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As the most prominent and ideal modality in female fertility preservation, ovarian tissue cryopreservation, and transplantation often confront the challenge of ischemic damage and follicular loss from avascular transplantation. To surmount this impediment, we engineered a novel platelet-derived factors-encapsulated fibrin hydrogel (PFH), a paradigmatic biomaterial. PFH encapsulates autologous platelet-derived factors, utilizing the physiological blood coagulation cascade for precise local delivery of bioactive molecules. In our study, PFH markedly bolstered the success of avascular ovarian tissue transplantation. Notably, the quantity and quality of follicles were preserved with improved neovascularization, accompanied by decreased DNA damage, increased ovulation, and superior embryonic development rates under a Low-concentration Platelet-rich plasma-derived factors encapsulated fibrin hydrogel (L-PFH) regimen. At a stabilized point of tissue engraftment, gene expression analysis mirrored normal ovarian tissue profiles, underscoring the effectiveness of L-PFH in mitigating the initial ischemic insult. This autologous blood-derived biomaterial, inspired by nature, capitalizes on the blood coagulation cascade, and combines biodegradability, biocompatibility, safety, and cost-effectiveness. The adjustable properties of this biomaterial, even in injectable form, extend its potential applications into the broader realm of personalized regenerative medicine. PFH emerges as a promising strategy to counter ischemic damage in tissue transplantation, signifying a broader therapeutic prospect. (197 words).

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Acute myeloid leukemia (AML) is a deadly form of leukemia with ineffective traditional treatment and frequent chemoresistance-associated relapse. Personalized drug screening holds promise in identifying optimal regimen, nevertheless, primary AML cells undergo spontaneous apoptosis during cultures, invalidating the drug screening results. Here, we reconstitute a 3D osteogenic niche (3DON) mimicking that in bone marrow to support primary AML cell survival and phenotype maintenance in cultures. Specifically, 3DON derived from osteogenically differentiated mesenchymal stem cells (MSC) from healthy and AML donors are co-cultured with primary AML cells. The AML cells under the AML_3DON niche showed enhanced viability, reduced apoptosis and maintained CD33+ CD34-phenotype, associating with elevated secretion of anti-apoptotic cytokines in the AML_3DON niche. Moreover, AML cells under the AML_3DON niche exhibited low sensitivity to two FDA-approved chemotherapeutic drugs, further suggesting the physiological resemblance of the AML_3DON niche. Most interestingly, AML cells co-cultured with the healthy_3DON niche are highly sensitive to the same sample drugs. This study demonstrates the differential responses of AML cells towards leukemic and healthy bone marrow niches, suggesting the impact of native cancer cell niche in drug screening, and the potential of re-engineering healthy bone marrow niche in AML patients as chemotherapeutic adjuvants overcoming chemoresistance, respectively.

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BACKGROUND: Metabolic syndrome (MetS) is a chronic disorder featuring overweight/obesity, high blood pressure, and dysfunction of lipid and carbohydrate metabolism. Microbiome-modulating probiotics, prebiotics, synbiotics and fecal microbiota transplant (FMT) are promising adjunct therapies for improving parameters of glucose homeostasis and insulinemia. METHODS: We conducted a comprehensive systematic review, meta-analyses, and meta-regressions to investigate the effect of the abovementioned microbiome therapies on various biomarkers after screening clinical trials published through April 2023. We pooled data using random effects meta-analyses, reporting them as mean differences (MDs) with 95 % confidence intervals (CIs), and conducting univariate linear model meta-regressions. RESULTS: Data from 21 trial comparisons across 19 studies (n = 911) revealed that, compared to placebo/control, microbiome-modulating therapies were associated with statistically significant changes in fasting plasma glucose (MD: 4.03 mg/dL [95%CI: 6.93; -1.13]; p effect = 0.006, I2 = 89.8 %), and fasting insulin (MD: 2.56 µU/mL [95%CI: 4.28; -0.84]; p effect = 0.004, I2 = 87.9 %), but not insulin resistance or sensitivity indices and HbA1c. Age, baseline BMI, baseline biomarker value, pro/synbiotic dosage, trial duration, nutraceutical type, and WHO region were factors affecting the efficacy of these interventions at producing changes in biomarkers, signaling the potential role of personalized precision medicine adjunct therapy for deranged glucose homeostasis in patients with MetS. Nevertheless, presence of heterogeneity calls for further investigation before their clinical application. CONCLUSIONS: Probiotics, prebiotics, synbiotics and FMT supplementation improved fasting glucose and insulin in patients with MetS. Further large-scale and high-quality trials are required before potential clinical applications.

