Phantom oscillations in principal component analysis.

Principal component analysis (PCA) is a dimensionality reduction method that is known for being simple and easy to interpret. Principal components are often interpreted as low-dimensional patterns in high-dimensional space. However, this simple interpretation fails for timeseries, spatial maps, and other continuous data. In these cases, nonoscillatory data may have oscillatory principal components. Here, we show that two common properties of data cause oscillatory principal components: smoothness and shifts in time or space. These two properties implicate almost all neuroscience data. We show how the oscillations produced by PCA, which we call "phantom oscillations," impact data analysis. We also show that traditional cross-validation does not detect phantom oscillations, so we suggest procedures that do. Our findings are supported by a collection of mathematical proofs. Collectively, our work demonstrates that patterns which emerge from high-dimensional data analysis may not faithfully represent the underlying data.

VCF2PCACluster: a simple, fast and memory-efficient tool for principal component analysis of tens of millions of SNPs.

Principal component analysis (PCA) is an important and widely used unsupervised learning method that determines population structure based on genetic variation. Genome sequencing of thousands of individuals usually generate tens of millions of SNPs, making it challenging for PCA analysis and interpretation. Here we present VCF2PCACluster, a simple, fast and memory-efficient tool for Kinship estimation, PCA and clustering analysis, and visualization based on VCF formatted SNPs. We implemented five Kinship estimation methods and three clustering methods for its users to choose from. Moreover, unlike other PCA tools, VCF2PCACluster possesses a clustering function based on PCA result, which enabling users to automatically and clearly know about population structure. We demonstrated the same accuracy but a higher performance of this tool in performing PCA analysis on tens of millions of SNPs compared to another popular PLINK2 software, especially in peak memory usage that is independent of the number of SNPs in VCF2PCACluster.

Predicting stroke occurrences: a stacked machine learning approach with feature selection and data preprocessing.

Stroke prediction remains a critical area of research in healthcare, aiming to enhance early intervention and patient care strategies. This study investigates the efficacy of machine learning techniques, particularly principal component analysis (PCA) and a stacking ensemble method, for predicting stroke occurrences based on demographic, clinical, and lifestyle factors. We systematically varied PCA components and implemented a stacking model comprising random forest, decision tree, and K-nearest neighbors (KNN).Our findings demonstrate that setting PCA components to 16 optimally enhanced predictive accuracy, achieving a remarkable 98.6% accuracy in stroke prediction. Evaluation metrics underscored the robustness of our approach in handling class imbalance and improving model performance, also comparative analyses against traditional machine learning algorithms such as SVM, logistic regression, and Naive Bayes highlighted the superiority of our proposed method.

Analyzing postprandial metabolomics data using multiway models: a simulation study.

BACKGROUND: Analysis of time-resolved postprandial metabolomics data can improve the understanding of metabolic mechanisms, potentially revealing biomarkers for early diagnosis of metabolic diseases and advancing precision nutrition and medicine. Postprandial metabolomics measurements at several time points from multiple subjects can be arranged as a subjects by metabolites by time points array. Traditional analysis methods are limited in terms of revealing subject groups, related metabolites, and temporal patterns simultaneously from such three-way data. RESULTS: We introduce an unsupervised multiway analysis approach based on the CANDECOMP/PARAFAC (CP) model for improved analysis of postprandial metabolomics data guided by a simulation study. Because of the lack of ground truth in real data, we generate simulated data using a comprehensive human metabolic model. This allows us to assess the performance of CP models in terms of revealing subject groups and underlying metabolic processes. We study three analysis approaches: analysis of fasting-state data using principal component analysis, T0-corrected data (i.e., data corrected by subtracting fasting-state data) using a CP model and full-dynamic (i.e., full postprandial) data using CP. Through extensive simulations, we demonstrate that CP models capture meaningful and stable patterns from simulated meal challenge data, revealing underlying mechanisms and differences between diseased versus healthy groups. CONCLUSIONS: Our experiments show that it is crucial to analyze both fasting-state and T0-corrected data for understanding metabolic differences among subject groups. Depending on the nature of the subject group structure, the best group separation may be achieved by CP models of T0-corrected or full-dynamic data. This study introduces an improved analysis approach for postprandial metabolomics data while also shedding light on the debate about correcting baseline values in longitudinal data analysis.

Cell-Engineered Recombinant α-Synuclein: A Gage R&R Validated Protocol.

