Sustainable lithium extraction enabled by responsive metal-organic frameworks with ion-sieving adsorption effects.

Metal-organic frameworks (MOFs) are superior ion adsorbents for selectively capturing toxic ions from water. Nevertheless, they have rarely been reported to have lithium selectivity over divalent cations due to the well-known flexibility of MOF framework and the similar physiochemical properties of Li+ and Mg2+. Herein, we report an ion-sieving adsorption approach to design sunlight-regenerable lithium adsorbents by subnanoporous MOFs for efficient lithium extraction. By integrating the ion-sieving agent of MOFs with light-responsive adsorption sites of polyspiropyran (PSP), the ion-sieving adsorption behaviors of PSP-MOFs with 6.0, 8.5, and 10.0 Å windows are inversely proportional to their pore size. The synthesized PSP-UiO-66 with a narrowest window size of 6.0 Å shows high LiCl adsorption capacity up to 10.17 mmol g-1 and good Li+/Mg2+ selectivity of 5.8 to 29 in synthetic brines with Mg/Li ratio of 1 to 0.1. It could be quickly regenerated by sunlight irradiation in 6 min with excellent cycling performance of 99% after five cycles. This work sheds light on designing selective adsorbents using responsive subnanoporous materials for environmentally friendly and energy-efficient ion separation and purification.

Computationally inferred cell-type specific epigenome-wide DNA methylation analysis unveils distinct methylation patterns among immune cells for HIV infection in three cohorts.

BACKGROUND: Epigenome-wide association studies (EWAS) have identified CpG sites associated with HIV infection in blood cells in bulk, which offer limited knowledge of cell-type specific methylation patterns associated with HIV infection. In this study, we aim to identify differentially methylated CpG sites for HIV infection in immune cell types: CD4+ T-cells, CD8+ T-cells, B cells, Natural Killer (NK) cells, and monocytes. METHODS: Applying a computational deconvolution method, we performed a cell-type based EWAS for HIV infection in three independent cohorts (Ntotal = 1,382). DNA methylation in blood or in peripheral blood mononuclear cells (PBMCs) was profiled by an array-based method and then deconvoluted by Tensor Composition Analysis (TCA). The TCA-computed CpG methylation in each cell type was first benchmarked by bisulfite DNA methylation capture sequencing in a subset of the samples. Cell-type EWAS of HIV infection was performed in each cohort separately and a meta-EWAS was conducted followed by gene set enrichment analysis. RESULTS: The meta-analysis unveiled a total of 2,021 cell-type unique significant CpG sites for five inferred cell types. Among these inferred cell-type unique CpG sites, the concordance rate in the three cohorts ranged from 96% to 100% in each cell type. Cell-type level meta-EWAS unveiled distinct patterns of HIV-associated differential CpG methylation, where 74% of CpG sites were unique to individual cell types (false discovery rate, FDR <0.05). CD4+ T-cells had the largest number of unique HIV-associated CpG sites (N = 1,624) compared to any other cell type. Genes harboring significant CpG sites are involved in immunity and HIV pathogenesis (e.g. CD4+ T-cells: NLRC5, CX3CR1, B cells: IFI44L, NK cells: IL12R, monocytes: IRF7), and in oncogenesis (e.g. CD4+ T-cells: BCL family, PRDM16, monocytes: PRDM16, PDCD1LG2). HIV-associated CpG sites were enriched among genes involved in HIV pathogenesis and oncogenesis that were enriched among interferon-α and -γ, TNF-α, inflammatory response, and apoptotic pathways. CONCLUSION: Our findings uncovered computationally inferred cell-type specific modifications in the host epigenome for people with HIV that contribute to the growing body of evidence regarding HIV pathogenesis.

Arabidopsis EXECUTER1 interacts with WRKY transcription factors to mediate plastid-to-nucleus singlet oxygen signaling.

