Enhancement of motor functional recovery in thoracic spinal cord injury: voluntary wheel running versus forced treadmill exercise.

JOURNAL/nrgr/04.03/01300535-202503000-00028/figure1/v/2024-06-17T092413Z/r/image-tiff Spinal cord injury necessitates effective rehabilitation strategies, with exercise therapies showing promise in promoting recovery. This study investigated the impact of rehabilitation exercise on functional recovery and morphological changes following thoracic contusive spinal cord injury. After a 7-day recovery period after spinal cord injury, mice were assigned to either a trained group (10 weeks of voluntary running wheel or forced treadmill exercise) or an untrained group. Bi-weekly assessments revealed that the exercise-trained group, particularly the voluntary wheel exercise subgroup, displayed significantly improved locomotor recovery, more plasticity of dopaminergic and serotonin modulation compared with the untrained group. Additionally, exercise interventions led to gait pattern restoration and enhanced transcranial magnetic motor-evoked potentials. Despite consistent injury areas across groups, exercise training promoted terminal innervation of descending axons. In summary, voluntary wheel exercise shows promise for enhancing outcomes after thoracic contusive spinal cord injury, emphasizing the role of exercise modality in promoting recovery and morphological changes in spinal cord injuries. Our findings will influence future strategies for rehabilitation exercises, restoring functional movement after spinal cord injury.

AcornHRD: an HRD algorithm highly associated with anthracycline-based neoadjuvant chemotherapy in breast cancer in China.

PURPOSE: Our study aimed to develop and validate a homologous recombination deficiency (HRD) scoring algorithm in the Chinese breast cancer population. METHODS AND MATERIALS: Ninety-six in-house breast cancer (BC) samples and 6 HRD-positive standard cells were analyzed by whole-genome sequencing (WGS). Besides, 122 BCs from the TCGA database were down-sampled to ~ 1X WGS. We constructed an algorithm named AcornHRD for HRD score calculated based on WGS at low coverage as input data to estimate large-scale copy number alteration (LCNA) events on the genome. A clinical cohort of 50 BCs (15 cases carrying BRCA mutation) was used to assess the association between HRD status and anthracyclines-based neoadjuvant treatment outcomes. RESULTS: A 100-kb window was defined as the optimal size using 41 in-house cases and the TCGA dataset. HRD score high threshold was determined as HRD score ≥ 10 using 55 in-house BCs with BRCA mutation to achieve a 95% BRCA-positive agreement rate. Furthermore, the HRD status agreement rate of AcornHRD is 100%, while the ShallowHRD is 60% in standard cells. BRCA mutation was significantly associated with a high HRD score evaluated by AcornHRD and ShallowHRD (p = 0.008 and p = 0.003, respectively) in the TCGA dataset. However, AcornHRD showed a higher positive agreement rate than did the ShallowHRD algorithm (70% vs 60%). In addition, the BRCA-positive agreement rate of AcornHRD was superior to that of ShallowHRD (87% vs 13%) in the clinical cohort. Importantly, the high HRD score assessed by AcornHRD was significantly correlated with a residual cancer burden score of 0 or 1 (RCB0/1). Besides, the HRD-positive group was more likely to respond to anthracycline-based chemotherapy than the HRD-negative group (pCR [OR = 9.5, 95% CI 1.11-81.5, p = 0.040] and RCB0/1 [OR = 10.29, 95% CI 2.02-52.36, p = 0.005]). CONCLUSION: Using the AcornHRD algorithm evaluation, our analysis demonstrated the high performance of the LCNA genomic signature for HRD detection in breast cancers.

Tailoring soy protein/corn zein mixture by limited enzymatic hydrolysis to improve digestibility and functionality.

This study aimed to modify plant protein mixture to improve their functionality and digestibility by limited hydrolysis. Soy protein isolate and corn zein were mixed at the ratio of 5:1 (w/w), followed by limited hydrolysis using papain from 15 to 30 min. The structural characteristics, in vitro digestibility, and functional properties were evaluated. Also, DPPH radical scavenging activity was determined. The results indicated that the molecular weight of different modified samples was largely reduced by limited hydrolysis, and the proportion of random coil was significantly increased. Furthermore, the solubility, foaming, emulsifying and water-holding capacity of hydrolyzed protein mixture were significantly improved, which were close to those of whey protein isolate. In vitro digestibility after 30-min limited hydrolysis was remarkably elevated. In addition, the hydrolyzed protein mixture exhibited a higher antioxidant activity than those of untreated proteins. Overall, limited hydrolysis of protein mixture led to improved digestibility, functionality and antioxidant activity.