α-Synuclein (α-Syn) misfolding and its presence in Lewy bodies are observed in almost all Parkinson's disease (PD) patients. Basic biomedical research would benefit from a quick, low-cost approach to purifying α-Syn and developing in vitro and in vivo models for PD. Several research groups utilize PFF-based models, yet the production of α-Syn PFFs is inconsistent, resulting in nonconclusive findings. Some research laboratories prepare recombinant α-Syn (r α-Syn) by molecular cloning to overexpress α-Syn with various purifying techniques. Laboratory-to-laboratory protocols cause considerable variability and sometimes contradictory findings. PD researchers spend more on protein than solving α-Syn's riddles. This article uncovered a novel method for expressing and purifying r α-Syn validated through gage reproducibility and repeatability (Gage R&R). For the production of r α-Syn, we have employed the ability of a high-cell-density-based expression system to overexpress protein in BL21(DE3). A simple, high-throughput, nonchromatographical purification protocol has been devised to facilitate research with higher reproducibility, which was validated through Gage R&R. A crossover experimental design was utilized, and the purified protein was characterized using orthogonal high-end analytical methods, which displayed higher similarity between the isolated r α-Syn. Batch-to-batch variability was the least for produced protein and hence can be utilized for exploring the iceberg of PD.

Comparative phylogenetic analysis of the mediator complex subunit in asparagus bean (Vigna unguiculata ssp. sesquipedialis) and its expression profile under cold stress.

BACKGROUND: The mediator complex subunits (MED) constitutes a multiprotein complex, with each subunit intricately involved in crucial aspects of plant growth, development, and responses to stress. Nevertheless, scant reports pertain to the VunMED gene within the context of asparagus bean (Vigna unguiculata ssp. sesquipedialis). Establishing the identification and exploring the responsiveness of VunMED to cold stress forms a robust foundation for the cultivation of cold-tolerant asparagus bean cultivars. RESULTS: Within this study, a comprehensive genome-wide identification of VunMED genes was executed in the asparagus bean cultivar 'Ningjiang3', resulting in the discovery of 36 distinct VunMED genes. A phylogenetic analysis encompassing 232 MED genes from diverse species, including Arabidopsis, tomatoes, soybeans, mung beans, cowpeas, and asparagus beans, underscored the highly conserved nature of MED gene sequences. Throughout evolutionary processes, each VunMED gene underwent purification and neutral selection, with the exception of VunMED19a. Notably, VunMED9/10b/12/13/17/23 exhibited structural variations discernible across four cowpea species. Divergent patterns of temporal and spatial expression were evident among VunMED genes, with a prominent role attributed to most genes during early fruit development. Additionally, an analysis of promoter cis-acting elements was performed, followed by qRT-PCR assessments on roots, stems, and leaves to gauge relative expression after exposure to cold stress and subsequent recovery. Both treatments induced transcriptional alterations in VunMED genes, with particularly pronounced effects observed in root-based genes following cold stress. Elucidating the interrelationships between subunits involved a preliminary understanding facilitated by correlation and principal component analyses. CONCLUSIONS: This study elucidates the pivotal contribution of VunMED genes to the growth, development, and response to cold stress in asparagus beans. Furthermore, it offers a valuable point of reference regarding the individual roles of MED subunits.

Assessing the effectiveness of spatial PCA on SVM-based decoding of EEG data.

Principal component analysis (PCA) has been widely employed for dimensionality reduction prior to multivariate pattern classification (decoding) in EEG research. The goal of the present study was to provide an evaluation of the effectiveness of PCA on decoding accuracy (using support vector machines) across a broad range of experimental paradigms. We evaluated several different PCA variations, including group-based and subject-based component decomposition and the application of Varimax rotation or no rotation. We also varied the numbers of PCs that were retained for the decoding analysis. We evaluated the resulting decoding accuracy for seven common event-related potential components (N170, mismatch negativity, N2pc, P3b, N400, lateralized readiness potential, and error-related negativity). We also examined more challenging decoding tasks, including decoding of face identity, facial expression, stimulus location, and stimulus orientation. The datasets also varied in the number and density of electrode sites. Our findings indicated that none of the PCA approaches consistently improved decoding performance related to no PCA, and the application of PCA frequently reduced decoding performance. Researchers should therefore be cautious about using PCA prior to decoding EEG data from similar experimental paradigms, populations, and recording setups.