Chloroplasts produce singlet oxygen (1O2), which causes changes in nuclear gene expression through plastid-to-nucleus retrograde signaling to increase plant fitness. However, the identity of this 1O2-triggered pathway remains unclear. Here, we identify mutations in GENOMES UNCOUPLED4 (GUN4) and GUN5 as suppressors of phytochrome-interacting factor1 (pif1) pif3 in regulating the photo-oxidative response in Arabidopsis thaliana. GUN4 and GUN5 specifically interact with EXECUTER1 (EX1) and EX2 in plastids, and this interaction is alleviated by treatment with Rose Bengal (RB) or white light. Impaired expression of GUN4, GUN5, EX1, or EX2 leads to insensitivity to excess light and overexpression of EX1 triggers photo-oxidative responses. Strikingly, upon light irradiation or RB treatment, EX1 transiently accumulates in the nucleus and the nuclear fraction of EX1 shows a similar molecular weight as the plastid-located protein. Point mutagenesis analysis indicated that nuclear localization of EX1 is required for its function. EX1 acts as a transcriptional co-activator and interacts with the transcription factors WRKY18 and WRKY40 to promote the expression of 1O2-responsive genes. This study suggests that EX1 may act in plastid-to-nucleus signaling and establishes a 1O2-triggered retrograde signaling pathway that allows plants adapt to changing light environments during chloroplast development.

Porcine deltacoronavirus nsp5 antagonizes type I interferon signaling by cleaving IFIT3.

Porcine deltacoronavirus (PDCoV) has caused enormous economic losses to the global pig industry. However, the immune escape mechanism of PDCoV remains to be fully clarified. Transcriptomic analysis revealed a high abundance of interferon (IFN)-induced protein with tetratricopeptide repeats 3 (IFIT3) transcripts after PDCoV infection, which initially implied a correlation between IFIT3 and PDCoV. Further studies showed that PDCoV nsp5 could antagonize the host type I interferon signaling pathway by cleaving IFIT3. We demonstrated that PDCoV nsp5 cleaved porcine IFIT3 (pIFIT3) at Gln-406. Similar cleavage of endogenous IFIT3 has also been observed in PDCoV-infected cells. The pIFIT3-Q406A mutant was resistant to nsp5-mediated cleavage and exhibited a greater ability to inhibit PDCoV infection than wild-type pIFIT3. Furthermore, we found that cleavage of IFIT3 is a common characteristic of nsp5 proteins of human coronaviruses, albeit not alphacoronavirus. This finding suggests that the cleavage of IFIT3 is an important mechanism by which PDCoV nsp5 antagonizes IFN signaling. Our study provides new insights into the mechanisms by which PDCoV antagonizes the host innate immune response.IMPORTANCEPorcine deltacoronavirus (PDCoV) is a potential emerging zoonotic pathogen, and studies on the prevalence and pathogenesis of PDCoV are ongoing. The main protease (nsp5) of PDCoV provides an excellent target for antivirals due to its essential and conserved function in the viral replication cycle. Previous studies have revealed that nsp5 of PDCoV antagonizes type I interferon (IFN) production by targeting the interferon-stimulated genes. Here, we provide the first demonstration that nsp5 of PDCoV antagonizes IFN signaling by cleaving IFIT3, which affects the IFN response after PDCoV infection. Our findings reveal that PDCoV nsp5 is an important interferon antagonist and enhance the understanding of immune evasion by deltacoronaviruses.

DeepSTF: predicting transcription factor binding sites by interpretable deep neural networks combining sequence and shape.

Precise targeting of transcription factor binding sites (TFBSs) is essential to comprehending transcriptional regulatory processes and investigating cellular function. Although several deep learning algorithms have been created to predict TFBSs, the models' intrinsic mechanisms and prediction results are difficult to explain. There is still room for improvement in prediction performance. We present DeepSTF, a unique deep-learning architecture for predicting TFBSs by integrating DNA sequence and shape profiles. We use the improved transformer encoder structure for the first time in the TFBSs prediction approach. DeepSTF extracts DNA higher-order sequence features using stacked convolutional neural networks (CNNs), whereas rich DNA shape profiles are extracted by combining improved transformer encoder structure and bidirectional long short-term memory (Bi-LSTM), and, finally, the derived higher-order sequence features and representative shape profiles are integrated into the channel dimension to achieve accurate TFBSs prediction. Experiments on 165 ENCODE chromatin immunoprecipitation sequencing (ChIP-seq) datasets show that DeepSTF considerably outperforms several state-of-the-art algorithms in predicting TFBSs, and we explain the usefulness of the transformer encoder structure and the combined strategy using sequence features and shape profiles in capturing multiple dependencies and learning essential features. In addition, this paper examines the significance of DNA shape features predicting TFBSs. The source code of DeepSTF is available at https://github.com/YuBinLab-QUST/DeepSTF/.

