Search Results (271)

The C-kinase-activated protein phosphatase-1 (PP1) inhibitor of 17 kDa (CPI-17) is a specific inhibitor of the PP1 catalytic subunit (PP1c) and the myosin phosphatase (MP) holoenzyme. CPI-17 requires the phosphorylation of Thr38 in the peptide segment ³⁵ARV(P)TVKYDRREL⁴⁶ for inhibitory activity. CPI-17 regulates myosin phosphorylation in smooth muscle contraction and the tumorigenic transformation of several cell lines via the inhibition of MP. A phosphospecific antibody (anti-CPI-17^pThr38) against the phosphorylation peptide was used to determine the phosphorylation levels in cells. We found that phospho-CPI-17 and its closely related proteins are not present in HeLa and MCF7 cells after inducing phosphorylation by inhibiting phosphatases with calyculin A. In contrast, cross-reactions of proteins in the 40–220 kDa range with anti-CPI-17^pThr38 were apparent. Searching the protein database for similarities to the CPI-17 phosphorylation sequence revealed several proteins with 42–75% sequence identities. The LIMK2-1 isoform emerged as a possible PP1 inhibitor. Experiments with Flag-LIMK2-1 overexpressed in tsA201 cells proved that LIMK2-1 interacts with PP1c isoforms and is phosphorylated predominantly by protein kinase C. Phosphorylated LIMK2-1 inhibits PP1c and the MP holoenzyme with similar potencies (IC50 ~28–47 nM). In conclusion, our results suggest that LIMK2-1 is a novel phosphorylation-dependent inhibitor of PP1c and MP and may function as a CPI-17-like phosphatase inhibitor in cells where CPI-17 is present but not phosphorylated upon phosphatase inhibition. Full article

Background: Ambulatory blood pressure monitoring (ABPM) is increasingly recognized as a more reliable indicator of blood pressure status in children than clinic-based measurements, with superior predictive value for cardiovascular morbidity and mortality. However, evidence on the clinical utility of ABPM-derived indices, such as pulse pressure (PP), pulse pressure index (PPI), rate pressure product (RPP), ambulatory arterial stiffness index (AASI), and average real variability (ARV), remains underexplored in the pediatric population, particularly among children with chronic kidney disease (CKD). Objective: To evaluate the correlation between ABPM-derived indices in children, with a subgroup analysis comparing those with and without CKD. Secondary objectives included identifying factors associated with AASI and ARV and assessing their utility in cardiovascular risk stratification. Methods: In this bicentric cross-sectional study, 70 children (41 with CKD and 29 controls) were enrolled. ABPM indices (PP, PPI, RPP, AASI, and ARV) were calculated, and both descriptive and inferential statistical analyses, including linear regression, were performed. Results: Systolic and diastolic hypertension were significant predictors of elevated ARV (p < 0.05), while body mass index (BMI) and glomerular filtration rate (GFR) were positively associated with AASI (p < 0.05). Use of angiotensin-converting enzyme inhibitors (ACEIs) was associated with reduced arterial stiffness (p = 0.02). Significant differences were observed in weight, BMI, PP, and PPI between the CKD and non-CKD groups, with ABPM demonstrating greater sensitivity in detecting vascular health markers. Conclusions: ABPM-derived indices, particularly PP, PPI, and ARV, show promise in improving cardiovascular risk assessment in children. These findings support the broader use of ABPM metrics for refined cardiovascular evaluation, especially in pediatric CKD. Full article

Avian reovirus (ARV) has emerged as an important pathogen in turkeys, causing economic losses through tenosynovitis, necrotizing hepatitis, immunosuppression, and enteric disease. Despite its ubiquity, the evolutionary history of ARV cross-species transmission among chickens, turkeys, and wild birds remains poorly understood, hindering effective control and surveillance. This study investigates ARV temporal phylogenetics with an emphasis on interspecies transmission in turkeys. Whole genome sequences (WGSs) from seventy-seven turkey cases and one quail case at the Iowa State University Veterinary Diagnostic Laboratory, along with 74–136 segment sequences per gene from GenBank (1970–2023), were analyzed. Temporal phylogenetic analyses identified chickens as the ancestral host, with spillover into turkeys beginning in the mid-20th century, followed by stable transmission within turkey populations. Migration analyses revealed predominantly unidirectional transmission from chickens to turkeys. WGS analyses showed high variability in the M2 and σC-encoding region of the S1 segment, suggesting selective pressure on outer capsid proteins. M2, S1 σC, and L3 had the highest substitution rates, implicating their role in adaptation and antigenic diversity. These findings highlight the complexity of ARV evolution across hosts and underscore the need for robust genotyping schemes and surveillance strategies to mitigate outbreaks in poultry. Full article