Diesel exhaust particles induce polarization state-dependent functional and transcriptional changes in human monocyte-derived macrophages.

Macrophage populations exist on a spectrum between the proinflammatory M1 and proresolution M2 states and have demonstrated the ability to reprogram between them after exposure to opposing polarization stimuli. Particulate matter (PM) has been repeatedly linked to worsening morbidity and mortality following respiratory infections and has been demonstrated to modify macrophage function and polarization. The purpose of this study was to determine whether diesel exhaust particles (DEP), a key component of airborne PM, would demonstrate polarization state-dependent effects on human monocyte-derived macrophages (hMDMs) and whether DEP would modify macrophage reprogramming. CD14+CD16- monocytes were isolated from the blood of healthy human volunteers and differentiated into macrophages with macrophage colony-stimulating factor (M-CSF). Resulting macrophages were left unpolarized or polarized into the proresolution M2 state before being exposed to DEP, M1-polarizing conditions (IFN-γ and LPS), or both and tested for phagocytic function, secretory profile, gene expression patterns, and bioenergetic properties. Contrary to previous reports, we observed a mixed M1/M2 phenotype in reprogrammed M2 cells when considering the broader range of functional readouts. In addition, we determined that DEP exposure dampens phagocytic function in all polarization states while modifying bioenergetic properties in M1 macrophages preferentially. Together, these data suggest that DEP exposure of reprogrammed M2 macrophages results in a highly inflammatory, highly energetic subpopulation of macrophages that may contribute to the poor health outcomes following PM exposure during respiratory infections.NEW & NOTEWORTHY We determined that reprogramming M2 macrophages in the presence of diesel exhaust particles (DEP) results in a highly inflammatory mixed M1/M2 phenotype. We also demonstrated that M1 macrophages are particularly vulnerable to particulate matter (PM) exposure as seen by dampened phagocytic function and modified bioenergetics. Our study suggests that PM causes reprogrammed M2 macrophages to become a highly energetic, highly secretory subpopulation of macrophages that may contribute to negative health outcomes observed in humans after PM exposure.

Development of a multigenomic liquid biopsy (PROSTest) for prostate cancer in whole blood.

INTRODUCTION: We describe the development of a molecular assay from publicly available tumor tissue mRNA databases using machine learning and present preliminary evidence of functionality as a diagnostic and monitoring tool for prostate cancer (PCa) in whole blood. MATERIALS AND METHODS: We assessed 1055 PCas (public microarray data sets) to identify putative mRNA biomarkers. Specificity was confirmed against 32 different solid and hematological cancers from The Cancer Genome Atlas (n = 10,990). This defined a 27-gene panel which was validated by qPCR in 50 histologically confirmed PCa surgical specimens and matched blood. An ensemble classifier (Random Forest, Support Vector Machines, XGBoost) was trained in age-matched PCas (n = 294), and in 72 controls and 64 BPH. Classifier performance was validated in two independent sets (n = 263 PCas; n = 99 controls). We assessed the panel as a postoperative disease monitor in a radical prostatectomy cohort (RPC: n = 47). RESULTS: A PCa-specific 27-gene panel was identified. Matched blood and tumor gene expression levels were concordant (r = 0.72, p < 0.0001). The ensemble classifier ("PROSTest") was scaled 0%-100% and the industry-standard operating point of ≥50% used to define a PCa. Using this, the PROSTest exhibited an 85% sensitivity and 95% specificity for PCa versus controls. In two independent sets, the metrics were 92%-95% sensitivity and 100% specificity. In the RPCs (n = 47), PROSTest scores decreased from 72% ± 7% to 33% ± 16% (p < 0.0001, Mann-Whitney test). PROSTest was 26% ± 8% in 37 with normal postoperative PSA levels (<0.1 ng/mL). In 10 with elevated postoperative PSA, PROSTest was 60% ± 4%. CONCLUSION: A 27-gene whole blood signature for PCa is concordant with tissue mRNA levels. Measuring blood expression provides a minimally invasive genomic tool that may facilitate prostate cancer management.

Phenazine-1 carboxylic acid of Pseudomonas aeruginosa induces the expression of Staphylococcus aureus Tet38 MDR efflux pump and mediates resistance to phenazines and antibiotics.

