Search Results (149)

Speculative execution attacks significantly compromise the security of modern processors by enabling information leakage. These well-known attacks exploit speculative cache-based covert channels to effectively exfiltrate secret data by altering cache states. Existing hardware defenses specifically designed to prevent cache-based covert channels are effective at blocking explicit channels. However, their protection against implicit attack variants remains limited, since these hardware defenses do not fully eliminate secret-dependent microarchitectural changes in caches. In this paper, we propose TrackRISC, a framework which comprises (i) a refined implicit attack flow model specifically for the exploration and analysis of implicit cache-based speculative execution attacks which severely compromise the security of existing hardware defenses, and (ii) a security-enhanced tracking and mitigation microarchitecture, termed TrackRISC-Defense, designed to mitigate both implicit and explicit attack variants that use speculative cache-based covert channels. To obtain realistic hardware evaluation results, we implement and evaluate both TrackRISC-Defense and a representative existing defense on top of the Berkeley’s out-of-order RISC-V processor core (SonicBOOM) using the VCU118 FPGA platform running Linux. Compared to the representative existing defense which incurs a performance overhead of 13.8%, TrackRISC-Defense ensures stronger security guarantees with a performance overhead of 19.4%. In addition, TrackRISC-Defense can mitigate both explicit and implicit speculative cache-based covert channels with a register-based hardware resource overhead of 0.4%. Full article

Background/Objectives: Parkinson’s disease (PD) is the second-most prevalent neurodegenerative disorder, characterized by the progressive loss of dopaminergic neurons in the Substantia Nigra pars compacta (SNpc). Experimental models that replicate core features of PD are critical to investigate underlying mechanisms and therapeutic strategies. Here we evaluated the effects of an acute unilateral intrastriatal lesion induced by 6-hydroxydopamine (6-OHDA) on neuronal loss and the associated inflammatory response. Methods: Adult male Wistar rats received an injection of 6-OHDA into the right striatum, while the contralateral side received vehicle. Motor behavior was assessed by cylinder and open field tests on post-lesion days (PLDs) 7 and 14. Brains were analyzed by immunohistochemistry for tyrosine hydroxylase (TH), glial response (GFAP and Iba1), and caspase-3 at PLD +14. Results: A marked reduction in TH-immunoreactivity in the lesioned striatum was observed, with ~40% loss of TH-positive neurons in the ipsilateral SNpc. Surviving neurons displayed a 28% increase in soma size compared to the contralateral side. The lesion was accompanied by robust astrocytic and microglial activation at the injection site, as well as enhanced GFAP immunoreactivity in the ipsilateral SN pars reticulata. Apoptotic profiles emerged in the SNpc at PLD +14. Functionally, these alterations were reflected in significant motor asymmetry and decreased locomotor activity. Conclusions: Our findings demonstrate that neuroinflammation accompanies early dopaminergic degeneration following intrastriatal 6-OHDA administration, contributing to motor deficits. Future studies with older animals and broader behavioral and anatomical assessments—including regions such as the ventral tegmental area and motivational or anxiety-related paradigms—may enhance translational relevance. Full article

Antimicrobial resistance is a critical global health issue exacerbated by biofilm-associated infections that often resist conventional therapies. Photodithazine-mediated antimicrobial photodynamic therapy (PDZ-aPDT) has emerged as a promising alternative, demonstrating a broad-spectrum antimicrobial efficacy against multidrug-resistant bacteria and fungi, including those in biofilms. This systematic review evaluates the efficacy, safety, and clinical applications of PDZ-aPDT by synthesizing evidence from preclinical and clinical studies. Databases including PubMed, Embase, Scopus, and Cochrane were systematically searched, resulting in the inclusion of 13 studies for qualitative analysis. PDZ-aPDT consistently reduced the microbial burden in various models, including oral candidiasis, denture stomatitis, acne, and infections related to medical devices. Synergistic combinations with conventional antimicrobials and adjunctive therapies (e.g., DNase I) further enhanced its effectiveness. However, the evidence base remains limited by methodological variability, small sample sizes, and short follow-up periods. Future research should focus on rigorous clinical trials with standardized protocols and extended follow-up to establish definitive efficacy and safety profiles, facilitating a broader clinical implementation in combating antimicrobial resistance. Full article