Zinc proteinate with moderate chelation strength enhances zinc absorption by up-regulating the expression of zinc and amino acid transporters in primary cultured duodenal epithelial cells of broiler embryos.

Recent study showed that zinc (Zn) and amino acid transporters may be involved in enhancing Zn absorption from Zn proteinate with moderate chelation strength (Zn-Prot M) in the duodenum of broilers. However, the specific mechanisms by which Zn-Prot M promotes the above Zn absorption are unknown. Therefore, in this study, three experiments were conducted to investigate specific and direct effects of Zn-Prot M and Zn sulfate (ZnS) on Zn absorption and expression of related transporters in primary duodenal epithelial cells of broiler embryos so as to preliminarily address possible mechanisms. In experiment 1, cells were treated with 100 µmol Zn/L as ZnS or Zn-Prot M for 20, 40, 60, 80, 100 or 120 min. Experiment 2 consisted of 3 sub-experiments. In experiment 2A, cells were treated with a Zn-unsupplemented basal medium (Control) or the basal medium supplemented with 100 or 200 µmol Zn/L as ZnS or Zn-Prot M for 60 min; in experiment 2B, cells were treated with a Zn-unsupplemented basal medium (Control) or the basal medium supplemented with 200 µmol Zn/L of as the ZnS or Zn-Prot M for 120 min; in experiment 2C, cells were treated with a Zn-unsupplemented basal medium (Control) or the basal medium supplemented with 400 or 800 µmol Zn/L as ZnS or Zn-Prot M for 120 min. In experiment 3, cells were treated with a Zn-unsupplemented basal medium (Control) or the basal medium supplemented with 400 µmol Zn/L as ZnS or Zn-Prot M for 120 min. The results of experiment 1 indicated that the minimum incubation time for saturable Zn absorption was determined to be 50.83 min using the best fit line. The results in experiment 2 demonstrated that a Zn concentration of 400 µmol/L and an incubation time of 120 min were suitable to increase the absorption of Zn from Zn-Prot M compared to ZnS. In experiment 3, Zn absorption across cell monolayers was significantly increased by Zn addition (P < 0.05), and was significantly greater with Zn-Prot M than with ZnS (P < 0.05). Compared to the control, Zn addition significantly decreased Zn transporter 10 and peptide-transporter 1 mRNA expression levels and increased y+L-type amino transporter 2 (y+LAT2) protein abundance (P < 0.05). Moreover, protein expression levels of zrt/irt-like protein 3 (ZIP3), ZIP5 and y+LAT2 were significantly greater for Zn-Prot M than for ZnS (P < 0.05). These findings suggest that Zn-Prot M promote Zn absorption by increasing ZIP3, ZIP5 and y+LAT2 protein expression levels in primary duodenal epithelial cells.

High-throughput preparation, scale up and solidification of andrographolide nanosuspension using hummer acoustic resonance technology.

The aim of this study was to rapidly develop a sufficiently robust andrographolide nanosuspension (AG-NS) system using hummer acoustic resonance (HAR) technology. The system can effectively improve the dissolution properties of AG, while having high stability and scale-up adaptability. The formulation of AG-NS was optimized in a high-throughput manner using HAR technology and the preparation process was optimized stepwise. Optimal AG-NS with Z-Ave = 223.99 ± 3.16 nm, PDI=0.095 ± 0.007 and zeta potential = -33.20 ± 0.58 mV was successfully prepared with Polyvinylpyrrolidone K30 and Sodium dodecyl sulfate. The optimal prescription was successfully scaled up 100 and 150 times using HAR technology, which was the initial exploration of its commercial scale production. AG-NS was solidified using freeze drying and fluid bed technology, respectively. The optimal AG-NS and its solidified products were exhaustively characterized using various analytical techniques. The high energy input of HAR technology and drying process converted part of the drug into the amorphous state. The in-vitro drug dissolution studies demonstrated relatively higher drug dissolution for AG-NS and its solidified products compared to controls at both the dissolution media (pH 1.2 buffer and pH 6.8 buffer). AG-NS and its solidified products successfully maintained their physical stability in short-term stability and accelerated stability experiments, respectively.