In this study, we showed that phenazine-1 carboxylic acid (PCA) of Pseudomonas aeruginosa induced the expression of Tet38 efflux pump triggering Staphylococcus aureus resistance to tetracycline and phenazines. Exposure of S. aureus RN6390 to supernatants of P. aeruginosa PA14 and its pyocyanin (PYO)-deficient mutants showed that P. aeruginosa non-PYO phenazines could induce the expression of Tet38 efflux pump. Direct exposure of RN6390 to PCA compound at 0.25× MIC led to a five-fold increase in tet38 transcripts. Expression of Tet38 protein was identified through confocal microscopy using RN6390(pRN-tet38p-yfp) that expressed YFP under control of the tet38 promoter by PCA at 0.25× MIC. The MICs of PCA of a Tet38-overexpressor and a Δtet38 mutant showed a three-fold increase and a two-fold decrease, respectively, compared with that of wild-type. Pre-exposure of RN6390 to PCA (0.25× MIC) for 1 hour prior to addition of tetracycline (1× or 10× MIC) improved bacteria viability of 1.5-fold and 2.6-fold, respectively, but addition of NaCl 7% together with tetracycline at 10× MIC reduced the number of viable PCA-exposed RN6390 of a 2.0-log10 CFU/mL. The transcript levels of tetR21, a repressor of tet38, decreased and increased two-fold in the presence of PCA and NaCl, respectively, suggesting that the effects of PCA and NaCl on tet38 production occurred through TetR21 expression. These data suggest that PCA-induced Tet38 protects S. aureus against tetracycline during coinfection with P. aeruginosa; however, induced tet38-mediated S. aureus resistance to tetracycline is reversed by NaCl 7%, a nebulized treatment used to enhance sputum mobilization in CF patients.

In-silico assessment of novel peptidomimetics inhibitor targeting STAT3 and STAT4 N-terminal domain dimerization: A comprehensive study using molecular docking, molecular dynamics simulation, and binding free energy analysis.

Dysregulation in Janus kinase-Signal Transducer and Activation of Transcription (JAK-STAT) pathway is closely linked to various cancer types. The N-terminal domain (NTD) of STAT proteins, upon dimerization, assumes a multifaceted role with remarkable adaptability in mediating interactions between proteins. Consequently, the strategic targeting of the N-terminal domain of STATs has emerged as a promising tactic for disrupting dimerization and impeding the translocation of STAT proteins. In this study, we have deployed an integrated in-silico methodology to rationally design Peptidomimetic foldamers as inhibitors of the N-terminal domains of STAT3 and STAT4, with the objective of disrupting protein dimerization. Consequently, we have judiciously designed a series of peptidomimetics that encompass ß3-amino acids, bearing side chains that mimic the residues within interface II of the dimeric structures of the NTDs. Employing molecular docking techniques; we have assessed the binding affinity of these designed peptidomimetics toward both the NTDs. Furthermore, we have conducted an evaluation of the stability and conformational alterations within the docked complexes over an extensive Molecular Dynamics, subsequently computing the binding free energy utilizing MM/PBSA calculations. Our findings unequivocally demonstrate that the peptidomimetic foldamers we have devised (Peptide-A, Peptide-B, and Peptide-C) exhibit a propensity to bind to and impede the dimerization process of the NTDs of both STAT3 and STAT4. These outcomes serve to underscore the potential of these meticulously designed peptidomimetics as potential candidates meriting further exploration in the realm of cancer prevention and management.

High performance liquid chromatography (HPLC) based genetic diversity profiling of chilli germplasm for fruit pungency and phytochemical contents.

Chilli peppers are widely consumed for their pungency, as used in flavoring the food and has many pharmaceutical and medicinal properties. Based on these properties an experiment was held using 83 varieties of chilli (Hot pepper and sweet pepper) were grown in suitable environment using Augment Block design and evaluated for fruit pungency and phytochemical contents using high proficiency liquid chromatography. Analysis of variance (ANOVA) of traits showed highly significant for all traits except for fruit length and capsaicin contents. The value of Least significant increase (LSI)was ranged 0.27-1289.9 for all traits showed high variation among varieties. Highly significant correlation was found among fruit diameter to fruit weight 0.98, while moderate to high correlation was present among all traits. The most pungent genotype 24,634 was 4.8 g in weight, while the least pungent genotypes i.e. PPE-311 (32.8 g), green wonder (40.67) had higher in weight. The genotypes 24,627, 32,344, 32,368 and 1108 marked as higher number of seeds in their placental region. It was observed that chilli genotype 24,621 had maximum length with considerable high amount of pungency act as novel cultivar. Principal component analysis (PCA) showed the high variability of 46.97 for two PCs with the eigen value 2.6 and 1.63 was recorded. Biplot analysis showed a considerable variability for fruit pungency, while huge variability was found for all traits among given varieties. PPE-311, T5 and T3 are found as highly divergent for all traits. The findings of this study are instrumental for selecting parents to improve desirable traits in future chilli pepper breeding programs. It will help plant/vegetable breeders for development of highly nutrient and pungent varieties and attractive for the consumer of food sector.