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OBJECTIVE: Modifying cognitive distortions, or thinking errors, is crucial in eating disorders (ED) treatment. To address the lack of a personalized measure for ED cognitions, the Thought Inventory was developed. The study aimed to establish its feasibility and validity, identify thinking error contents and types, examine changes in belief of irrational thoughts, and investigate associations with change in ED symptoms. Hypotheses, procedure, and planned analyses were pre-registered to ensure transparency. METHODS: Participants (N = 55) completed the Thought Inventory, the Eating Disorder Examination Questionnaire, the Eating Pathology Symptom Inventory, the Frost Multidimensional Perfectionism Scale, the Beck Depression Inventory, and the Penn State Worry Questionnaire at pre-and post-ten weeks of treatment. Using the Thought Inventory, participants collaborated with study therapists to identify ED-related thinking errors and rate the degree of belief in these thoughts on a scale of 0 to 100 %. RESULTS: Cognitions primarily contained self-judgments, food rules, and concern over shape, while catastrophizing/fortune telling, emotional reasoning, and should/must statements were the most common types of thinking errors. Belief in cognitions significantly decreased over treatment and change in thought belief was positively associated with change in ED symptoms. CONCLUSION: The Thought Inventory shows promise as a personalized measure. Future research should explore whether ED cognitions, assessed in this manner, are a mechanism of change in ED treatment.

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Both ischemic and hemorrhagic strokes are critical health issues and the incidence is on the rise. The rapid neurological degeneration that can occur with either type of stroke warrants prompt medical attention. In the article, we critically reviewed the literature examining their incidence, pathophysiology, and present treatment strategies. Clinical trials show conflicting findings, with ischemic strokes accounting for 87% of all strokes. Brain injury following an ischemic stroke results in cell death and necrosis, immune cells being the primary actors in the process of neuroinflammation. In order to develop neuroprotective drugs against ischemic stroke, detailed investigation of glutamate production and metabolism as well as downstream pathways controlled by glutamate receptors provides significant information on the underlying mechanisms. The permeability of the blood-brain barrier and the degradation of glutamine synthase are two potential mechanisms by which peritoneal dialysis accelerates brain-to-blood glutamate clearance and thus reduces glutamate levels in the brain after a stroke. Oxidative stress in an ischemic stroke disturbs the oxidant-antioxidant balance, which is particularly problematic for brain cells that are high in polyunsaturated fatty acids. Because of demographic factors like age, sex, race/ethnicity, and socioeconomic status, the incidence and prevalence of stroke differ across people and regions. For rapid diagnosis and treatment decisions, diagnostic imaging tools such as vascular imaging, CT, and MRI are essential. To aid in the recovery and lessen neurological impairments following a stroke, novel avenues of research are under investigation on neuroprotective medications that target inflammation, oxidative stress, and neuronal death.

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Depression is a prevalent mental health disorder that significantly impacts primary care settings. This editorial explores the potential of artificial intelligence (AI)-powered chatbots in managing depression within primary care environments. AI chatbots offer innovative solutions to challenges faced by healthcare providers, including limited appointment times, delayed access to specialists, and stigma associated with mental health issues. These digital tools provide continuous support, personalized interactions, and early symptom detection, potentially improving accessibility and outcomes in depression management. The integration of AI chatbots in primary care presents opportunities for round-the-clock patient support, personalized interventions, and the reduction of mental health stigma. However, challenges persist, including concerns about assessment accuracy, data privacy, and integration with existing healthcare systems. Successful implementation requires systematic approaches, stakeholder engagement, and comprehensive training for healthcare providers. Ethical considerations, such as ensuring informed consent, managing algorithmic biases, and maintaining the human element in care, are crucial for responsible deployment. As AI technology evolves, future directions may include enhanced natural language processing, multimodal integration, and AI-augmented clinical decision support. This editorial emphasizes the need for a balanced approach that leverages the potential of AI while acknowledging its limitations and the irreplaceable value of human clinical judgment in depression management within primary care settings.

