UNASSIGNED: Clear cell renal cell carcinoma (ccRCC) is a metabolic disorder characterized by abnormal lipid accumulation in the cytoplasm. Lipid metabolism-related genes may have important clinical significance for prognosis prediction and individualized treatment.
UNASSIGNED: We collected bulk and single-cell transcriptomic data of ccRCC and normal samples to identify key lipid metabolism-related prognostic signatures. qPCR was used to confirm the expression of signatures in cancer cell lines. Based on the identified signatures, we developed a lipid metabolism risk score (LMRS) as a risk index. We explored the potential application value of prognostic signatures and LMRS in precise treatment from multiple perspectives.
UNASSIGNED: Through comprehensive analysis, we identified five lipid metabolism-related prognostic signatures (ACADM, ACAT1, ECHS1, HPGD, DGKZ). We developed a risk index LMRS, which was significantly associated with poor prognosis in patients. There was a significant correlation between LMRS and the infiltration levels of multiple immune cells. Patients with high LMRS may be more likely to respond to immunotherapy. The different LMRS groups were suitable for different anticancer drug treatment regimens.
UNASSIGNED: Prognostic signatures and LMRS we developed may be applied to the risk assessment of ccRCC patients, which may have potential guiding significance in the diagnosis and precise treatment of ccRCC patients.

Migraine, a prevalent neurological disorder, affects approximately 14.1% of the global population and disproportionately impacts females. This debilitating condition significantly compromises quality of life, productivity, and incurs high healthcare costs, presenting a challenge not only to individuals but to societal structures as a whole. Despite advances in our understanding of migraine pathophysiology, treatment options remain limited, necessitating ongoing research into effective therapies. This review delves into the complexity of migraine management, examining the roles of genetic predisposition, environmental influences, personalized treatment approaches, comorbidities, efficacy and safety of existing acute and preventive treatments. It further explores the continuum between migraine and tension-type headaches and discusses the intricacies of treating various migraine subtypes, including those with and without aura. We emphasize the recent paradigm shift toward trigeminovascular activation and the release of vasoactive substances, such as calcitonin gene-related peptide (CGRP), which offer novel therapeutic targets. We assess groundbreaking clinical trials, pharmacokinetic and pharmacodynamic perspectives, safety, tolerability, and the real-world application of CGRP monoclonal antibodies and gepants. In the face of persisting treatment barriers such as misdiagnosis, medication overuse headaches, and limited access to specialist care, we discuss innovative CGRP-targeted strategies, the high cost and scarcity of long-term efficacy data, and suggest comprehensive solutions tailored to Turkiye and developing countries. The review offers strategic recommendations including the formulation of primary care guidelines, establishment of specialized outpatient clinics, updating physicians on novel treatments, enhancing global accessibility to advanced therapies, and fostering patient education. Emphasizing the importance of lifestyle modifications and holistic approaches, the review underscores the potential of mass media and patient groups in disseminating critical health information and shaping the future of migraine management.

BACKGROUND: Decades of research have firmly established that cognitive health and cognitive treatment services are a key need for people living with psychosis. However, many current clinical programs do not address this need, despite the essential role that an individual\'s cognitive and social cognitive capacities play in determining their real-world functioning. Preliminary practice-based research in the Early Psychosis Intervention Network early psychosis intervention network shows that it is possible to develop and implement tools that delineate an individuals\' cognitive health profile and that help engage the client and the clinician in shared decision-making and treatment planning that includes cognitive treatments. These findings signify a promising shift toward personalized cognitive health.
METHODS: Extending upon this early progress, we review the concept of interindividual variability in cognitive domains/processes in psychosis as the basis for offering personalized treatment plans. We present evidence from studies that have used traditional neuropsychological measures as well as findings from emerging computational studies that leverage trial-by-trial behavior data to illuminate the different latent strategies that individuals employ.
UNASSIGNED: We posit that these computational techniques, when combined with traditional cognitive assessments, can enrich our understanding of individual differences in treatment needs, which in turn can guide evermore personalized interventions.
CONCLUSIONS: As we find clinically relevant ways to decompose maladaptive behaviors into separate latent cognitive elements captured by model parameters, the ultimate goal is to develop and implement approaches that empower clients and their clinical providers to leverage individual\'s existing learning capacities to improve their cognitive health and well-being.