Raman developmental markers in root cell walls are associated with lodging tendency in tef.

MAIN CONCLUSION: Using Raman micro-spectroscopy on tef roots, we could monitor cell wall maturation in lines with varied genetic lodging tendency. We describe the developing cell wall composition in root endodermis and cylinder tissue. Tef [Eragrostis tef (Zucc.) Trotter] is an important staple crop in Ethiopia and Eritrea, producing gluten-free and protein-rich grains. However, this crop is not adapted to modern farming practices due to high lodging susceptibility, which prevents the application of mechanical harvest. Lodging describes the displacement of roots (root lodging) or fracture of culms (stem lodging), forcing plants to bend or fall from their vertical position, causing significant yield losses. In this study, we aimed to understand the microstructural properties of crown roots, underlining tef tolerance/susceptibility to lodging. We analyzed plants at 5 and 10 weeks after emergence and compared trellised to lodged plants. Root cross sections from different tef genotypes were characterized by scanning electron microscopy, micro-computed tomography, and Raman micro-spectroscopy. Lodging susceptible genotypes exhibited early tissue maturation, including developed aerenchyma, intensive lignification, and lignin with high levels of crosslinks. A comparison between trellised and lodged plants suggested that lodging itself does not affect the histology of root tissue. Furthermore, cell wall composition along plant maturation was typical to each of the tested genotypes independently of trellising. Our results suggest that it is possible to select lines that exhibit slow maturation of crown roots. Such lines are predicted to show reduction in lodging and facilitate mechanical harvest.

Association of race/ethnicity and patient care experiences with receipt of definitive treatment among prostate cancer survivors: a SEER-CAHPS study.

PURPOSE: This study aimed to evaluate the association of race/ethnicity, patient care experiences (PCEs), and receipt of definitive treatment and treatment modality among older adults in the United States (US) with localized prostate cancer (PCa). METHODS: Using Surveillance, Epidemiology and End Results dataset linked to Medicare Consumer Assessment of Healthcare Providers and Systems (SEER-CAHPS) for 2007-2015, we identified men aged ≥ 65 years who completed a CAHPS survey within one year before and one year after PCa diagnosis. Associations of race/ethnicity (non-Hispanic White (NHW), non-Hispanic Black (NHB), Hispanic, non-Hispanic Asian (NHA), and other) and of interactions between race/ethnicity and PCEs (getting needed care, getting care quickly, doctor communication, and care coordination) with the receipt of definitive PCa treatment and treatment modality within 3 and 6 months of diagnosis were examined using logistic regressions. RESULTS: Among 1,438 PCa survivors, no racial/ethnic disparities in the receipt of definitive treatment were identified. However, NHB patients were less likely to receive surgery (vs. radiation) within 3 and 6 months of PCa diagnosis than NHW patients (OR 0.397, p = 0.006 and OR 0.419, p = 0.005), respectively. Among NHA patients, a 1-point higher score for getting care quickly was associated with lower odds (OR 0.981, p = 0.043) of receiving definitive treatment within 3 months of PCa diagnosis, whereas among NHB patients, a 1-point higher score for doctor communication was associated with higher odds (OR 1.023, p = 0.039) of receiving definitive treatment within 6 months of PCa diagnosis. DISCUSSION: We observed differential associations between PCEs and receipt of definitive treatment based on patient race/ethnicity. Further research is needed to explore these associations.

New advances of the androgen receptor in prostate cancer: report from the 1st International Androgen Receptor Symposium.