Deep learning in pulmonary nodule detection and segmentation: a systematic review.

OBJECTIVES: The accurate detection and precise segmentation of lung nodules on computed tomography are key prerequisites for early diagnosis and appropriate treatment of lung cancer. This study was designed to compare detection and segmentation methods for pulmonary nodules using deep-learning techniques to fill methodological gaps and biases in the existing literature. METHODS: This study utilized a systematic review with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, searching PubMed, Embase, Web of Science Core Collection, and the Cochrane Library databases up to May 10, 2023. The Quality Assessment of Diagnostic Accuracy Studies 2 criteria was used to assess the risk of bias and was adjusted with the Checklist for Artificial Intelligence in Medical Imaging. The study analyzed and extracted model performance, data sources, and task-focus information. RESULTS: After screening, we included nine studies meeting our inclusion criteria. These studies were published between 2019 and 2023 and predominantly used public datasets, with the Lung Image Database Consortium Image Collection and Image Database Resource Initiative and Lung Nodule Analysis 2016 being the most common. The studies focused on detection, segmentation, and other tasks, primarily utilizing Convolutional Neural Networks for model development. Performance evaluation covered multiple metrics, including sensitivity and the Dice coefficient. CONCLUSIONS: This study highlights the potential power of deep learning in lung nodule detection and segmentation. It underscores the importance of standardized data processing, code and data sharing, the value of external test datasets, and the need to balance model complexity and efficiency in future research. CLINICAL RELEVANCE STATEMENT: Deep learning demonstrates significant promise in autonomously detecting and segmenting pulmonary nodules. Future research should address methodological shortcomings and variability to enhance its clinical utility. KEY POINTS: Deep learning shows potential in the detection and segmentation of pulmonary nodules. There are methodological gaps and biases present in the existing literature. Factors such as external validation and transparency affect the clinical application.

Microbiomes on microplastics versus natural microcarriers: Stability and transformation during aquatic travel from aquaculture ponds to adjacent stream.

Microplastics (MPs) with different physical-chemical properties are considered as vectors for the propagation of microbes in aquatic environments. It remains unclear how plastic types impact on the plastisphere and whether different MPs spread microbes more rapidly than natural materials in microbes across distinct water bodies as proposed previously. We used in-situ incubation to investigate the microbes attached on MPs of polyethylene (PE), polypropylene (PP), and polyvinyl chloride (PVC), versus that on two natural microcarriers (quartz sands and bamboo) during the travel from aquaculture ponds with impacted by fish farming to adjacent freshwater stream. The results showed that the microbial communities on the carriers were shaped not only by environmental conditions, which were primary determinants but also by carrier types. All the tested plastics did not carry more microbes than the natural carriers during the journey. The biofilm community composition on PVC is distinct from that on PE and PP MPs and natural carriers. The plastisphere of PE and PP kept microbial proportions as natural materials did but PVC retained less than nature materials. Bamboo carried more potential pathogens than plastic polymers and quartz. The results indicated that the communities of plastisphere is polymer-type dependent, and, compared with the natural materials, MPs did not show enhanced propagation of microbes, including pathogens, cross distinct environments.

Membrane Disruption-Enhanced Photodynamic Therapy against Gram-Negative Bacteria by a Peptide-Photosensitizer Conjugate.

