A novel bispecific T-cell engager using the ligand-target csGRP78 against acute myeloid leukemia.

Current medical therapies for treating acute myeloid leukemia (AML) remain unmet, and AML patients may benefit from targeted immunotherapy approaches that focus on specific tumor antigens. GRP78, which is upregulated in various malignant tumors such as AML, is partially expressed as cell surface GRP78 (csGRP78) on the cell membrane, making it an ideal target for redirecting T cells, including T-cell engagers. However, considering the conventional approach of using two scFv segments to construct a bispecific T-cell engager (BiTE), we have undertaken the development of a novel BiTE that utilizes a cyclic peptide ligand to specifically target csGRP78, which we refer to as GRP78-CD3/BiTE. We studied the effects of GRP78-CD3/BiTE on treatments for AML in vitro and in vivo and assessed the pharmacokinetics of this engager. Our findings demonstrated that GRP78-CD3/BiTE could not only effectively mediate the cytotoxicity of T cells against csGRP78-expressing AML cells but also specifically eliminate primary AML tumor cells in vitro. Furthermore, GRP78-CD3/BiTE exhibited a longer half-life despite having a lower molecular weight than CD19-CD3/BiTE. In a xenograft mouse model of AML, treatment with GRP78-CD3/BiTE prolonged the survival time of the mice. Our findings demonstrate that GRP78-CD3/BiTE is effective and selective for eliminating csGRP78-expressing AML cells and suggest that this approach to targeted immunotherapy could lead to effective new treatments for AML.

Upregulation of POC1A in lung adenocarcinoma promotes tumour progression and predicts poor prognosis.

Lung adenocarcinoma (LUAD) is characterized by a high incidence rate and mortality. Recently, POC1 centriolar protein A (POC1A) has emerged as a potential biomarker for various cancers, contributing to cancer onset and development. However, the association between POC1A and LUAD remains unexplored. We extracted The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) data sets to analyse the differential expression of POC1A and its relationship with clinical stage. Additionally, we performed diagnostic receiver operator characteristic (ROC) curve analysis and Kaplan-Meier (KM) survival analysis to assess the diagnostic and prognostic value of POC1A in LUAD. Furthermore, we investigated the correlation between POC1A expression and immune infiltration, tumour mutation burden (TMB), immune checkpoint expression and drug sensitivity. Finally, we verified POC1A expression using real-time quantitative polymerase chain reaction (RT-qPCR) and immunohistochemistry (IHC). Cell experiments were conducted to validate the effect of POC1A expression on the proliferation, migration and invasion of lung cancer cells. POC1A exhibited overexpression in most tumour tissues, and its overexpression in LUAD was significantly correlated with late-stage presentation and poor prognosis. The high POC1A expression group showed lower levels of immune infiltration but higher levels of immune checkpoint expression and TMB. Moreover, the high POC1A expression group demonstrated sensitivity to multiple drugs. In vitro experiments confirmed that POC1A knockdown led to decreased proliferation, migration, and invasion of lung cancer cells. Our findings suggest that POC1A may contribute to tumour development by modulating the cell cycle and immune cell infiltration. It also represents a potential therapeutic target and marker for the diagnosis and prognosis of LUAD.

Novel CAR-T cells targeting TRKB for the treatment of solid cancer.

Chimeric antigen receptor (CAR) T-cell therapy is highly effective for treating blood cancers such as B-cell malignancies, however, its effectiveness as an approach to treat solid tumors remains to be further explored. Here, we focused on the development of CAR-T cell therapies targeting tropomyosin-related kinase receptor B (TRKB), a highly expressed protein that is significantly associated with tumor progression, malignancy, and drug resistance in multiple forms of aggressive solid tumors. To achieve this, we screened brain-derived neurotrophic factor (BDNF) and neurotrophin 4 (NTF4) ligand-based CAR-T cells for their efficiency in targeting the TRKB receptor in the context of solid tumors, particularly hepatocellular carcinoma and pancreatic cancer. We demonstrated that TRKB is overexpressed not only in hepatocellular carcinoma and pancreatic carcinoma cell lines but also in cancer stem-like cells (CSCs). Notably, BDNF-CAR T and NTF4-CAR T cells could not only effectively target and kill TRKB-expressing pan-cancer cell lines in a dose-dependent manner but also effectively kill CSCs. We also performed in vivo studies to show that NTF4-CAR T cells have a better potential to inhibit the tumor growth of hepatocellular carcinoma xenografts in mice, compared with BDNF-CAR T cells. Taken together, our findings suggest that CAR-T targeting TRKB may be a promising approach for developing novel therapies to treat solid cancers.

