Near-infrared hemicyanine photosensitizer for targeted mitochondrial viscosity imaging and efficient photodynamic therapy.

As a severe threat to human health, cancer has always been one of the most significant challenges facing the medical field. However, there is currently no effective technology or method to diagnose and treat cancer simultaneously. Therefore, developing a new approach that integrates diagnosis and treatment holds promise as a means of achieving personalized and precise cancer therapy. In this study, we developed a novel dual-functional near-infrared mitochondrial-targeted photosensitizer, Hcy-I, which is capable of simultaneously monitoring cellular viscosity and specifically targeting mitochondria for photodynamic therapy. Compared with traditional hemicyanine dyes, the introduction of iodine atoms in Hcy-I enhanced spin-orbit coupling (SOC) and promoted the intersystem crossing (ISC) rate, thereby increasing the efficiency of singlet oxygen (1O2) generation. In vitro experiments demonstrated that Hcy-I exhibited high sensitivity to viscosity variations and efficiently generated 1O2 under 638 nm laser irradiation, with an 1O2 quantum yield of up to 48.9 %. Cell experiments further revealed that this photosensitizer could effectively target mitochondria for photodynamic therapy, disrupting mitochondrial membrane potential and inducing cell death. When treated with Hcy-I at a concentration of 0.8 µM, the survival rate of HepG-2 cells was only 13 %. These results suggested that Hcy-I had the potential to integrate cancer diagnosis and treatment. The research not only promotes the development of photodynamic thereby technology, but also opens up new avenues for the diagnosis and treatment of cancer.

Highly Efficient Synergistic Chemotherapy and Magnetic Resonance Imaging for Targeted Ovarian Cancer Therapy Using Hyaluronic Acid-Coated Coordination Polymer Nanoparticles.

The diagnosis and treatment of ovarian cancer (OC) are still a grand challenge, more than 70% of patients are diagnosed at an advanced stage with a dismal prognosis. Magnetic resonance imaging (MRI) has shown superior results to other examinations in preoperative assessment, while cisplatin-based chemotherapy is the first-line treatment for OC. However, few previous studies have brought together the two rapidly expanding fields. Here a technique is presented using cisplatin prodrug (Pt-COOH), Fe3+, and natural polyphenols (Gossypol) to construct the nanoparticles (HA@PFG NPs) that have a stable structure, controllable drug release behavior, and high drug loading capacity. The acidic pH values in tumor sites facilitate the release of Fe3+, Pt-COOH, and Gossypol from HA@PFG NPs. Pt-COOH with GSH consumption and cisplatin-based chemotherapy plus Gossypol with pro-apoptotic effects displays a synergistic effect for killing tumor cells. Furthermore, the release of Fe3+ at the tumor sites promotes ferroptosis and enables MRI imaging of OC. In the patient-derived tumor xenograft (PDX) model, HA@PFG NPs alleviate the tumor activity. RNA sequencing analysis reveals that HA@PFG NPs ameliorate OC symptoms mainly through IL-6 signal pathways. This work combines MRI imaging with cisplatin-based chemotherapy, which holds great promise for OC diagnosis and synergistic therapy.

Integrated Diagnosis in Africa's Low- and Middle-Income Countries: What Is It, What Works, and for Whom? A Realist Synthesis.