Head and neck squamous cell carcinoma (HNSCC) remains challenging to treat despite multimodal therapeutic approaches. Cisplatin treatment is effective and cost-efficient, although chemoresistance and disease recurrence limit its efficacy. Understanding the mechanisms of cisplatin resistance and the identification of compounds to target resistant tumor cells are critical for improving patient outcomes. We have demonstrated that cisplatin-induced senescent HN30 HNSCC cells can be eliminated by ABT-263 (navitoclax), a BCL-2/BCL-X_L inhibitor that has senolytic properties. Here, we report the development of a cisplatin-resistant cell line (HN30R) for the testing of ABT-263 and the PROTAC BET degraders ARV-825 and ARV-771. ABT-263 was ineffective in sensitizing HN30R cells to cisplatin, largely due to a lack of senescence induction. However, the BET degraders in combination with cisplatin promoted apoptotic cell death in both HN30 and HN30R cells. The effectiveness of ARV-825 did not appear to depend on the cells entering into senescence, indicating that it was not acting as a conventional senolytic. ARV-825 treatment downregulated BRD4 and its downstream targets, c-Myc and Survivin, as well as decreased the expression of RAD51, a DNA repair marker. These results suggest that the BET degraders ARV-825 and ARV-771 may be effective in improving the response of chemoresistant head and neck cancer to cisplatin treatment. Full article

The treatment of choice for prostate cancer is androgen deprivation (ADT) and novel hormonal agents such as Abiraterone, Enzalutamide, or Apalutamide. Initially, this therapy is highly effective, but a significant challenge arises as most patients eventually develop resistance, resulting in castration-resistant prostate cancer (CRPC). Furthermore, the sequential use of these drugs can lead to cross-resistance, diminishing their efficacy. Tumor heterogeneity plays a pivotal role in the development of resistance to different treatments. This study utilized cellular models of CRPC to assess the response to Apalutamide when it was administered as a second- or third-line treatment. Functional and genetic analyses were conducted in various CRPC cell models exposed to Apalutamide. These analyses included real-time cell monitoring assays, flow cytometry, clonogenicity assays, and RT-qPCR. CRPC cell models were capable of continued proliferation, maintained cell cycle profiles similar to those of untreated cells, and retained their clonogenic potential. Cross-resistance to Apalutamide in models of ADT, ADT plus Enzalutamide, or Abiraterone resistance did not correlate with the expression levels of AR-V7 and AR-V9 variants. Gene expression analysis of resistant prostate cancer cell lines revealed that treatment with Apalutamide induced the emergence of more aggressive phenotypes, including cancer stem cells or neuroendocrine differentiation profiles. Most CRPC cell models developed cross-resistance to Apalutamide and were able to proliferate and retain their clonogenic capability. Apalutamide resistance was not linked to the expression of AR-V7 or AR-V9 variants but was instead associated to bypass of AR signaling pathway and the emergence of more aggressive expression profiles. Full article

The landscape of clinical trials aimed at targeting specific proteins has experienced significant advancements, presenting promising opportunities for the development of effective therapeutics across a range of diseases. These trials focus on the investigation of modulation of protein functions, utilizing innovative technologies such as PROTACs (Proteolysis-Targeting Chimeras) and other protein degraders. These innovative approaches aim to address previously undruggable targets, enhancing the specificity and efficacy of treatments. The current landscape of clinical trials encompasses a diverse array of therapeutic areas, including oncology, autoimmune diseases, and neurological disorders. For instance, drugs like ARV-471 and ARV-110 are in advanced phases for treating metastatic breast cancer and prostate cancer, respectively, by targeting estrogen and androgen receptors. Early-phase trials explored the potential of targeting proteins like IKZF1/3 in multiple myeloma and IRAK4 in autoimmune diseases. The conducted trials not only emphasize the therapeutic potential of protein degradation but also highlight the challenges associated with bioavailability, stability, and delivery mechanisms. As these clinical trials advance, they possess the potential to transform treatment paradigms, providing renewed hope for patients facing complex and refractory conditions. Full article