The androgen receptor (AR) is a crucial player in various aspects of male reproduction and has been associated with the development and progression of prostate cancer (PCa). Therefore, the protein is the linchpin of current PCa therapies. Despite great research efforts, the AR signaling pathway has still not been deciphered, and the emergence of resistance is still the biggest problem in PCa treatment. To discuss the latest developments in AR research, the "1st International Androgen Receptor Symposium" offered a forum for the exchange of clinical and scientific innovations around the role of the AR in prostate cancer (PCa) and to stimulate new collaborative interactions among leading scientists from basic, translational, and clinical research. The symposium included three sessions covering preclinical studies, prognostic and diagnostic biomarkers, and ongoing prostate cancer clinical trials. In addition, a panel discussion about the future direction of androgen deprivation therapy and anti-AR therapy in PCa was conducted. Therefore, the newest insights and developments in therapeutic strategies and biomarkers are discussed in this report.

K-t PCA accelerated in-plane balanced steady-state free precession phase-contrast (PC-SSFP) for all-in-one diastolic function evaluation.

PURPOSE: Diastolic function evaluation requires estimates of early and late diastolic mitral filling velocities (E and A) and of mitral annulus tissue velocity (e'). We aimed to develop an MRI method for simultaneous all-in-one diastolic function evaluation in a single scan by generating a 2D phase-contrast (PC) sequence with balanced steady-state free precession (bSSFP) contrast (PC-SSFP). E and A could then be measured with PC, and e' estimated by valve tracking on the magnitude images, using an established deep learning framework. METHODS: Our PC-SSFP used in-plane flow-encoding, with zeroth and first moment nulling over each TR. For further acceleration, different k-t principal component analysis (PCA) methods were investigated with both retrospective and prospective undersampling. PC-SSFP was compared to separate balanced SSFP cine and PC-gradient echo acquisitions in phantoms and in 10 healthy subjects. RESULTS: Phantom experiments showed that PC-SSFP measured accurate velocities compared to PC-gradient echo (r = 0.98 for a range of pixel-wise velocities -80 cm/s to 80 cm/s). In subjects, PC-SSFP generated high SNR and myocardium-blood contrast, and excellent agreement for E (limits of agreement [LOA] 0.8 ± 2.4 cm/s, r = 0.98), A (LOA 2.5 ± 4.1 cm/s, r = 0.97), and e' (LOA 0.3 ± 2.6 cm/s, r = 1.00), versus the standard methods. The best k-t PCA approach processed the complex difference data and substituted in raw k-space data. With prospective k-t PCA acceleration, higher frame rates were achieved (50 vs. 25 frames per second without k-t PCA), yielding a 13% higher e'. CONCLUSION: The proposed PC-SSFP method achieved all-in-one diastolic function evaluation.

State-of-the-art application of nanoparticles in radiotherapy: a platform for synergistic effects in cancer treatment.

Radiotherapy (RT) is a gold standard cancer treatment worldwide. However, RT has limitations and many side effects. Nanoparticles (NPs) have exclusive properties that allow them to be used in cancer therapy. Consequently, the combination of NP and RT opens up a new frontier in cancer treatment. Among NPs, gold nanoparticles (GNPs) are the most extensively studied and are considered ideal radiosensitizers for radiotherapy due to their unique physicochemical properties and high X­ray absorption. This review analyzes the various roles of NPs as radiosensitizers in radiotherapy of glioblastoma (GBS), prostate cancer, and breast cancer and summarizes recent advances. Furthermore, the underlying mechanisms of NP radiosensitization, including physical, chemical, and biological mechanisms, are discussed, which may provide new directions for next-generation GNP optimization and clinical transformation.

Development and first-in-human study of PSMA-targeted PET tracers with improved pharmacokinetic properties.

