5-Aminolevulinic acid (5-ALA)-based photodynamic therapy (PDT) has demonstrated considerable potential in breast cancer treatment. However, its efficacy is limited by low tissue selectivity and the rapid conversion of 5-ALA to non-photosensitive heme in tumor tissues, reducing its therapeutic effectiveness. This study aims to develop a multifunctional nanomedicine to enhance 5-ALA's PDT efficacy while introducing chemodynamic therapy (CDT) for synergistic tumor inhibition. By designing a zinc-ion-doped cuprous metal-organic framework (MOF) nanocarrier loaded with 5-ALA (5-ALA@Zn-CuTz), we seek to improve tumor targeting, prolong photosensitizer retention, and enhance therapeutic outcomes. To enhance biocompatibility and active tumor targeting, the surface of 5-ALA@Zn-CuTz nanoparticles (NPs) was modified with a platelet membrane (PM), forming 5-ALA@Zn-CuTz@PM NPs. The therapeutic efficacy was evaluated in vitro and in vivo using mice breast cancer models. Cellular uptake, reactive oxygen species (ROS) generation, and tumor inhibition efficiency were analyzed through fluorescence imaging, biochemical assays, and histological analysis. Upon intravenous administration, 5-ALA@Zn-CuTz@PM NPs selectively accumulated in breast cancer cells. Within the tumor, Zn²⁺ bound to intracellular protoporphyrin IX (PpIX) to form PpIX-Zn, inhibiting heme oxygenase-1 (HO-1) activity and preventing the conversion of PpIX into heme. This increased the effective intracellular concentration of the photosensitizer, thereby enhancing PDT. Additionally, Cu⁺ catalyzed the decomposition of excess H₂O₂ in the tumor microenvironment, generating oxygen and hydroxyl radicals, which alleviated hypoxia and activated CDT. The synergistic PDT/CDT effect significantly enhanced tumor growth inhibition in vitro and in vivo. 5-ALA@Zn-CuTz@PM NPs effectively enhance PDT efficacy through selective tumor targeting and HO-1 inhibition while simultaneously leveraging CDT for additional tumor suppression. The combined PDT/CDT strategy demonstrated superior therapeutic outcomes, highlighting the potential of this nanoplatform as a promising approach for breast cancer treatment.

Objectives: Fibromyalgia (FM) has been associated with decreased hippocampal volume; however, the atrophy patterns of hippocampal subregions have not yet been identified. We therefore aimed to evaluate the volumes of hippocampal subregions in FM patients with mild cognitive impairment (MCI), and to explore the relationship between different subregional alterations and cognitive function.Methods: The study included 35 FM patients (21 with MCI and 14 without MCI) and 35 healthy subjects. All subjects performed the Montreal Cognitive Assessment (MoCA) to assess cognitive function. FreeSurfer V.7.3.2 was used to calculate hippocampal subregion volumes. We then compared hippocampal subregion volumes between the groups, and analyzed the relationship between hippocampal subregion volume and cognitive function using a partial correlation analysis method.Results: Compared with the healthy subjects, FM patients with MCI had smaller hippocampal volumes in the left and right CA1 head, Molecular layer head, GC-DG head, and CA4 head, and in the left Presubiculum head. Poorer executive function, naming ability, and attention were associated with left CA1 head and left Molecular layer head atrophy. By contrast, hippocampal subregion volumes in the FM patients without MCI were slightly larger than or similar to those in the healthy subjects, and were not significantly correlated with cognitive function.Conclusion: Smaller volumes of left CA1 head and left Molecular layer head were associated with poorer executive function, naming ability, and attention in FM patients with MCI. However, these results were not observed in the FM patients without MCI. These findings suggest that the hippocampal subregions of FM patients might present compensatory mechanisms before cognitive decline occurs.

This study investigates the network mechanisms of temporal lobe epilepsy (TLE) using MEG data, focusing on directed connectivity networks across different frequency bands. Unlike previous studies that primarily localize epileptogenic zones, this research aims to explore whole-brain network differences between left TLE (lTLE), right TLE (rTLE), and healthy controls (HCs). MEG data from 13 lTLE patients, 21 rTLE patients, and 14 HCs were source-reconstructed to 116 brain regions (AAL116). Directed Transfer Function (DTF) was used to construct directed connectivity networks, followed by networks and graph-theoretical analyses. The results indicate that, compared to HCs, TLE subjects exhibited a significant increase in average connectivity strength in the Low Gamma band. The connectivity patterns across frequency bands in TLE patients were found to be unstable. Both HC and TLE subjects demonstrated left hemisphere lateralization. In the mid-to-low frequency bands, TLE subjects showed increases in global clustering coefficient (GCC), global characteristic path length (GCPL), and local efficiency (LE) compared to HCs, which is attributed to enhanced synchronization between local brain regions in TLE subjects.