Introduction: Prostate cancer with spinal metastases (PCSM) is associated with high morbidity and mortality. The impact of biomarkers on the prognosis of spinal metastases, however, remains unclear. Objective: This study explored associations between potential biomarkers, treatment modalities, survival, and neurological outcomes in PCSM patients. Methods: We conducted a retrospective analysis of 68 patients as part of a neurosurgical cohort with PCSM at a comprehensive cancer center from 2013 to 2023, examining the influence of potential biomarkers, treatment modalities, and demographics on prognosis. The primary outcomes were the identification of biomarkers, overall survival (OS) in years, survival after spinal metastasis in years, spinal metastasis recurrence, and postoperative neurological outcomes via Frankel scores. Results: All the patients (n = 68) had adenocarcinoma, and the median age was 69 years. The mortality rate was 66% with a median OS of 6 years. Seventy-two biomarkers were identified. An accelerated failure time model (AFT) showed that radiotherapy to the prostate increased the OS (TR = 1.805, p = 0.001), while smoking status (TR = 0.625, p < 0.001) and PTEN gene mutations (TR = 0.504, p = 0.006) were associated with decreased OS. Kaplan–Meier analysis associated PTEN mutations with reduced median OS using the Gehan–Breslow–Wilcoxon test (3.50 vs. 9.49 years; p = 0.001). PTEN mutations were trending towards but were not significant for decreased survival following spinal metastases (2.04 vs. 3.15 years; p = 0.08). Both PTEN (p = 0.02) and Tumor Protein 53 (TP53, p = 0.01) mutations were associated with increased spinal metastasis recurrence when analyzed using Fisher’s exact test. No differences were observed in the median OS or survival after spinal metastases among patients with or without androgen receptor splice variant-7 (AR-V7), prostate-specific membrane antigen (PSMA), TP53, or other analyzed biomarkers. Similarly, neither age, receipt of chemotherapy, nor radiotherapy to the spine correlated with OS. Only chemotherapy was associated with a decreased postoperative Frankel Score (p = 0.002). Conclusions: PTEN mutations and smoking status were associated with decreased OS in patients with PCSM. Both PTEN and TP53 mutations were associated with increased spinal metastasis recurrence. Receipt of radiotherapy to the prostate was correlated with prolonged survival, whereas receipt of radiotherapy to the spine was not. Chemotherapy was associated with decreased postoperative neurological outcomes. Full article

Transcription factors (TFs) play central roles in gene regulation and disease progression but have long been considered undruggable due to the absence of well-defined binding pockets and their reliance on protein–protein or protein–DNA interactions. Proteolysis-targeting chimeras (PROTACs) offer a novel strategy to overcome these limitations by inducing selective degradation of TFs via the ubiquitin–proteasome system. This review highlights recent advances in TF-targeting PROTACs, focusing on key oncogenic TFs such as androgen receptor (AR), estrogen receptor alpha (ERα), BRD4, c-Myc, and STAT family members. Strategies for ligand design—including small molecules, peptides, and nucleic acid-based elements—are discussed alongside the use of various E3 ligases such as VHL, CRBN, and IAP. Several clinically advanced PROTACs, including ARV-110 and ARV-471, demonstrate the therapeutic potential of this technology. Despite challenges in pharmacokinetics and E3 ligase selection, emerging data suggest that PROTACs can successfully target TFs, paving the way for new treatment strategies across oncology and other disease areas. Full article

HIV/AIDS remains a global public health concern, with a high prevalence in sub-Saharan Africa. The President’s Emergency Plan for AIDS Relief (PEPFAR) initiatives, including preexposure prophylaxis (PREP) and postexposure prophylaxis (PEP), significantly reduced HIV infections in South Africa and Nigeria. The suspension of United States (U.S.) foreign aid may impact these preventive measures. Although some emergency aid programs were exempted, uncertainty persists, impacting global health initiatives, especially in South Africa and Nigeria. This study investigates the public health impacts of the United States (U.S.) government’s January 2025 suspension of U.S. foreign aid, focusing on its implications for HIV prevention initiatives, such as PREP and PEP, in South Africa and Nigeria. We comprehensively searched keywords such as PEPFAR, PREP, PEP, HIV infection in South Africa or Nigeria, antiretroviral (ARV) drugs, public healthcare impact, 2025 Trump’s foreign aid withdrawal, titles, and abstracts in Google Scholar, PubMed, and Web of Science. The search results were screened from 500 to 150 included articles based on their relevance and quality assessment for inclusion. The review unveiled that Nigeria maintained a continuous increase in HIV/AIDS-related deaths and new HIV infections from 1990, reaching the climax between 1999 and 2005, showing approximately 110,000 HIV/AIDS-related deaths and 200,000 new HIV infections. Notably, due to the PEPFAR intervention in Nigeria, an improved decrease in both HIV/AIDS-related deaths (45,000) and new HIV infections (75,000) was experienced from 2010 to 2023. South Africa experienced a rapid increase between 1990 and 2003 in both HIV/AIDS-related deaths and new HIV infections, reaching the climax around the early 2000s, with about 520,000 new HIV infections and 260,000 HIV/AIDS-related deaths in 2005. Furthermore, there was a continuous decline from 2005 onwards, with 50,000 HIV/AIDS-related deaths and 150,000 new HIV infections by 2023. Therefore, the suspension of this aid threatens disruptions in ARV therapy, possible increases in HIV transmission, shortages in PREP and PEP, the retrenchment of healthcare workers, the suspension of non-governmental organization activities, and the reversal of gains in vulnerable populations, reversing progress toward the 95-95-95 vision, increasing morbidity and mortality rates and financial strain on healthcare systems in these two countries. We recommend proactive measures, such as increased budget allocations for healthcare reforms, exploring local vaccine and health product development and diversifying funding sources in Nigeria, and implementing universal healthcare coverage for South Africans to mitigate the adverse consequences of aid withdrawal. Full article