PURPOSE: A series of new 68Ga-labeled tracers based on [68Ga]Ga-PSMA-617 were developed to augment the tumor-to-kidney ratio and reduce the activity accumulation in bladder, ultimately minimize radiation toxicity to the urinary system. METHODS: We introduced quinoline group, phenylalanine and decanoic acid into different tracers to enhance their lipophilicity, strategically limiting their metabolic pathway through the urinary system. Their binding affinity onto LNCaP cells was determined through in vitro saturation assays and competition binding assays. In vivo metabolic study, PET imaging and biodistribution experiment were performed in LNCaP tumor-bearing B-NSG male mice. The most promising tracer was selected for first-in-human study. RESULTS: Four radiotracers were synthesized with radiochemical purity (RCP) > 95% and molar activity in a range of 20.0-25.5 GBq/µmol. The binding affinities (Ki) of TWS01, TWS02 to PSMA were in the low nanomolar range (< 10 nM), while TWS03 and TWS04 exhibited binding affinities with Ki > 20 nM (59.42 nM for TWS03 and 37.14 nM for TWS04). All radiotracers exhibited high stability in vivo except [68Ga]Ga-TWS03. Micro PET/CT imaging and biodistribution analysis revealed that [68Ga]Ga-TWS02 enabled clear tumor visualization in PET images at 1.5 h post-injection, with higher tumor-to-kidney ratio (T/K, 0.93) and tumor-to-muscle ratio (T/M, 107.62) compared with [68Ga]Ga-PSMA-617 (T/K: 0.39, T/M: 15.01) and [68Ga]Ga-PSMA-11 (T/K: 0.15, T/M: 24.00). In first-in-human study, [68Ga]Ga-TWS02 effectively detected PCa-associated lesions including primary and metastatic lesions, with lower accumulation in urinary system, suggesting that [68Ga]Ga-TWS02 might be applied in the detection of bladder invasion, with minimized radiation toxicity to the urinary system. CONCLUSION: Introduction of quinoline group, phenylalanine and decanoic acid into different tracers can modulate the binding affinity and pharmacokinetics of PSMA in vivo. [68Ga]Ga-TWS02 showed high binding affinity to PSMA, excellent pharmacokinetic properties and clear imaging of PCa-associated lesions, making it a promising radiotracer for the clinical diagnosis of PCa. Moreover, TWS02 with a chelator DOTA could also label 177Lu and 225Ac, which could be used for PCa treatment without significant side effects. TRIAL REGISTRATION: The clinical evaluation of this study was registered On October 30, 2021 at https://www.chictr.org.cn/ (No: ChiCTR2100052545).

Menadione and protocatechuic acid: A drug combination with antitumor effects in murine osteosarcoma cells.

Osteosarcoma (OS) is a primary malignant bone tumor that has an abnormal expression of oncogenesis and tumor suppressors and causes dysregulation of various signaling pathways. Thus, novel therapeutic strategies for OS are needed to overcome the resistance of traditional treatments. This study evaluated the cytotoxic and anticancer effects of the association between menadione (MEN) and protocatechuic acid (PCA) in murine OS cells (UMR-106). The concentrations were 3.12 µM of isolated MEN, 500 µM of isolated PCA, and their associations. We performed cell viability assays, morphology modification analysis, cell migration by the wound-healing method, apoptosis by flow cytometry, reactive oxygen species (ROS) production, gene expression of NOX by RT-qPCR, and degradation of MMP-2 and 9 by zymography. Our results showed that the association of MEN+PCA was more effective in OS cells than the compounds alone. The association decreased cell viability, delayed cell migration, and decreased the expression of NOX-2 and ROS. In addition, the MEN+PCA association induced a slight increase in the apoptotic process. In summary, the association can enhance the compound's antitumor effects and establish a higher selectivity for tumor cells, possibly caused by significant mitochondrial damage and antioxidant properties.

Chemical composition alterations in rat brain hypothalamus induced by irisin administration using spectroscopic and machine learning techniques.

This study employed Fourier transform infrared (FTIR) spectroscopy to determine the chemical composition of brain tissues and the changes induced by irisin at doses of 50 mg and 100 mg. Brain tissues were collected from control rats and those administered with irisin, and key vibrational peaks were analyzed. In the 50 mg irisin group, all described vibrations decreased compared to control tissues, while the 100 mg group showed a decrease only in lipid vibrations. Comparatively, the 50 mg group had lower absorbance of phospholipids, amides, and lipid functional groups than the 100 mg group. Lower amounts of these compounds were found in treated tissues compared to controls, with higher levels in the 100 mg group. Ratios between amide peaks revealed significant differences between groups. Principal component analysis (PCA) differentiated control and irisin-treated tissues, primarily using PC1 and PC3. The decision tree model exhibited high classification accuracy, especially in the 800-1800 cm⁻1 range, with high sensitivity and specificity. FTIR spectroscopy effectively highlighted chemical changes in brain tissues due to irisin, demonstrating dose-dependent variations. The combination of PCA, ROC analysis, and decision tree modeling underscored the potential of FTIR spectroscopy for studying the biochemical effects of compounds like irisin.