Mesothelin-based CAR-T cells exhibit potent antitumor activity against ovarian cancer.

BACKGROUND: Ovarian cancer (OC) is characterized by its rapid growth and spread which, accompanied by a low 5-year survival rate, necessitates the development of improved treatments. In ovarian cancer, the selective overexpression of Mucin-16 (MUC16, CA125) in tumor cells highlights its potential as a promising target for developing anti-tumor therapies. However, the potential effectiveness of CAR-T cell therapy that targets MUC16 in ovarian cancer cells is unknown. METHODS: The expression of MUC16 in viable OC cells was detected using immunofluorescence and flow cytometry techniques. A MSLN-CAR construct, comprising the MUC16-binding polypeptide region of mesothelin (MSLN), a CD8 hinge spacer and transmembrane domain, 4-1BB, and CD3ζ endo-domains; was synthesized and introduced into T cells using lentiviral particles. The cytotoxicity of the resultant CAR-T cells was evaluated in vitro using luciferase assays. Cytokine release by CAR-T cells was measured using enzyme-linked immunosorbent assays. The anti-tumor efficacy of the CAR-T cells was subsequently assessed in mice through both systemic and local administration protocols. RESULTS: MSLN-CAR T cells exhibited potent cytotoxicity towards OVCAR3 cells and their stem-like cells that express high levels of MUC16. Also, MSLN-CAR T cells were inefficient at killing SKOV3 cells that express low levels of MUC16, but were potently cytotoxic to such cells overexpressing MUC16. Moreover, MSLN-CAR T cells delivered via tail vein or peritoneal injection could shrink OVCAR3 xenograft tumors in vivo, with sustained remission observed following peritoneal delivery of MSLN-CAR T cells. CONCLUSIONS: Collectively, these results suggested that MSLN-CAR T cells could potently eliminate MUC16- positive ovarian cancer tumor cells both in vitro and in vivo, thereby providing a promising therapeutic intervention for MUC16-positive patients.

Unsupervised representation learning of spontaneous MEG data with nonlinear ICA.

Resting-state magnetoencephalography (MEG) data show complex but structured spatiotemporal patterns. However, the neurophysiological basis of these signal patterns is not fully known and the underlying signal sources are mixed in MEG measurements. Here, we developed a method based on the nonlinear independent component analysis (ICA), a generative model trainable with unsupervised learning, to learn representations from resting-state MEG data. After being trained with a large dataset from the Cam-CAN repository, the model has learned to represent and generate patterns of spontaneous cortical activity using latent nonlinear components, which reflects principal cortical patterns with specific spectral modes. When applied to the downstream classification task of audio-visual MEG, the nonlinear ICA model achieves competitive performance with deep neural networks despite limited access to labels. We further validate the generalizability of the model across different datasets by applying it to an independent neurofeedback dataset for decoding the subject's attentional states, providing a real-time feature extraction and decoding mindfulness and thought-inducing tasks with an accuracy of around 70% at the individual level, which is much higher than obtained by linear ICA or other baseline methods. Our results demonstrate that nonlinear ICA is a valuable addition to existing tools, particularly suited for unsupervised representation learning of spontaneous MEG activity which can then be applied to specific goals or tasks when labelled data are scarce.

RNF34 functions in immunity and selective mitophagy by targeting MAVS for autophagic degradation.