Temporal lobe epilepsy (TLE) is a chronic neurological disorder that is divided into two subtypes, complex partial seizures (CPS) and simple partial seizures (SPS), based on clinical phenotypes. Revealing differences among the functional networks of different types of TLE can lead to a better understanding of the symbology of epilepsy. Whereas Although most studies had focused on differences between epileptic patients and healthy controls, the neural mechanisms behind the differences in clinical representations of CPS and SPS were unclear. In the context of the era of precision, medicine makes precise classification of CPS and SPS, which is crucial. To address the above issues, we aimed to investigate the functional network differences between CPS and SPS by constructing support vector machine (SVM) models. They mainly include magnetoencephalography (MEG) data acquisition and processing, construction of functional connectivity matrix of the brain network, and the use of SVM to identify differences in the resting state functional connectivity (RSFC). The obtained results showed that classification was effective and accuracy could be up to 82.69% (training) and 81.37% (test). The differences in functional connectivity between CPS and SPS were smaller in temporal and insula. The differences between the two groups were concentrated in the parietal, occipital, frontal, and limbic systems. Loss of consciousness and behavioral disturbances in patients with CPS might be caused by abnormal functional connectivity in extratemporal regions produced by post-epileptic discharges. This study not only contributed to the understanding of the cognitive-behavioral comorbidity of epilepsy but also improved the accuracy of epilepsy classification.

Temporal lobe epilepsy (TLE) is considered a network disorder rather than a localized lesion, making it essential to study the network mechanisms underlying TLE. In this study, we constructed directed brain networks based on clinical MEG data using the Granger Causality Analysis (GCA) method, aiming to provide new insights into the network mechanisms of TLE. MEG data from 13 lTLE and 21 rTLE patients and 14 healthy controls (HCs) were analyzed. The preprocessed MEG data were used to construct directed brain networks using the GCA method and undirected brain networks using the Pearson Correlation Coefficient (PCC) method. Graph theoretical analysis extracted global and local topologies from the binary matrix, and SVM classified topologies with significant differences (p < 0.05). Comparative studies were performed on connectivity strengths, graph theory metrics, and SVM classifications between GCA and PCC, with an additional analysis of GCA-weighted network connectivity. The results show that TLE patients showed significantly increased functional connectivity based on GCA compared to the control group; similarities of the hub brain regions between lTLE and rTLE patients and the cortical–limbic–thalamic–cortical loop were identified; TLE patients exhibited a significant increase in GCA-based Global Clustering Coefficient (GCC) and Global Local Efficiency (GLE); most brain regions with abnormal local topological properties in TLE patients overlapped with their hub regions. The directionality of brain connectivity has played a significantly more pivotal role in research on TLE. GCA may be a potential tool in MEG analysis to distinguish TLE patients and HC effectively.

Background: Fibromyalgia syndrome (FMS) is a prevalent central chronic pain condition of unknown pathophysiology. White matter (WM) plays a crucial role in brain signal transmission, and WM structural abnormalities have been reported in FMS. However, functional WM changes in FMS patients have not been investigated. This study aimed to investigate whether functional neural changes in WM accompany structural changes observed in FMS. Methods: The study included 43 FMS patients and 43 healthy controls. Structural and functional analyses of WM were assessed using fractional anisotropy (FA) and amplitude of low-frequency fluctuation (ALFF), respectively, to explore WM alterations in FMS patients. Results: Structural analysis revealed altered FA values in the left corticospinal tract (CST), right cingulate/hippocampus, right fornix/stria terminalis (FX/ST), superior occipitofrontal fasciculus (SOFF), right superior corona radiata (SCR), right posterior corona radiata (PCR), sagittal stratum, and left medial lemniscus (ML) in FMS patients. Some regions showing structural changes also showed changes in resting-state functional activation. Functional analysis showed that FMS patients have reduced ALFF values in the left CST, left ML, right PCR, right cingulate/hippocampus, and right FX/ST. Furthermore, the degree of ALFF reduction in the right cingulate/hippocampus and left ML was positively correlated with anxiety, depression, and pain severity scores. Conclusion: This study provides a preliminary exploration of the mechanisms underlying FMS in terms of WM functional signals. The observed reduction in WM functional activation offers novel insights into the pathophysiology of FMS and highlights potential targets for WM-focused therapeutic strategies.