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Introduction: Cervical cancer represents one of the main causes of female, cancer-related mortality worldwide. The majority of cancers are caused by human papillomaviruses such as HPV16 and HPV18. As chemotherapeutic resistance to first-line platinum treatment is still a predominant clinical challenge in advanced cervical cancer, novel treatment options including combinatorial therapies are urgently required to overcome chemotherapeutic resistance. Inhibition of A Disintegrin And Metalloproteinase (ADAM)-family members, heavily involved in tumour progression of a vast range of solid tumours, strongly improved response to chemotherapeutic treatment in other tumour entities including ovarian cancer. Methods: We established two- and three-dimensional models derived from three traditional cervical cancer cell lines and ectocervical cancer-derived organoids. Following characterisation, these models were used to investigate their response to cisplatin treatment in the absence and presence of ADAM inhibitors using viability assays and automated live cell imaging. Results: The pivotal role of the metalloprotease ADAM17 driving chemotherapy resistance was detectable in all ectocervical cultures irrespective of the model system used, whereas ADAM10 inhibition was predominantly effective only in loosely aggregated spheroids. We showed prominent differences regarding treatment responses between 2D monolayers compared to 3D spheroid and 3D organoid model systems. Particularly, the organoid system, regarded as the closest representation of primary tumours, exhibited reliably the combinatorial effect of ADAM17 inhibition and cisplatin in all three individual donors. Discussion: As two- and three-dimensional models of the same cell lines differ in their responses to chemotherapy it is essential to validate treatment strategies in more advanced model systems representing the patient situation more realistically. Ectocervical organoids showed reliable results regarding treatment responses closely mimicking the primary tumours and could therefore serve as an important tool for personalized medicine in cervical cancer. These findings strengthen the role of ADAM17 as a potential novel target for combinatorial treatments to overcome chemoresistance in cervical cancer.

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Amyotrophic lateral sclerosis (ALS) characterized by progressive degeneration of motor neurons is a debilitating disease, posing substantial challenges in both prognosis and daily life assistance. However, with the advancement of machine learning (ML) which is renowned for tackling many real-world settings, it can offer unprecedented opportunities in prognostic studies and facilitate individuals with ALS in motor-imagery tasks. ML models, such as random forests (RF), have emerged as the most common and effective algorithms for predicting disease progression and survival time in ALS. The findings revealed that RF models had an excellent predictive performance for ALS, with a testing R2 of 0.524 and minimal treatment effects of 0.0717 for patient survival time. Despite significant limitations in sample size, with a maximum of 18 participants, which may not adequately reflect the population diversity being studied, ML approaches have been effectively applied to ALS datasets, and numerous prognostic models have been tested using neuroimaging data, longitudinal datasets, and core clinical variables. In many literatures, the constraints of ML models are seldom explicitly enunciated. Therefore, the main objective of this research is to provide a review of the most significant studies on the usage of ML models for analyzing ALS. This review covers a variation of ML algorithms involved in applications in ALS prognosis besides, leveraging ML to improve the efficacy of brain-computer interfaces (BCIs) for ALS individuals in later stages with restricted voluntary muscular control. The key future advances in individualized care and ALS prognosis may include the advancement of more personalized care aids that enable real-time input and ongoing validation of ML in diverse healthcare contexts.