Introduction: Integrated diagnosis can improve health outcomes and patient experiences through early diagnosis and identification of cases that could otherwise be overlooked. Although existing research highlight the feasibility of integrated diagnosis across various conditions, a significant evidence gap remains regarding its direct impact on patient experiences and health outcomes. This review explores the conceptualizations of integrated diagnosis by different stakeholders along the healthcare pathway and examines the necessary contexts and mechanisms crucial for its effectiveness. Methods: This study adopts a realist methodology to explore integrated diagnosis. Using a systematic approach, the research aims to collect, assess, and synthesize existing evidence on integrated diagnosis, guided by a program theory developed through literature review and expert consultations. Primary studies and reviews related to integrated diagnosis, multi-disease testing, or integrated healthcare with a diagnostic focus were sourced from major databases and global health organization websites. The collected evidence was used to construct and refine the evolving theoretical framework. Results: This study identified three models of integrated diagnosis interventions: individual/human resource integration, facility or mobile-based integration, and technology integration. Successful implementation of these models relies on understanding the values and perceptions of both healthcare workers and patients/clients. This research emphasizes a holistic approach that considers all elements within the health system and underscores their interdependence. Using the WHO health systems framework to contextualise factors, the study positions diagnosis as an integral component of the broader health ecosystem. A key finding of the research is the importance of addressing the barriers and facilitators of integrated diagnosis interventions. This includes policy frameworks, diagnostic tools, funding mechanisms, treatment pathways, and human resource issues. Improving patient experiences requires cultivating positive relationships with healthcare workers ensuring elements such as respect, confidentiality, accessibility, and timeliness of services are prioritised. Discussion and Conclusion: The diverse conceptualisations of integrated diagnosis highlight the importance of clear definitions for each intervention. This clarity is essential for transferring lessons learned, comparing programs, and effectively measuring results. The success of integrated diagnosis is not a one-size-fits-all scenario; decisions regarding the approach, conditions to be integrated, and timing of integration must be guided by local contexts to ensure sustainable outcomes. The review findings suggest that integrated diagnosis may be suitable at the primary care level in LMICs under specific circumstances. Successful implementation hinges on addressing the perspectives of healthcare workers and patients/clients alike, requiring adequate time, resources, and a well-defined intervention model.

Novel insights toward diagnosis and treatment of glioneuronal and neuronal tumors in young adults.

Aim: Glioneuronal and neuronal tumors are rare primary central nervous system malignancies with heterogeneous features. Due to the rarity of these malignancies diagnosis and treatment remains a clinical challenge. Methods: Here we performed a narrative review aimed to investigate the principal issues concerning the diagnosis, pathology, and clinical management of glioneuronal tumors. Results: Diagnostic criteria have been recently overturned thanks to a better characterization on a histological and molecular biology level. The study of genomic alterations occurring within these tumors has allowed us to identify potential therapeutic targets including BRAF, FGFR, and PDGFRA. Conclusion: Techniques allowing molecular sequencing DNA methylation assessment of the disease are essential diagnostic tools. Targeting agents should be included in the therapeutic armamentarium after loco-regional treatment failure.

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Clinical roles of EGFR amplification in diffuse gliomas: a real-world study using the 2021 WHO classification of CNS tumors.

Background: The 2021 World Health Organization Classification of Central Nervous System Tumors updates glioma subtyping and grading system, and incorporates EGFR amplification (Amp) as one of diagnostic markers for glioblastoma (GBM). Purpose: This study aimed to describe the frequency, clinical value and molecular correlation of EGFR Amp in diffuse gliomas based on the latest classification. Methods: We reviewed glioma patients between 2011 and 2022 at our hospital, and included 187 adult glioma patients with available tumor tissue for detection of EGFR Amp and other 59 molecular markers of interest. Clinical, radiological and pathological data was analyzed based on the status of EGFR Amp in different glioma subtypes. Results: 163 gliomas were classified as adult-type diffuse gliomas, and the number of astrocytoma, oligodendroglioma and GBM was 41, 46, and 76. EGFR Amp was more common in IDH-wildtype diffuse gliomas (66.0%) and GBM (85.5%) than IDH-mutant diffuse gliomas (32.2%) and its subtypes (astrocytoma, 29.3%; oligodendroglioma, 34.8%). EGFR Amp did not stratify overall survival (OS) in IDH-mutant diffuse gliomas and astrocytoma, while was significantly associated with poorer OS in IDH-wildtype diffuse gliomas, histologic grade 2 and 3 IDH-wildtype diffuse astrocytic gliomas and GBM. Conclusion: Our study validated EGFR Amp as a diagnostic marker for GBM and still a useful predictor for shortened OS in this group.

Concordance analysis of cerebrospinal fluid with the tumor tissue for integrated diagnosis in gliomas based on next-generation sequencing.