The prediction of agricultural commodity futures returns is crucial for understanding global economic trends, alleviating inflationary pressures, and optimizing investment portfolios. However, current research that uses full-sample decomposition to predict agricultural futures returns suffers from data leakage, and the resulting forecast bias leads to overly optimistic outcomes. Additionally, previous studies have lacked a comprehensive consideration of key economic variables that influence agricultural prices. To address these issues, this study proposes the “Rolling VMD-LASSO-Mixed Ensemble” forecasting framework and compares its performance with “Rolling VMD” against univariate models, “Rolling VMD-LASSO” against “Rolling VMD”, and “Rolling VMD-LASSO-Mixed Ensemble” against “Rolling VMD-LASSO”. Empirical results show that, on average, “Rolling VMD” improved MSE, MAE, Theil U, ARV, and DA by 3.05%, 1.09%, 1.52%, 2.96%, and 11.11%, respectively, compared to univariate models. “Rolling VMD-LASSO” improved these five indicators by 2.11%, 1.15%, 1.09%, 2.13%, and 1.00% over “Rolling VMD”. The decision tree-based “Rolling VMD-LASSO-Mixed Ensemble” outperformed “Rolling VMD-LASSO” by 1.98%, 0.96%, 1.28%, 2.55%, and 4.18% in the five metrics. Furthermore, the daily average return, maximum drawdown, Sharpe ratio, Sortino ratio, and Calmar ratio based on prediction results also show that “Rolling VMD” outperforms univariate forecasting, “Rolling VMD-LASSO” outperforms “Rolling VMD”, and “Rolling VMD-LASSO-Mixed Ensemble” outperforms “Rolling VMD-LASSO”. This study provides a more accurate and robust forecasting framework for the global agricultural futures market, offering significant practical value for investor risk management and policymakers in stabilizing prices. Full article

Muscle fatigue impacts performance in sports, rehabilitation, and daily activities, with surface electromyography (sEMG) widely used for monitoring. In this study, we developed a wearable sEMG device and conducted experiments to create a dataset for fatigue analysis. The sEMG signals were analyzed through a multi-domain feature extraction pipeline, incorporating time-domain (e.g., RMS, ARV), frequency-domain (e.g., MNF), and hybrid-domain metrics (e.g., MNF/ARV ratio, Instantaneous Mean Amplitude Difference), to identify physiologically meaningful indicators of fatigue. To ensure inter-subject comparability, we applied a dynamic standardization strategy that normalized each feature based on the RMS value of the first active segment, establishing a consistent baseline across participants. Using these standardized features, we explored several fatigue index construction methods—such as weighted sums, t-SNE, and Principal Component Analysis (PCA)—to capture fatigue progression effectively. We then trained and evaluated multiple machine learning models such as LR, SVR, RF, GBM, LSTM, CNN, and kNN to predict fatigue levels, selecting the most effective approach for real-time monitoring. Integrated into a wireless BLE-enabled sensor platform, the system offers seamless body placement, mobility, and efficient data transmission. An initial calibration phase ensures adaptation to individual muscle profiles, enhancing accuracy. By balancing on-device processing with efficient wireless communication, this platform delivers scalable, real-time fatigue monitoring across diverse applications. Full article