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Systemic lupus erythematosus (SLE) is a chronic, heterogeneous, systemic autoimmune disease characterized by autoantibody production, complement activation, and immune complex deposition. SLE predominantly affects young, middle-aged, and child-bearing women with episodes of flare-up and remission, although it affects males at a much lower frequency (female: male; 7:1 to 15:1). Technological and molecular advancements have helped in patient stratification and improved patient prognosis, morbidity, and treatment regimens overall, impacting quality of life. Despite several attempts to comprehend the pathogenesis of SLE, knowledge about the precise molecular mechanisms underlying this disease is still lacking. The current treatment options for SLE are pragmatic and aim to develop composite biomarkers for daily practice, which necessitates the robust development of novel treatment strategies and drugs targeting specific responsive pathways. In this communication, we review and aim to explore emerging therapeutic modalities, including multiomics-based approaches, rational drug design, and CAR-T-cell-based immunotherapy, for the management of SLE.

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BACKGROUND: Pharmacogenetics/pharmacogenomics (PGx) focuses on the genetic variation that causes the heterogeneity of pharmacokinetics and drug response among individuals and has the potential to predict individual efficacy and/or side effects. This study aims to investigate and understand the implementation of genetic testing for the personalized medication (GTPM) in children's hospitals in Mainland China. METHODS: A survey was conducted on 50 children's hospitals from 31 provinces, municipalities, and autonomous regions across Mainland China, and statistical analysis and recommendations were made. RESULTS: Questionnaire response was rate of 76.0% (38/50). Data from 15 hospitals conducting GTPM were included in this study, but only 6 hospitals had offered PGx tests for no less than five drug-related genes, and only 5 hospitals had covered more than ten drugs, which was a small scale overall. 20.0% of the laboratories did not conduct internal quality control, and 33.3% did not participate in inter-laboratory quality assessment. 46.7% of the practitioners did not receive external training. The primary goal for GTPM was to optimize drug dosage in the 15 hospitals, while the main challenge for GTPM was the implementation cost. CONCLUSION: Although GTPM in pediatrics has made major progress in Mainland China in recent years, there were still various problems in terms of software, hardware configuration, personnel allocation, business scale, quality control, and result interpretation. This requires joint efforts of health administration, medical insurance departments, researchers, and hospitals to promote and improve GTPM.

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Endoplasmic reticulum stress (ERS) becomes a significant factor in inflammatory bowel disease (IBD), like Crohn's disease (CD) and ulcerative colitis (UC). Our research was aimed at identifying molecular markers to enhance our understanding of ERS and inflammation in IBD, recognizing risk factors and high-risk groups at the molecular level, and developing a predictive model on the grounds of based on ERS-associated genes. This research adopted the least absolute shrinkage and selection operator (LASSO) regression and logistic regression to build a predictive model, and categorized IBD patients into high- and low-risk groups, and then identified four gene clusters. Our key findings included a significant increase in drug target gene expression in high-risk groups, notable discrepancies in immune levels, and functions between high-risk and low-risk groups. Notably, the TAP1 gene emerged as a strong predictor with the highest diagnostic value (area under the curve [AUC] = 0.941). TAP1 encodes proteins required for antigenic peptide transfer across the endoplasmic reticulum (ER) membrane, and its potential as a diagnostic marker and therapeutic target is reflected by its overexpression in IBD tissues. Our study established a new ERS-associated gene model which could forecast the risk, immunological status, and treatment efficacy of patients with IBD. These findings suggest potential targets for personalized therapy and highlight the significance of ERS in the etiology and therapy of IBD. Future studies should explore the therapeutic potential of targeting TAP1 and other ERS-related genes for IBD management.

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Endometrial cancer is a complex disease influenced by both somatic and germline mutations. While individual mutations in genes such as PTEN, PIK3CA, and members of the DNA mismatch repair (MMR) system have been extensively studied, comprehensive analyses comparing somatic and germline mutations within the same cohort are limited. This study compares these mutations using whole exome sequencing (WES) data from tumor and blood samples in patients with endometrial cancer. Thirteen female patients with histologically confirmed endometrial cancer were selected. Tumor tissues and matched blood samples were collected and subjected to WES at the CeGaT laboratory, followed by bioinformatics analysis and annotation using the Geneyx platform. WES revealed significant somatic and germline DNA mutations, with key pathogenic variants identified in genes such as PTEN, PIK3CA, TP53, MLH1, and MSH2. Comparative analysis showed distinct and overlapping mutation profiles, highlighting the importance of integrating somatic and germline data in endometrial cancer research.

