Selective disrupted gray matter volume covariance of amygdala subregions in schizophrenia.

Objective: Although extensive structural and functional abnormalities have been reported in schizophrenia, the gray matter volume (GMV) covariance of the amygdala remain unknown. The amygdala contains several subregions with different connection patterns and functions, but it is unclear whether the GMV covariance of these subregions are selectively affected in schizophrenia. Methods: To address this issue, we compared the GMV covariance of each amygdala subregion between 807 schizophrenia patients and 845 healthy controls from 11 centers. The amygdala was segmented into nine subregions using FreeSurfer (v7.1.1), including the lateral (La), basal (Ba), accessory-basal (AB), anterior-amygdaloid-area (AAA), central (Ce), medial (Me), cortical (Co), corticoamygdaloid-transition (CAT), and paralaminar (PL) nucleus. We developed an operational combat harmonization model for 11 centers, subsequently employing a voxel-wise general linear model to investigate the differences in GMV covariance between schizophrenia patients and healthy controls across these subregions and the entire brain, while adjusting for age, sex and TIV. Results: Our findings revealed that five amygdala subregions of schizophrenia patients, including bilateral AAA, CAT, and right Ba, demonstrated significantly increased GMV covariance with the hippocampus, striatum, orbitofrontal cortex, and so on (permutation test, P< 0.05, corrected). These findings could be replicated in most centers. Rigorous correlation analysis failed to identify relationships between the altered GMV covariance with positive and negative symptom scale, duration of illness, and antipsychotic medication measure. Conclusion: Our research is the first to discover selectively impaired GMV covariance patterns of amygdala subregion in a large multicenter sample size of patients with schizophrenia.

Individualized Texture Similarity Network in Schizophrenia.

BACKGROUND: Structural covariance network disruption has been considered an important pathophysiological indicator for schizophrenia. Here, we introduced a novel individualized structural covariance network measure, referred to as a texture similarity network (TSN), and hypothesized that the TSN could reliably reveal unique intersubject heterogeneity and complex dysconnectivity patterns in schizophrenia. METHODS: The TSN was constructed by measuring the covariance of 180 three-dimensional voxelwise gray-level co-occurrence matrix feature maps between brain areas in each participant. We first tested the validity and reproducibility of the TSN in characterizing the intersubject variability in 2 longitudinal test-retest healthy cohorts. The TSN was further applied to elucidate intersubject variability and dysconnectivity patterns in 10 schizophrenia case-control datasets (609 schizophrenia cases vs. 579 controls) as well as in a first-episode depression dataset (69 patients with depression vs. 69 control participants). RESULTS: The test-retest analysis demonstrated higher TSN intersubject than intrasubject variability. Moreover, the TSN reliably revealed higher intersubject variability in both chronic and first-episode schizophrenia, but not in depression. The TSN also reproducibly detected coexistent increased and decreased TSN strength in widespread brain areas, increased global small-worldness, and the coexistence of both structural hyposynchronization in the central networks and hypersynchronization in peripheral networks in patients with schizophrenia but not in patients with depression. Finally, aberrant intersubject variability and covariance strength patterns revealed by the TSN showed a missing or weak correlation with other individualized structural covariance network measures, functional connectivity, and regional volume changes. CONCLUSIONS: These findings support the reliability of a TSN in revealing unique structural heterogeneity and complex dysconnectivity in patients with schizophrenia.

Hydrogen sulfide ameliorates lipopolysaccharide-induced anxiety-like behavior by inhibiting checkpoint kinase 1 activation in the hippocampus of mice.