Purpose: The driver mutations of gliomas have been identified in cerebrospinal fluid (CSF). Here we compared the concordance between CSF and tumor tissue for integrated diagnosis in gliomas using next-generation sequencing (NGS) to evaluate the feasibility of CSF detection in gliomas. Patients and methods: 27 paired CSF/tumor tissues of glioma patients were sequenced by a customized gene panel based on NGS. All CSF samples were collected through lumbar puncture before surgery. Integrated diagnosis was made by analysis of histology and tumor DNA molecular pathology according to the 2021 WHO classification of the central nervous system tumors. Results: A total of 24 patients had detectable circulating tumor DNA (ctDNA) and 22 had at least one somatic mutation or chromosome alteration in CSF. The ctDNA levels varied significantly across different ages, Ki-67 index, magnetic resonance imaging signal and glioma subtypes (p < 0.05). The concordance between integrated ctDNA diagnosis and the final diagnosis came up to 91.6% (Kappa, 0.800). We reclassified the clinical diagnosis of 3 patients based on the results of CSF ctDNA sequencing, and 4 patients were reassessed depending on tumor DNA. Interestingly, a rare IDH1 R132C was identified in CSF ctDNA, but not in the corresponding tumor sample. Conclusion: This study demonstrates a high concordance between integrated ctDNA diagnosis and the final diagnosis of gliomas, highlighting the practicability of NGS based detection of mutations of CSF in assisting integrated diagnosis of gliomas, especially glioblastoma.

Ultrasound Sonosensitizers for Tumor Sonodynamic Therapy and Imaging: A New Direction with Clinical Translation.

With the rapid development of sonodynamic therapy (SDT), sonosensitizers have evolved from traditional treatments to comprehensive diagnostics and therapies. Sonosensitizers play a crucial role in the integration of ultrasound imaging (USI), X-ray computed tomography (CT), and magnetic resonance imaging (MRI) diagnostics while also playing a therapeutic role. This review was based on recent articles on multifunctional sonosensitizers that were used in SDT for the treatment of cancer and have the potential for clinical USI, CT, and MRI applications. Next, some of the shortcomings of the clinical examination and the results of sonosensitizers in animal imaging were described. Finally, this paper attempted to inform the future development of sonosensitizers in the field of integrative diagnostics and therapeutics and to point out current problems and prospects for their application.

Missed opportunities for integrated testing of HIV and tuberculosis on the GeneXpert platform in Lesotho.

Background: Integrated testing, treatment and care are key strategies for addressing the dual burdens of tuberculosis and HIV. The GeneXpert instrument allows simultaneous HIV and tuberculosis testing, but its utilisation for integrated testing remains suboptimal. Objective: The study determined the extent to which tuberculosis testing and HIV early infant detection (EID) were integrated on the GeneXpert platform, or the potential for integration at selected health facilities. Methods: A mixed methods evaluation was conducted using retrospective secondary data analysis of laboratory records from 2017 to 2019, and semi-structured interviews. Data were collected between January 2020 and March 2020 in Lesotho. Results: Forty-four health staff were interviewed across 13 health facilities: one regional, nine district, and three clinic level. Six were government facilities, six were mission hospitals, and one was a non-profit clinic. All facilities selected had at least one GeneXpert instrument used for tuberculosis or HIV testing; none included simultaneous testing for tuberculosis and HIV. In 2017, the average utilisation rate for the GeneXpert instrument for tuberculosis and EID testing was 63% and 24%, while in 2019, the average utilisation rate was 61% for tuberculosis testing and 27% for EID. Conclusion: Except for three sites where the testing rates were high, utilisation rates were sufficiently low that all the HIV EID and tuberculosis tests undertaken in 2017 and 2019 could have been performed using only the instruments currently dedicated to tuberculosis testing. There is a missed opportunity for the integration of testing for tuberculosis and HIV on the GeneXpert instrument. What this study adds: This study adds to the body of evidence on the need for integration of testing and highlights some practical and technical considerations for successful implementation of integrated tuberculosis and HIV testing.

A "masked" pleomorphic xanthoastrocytoma.

The latest WHO Classification of tumours of the Central Nervous System (CNS) emphasizes the necessity of an integrated diagnostic approach during the workup of a CNS neoplasm. In addition to the mutational status, assessment of methylation profile of a tumour emerged as a helpful (often necessary) tool to make a correct and unequivocal diagnosis. Here we present a case of a Pleomorphic Xanthoastrocytoma with clinical, radiological and histopathological findings remarkably overlapping with a recently described paediatric-type glioma namly Polymorphic Low-grade Neuroepithelial Tumour of the Young (PLNTY). The differential diagnosis here discussed represents a methodological paradigm in the modern neuropathology. In fact, the presentation of this case is a demonstration that in day-to-day practice, clinical, radiological, and histopathological data can all be misleading, and the correct diagnosis can only be reached by integration with molecular analysis. In the modern neuro-oncology, it is by far mandatory for all the specialists dealing with cerebral tumours to "contaminate" their own cultural heritage with other ones, to optimally manage a patient with CNS tumour.