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Over the course of several decades, anticancer treatment with chemotherapy drugs for lung cancer has not changed significantly. Unfortunately, this treatment prolongs the patient's life only by a few months, causing many side effects in the human body. It has also been proven that drugs such as Cisplatin, Carboplatin, Oxaliplatin and others can react with other substances containing an aromatic ring in which the nitrogen atom has a free electron group in its structure. Thus, such structures may have a competitive effect on the nucleobases of DNA. Therefore, scientists are looking not only for new drugs, but also for new alternative ways of delivering the drug to the cancer site. Nanotechnology seems to be a great hope in this matter. Creating a new nanomedicine would reduce the dose of the drug to an absolute minimum, and thus limit the toxic effect of the drug; it would allow for the exclusion of interactions with competitive compounds with a structure similar to nucleobases; it would also permit using the so-called targeted treatment and bypassing healthy cells; it would allow for the introduction of other treatment options, such as radiotherapy directly to the cancer site; and it would provide diagnostic possibilities. This article is a review that aims to systematize the knowledge regarding the anticancer treatment of lung cancer, but not only. It shows the clear possibility of interactions of chemotherapeutics with compounds competitive to the nitrogenous bases of DNA. It also shows the possibilities of using nanostructures as potential Platinum drug carriers, and proves that nanomedicine can easily become a new medicinal product in personalized medicine.

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BACKGROUND: Predictions based on patient-derived materials of CFTR modulators efficacy have been performed lately in patient-derived cells, extending FDA-approved drugs for CF patients harboring rare variants. Here we developed intestinal organoids from subjects carrying S737F- and T465N-CFTR in trans with null alleles to evaluate their functional impact on CFTR protein function and their restoration upon CFTR modulator treatment. The characterization of S737F-CFTR was performed in two subjects recently assessed in nasal epithelial cells but not in colonoids. RESULTS: Our functional analysis (Ussing chamber) confirmed that S737F-CFTR is a mild variant with residual function as investigated in colonoids of patients with S737F/Dele22-24 and S737F/W1282X genotypes. An increase of current upon Elexacaftor/Tezacaftor/Ivacaftor (ETI) treatment was recorded for the former genotype. T465N is a poorly characterized missense variant that strongly impacts CFTR function, as almost no CFTR-mediated anion secretion was registered for T465N/Q39X colonoids. ETI treatment substantially improved CFTR-mediated anion secretion and increased the rescue of mature CFTR expression compared to either untreated colonoids or to dual CFTR modulator therapies. CONCLUSIONS: Our study confirms the presence of a residual function of the S737F variant and its limited response to CFTR modulators while predicting for the first time the potential clinical benefit of Trikafta® for patients carrying the rare T465N variant.

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Chronic lymphocytic leukemia (CLL) is the most common form of leukemia among adults in Western countries. Despite the introduction of targeted therapies, including first-line Bruton's tyrosine kinase inhibitor (BTKi) treatment, CLL remains largely incurable. Frequent disease relapses occur due to remaining treatment-resistant CLL cells, calling for novel therapies to eliminate minimal residual disease (MRD). Peptide-based vaccination targeting human leucocyte antigen (HLA)-presented CLL-associated antigens represents a promising, low-side-effect therapeutic option to optimize treatment responses and eliminate residual tumor cells by inducing an anti-leukemic immune response. The iVAC-XS15-CLL01 trial is an open-label, first-in-human (FIH) Phase I trial, evaluating the CLL-VAC-XS15 vaccine in CLL patients undergoing BTKi-based therapy. The vaccine was developed from HLA-presented CLL-associated antigen peptides, identified through comparative mass-spectrometry-based immunopeptidome analyses of CLL versus healthy samples in a previous study. To facilitate rapid and cost-effective deployment, vaccine peptides are selected for each patient from a pre-manufactured "peptide warehouse" based on the patient's individual HLA allotype and CLL immunopeptidome. The trial enrolls 20 CLL patients, who receive up to three doses of the vaccine, adjuvanted with the toll-like-receptor (TLR) 1/2 ligand XS15 and emulsified in Montanide ISA 51 VG. The primary objective of the iVAC-XS15-CLL01 trial is to assess the safety and immunogenicity of the CLL-VAC-XS15 vaccine. Secondary objectives are to evaluate the vaccine impact on MRD, progression-free survival, and overall survival, as well as comprehensive immunophenotyping to characterize vaccine-induced T-cell responses. This Phase I trial aims to advance CLL treatment by enhancing immune-mediated disease clearance and guiding the design of subsequent Phase II/III trials to implement a new therapeutic strategy for CLL patients.

