healthy volunteers were used for control. By exploring the general and specific differential expression analysis after transcriptome sequencing, specific gene expression patterns of T2D and LEAOD were verified. Results: Transcriptome analysis found differentially expressed genes in T2D, and T2D + LEAOD (vs normal) separately, of which 35/486 (T2D/T2D + LEAOD) were up-regulated and 1290/2970 (T2D/T2D + LEAOD) were down-regulated. A strong overlap of 571 genes across T2D, LEAOD, and coexisting conditions was mainly involved in extracellular exosomes and the transcription process. By exploring the sex difference gene expression features between T2D, T2D + LEAOD, and healthy controls, we noticed that sex chromosome-associated genes do not participate in the sexual dimorphism gene expression profiles of T2D and LEAOD. Protein-Protein Interaction Network analysis and drug target prediction provided the drug candidates to treat T2D and LEAOD. Conclusion: This study provides some evidence at the transcript level to uncover the association of T2D with LEAOD. The screened hub genes and predicted target drugs may be therapeutic targets.

Characterization of AST-001 non-clinical pharmacokinetics: A novel selective AKR1C3-activated prodrug in mice, rats, and cynomolgus monkeys.

AST-001 is a chemically synthesized inactive nitrogen mustard prodrug that is selectively cleaved to a cytotoxic aziridine (AST-2660) via aldo-keto reductase family 1 member C3 (AKR1C3). The purpose of this study was to investigate the pharmacokinetics and tissue distribution of the prodrug, AST-001, and its active metabolite, AST-2660, in mice, rats, and monkeys. After single and once daily intravenous bolus doses of 1.5, 4.5, and 13.5 mg/kg AST-001 to Sprague-Dawley rats and once daily 1 h intravenous infusions of 0.5, 1.5, and 4.5 mg/kg AST-001 to cynomolgus monkeys, AST-001 exhibited dose-dependent pharmacokinetics and reached peak plasma levels at the end of the infusion. No significant accumulation and gender differences were observed after 7 days of repeated dosing. In rats, the half-life of AST-001 was dose independent and ranged from 4.89 to 5.75 h. In cynomolgus monkeys, the half-life of AST-001 was from 1.66 to 5.56 h and increased with dose. In tissue distribution studies conducted in Sprague-Dawley rats and in liver cancer PDX models in female athymic nude mice implanted with LI6643 or LI6280 HepG2-GFP tumor fragments, AST-001 was extensively distributed to selected tissues. Following a single intravenous dose, AST-001 was not excreted primarily as the prodrug, AST-001 or the metabolite AST-2660 in the urine, feces, and bile. A comprehensive analysis of the preclinical data and inter-species allometric scaling were used to estimate the pharmacokinetic parameters of AST-001 in humans and led to the recommendation of a starting dose of 5 mg/m2 in the first-in-human dose escalation study.

When inflammatory stressors dramatically change, disease phenotypes may transform between autoimmune hematopoietic failure and myeloid neoplasms.

Aplastic anemia (AA) and hypoplastic myelodysplastic syndrome are paradigms of autoimmune hematopoietic failure (AHF). Myelodysplastic syndrome and acute myeloid leukemia are unequivocal myeloid neoplasms (MNs). Currently, AA is also known to be a clonal hematological disease. Genetic aberrations typically observed in MNs are detected in approximately one-third of AA patients. In AA patients harboring MN-related genetic aberrations, a poor response to immunosuppressive therapy (IST) and an increased risk of transformation to MNs occurring either naturally or after IST are predicted. Approximately 10%-15% of patients with severe AA transform the disease phenotype to MNs following IST, and in some patients, leukemic transformation emerges during or shortly after IST. Phenotypic transformations between AHF and MNs can occur reciprocally. A fraction of advanced MN patients experience an aplastic crisis during which leukemic blasts are repressed. The switch that shapes the disease phenotype is a change in the strength of extramedullary inflammation. Both AHF and MNs have an immune-active bone marrow (BM) environment (BME). In AHF patients, an inflamed BME can be evoked by infiltrated immune cells targeting neoplastic molecules, which contributes to the BM-specific autoimmune impairment. Autoimmune responses in AHF may represent an antileukemic mechanism, and inflammatory stressors strengthen antileukemic immunity, at least in a significant proportion of patients who have MN-related genetic aberrations. During active inflammatory episodes, normal and leukemic hematopoieses are suppressed, which leads to the occurrence of aplastic cytopenia and leukemic cell regression. The successful treatment of underlying infections mitigates inflammatory stress-related antileukemic activities and promotes the penetration of leukemic hematopoiesis. The effect of IST is similar to that of treating underlying infections. Investigating inflammatory stress-powered antileukemic immunity is highly important in theoretical studies and clinical practice, especially given the wide application of immune-activating agents and immune checkpoint inhibitors in the treatment of hematological neoplasms.