Cervical cancer represents a global health issue as it is mostly encountered in women of reproductive age, while at the same time, survival outcomes seem to have remained constant during the last two decades. The need to implement fertility-sparing strategies as well as to decrease the morbidity that accompanies radical treatment has been extensively studied. During the last decade, several randomized clinical trials have been released, resulting in significant advances in the surgical treatment of early-stage disease. At the same time, evidence about the surgical treatment of advanced-stage disease as well as recurrent disease has gradually appeared and seems to be promising, thus leading the point forward towards personalized medicine that will remove the surgical barriers that seem concrete in our era. Nevertheless, the discrepancies in perioperative morbidity and survival outcomes that were observed among published studies raise several questions. In the present article, we chose to review the gray fields in the surgical treatment of early-stage and advanced-stage cervical cancer. Studies that are based on strong evidence that support current clinical practice are compared to smaller cohorts that present novel data that may form the basis for future research, and issues that remain poorly explored are discussed in an effort to help establish a consensus for future research development.

The goal-setting process is pivotal in managing patients with disabling spasticity. This case-control study assessed the role of diagnostic nerve blocks in guiding the goal-setting process within goal-targeted treatment of spasticity with botulinum neurotoxin-A. In this case-control study, patients with disabling spasticity underwent either a goal-setting process based on the patient\'s needs and clinical evaluation (control group) or additional diagnostic nerve block procedures (case group). All enrolled patients underwent a focal treatment with botulinum neurotoxin-A injection and a 1-month follow-up evaluation during which goal achievement was quantified using the goal attainment scaling-light score system. Data showed a higher goal achievement rate in the case group (70%) than in the control group (40%). In conclusion, diagnostic nerve blocks may help guide the goal-setting process within goal-targeted treatment of spasticity with botulinum neurotoxin-A towards more realistic and achievable goals, thereby improving the outcomes of botulinum neurotoxin-A injection. Future studies should better explore the role of diagnostic nerve blocks to further personalize botulinum neurotoxin-A according to individual patients\' preferences and requirements.

Prostate cancer is one of the most prevalent malignancies in men. In the United States, 1 in 8 men will be diagnosed with prostate cancer in their lifetime. Specifically, studies have delved into male subgroups that present a heightened risk for prostate cancer. Despite such high prevalence, prostate cancer can be heterogeneous and carry complexities that manifest differently between individuals. Metastatic hormone-sensitive prostate cancer (mHSPC) often has an abbreviated, aggressive disease course, and can have varying presentations with different molecular profiles that determine response/resistance to the approved treatments targeting the androgen-receptor pathway (eg, enzalutamide, apalutamide, darolutamide, and abiraterone acetate). We present a case of mHSPC quickly progressing to mCRPC, found to have microsatellite instability in mCRPC and excellent response to pembrolizumab, which raises the critical issues of early molecular testing and treatments personalized for the individual patient.

Lung cancer is categorized into two main types: non-small cell lung cancer (NSCLC) and small cell lung cancer. Of these, NSCLC accounts for approximately 85% of all cases and encompasses varieties such as squamous cell carcinoma and adenocarcinoma. For patients with advanced NSCLC that do not have oncogene addiction, the preferred treatment approach is a combination of immunotherapy and chemotherapy. However, the progression-free survival (PFS) typically ranges only from about 6 to 8 months, accompanied by certain adverse events. In order to carry out individualized treatment more effectively, it is urgent to accurately screen patients with PFS for more than 12 months under this treatment regimen. Therefore, this study undertook a retrospective collection of pulmonary CT images from 60 patients diagnosed with NSCLC treated at the First Affiliated Hospital of Wenzhou Medical University. It developed a machine learning model, designated as bSGSRIME-SVM, which integrates the rime optimization algorithm with self-adaptive Gaussian kernel probability search (SGSRIME) and support vector machine (SVM) classifier. Specifically, the model initiates its process by employing the SGSRIME algorithm to identify pivotal image features. Subsequently, it utilizes an SVM classifier to assess these features, aiming to enhance the model\'s predictive accuracy. Initially, the superior optimization capability and robustness of SGSRIME in IEEE CEC 2017 benchmark functions were validated. Subsequently, employing color moments and gray-level co-occurrence matrix methods, image features were extracted from images of 60 NSCLC patients undergoing immunotherapy combined with chemotherapy. The developed model was then utilized for analysis. The results indicate a significant advantage of the model in predicting the efficacy of immunotherapy combined with chemotherapy for NSCLC, with an accuracy of 92.381% and a specificity of 96.667%. This lays the foundation for more accurate PFS predictions and personalized treatment plans.