Photodynamic therapy (PDT) emerges as a promising strategy for combating bacteria with minimal drug resistance. However, a significant hurdle lies in the ineffectiveness of most photosensitizers against Gram-negative bacteria, primarily attributable to their characteristic impermeable outer membrane (OM) barrier. To tackle this obstacle, we herein report an amphipathic peptide-photosensitizer conjugate (PPC) with intrinsic outer membrane disruption capability to enhance PDT efficiency against Gram-negative bacteria. PPC is constructed by conjugating a hydrophilic ultrashort cationic peptide to a hydrophobic photosensitizer. PPC could efficiently bind to the OM of Gram-negative bacteria through electrostatic adsorption, and subsequently disrupt the structural integrity of the OM. Mechanistic investigations revealed that PPC triggers membrane disruption by binding to both lipopolysaccharide (LPS) and phospholipid leaflet in the OM, enabling effective penetration of PPC into the Gram-negative bacteria interior. Upon light irradiation, PPC inside bacteria generates singlet oxygen not only to effectively decrease the survival of Gram-negative bacteria P. aeruginosa and E. coli to nearly zero in vitro, but also successfully cure the full-thickness skin infection and bacterial keratitis (BK) induced by P. aeruginosa in animal models. Thus, this study provides a broad-spectrum antibacterial phototherapeutic design strategy by the synergistic action of membrane disruption and PDT to combat Gram-negative bacteria.

Association Between Pentoxifylline Use and Diabetic Retinopathy in Patients with Type 2 Diabetes Mellitus and Chronic Kidney Disease: A Multi-Institutional Cohort Study.

BACKGROUND: Pentoxifylline is administrated to improve the hemodynamics of patients with chronic kidney disease (CKD). Despite the improvement of capillary blood flow velocity in retina after pentoxifylline use, no evidence has been provided to prove the protective effect for diabetic retinopathy (DR). Therefore, this study aimed to assess the risk of DR in pentoxifylline users with CKD and diabetes mellitus (DM). MATERIAL AND METHODS: In this retrospective cohort study, Chang Gung Research Database, which includes the data of patients with CKD and DM from 2003 to 2019, was used. Each calendar year was divided into 4 data units with 3 months each for every patient and every year during the follow-up. The ocular outcomes were new-onset DR, DR-related complications, and vitreoretinal interventions. RESULTS: Total 56,439 patients without preexisting DR and 5,039 patients with preexisting DR were included in this study. Exposure to pentoxifylline was associated with elevated risk of new-onset DR (adjusted hazard ratio = 1.24, 95% confidence interval = 1.13-1.36) in patients without preexisting DR. Additionally, exposure to pentoxifylline was associated with elevated risk of DR-related complications and vitreoretinal interventions in patients with or without preexisting DR. CONCLUSIONS: Exposure to pentoxifylline is associated with elevated risk of DR, regardless of whether patients have preexisting DR.

Statistics of quantum heat in the Caldeira-Leggett model.

Nonequilibrium fluctuation relation lies at the heart of the quantum thermodynamics. Many previous studies have demonstrated that the heat exchange between a quantum system and a thermal bath initially prepared in their own Gibbs states at different temperatures obeys the famous Jarzynski-Wójcik fluctuation theorem. However, this conclusion is obtained under the assumption of Born-Markovian approximation. In this paper, going beyond the Born-Markovian limitation, we investigate the statistics of quantum heat in an exactly non-Markovian relaxation process described by the well-known Caldeira-Leggett model. It is revealed that the Jarzynski-Wójcik fluctuation theorem breaks down in the strongly non-Markovian regime. Moreover, we find the steady-state quantum heat within the non-Markovian framework can be widely tunable by using the quantum reservoir-engineering technique. These results are sharply contrary to the common Born-Markovian predictions. Our results presented in this paper may update the understanding of the quantum thermodynamics in strongly coupled and low-temperature systems. Moreover, the controllable heat may have some potential applications in improving the performance of a quantum heat engine.

Julolidinyl aza-BODIPYs as NIR-II fluorophores for the bioimaging of nanocarriers.

The aggregation-caused quenching (ACQ) rationale has been employed to improve the fluorescence imaging accuracy of nanocarriers by precluding free probe-derived interferences. However, its usefulness is undermined by limited penetration and low spatiotemporal resolution of NIR-I (700-900 nm) bioimaging owing to absorption and diffraction by biological tissues and tissue-derived autofluorescence. This study aimed to develop ACQ-based NIR-II (1000-1700 nm) probes to further improve the imaging resolution and accuracy. The strategy employed is to install highly planar and electron-rich julolidine into the 3,5-position of aza-BODIPY based on the larger substituent effects. The newly developed probes displayed remarkable photophysical properties, with intense absorption centered at approximately 850 nm and bright emission in the 950-1300 nm region. Compared with the NIR-I counterpart P2, the NIR-II probes demonstrated superior water sensitivity and quenching stability. ACQ1 and ACQ6 exhibited more promising ACQ effects with absolute fluorescence quenching at water fractions above 40% and higher quenching stability with less than 2.0% fluorescence reillumination in plasma after 24 h of incubation. Theoretical calculations verified that molecular planarity is more important than hydrophobicity for ACQ properties. Additionally, in vivo and ex vivo reillumination studies revealed less than 2.5% signal interference from prequenched ACQ1, in contrast to 15% for P2.