Pediatric brain tumors: A neuropathologist's approach to the integrated diagnosis.

The classification of tumors of the central nervous system (CNS) is a rapidly evolving field. While tumors were historically classified on the basis of morphology, the recent integration of molecular information has greatly refined this process. In some instances, molecular alterations provide significant prognostic implications beyond what can be ascertained by morphologic examination alone. Additionally, tumors may harbor molecular alterations that provide a therapeutic target. Pediatric CNS tumors, in particular, rely heavily on the integration of molecular data with histologic, clinical, and radiographic features to reach the most accurate diagnosis. This review aims to provide insight into a neuropathologist's approach to the clinical workup of pediatric brain tumors with an ultimate goal of reaching an integrated diagnosis that provides the most accurate classification and informs prognosis and therapy selection. The primary focus will center on how histology and molecular findings are used in combination with clinical and radiographic information to reach a final, integrated diagnosis.

Clinical updates on gliomas and implications of the 5th edition of the WHO classification of central nervous system tumors.

Background: The 5th edition of the World Health Organization (WHO) classification of central nervous system tumors incorporated specific molecular alterations into the categorization of gliomas. The major revision of the classification scheme effectuates significant changes in the diagnosis and management of glioma. This study aimed to depict the clinical, molecular, and prognostic characteristics of glioma and its subtypes according to the current WHO classification. Methods: Patients who underwent surgery for glioma at Peking Union Medical College Hospital during 11 years were re-examined for tumor genetic alterations using next-generation sequencing, polymerase chain reaction-based assay, and fluorescence in situ hybridization methods and enrolled in the analysis. Results: The enrolled 452 gliomas were reclassified into adult-type diffuse glioma (ntotal=373; astrocytoma, n=78; oligodendroglioma, n=104; glioblastoma, n=191), pediatric-type diffuse glioma (ntotal=23; low-grade, n=8; high-grade, n=15), circumscribed astrocytic glioma (n=20), and glioneuronal and neuronal tumor (n=36). The composition, definition, and incidence of adult- and pediatric-type gliomas changed significantly between the 4th and the 5th editions of the classification. The clinical, radiological, molecular, and survival characteristics of each subtype of glioma were identified. Alterations in CDK4/6, CIC, FGFR2/3/4, FUBP1, KIT, MET, NF1, PEG3, RB1, and NTRK2 were additional factors correlated with the survival of different subtypes of gliomas. Conclusions: The updated WHO classification based on histology and molecular alterations has updated our understanding of the clinical, radiological, molecular, survival, and prognostic characteristics of varied subtypes of gliomas and provided accurate guidance for diagnosis and potential prognosis for patients.

Clinical Profile, Pathology, and Molecular Typing of Gliomas with Oligodendroglial Morphology: A Single Institutional Experience.

Background: Diffuse gliomas are represented in the 2007 WHO classification of CNS tumors as astrocytomas, oligoastrocytoma, and oligodendroglioma of grades II/III and glioblastomas WHO grade IV, which was a pure morphologic classification. WHO 2016 classification combines morphology with molecular markers like IDH, ATRX, and 1p/19q codeletion to give an integrated diagnosis. Methods: The study was carried out on formalin fixed paraffin embedded tissues from 54 patients including three pediatric patients. Molecular studies were performed to know the 1p/19q codeletion status, IDH1R132H, and ATRX immunoexpression. Also, the IDH1R132H status was correlated with survival data. Results: The study included 54 tumors with oligodendroglial morphology. IDH1R132H positivity was seen in 85% of total cases and codeletion was seen in 72%. The integrated diagnosis revised the cases into oligodendroglioma (39), astrocytoma (5), and glioblastoma (6).IDH mutant tumors were found to have better survival than negative ones which was statistically significant. Conclusion: This study emphasizes the need for molecular work up of tumors with oligodendroglial morphology with readily available techniques like IHC and Fluorescence in situ hybridization.