Trained immunity induced by high-salt diet impedes stroke recovery.

A high-salt diet (HSD) elicits sustained sterile inflammation and worsens tissue injury. However, how this occurs after stroke, a leading cause of morbidity and mortality, remains unknown. Here, we report that HSD impairs long-term brain recovery after intracerebral hemorrhage, a severe form of stroke, despite salt withdrawal prior to the injury. Mechanistically, HSD induces innate immune priming and training in hematopoietic stem and progenitor cells (HSPCs) by downregulation of NR4a family and mitochondrial oxidative phosphorylation. This training compromises alternative activation of monocyte-derived macrophages (MDMs) without altering the initial inflammatory responses of the stroke brain. Healthy mice transplanted with bone marrow from HSD-fed mice retain signatures of reduced MDM reparative functions, further confirming a persistent form of innate immune memory that originates in the bone marrow. Loss of NR4a1 in macrophages recapitulates HSD-induced negative impacts on stroke outcomes while gain of NR4a1 enables stroke recovery in HSD animals. Together, we provide the first evidence that links HSD-induced innate immune memory to the acquisition of persistent dysregulated inflammatory responses and unveils NR4a1 as a potential therapeutic target.

Genome-wide direct quantification of in vivo mutagenesis using high-accuracy paired-end and complementary consensus sequencing.

Error-corrected next-generation sequencing (ecNGS) is an emerging technology for accurately measuring somatic mutations. Here, we report paired-end and complementary consensus sequencing (PECC-Seq), a high-accuracy ecNGS approach for genome-wide somatic mutation detection. We characterize a novel 2-aminoimidazolone lesion besides 7,8-dihydro-8-oxoguanine and the resulting end-repair artifacts originating from NGS library preparation that obscure the sequencing accuracy of NGS. We modify library preparation protocol for the enzymatic removal of end-repair artifacts and improve the accuracy of our previously developed duplex consensus sequencing method. Optimized PECC-Seq shows an error rate of <5 × 10-8 with consensus bases compressed from approximately 25 Gb of raw sequencing data, enabling the accurate detection of low-abundance somatic mutations. We apply PECC-Seq to the quantification of in vivo mutagenesis. Compared with the classic gpt gene mutation assay using gpt delta transgenic mice, PECC-Seq exhibits high sensitivity in quantitatively measuring dose-dependent mutagenesis induced by Aristolochic acid I (AAI). Moreover, PECC-Seq specifically characterizes the distinct genome-wide mutational signatures of AAI, Benzo[a]pyrene, N-Nitroso-N-ethylurea and N-nitrosodiethylamine and reveals the mutational signature of Quinoline in common mouse models. Overall, our findings demonstrate that high-accuracy PECC-Seq is a promising tool for genome-wide somatic mutagenesis quantification and for in vivo mutagenicity testing.

Protective anti-gB neutralizing antibodies targeting two vulnerable sites for EBV-cell membrane fusion.

Epstein-Barr virus (EBV) infects more than 90% of the world's adult population and accounts for a significant cancer burden of epithelial and B cell origins. Glycoprotein B (gB) is the primary fusogen essential for EBV entry into host cells. Here, we isolated two EBV gB-specific neutralizing antibodies, 3A3 and 3A5; both effectively neutralized the dual-tropic EBV infection of B and epithelial cells. In humanized mice, both antibodies showed effective protection from EBV-induced lymphoproliferative disorders. Cryoelectron microscopy analyses identified that 3A3 and 3A5 bind to nonoverlapping sites on domains D-II and D-IV, respectively. Structure-based mutagenesis revealed that 3A3 and 3A5 inhibit membrane fusion through different mechanisms involving the interference with gB-cell interaction and gB activation. Importantly, the 3A3 and 3A5 epitopes are major targets of protective gB-specific neutralizing antibodies elicited by natural EBV infection in humans, providing potential targets for antiviral therapies and vaccines.

Reverse Mechanotransduction: Driving Chromatin Compaction to Decompaction Increases Cell Adhesion Strength and Contractility.