Hydrogen sulfide (H2S), an endogenous gasotransmitter, exhibits the anxiolytic roles through its anti-inflammatory effects, although its underlying mechanisms remain largely elusive. Emerging evidence has documented that cell cycle checkpoint kinase 1 (Chk1)-regulated DNA damage plays an important role in the neurodegenerative diseases; however, there are few relevant reports on the research of Chk1 in neuropsychiatric diseases. Here, we aimed to investigate the regulatory role of H2S on Chk1 in lipopolysaccharide (LPS)-induced anxiety-like behavior focusing on inflammasome activation in the hippocampus. Cystathionine γ-lyase (CSE, a H2S-producing enzyme) knockout (CSE-/-) mice displayed anxiety-like behavior and activation of inflammasome-mediated inflammatory responses, manifesting by the increase levels of interleukin-1ß (IL-1ß), IL-6, and ionized calcium-binding adaptor molecule-1 (Iba-1, microglia marker) expression in the hippocampus. Importantly, expression of p-Chk1 and γ-H2AX (DNA damage marker) levels were also increased in the hippocampus of CSE-/- mice. LPS treatment decreased the expression of CSE and CBS while increased p-Chk1 and γ-H2AX levels and inflammasome-activated neuroinflammation in the hippocampus of mice. Moreover, p-Chk1 and γ-H2AX protein levels and cellular immunoactivity were significantly increased while CSE and CBS were markedly decreased in cultured BV2 cells followed by LPS treatment. Treatment of mice with GYY4137, a donor of H2S, inhibited LPS-induced increased in p-Chk1 and γ-H2AX levels, mitigated inflammasome activation and inflammatory responses as well as amelioration of anxiety-like behavior. Notably, SB-218078, a selective Chk1 inhibitor treatment attenuated the effect of LPS on inflammasome activation and inflammatory responses and the induction of anxiety-like behavior. Finally, STAT3 knockdown with AAV-STAT3 shRNA alleviated LPS-induced anxiety-like behavior and inhibited inflammasome activation in the hippocampus, and blockade of NLRP3 with MCC950 attenuated neuroinflammation induction and ameliorated LPS-induced anxiety-like behavior. Overall, this study indicates that downregulation of Chk1 activity by H2S activation may be considered as a valid strategy for preventing the progression of LPS-induced anxiety-like behavior.

FGF10 protects against LPS-induced epithelial barrier injury and inflammation by inhibiting SIRT1-ferroptosis pathway in acute lung injury in mice.

Pulmonary alveolar epithelial cell injury is considered the main pathological and physiological change in acute lung injury. Ferroptosis in alveolar epithelial cells is one of crucial factors contributing to acute lung injury (ALI). Therefore, reducing ferroptosis and repair epithelial barrier is very necessary. More and more evidence suggested that FGF10 plays an important role in lung development and repair after injury. However, the relationship between FGF10 and ferroptosis remains unclear. This study aims to explore the regulatory role of FGF10 on ferroptosis in ALI. Differential gene expression analysis indicated that genes associated with ferroptosis showed that FGF10 can significantly alleviate LPS induced lung injury and epithelial barrier damage by decreasing levels of malonaldehyde(MDA), and lipid ROS. SIRT1 activator (Resveratrol) and inhibitor (EX527) are used in vivo showed that FGF10 protects ferroptosis of pulmonary epithelial cells through SIRT1 signal. Furthermore, knockdown of FGFR2 gene reduced the protective effect of FGF10 on acute lung injury in mice and SIRT1 activation. After the application of NRF2 inhibitor ML385 in vitro, the results showed that SIRT1 regulated the expression of ferroptosis related proteins NRF2, GPX4 and FTH1 are related to activation of NRF2. These data indicate that SIRT-ferroptosis was one of the critical mechanisms contributing to LPS-induced ALI. FGF10 is promising as a therapeutic candidate against ALI through inhibiting ferroptosis.

Room-Temperature Molding of Complex-Shaped Transparent Fused Silica Lenses.

The high hardness, brittleness, and thermal resistance impose significant challenges in the scalable manufacturing of fused silica lenses, which are widely used in numerous applications. Taking advantage of the nanocomposites by stirring silica nanopowders with photocurable resins, the newly emerged low-temperature pre-shaping technique provides a paradigm shift in fabricating transparent fused silica components. However, preparing the silica slurry and carefully evaporating the organics may significantly increase the process complexity and decrease the manufacturing efficiency for the nanocomposite-based technique. By directly pressing pure silica nanopowders against the complex-shaped metal molds in minutes, this work reports an entirely different room-temperature molding method capable of mass replication of complex-shaped silica lenses without organic additives. After sintering the replicated lenses, fully transparent fused silica lenses with spherical, arrayed, and freeform patterns are generated with nanometric surface roughness and well-reserved mold shapes, demonstrating a scalable and cost-effective route surpassing the current techniques for the manufacturing of high-quality fused silica lenses.

Dissociation between neuroanatomical and symptomatic subtypes in schizophrenia.