Atomically dispersed cobalt catalysts for tandem synthesis of primary benzylamines from oxidized ß-O-4 segments.

This work presents an innovative approach focusing on fine-tuning the coordination environment of atomically dispersed cobalt catalysts for tandem synthesis of primary benzylamines from oxidized lignin model compounds. By meticulously regulating the Co-N coordination environment, the activity of these catalysts in the hydrogenolysis and reductive amination reactions was effectively controlled. Notably, our study demonstrates that, in contrast to cobalt nanoparticle catalysts, atomically dispersed cobalt catalysts exhibit precise control of the sequence of hydrogenolysis and reductive amination reactions. Particularly, the CoN3 catalyst with a triple Co-N coordination number achieved a remarkable 94% yield in the synthesis of primary benzylamine. To our knowledge, there is no previous documentation of the synthesis of primary benzylamines from lignin dimer model compounds. Our study highlights a promising one-pot route for sustainable production of nitrogen-containing aromatic chemicals from lignin.

Impact of Esophageal Motility on Microbiome Alterations in Symptomatic Gastroesophageal Reflux Disease Patients With Negative Endoscopy: Exploring the Role of Ineffective Esophageal Motility and Contraction Reserve.

Background/Aims: Ineffective esophageal motility (IEM) is common in patients with gastroesophageal reflux disease (GERD) and can be associated with poor esophageal contraction reserve on multiple rapid swallows. Alterations in the esophageal microbiome have been reported in GERD, but the relationship to presence or absence of contraction reserve in IEM patients has not been evaluated. We aim to investigate whether contraction reserve influences esophageal microbiome alterations in patients with GERD and IEM. Methods: We prospectively enrolled GERD patients with normal endoscopy and evaluated esophageal motility and contraction reserve with multiple rapid swallows during high-resolution manometry. The esophageal mucosa was biopsied for DNA extraction and 16S ribosomal RNA gene V3-V4 (Illumina)/full-length (Pacbio) amplicon sequencing analysis. Results: Among the 56 recruited patients, 20 had normal motility (NM), 19 had IEM with contraction reserve (IEM-R), and 17 had IEM without contraction reserve (IEM-NR). Esophageal microbiome analysis showed a significant decrease in microbial richness in patients with IEM-NR when compared to NM. The beta diversity revealed different microbiome profiles between patients with NM or IEM-R and IEM-NR (P = 0.037). Several esophageal bacterial taxa were characteristic in patients with IEM-NR, including reduced Prevotella spp. and Veillonella dispar, and enriched Fusobacterium nucleatum. In a microbiome-based random forest model for predicting IEM-NR, an area under the receiver operating characteristic curve of 0.81 was yielded. Conclusions: In symptomatic GERD patients with normal endoscopic findings, the esophageal microbiome differs based on contraction reserve among IEM. Absent contraction reserve appears to alter the physiology and microbiota of the esophagus.

Experimental study on the biomechanical stability of complex acetabular fractures in the quadrilateral area: application of a dynamic anterior titanium-plate screw system.