Mechanical extracellular signals elicit chromatin remodeling via the mechanotransduction pathway, thus determining cellular function. However, the reverse pathway is an open question: does chromatin remodeling shape cells, regulating their adhesion strength? With fluidic force microscopy, we can directly measure the adhesion strength of epithelial cells by driving chromatin compaction to decompaction with chromatin remodelers. We observe that chromatin compaction, induced by performing histone acetyltransferase inhibition or ATP depletion, leads to a reduction in nuclear volume, disrupting actin cytoskeleton and focal adhesion assembly, and ultimately decreases in cell adhesion strength and traction force. Conversely, when chromatin decompaction is drived by removing the remodelers, cells recover their original shape, adhesion strength, and traction force. During chromatin decompaction, cells use depolymerized proteins to restore focal adhesion assemblies rather than neo-synthesized cytoskeletal proteins. We conclude that chromatin remodeling shapes cells, regulating adhesion strength through a reverse mechanotransduction pathway from the nucleus to the cell surface involving RhoA activation.

Disruption of CerS6-mediated sphingolipid metabolism by FTO deficiency aggravates ulcerative colitis.

BACKGROUND AND AIMS: Deregulation of RNA N6-methyladenosine (m6A) modification in intestinal epithelial cells (IECs) influences intestinal immune cells and leads to intestinal inflammation. We studied the function of fat mass-and obesity-associated protein (FTO), one of the m6A demethylases, in patients with ulcerative colitis (UC). METHODS: We analysed colon tissues of Ftoflox/flox; Villin-cre mice and their Ftoflox/flox littermates with dextran sulfate sodium (DSS) using real-time PCR and 16s rRNA sequencing. RNA and methylated RNA immunoprecipitation sequencing were used to analyse immunocytes and IECs. Macrophages were treated with conditioned medium of FTO-knockdown MODE-K cells or sphingosine-1-phosphate (S1P) and analysed for gene expression. Liquid chromatograph mass spectrometry identified C16-ceramide. RESULTS: FTO downregulation was identified in our in-house cohort and external cohorts of UC patients. Dysbiosis of gut microbiota, increased infiltration of proinflammatory macrophages, and enhanced differentiation of Th17 cells were observed in Ftoflox/flox;Villin-cre mice under DSS treatment. FTO deficiency resulted in an increase in m6A modification and a decrease in mRNA stability of CerS6, the gene encoding ceramide synthetase, leading to the downregulation of CerS6 and the accumulation of S1P in IECs. Subsequentially, the secretion of S1P by IECs triggered proinflammatory macrophages to secrete serum amyloid A protein 1/3, ultimately inducing Th17 cell differentiation. In addition, through bioinformatic analysis and experimental validation, we identified UC patients with lower FTO expression might respond better to vedolizumab treatment. CONCLUSIONS: FTO downregulation promoted UC by decreasing CerS6 expression, leading to increased S1P accumulation in IECs and aggravating colitis via m6A-dependent mechanisms. Lower FTO expression in UC patients may enhance their response to vedolizumab treatment.

Proteomic Analysis of Idiopathic Nephrotic Syndrome Triggered by Primary Podocytopathies in Adults: Regulatory Mechanisms and Diagnostic Implications.

Idiopathic nephrotic syndrome (NS) is a heterogeneous group of glomerular disorders which includes two major phenotypes: minimal change disease (MCD) and focal segmental glomerulosclerosis (FSGS). MCD and FSGS are classic types of primary podocytopathies. We aimed to explore the molecular mechanisms in NS triggered by primary podocytopathies and evaluate diagnostic value of the selected proteomic signatures by analyzing blood proteome profiling. Totally, we recruited 90 participants in two cohorts. The first cohort was analyzed using label-free quantitative (LFQ) proteomics to discover differential expressed proteins and identify enriched biological process in NS which were further studied in relation to clinical markers of kidney injury. The second cohort was analyzed using parallel reaction monitoring-based quantitative proteomics to verify the data of LFQ proteomics and assess the diagnostic performance of the selected proteins using receiver-operating characteristic curve analysis. Several biological processes (such as immune response, cell adhesion, and response to hypoxia) were found to be associated with kidney injury during MCD and FSGS. Moreover, three proteins (CSF1, APOC3, and LDLR) had over 90% sensitivity and specificity in detecting adult NS triggered by primary podocytopathies. The identified biological processes may play a crucial role in MCD and FSGS pathogenesis. The three blood protein markers are promising for diagnosing adult NS triggered by primary podocytopathies.