BACKGROUND: Schizophrenia is a complex and heterogeneous syndrome with high clinical and biological stratification. Identifying distinctive subtypes can improve diagnostic accuracy and help precise therapy. A key challenge for schizophrenia subtyping is understanding the subtype-specific biological underpinnings of clinical heterogeneity. This study aimed to investigate if the machine learning (ML)-based neuroanatomical and symptomatic subtypes of schizophrenia are associated. METHODS: A total of 314 schizophrenia patients and 257 healthy controls from four sites were recruited. Gray matter volume (GMV) and Positive and Negative Syndrome Scale (PANSS) scores were employed to recognize schizophrenia neuroanatomical and symptomatic subtypes using K-means and hierarchical methods, respectively. RESULTS: Patients with ML-based neuroanatomical subtype-1 had focally increased GMV, and subtype-2 had widespread reduced GMV than the healthy controls based on either K-means or Hierarchical methods. In contrast, patients with symptomatic subtype-1 had severe PANSS scores than subtype-2. No differences in PANSS scores were shown between the two neuroanatomical subtypes; similarly, no GMV differences were found between the two symptomatic subtypes. Cohen's Kappa test further demonstrated an apparent dissociation between the ML-based neuroanatomical and symptomatic subtypes (P > 0.05). The dissociation patterns were validated in four independent sites with diverse disease progressions (chronic vs. first episodes) and ancestors (Chinese vs. Western). CONCLUSIONS: These findings revealed a replicable dissociation between ML-based neuroanatomical and symptomatic subtypes of schizophrenia, which provides a new viewpoint toward understanding the heterogeneity of schizophrenia.

Unraveling schizophrenia replicable functional connectivity disruption patterns across sites.

Functional connectivity (FC) disruption is a remarkable characteristic of schizophrenia. However, heterogeneous patterns reported across sites severely hindered its clinical generalization. Based on qualified nodal-based FC of 340 schizophrenia patients (SZ) and 348 normal controls (NC) acquired from seven different scanners, this study compared four commonly used site-effect correction methods in removing the site-related heterogeneities, and then tried to cluster the abnormal FCs into several replicable and independent disrupted subnets across sites, related them to clinical symptoms, and evaluated their potentials in schizophrenia classification. Among the four site-related heterogeneity correction methods, ComBat harmonization (F1 score: 0.806 ± 0.145) achieved the overall best balance between sensitivity and false discovery rate in unraveling the aberrant FCs of schizophrenia in the local and public data sets. Hierarchical clustering analysis identified three replicable FC disruption subnets across the local and public data sets: hypo-connectivity within sensory areas (Net1), hypo-connectivity within thalamus, striatum, and ventral attention network (Net2), and hyper-connectivity between thalamus and sensory processing system (Net3). Notably, the derived composite FC within Net1 was negatively correlated with hostility and disorientation in the public validation set (p < .05). Finally, the three subnet-specific composite FCs (Best area under the receiver operating characteristic curve [AUC] = 0.728) can robustly and meaningfully discriminate the SZ from NC with comparable performance with the full identified FCs features (best AUC = 0.765) in the out-of-sample public data set (Z = -1.583, p = .114). In conclusion, ComBat harmonization was most robust in detecting aberrant connectivity for schizophrenia. Besides, the three subnet-specific composite FC measures might be replicable neuroimaging markers for schizophrenia.

Mapping cerebral atrophic trajectory from amnestic mild cognitive impairment to Alzheimer's disease.

Alzheimer's disease (AD) patients suffer progressive cerebral atrophy before dementia onset. However, the region-specific atrophic processes and the influences of age and apolipoprotein E (APOE) on atrophic trajectory are still unclear. By mapping the region-specific nonlinear atrophic trajectory of whole cerebrum from amnestic mild cognitive impairment (aMCI) to AD based on longitudinal structural magnetic resonance imaging data from Alzheimer's disease Neuroimaging Initiative (ADNI) database, we unraveled a quadratic accelerated atrophic trajectory of 68 cerebral regions from aMCI to AD, especially in the superior temporal pole, caudate, and hippocampus. Besides, interaction analyses demonstrated that APOE ε4 carriers had faster atrophic rates than noncarriers in 8 regions, including the caudate, hippocampus, insula, etc.; younger patients progressed faster than older patients in 32 regions, especially for the superior temporal pole, hippocampus, and superior temporal gyrus; and 15 regions demonstrated complex interaction among age, APOE, and disease progression, including the caudate, hippocampus, etc. (P < 0.05/68, Bonferroni correction). Finally, Cox proportional hazards regression model based on the identified region-specific biomarkers could effectively predict the time to AD conversion within 10 years. In summary, cerebral atrophic trajectory mapping could help a comprehensive understanding of AD development and offer potential biomarkers for predicting AD conversion.