Viral infection triggers the formation of mitochondrial antiviral signaling protein (MAVS) aggregates, which potently promote immune signaling. Autophagy plays an important role in controlling MAVS-mediated antiviral signaling; however, the exact molecular mechanism underlying the targeted autophagic degradation of MAVS remains unclear. Here, we investigated the mechanism by which RNF34 regulates immunity and mitophagy by targeting MAVS. RNF34 binds to MAVS in the mitochondrial compartment after viral infection and negatively regulates RIG-I-like receptor (RLR)-mediated antiviral immunity. Moreover, RNF34 catalyzes the K27-/K29-linked ubiquitination of MAVS at Lys 297, 311, 348, and 362 Arg, which serves as a recognition signal for NDP52-dependent autophagic degradation. Specifically, RNF34 initiates the K63- to K27-linked ubiquitination transition on MAVS primarily at Lys 311, which facilitates the autophagic degradation of MAVS upon RIG-I stimulation. Notably, RNF34 is required for the clearance of damaged mitochondria upon viral infection. Thus, we elucidated the mechanism by which RNF34-mediated autophagic degradation of MAVS regulates the innate immune response, mitochondrial homeostasis, and infection.

Hepatocyte-specific HDAC3 ablation promotes hepatocellular carcinoma in females by suppressing Foxa1/2.

BACKGROUND: Hepatocellular carcinoma (HCC), the most common primary liver cancer, prevails mainly in males and has long been attributed to androgens and higher circumstantial levels of interleukin-6 (IL-6) produced by resident hepatic macrophages. METHODS: Constitutively hepatocyte-specific histone deacetylase 3 (HDAC3)-deficient (HDAC3LCKO) mice and constitutively hepatocyte-specific HDAC3 knockout and systemic IL-6 simultaneously ablated (HDAC3LCKO& IL-6-/-) mice were used in our study to explore the causes of sex differences in HCC. Additionally, we performed human HCC tissues with an IHC score. Correlation analysis and linear regression plots were constructed to reveal the association between HDAC3 and its candidate genes. To further elucidate that HDAC3 controls the expression of Foxa1/2, we knocked down HDAC3 in HUH7 liver cancer cells. RESULTS: We observed a contrary sex disparity, with an earlier onset and higher incidence of HCC in female mice when HDAC3 was selectively ablated in the liver. Loss of HDAC3 led to constant liver injury and the spontaneous development of HCC. Unlike the significant elevation of IL-6 in male mice at a very early age, female mice exhibit stable IL-6 levels, and IL-6 ablation did not eliminate the sex disparity in hepatocarcinogenesis in HDAC3-deficient mice. Oestrogen often protects the liver when combined with oestrogen receptor alpha (ERα); however, ovariectomy in HDAC3-ablated female mice significantly delayed tumourigenesis. The oestrogen-ERα axis can also play a role in tumour promotion in the absence of Foxa1 and Foxa2 in the receptor complex. Loss of HDAC3 profoundly reduced the expression of both Foxa1 and Foxa2 and impaired the binding between Foxa1/2 and ERα. Furthermore, a more frequent HDAC3 decrease accompanied by the simultaneous Foxa1/2 decline was found in female HCC compared to that in male HCC. CONCLUSION: In summary, we reported that loss of HDAC3 reduces Foxa1/2 and thus promotes HCC development in females in an oestrogen-dependent manner.

CAR-T Therapy Targets Extra Domain B of Fibronectin Positive Solid Tumor Cells.

BACKGROUND: CAR-T cell immunotherapy has achieved remarkable success in malignant B-cell malignancies, but progress in solid tumors is slow, and one of the key reasons is the lack of ideal targets. Cancer-specific extra domain B of fibronectin (EDB-FN) is widely upregulated in solid tumors and expressed at low levels in normal tissues. Many imaging and targeted cancer therapies based on EDB-FN targets have been developed and tested in clinical trials, making EDB-FN an ideal target for immunotherapy. METHODS: We constructed two EDB-FN-targeted CAR-Ts based on the peptide APT0 and the single-chain antibody CGS2 in a lentiviral infection manner for the first time. Luciferase cytotoxicity assay to assess CAR-T killing of tumor cells. An enzyme-linked immunosorbent assay was used to detect the release of the cytokine IFN-γ. Fluorescence imaging to evaluate the dynamics of CAR-T cell and tumor cell coculture. Knockdown assays were used to validate the target specificity of CAR-T cells. RESULTS: In this research, two CAR-Ts targeting EDB-FN, APT0 CAR-T, and CGS2 CAR-T, were constructed. In vitro, both CAR-T cells produced broad-spectrum killing of multiple EDB-FN-positive solid tumor cell lines and were accompanied by cytokine IFN-γ release. Regarding safety, the two CAR-T cells did not affect T cells' normal growth and proliferation and were not toxic to HEK-293T human embryonic kidney epithelial cells. CONCLUSION: APT0 CAR-T and CGS2 CAR-T cells are two new CAR-Ts targeting EDB-FN. Both CAR-T cells can successfully identify and specifically kill various EDB-FN-positive solid tumor cells with potential clinical applications.