In 2023, the HIV-1 pandemic claimed around 630,000 lives worldwide due to AIDS-related complications. Its burden is significantly heavier in Sub-Saharan Africa, where an increased HIV-1 genetic diversity is common, which increases the risk of resistance to antiretroviral (ARV) drugs. This study aims to update the molecular epidemiology of HIV-1 in Angola, focusing specifically on the gag gene, which is often overlooked, and to assess the potential viability of lenacapavir (LEN)-based ARV therapy in the region. A total of 243 blood samples were collected from ARV-naïve, HIV-infected patients at the General Hospital of Benguela, city of Benguela, Angola. The capsid-encoding region of HIV-1 proviral DNA was amplified by PCR and sequenced. Phylogenetic analysis was performed using the maximum likelihood method, and genome recombinant forms were characterised through bootscanning analysis. Primary resistance mutations to LEN were identified using Stanford University’s HIVdb algorithm. Among the 80 successfully sequenced samples, 13 different genetic forms/subtypes were identified, with unique recombinant forms (URFs) (37.5%, 30/80) and subtype C (31.25%, 25/80) being the most prevalent. Regarding resistance mutations, none were detected, apart from four polymorphic mutations. These findings reinforce Angola’s position as a transitional HIV-1 hotspot between the genetically highly diverse Central Africa and the subtype C-dominated Southern Africa, while also supporting the potential effectiveness of LEN-based regimens for treatment and prevention of HIV-1 infections in the future. Full article

The publication focuses on the innovative applications of PROTAC (proteolysis-targeting chimera) technology in modern pharmacotherapy, with particular emphasis on cancer treatment. PROTACs represent an advanced therapeutic strategy that enables selective protein degradation, opening new possibilities in drug design. This technology shows potential in the treatment of cancers, viral infections (such as HIV and COVID-19), and chronic diseases including atherosclerosis, Alzheimer’s disease, atopic dermatitis, and Huntington’s disease. Promising results from clinical studies on the compound ARV-471 confirm the effectiveness of this approach. New types of PROTACs, like TF-PROTAC and PhosphoTAC, are designed to enhance the effectiveness, stability, and absorption of treatment drugs. The conclusions of the review highlight the broad therapeutic potential of PROTACs in various diseases and their relevance for the future of therapies, particularly in oncology. Full article

Avian reovirus (ARV) infections significantly impact the global poultry industry, but host responses across infection models remain poorly characterized. Using specific-pathogen-free chicken embryos, this study examined tissue-specific transcriptomic changes following in ovo inoculation with two doses of ARV S1133 at embryonic day 18. Quantitative PCR confirmed dose- and time-dependent viral replication, with the liver exhibiting the highest viral load at 24 h post-inoculation (hpi), whereas the kidneys, intestines, and bursa were only positive at 48 hpi with the higher viral dose. Transcriptomic profiling revealed the intestines mounted an extensive gene expression response, implicating early immune activation. Liver samples demonstrated strong upregulation of antiviral pathways, including interferon signaling and viral replication inhibition, while kidneys and intestines were enriched for coagulation and wound healing pathways. The bursae exhibited minimal immunity-related responses, suggesting insufficient maturation. Functional analyses confirmed tissue-specific immune and metabolic adaptations to infection. These findings indicate that ARV replication efficiency and host molecular responses are dose-, tissue-, and time-dependent. Notably, intestinal responses suggest preemptive immune engagement, while hepatic antiviral mechanisms may play a critical role in restricting viral spread. This study establishes foundational knowledge of host molecular responses to ARV in late-stage embryos, with implications for in ovo vaccination and early immunity. Full article

Background: Accurate estimation of myocardial material parameters is crucial to understand cardiac biomechanics and plays a key role in advancing computational modeling and clinical applications. Traditional inverse finite element (FE) methods rely on iterative optimization to infer these parameters, which is computationally expensive and time-consuming, limiting their clinical applicability. Methods: This study proposes a deep learning-based approach to rapidly and accurately estimate the left ventricular myocardial material parameters directly from routine cardiac magnetic resonance imaging (CMRI) data. A ResNet18-based model was trained on FEM-derived parameters from a dataset of 1288 healthy subjects. Results: The proposed model demonstrated high predictive accuracy on healthy subjects, achieving mean absolute errors of 0.0146 for $C_a$ and 0.0139 for $C_b$, with mean relative errors below 5.00%. Additionally, we evaluated the model on a small pathological subset (including ARV and HCM cases). The results revealed that while the model maintained strong performance on healthy data, the prediction errors in the pathological samples were higher, indicating increased challenges in modeling diseased myocardial tissue. Conclusion: This study establishes a computationally efficient and accurate deep learning framework for estimating myocardial material parameters, eliminating the need for time-consuming iterative FE optimization. While the model shows promising performance on healthy subjects, further validation and refinement are required to address its limitations in pathological conditions, thereby paving the way for personalized cardiac modeling and improved clinical decision-making. Full article