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Breast cancer is the most common malignant tumor in women. Due to the high heterogeneity of breast cancer cells, traditional in vitro research models still have major limitations. Therefore, it is urgent to establish an experimental model that can accurately simulate the characteristics of human breast cancer. Breast cancer organoid technology emerged as the times required, that is, to construct tissue analogs with organ characteristics by using a patient's tumor tissue through 3D culture in vitro. Since the breast cancer organoid can fully preserve the histology and genetic characteristics of the original tumor, it provides a reliable model for preclinical drug screening, establishment of breast cancer organoid biobanks, research into the mechanisms of tumor development, and determination of cancer targets. It has promoted personalized treatment for clinical breast cancer patients. This article mainly focuses on recent research progress and applications of organoid technology in breast cancer, discussing the current limitations and prospects of breast cancer organoid technology.

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This narrative review examines the promising potential of integrating artificial intelligence (AI) with CRISPR-Cas9 genome editing to advance CAR T-cell therapy. AI algorithms offer unparalleled precision in identifying genetic targets, essential for enhancing the therapeutic efficacy of CAR T-cell treatments. This precision is critical for eliminating negative regulatory elements that undermine therapy effectiveness. Additionally, AI streamlines the manufacturing process, significantly reducing costs and increasing accessibility, thereby encouraging further research and development investment. A key benefit of AI integration is improved safety; by predicting and minimizing off-target effects, AI enhances the specificity of CRISPR-Cas9 edits, contributing to safer CAR T-cell therapy. This advancement is crucial for patient safety and broader clinical adoption. The convergence of AI and CRISPR-Cas9 has transformative potential, poised to revolutionize personalized immunotherapy. These innovations could expand the application of CAR T-cell therapy beyond hematologic malignancies to various solid tumors and other non-hematologic conditions, heralding a new era in cancer treatment that substantially improves patient outcomes.

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Depression is a heterogenous diagnostic construct; however, dynamic interactions between specific depressive symptoms across their qualitatively different profiles remain largely unknown. The study aimed to recognize the most prevalent profiles of depressive symptoms and assess their dynamics in young adults without a history of psychiatric treatment. Depressive symptoms were recorded using the Patient Health Questionnaire-9 (PHQ-9). The data were assessed for all theoretical and empirical combinations of depressive symptoms in participants with a positive screening for depression. The profiles identified in the majority of participants were analyzed using partial correlation and Bayesian networks. Data from 3583 individuals with a positive screening for depression were analyzed. Out of 382 theoretical profiles, 150 profiles (39.3%) were present in this dataset. The majority of participants (56.8%) showed 4 profiles of depressive symptoms including the profile with all depressive symptoms present, the profile without suicidal ideation, the profile without psychomotor impairment, and the profile without both psychomotor impairment and suicidal ideation. The profiles differed largely in terms of their dynamics and symptoms that are necessary to activate the whole network. The network characteristics within specific profiles did not differ significantly across the level of difficulties attributable to depressive symptoms. Our findings indicate that depression emerging in young adults shows a limited number of symptom profiles. However, dynamics of depressive symptoms differs largely between specific profiles regardless of functional impairment indicating the need to personalize therapeutic approaches. Future studies should further disentangle the heterogeneity of depressive symptoms, e.g., by dissecting the symptoms that are combined together by single PHQ-9 items (i.e., hypersomnia and insomnia; psychomotor agitation and retardation).