Identification of PYGL as a key prognostic gene of glioma by integrated bioinformatics analysis.

Aim: PYGL has been reported to have carcinogenic effects in a variety of tumors. This study is the first to reveal the relationship between PYGL and the prognosis of glioma. Materials & methods: Analyzing the Chinese Glioma Genome Atlas database, the authors revealed the expression status and prognostic value of PYGL in gliomas and used quantitative real-time PCR to verify PYGL expression again. Subsequently, they used Gene Set Enrichment Analysis to explore the biological pathways that PYGL may participate in. The authors also used the tumor immune estimation resource database to explore the relationship between PYGL and tumor immune cells. Results: PYGL is involved in the malignant progression of glioma. Conclusions: PYGL can be used as a new biomarker and molecular target for evaluating the prognosis and immunotherapy of glioma.

Overexpression of GINS4 is associated with poor prognosis and survival in glioma patients.

BACKGROUND: GINS4, an indispensable component of the GINS complex, is vital for a variety of cancer. However, no known empirical research has focused on exploring relationships between GINS4 and glioma. Thus, this study aims to understand and explain the role of GINS4 in glioma. METHOD: First, we used the data in the CGGA, TCGA, GEO, GEPIA, and HPA databases to explore the expression level of GINS4 in glioma, the correlation between GINS4 expression and the clinical features of glioma, its impact on the survival of glioma patients, and verified the analysis results through RT-qPCR, IHC, and meta-analysis. Subsequently, GSEA enrichment analysis is used to find the potential molecular mechanism of GINS4 to promote the malignant process of glioma and the anti-glioma drugs that may target GINS4 screened by CMap analysis. Moreover, we further explored the influence of the GINS4 expression on the immune microenvironment of glioma patients through the TIMER database. RESULTS: Our results suggested that GINS4 was elevated in glioma, and the overexpression of GINS4 was connected with a vast number of clinical features. The next, GINS4 as an independent prognostic factor, which can result in an unfavorable prognosis of glioma. Once more, GINS4 may be participating in the oncogenesis of glioma through JAK-STAT signaling pathways, etc. 6-thioguanine, Doxazosin, and Emetine had potential value in the clinical application of drugs targeting GINS4. Finally, the expression exhibited a close relationship with some immune cells, especially Dendritic cells. CONCLUSION: GINS4 is an independent prognostic factor that led to a poor prognosis of glioma. The present study revealed the probable underlying molecular mechanisms of GINS4 in glioma and provided a potential target for improving the prognosis of glioma.

Cross-Strand Interaction, Central Bending, and Sequence Pattern Act as Biomodulators of Simplified ß-Hairpin Antimicrobial Amphiphiles.

Novel antimicrobial peptides (AMPs) have revolutionarily evolved into formidable candidates for antibiotic substitute materials against pathogenic infections. However, cost, lability, disorderly sequences, systemic toxicology, and biological profiles have plagued the perennial search. Here, a progressive ß-hairpin solution with the simplest formulation is implanted into an AMP-based therapeutic strategy to systematically reveal the complex balance between function and toxicity of structural moieties, including cationicity, hydrophobicity, cross-strand interactions, center bending, and sequence pattern. Comprehensive implementation of structural identification, ten microorganisms, eleven in vitro barriers, four mammalian cells, and a diversified membrane operation setup led to the emergence of ß-hairpin prototypes from a 24-member library. Lead amphiphiles, WKF-PG and WRF-NG, can tackle bacterial infection through direct antimicrobial efficacy and potential inflammation-limiting capabilities, such as an Escherichia coli challenge in a mouse peritonitis-sepsis model, without observed toxicity after systemic administration. Their optimal states with dissimilar modulators and the unavailable drug resistance related to membrane lytic mechanisms, also provide an usher for renewed innovation among ß-sheet peptide-based antimicrobial biomaterials.