Iron-Catalyzed C(sp3)-C(sp3) Coupling to Construct Quaternary Carbon Centers.

The construction of quaternary carbon centers via C-C coupling protocols remains challenging. The coupling of tertiary C(sp3) with secondary or tertiary C(sp3) counterparts has been hindered by pronounced steric clashes and many side reactions. Herein, we have successfully developed a type of bisphosphine ligand iron complex-catalyzed coupling reactions of tertiary alkyl halides with secondary alkyl zinc reagents and efficiently realized the coupling reaction between tertiary C(sp3) and secondary C(sp3) with high selectivity for the initial instance, which provided an efficient method for the construction of quaternary carbon centers with high steric hindrance. The combination of an iron catalyst and directing group of the substrate makes the great challenging transformation possible.

Direct Visualization of Molecular Stacking in Quasi-2D Hexagonal Ice.

Understanding ice nucleation and growth is of great interest to researchers due to its importance in the biological, cryopreservation, and environmental fields. However, microstructural investigations of ice on the molecular scale are still lacking. In this paper, a simple method is proposed to prepare quasi-2-dimensional ice Ih films, which have been characterized via cryogenic transmission electron microscope. The intersecting stacking faults of basal (BSF) and prismatic (PSF) types have been directly visualized and resolved with a notable first-time report of PSF in ice Ih. Moreover, the possible growth pathways of BSF, namely, the Ic phase, were elucidated by the theoretical calculations and the chair conformation of H2O molecules. This study offers valuable insights that can enhance researchers' understanding of the growth kinetics of crystalline ice.

Enhancing pathological complete response prediction in breast cancer: the role of dynamic characterization of DCE-MRI and its association with tumor heterogeneity.

BACKGROUND: Early prediction of pathological complete response (pCR) is important for deciding appropriate treatment strategies for patients. In this study, we aimed to quantify the dynamic characteristics of dynamic contrast-enhanced magnetic resonance images (DCE-MRI) and investigate its value to improve pCR prediction as well as its association with tumor heterogeneity in breast cancer patients. METHODS: The DCE-MRI, clinicopathologic record, and full transcriptomic data of 785 breast cancer patients receiving neoadjuvant chemotherapy were retrospectively included from a public dataset. Dynamic features of DCE-MRI were computed from extracted phase-varying radiomic feature series using 22 CAnonical Time-sereis CHaracteristics. Dynamic model and radiomic model were developed by logistic regression using dynamic features and traditional radiomic features respectively. Various combined models with clinical factors were also developed to find the optimal combination and the significance of each components was evaluated. All the models were evaluated in independent test set in terms of area under receiver operating characteristic curve (AUC). To explore the potential underlying biological mechanisms, radiogenomic analysis was implemented on patient subgroups stratified by dynamic model to identify differentially expressed genes (DEGs) and enriched pathways. RESULTS: A 10-feature dynamic model and a 4-feature radiomic model were developed (AUC = 0.688, 95%CI: 0.635-0.741 and AUC = 0.650, 95%CI: 0.595-0.705) and tested (AUC = 0.686, 95%CI: 0.594-0.778 and AUC = 0.626, 95%CI: 0.529-0.722), with the dynamic model showing slightly higher AUC (train p = 0.181, test p = 0.222). The combined model of clinical, radiomic, and dynamic achieved the highest AUC in pCR prediction (train: 0.769, 95%CI: 0.722-0.816 and test: 0.762, 95%CI: 0.679-0.845). Compared with clinical-radiomic combined model (train AUC = 0.716, 95%CI: 0.665-0.767 and test AUC = 0.695, 95%CI: 0.656-0.714), adding the dynamic component brought significant improvement in model performance (train p < 0.001 and test p = 0.005). Radiogenomic analysis identified 297 DEGs, including CXCL9, CCL18, and HLA-DPB1 which are known to be associated with breast cancer prognosis or angiogenesis. Gene set enrichment analysis further revealed enrichment of gene ontology terms and pathways related to immune system. CONCLUSION: Dynamic characteristics of DCE-MRI were quantified and used to develop dynamic model for improving pCR prediction in breast cancer patients. The dynamic model was associated with tumor heterogeniety in prognostic-related gene expression and immune-related pathways.