This paper proposes an AI-driven automated test generation framework for vehicle control units (VCUs), integrating natural language processing (NLP) and dynamic variable binding. To address the critical limitation of traditional AI-generated test cases lacking executable variables, the framework establishes a closed-loop transformation from requirements to executable code through a five-layer architecture: (1) structured parsing of PDF requirements using domain-adaptive prompt engineering; (2) construction of a multidimensional variable knowledge graph; (3) semantic atomic decomposition of requirements and logic expression generation; (4) dynamic visualization of cause–effect graphs; (5) path-sensitization-driven optimization of test sequences. Validated on VCU software from a leading OEM, the method achieves 97.3% variable matching accuracy and 100% test case executability, reducing invalid cases by 63% compared to conventional NLP approaches. This framework provides an explainable and traceable automated solution for intelligent vehicle software validation, significantly enhancing efficiency and reliability in automotive testing. Full article

Precision medicine is transforming hematologic cancer care by tailoring treatments to individual patient profiles and moving beyond the traditional “one-size-fits-all” model. This review outlines foundational technologies, disease-specific advances, and emerging directions in precision hematology. The field is enabled by molecular profiling techniques, including next-generation sequencing (NGS), whole-exome sequencing (WES), and RNA sequencing (RNA-seq), as well as epigenomic and proteomic analyses. Complementary tools such as liquid biopsy and minimal residual disease (MRD) monitoring have improved diagnosis, risk stratification, and therapeutic decision making. We discuss major molecular targets and personalized strategies across hematologic malignancies: FLT3 and IDH1/2 in acute myeloid leukemia (AML); Philadelphia chromosome–positive and Ph-like subtypes in acute lymphoblastic leukemia (ALL); BCR-ABL1 in chronic myeloid leukemia (CML); TP53 and IGHV mutations in chronic lymphocytic leukemia (CLL); molecular subtypes and immune targets in diffuse large B-cell lymphoma (DLBCL) and other lymphomas; and B-cell maturation antigen (BCMA) in multiple myeloma. Despite significant progress, challenges remain, including high costs, disparities in access, a lack of standardization, and integration barriers in clinical practice. However, advances in single-cell sequencing, spatial transcriptomics, drug repurposing, immunotherapies, pan-cancer trials, precision prevention, and AI-guided algorithms offer promising avenues to refine treatment and improve outcomes. Overcoming these barriers will be critical for ensuring the equitable and widespread implementation of precision medicine in routine hematologic oncology care. Full article

Objective: This in vitro study evaluated the effectiveness of three laser systems—diode, CO₂, and Er:YAG—for debonding composite attachments used in aligner orthodontic therapy. Materials and Methods: Fifty extracted human premolars with composite attachments were divided into five groups (n = 10): control, RT (rotary tools), diode laser (980 nm, irradiance was 4811 W/cm²), CO₂ laser (10.6 µm, irradiance 1531 W/cm²), and Er:YAG laser (2940 nm, irradiance 471.7 W/cm²). Shear bond strength (SBS) testing measured debonding forces. Enamel surface changes were evaluated using micro-CT, optical profilometry, and stereomicroscopy. The Adhesive Remnant Index (ARI) assessed residual bonding material. Results: Laser treatment increased enamel roughness (p < 0.05). Er:YAG laser caused the highest roughness (Sa = 2.03 µm) and up to 0.17 mm enamel loss but left minimal adhesive remnants and no fractures. Diode laser preserved surface smoothness with moderate bond weakening. CO₂ laser had intermediate effects. RT showed the highest SBS but resulted in greater enamel alteration. SBS was significantly reduced in the laser groups, lowest for Er:YAG (81.7 ± 45.5 MPa vs. control 196.2 ± 75.3 MPa). ARI indicated better adhesive removal in the laser-treated groups, with Er:YAG showing the highest percentage of clean enamel surfaces (67% vs. 25%). Conclusions: Er:YAG demonstrated the best balance between effective debonding and enamel preservation. Diode and CO₂ lasers also offer viable alternatives to rotary tools. Further clinical studies are recommended. Full article

Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD), previously referred to as Non-Alcoholic Fatty Liver Disease (NAFLD), is a prevalent chronic liver condition strongly linked to Type 2 Diabetes Mellitus (T2DM) and obesity. Globally, MASLD is the most common cause of chronic liver disease. The bidirectional relationship between MASLD and T2DM underscores the pivotal role of insulin resistance in disease progression, which contributes to hepatic steatosis, oxidative stress, and inflammation, forming a vicious cycle. MASLD is also associated with heightened risks of cardiovascular and chronic kidney diseases, necessitating comprehensive treatment approaches. While lifestyle interventions and weight loss remain the cornerstone of management, their sustainability is challenging. This review highlights the evolving pharmacological landscape targeting MASLD and its advanced form, Metabolic Dysfunction-Associated Steatohepatitis (MASH). Currently, Resmetirom is the only FDA-approved drug for MASH. Current and investigational therapies, including insulin-sensitizing agents like peroxisome proliferator-activated receptor (PPAR) agonists, glucose-lowering drugs such as sodium-glucose co-transporter 2 inhibitors (SGLT2i) and glucagon-like peptide-1 receptor agonists (GLP-1 RA), drugs that target intermediary metabolism such as Vitamin E, de novo lipogenesis inhibitors, and emerging agents targeting the gut-liver axis and oxidative stress, are explored. These therapies demonstrate promising effects on hepatic steatosis, inflammation, and fibrosis, providing new avenues to address the multifaceted pathophysiology of MASLD. Full article

Anthracyclines remain a cornerstone of cancer therapy but are associated with a significant risk of cardiotoxicity, which can lead to overt heart failure. The risk is modulated by cumulative dose, pre-existing cardiovascular disease, and patient-specific factors. As cancer survival improves, the long-term cardiovascular consequences of anthracycline exposure have become a growing concern, underscoring the need for effective preventive strategies. This narrative review examines lifestyle and pharmacological interventions aimed at mitigating anthracycline-induced cardiotoxicity. Evidence suggests that structured exercise programs and antioxidant-rich diets may enhance cardiovascular resilience, while beta-blockers, renin-angiotensin system inhibitors, and dexrazoxane remain central pharmacological options. Emerging therapies, including sodium-glucose co-transporter 2 inhibitors and sacubitril/valsartan, show promise but require further investigation. A comprehensive approach that integrates lifestyle modifications with pharmacological strategies within a multidisciplinary cardio-oncology framework may provide optimal protection, improving long-term cardiovascular outcomes in cancer patients receiving anthracyclines. Full article

Variety testing systems in Europe do not account for cannabis varieties selected specifically for flower and cannabinoid production. These “flower varieties” are morphologically distinct from industrial varieties, with significant implications for agronomic characterization in the Value for Cultivation and Use (VCU) testing system. However, they are not considered as drug-type varieties due to their low Δ⁹-tetrahydrocannabinol (Δ⁹-THC) content. Identifying specific traits that can objectively describe these varieties is integral to establishing stable and high-quality production standards. We evaluated specific traits tailored to the VCU testing of flower varieties in two field trials. The assessed phenological traits showed significant differences between varieties (p < 0.0001) for all traits except ease of harvest (EH) and lodging, with significant differences also found in all yield-related traits. The number of branches per plant (NBP), flower and leaf yield (FLY), harvest index (HI) and raceme compactness index (RCI) could therefore be considered for VCU testing. The varieties differed significantly in their cannabinoid content, with all falling below the THC limit under Swiss regulation (1%) but not all meeting the 0.3% limit set by European countries. Variations in THC content were dependent on the testing year, the timing of sampling and the number of plants sampled, underscoring the need to clarify VCU testing methodologies. Incorporating cannabinoid content along with morphological and phenological traits is crucial in introducing a new “flower” category within the VCU system for cannabis. Full article