Discovering dynamic task-modulated functional networks with specific spectral modes using MEG.

Efficient neuronal communication between brain regions through oscillatory synchronization at certain frequencies is necessary for cognition. Such synchronized networks are transient and dynamic, established on the timescale of milliseconds in order to support ongoing cognitive operations. However, few studies characterizing dynamic electrophysiological brain networks have simultaneously accounted for temporal non-stationarity, spectral structure, and spatial properties. Here, we propose an analysis framework for characterizing the large-scale phase-coupling network dynamics during task performance using magnetoencephalography (MEG). We exploit the high spatiotemporal resolution of MEG to measure time-frequency dynamics of connectivity between parcellated brain regions, yielding data in tensor format. We then use a tensor component analysis (TCA)-based procedure to identify the spatio-temporal-spectral modes of covariation among separate regions in the human brain. We validate our pipeline using MEG data recorded during a hand movement task, extracting a transient motor network with beta-dominant spectral mode, which is significantly modulated by the movement task. Next, we apply the proposed pipeline to explore brain networks that support cognitive operations during a working memory task. The derived results demonstrate the temporal formation and dissolution of multiple phase-coupled networks with specific spectral modes, which are associated with face recognition, vision, and movement. The proposed pipeline can characterize the spectro-temporal dynamics of functional connectivity in the brain on the subsecond timescale, commensurate with that of cognitive performance.

Sustaining Attention for a Prolonged Duration Affects Dynamic Organizations of Frequency-Specific Functional Connectivity.

Sustained attention encompasses a cascade of fundamental functions. The human ability to implement a sustained attention task is supported by brain networks that dynamically formed and dissolved through oscillatory synchronization. The decrement of vigilance induced by prolonged task engagement affects sustained attention. However, little is known about which stage or combinations are affected by vigilance decrement. Here, we applied an analysis framework composed of weighted phase lag index (wPLI) and tensor component analysis (TCA) to an EEG dataset collected during 80 min sustained attention task to examine the electrophysiological basis of such effect. We aimed to characterize the phase-coupling networks to untangle different phases involved in sustained attention and study how they are modulated by vigilance decrement. We computed the time-frequency domain wPLI from each block and subject and constructed a fourth-order tensor, containing the time, frequency, functional connectivity (FC), and blocks × subjects. This tensor was subjected to the TCA to identify the interacted and low-dimensional components representing the frequency-specific dynamic FC (fdFC). We extracted four types of neuromakers during a sustained attention task, namely the pre-stimulus alpha right-lateralized parieto-occipital FC, the post-stimulus theta fronto-parieto-occipital FC, delta fronto-parieto-occipital FC, and beta right/left sensorimotor FCs. All these fdFCs were impaired by vigilance decrement. These fdFCs, except for the beta left sensorimotor network, were restored by rewards, although the restoration by reward in the beta right sensorimotor network was transient. These findings provide implications for dissociable effects of vigilance decrement on sustained attention by utilizing the tensor-based framework.

Exploring Frequency-Dependent Brain Networks from Ongoing EEG Using Spatial ICA During Music Listening.

Recently, exploring brain activity based on functional networks during naturalistic stimuli especially music and video represents an attractive challenge because of the low signal-to-noise ratio in collected brain data. Although most efforts focusing on exploring the listening brain have been made through functional magnetic resonance imaging (fMRI), sensor-level electro- or magnetoencephalography (EEG/MEG) technique, little is known about how neural rhythms are involved in the brain network activity under naturalistic stimuli. This study exploited cortical oscillations through analysis of ongoing EEG and musical feature during freely listening to music. We used a data-driven method that combined music information retrieval with spatial Fourier Independent Components Analysis (spatial Fourier-ICA) to probe the interplay between the spatial profiles and the spectral patterns of the brain network emerging from music listening. Correlation analysis was performed between time courses of brain networks extracted from EEG data and musical feature time series extracted from music stimuli to derive the musical feature related oscillatory patterns in the listening brain. We found brain networks of musical feature processing were frequency-dependent. Musical feature time series, especially fluctuation centroid and key feature, were associated with an increased beta activation in the bilateral superior temporal gyrus. An increased alpha oscillation in the bilateral occipital cortex emerged during music listening, which was consistent with alpha functional suppression hypothesis in task-irrelevant regions. We also observed an increased delta-beta oscillatory activity in the prefrontal cortex associated with musical feature processing. In addition to these findings, the proposed method seems valuable for characterizing the large-scale frequency-dependent brain activity engaged in musical feature processing.