Endometrial cancer (EC) accounts for 90% of uterine cancer cases. It is considered not only one of the most common gynecological malignancies but also one of the most frequent cancers among women overall. Nowadays, the differentiation of EC subtypes is based on immunohistochemistry and molecular techniques. It is considered that patients\' prognosis and the implementation of the appropriate treatment depend on the cancer subtype. Patients with pathogenic variants in POLE have the most favorable outcome, while those with abnormal p53 protein have the poorest. Therefore, in patients with POLE mutation, the de-escalation of postoperative treatment may be considered, and patients with abnormal p53 protein should be subjected to intensive adjuvant therapy. Patients with a DNA mismatch repair (dMMR) deficiency are classified in the intermediate prognosis group as EC patients without a specific molecular profile. Immunotherapy has been recognized as an effective treatment method in patients with advanced or recurrent EC with a mismatch deficiency. Thus, different adjuvant therapy approaches, including targeted therapy and immunotherapy, are being proposed depending on the EC subtype, and international guidelines, such as those published by ESMO and ESGO/ESTRO/ESP, include recommendations for performing the molecular classification of all EC cases. The decision about adjuvant therapy selection has to be based not only on clinical data and histological type and stage of cancer, but, following international recommendations, has to include EC molecular subtyping. This review describes how molecular classification could support more optimal therapeutic management in endometrial cancer patients.

BACKGROUND: Programmed death 1 (PD-1)/programmed death 1 ligand 1 (PD-L1)-directed immunotherapy has revolutionized the treatments for advanced non-small cell lung cancer (NSCLC), whereas the optimal therapeutic combinations remain uncertain.
METHODS: Our study encompassed phase Ⅱ/III randomized controlled trials (RCTs) that involved anti-PD-(L)1-based therapies for stage-IV NSCLC. The primary outcomes included overall survival (OS), progression-free survival (PFS), objective response rate (ORR), and incidences of adverse events (AEs). Subgroup analyses were conducted by treatment lines, PD-L1 expression levels, histological types, and metastatic sites.
RESULTS: Our analysis incorporated 38 publications, covering 14 therapeutic combinations and involving 18,048 participants. PD-(L)1+chemotherapy (CT), PD-(L)1+ cytotoxic T lymphocyte-associated antigen-4 (CTLA4) +CT, and PD-(L)1+ T-cell immunoglobulin and ITIM domain (TIGIT) were notably effective in prolonging OS. Overall, PD-(L)1+CT and PD-(L)1+CT+ vascular endothelial growth factor (VEGF) were significantly beneficial for PFS and ORR. As for the subsequent-line treatments, incorporating radiotherapy can enhance PFS and ORR (ranked fourth among enrolled treatments). For patients with PD-L1 < 1%, PD-(L)1+CT+VEGF and PD-(L)1+CTLA4+CT were favorable approaches. Conversely, in patients with PD-L1 ≥ 50%, PD-(L)1+CT represented an effective treatment. Patients with non-squamous cell carcinoma or liver metastases might benefit from the addition of VEGF. In cases of squamous cell carcinoma or brain metastases, the combination of PD-(L)1+CTLA4+CT yielded superior benefits.
CONCLUSIONS: This study underscores the enhanced efficacy of combination immunotherapies over monotherapy. It highlights the necessity for personalized treatment, considering individual factors. These insights are vital for clinical decision-making in the management of advanced NSCLC.

Enzymes in peri-implant sulcular fluid (PISF) have emerged as essential biomarkers in the field of periodontics, providing critical insights into the health and stability of dental implants. This essay explores the significance of various enzymes in PISF, including matrix metalloproteinases (MMPs), elastase, alkaline phosphatase, acid phosphatase, aspartate aminotransferase (AST), and alanine aminotransferase (ALT), in assessing the local inflammatory environment and diagnosing peri-implant diseases. The analysis of these enzymes facilitates early detection of complications, personalized treatment planning, and long-term monitoring, emphasizing the need for a multidisciplinary approach to patient care. Collaboration among dental professionals and patient education is crucial in ensuring the successful management and maintenance of dental implants. Understanding the role of enzymes in PISF and their implications in periodontal health underscores their significance in contemporary periodontics and emphasizes the need for ongoing research and technological advancements.