Detection of Helicobacter pylori Infection in Human Gastric Fluid Through Surface-Enhanced Raman Spectroscopy Coupled With Machine Learning Algorithms.

Diagnostic methods for Helicobacter pylori infection include, but are not limited to, urea breath test, serum antibody test, fecal antigen test, and rapid urease test. However, these methods suffer drawbacks such as low accuracy, high false-positive rate, complex operations, invasiveness, etc. Therefore, there is a need to develop simple, rapid, and noninvasive detection methods for H. pylori diagnosis. In this study, we propose a novel technique for accurately detecting H. pylori infection through machine learning analysis of surface-enhanced Raman scattering (SERS) spectra of gastric fluid samples that were noninvasively collected from human stomachs via the string test. One hundred participants were recruited to collect gastric fluid samples noninvasively. Therefore, 12,000 SERS spectra (n = 120 spectra/participant) were generated for building machine learning models evaluated by standard metrics in model performance assessment. According to the results, the Light Gradient Boosting Machine algorithm exhibited the best prediction capacity and time efficiency (accuracy = 99.54% and time = 2.61 seconds). Moreover, the Light Gradient Boosting Machine model was blindly tested on 2,000 SERS spectra collected from 100 participants with unknown H. pylori infection status, achieving a prediction accuracy of 82.15% compared with qPCR results. This novel technique is simple and rapid in diagnosing H. pylori infection, potentially complementing current H. pylori diagnostic methods.

Impacted spike frequency adaptation associated with reduction of KCNQ2/3 exacerbates seizure activity in temporal lobe epilepsy.

Numerous epilepsy-related genes have been identified in recent decades by unbiased genome-wide screens. However, the available druggable targets for temporal lobe epilepsy (TLE) remain limited. Furthermore, a substantial pool of candidate genes potentially applicable to TLE therapy awaits further validation. In this study, we reveal the significant role of KCNQ2 and KCNQ3, two M-type potassium channel genes, in the onset of seizures in TLE. Our investigation began with a quantitative analysis of two publicly available TLE patient databases to establish a correlation between seizure onset and the downregulated expression of KCNQ2/3. We then replicated these pathological changes in a pilocarpine seizure mouse model and observed a decrease in spike frequency adaptation due to the affected M-currents in dentate gyrus granule neurons. In addition, we performed a small-scale simulation of the dentate gyrus network and confirmed that the impaired spike frequency adaptation of granule cells facilitated epileptiform activity throughout the network. This, in turn, resulted in prolonged seizure duration and reduced interictal intervals. Our findings shed light on an underlying mechanism contributing to ictogenesis in the TLE hippocampus and suggest a promising target for the development of antiepileptic drugs.

Multi-scale brain attributes contribute to the distribution of diffuse glioma subtypes.

Gliomas are primary brain tumors and are among the most malignant types. Adult-type diffuse gliomas can be classified based on their histological and molecular signatures as IDH-wildtype glioblastoma, IDH-mutant astrocytoma, and IDH-mutant and 1p/19q-codeleted oligodendroglioma. Recent studies have shown that each subtype of glioma has its own specific distribution pattern. However, the mechanisms underlying the specific distributions of glioma subtypes are not entirely clear despite partial explanations such as cell origin. To investigate the impact of multi-scale brain attributes on glioma distribution, we constructed cumulative frequency maps for diffuse glioma subtypes based on T1w structural images and evaluated the spatial correlation between tumor frequency and diverse brain attributes, including postmortem gene expression, functional connectivity metrics, cerebral perfusion, glucose metabolism, and neurotransmitter signaling. Regression models were constructed to evaluate the contribution of these factors to the anatomic distribution of different glioma subtypes. Our findings revealed that the three different subtypes of gliomas had distinct distribution patterns, showing spatial preferences toward different brain environmental attributes. Glioblastomas were especially likely to occur in regions enriched with synapse-related pathways and diverse neurotransmitter receptors. Astrocytomas and oligodendrogliomas preferentially occurred in areas enriched with genes associated with neutrophil-mediated immune responses. The functional network characteristics and neurotransmitter distribution also contributed to oligodendroglioma distribution. Our results suggest that different brain transcriptomic, neurotransmitter, and connectomic attributes are the factors that determine the specific distributions of glioma subtypes. These findings highlight the importance of bridging diverse scales of biological organization when studying neurological dysfunction.