ERRα negatively regulates type I interferon induction by inhibiting TBK1-IRF3 interaction.

Estrogen-related receptor α (ERRα) is a member of the nuclear receptor superfamily controlling energy homeostasis; however, its precise role in regulating antiviral innate immunity remains to be clarified. Here, we showed that ERRα deficiency conferred resistance to viral infection both in vivo and in vitro. Mechanistically, ERRα inhibited the production of type-I interferon (IFN-I) and the expression of multiple interferon-stimulated genes (ISGs). Furthermore, we found that viral infection induced TBK1-dependent ERRα stabilization, which in turn associated with TBK1 and IRF3 to impede the formation of TBK1-IRF3, IRF3 phosphorylation, IRF3 dimerization, and the DNA binding affinity of IRF3. The effect of ERRα on IFN-I production was independent of its transcriptional activity and PCG-1α. Notably, ERRα chemical inhibitor XCT790 has broad antiviral potency. This work not only identifies ERRα as a critical negative regulator of antiviral signaling, but also provides a potential target for future antiviral therapy.

Decreased expression of HDAC8 indicates poor prognosis in patients with intrahepatic cholangiocarcinoma.

BACKGROUND: Intrahepatic cholangiocarcinoma (ICC) is a highly malignant primary tumor in the liver, and the rates of incidence and mortality are rapidly increasing globally. Histone deacetylase 8 (HDAC8) is a transcriptional regulator and is associated with tumorigenesis of several tumor types. This study aimed to evaluate the correlation between HDAC8 expression and clinicopathological parameters in ICC patients. METHODS: ICC tissues and corresponding nonmalignant bile duct tissues were obtained from 60 patients. HDAC8 and Ki-67 expression were evaluated by immunohistochemistry staining. HDAC8 expression and the clinicopathological features and prognosis of the patients were analyzed. The mRNA level of HDAC8 in ICC was further analyzed using data from The Cancer Genome Atlas (TCGA). RESULTS: The expression of HDAC8 were lower in ICC tissues (39/60, 65%) than in the corresponding nonmalignant bile duct tissues (54/60, 90%) (P = 0.001). Low HDAC8 expression in ICC was significantly associated with lymph node metastases (47.6% vs. 17.9%, P = 0.015). In addition, the positive cells rate of HDAC8 was statistically and negatively correlated with the Ki-67 index in ICC lesions (r = -0.7660, P < 0.001). Importantly, the overall survival rate and recurrence-free survival rate in ICC patients with low HDAC8 expression were lower than those with high HDAC8 expression (P = 0.008 and P = 0.011, respectively). CONCLUSIONS: Decreased HDAC8 expression in ICC is related to poor prognosis, and HDAC8 may be an independent prognostic indicator of ICC patients after curative resection.

Circulating monocytes accelerate acute liver failure by IL-6 secretion in monkey.

Acute liver failure (ALF) is associated with high mortality, and a poor understanding of the underlying pathophysiology has resulted in a lack of effective treatments so far. Here, using an amatoxin-induced rhesus monkey model of ALF, we panoramically revealed the cellular and molecular events that lead to the development of ALF. The challenged monkeys with toxins underwent a typical course of ALF including severe hepatic injury, systemic inflammation and eventual death. Adaptive immune was not noticeably disturbed throughout the progress of ALF. A systematic examination of serum factors and cytokines revealed that IL-6 increase was the most rapid and drastic. Interestingly, we found that IL-6 was mainly produced by circulating monocytes. Furthermore, ablation of monocyte-derived IL-6 in mice decreased liver injury and systemic inflammation following chemical injection. Our findings reveal a critical role of circulating monocytes in initiating and accelerating ALF, indicating a potential therapeutic target in clinical treatment for ALF.