BACKGROUND AND OBJECTIVE: Complex acetabular fractures involving quadrilateral areas are more challenging to treat during surgery. To date, there has been no ideal internal fixation for these acetabular fractures. The purpose of this study was to evaluate the biomechanical stability of complex acetabular fractures using a dynamic anterior titanium-plate screw system of the quadrilateral area (DAPSQ) by simulating the standing and sitting positions of pelvic specimens. MATERIALS AND METHODS: Eight formal in-preserved cadaveric pelvises aged 30-50 years were selected as the research objects. First, one hip of the normal pelvises was randomly used as the control model (group B) for measurement, and then one hip of the pelvises was randomly selected to make the fracture model in the 8 intact pelvises as the experimental model (group A) for measurement. In group A, acetabular both-column fractures in the quadrilateral area were established, and the fractures were fixed by DAPSQ. The biomechanical testing machine was used to load (simulated physiological load) from 400 N to 700 N at a 1 mm/min speed for 30 s in the vertical direction when the specimens were measured at random in simulated standing or sitting positions in groups. The horizontal displacement and longitudinal displacement of the acetabular fractures in the quadrilateral area were measured in both the standing and sitting simulations. RESULTS: As the load increased, no dislocation or internal fixation breakage occurred during the measurements. In the standing position, the horizontal displacement of the quadrilateral area fractures in group A and group B appeared to be less than 1 mm with loads ranging from 400 N to 700 N, and there was no significant difference between group A and group B (p > 0.05). The longitudinal displacement appeared to be greater than 1 mm with a load of 700 mm in group A (700 N, 2 cases), and the difference was significant between group A and group B (p < 0.05). In the sitting position, the horizontal and longitudinal displacements of the quadrilateral areas were within 0.5 mm in group A and group B, and there was no significant difference between group A and group B (p > 0.05). CONCLUSION: For complex acetabular fractures in the quadrilateral area, DAPSQ fixation may provide early sitting stability, but it is inappropriate for patients to stand too early.

CSMC: A Secure and Efficient Visualized Malware Classification Method Inspired by Compressed Sensing.

With the rapid development of the Internet of Things (IoT), the sophistication and intelligence of sensors are continually evolving, playing increasingly important roles in smart homes, industrial automation, and remote healthcare. However, these intelligent sensors face many security threats, particularly from malware attacks. Identifying and classifying malware is crucial for preventing such attacks. As the number of sensors and their applications grow, malware targeting sensors proliferates. Processing massive malware samples is challenging due to limited bandwidth and resources in IoT environments. Therefore, compressing malware samples before transmission and classification can improve efficiency. Additionally, sharing malware samples between classification participants poses security risks, necessitating methods that prevent sample exploitation. Moreover, the complex network environments also necessitate robust classification methods. To address these challenges, this paper proposes CSMC (Compressed Sensing Malware Classification), an efficient malware classification method based on compressed sensing. This method compresses malware samples before sharing and classification, thus facilitating more effective sharing and processing. By introducing deep learning, the method can extract malware family features during compression, which classical methods cannot achieve. Furthermore, the irreversibility of the method enhances security by preventing classification participants from exploiting malware samples. Experimental results demonstrate that for malware targeting Windows and Android operating systems, CSMC outperforms many existing methods based on compressed sensing and machine or deep learning. Additionally, experiments on sample reconstruction and noise demonstrate CSMC's capabilities in terms of security and robustness.

Densely sampled stimulus-response map of human cortex with single pulse TMS-EEG and its relation to whole brain neuroimaging measures.

Large-scale networks underpin brain functions. How such networks respond to focal stimulation can help decipher complex brain processes and optimize brain stimulation treatments. To map such stimulation-response patterns across the brain non-invasively, we recorded concurrent EEG responses from single-pulse transcranial magnetic stimulation (i.e., TMS-EEG) from over 100 cortical regions with two orthogonal coil orientations from one densely-sampled individual. We also acquired Human Connectome Project (HCP)-styled diffusion imaging scans (six), resting-state functional Magnetic Resonance Imaging (fMRI) scans (120 mins), resting-state EEG scans (108 mins), and structural MR scans (T1- and T2-weighted). Using the TMS-EEG data, we applied network science-based community detection to reveal insights about the brain's causal-functional organization from both a stimulation and recording perspective. We also computed structural and functional maps and the electric field of each TMS stimulation condition. Altogether, we hope the release of this densely sampled (n=1) dataset will be a uniquely valuable resource for both basic and clinical neuroscience research.

Multiple Riemannian Kernel Hashing for Large-Scale Image Set Classification and Retrieval.