Risk Stratification of Childhood Medulloblastoma Using Integrated Diagnosis: Discrepancies with Clinical Risk Stratification.

BACKGROUND: Recent genomic studies identified four discrete molecular subgroups of medulloblastoma (MB), and the risk stratification of childhood MB in the context of subgroups was refined in 2015. In this study, we investigated the effect of molecular subgroups on the risk stratification of childhood MB. METHODS: The nCounter® system and a customized cancer panel were used for molecular subgrouping and risk stratification in archived tissues. RESULTS: A total of 44 patients were included in this study. In clinical risk stratification, based on the presence of residual tumor/metastasis and histological findings, 24 and 20 patients were classified into the average-risk and high-risk groups, respectively. Molecular subgroups were successfully defined in 37 patients using limited gene expression analysis, and DNA panel sequencing additionally classified the molecular subgroups in three patients. Collectively, 40 patients were classified into molecular subgroups as follows: WNT (n = 7), SHH (n = 4), Group 3 (n = 8), and Group 4 (n = 21). Excluding the four patients whose molecular subgroups could not be determined, among the 17 average-risk group patients in clinical risk stratification, one patient in the SHH group with the TP53 variant was reclassified as very-high-risk using the new risk classification system. In addition, 5 out of 23 patients who were initially classified as high-risk group in clinical risk stratification were reclassified into the low- or standard-risk groups in the new risk classification system. CONCLUSION: The new risk stratification incorporating integrated diagnosis showed some discrepancies with clinical risk stratification. Risk stratification based on precise molecular subgrouping is needed for the tailored treatment of MB patients.

Adolescent and young adult brain tumors: current topics and review.

The management of brain tumors developed in adolescents and young adults (AYAs) is challenging because of their histological heterogeneity and low incidence. The brain tumor and its treatment interventions can negatively affect neurological, neurocognitive, and endocrinological function, and dramatically affect the circumstances of AYA patients progressing to further education, employment, and marriage. Specific support is thus necessary to maintain the quality of life (QOL) of AYA brain tumor patients. AYA patients and survivors require active intervention and support for returning to school or work, progressing to further education, finding employment, and preserving fertility. Recent cancer genome profiling revealed that AYA gliomas include pediatric- and adult-type genetic alteration. Insights into the biology underlying the distribution of tumors in AYAs may influence the development of prospective trials. A more individualized view of brain tumors may influence stratification of patients' in future clinical studies as well as selection for molecular targeted therapy. Here I review strategies for achieving a better outcome to decrease late effects and improve QOL.

NIR-Activated Multimodal Photothermal/Chemodynamic/Magnetic Resonance Imaging Nanoplatform for Anticancer Therapy by Fe(II) Ions Doped MXenes (Fe-Ti3 C2 ).

2D MXene, Ti3 C2 (TC), has displayed enormous potential in applications in photothermal therapy (PTT), attributing to its biocompatibility and outstanding photothermal conversion capability. However, some tumor ablations are difficult to be realized completely by monotherapy due to the essential defects of monotherapy and intricate tumor microenvironment (TME). In this work, the appropriate doped Fe2+ ions are anchored into the layers of 2D ultrathin TC nanosheets (TC NSs) to synthesize a novel multifunctional nanoshell of Fe(II)-Ti3 C2 (FTC) through interlayer electrostatic adsorption. FTC possesses superior photothermal conversion efficiency (PTCE) than TC NSs, attributing to the enhanced conductivity promoted by interlaminar ferrous ion-channels. Moreover, Fenton reaction based on ferrous ions endows FTC the abilities of reactive oxide species (ROS) releasing and glutathione (GSH) suppression triggered by near-infrared (NIR) laser, featuring splendid biocompatibility and curative effect in hypoxic TME. Meanwhile, magnetic resonance imaging (MRI) responding in FTC reveals the potential as an integrated diagnosis and treatment nanoplatform. FTC could provide new insights into the development of multimoded synergistic nanoplatform for biological applications, especially breaking the shackles of MXenes merely used as a photo-thermal agent (PTA), adopting it to bioimaging sensor and drug loading.

The Implementation of DNA Methylation Profiling into a Multistep Diagnostic Process in Pediatric Neuropathology: A 2-Year Real-World Experience by the French Neuropathology Network.