Spondylodiscitis is a devastating invasive infection that can lead to debilitating pain, motor weakness, or paralysis, even with appropriate medical and surgical treatment. Over the past two decades, there has been a worldwide increase in the incidence of spondylodiscitis, which can be attributed to a higher prevalence of various risk factors including intravenous drug use, hemodialysis, and spinal surgeries. The lumbar spine is the most likely region to be affected, with Staphylococcus aureus being the predominant pathogen. Management of spondylodiscitis requires a multi-disciplinary approach, with close coordination between the spinal surgeon and the infectious diseases specialist. Clinicians should become familiar with the epidemiology and presentation of patients with suspected spondylodiscitis because timely diagnosis and treatment may lead to improved outcomes. This unique review incorporates the perspectives from infectious disease and spine surgery specialists. Full article

Accurately predicting protein–ligand binding affinity is an important step in the drug discovery process. Deep learning (DL) methods have improved binding affinity prediction by using diverse categories of molecular data. However, many models rely heavily on interaction and sequence data, which impedes proper learning and limits performance in de novo applications. To address these limitations, we developed a novel graph neural network model, called StructureNet (structure-based graph neural network), to predict protein–ligand binding affinity. StructureNet improves existing DL methods by focusing entirely on structural descriptors to mitigate data memorization issues introduced by sequence and interaction data. StructureNet represents the protein and ligand structures as graphs, which are processed using a GNN-based ensemble deep learning model. StructureNet achieved a PCC of 0.68 and an AUC of 0.75 on the PDBBind v.2020 Refined Set, outperforming similar structure-based models. External validation on the DUDE-Z dataset showed that StructureNet can effectively distinguish between active and decoy ligands. Further testing on a small subset of well-known drugs indicates that StructureNet has high potential for rapid virtual screening applications. We also hybridized StructureNet with interaction- and sequence-based models to investigate their impact on testing accuracy and found minimal difference (0.01 PCC) between merged models and StructureNet as a standalone model. An ablation study found that geometric descriptors were the key drivers of model performance, with their removal leading to a PCC decrease of over 15.7%. Lastly, we tested StructureNet on ensembles of binding complex conformers generated using molecular dynamics (MD) simulations and found that incorporating multiple conformations of the same complex often improves model accuracy by capturing binding site flexibility. Overall, the results show that structural data alone are sufficient for binding affinity predictions and can address pattern recognition challenges introduced by sequence and interaction features. Additionally, structural representations of protein–ligand complexes can be considerably improved using geometric and topological descriptors. We made StructureNet GUI interface freely available online. Full article

Background/Objectives: The development of pharmacotherapy, particularly in antiangiogenic drugs, has led to the emergence of MRONJ as a significant side effect. With the increasing incidence of cancer, the management of MRONJ poses a growing challenge for clinicians. The aim of the study is to evaluate the effectiveness of photobiomodulation (PBM) in treating patients with stage I, II, and III medication-related osteonecrosis of the jaw (MRONJ). Methods: A total of 31 patients were divided into two groups: Group 1 (n = 14 patients), with Stage 1 MRONJ; and Group 2 (n = 17 patients), with Stage II and III MRONJ. In total, 10 patients had osteoporosis and 21 underwent cancer treatment. The sole variable under investigation was the stage of MRONJ, as all patients underwent the same photobiomodulation (PBM) procedure. For treatment protocol, PBM with a diode laser was used (Lasotronix Smart M Pro, Piaseczno, Poland) with the following parameters: 100 mW; continuous wave; 635 nm; 4 J/cm² for 20 s; irradiance for one point: 0.398 W/cm²; fluency for one point: 7.96 J/cm², and for four points, which was one appointment: 31.83 J/cm²; and tip diameter 8 mm (three points from buccal surface, perpendicular for the lesion and one point on the floor of the mouth) during each session. The protocol assumed 10 sessions at 3 days intervals. Antibiotic therapy (amoxicillin with clavulanic acid 875 mg + 125 mg or clindamycin 600 mg every 12 h) was started 3 days before PBM and continued for 14 days. Antibiotics were taken for 14 days in total. Pain was measured with VAS scale. Follow-up was after 3 and 6 months. Results: Among the 14 patients in Group 1, none exhibited any clinical signs or symptoms of MRONJ during the 3 months follow-up, and complete cure was achieved. While PBM resolved inflammation and pain in stage II MRONJ, further surgical intervention was necessary to fully address the condition. Conclusions: PBM is an effective treatment for achieving complete recovery in patients with Stage 1 MRONJ. However, in Stages II and III MRONJ, PBM significantly alleviates symptoms but requires complementary surgical intervention to achieve full resolution. A beneficial aspect is the reduction in pain symptoms and the extent of surgical intervention. Full article