Nonaqueous Electroextraction with Tunable Selectivity for Direct, Fast, and Exhaustive Enrichment of Per- and Polyfluoroalkyl Acids from Oils and Food Contact Materials.

Widespread concerns have been raised due to the ever-increasing number of novel per- and polyfluoroalkyl acids (PFAAs) and the ever-decreasing level of legacy PFAAs. Most analytical methods for PFAAs suffer from a narrow range of analyzable PFAAs, insufficient sensitivity, poor performance for oil samples, and defective quantification without internal standards or blank matrices. To solve these challenges, a highly selective method for multiple PFAAs from oils and food contact materials (FCMs) was developed based on nonaqueous electroextraction (NE). Through theoretical derivation and experimental investigation, the selectivity of NE was discovered to be tunable, and the range of extractable analytes could be tuned by adjusting the dielectric constant of the sample solution. For PFAAs, the selectivity was attributed to the pKa-based differential migration mechanism, as PFAAs exhibited less variable pKa values in different solvents compared to interference components. The method achieved nonmatrix-matched calibration without internal standards and integration of sample cleanup, selective extraction, and exhaustive enrichment into a fast and convenient operation. The method provided low limits of detection (0.002-0.03 µg·kg-1), satisfactory accuracy (88.0-107.8%), and RSDs (<11.7%). Migration experiments from 33 FCMs to oils were further investigated. PFBS (<0.05-2.34 µg·kg-1) and PFBA (<0.2-0.398 µg·kg-1) were detected from most FCMs. This was the first attempt at PFAA analysis as well as oil sample analysis using an electric field-assisted extraction technique and also the first report on PFAA migration from FCMs into edible oils.

Disrupted local functional connectivity in schizophrenia: An updated and extended meta-analysis.

Neuroimaging studies have shown that schizophrenia is associated with disruption of resting-state local functional connectivity. However, these findings vary considerably, which hampers our understanding of the underlying pathophysiological mechanisms of schizophrenia. Here, we performed an updated and extended meta-analysis to identify the most consistent changes of local functional connectivity measured by regional homogeneity (ReHo) in schizophrenia. Specifically, a systematic search of ReHo studies in patients with schizophrenia in PubMed, Embase, and Web of Science identified 18 studies (20 datasets), including 652 patients and 596 healthy controls. In addition, we included three whole-brain statistical maps of ReHo differences calculated based on independent datasets (163 patients and 194 controls). A voxel-wise meta-analysis was then conducted to investigate ReHo alterations and their relationship with clinical characteristics using the newly developed seed-based d mapping with permutation of subject images (SDM-PSI) meta-analytic approach. Compared with healthy controls, patients with schizophrenia showed significantly higher ReHo in the bilateral medial superior frontal gyrus, while lower ReHo in the bilateral postcentral gyrus, right precentral gyrus, and right middle occipital gyrus. The following sensitivity analyses including jackknife analysis, subgroup analysis, heterogeneity test, and publication bias test demonstrated that our results were robust and highly reliable. Meta-regression analysis revealed that illness duration was negatively correlated with ReHo abnormalities in the right precentral/postcentral gyrus. This comprehensive meta-analysis not only identified consistent and reliably aberrant local functional connectivity in schizophrenia but also helped to further deepen our understanding of its pathophysiology.

Morphometric Integrated Classification Index: A Multisite Model-Based, Interpretable, Shareable and Evolvable Biomarker for Schizophrenia.