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BACKGROUND: Pulmonary arterial hypertension (PAH) is a major concern in patients with Down syndrome (DS) and congenital heart disease (CHD). Understanding the unique characteristics of PAH in these populations is essential for developing tailored management strategies. This review examines differences in PAH between DS and non-DS (nDS) patients with CHD, focusing on pathophysiology, clinical presentation, hemodynamic profiles, and treatment outcomes. METHODS: A retrospective analysis of 93 adults with PAH was conducted, including 18 with DS and 75 with CHD but without DS (nDS). Data on demographics, clinical presentations, comorbidities, and hemodynamic parameters were collected using echocardiography and right heart catheterization. Statistical analyses included Mann-Whitney U tests, Student's t-tests, and Kaplan-Meier survival analysis to compare the DS and nDS groups. RESULTS: DS patients presented with PAH at a younger age (mean age 25.06 years) compared to nDS patients (mean age 42.4 years; p < 0.001). Hypothyroidism was more prevalent in DS patients (61.1 %) than in nDS patients (29.3 %; p = 0.012). Hemodynamic assessments showed lower mean arterial pressure (MAP) in DS patients (76.24 ± 11.6 mmHg) versus nDS patients (93.95 ± 15 mmHg; p < 0.001), and a higher TAPSE/PASP ratio (0.41 vs. 0.23; p = 0.009), suggesting less severe right ventricular dysfunction. DS patients had a significant survival advantage over nDS patients (p = 0.043). CONCLUSIONS: DS patients have distinct clinical and hemodynamic profiles in PAH, requiring personalized management. Early detection and tailored treatment are crucial for improving outcomes. Further research should refine these strategies and explore new therapies.

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BACKGROUND: Two-stage models of heterogenous treatment effects (HTE) may advance personalized medicine in multiple sclerosis (MS). Brain atrophy is a relatively objective outcome measure that has strong relationships to MS prognosis and treatment effects and is enabled by standardized MRI. OBJECTIVES: To predict brain atrophy outcomes for patients initiating disease-modifying therapies (DMT) with different efficacies, considering the patients' baseline brain atrophy risk measured via brain parenchymal fraction (BPF). METHODS: Analyses included patients enrolled in the Multiple Sclerosis Partners Advancing Technology and Health Solutions (MS PATHS) network who started DMT and had complete baseline data and ≥ 6-month brain MRI follow-up. All brain MRIs were acquired using standardized acquisition sequences on Siemens 3T scanners. BPF change risk was derived by linear mixed effects models using baseline covariates. Model performance was assessed by predicted versus actual BPF change R2. Propensity score (PS) weighting was used to balance covariates between groups defined by DMT efficacy (high: natalizumab, alemtuzumab, ocrelizumab, and rituximab; moderate: dimethyl fumarate, fingolimod, and cladribine; low: teriflunomide, interferons, and glatiramer acetate). HTE models predicting 1 year change in BPF were built using a weighted linear mixed effects model with low-efficacy DMT as the reference. RESULTS: Analyses included 581 high-, 183 moderate-, and 106 low-efficacy DMT-treated patients. The mean and median number of brain MRI observations per treatment period were 2.9 and 3.0, respectively. Risk model performance R2=0.55. After PS weighting, covariate standardized mean differences were <10 %, indicating excellent balance across measured variables. Changes in BPF between baseline and follow-up were found to be statistically significant (p < 0.001), suggesting a pathological change. Patients with low brain atrophy risk had a similar outcome regardless of DMT selection. In patients with high brain atrophy risk, high- and moderate-efficacy DMTs performed similarly, while a 2-fold worse BPF change was predicted for patients selecting low-efficacy DMTs (p < 0.001). Similar results were observed in a sensitivity analysis adjusting for pseudoatrophy effects in a sub-population of patients treated with natalizumab. CONCLUSIONS: The relative benefit of selecting higher efficacy treatments may vary depending on patients' baseline brain atrophy risk. Poor outcomes are predicted in individuals with high baseline risk who are treated with low-efficacy DMTs.