Changes in decision-making function in patients with subacute mild traumatic brain injury.

Although awareness regarding patients with mild traumatic brain injury has increased, they have not received sufficient attention in clinics; hence, many patients still experience only partial recovery. Deficits in decision-making function are frequently experienced by these patients. Accurate identification of impairment in the early stages after brain injury is particularly crucial for timely intervention and the prevention of long-term cognitive consequences. Therefore, we investigated the changes in decision-making ability under tasks of ambiguity and risk in patients with mild traumatic brain injury with a rule-based neuropsychological paradigm. In this study, patients (n = 39) and matched healthy controls (n = 38) completed general neuropsychological background tests and decision-making tasks (Iowa Gambling Task and Game of Dice Task). We found that patients had extensive cognitive impairment in general attention, memory and information processing speed in the subacute phase, and confirmed that patients had different degrees of impairment in decision-making abilities under ambiguity and risk. Furthermore, the decline of memory and executive function may be related to decision-making dysfunction.

Multispectral 3D DNA Machine Combined with Multimodal Machine Learning for Noninvasive Precise Diagnosis of Bladder Cancer.

Extracellular vesicle (EV) molecular phenotyping offers enormous opportunities for cancer diagnostics. However, the majority of the associated studies adopted biomarker-based unimodal analysis to achieve cancer diagnosis, which has high false positives and low precision. Herein, we report a multimodal platform for the high-precision diagnosis of bladder cancer (BCa) through a multispectral 3D DNA machine in combination with a multimodal machine learning (ML) algorithm. The DNA machine was constructed using magnetic microparticles (MNPs) functionalized with aptamers that specifically identify the target of interest, i.e., five protein markers on bladder-cancer-derived urinary EVs (uEVs). The aptamers were hybridized with DNA-stabilized silver nanoclusters (DNA/AgNCs) and a G-quadruplex/hemin complex to form a sensing module. Such a DNA machine ensured multispectral detection of protein markers by fluorescence (FL), inductively coupled plasma mass spectrometry (ICP-MS), and UV-vis absorption (Abs). The obtained data sets then underwent uni- or multimodal ML for BCa diagnosis to compare the analytical performance. In this study, urine samples were obtained from our prospective cohort (n = 45). Our analytical results showed that the 3D DNA machine provided a detection limit of 9.2 × 103 particles mL-1 with a linear range of 4 × 104 to 5 × 107 particles mL-1 for uEVs. Moreover, the multimodal data fusion model exhibited an accuracy of 95.0%, a precision of 93.1%, and a recall rate of 93.2% on average, while those of the three types of unimodal models were no more than 91%. The elevated diagnosis precision by using the present fusion platform offers a perspective approach to diminishing the rate of misdiagnosis and overtreatment of BCa.

Hypersensitive MR Angiography for Diagnosis of Ischemic Stroke and Reperfusion Subarachnoid Hemorrhage.

Stroke is an acute injury of the central nervous system caused by the disorders of cerebral blood circulation, which has become one of the major causes of disability and death. Hemorrhage, particularly subarachnoid hemorrhage (SAH), is one of the poorest prognostic factors in stroke, which is related to the thrombolytic therapy, and has been considered very dangerous. In this context, the MR angiography with high sensitivity and resolution has been developed based on biocompatible paramagnetic ultrasmall NaGdF4 nanoprobes. Owing to the appropriate hydrodynamic diameter, the nanoprobe can be confined inside the blood vessels and it only extravasates at the vascular injury site when the bleeding occurs. Relying on this property, the three-dimensional (3D) anatomic structures of artery occlusion of stroke rat can be precisely visualized; reperfusion-related SAH has been successfully visualized and identified. Benefiting from the long blood half-life of the nanoprobe, the observation window of MR angiography can last for the whole period of reperfusion, thereby monitoring the probable SAH in real time during thrombolytic therapy. More importantly, through reconstruction of multiparametric MRI, the arterial occlusion, cerebral ischemic region, and SAH can be simultaneously visualized in vivo in a 3D manner for the first time. Therefore, the current study provides a novel approach for both noninvasive 3D vascular visualization and hemorrhage alert, which possesses great prospects for clinical translation.