BACKGROUND AND HYPOTHESIS: Multisite massive schizophrenia neuroimaging data sharing is becoming critical in understanding the pathophysiological mechanism and making an objective diagnosis of schizophrenia; it remains challenging to obtain a generalizable and interpretable, shareable, and evolvable neuroimaging biomarker for schizophrenia diagnosis. STUDY DESIGN: A Morphometric Integrated Classification Index (MICI) was proposed as a potential biomarker for schizophrenia diagnosis based on structural magnetic resonance imaging data of 1270 subjects from 10 sites (588 schizophrenia patients and 682 normal controls). An optimal XGBoost classifier plus sample-weighted SHapley Additive explanation algorithms were used to construct the MICI measure. STUDY RESULTS: The MICI measure achieved comparable performance with the sample-weighted ensembling model and merged model based on raw data (Delong test, P > 0.82) while outperformed the single-site models (Delong test, P < 0.05) in either the independent-sample testing datasets from the 9 sites or the independent-site dataset (generalizable). Besides, when new sites were embedded in, the performance of this measure was gradually increasing (evolvable). Finally, MICI was strongly associated with the severity of schizophrenia brain structural abnormality, with the patients' positive and negative symptoms, and with the brain expression profiles of schizophrenia risk genes (interpretable). CONCLUSIONS: In summary, the proposed MICI biomarker may provide a simple and explainable way to support clinicians for objectively diagnosing schizophrenia. Finally, we developed an online model share platform to promote biomarker generalization and provide free individual prediction services (http://micc.tmu.edu.cn/mici/index.html).

Ultrasound-assisted micellar cleanup coupled with large-volume-injection enrichment for the analysis of polar drugs in blood and zebrafish samples.

A novel ultrasound-assisted micellar cleanup strategy (UAMC) coupled with large volume injection (LVI) high performance liquid chromatography (HPLC) method was proposed and successfully applied to the analysis of cefathiamidine in complex biological samples such as whole blood, plasma, serum and even zebrafish, a challenging positive real sample. Based on the micelle-biomacromolecule interaction, the phase-separation feature of surfactant micelles and ultrasound cavitation, UAMC possessed an impressive matrix cleanup capability and could rapidly reach distribution equilibrium (approximately 2 min), which enabled simultaneous sample cleanup and analyte extraction within 8 min. Due to the high cleanup efficiency of UAMC, large volume of pretreated samples could be injected for analysis without peak broadening, impurity interference and column degradation. Thus, online analyte enrichment could be automatically performed to significantly improve method sensitivity by the column-switching LVI-HPLC system, a commercial HPLC system with small modifications. The UAMC-LVI-HPLC method creatively integrated sample cleanup, analyte extraction and on-column enrichment into simple operation. In addition, the UAMC-LVI-HPLC method enabled non-matrix-matched analysis of cefathiamidine in complex biological samples. This feature was helpful to address the problems caused by conventional matrix-matched or internal standard calibration methods, such as matrix bias, increased workload, limited availability of suitable blank matrices and the use of expensive internal standards. The method had low limits of detections (e.g., 0.0051 mg/L and 0.038 µg/g), wide linear ranges (0.030-100 mg/L and 0.15-489 µg/g), good linear correlation (R2 = 0.9999), satisfactory accuracy (97.6-109.7%) and excellent intra- and interday precision (0.5-4.9%). Thus, UAMC-LVI-HPLC is expected to be a promising candidate for bioanalysis in therapeutic drug monitoring or pharmacokinetic and toxicology studies in the future.

Exploring Older Adults' Adoption and Use of a Tablet Computer During COVID-19: Longitudinal Qualitative Study.

BACKGROUND: As mobile computing technology evolves, such as smartphones and tablet computers, it increasingly offers features that may be particularly beneficial to older adults. However, the digital divide exists, and many older adults have been shown to have difficulty using these devices. The COVID-19 pandemic has magnified how much older adults need but are excluded from having access to technologies to meet essential daily needs and overcome physical distancing restrictions. OBJECTIVE: This study sought to understand how older adults who had never used a tablet computer learn to use it, what they want to use it for, and what barriers they experience as they continue to use it during social isolation caused by the COVID-19 pandemic. METHODS: We conducted a series of semistructured interviews with eight people aged 65 years and older for 16 weeks, investigating older novice users' adoption and use of a tablet computer during the nationwide lockdown due to COVID-19. RESULTS: Participants were gradually yet successfully accustomed to using a tablet computer to serve various daily needs, including entertainment, social connectedness, and information-seeking. However, this success was not achieved through developing sufficient digital skills but rather by applying the methods they were already familiar with in its operation, such as taking and referring to instruction notes. CONCLUSIONS: Our findings imply that older adults without digital literacy can still benefit from a digital device for quality of later life if proper traditional methods they are already familiar with are offered in its use.