Conventional image set methods typically learn from small to medium-sized image set datasets. However, when applied to large-scale image set applications such as classification and retrieval, they face two primary challenges: 1) effectively modeling complex image sets; and 2) efficiently performing tasks. To address the above issues, we propose a novel Multiple Riemannian Kernel Hashing (MRKH) method that leverages the powerful capabilities of Riemannian manifold and Hashing on effective and efficient image set representation. MRKH considers multiple heterogeneous Riemannian manifolds to represent each image set. It introduces a multiple kernel learning framework designed to effectively combine statistics from multiple manifolds, and constructs kernels by selecting a small set of anchor points, enabling efficient scalability for large-scale applications. In addition, MRKH further exploits inter- and intra-modal semantic structure to enhance discrimination. Instead of employing continuous feature to represent each image set, MRKH suggests learning hash code for each image set, thereby achieving efficient computation and storage. We present an iterative algorithm with theoretical convergence guarantee to optimize MRKH, and the computational complexity is linear with the size of dataset. Extensive experiments on five image set benchmark datasets including three large-scale ones demonstrate the proposed method outperforms state-of-the-arts in accuracy and efficiency particularly in large-scale image set classification and retrieval.

LncRNA FEZF1-AS1 facilitates cisplatin resistance in non-small cell lung cancer through modulating the miR-32-5p-glutaminase axis.

Non-small cell lung cancer (NSCLC) is one of the prevalent malignancies. Cisplatin (CDDP) is a conventional chemotherapeutic agent against NSCLC. However, inherent and acquired chemoresistance limited the effectiveness of cisplatin in treatment of NSCLC. This study aimed to investigate the roles and underlying mechanisms of lncRNA-FEZF1-AS1 in mediating cisplatin sensitivity in NSCLC. We found that FEZF1-AS1 levels were significantly higher in lung cancer patients and cell lines. Blocking FEZF1-AS1 sensitized lung cancer cells to cisplatin. Additionally, both glutamine metabolism and FEZF1-AS1 were significantly elevated in cisplatin resistant NSCLC cell lines, A549/CDDP R and SK-MES-1 CDDP/R. Analysis using bioinformatics, RNA pull-down assay and luciferase assay demonstrated that FEZF1-AS1 sponged miR-32-5p, which acted as a tumor suppressor in NSCLC. Glutaminase (GLS), a key enzyme in the glutamine metabolism, was predicted and validated as the direct target of miR-32-5p in NSCLC cells. Inhibiting glutamine metabolism or reducing glutamine supply effectively resensitized cisplatin-resistant cells. Furthermore, restoring miR-32-5p in FEZF1-AS1-overexpressing cisplatin resistant cells successfully overcame FEZF1-AS1-mediated cisplatin resistance by targeting GLS. These findings were further supported by in vivo xenograft mice experiments. This study uncovered the roles and molecular mechanisms of lncRNA FEZF1-AS1 in mediating cisplatin resistance in NSCLC, specifically through modulating the miR-32-5p-GLS axis, providing support for the development of new therapeutic approaches against chemoresistant lung cancer.

Functional integration and segregation during semantic cognition: Evidence across age groups.

Semantic cognition is underpinned by ventral anterior temporal lobe (vATL) which encodes knowledge representations and inferior frontal gyrus (IFG), which controls activation of knowledge based on the needs of the current context. This core semantic network has been validated in substantial empirical findings in the past. However, it remains unclear how these core semantic areas dynamically communicate with each other, and with other neural networks, to achieve successful semantic processing. Here, we investigated this question by testing functional connectivity in the core semantic network during semantic tasks and whether these connections were affected by cognitive ageing. Compared to a non-semantic task, semantic tasks increased the connectivity between left and right IFGs, indicating a bilateral semantic control system. Strengthened connectivity was also found between left IFG and left vATL, and this effect was stronger in the young group. At a whole-brain scale, IFG and vATL increased their coupling with multiple-demand regions during semantic tasks, even though these areas were deactivated relative to non-semantic tasks. This suggests that the domain-general executive network contributes to semantic processing. In contrast, IFG and vATL decreased their interaction with default mode network (DMN) areas during semantic tasks, even though these areas were positively activated by the task. This suggests that DMN areas do not contribute to all semantic tasks: their activation may sometimes reflect automatic retrieval of task-irrelevant memories and associations. Taken together, our study characterizes a dynamic connectivity mechanism supporting semantic cognition within and beyond core semantic regions.