DNA methylation profiling has recently emerged as a powerful tool to help establish diagnosis in neuro-oncology. Here we present our national diagnostic strategy as the French neuropathology network (RENOCLIP-LOC) and our current approach of integrating DNA methylation profiling into our multistep diagnostic process for challenging pediatric CNS tumors. The tumors with diagnostic uncertainty were prospectively selected for DNA methylation after two rounds of review by neuropathology experts. We first integrated the classifier score into the histopathological findings. Subsequent analyses using t-SNE (t-Distributed Stochastic Neighbor Embedding) representation were performed. An additional step consisted of analyzing copy-number variation data (CNV). Finally, we combined all data to establish diagnoses and evaluated the impact of DNA methylation profiling on diagnostic and grading changes that would affect patient management. Over two years, 62 pediatric tumors were profiled. (1) Integrating the classifier score to the histopathological findings impacted the diagnosis in 33 cases (53%). (2) t-SNE analysis provided arguments for diagnosis in 26/35 cases with calibrated scores <0.84 (74.3%). (3) CNV investigations also evidenced alterations used for diagnosis and prognostication. (4) A diagnosis was finally established for 44 tumors (71%). Our results support the use of DNA methylation for challenging pediatric tumors. We demonstrated how additional methylation-based analyses complement the classifier score to support conventional histopathological diagnosis.

What Every Neuropathologist Needs to Know: Practical Aspects and Pitfalls in Molecular Diagnosis of Brain Tumors.

Molecular testing has become part of the routine diagnostic workup of brain tumors after the implementation of integrated histomolecular diagnoses in the 2016 WHO classification update. It is important for every neuropathologist to be aware of practical preanalytical, analytical, and postanalytical factors that impact the performance and interpretation of molecular tests. Prior to testing, optimizing tumor purity and tumor amount increases the ability of the molecular test to detect the genetic alteration of interest. Recognizing basic molecular testing platform analytical characteristics allows selection of the optimal platform for each clinicopathological scenario. Finally, postanalytical considerations to properly interpret molecular test results include understanding the clinical significance of the detected genetic alteration, recognizing that detected clinically significant genetic alterations are occasionally germline constitutional rather than somatic tumor-specific, and being cognizant that recommended and commonly used genetic nomenclature may differ. Potential pitfalls in brain tumor molecular diagnosis are also discussed.

A new deep learning approach integrated with clinical data for the dermoscopic differentiation of early melanomas from atypical nevi.

BACKGROUND: Timely recognition of malignant melanoma (MM) is challenging for dermatologists worldwide and represents the main determinant for mortality. Dermoscopic examination is influenced by dermatologists' experience and fails to achieve adequate accuracy and reproducibility in discriminating atypical nevi (AN) from early melanomas (EM). OBJECTIVE: We aimed to develop a Deep Convolutional Neural Network (DCNN) model able to support dermatologists in the classification and management of atypical melanocytic skin lesions (aMSL). METHODS: A training set (630 images), a validation set (135) and a testing set (214) were derived from the idScore dataset of 979 challenging aMSL cases in which the dermoscopic image is integrated with clinical data (age, sex, body site and diameter) and associated with histological data. A DCNN_aMSL architecture was designed and then trained on both dermoscopic images of aMSL and the clinical/anamnestic data, resulting in the integrated "iDCNN_aMSL" model. Responses of 111 dermatologists with different experience levels on both aMSL classification (intuitive diagnosis) and management decisions (no/long follow-up; short follow-up; excision/preventive excision) were compared with the DCNNs models. RESULTS: In the lesion classification study, the iDCNN_aMSL achieved the best accuracy, reaching an AUC = 90.3 %, SE = 86.5 % and SP = 73.6 %, compared to DCNN_aMSL (SE = 89.2 %, SP = 65.7 %) and intuitive diagnosis of dermatologists (SE = 77.0 %; SP = 61.4 %). CONCLUSIONS: The iDCNN_aMSL proved to be the best support tool for management decisions reducing the ratio of inappropriate excision. The proposed iDCNN_aMSL model can represent a valid support for dermatologists in discriminating AN from EM with high accuracy and for medical decision making by reducing their rates of inappropriate excisions.