Analysis of the Influence of the Breaking Radiation Magnetic Field of a 10 kV Intelligent Circuit Breaker on an Electronic Transformer.

The development of the smart grid requires the distribution switch to not be limited to the original breaking function. More functional requirements lead to more complex switch structures, especially the intelligent processing unit on the secondary side. A technology called primary and secondary integration optimizes the structure of the switch, which greatly increases the intelligence level of the switch, but also has disadvantages. The secondary intelligent unit is arranged close to the primary high-voltage electromagnetic environment, and the distribution switch is prone to failure due to electromagnetic interference. In order to explore the influence of electromagnetic interference on it, a transient electromagnetic interference simulation test platform was built for a 10 kV intelligent distribution switch based on the principle of spherical gap arc discharge, and the interference signal of the intelligent distribution switch was measured; the law of the spatial magnetic field near the electronic transformer is mainly studied in this paper. The shielding effectiveness of the distribution terminal of the switch was analyzed, and the interference of the power line of the sensor merging unit circuit board was calculated. The results show that the electronic transformer may have serious faults under continuous strong transient electromagnetic interference. The electromagnetic transient simulation test system studied in this paper can evaluate the anti strong electromagnetic interference ability of the electronic transformer.

Nonaqueous Miscible Liquid-Liquid Electroextraction for Fast Exhaustive Enrichment of Ultratrace Analytes by an Exponential Transfer and Deceleration Mechanism.

Conventional electrical-field-assisted sample preparation (EFASP) methods rely on analyte transfer between immiscible phases and require at least one aqueous phase in contact with the electrode. In this paper, we report a novel nonaqueous miscible liquid-liquid electroextraction (NMLEE) technique that enables fast exhaustive enrichment of ultratrace analytes from a milliliter-level donor in a vial to a microliter-level acceptor in a tube. Miscible nonaqueous solvents are used for the donor and acceptor to overcome common EFASP problems such as high charge or mass transfer resistance, loss of analytes in the membrane phase, water electrolysis, back-extraction, bubble generation, and difficulties in the application of high voltage for fast migration. According to theoretical derivation and experimental verification results, the concentrations of analytes in the donor and their migration velocity in the acceptor both decrease exponentially with time, and the extraction recovery correlates linearly with the current variation. These mechanisms result in efficient enrichment by forming an analyte-enriched zone and allow the extraction progress and recovery to be monitored and estimated based on the current variation. NMLEE was coupled with liquid chromatography-mass spectrometry to analyze 10 amphetamine-type drugs, atropine, nortriptyline, and methadone in blood and urine samples. This method provided low limits of detection (0.003-0.1 ng·mL-1), satisfactory extraction recoveries (89.6-104.1%), and RSDs (<12.3% for intraday and <8.8% for interday), which met the requirements of the ICH guidelines. This study may contribute to the further development of EFASP methods for effective ultratrace analyses in forensic science.

Contribution of carboxyl modified chiral mesoporous silica nanoparticles in delivering doxorubicin hydrochloride in vitro: pH-response controlled release, enhanced drug cellular uptake and cytotoxicity.

In this study, dual functionalized mesoporous silica nanoparticle (Dual-MSN) with functions of carboxyl modification and chirality was successfully developed and its special contribution in delivering doxorubicin hydrochloride (DOX) in vitro was mainly studied. Characteristics of Dual-MSN and its application as DOX carrier were intensively explored by comparing with naked non-functionalized MSN (Naked MSN). The results indicated that both Naked MSN and Dual-MSN significantly controlled DOX release due to the release hindrance caused by mesopores. As expected, Dual-MSN exhibited obvious enhanced pH-response because of its negative charges of carboxyl groups. DOX loaded Naked MSN and DOX loaded Dual-MSN presented better cytotoxicity than DOX due to carrier-mediated endocytosis and the favorable intercalation of DOX into DNA in the nuclei. The cytotoxicity of DOX loaded Dual-MSN was better than DOX loaded Naked MSN owing to its enhanced cellular uptake induced by chirality of Dual-MSN, demonstrating that double functions of Dual-MSN had unique advantages in improving antitumor effect of DOX towards MCF-7 cells and thus confirming its special contribution in DOX delivery.