Analysis of modulations of mental fatigue on intra-individual variability from single-trial event related potentials.

BACKGROUND: Intra-individual variability (IIV), a measure of variance within an individual's performance, has been demonstrated as metrics of brain responses for neural functionality. However, how mental fatigue modulates IIV remains unclear. Consequently, the development of robust mental fatigue detection methods at the single-trial level is challenging. NEW METHODS: Based on a long-duration flanker task EEG dataset, the modulations of mental fatigue on IIV were explored in terms of response time (RT) and trial-to-trial latency variations of event-related potentials (ERPs). Specifically, latency variations were quantified using residue iteration decomposition (RIDE) to reconstruct latency-corrected ERPs. We compared reconstructed ERPs with raw ERPs by means of temporal principal component analysis (PCA). Furthermore, a single-trial classification pipeline was developed to detect the changes of mental fatigue levels. RESULTS: We found an increased IIV in the RT metric in the fatigue state compared to the alert state. The same sequence of ERPs (N1, P2, N2, P3a, P3b, and slow wave, or SW) was separated from both raw and reconstructed ERPs using PCA, whereas differences between raw and reconstructed ERPs in explained variances for separated ERPs were found owing to IIV. Particularly, a stronger N2 was detected in the fatigue than alert state after RIDE. The single-trial fatigue detection pipeline yielded an acceptable accuracy of 73.3%. COMPARISON WITH EXISTING METHODS: The IIV has been linked to aging and brain disorders, and as an extension, our finding demonstrates IIV as an efficient indicator of mental fatigue. CONCLUSIONS: This study reveals significant modulations of mental fatigue on IIV at the behavioral and neural levels and establishes a robust mental fatigue detection pipeline.

SPLiT: Single Portrait Lighting Estimation via a Tetrad of Face Intrinsics.

This paper proposes a novel pipeline to estimate a non-parametric environment map with high dynamic range from a single human face image. Lighting-independent and -dependent intrinsic images of the face are first estimated separately in a cascaded network. The influence of face geometry on the two lighting-dependent intrinsics, diffuse shading and specular reflection, are further eliminated by distributing the intrinsics pixel-wise onto spherical representations using the surface normal as indices. This results in two representations simulating images of a diffuse sphere and a glossy sphere under the input scene lighting. Taking into account the distinctive nature of light sources and ambient terms, we further introduce a two-stage lighting estimator to predict both accurate and realistic lighting from these two representations. Our model is trained supervisedly on a large-scale and high-quality synthetic face image dataset. We demonstrate that our method allows accurate and detailed lighting estimation and intrinsic decomposition, outperforming state-of-the-art methods both qualitatively and quantitatively on real face images.

Facile synthesis of a hydrazone-based zinc(ii) complex for ferroptosis-augmented sonodynamic therapy.

Sonodynamic therapy (SDT), as a novel non-invasive cancer treatment modality derived from photodynamic therapy (PDT), has drawn much attention due to its unique advantages for the treatment of deep tumors. Zinc-based complexes have shown great clinical prospect in PDT due to their excellent photodynamic activity and biosafety. However, their application in SDT has lagged seriously behind. Exploring efficient zinc-based complexes as sono-sensitizers remains an appealing but significantly challenging task. Herein, we develop a hydrazone ligand-based zinc complex (ZnAMTC) for SDT of tumors in vitro and in vivo. ZnAMTC was facilely synthesized via a two-step reaction from low-cost raw materials without tedious purification. It shows negligible dark toxicity and can produce singlet oxygen (1O2) under ultrasound (US) irradiation, exhibiting high sono-cytotoxicity to various cancer cells. Mechanism studies show that ZnAMTC can effectively reduce the levels of glutathione (GSH) and glutathione peroxidase 4 (GPX4) under US irradiation and later cause ferroptosis of cancer cells. In vivo studies further demonstrate that ZnAMTC exhibits efficient tumor growth inhibition under US irradiation and has good biosafety. This work provides useful insights into the design of first-row transition metal complexes for SDT application.