Medication adherence is a crucial factor for managing chronic conditions, especially in aging adults. Previous studies have identified predictors of medication adherence. However, current methods fail to capture the time-varying nature of how risk factors can influence adherence behavior. This objective of this study was to implement multitrajectory group-based models to compare a time-varying to a time-fixed approach to identifying non-adherence risk factors. The study population comprised 11,068 Medicare beneficiaries aged 65 and older taking select medications for hypertension, high blood cholesterol, and oral diabetes medications, between 2008 and 2016. Time-fixed predictors (e.g., sex, education) were examined using generalized multinomial logistic regression, while time-varying predictors were explored through multitrajectory group-based modeling. Several predisposing, enabling, and need characteristics were identified as risk factors for following at least one non-adherence trajectory. Time-varying predictors displayed an alternative representation of those risk factors, especially depression symptoms. This study highlights the dynamic nature of medication adherence predictors and the utility of multitrajectory modeling. Findings suggest that targeted interventions can be developed by addressing the key time-varying factors affecting adherence. Full article

Endocrine-disrupting chemicals (EDCs) are notable for their persistence, bioaccumulation, and associations with cancer. Human nuclear receptors (hNRs) are primary targets disrupted by these persistent EDCs, resulting in alterations to xenobiotic metabolism, lipid homeostasis, and endocrine function, which can lead to carcinogenic effects. Despite their hazardous effects, comprehensive studies on EDC interactions and their impacts on hNRs remain limited. Here, we profiled the interactions of persistent EDCs, including PFAS, plastic additives, bisphenols, polybrominated diphenyl ethers, and phthalates, with key hNRs such as PXR, CAR, PPARα, PPARγ, PPARδ, AR, and RORγt. Through controlled molecular docking simulations, we observed strong binding of the EDCs to these receptors. Further analysis showed that EDCs exhibit strong binding activity towards hNRs by preferentially interacting with hydrophobic amino acids, namely leucine, isoleucine, methionine, and phenylalanine. PFAS demonstrated the highest binding affinity, characterized by a combination of complementary hydrophobic interactions from their fluorinated carbon chains and polar interactions from their functional groups (e.g., carboxylate, sulfonate) across all receptors. Distinct polycyclic and hydrophobic trends, contributing to strong NR binding, were evident in non-PFAS and nonplastic EDCs. The hNR activity assay in HepG2 cells revealed agonistic effects of dicyclohexyl phthalate (DCHP) and di-2-ethylhexyl phthalate (DEHP) on most receptors, except for PPARα. The hNR transcription factor pathway assay in HepG2 cells demonstrated increased gene expression of VDRE and PXR, suggesting potential chronic effects on xenobiotic metabolism and calcium homeostasis. Overall, our findings demonstrate the need for further research into the endocrine disruption and carcinogenic effects of these persistent EDCs. Full article

In early-phase dose-finding clinical trials, integrating patient-reported outcomes (PROs) is essential for enhancing patient-centered decision-making. This short communication advocates for several key practices to achieve such integration. Firstly, foster patient-centered communication that ensures patient understanding of the potential benefits of early-phase trials, thereby mitigating therapeutic misconceptions. Secondly, (a) facilitate partnerships to understand and address the underlying reasons for discrepancies between clinician and patient reports of adverse events and (b) facilitate partnerships among clinical trialists, statisticians, clinicians, patients, and advocates to gain diverse perspectives of adverse events and in so doing ensure that patients comprehend how their data will be used. Thirdly, optimize trial design and data collection by (a) determining optimal and feasible frequencies for PRO collection to minimize patient burden while maintaining data integrity and (b) effectively incorporating concordant PROs to guide dose recommendation decisions and adapt trial designs and statistical methods accordingly. Future research will involve investigating the application of these practices in patients within the Virginia Commonwealth University (VCU) Massey Comprehensive Cancer Center Catchment Area. By integrating these recommendations, early-phase dose-finding clinical trials have the potential to achieve more informed and patient-centered objectives. Full article